diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/__init__.py b/env-llmeval/lib/python3.10/site-packages/chardet/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..fe581623d89d67a49eb43f3c3e88f3f450257707
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/__init__.py
@@ -0,0 +1,115 @@
+######################## BEGIN LICENSE BLOCK ########################
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from typing import List, Union
+
+from .charsetgroupprober import CharSetGroupProber
+from .charsetprober import CharSetProber
+from .enums import InputState
+from .resultdict import ResultDict
+from .universaldetector import UniversalDetector
+from .version import VERSION, __version__
+
+__all__ = ["UniversalDetector", "detect", "detect_all", "__version__", "VERSION"]
+
+
+def detect(
+ byte_str: Union[bytes, bytearray], should_rename_legacy: bool = False
+) -> ResultDict:
+ """
+ Detect the encoding of the given byte string.
+
+ :param byte_str: The byte sequence to examine.
+ :type byte_str: ``bytes`` or ``bytearray``
+ :param should_rename_legacy: Should we rename legacy encodings
+ to their more modern equivalents?
+ :type should_rename_legacy: ``bool``
+ """
+ if not isinstance(byte_str, bytearray):
+ if not isinstance(byte_str, bytes):
+ raise TypeError(
+ f"Expected object of type bytes or bytearray, got: {type(byte_str)}"
+ )
+ byte_str = bytearray(byte_str)
+ detector = UniversalDetector(should_rename_legacy=should_rename_legacy)
+ detector.feed(byte_str)
+ return detector.close()
+
+
+def detect_all(
+ byte_str: Union[bytes, bytearray],
+ ignore_threshold: bool = False,
+ should_rename_legacy: bool = False,
+) -> List[ResultDict]:
+ """
+ Detect all the possible encodings of the given byte string.
+
+ :param byte_str: The byte sequence to examine.
+ :type byte_str: ``bytes`` or ``bytearray``
+ :param ignore_threshold: Include encodings that are below
+ ``UniversalDetector.MINIMUM_THRESHOLD``
+ in results.
+ :type ignore_threshold: ``bool``
+ :param should_rename_legacy: Should we rename legacy encodings
+ to their more modern equivalents?
+ :type should_rename_legacy: ``bool``
+ """
+ if not isinstance(byte_str, bytearray):
+ if not isinstance(byte_str, bytes):
+ raise TypeError(
+ f"Expected object of type bytes or bytearray, got: {type(byte_str)}"
+ )
+ byte_str = bytearray(byte_str)
+
+ detector = UniversalDetector(should_rename_legacy=should_rename_legacy)
+ detector.feed(byte_str)
+ detector.close()
+
+ if detector.input_state == InputState.HIGH_BYTE:
+ results: List[ResultDict] = []
+ probers: List[CharSetProber] = []
+ for prober in detector.charset_probers:
+ if isinstance(prober, CharSetGroupProber):
+ probers.extend(p for p in prober.probers)
+ else:
+ probers.append(prober)
+ for prober in probers:
+ if ignore_threshold or prober.get_confidence() > detector.MINIMUM_THRESHOLD:
+ charset_name = prober.charset_name or ""
+ lower_charset_name = charset_name.lower()
+ # Use Windows encoding name instead of ISO-8859 if we saw any
+ # extra Windows-specific bytes
+ if lower_charset_name.startswith("iso-8859") and detector.has_win_bytes:
+ charset_name = detector.ISO_WIN_MAP.get(
+ lower_charset_name, charset_name
+ )
+ # Rename legacy encodings with superset encodings if asked
+ if should_rename_legacy:
+ charset_name = detector.LEGACY_MAP.get(
+ charset_name.lower(), charset_name
+ )
+ results.append(
+ {
+ "encoding": charset_name,
+ "confidence": prober.get_confidence(),
+ "language": prober.language,
+ }
+ )
+ if len(results) > 0:
+ return sorted(results, key=lambda result: -result["confidence"])
+
+ return [detector.result]
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/__main__.py b/env-llmeval/lib/python3.10/site-packages/chardet/__main__.py
new file mode 100644
index 0000000000000000000000000000000000000000..c19b0d2d7a3d8fa0d914ca4031e88241fd63a90f
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/__main__.py
@@ -0,0 +1,6 @@
+"""Wrapper so people can run python -m chardet"""
+
+from .cli.chardetect import main
+
+if __name__ == "__main__":
+ main()
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/big5freq.py b/env-llmeval/lib/python3.10/site-packages/chardet/big5freq.py
new file mode 100644
index 0000000000000000000000000000000000000000..87d9f972edde20d1f8e391b8010703242a8de977
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/big5freq.py
@@ -0,0 +1,386 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+# Big5 frequency table
+# by Taiwan's Mandarin Promotion Council
+#
+#
+# 128 --> 0.42261
+# 256 --> 0.57851
+# 512 --> 0.74851
+# 1024 --> 0.89384
+# 2048 --> 0.97583
+#
+# Ideal Distribution Ratio = 0.74851/(1-0.74851) =2.98
+# Random Distribution Ration = 512/(5401-512)=0.105
+#
+# Typical Distribution Ratio about 25% of Ideal one, still much higher than RDR
+
+BIG5_TYPICAL_DISTRIBUTION_RATIO = 0.75
+
+# Char to FreqOrder table
+BIG5_TABLE_SIZE = 5376
+# fmt: off
+BIG5_CHAR_TO_FREQ_ORDER = (
+ 1,1801,1506, 255,1431, 198, 9, 82, 6,5008, 177, 202,3681,1256,2821, 110, # 16
+3814, 33,3274, 261, 76, 44,2114, 16,2946,2187,1176, 659,3971, 26,3451,2653, # 32
+1198,3972,3350,4202, 410,2215, 302, 590, 361,1964, 8, 204, 58,4510,5009,1932, # 48
+ 63,5010,5011, 317,1614, 75, 222, 159,4203,2417,1480,5012,3555,3091, 224,2822, # 64
+3682, 3, 10,3973,1471, 29,2787,1135,2866,1940, 873, 130,3275,1123, 312,5013, # 80
+4511,2052, 507, 252, 682,5014, 142,1915, 124, 206,2947, 34,3556,3204, 64, 604, # 96
+5015,2501,1977,1978, 155,1991, 645, 641,1606,5016,3452, 337, 72, 406,5017, 80, # 112
+ 630, 238,3205,1509, 263, 939,1092,2654, 756,1440,1094,3453, 449, 69,2987, 591, # 128
+ 179,2096, 471, 115,2035,1844, 60, 50,2988, 134, 806,1869, 734,2036,3454, 180, # 144
+ 995,1607, 156, 537,2907, 688,5018, 319,1305, 779,2145, 514,2379, 298,4512, 359, # 160
+2502, 90,2716,1338, 663, 11, 906,1099,2553, 20,2441, 182, 532,1716,5019, 732, # 176
+1376,4204,1311,1420,3206, 25,2317,1056, 113, 399, 382,1950, 242,3455,2474, 529, # 192
+3276, 475,1447,3683,5020, 117, 21, 656, 810,1297,2300,2334,3557,5021, 126,4205, # 208
+ 706, 456, 150, 613,4513, 71,1118,2037,4206, 145,3092, 85, 835, 486,2115,1246, # 224
+1426, 428, 727,1285,1015, 800, 106, 623, 303,1281,5022,2128,2359, 347,3815, 221, # 240
+3558,3135,5023,1956,1153,4207, 83, 296,1199,3093, 192, 624, 93,5024, 822,1898, # 256
+2823,3136, 795,2065, 991,1554,1542,1592, 27, 43,2867, 859, 139,1456, 860,4514, # 272
+ 437, 712,3974, 164,2397,3137, 695, 211,3037,2097, 195,3975,1608,3559,3560,3684, # 288
+3976, 234, 811,2989,2098,3977,2233,1441,3561,1615,2380, 668,2077,1638, 305, 228, # 304
+1664,4515, 467, 415,5025, 262,2099,1593, 239, 108, 300, 200,1033, 512,1247,2078, # 320
+5026,5027,2176,3207,3685,2682, 593, 845,1062,3277, 88,1723,2038,3978,1951, 212, # 336
+ 266, 152, 149, 468,1899,4208,4516, 77, 187,5028,3038, 37, 5,2990,5029,3979, # 352
+5030,5031, 39,2524,4517,2908,3208,2079, 55, 148, 74,4518, 545, 483,1474,1029, # 368
+1665, 217,1870,1531,3138,1104,2655,4209, 24, 172,3562, 900,3980,3563,3564,4519, # 384
+ 32,1408,2824,1312, 329, 487,2360,2251,2717, 784,2683, 4,3039,3351,1427,1789, # 400
+ 188, 109, 499,5032,3686,1717,1790, 888,1217,3040,4520,5033,3565,5034,3352,1520, # 416
+3687,3981, 196,1034, 775,5035,5036, 929,1816, 249, 439, 38,5037,1063,5038, 794, # 432
+3982,1435,2301, 46, 178,3278,2066,5039,2381,5040, 214,1709,4521, 804, 35, 707, # 448
+ 324,3688,1601,2554, 140, 459,4210,5041,5042,1365, 839, 272, 978,2262,2580,3456, # 464
+2129,1363,3689,1423, 697, 100,3094, 48, 70,1231, 495,3139,2196,5043,1294,5044, # 480
+2080, 462, 586,1042,3279, 853, 256, 988, 185,2382,3457,1698, 434,1084,5045,3458, # 496
+ 314,2625,2788,4522,2335,2336, 569,2285, 637,1817,2525, 757,1162,1879,1616,3459, # 512
+ 287,1577,2116, 768,4523,1671,2868,3566,2526,1321,3816, 909,2418,5046,4211, 933, # 528
+3817,4212,2053,2361,1222,4524, 765,2419,1322, 786,4525,5047,1920,1462,1677,2909, # 544
+1699,5048,4526,1424,2442,3140,3690,2600,3353,1775,1941,3460,3983,4213, 309,1369, # 560
+1130,2825, 364,2234,1653,1299,3984,3567,3985,3986,2656, 525,1085,3041, 902,2001, # 576
+1475, 964,4527, 421,1845,1415,1057,2286, 940,1364,3141, 376,4528,4529,1381, 7, # 592
+2527, 983,2383, 336,1710,2684,1846, 321,3461, 559,1131,3042,2752,1809,1132,1313, # 608
+ 265,1481,1858,5049, 352,1203,2826,3280, 167,1089, 420,2827, 776, 792,1724,3568, # 624
+4214,2443,3281,5050,4215,5051, 446, 229, 333,2753, 901,3818,1200,1557,4530,2657, # 640
+1921, 395,2754,2685,3819,4216,1836, 125, 916,3209,2626,4531,5052,5053,3820,5054, # 656
+5055,5056,4532,3142,3691,1133,2555,1757,3462,1510,2318,1409,3569,5057,2146, 438, # 672
+2601,2910,2384,3354,1068, 958,3043, 461, 311,2869,2686,4217,1916,3210,4218,1979, # 688
+ 383, 750,2755,2627,4219, 274, 539, 385,1278,1442,5058,1154,1965, 384, 561, 210, # 704
+ 98,1295,2556,3570,5059,1711,2420,1482,3463,3987,2911,1257, 129,5060,3821, 642, # 720
+ 523,2789,2790,2658,5061, 141,2235,1333, 68, 176, 441, 876, 907,4220, 603,2602, # 736
+ 710, 171,3464, 404, 549, 18,3143,2398,1410,3692,1666,5062,3571,4533,2912,4534, # 752
+5063,2991, 368,5064, 146, 366, 99, 871,3693,1543, 748, 807,1586,1185, 22,2263, # 768
+ 379,3822,3211,5065,3212, 505,1942,2628,1992,1382,2319,5066, 380,2362, 218, 702, # 784
+1818,1248,3465,3044,3572,3355,3282,5067,2992,3694, 930,3283,3823,5068, 59,5069, # 800
+ 585, 601,4221, 497,3466,1112,1314,4535,1802,5070,1223,1472,2177,5071, 749,1837, # 816
+ 690,1900,3824,1773,3988,1476, 429,1043,1791,2236,2117, 917,4222, 447,1086,1629, # 832
+5072, 556,5073,5074,2021,1654, 844,1090, 105, 550, 966,1758,2828,1008,1783, 686, # 848
+1095,5075,2287, 793,1602,5076,3573,2603,4536,4223,2948,2302,4537,3825, 980,2503, # 864
+ 544, 353, 527,4538, 908,2687,2913,5077, 381,2629,1943,1348,5078,1341,1252, 560, # 880
+3095,5079,3467,2870,5080,2054, 973, 886,2081, 143,4539,5081,5082, 157,3989, 496, # 896
+4224, 57, 840, 540,2039,4540,4541,3468,2118,1445, 970,2264,1748,1966,2082,4225, # 912
+3144,1234,1776,3284,2829,3695, 773,1206,2130,1066,2040,1326,3990,1738,1725,4226, # 928
+ 279,3145, 51,1544,2604, 423,1578,2131,2067, 173,4542,1880,5083,5084,1583, 264, # 944
+ 610,3696,4543,2444, 280, 154,5085,5086,5087,1739, 338,1282,3096, 693,2871,1411, # 960
+1074,3826,2445,5088,4544,5089,5090,1240, 952,2399,5091,2914,1538,2688, 685,1483, # 976
+4227,2475,1436, 953,4228,2055,4545, 671,2400, 79,4229,2446,3285, 608, 567,2689, # 992
+3469,4230,4231,1691, 393,1261,1792,2401,5092,4546,5093,5094,5095,5096,1383,1672, # 1008
+3827,3213,1464, 522,1119, 661,1150, 216, 675,4547,3991,1432,3574, 609,4548,2690, # 1024
+2402,5097,5098,5099,4232,3045, 0,5100,2476, 315, 231,2447, 301,3356,4549,2385, # 1040
+5101, 233,4233,3697,1819,4550,4551,5102, 96,1777,1315,2083,5103, 257,5104,1810, # 1056
+3698,2718,1139,1820,4234,2022,1124,2164,2791,1778,2659,5105,3097, 363,1655,3214, # 1072
+5106,2993,5107,5108,5109,3992,1567,3993, 718, 103,3215, 849,1443, 341,3357,2949, # 1088
+1484,5110,1712, 127, 67, 339,4235,2403, 679,1412, 821,5111,5112, 834, 738, 351, # 1104
+2994,2147, 846, 235,1497,1881, 418,1993,3828,2719, 186,1100,2148,2756,3575,1545, # 1120
+1355,2950,2872,1377, 583,3994,4236,2581,2995,5113,1298,3699,1078,2557,3700,2363, # 1136
+ 78,3829,3830, 267,1289,2100,2002,1594,4237, 348, 369,1274,2197,2178,1838,4552, # 1152
+1821,2830,3701,2757,2288,2003,4553,2951,2758, 144,3358, 882,4554,3995,2759,3470, # 1168
+4555,2915,5114,4238,1726, 320,5115,3996,3046, 788,2996,5116,2831,1774,1327,2873, # 1184
+3997,2832,5117,1306,4556,2004,1700,3831,3576,2364,2660, 787,2023, 506, 824,3702, # 1200
+ 534, 323,4557,1044,3359,2024,1901, 946,3471,5118,1779,1500,1678,5119,1882,4558, # 1216
+ 165, 243,4559,3703,2528, 123, 683,4239, 764,4560, 36,3998,1793, 589,2916, 816, # 1232
+ 626,1667,3047,2237,1639,1555,1622,3832,3999,5120,4000,2874,1370,1228,1933, 891, # 1248
+2084,2917, 304,4240,5121, 292,2997,2720,3577, 691,2101,4241,1115,4561, 118, 662, # 1264
+5122, 611,1156, 854,2386,1316,2875, 2, 386, 515,2918,5123,5124,3286, 868,2238, # 1280
+1486, 855,2661, 785,2216,3048,5125,1040,3216,3578,5126,3146, 448,5127,1525,5128, # 1296
+2165,4562,5129,3833,5130,4242,2833,3579,3147, 503, 818,4001,3148,1568, 814, 676, # 1312
+1444, 306,1749,5131,3834,1416,1030, 197,1428, 805,2834,1501,4563,5132,5133,5134, # 1328
+1994,5135,4564,5136,5137,2198, 13,2792,3704,2998,3149,1229,1917,5138,3835,2132, # 1344
+5139,4243,4565,2404,3580,5140,2217,1511,1727,1120,5141,5142, 646,3836,2448, 307, # 1360
+5143,5144,1595,3217,5145,5146,5147,3705,1113,1356,4002,1465,2529,2530,5148, 519, # 1376
+5149, 128,2133, 92,2289,1980,5150,4003,1512, 342,3150,2199,5151,2793,2218,1981, # 1392
+3360,4244, 290,1656,1317, 789, 827,2365,5152,3837,4566, 562, 581,4004,5153, 401, # 1408
+4567,2252, 94,4568,5154,1399,2794,5155,1463,2025,4569,3218,1944,5156, 828,1105, # 1424
+4245,1262,1394,5157,4246, 605,4570,5158,1784,2876,5159,2835, 819,2102, 578,2200, # 1440
+2952,5160,1502, 436,3287,4247,3288,2836,4005,2919,3472,3473,5161,2721,2320,5162, # 1456
+5163,2337,2068, 23,4571, 193, 826,3838,2103, 699,1630,4248,3098, 390,1794,1064, # 1472
+3581,5164,1579,3099,3100,1400,5165,4249,1839,1640,2877,5166,4572,4573, 137,4250, # 1488
+ 598,3101,1967, 780, 104, 974,2953,5167, 278, 899, 253, 402, 572, 504, 493,1339, # 1504
+5168,4006,1275,4574,2582,2558,5169,3706,3049,3102,2253, 565,1334,2722, 863, 41, # 1520
+5170,5171,4575,5172,1657,2338, 19, 463,2760,4251, 606,5173,2999,3289,1087,2085, # 1536
+1323,2662,3000,5174,1631,1623,1750,4252,2691,5175,2878, 791,2723,2663,2339, 232, # 1552
+2421,5176,3001,1498,5177,2664,2630, 755,1366,3707,3290,3151,2026,1609, 119,1918, # 1568
+3474, 862,1026,4253,5178,4007,3839,4576,4008,4577,2265,1952,2477,5179,1125, 817, # 1584
+4254,4255,4009,1513,1766,2041,1487,4256,3050,3291,2837,3840,3152,5180,5181,1507, # 1600
+5182,2692, 733, 40,1632,1106,2879, 345,4257, 841,2531, 230,4578,3002,1847,3292, # 1616
+3475,5183,1263, 986,3476,5184, 735, 879, 254,1137, 857, 622,1300,1180,1388,1562, # 1632
+4010,4011,2954, 967,2761,2665,1349, 592,2134,1692,3361,3003,1995,4258,1679,4012, # 1648
+1902,2188,5185, 739,3708,2724,1296,1290,5186,4259,2201,2202,1922,1563,2605,2559, # 1664
+1871,2762,3004,5187, 435,5188, 343,1108, 596, 17,1751,4579,2239,3477,3709,5189, # 1680
+4580, 294,3582,2955,1693, 477, 979, 281,2042,3583, 643,2043,3710,2631,2795,2266, # 1696
+1031,2340,2135,2303,3584,4581, 367,1249,2560,5190,3585,5191,4582,1283,3362,2005, # 1712
+ 240,1762,3363,4583,4584, 836,1069,3153, 474,5192,2149,2532, 268,3586,5193,3219, # 1728
+1521,1284,5194,1658,1546,4260,5195,3587,3588,5196,4261,3364,2693,1685,4262, 961, # 1744
+1673,2632, 190,2006,2203,3841,4585,4586,5197, 570,2504,3711,1490,5198,4587,2633, # 1760
+3293,1957,4588, 584,1514, 396,1045,1945,5199,4589,1968,2449,5200,5201,4590,4013, # 1776
+ 619,5202,3154,3294, 215,2007,2796,2561,3220,4591,3221,4592, 763,4263,3842,4593, # 1792
+5203,5204,1958,1767,2956,3365,3712,1174, 452,1477,4594,3366,3155,5205,2838,1253, # 1808
+2387,2189,1091,2290,4264, 492,5206, 638,1169,1825,2136,1752,4014, 648, 926,1021, # 1824
+1324,4595, 520,4596, 997, 847,1007, 892,4597,3843,2267,1872,3713,2405,1785,4598, # 1840
+1953,2957,3103,3222,1728,4265,2044,3714,4599,2008,1701,3156,1551, 30,2268,4266, # 1856
+5207,2027,4600,3589,5208, 501,5209,4267, 594,3478,2166,1822,3590,3479,3591,3223, # 1872
+ 829,2839,4268,5210,1680,3157,1225,4269,5211,3295,4601,4270,3158,2341,5212,4602, # 1888
+4271,5213,4015,4016,5214,1848,2388,2606,3367,5215,4603, 374,4017, 652,4272,4273, # 1904
+ 375,1140, 798,5216,5217,5218,2366,4604,2269, 546,1659, 138,3051,2450,4605,5219, # 1920
+2254, 612,1849, 910, 796,3844,1740,1371, 825,3845,3846,5220,2920,2562,5221, 692, # 1936
+ 444,3052,2634, 801,4606,4274,5222,1491, 244,1053,3053,4275,4276, 340,5223,4018, # 1952
+1041,3005, 293,1168, 87,1357,5224,1539, 959,5225,2240, 721, 694,4277,3847, 219, # 1968
+1478, 644,1417,3368,2666,1413,1401,1335,1389,4019,5226,5227,3006,2367,3159,1826, # 1984
+ 730,1515, 184,2840, 66,4607,5228,1660,2958, 246,3369, 378,1457, 226,3480, 975, # 2000
+4020,2959,1264,3592, 674, 696,5229, 163,5230,1141,2422,2167, 713,3593,3370,4608, # 2016
+4021,5231,5232,1186, 15,5233,1079,1070,5234,1522,3224,3594, 276,1050,2725, 758, # 2032
+1126, 653,2960,3296,5235,2342, 889,3595,4022,3104,3007, 903,1250,4609,4023,3481, # 2048
+3596,1342,1681,1718, 766,3297, 286, 89,2961,3715,5236,1713,5237,2607,3371,3008, # 2064
+5238,2962,2219,3225,2880,5239,4610,2505,2533, 181, 387,1075,4024, 731,2190,3372, # 2080
+5240,3298, 310, 313,3482,2304, 770,4278, 54,3054, 189,4611,3105,3848,4025,5241, # 2096
+1230,1617,1850, 355,3597,4279,4612,3373, 111,4280,3716,1350,3160,3483,3055,4281, # 2112
+2150,3299,3598,5242,2797,4026,4027,3009, 722,2009,5243,1071, 247,1207,2343,2478, # 2128
+1378,4613,2010, 864,1437,1214,4614, 373,3849,1142,2220, 667,4615, 442,2763,2563, # 2144
+3850,4028,1969,4282,3300,1840, 837, 170,1107, 934,1336,1883,5244,5245,2119,4283, # 2160
+2841, 743,1569,5246,4616,4284, 582,2389,1418,3484,5247,1803,5248, 357,1395,1729, # 2176
+3717,3301,2423,1564,2241,5249,3106,3851,1633,4617,1114,2086,4285,1532,5250, 482, # 2192
+2451,4618,5251,5252,1492, 833,1466,5253,2726,3599,1641,2842,5254,1526,1272,3718, # 2208
+4286,1686,1795, 416,2564,1903,1954,1804,5255,3852,2798,3853,1159,2321,5256,2881, # 2224
+4619,1610,1584,3056,2424,2764, 443,3302,1163,3161,5257,5258,4029,5259,4287,2506, # 2240
+3057,4620,4030,3162,2104,1647,3600,2011,1873,4288,5260,4289, 431,3485,5261, 250, # 2256
+ 97, 81,4290,5262,1648,1851,1558, 160, 848,5263, 866, 740,1694,5264,2204,2843, # 2272
+3226,4291,4621,3719,1687, 950,2479, 426, 469,3227,3720,3721,4031,5265,5266,1188, # 2288
+ 424,1996, 861,3601,4292,3854,2205,2694, 168,1235,3602,4293,5267,2087,1674,4622, # 2304
+3374,3303, 220,2565,1009,5268,3855, 670,3010, 332,1208, 717,5269,5270,3603,2452, # 2320
+4032,3375,5271, 513,5272,1209,2882,3376,3163,4623,1080,5273,5274,5275,5276,2534, # 2336
+3722,3604, 815,1587,4033,4034,5277,3605,3486,3856,1254,4624,1328,3058,1390,4035, # 2352
+1741,4036,3857,4037,5278, 236,3858,2453,3304,5279,5280,3723,3859,1273,3860,4625, # 2368
+5281, 308,5282,4626, 245,4627,1852,2480,1307,2583, 430, 715,2137,2454,5283, 270, # 2384
+ 199,2883,4038,5284,3606,2727,1753, 761,1754, 725,1661,1841,4628,3487,3724,5285, # 2400
+5286, 587, 14,3305, 227,2608, 326, 480,2270, 943,2765,3607, 291, 650,1884,5287, # 2416
+1702,1226, 102,1547, 62,3488, 904,4629,3489,1164,4294,5288,5289,1224,1548,2766, # 2432
+ 391, 498,1493,5290,1386,1419,5291,2056,1177,4630, 813, 880,1081,2368, 566,1145, # 2448
+4631,2291,1001,1035,2566,2609,2242, 394,1286,5292,5293,2069,5294, 86,1494,1730, # 2464
+4039, 491,1588, 745, 897,2963, 843,3377,4040,2767,2884,3306,1768, 998,2221,2070, # 2480
+ 397,1827,1195,1970,3725,3011,3378, 284,5295,3861,2507,2138,2120,1904,5296,4041, # 2496
+2151,4042,4295,1036,3490,1905, 114,2567,4296, 209,1527,5297,5298,2964,2844,2635, # 2512
+2390,2728,3164, 812,2568,5299,3307,5300,1559, 737,1885,3726,1210, 885, 28,2695, # 2528
+3608,3862,5301,4297,1004,1780,4632,5302, 346,1982,2222,2696,4633,3863,1742, 797, # 2544
+1642,4043,1934,1072,1384,2152, 896,4044,3308,3727,3228,2885,3609,5303,2569,1959, # 2560
+4634,2455,1786,5304,5305,5306,4045,4298,1005,1308,3728,4299,2729,4635,4636,1528, # 2576
+2610, 161,1178,4300,1983, 987,4637,1101,4301, 631,4046,1157,3229,2425,1343,1241, # 2592
+1016,2243,2570, 372, 877,2344,2508,1160, 555,1935, 911,4047,5307, 466,1170, 169, # 2608
+1051,2921,2697,3729,2481,3012,1182,2012,2571,1251,2636,5308, 992,2345,3491,1540, # 2624
+2730,1201,2071,2406,1997,2482,5309,4638, 528,1923,2191,1503,1874,1570,2369,3379, # 2640
+3309,5310, 557,1073,5311,1828,3492,2088,2271,3165,3059,3107, 767,3108,2799,4639, # 2656
+1006,4302,4640,2346,1267,2179,3730,3230, 778,4048,3231,2731,1597,2667,5312,4641, # 2672
+5313,3493,5314,5315,5316,3310,2698,1433,3311, 131, 95,1504,4049, 723,4303,3166, # 2688
+1842,3610,2768,2192,4050,2028,2105,3731,5317,3013,4051,1218,5318,3380,3232,4052, # 2704
+4304,2584, 248,1634,3864, 912,5319,2845,3732,3060,3865, 654, 53,5320,3014,5321, # 2720
+1688,4642, 777,3494,1032,4053,1425,5322, 191, 820,2121,2846, 971,4643, 931,3233, # 2736
+ 135, 664, 783,3866,1998, 772,2922,1936,4054,3867,4644,2923,3234, 282,2732, 640, # 2752
+1372,3495,1127, 922, 325,3381,5323,5324, 711,2045,5325,5326,4055,2223,2800,1937, # 2768
+4056,3382,2224,2255,3868,2305,5327,4645,3869,1258,3312,4057,3235,2139,2965,4058, # 2784
+4059,5328,2225, 258,3236,4646, 101,1227,5329,3313,1755,5330,1391,3314,5331,2924, # 2800
+2057, 893,5332,5333,5334,1402,4305,2347,5335,5336,3237,3611,5337,5338, 878,1325, # 2816
+1781,2801,4647, 259,1385,2585, 744,1183,2272,4648,5339,4060,2509,5340, 684,1024, # 2832
+4306,5341, 472,3612,3496,1165,3315,4061,4062, 322,2153, 881, 455,1695,1152,1340, # 2848
+ 660, 554,2154,4649,1058,4650,4307, 830,1065,3383,4063,4651,1924,5342,1703,1919, # 2864
+5343, 932,2273, 122,5344,4652, 947, 677,5345,3870,2637, 297,1906,1925,2274,4653, # 2880
+2322,3316,5346,5347,4308,5348,4309, 84,4310, 112, 989,5349, 547,1059,4064, 701, # 2896
+3613,1019,5350,4311,5351,3497, 942, 639, 457,2306,2456, 993,2966, 407, 851, 494, # 2912
+4654,3384, 927,5352,1237,5353,2426,3385, 573,4312, 680, 921,2925,1279,1875, 285, # 2928
+ 790,1448,1984, 719,2168,5354,5355,4655,4065,4066,1649,5356,1541, 563,5357,1077, # 2944
+5358,3386,3061,3498, 511,3015,4067,4068,3733,4069,1268,2572,3387,3238,4656,4657, # 2960
+5359, 535,1048,1276,1189,2926,2029,3167,1438,1373,2847,2967,1134,2013,5360,4313, # 2976
+1238,2586,3109,1259,5361, 700,5362,2968,3168,3734,4314,5363,4315,1146,1876,1907, # 2992
+4658,2611,4070, 781,2427, 132,1589, 203, 147, 273,2802,2407, 898,1787,2155,4071, # 3008
+4072,5364,3871,2803,5365,5366,4659,4660,5367,3239,5368,1635,3872, 965,5369,1805, # 3024
+2699,1516,3614,1121,1082,1329,3317,4073,1449,3873, 65,1128,2848,2927,2769,1590, # 3040
+3874,5370,5371, 12,2668, 45, 976,2587,3169,4661, 517,2535,1013,1037,3240,5372, # 3056
+3875,2849,5373,3876,5374,3499,5375,2612, 614,1999,2323,3877,3110,2733,2638,5376, # 3072
+2588,4316, 599,1269,5377,1811,3735,5378,2700,3111, 759,1060, 489,1806,3388,3318, # 3088
+1358,5379,5380,2391,1387,1215,2639,2256, 490,5381,5382,4317,1759,2392,2348,5383, # 3104
+4662,3878,1908,4074,2640,1807,3241,4663,3500,3319,2770,2349, 874,5384,5385,3501, # 3120
+3736,1859, 91,2928,3737,3062,3879,4664,5386,3170,4075,2669,5387,3502,1202,1403, # 3136
+3880,2969,2536,1517,2510,4665,3503,2511,5388,4666,5389,2701,1886,1495,1731,4076, # 3152
+2370,4667,5390,2030,5391,5392,4077,2702,1216, 237,2589,4318,2324,4078,3881,4668, # 3168
+4669,2703,3615,3504, 445,4670,5393,5394,5395,5396,2771, 61,4079,3738,1823,4080, # 3184
+5397, 687,2046, 935, 925, 405,2670, 703,1096,1860,2734,4671,4081,1877,1367,2704, # 3200
+3389, 918,2106,1782,2483, 334,3320,1611,1093,4672, 564,3171,3505,3739,3390, 945, # 3216
+2641,2058,4673,5398,1926, 872,4319,5399,3506,2705,3112, 349,4320,3740,4082,4674, # 3232
+3882,4321,3741,2156,4083,4675,4676,4322,4677,2408,2047, 782,4084, 400, 251,4323, # 3248
+1624,5400,5401, 277,3742, 299,1265, 476,1191,3883,2122,4324,4325,1109, 205,5402, # 3264
+2590,1000,2157,3616,1861,5403,5404,5405,4678,5406,4679,2573, 107,2484,2158,4085, # 3280
+3507,3172,5407,1533, 541,1301, 158, 753,4326,2886,3617,5408,1696, 370,1088,4327, # 3296
+4680,3618, 579, 327, 440, 162,2244, 269,1938,1374,3508, 968,3063, 56,1396,3113, # 3312
+2107,3321,3391,5409,1927,2159,4681,3016,5410,3619,5411,5412,3743,4682,2485,5413, # 3328
+2804,5414,1650,4683,5415,2613,5416,5417,4086,2671,3392,1149,3393,4087,3884,4088, # 3344
+5418,1076, 49,5419, 951,3242,3322,3323, 450,2850, 920,5420,1812,2805,2371,4328, # 3360
+1909,1138,2372,3885,3509,5421,3243,4684,1910,1147,1518,2428,4685,3886,5422,4686, # 3376
+2393,2614, 260,1796,3244,5423,5424,3887,3324, 708,5425,3620,1704,5426,3621,1351, # 3392
+1618,3394,3017,1887, 944,4329,3395,4330,3064,3396,4331,5427,3744, 422, 413,1714, # 3408
+3325, 500,2059,2350,4332,2486,5428,1344,1911, 954,5429,1668,5430,5431,4089,2409, # 3424
+4333,3622,3888,4334,5432,2307,1318,2512,3114, 133,3115,2887,4687, 629, 31,2851, # 3440
+2706,3889,4688, 850, 949,4689,4090,2970,1732,2089,4335,1496,1853,5433,4091, 620, # 3456
+3245, 981,1242,3745,3397,1619,3746,1643,3326,2140,2457,1971,1719,3510,2169,5434, # 3472
+3246,5435,5436,3398,1829,5437,1277,4690,1565,2048,5438,1636,3623,3116,5439, 869, # 3488
+2852, 655,3890,3891,3117,4092,3018,3892,1310,3624,4691,5440,5441,5442,1733, 558, # 3504
+4692,3747, 335,1549,3065,1756,4336,3748,1946,3511,1830,1291,1192, 470,2735,2108, # 3520
+2806, 913,1054,4093,5443,1027,5444,3066,4094,4693, 982,2672,3399,3173,3512,3247, # 3536
+3248,1947,2807,5445, 571,4694,5446,1831,5447,3625,2591,1523,2429,5448,2090, 984, # 3552
+4695,3749,1960,5449,3750, 852, 923,2808,3513,3751, 969,1519, 999,2049,2325,1705, # 3568
+5450,3118, 615,1662, 151, 597,4095,2410,2326,1049, 275,4696,3752,4337, 568,3753, # 3584
+3626,2487,4338,3754,5451,2430,2275, 409,3249,5452,1566,2888,3514,1002, 769,2853, # 3600
+ 194,2091,3174,3755,2226,3327,4339, 628,1505,5453,5454,1763,2180,3019,4096, 521, # 3616
+1161,2592,1788,2206,2411,4697,4097,1625,4340,4341, 412, 42,3119, 464,5455,2642, # 3632
+4698,3400,1760,1571,2889,3515,2537,1219,2207,3893,2643,2141,2373,4699,4700,3328, # 3648
+1651,3401,3627,5456,5457,3628,2488,3516,5458,3756,5459,5460,2276,2092, 460,5461, # 3664
+4701,5462,3020, 962, 588,3629, 289,3250,2644,1116, 52,5463,3067,1797,5464,5465, # 3680
+5466,1467,5467,1598,1143,3757,4342,1985,1734,1067,4702,1280,3402, 465,4703,1572, # 3696
+ 510,5468,1928,2245,1813,1644,3630,5469,4704,3758,5470,5471,2673,1573,1534,5472, # 3712
+5473, 536,1808,1761,3517,3894,3175,2645,5474,5475,5476,4705,3518,2929,1912,2809, # 3728
+5477,3329,1122, 377,3251,5478, 360,5479,5480,4343,1529, 551,5481,2060,3759,1769, # 3744
+2431,5482,2930,4344,3330,3120,2327,2109,2031,4706,1404, 136,1468,1479, 672,1171, # 3760
+3252,2308, 271,3176,5483,2772,5484,2050, 678,2736, 865,1948,4707,5485,2014,4098, # 3776
+2971,5486,2737,2227,1397,3068,3760,4708,4709,1735,2931,3403,3631,5487,3895, 509, # 3792
+2854,2458,2890,3896,5488,5489,3177,3178,4710,4345,2538,4711,2309,1166,1010, 552, # 3808
+ 681,1888,5490,5491,2972,2973,4099,1287,1596,1862,3179, 358, 453, 736, 175, 478, # 3824
+1117, 905,1167,1097,5492,1854,1530,5493,1706,5494,2181,3519,2292,3761,3520,3632, # 3840
+4346,2093,4347,5495,3404,1193,2489,4348,1458,2193,2208,1863,1889,1421,3331,2932, # 3856
+3069,2182,3521, 595,2123,5496,4100,5497,5498,4349,1707,2646, 223,3762,1359, 751, # 3872
+3121, 183,3522,5499,2810,3021, 419,2374, 633, 704,3897,2394, 241,5500,5501,5502, # 3888
+ 838,3022,3763,2277,2773,2459,3898,1939,2051,4101,1309,3122,2246,1181,5503,1136, # 3904
+2209,3899,2375,1446,4350,2310,4712,5504,5505,4351,1055,2615, 484,3764,5506,4102, # 3920
+ 625,4352,2278,3405,1499,4353,4103,5507,4104,4354,3253,2279,2280,3523,5508,5509, # 3936
+2774, 808,2616,3765,3406,4105,4355,3123,2539, 526,3407,3900,4356, 955,5510,1620, # 3952
+4357,2647,2432,5511,1429,3766,1669,1832, 994, 928,5512,3633,1260,5513,5514,5515, # 3968
+1949,2293, 741,2933,1626,4358,2738,2460, 867,1184, 362,3408,1392,5516,5517,4106, # 3984
+4359,1770,1736,3254,2934,4713,4714,1929,2707,1459,1158,5518,3070,3409,2891,1292, # 4000
+1930,2513,2855,3767,1986,1187,2072,2015,2617,4360,5519,2574,2514,2170,3768,2490, # 4016
+3332,5520,3769,4715,5521,5522, 666,1003,3023,1022,3634,4361,5523,4716,1814,2257, # 4032
+ 574,3901,1603, 295,1535, 705,3902,4362, 283, 858, 417,5524,5525,3255,4717,4718, # 4048
+3071,1220,1890,1046,2281,2461,4107,1393,1599, 689,2575, 388,4363,5526,2491, 802, # 4064
+5527,2811,3903,2061,1405,2258,5528,4719,3904,2110,1052,1345,3256,1585,5529, 809, # 4080
+5530,5531,5532, 575,2739,3524, 956,1552,1469,1144,2328,5533,2329,1560,2462,3635, # 4096
+3257,4108, 616,2210,4364,3180,2183,2294,5534,1833,5535,3525,4720,5536,1319,3770, # 4112
+3771,1211,3636,1023,3258,1293,2812,5537,5538,5539,3905, 607,2311,3906, 762,2892, # 4128
+1439,4365,1360,4721,1485,3072,5540,4722,1038,4366,1450,2062,2648,4367,1379,4723, # 4144
+2593,5541,5542,4368,1352,1414,2330,2935,1172,5543,5544,3907,3908,4724,1798,1451, # 4160
+5545,5546,5547,5548,2936,4109,4110,2492,2351, 411,4111,4112,3637,3333,3124,4725, # 4176
+1561,2674,1452,4113,1375,5549,5550, 47,2974, 316,5551,1406,1591,2937,3181,5552, # 4192
+1025,2142,3125,3182, 354,2740, 884,2228,4369,2412, 508,3772, 726,3638, 996,2433, # 4208
+3639, 729,5553, 392,2194,1453,4114,4726,3773,5554,5555,2463,3640,2618,1675,2813, # 4224
+ 919,2352,2975,2353,1270,4727,4115, 73,5556,5557, 647,5558,3259,2856,2259,1550, # 4240
+1346,3024,5559,1332, 883,3526,5560,5561,5562,5563,3334,2775,5564,1212, 831,1347, # 4256
+4370,4728,2331,3909,1864,3073, 720,3910,4729,4730,3911,5565,4371,5566,5567,4731, # 4272
+5568,5569,1799,4732,3774,2619,4733,3641,1645,2376,4734,5570,2938, 669,2211,2675, # 4288
+2434,5571,2893,5572,5573,1028,3260,5574,4372,2413,5575,2260,1353,5576,5577,4735, # 4304
+3183, 518,5578,4116,5579,4373,1961,5580,2143,4374,5581,5582,3025,2354,2355,3912, # 4320
+ 516,1834,1454,4117,2708,4375,4736,2229,2620,1972,1129,3642,5583,2776,5584,2976, # 4336
+1422, 577,1470,3026,1524,3410,5585,5586, 432,4376,3074,3527,5587,2594,1455,2515, # 4352
+2230,1973,1175,5588,1020,2741,4118,3528,4737,5589,2742,5590,1743,1361,3075,3529, # 4368
+2649,4119,4377,4738,2295, 895, 924,4378,2171, 331,2247,3076, 166,1627,3077,1098, # 4384
+5591,1232,2894,2231,3411,4739, 657, 403,1196,2377, 542,3775,3412,1600,4379,3530, # 4400
+5592,4740,2777,3261, 576, 530,1362,4741,4742,2540,2676,3776,4120,5593, 842,3913, # 4416
+5594,2814,2032,1014,4121, 213,2709,3413, 665, 621,4380,5595,3777,2939,2435,5596, # 4432
+2436,3335,3643,3414,4743,4381,2541,4382,4744,3644,1682,4383,3531,1380,5597, 724, # 4448
+2282, 600,1670,5598,1337,1233,4745,3126,2248,5599,1621,4746,5600, 651,4384,5601, # 4464
+1612,4385,2621,5602,2857,5603,2743,2312,3078,5604, 716,2464,3079, 174,1255,2710, # 4480
+4122,3645, 548,1320,1398, 728,4123,1574,5605,1891,1197,3080,4124,5606,3081,3082, # 4496
+3778,3646,3779, 747,5607, 635,4386,4747,5608,5609,5610,4387,5611,5612,4748,5613, # 4512
+3415,4749,2437, 451,5614,3780,2542,2073,4388,2744,4389,4125,5615,1764,4750,5616, # 4528
+4390, 350,4751,2283,2395,2493,5617,4391,4126,2249,1434,4127, 488,4752, 458,4392, # 4544
+4128,3781, 771,1330,2396,3914,2576,3184,2160,2414,1553,2677,3185,4393,5618,2494, # 4560
+2895,2622,1720,2711,4394,3416,4753,5619,2543,4395,5620,3262,4396,2778,5621,2016, # 4576
+2745,5622,1155,1017,3782,3915,5623,3336,2313, 201,1865,4397,1430,5624,4129,5625, # 4592
+5626,5627,5628,5629,4398,1604,5630, 414,1866, 371,2595,4754,4755,3532,2017,3127, # 4608
+4756,1708, 960,4399, 887, 389,2172,1536,1663,1721,5631,2232,4130,2356,2940,1580, # 4624
+5632,5633,1744,4757,2544,4758,4759,5634,4760,5635,2074,5636,4761,3647,3417,2896, # 4640
+4400,5637,4401,2650,3418,2815, 673,2712,2465, 709,3533,4131,3648,4402,5638,1148, # 4656
+ 502, 634,5639,5640,1204,4762,3649,1575,4763,2623,3783,5641,3784,3128, 948,3263, # 4672
+ 121,1745,3916,1110,5642,4403,3083,2516,3027,4132,3785,1151,1771,3917,1488,4133, # 4688
+1987,5643,2438,3534,5644,5645,2094,5646,4404,3918,1213,1407,2816, 531,2746,2545, # 4704
+3264,1011,1537,4764,2779,4405,3129,1061,5647,3786,3787,1867,2897,5648,2018, 120, # 4720
+4406,4407,2063,3650,3265,2314,3919,2678,3419,1955,4765,4134,5649,3535,1047,2713, # 4736
+1266,5650,1368,4766,2858, 649,3420,3920,2546,2747,1102,2859,2679,5651,5652,2000, # 4752
+5653,1111,3651,2977,5654,2495,3921,3652,2817,1855,3421,3788,5655,5656,3422,2415, # 4768
+2898,3337,3266,3653,5657,2577,5658,3654,2818,4135,1460, 856,5659,3655,5660,2899, # 4784
+2978,5661,2900,3922,5662,4408, 632,2517, 875,3923,1697,3924,2296,5663,5664,4767, # 4800
+3028,1239, 580,4768,4409,5665, 914, 936,2075,1190,4136,1039,2124,5666,5667,5668, # 4816
+5669,3423,1473,5670,1354,4410,3925,4769,2173,3084,4137, 915,3338,4411,4412,3339, # 4832
+1605,1835,5671,2748, 398,3656,4413,3926,4138, 328,1913,2860,4139,3927,1331,4414, # 4848
+3029, 937,4415,5672,3657,4140,4141,3424,2161,4770,3425, 524, 742, 538,3085,1012, # 4864
+5673,5674,3928,2466,5675, 658,1103, 225,3929,5676,5677,4771,5678,4772,5679,3267, # 4880
+1243,5680,4142, 963,2250,4773,5681,2714,3658,3186,5682,5683,2596,2332,5684,4774, # 4896
+5685,5686,5687,3536, 957,3426,2547,2033,1931,2941,2467, 870,2019,3659,1746,2780, # 4912
+2781,2439,2468,5688,3930,5689,3789,3130,3790,3537,3427,3791,5690,1179,3086,5691, # 4928
+3187,2378,4416,3792,2548,3188,3131,2749,4143,5692,3428,1556,2549,2297, 977,2901, # 4944
+2034,4144,1205,3429,5693,1765,3430,3189,2125,1271, 714,1689,4775,3538,5694,2333, # 4960
+3931, 533,4417,3660,2184, 617,5695,2469,3340,3539,2315,5696,5697,3190,5698,5699, # 4976
+3932,1988, 618, 427,2651,3540,3431,5700,5701,1244,1690,5702,2819,4418,4776,5703, # 4992
+3541,4777,5704,2284,1576, 473,3661,4419,3432, 972,5705,3662,5706,3087,5707,5708, # 5008
+4778,4779,5709,3793,4145,4146,5710, 153,4780, 356,5711,1892,2902,4420,2144, 408, # 5024
+ 803,2357,5712,3933,5713,4421,1646,2578,2518,4781,4782,3934,5714,3935,4422,5715, # 5040
+2416,3433, 752,5716,5717,1962,3341,2979,5718, 746,3030,2470,4783,4423,3794, 698, # 5056
+4784,1893,4424,3663,2550,4785,3664,3936,5719,3191,3434,5720,1824,1302,4147,2715, # 5072
+3937,1974,4425,5721,4426,3192, 823,1303,1288,1236,2861,3542,4148,3435, 774,3938, # 5088
+5722,1581,4786,1304,2862,3939,4787,5723,2440,2162,1083,3268,4427,4149,4428, 344, # 5104
+1173, 288,2316, 454,1683,5724,5725,1461,4788,4150,2597,5726,5727,4789, 985, 894, # 5120
+5728,3436,3193,5729,1914,2942,3795,1989,5730,2111,1975,5731,4151,5732,2579,1194, # 5136
+ 425,5733,4790,3194,1245,3796,4429,5734,5735,2863,5736, 636,4791,1856,3940, 760, # 5152
+1800,5737,4430,2212,1508,4792,4152,1894,1684,2298,5738,5739,4793,4431,4432,2213, # 5168
+ 479,5740,5741, 832,5742,4153,2496,5743,2980,2497,3797, 990,3132, 627,1815,2652, # 5184
+4433,1582,4434,2126,2112,3543,4794,5744, 799,4435,3195,5745,4795,2113,1737,3031, # 5200
+1018, 543, 754,4436,3342,1676,4796,4797,4154,4798,1489,5746,3544,5747,2624,2903, # 5216
+4155,5748,5749,2981,5750,5751,5752,5753,3196,4799,4800,2185,1722,5754,3269,3270, # 5232
+1843,3665,1715, 481, 365,1976,1857,5755,5756,1963,2498,4801,5757,2127,3666,3271, # 5248
+ 433,1895,2064,2076,5758, 602,2750,5759,5760,5761,5762,5763,3032,1628,3437,5764, # 5264
+3197,4802,4156,2904,4803,2519,5765,2551,2782,5766,5767,5768,3343,4804,2905,5769, # 5280
+4805,5770,2864,4806,4807,1221,2982,4157,2520,5771,5772,5773,1868,1990,5774,5775, # 5296
+5776,1896,5777,5778,4808,1897,4158, 318,5779,2095,4159,4437,5780,5781, 485,5782, # 5312
+ 938,3941, 553,2680, 116,5783,3942,3667,5784,3545,2681,2783,3438,3344,2820,5785, # 5328
+3668,2943,4160,1747,2944,2983,5786,5787, 207,5788,4809,5789,4810,2521,5790,3033, # 5344
+ 890,3669,3943,5791,1878,3798,3439,5792,2186,2358,3440,1652,5793,5794,5795, 941, # 5360
+2299, 208,3546,4161,2020, 330,4438,3944,2906,2499,3799,4439,4811,5796,5797,5798, # 5376
+)
+# fmt: on
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/big5prober.py b/env-llmeval/lib/python3.10/site-packages/chardet/big5prober.py
new file mode 100644
index 0000000000000000000000000000000000000000..ef09c60e327a0122e32f95f2f10a826a033c573c
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/big5prober.py
@@ -0,0 +1,47 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from .chardistribution import Big5DistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import BIG5_SM_MODEL
+
+
+class Big5Prober(MultiByteCharSetProber):
+ def __init__(self) -> None:
+ super().__init__()
+ self.coding_sm = CodingStateMachine(BIG5_SM_MODEL)
+ self.distribution_analyzer = Big5DistributionAnalysis()
+ self.reset()
+
+ @property
+ def charset_name(self) -> str:
+ return "Big5"
+
+ @property
+ def language(self) -> str:
+ return "Chinese"
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/charsetgroupprober.py b/env-llmeval/lib/python3.10/site-packages/chardet/charsetgroupprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..6def56b4a75f67000ed8181ae2d2c40eefb645fb
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/charsetgroupprober.py
@@ -0,0 +1,106 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from typing import List, Optional, Union
+
+from .charsetprober import CharSetProber
+from .enums import LanguageFilter, ProbingState
+
+
+class CharSetGroupProber(CharSetProber):
+ def __init__(self, lang_filter: LanguageFilter = LanguageFilter.NONE) -> None:
+ super().__init__(lang_filter=lang_filter)
+ self._active_num = 0
+ self.probers: List[CharSetProber] = []
+ self._best_guess_prober: Optional[CharSetProber] = None
+
+ def reset(self) -> None:
+ super().reset()
+ self._active_num = 0
+ for prober in self.probers:
+ prober.reset()
+ prober.active = True
+ self._active_num += 1
+ self._best_guess_prober = None
+
+ @property
+ def charset_name(self) -> Optional[str]:
+ if not self._best_guess_prober:
+ self.get_confidence()
+ if not self._best_guess_prober:
+ return None
+ return self._best_guess_prober.charset_name
+
+ @property
+ def language(self) -> Optional[str]:
+ if not self._best_guess_prober:
+ self.get_confidence()
+ if not self._best_guess_prober:
+ return None
+ return self._best_guess_prober.language
+
+ def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+ for prober in self.probers:
+ if not prober.active:
+ continue
+ state = prober.feed(byte_str)
+ if not state:
+ continue
+ if state == ProbingState.FOUND_IT:
+ self._best_guess_prober = prober
+ self._state = ProbingState.FOUND_IT
+ return self.state
+ if state == ProbingState.NOT_ME:
+ prober.active = False
+ self._active_num -= 1
+ if self._active_num <= 0:
+ self._state = ProbingState.NOT_ME
+ return self.state
+ return self.state
+
+ def get_confidence(self) -> float:
+ state = self.state
+ if state == ProbingState.FOUND_IT:
+ return 0.99
+ if state == ProbingState.NOT_ME:
+ return 0.01
+ best_conf = 0.0
+ self._best_guess_prober = None
+ for prober in self.probers:
+ if not prober.active:
+ self.logger.debug("%s not active", prober.charset_name)
+ continue
+ conf = prober.get_confidence()
+ self.logger.debug(
+ "%s %s confidence = %s", prober.charset_name, prober.language, conf
+ )
+ if best_conf < conf:
+ best_conf = conf
+ self._best_guess_prober = prober
+ if not self._best_guess_prober:
+ return 0.0
+ return best_conf
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/cli/__pycache__/__init__.cpython-310.pyc b/env-llmeval/lib/python3.10/site-packages/chardet/cli/__pycache__/__init__.cpython-310.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..a09cbb2717eea04407def101684432931259c0bb
Binary files /dev/null and b/env-llmeval/lib/python3.10/site-packages/chardet/cli/__pycache__/__init__.cpython-310.pyc differ
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/cli/__pycache__/chardetect.cpython-310.pyc b/env-llmeval/lib/python3.10/site-packages/chardet/cli/__pycache__/chardetect.cpython-310.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..11cdec06fb5dfcdc188a8bfb5ec48b34d339d8fe
Binary files /dev/null and b/env-llmeval/lib/python3.10/site-packages/chardet/cli/__pycache__/chardetect.cpython-310.pyc differ
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/cli/chardetect.py b/env-llmeval/lib/python3.10/site-packages/chardet/cli/chardetect.py
new file mode 100644
index 0000000000000000000000000000000000000000..43f6e144f677a113b5362dcbdfb75db4f41c2b2f
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/cli/chardetect.py
@@ -0,0 +1,112 @@
+"""
+Script which takes one or more file paths and reports on their detected
+encodings
+
+Example::
+
+ % chardetect somefile someotherfile
+ somefile: windows-1252 with confidence 0.5
+ someotherfile: ascii with confidence 1.0
+
+If no paths are provided, it takes its input from stdin.
+
+"""
+
+
+import argparse
+import sys
+from typing import Iterable, List, Optional
+
+from .. import __version__
+from ..universaldetector import UniversalDetector
+
+
+def description_of(
+ lines: Iterable[bytes],
+ name: str = "stdin",
+ minimal: bool = False,
+ should_rename_legacy: bool = False,
+) -> Optional[str]:
+ """
+ Return a string describing the probable encoding of a file or
+ list of strings.
+
+ :param lines: The lines to get the encoding of.
+ :type lines: Iterable of bytes
+ :param name: Name of file or collection of lines
+ :type name: str
+ :param should_rename_legacy: Should we rename legacy encodings to
+ their more modern equivalents?
+ :type should_rename_legacy: ``bool``
+ """
+ u = UniversalDetector(should_rename_legacy=should_rename_legacy)
+ for line in lines:
+ line = bytearray(line)
+ u.feed(line)
+ # shortcut out of the loop to save reading further - particularly useful if we read a BOM.
+ if u.done:
+ break
+ u.close()
+ result = u.result
+ if minimal:
+ return result["encoding"]
+ if result["encoding"]:
+ return f'{name}: {result["encoding"]} with confidence {result["confidence"]}'
+ return f"{name}: no result"
+
+
+def main(argv: Optional[List[str]] = None) -> None:
+ """
+ Handles command line arguments and gets things started.
+
+ :param argv: List of arguments, as if specified on the command-line.
+ If None, ``sys.argv[1:]`` is used instead.
+ :type argv: list of str
+ """
+ # Get command line arguments
+ parser = argparse.ArgumentParser(
+ description=(
+ "Takes one or more file paths and reports their detected encodings"
+ )
+ )
+ parser.add_argument(
+ "input",
+ help="File whose encoding we would like to determine. (default: stdin)",
+ type=argparse.FileType("rb"),
+ nargs="*",
+ default=[sys.stdin.buffer],
+ )
+ parser.add_argument(
+ "--minimal",
+ help="Print only the encoding to standard output",
+ action="store_true",
+ )
+ parser.add_argument(
+ "-l",
+ "--legacy",
+ help="Rename legacy encodings to more modern ones.",
+ action="store_true",
+ )
+ parser.add_argument(
+ "--version", action="version", version=f"%(prog)s {__version__}"
+ )
+ args = parser.parse_args(argv)
+
+ for f in args.input:
+ if f.isatty():
+ print(
+ "You are running chardetect interactively. Press "
+ "CTRL-D twice at the start of a blank line to signal the "
+ "end of your input. If you want help, run chardetect "
+ "--help\n",
+ file=sys.stderr,
+ )
+ print(
+ description_of(
+ f, f.name, minimal=args.minimal, should_rename_legacy=args.legacy
+ )
+ )
+
+
+if __name__ == "__main__":
+ main()
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/codingstatemachine.py b/env-llmeval/lib/python3.10/site-packages/chardet/codingstatemachine.py
new file mode 100644
index 0000000000000000000000000000000000000000..8ed4a8773b8404c2705aa8728e5fd692362ba168
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/codingstatemachine.py
@@ -0,0 +1,90 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+import logging
+
+from .codingstatemachinedict import CodingStateMachineDict
+from .enums import MachineState
+
+
+class CodingStateMachine:
+ """
+ A state machine to verify a byte sequence for a particular encoding. For
+ each byte the detector receives, it will feed that byte to every active
+ state machine available, one byte at a time. The state machine changes its
+ state based on its previous state and the byte it receives. There are 3
+ states in a state machine that are of interest to an auto-detector:
+
+ START state: This is the state to start with, or a legal byte sequence
+ (i.e. a valid code point) for character has been identified.
+
+ ME state: This indicates that the state machine identified a byte sequence
+ that is specific to the charset it is designed for and that
+ there is no other possible encoding which can contain this byte
+ sequence. This will to lead to an immediate positive answer for
+ the detector.
+
+ ERROR state: This indicates the state machine identified an illegal byte
+ sequence for that encoding. This will lead to an immediate
+ negative answer for this encoding. Detector will exclude this
+ encoding from consideration from here on.
+ """
+
+ def __init__(self, sm: CodingStateMachineDict) -> None:
+ self._model = sm
+ self._curr_byte_pos = 0
+ self._curr_char_len = 0
+ self._curr_state = MachineState.START
+ self.active = True
+ self.logger = logging.getLogger(__name__)
+ self.reset()
+
+ def reset(self) -> None:
+ self._curr_state = MachineState.START
+
+ def next_state(self, c: int) -> int:
+ # for each byte we get its class
+ # if it is first byte, we also get byte length
+ byte_class = self._model["class_table"][c]
+ if self._curr_state == MachineState.START:
+ self._curr_byte_pos = 0
+ self._curr_char_len = self._model["char_len_table"][byte_class]
+ # from byte's class and state_table, we get its next state
+ curr_state = self._curr_state * self._model["class_factor"] + byte_class
+ self._curr_state = self._model["state_table"][curr_state]
+ self._curr_byte_pos += 1
+ return self._curr_state
+
+ def get_current_charlen(self) -> int:
+ return self._curr_char_len
+
+ def get_coding_state_machine(self) -> str:
+ return self._model["name"]
+
+ @property
+ def language(self) -> str:
+ return self._model["language"]
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/codingstatemachinedict.py b/env-llmeval/lib/python3.10/site-packages/chardet/codingstatemachinedict.py
new file mode 100644
index 0000000000000000000000000000000000000000..7a3c4c7e3fe16e91225a87cbc58b8bbd798f9cc1
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/codingstatemachinedict.py
@@ -0,0 +1,19 @@
+from typing import TYPE_CHECKING, Tuple
+
+if TYPE_CHECKING:
+ # TypedDict was introduced in Python 3.8.
+ #
+ # TODO: Remove the else block and TYPE_CHECKING check when dropping support
+ # for Python 3.7.
+ from typing import TypedDict
+
+ class CodingStateMachineDict(TypedDict, total=False):
+ class_table: Tuple[int, ...]
+ class_factor: int
+ state_table: Tuple[int, ...]
+ char_len_table: Tuple[int, ...]
+ name: str
+ language: str # Optional key
+
+else:
+ CodingStateMachineDict = dict
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/enums.py b/env-llmeval/lib/python3.10/site-packages/chardet/enums.py
new file mode 100644
index 0000000000000000000000000000000000000000..5e3e198233698f2b007489dd299cecb87d971067
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/enums.py
@@ -0,0 +1,85 @@
+"""
+All of the Enums that are used throughout the chardet package.
+
+:author: Dan Blanchard (dan.blanchard@gmail.com)
+"""
+
+from enum import Enum, Flag
+
+
+class InputState:
+ """
+ This enum represents the different states a universal detector can be in.
+ """
+
+ PURE_ASCII = 0
+ ESC_ASCII = 1
+ HIGH_BYTE = 2
+
+
+class LanguageFilter(Flag):
+ """
+ This enum represents the different language filters we can apply to a
+ ``UniversalDetector``.
+ """
+
+ NONE = 0x00
+ CHINESE_SIMPLIFIED = 0x01
+ CHINESE_TRADITIONAL = 0x02
+ JAPANESE = 0x04
+ KOREAN = 0x08
+ NON_CJK = 0x10
+ ALL = 0x1F
+ CHINESE = CHINESE_SIMPLIFIED | CHINESE_TRADITIONAL
+ CJK = CHINESE | JAPANESE | KOREAN
+
+
+class ProbingState(Enum):
+ """
+ This enum represents the different states a prober can be in.
+ """
+
+ DETECTING = 0
+ FOUND_IT = 1
+ NOT_ME = 2
+
+
+class MachineState:
+ """
+ This enum represents the different states a state machine can be in.
+ """
+
+ START = 0
+ ERROR = 1
+ ITS_ME = 2
+
+
+class SequenceLikelihood:
+ """
+ This enum represents the likelihood of a character following the previous one.
+ """
+
+ NEGATIVE = 0
+ UNLIKELY = 1
+ LIKELY = 2
+ POSITIVE = 3
+
+ @classmethod
+ def get_num_categories(cls) -> int:
+ """:returns: The number of likelihood categories in the enum."""
+ return 4
+
+
+class CharacterCategory:
+ """
+ This enum represents the different categories language models for
+ ``SingleByteCharsetProber`` put characters into.
+
+ Anything less than CONTROL is considered a letter.
+ """
+
+ UNDEFINED = 255
+ LINE_BREAK = 254
+ SYMBOL = 253
+ DIGIT = 252
+ CONTROL = 251
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/escsm.py b/env-llmeval/lib/python3.10/site-packages/chardet/escsm.py
new file mode 100644
index 0000000000000000000000000000000000000000..11d4adf771f3f90bb5f1cc11043599b48e955c22
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/escsm.py
@@ -0,0 +1,261 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from .codingstatemachinedict import CodingStateMachineDict
+from .enums import MachineState
+
+# fmt: off
+HZ_CLS = (
+ 1, 0, 0, 0, 0, 0, 0, 0, # 00 - 07
+ 0, 0, 0, 0, 0, 0, 0, 0, # 08 - 0f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 10 - 17
+ 0, 0, 0, 1, 0, 0, 0, 0, # 18 - 1f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 20 - 27
+ 0, 0, 0, 0, 0, 0, 0, 0, # 28 - 2f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 30 - 37
+ 0, 0, 0, 0, 0, 0, 0, 0, # 38 - 3f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 40 - 47
+ 0, 0, 0, 0, 0, 0, 0, 0, # 48 - 4f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 50 - 57
+ 0, 0, 0, 0, 0, 0, 0, 0, # 58 - 5f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 60 - 67
+ 0, 0, 0, 0, 0, 0, 0, 0, # 68 - 6f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 70 - 77
+ 0, 0, 0, 4, 0, 5, 2, 0, # 78 - 7f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 80 - 87
+ 1, 1, 1, 1, 1, 1, 1, 1, # 88 - 8f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 90 - 97
+ 1, 1, 1, 1, 1, 1, 1, 1, # 98 - 9f
+ 1, 1, 1, 1, 1, 1, 1, 1, # a0 - a7
+ 1, 1, 1, 1, 1, 1, 1, 1, # a8 - af
+ 1, 1, 1, 1, 1, 1, 1, 1, # b0 - b7
+ 1, 1, 1, 1, 1, 1, 1, 1, # b8 - bf
+ 1, 1, 1, 1, 1, 1, 1, 1, # c0 - c7
+ 1, 1, 1, 1, 1, 1, 1, 1, # c8 - cf
+ 1, 1, 1, 1, 1, 1, 1, 1, # d0 - d7
+ 1, 1, 1, 1, 1, 1, 1, 1, # d8 - df
+ 1, 1, 1, 1, 1, 1, 1, 1, # e0 - e7
+ 1, 1, 1, 1, 1, 1, 1, 1, # e8 - ef
+ 1, 1, 1, 1, 1, 1, 1, 1, # f0 - f7
+ 1, 1, 1, 1, 1, 1, 1, 1, # f8 - ff
+)
+
+HZ_ST = (
+MachineState.START, MachineState.ERROR, 3, MachineState.START, MachineState.START, MachineState.START, MachineState.ERROR, MachineState.ERROR, # 00-07
+MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, # 08-0f
+MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.START, MachineState.START, 4, MachineState.ERROR, # 10-17
+ 5, MachineState.ERROR, 6, MachineState.ERROR, 5, 5, 4, MachineState.ERROR, # 18-1f
+ 4, MachineState.ERROR, 4, 4, 4, MachineState.ERROR, 4, MachineState.ERROR, # 20-27
+ 4, MachineState.ITS_ME, MachineState.START, MachineState.START, MachineState.START, MachineState.START, MachineState.START, MachineState.START, # 28-2f
+)
+# fmt: on
+
+HZ_CHAR_LEN_TABLE = (0, 0, 0, 0, 0, 0)
+
+HZ_SM_MODEL: CodingStateMachineDict = {
+ "class_table": HZ_CLS,
+ "class_factor": 6,
+ "state_table": HZ_ST,
+ "char_len_table": HZ_CHAR_LEN_TABLE,
+ "name": "HZ-GB-2312",
+ "language": "Chinese",
+}
+
+# fmt: off
+ISO2022CN_CLS = (
+ 2, 0, 0, 0, 0, 0, 0, 0, # 00 - 07
+ 0, 0, 0, 0, 0, 0, 0, 0, # 08 - 0f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 10 - 17
+ 0, 0, 0, 1, 0, 0, 0, 0, # 18 - 1f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 20 - 27
+ 0, 3, 0, 0, 0, 0, 0, 0, # 28 - 2f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 30 - 37
+ 0, 0, 0, 0, 0, 0, 0, 0, # 38 - 3f
+ 0, 0, 0, 4, 0, 0, 0, 0, # 40 - 47
+ 0, 0, 0, 0, 0, 0, 0, 0, # 48 - 4f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 50 - 57
+ 0, 0, 0, 0, 0, 0, 0, 0, # 58 - 5f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 60 - 67
+ 0, 0, 0, 0, 0, 0, 0, 0, # 68 - 6f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 70 - 77
+ 0, 0, 0, 0, 0, 0, 0, 0, # 78 - 7f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 80 - 87
+ 2, 2, 2, 2, 2, 2, 2, 2, # 88 - 8f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 90 - 97
+ 2, 2, 2, 2, 2, 2, 2, 2, # 98 - 9f
+ 2, 2, 2, 2, 2, 2, 2, 2, # a0 - a7
+ 2, 2, 2, 2, 2, 2, 2, 2, # a8 - af
+ 2, 2, 2, 2, 2, 2, 2, 2, # b0 - b7
+ 2, 2, 2, 2, 2, 2, 2, 2, # b8 - bf
+ 2, 2, 2, 2, 2, 2, 2, 2, # c0 - c7
+ 2, 2, 2, 2, 2, 2, 2, 2, # c8 - cf
+ 2, 2, 2, 2, 2, 2, 2, 2, # d0 - d7
+ 2, 2, 2, 2, 2, 2, 2, 2, # d8 - df
+ 2, 2, 2, 2, 2, 2, 2, 2, # e0 - e7
+ 2, 2, 2, 2, 2, 2, 2, 2, # e8 - ef
+ 2, 2, 2, 2, 2, 2, 2, 2, # f0 - f7
+ 2, 2, 2, 2, 2, 2, 2, 2, # f8 - ff
+)
+
+ISO2022CN_ST = (
+ MachineState.START, 3, MachineState.ERROR, MachineState.START, MachineState.START, MachineState.START, MachineState.START, MachineState.START, # 00-07
+ MachineState.START, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 08-0f
+ MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, # 10-17
+ MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, 4, MachineState.ERROR, # 18-1f
+ MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 20-27
+ 5, 6, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 28-2f
+ MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 30-37
+ MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.START, # 38-3f
+)
+# fmt: on
+
+ISO2022CN_CHAR_LEN_TABLE = (0, 0, 0, 0, 0, 0, 0, 0, 0)
+
+ISO2022CN_SM_MODEL: CodingStateMachineDict = {
+ "class_table": ISO2022CN_CLS,
+ "class_factor": 9,
+ "state_table": ISO2022CN_ST,
+ "char_len_table": ISO2022CN_CHAR_LEN_TABLE,
+ "name": "ISO-2022-CN",
+ "language": "Chinese",
+}
+
+# fmt: off
+ISO2022JP_CLS = (
+ 2, 0, 0, 0, 0, 0, 0, 0, # 00 - 07
+ 0, 0, 0, 0, 0, 0, 2, 2, # 08 - 0f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 10 - 17
+ 0, 0, 0, 1, 0, 0, 0, 0, # 18 - 1f
+ 0, 0, 0, 0, 7, 0, 0, 0, # 20 - 27
+ 3, 0, 0, 0, 0, 0, 0, 0, # 28 - 2f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 30 - 37
+ 0, 0, 0, 0, 0, 0, 0, 0, # 38 - 3f
+ 6, 0, 4, 0, 8, 0, 0, 0, # 40 - 47
+ 0, 9, 5, 0, 0, 0, 0, 0, # 48 - 4f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 50 - 57
+ 0, 0, 0, 0, 0, 0, 0, 0, # 58 - 5f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 60 - 67
+ 0, 0, 0, 0, 0, 0, 0, 0, # 68 - 6f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 70 - 77
+ 0, 0, 0, 0, 0, 0, 0, 0, # 78 - 7f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 80 - 87
+ 2, 2, 2, 2, 2, 2, 2, 2, # 88 - 8f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 90 - 97
+ 2, 2, 2, 2, 2, 2, 2, 2, # 98 - 9f
+ 2, 2, 2, 2, 2, 2, 2, 2, # a0 - a7
+ 2, 2, 2, 2, 2, 2, 2, 2, # a8 - af
+ 2, 2, 2, 2, 2, 2, 2, 2, # b0 - b7
+ 2, 2, 2, 2, 2, 2, 2, 2, # b8 - bf
+ 2, 2, 2, 2, 2, 2, 2, 2, # c0 - c7
+ 2, 2, 2, 2, 2, 2, 2, 2, # c8 - cf
+ 2, 2, 2, 2, 2, 2, 2, 2, # d0 - d7
+ 2, 2, 2, 2, 2, 2, 2, 2, # d8 - df
+ 2, 2, 2, 2, 2, 2, 2, 2, # e0 - e7
+ 2, 2, 2, 2, 2, 2, 2, 2, # e8 - ef
+ 2, 2, 2, 2, 2, 2, 2, 2, # f0 - f7
+ 2, 2, 2, 2, 2, 2, 2, 2, # f8 - ff
+)
+
+ISO2022JP_ST = (
+ MachineState.START, 3, MachineState.ERROR, MachineState.START, MachineState.START, MachineState.START, MachineState.START, MachineState.START, # 00-07
+ MachineState.START, MachineState.START, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 08-0f
+ MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, # 10-17
+ MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, # 18-1f
+ MachineState.ERROR, 5, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, 4, MachineState.ERROR, MachineState.ERROR, # 20-27
+ MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, 6, MachineState.ITS_ME, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, # 28-2f
+ MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, # 30-37
+ MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 38-3f
+ MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.START, MachineState.START, # 40-47
+)
+# fmt: on
+
+ISO2022JP_CHAR_LEN_TABLE = (0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
+
+ISO2022JP_SM_MODEL: CodingStateMachineDict = {
+ "class_table": ISO2022JP_CLS,
+ "class_factor": 10,
+ "state_table": ISO2022JP_ST,
+ "char_len_table": ISO2022JP_CHAR_LEN_TABLE,
+ "name": "ISO-2022-JP",
+ "language": "Japanese",
+}
+
+# fmt: off
+ISO2022KR_CLS = (
+ 2, 0, 0, 0, 0, 0, 0, 0, # 00 - 07
+ 0, 0, 0, 0, 0, 0, 0, 0, # 08 - 0f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 10 - 17
+ 0, 0, 0, 1, 0, 0, 0, 0, # 18 - 1f
+ 0, 0, 0, 0, 3, 0, 0, 0, # 20 - 27
+ 0, 4, 0, 0, 0, 0, 0, 0, # 28 - 2f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 30 - 37
+ 0, 0, 0, 0, 0, 0, 0, 0, # 38 - 3f
+ 0, 0, 0, 5, 0, 0, 0, 0, # 40 - 47
+ 0, 0, 0, 0, 0, 0, 0, 0, # 48 - 4f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 50 - 57
+ 0, 0, 0, 0, 0, 0, 0, 0, # 58 - 5f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 60 - 67
+ 0, 0, 0, 0, 0, 0, 0, 0, # 68 - 6f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 70 - 77
+ 0, 0, 0, 0, 0, 0, 0, 0, # 78 - 7f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 80 - 87
+ 2, 2, 2, 2, 2, 2, 2, 2, # 88 - 8f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 90 - 97
+ 2, 2, 2, 2, 2, 2, 2, 2, # 98 - 9f
+ 2, 2, 2, 2, 2, 2, 2, 2, # a0 - a7
+ 2, 2, 2, 2, 2, 2, 2, 2, # a8 - af
+ 2, 2, 2, 2, 2, 2, 2, 2, # b0 - b7
+ 2, 2, 2, 2, 2, 2, 2, 2, # b8 - bf
+ 2, 2, 2, 2, 2, 2, 2, 2, # c0 - c7
+ 2, 2, 2, 2, 2, 2, 2, 2, # c8 - cf
+ 2, 2, 2, 2, 2, 2, 2, 2, # d0 - d7
+ 2, 2, 2, 2, 2, 2, 2, 2, # d8 - df
+ 2, 2, 2, 2, 2, 2, 2, 2, # e0 - e7
+ 2, 2, 2, 2, 2, 2, 2, 2, # e8 - ef
+ 2, 2, 2, 2, 2, 2, 2, 2, # f0 - f7
+ 2, 2, 2, 2, 2, 2, 2, 2, # f8 - ff
+)
+
+ISO2022KR_ST = (
+ MachineState.START, 3, MachineState.ERROR, MachineState.START, MachineState.START, MachineState.START, MachineState.ERROR, MachineState.ERROR, # 00-07
+ MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, # 08-0f
+ MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, 4, MachineState.ERROR, MachineState.ERROR, # 10-17
+ MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, 5, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 18-1f
+ MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.START, MachineState.START, MachineState.START, MachineState.START, # 20-27
+)
+# fmt: on
+
+ISO2022KR_CHAR_LEN_TABLE = (0, 0, 0, 0, 0, 0)
+
+ISO2022KR_SM_MODEL: CodingStateMachineDict = {
+ "class_table": ISO2022KR_CLS,
+ "class_factor": 6,
+ "state_table": ISO2022KR_ST,
+ "char_len_table": ISO2022KR_CHAR_LEN_TABLE,
+ "name": "ISO-2022-KR",
+ "language": "Korean",
+}
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/euckrfreq.py b/env-llmeval/lib/python3.10/site-packages/chardet/euckrfreq.py
new file mode 100644
index 0000000000000000000000000000000000000000..7dc3b10387d1c3d2da8b4e27e917ee2a85086e0c
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/euckrfreq.py
@@ -0,0 +1,196 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+# Sampling from about 20M text materials include literature and computer technology
+
+# 128 --> 0.79
+# 256 --> 0.92
+# 512 --> 0.986
+# 1024 --> 0.99944
+# 2048 --> 0.99999
+#
+# Idea Distribution Ratio = 0.98653 / (1-0.98653) = 73.24
+# Random Distribution Ration = 512 / (2350-512) = 0.279.
+#
+# Typical Distribution Ratio
+
+EUCKR_TYPICAL_DISTRIBUTION_RATIO = 6.0
+
+EUCKR_TABLE_SIZE = 2352
+
+# Char to FreqOrder table ,
+# fmt: off
+EUCKR_CHAR_TO_FREQ_ORDER = (
+ 13, 130, 120,1396, 481,1719,1720, 328, 609, 212,1721, 707, 400, 299,1722, 87,
+1397,1723, 104, 536,1117,1203,1724,1267, 685,1268, 508,1725,1726,1727,1728,1398,
+1399,1729,1730,1731, 141, 621, 326,1057, 368,1732, 267, 488, 20,1733,1269,1734,
+ 945,1400,1735, 47, 904,1270,1736,1737, 773, 248,1738, 409, 313, 786, 429,1739,
+ 116, 987, 813,1401, 683, 75,1204, 145,1740,1741,1742,1743, 16, 847, 667, 622,
+ 708,1744,1745,1746, 966, 787, 304, 129,1747, 60, 820, 123, 676,1748,1749,1750,
+1751, 617,1752, 626,1753,1754,1755,1756, 653,1757,1758,1759,1760,1761,1762, 856,
+ 344,1763,1764,1765,1766, 89, 401, 418, 806, 905, 848,1767,1768,1769, 946,1205,
+ 709,1770,1118,1771, 241,1772,1773,1774,1271,1775, 569,1776, 999,1777,1778,1779,
+1780, 337, 751,1058, 28, 628, 254,1781, 177, 906, 270, 349, 891,1079,1782, 19,
+1783, 379,1784, 315,1785, 629, 754,1402, 559,1786, 636, 203,1206,1787, 710, 567,
+1788, 935, 814,1789,1790,1207, 766, 528,1791,1792,1208,1793,1794,1795,1796,1797,
+1403,1798,1799, 533,1059,1404,1405,1156,1406, 936, 884,1080,1800, 351,1801,1802,
+1803,1804,1805, 801,1806,1807,1808,1119,1809,1157, 714, 474,1407,1810, 298, 899,
+ 885,1811,1120, 802,1158,1812, 892,1813,1814,1408, 659,1815,1816,1121,1817,1818,
+1819,1820,1821,1822, 319,1823, 594, 545,1824, 815, 937,1209,1825,1826, 573,1409,
+1022,1827,1210,1828,1829,1830,1831,1832,1833, 556, 722, 807,1122,1060,1834, 697,
+1835, 900, 557, 715,1836,1410, 540,1411, 752,1159, 294, 597,1211, 976, 803, 770,
+1412,1837,1838, 39, 794,1413, 358,1839, 371, 925,1840, 453, 661, 788, 531, 723,
+ 544,1023,1081, 869, 91,1841, 392, 430, 790, 602,1414, 677,1082, 457,1415,1416,
+1842,1843, 475, 327,1024,1417, 795, 121,1844, 733, 403,1418,1845,1846,1847, 300,
+ 119, 711,1212, 627,1848,1272, 207,1849,1850, 796,1213, 382,1851, 519,1852,1083,
+ 893,1853,1854,1855, 367, 809, 487, 671,1856, 663,1857,1858, 956, 471, 306, 857,
+1859,1860,1160,1084,1861,1862,1863,1864,1865,1061,1866,1867,1868,1869,1870,1871,
+ 282, 96, 574,1872, 502,1085,1873,1214,1874, 907,1875,1876, 827, 977,1419,1420,
+1421, 268,1877,1422,1878,1879,1880, 308,1881, 2, 537,1882,1883,1215,1884,1885,
+ 127, 791,1886,1273,1423,1887, 34, 336, 404, 643,1888, 571, 654, 894, 840,1889,
+ 0, 886,1274, 122, 575, 260, 908, 938,1890,1275, 410, 316,1891,1892, 100,1893,
+1894,1123, 48,1161,1124,1025,1895, 633, 901,1276,1896,1897, 115, 816,1898, 317,
+1899, 694,1900, 909, 734,1424, 572, 866,1425, 691, 85, 524,1010, 543, 394, 841,
+1901,1902,1903,1026,1904,1905,1906,1907,1908,1909, 30, 451, 651, 988, 310,1910,
+1911,1426, 810,1216, 93,1912,1913,1277,1217,1914, 858, 759, 45, 58, 181, 610,
+ 269,1915,1916, 131,1062, 551, 443,1000, 821,1427, 957, 895,1086,1917,1918, 375,
+1919, 359,1920, 687,1921, 822,1922, 293,1923,1924, 40, 662, 118, 692, 29, 939,
+ 887, 640, 482, 174,1925, 69,1162, 728,1428, 910,1926,1278,1218,1279, 386, 870,
+ 217, 854,1163, 823,1927,1928,1929,1930, 834,1931, 78,1932, 859,1933,1063,1934,
+1935,1936,1937, 438,1164, 208, 595,1938,1939,1940,1941,1219,1125,1942, 280, 888,
+1429,1430,1220,1431,1943,1944,1945,1946,1947,1280, 150, 510,1432,1948,1949,1950,
+1951,1952,1953,1954,1011,1087,1955,1433,1043,1956, 881,1957, 614, 958,1064,1065,
+1221,1958, 638,1001, 860, 967, 896,1434, 989, 492, 553,1281,1165,1959,1282,1002,
+1283,1222,1960,1961,1962,1963, 36, 383, 228, 753, 247, 454,1964, 876, 678,1965,
+1966,1284, 126, 464, 490, 835, 136, 672, 529, 940,1088,1435, 473,1967,1968, 467,
+ 50, 390, 227, 587, 279, 378, 598, 792, 968, 240, 151, 160, 849, 882,1126,1285,
+ 639,1044, 133, 140, 288, 360, 811, 563,1027, 561, 142, 523,1969,1970,1971, 7,
+ 103, 296, 439, 407, 506, 634, 990,1972,1973,1974,1975, 645,1976,1977,1978,1979,
+1980,1981, 236,1982,1436,1983,1984,1089, 192, 828, 618, 518,1166, 333,1127,1985,
+ 818,1223,1986,1987,1988,1989,1990,1991,1992,1993, 342,1128,1286, 746, 842,1994,
+1995, 560, 223,1287, 98, 8, 189, 650, 978,1288,1996,1437,1997, 17, 345, 250,
+ 423, 277, 234, 512, 226, 97, 289, 42, 167,1998, 201,1999,2000, 843, 836, 824,
+ 532, 338, 783,1090, 182, 576, 436,1438,1439, 527, 500,2001, 947, 889,2002,2003,
+2004,2005, 262, 600, 314, 447,2006, 547,2007, 693, 738,1129,2008, 71,1440, 745,
+ 619, 688,2009, 829,2010,2011, 147,2012, 33, 948,2013,2014, 74, 224,2015, 61,
+ 191, 918, 399, 637,2016,1028,1130, 257, 902,2017,2018,2019,2020,2021,2022,2023,
+2024,2025,2026, 837,2027,2028,2029,2030, 179, 874, 591, 52, 724, 246,2031,2032,
+2033,2034,1167, 969,2035,1289, 630, 605, 911,1091,1168,2036,2037,2038,1441, 912,
+2039, 623,2040,2041, 253,1169,1290,2042,1442, 146, 620, 611, 577, 433,2043,1224,
+ 719,1170, 959, 440, 437, 534, 84, 388, 480,1131, 159, 220, 198, 679,2044,1012,
+ 819,1066,1443, 113,1225, 194, 318,1003,1029,2045,2046,2047,2048,1067,2049,2050,
+2051,2052,2053, 59, 913, 112,2054, 632,2055, 455, 144, 739,1291,2056, 273, 681,
+ 499,2057, 448,2058,2059, 760,2060,2061, 970, 384, 169, 245,1132,2062,2063, 414,
+1444,2064,2065, 41, 235,2066, 157, 252, 877, 568, 919, 789, 580,2067, 725,2068,
+2069,1292,2070,2071,1445,2072,1446,2073,2074, 55, 588, 66,1447, 271,1092,2075,
+1226,2076, 960,1013, 372,2077,2078,2079,2080,2081,1293,2082,2083,2084,2085, 850,
+2086,2087,2088,2089,2090, 186,2091,1068, 180,2092,2093,2094, 109,1227, 522, 606,
+2095, 867,1448,1093, 991,1171, 926, 353,1133,2096, 581,2097,2098,2099,1294,1449,
+1450,2100, 596,1172,1014,1228,2101,1451,1295,1173,1229,2102,2103,1296,1134,1452,
+ 949,1135,2104,2105,1094,1453,1454,1455,2106,1095,2107,2108,2109,2110,2111,2112,
+2113,2114,2115,2116,2117, 804,2118,2119,1230,1231, 805,1456, 405,1136,2120,2121,
+2122,2123,2124, 720, 701,1297, 992,1457, 927,1004,2125,2126,2127,2128,2129,2130,
+ 22, 417,2131, 303,2132, 385,2133, 971, 520, 513,2134,1174, 73,1096, 231, 274,
+ 962,1458, 673,2135,1459,2136, 152,1137,2137,2138,2139,2140,1005,1138,1460,1139,
+2141,2142,2143,2144, 11, 374, 844,2145, 154,1232, 46,1461,2146, 838, 830, 721,
+1233, 106,2147, 90, 428, 462, 578, 566,1175, 352,2148,2149, 538,1234, 124,1298,
+2150,1462, 761, 565,2151, 686,2152, 649,2153, 72, 173,2154, 460, 415,2155,1463,
+2156,1235, 305,2157,2158,2159,2160,2161,2162, 579,2163,2164,2165,2166,2167, 747,
+2168,2169,2170,2171,1464, 669,2172,2173,2174,2175,2176,1465,2177, 23, 530, 285,
+2178, 335, 729,2179, 397,2180,2181,2182,1030,2183,2184, 698,2185,2186, 325,2187,
+2188, 369,2189, 799,1097,1015, 348,2190,1069, 680,2191, 851,1466,2192,2193, 10,
+2194, 613, 424,2195, 979, 108, 449, 589, 27, 172, 81,1031, 80, 774, 281, 350,
+1032, 525, 301, 582,1176,2196, 674,1045,2197,2198,1467, 730, 762,2199,2200,2201,
+2202,1468,2203, 993,2204,2205, 266,1070, 963,1140,2206,2207,2208, 664,1098, 972,
+2209,2210,2211,1177,1469,1470, 871,2212,2213,2214,2215,2216,1471,2217,2218,2219,
+2220,2221,2222,2223,2224,2225,2226,2227,1472,1236,2228,2229,2230,2231,2232,2233,
+2234,2235,1299,2236,2237, 200,2238, 477, 373,2239,2240, 731, 825, 777,2241,2242,
+2243, 521, 486, 548,2244,2245,2246,1473,1300, 53, 549, 137, 875, 76, 158,2247,
+1301,1474, 469, 396,1016, 278, 712,2248, 321, 442, 503, 767, 744, 941,1237,1178,
+1475,2249, 82, 178,1141,1179, 973,2250,1302,2251, 297,2252,2253, 570,2254,2255,
+2256, 18, 450, 206,2257, 290, 292,1142,2258, 511, 162, 99, 346, 164, 735,2259,
+1476,1477, 4, 554, 343, 798,1099,2260,1100,2261, 43, 171,1303, 139, 215,2262,
+2263, 717, 775,2264,1033, 322, 216,2265, 831,2266, 149,2267,1304,2268,2269, 702,
+1238, 135, 845, 347, 309,2270, 484,2271, 878, 655, 238,1006,1478,2272, 67,2273,
+ 295,2274,2275, 461,2276, 478, 942, 412,2277,1034,2278,2279,2280, 265,2281, 541,
+2282,2283,2284,2285,2286, 70, 852,1071,2287,2288,2289,2290, 21, 56, 509, 117,
+ 432,2291,2292, 331, 980, 552,1101, 148, 284, 105, 393,1180,1239, 755,2293, 187,
+2294,1046,1479,2295, 340,2296, 63,1047, 230,2297,2298,1305, 763,1306, 101, 800,
+ 808, 494,2299,2300,2301, 903,2302, 37,1072, 14, 5,2303, 79, 675,2304, 312,
+2305,2306,2307,2308,2309,1480, 6,1307,2310,2311,2312, 1, 470, 35, 24, 229,
+2313, 695, 210, 86, 778, 15, 784, 592, 779, 32, 77, 855, 964,2314, 259,2315,
+ 501, 380,2316,2317, 83, 981, 153, 689,1308,1481,1482,1483,2318,2319, 716,1484,
+2320,2321,2322,2323,2324,2325,1485,2326,2327, 128, 57, 68, 261,1048, 211, 170,
+1240, 31,2328, 51, 435, 742,2329,2330,2331, 635,2332, 264, 456,2333,2334,2335,
+ 425,2336,1486, 143, 507, 263, 943,2337, 363, 920,1487, 256,1488,1102, 243, 601,
+1489,2338,2339,2340,2341,2342,2343,2344, 861,2345,2346,2347,2348,2349,2350, 395,
+2351,1490,1491, 62, 535, 166, 225,2352,2353, 668, 419,1241, 138, 604, 928,2354,
+1181,2355,1492,1493,2356,2357,2358,1143,2359, 696,2360, 387, 307,1309, 682, 476,
+2361,2362, 332, 12, 222, 156,2363, 232,2364, 641, 276, 656, 517,1494,1495,1035,
+ 416, 736,1496,2365,1017, 586,2366,2367,2368,1497,2369, 242,2370,2371,2372,1498,
+2373, 965, 713,2374,2375,2376,2377, 740, 982,1499, 944,1500,1007,2378,2379,1310,
+1501,2380,2381,2382, 785, 329,2383,2384,1502,2385,2386,2387, 932,2388,1503,2389,
+2390,2391,2392,1242,2393,2394,2395,2396,2397, 994, 950,2398,2399,2400,2401,1504,
+1311,2402,2403,2404,2405,1049, 749,2406,2407, 853, 718,1144,1312,2408,1182,1505,
+2409,2410, 255, 516, 479, 564, 550, 214,1506,1507,1313, 413, 239, 444, 339,1145,
+1036,1508,1509,1314,1037,1510,1315,2411,1511,2412,2413,2414, 176, 703, 497, 624,
+ 593, 921, 302,2415, 341, 165,1103,1512,2416,1513,2417,2418,2419, 376,2420, 700,
+2421,2422,2423, 258, 768,1316,2424,1183,2425, 995, 608,2426,2427,2428,2429, 221,
+2430,2431,2432,2433,2434,2435,2436,2437, 195, 323, 726, 188, 897, 983,1317, 377,
+ 644,1050, 879,2438, 452,2439,2440,2441,2442,2443,2444, 914,2445,2446,2447,2448,
+ 915, 489,2449,1514,1184,2450,2451, 515, 64, 427, 495,2452, 583,2453, 483, 485,
+1038, 562, 213,1515, 748, 666,2454,2455,2456,2457, 334,2458, 780, 996,1008, 705,
+1243,2459,2460,2461,2462,2463, 114,2464, 493,1146, 366, 163,1516, 961,1104,2465,
+ 291,2466,1318,1105,2467,1517, 365,2468, 355, 951,1244,2469,1319,2470, 631,2471,
+2472, 218,1320, 364, 320, 756,1518,1519,1321,1520,1322,2473,2474,2475,2476, 997,
+2477,2478,2479,2480, 665,1185,2481, 916,1521,2482,2483,2484, 584, 684,2485,2486,
+ 797,2487,1051,1186,2488,2489,2490,1522,2491,2492, 370,2493,1039,1187, 65,2494,
+ 434, 205, 463,1188,2495, 125, 812, 391, 402, 826, 699, 286, 398, 155, 781, 771,
+ 585,2496, 590, 505,1073,2497, 599, 244, 219, 917,1018, 952, 646,1523,2498,1323,
+2499,2500, 49, 984, 354, 741,2501, 625,2502,1324,2503,1019, 190, 357, 757, 491,
+ 95, 782, 868,2504,2505,2506,2507,2508,2509, 134,1524,1074, 422,1525, 898,2510,
+ 161,2511,2512,2513,2514, 769,2515,1526,2516,2517, 411,1325,2518, 472,1527,2519,
+2520,2521,2522,2523,2524, 985,2525,2526,2527,2528,2529,2530, 764,2531,1245,2532,
+2533, 25, 204, 311,2534, 496,2535,1052,2536,2537,2538,2539,2540,2541,2542, 199,
+ 704, 504, 468, 758, 657,1528, 196, 44, 839,1246, 272, 750,2543, 765, 862,2544,
+2545,1326,2546, 132, 615, 933,2547, 732,2548,2549,2550,1189,1529,2551, 283,1247,
+1053, 607, 929,2552,2553,2554, 930, 183, 872, 616,1040,1147,2555,1148,1020, 441,
+ 249,1075,2556,2557,2558, 466, 743,2559,2560,2561, 92, 514, 426, 420, 526,2562,
+2563,2564,2565,2566,2567,2568, 185,2569,2570,2571,2572, 776,1530, 658,2573, 362,
+2574, 361, 922,1076, 793,2575,2576,2577,2578,2579,2580,1531, 251,2581,2582,2583,
+2584,1532, 54, 612, 237,1327,2585,2586, 275, 408, 647, 111,2587,1533,1106, 465,
+ 3, 458, 9, 38,2588, 107, 110, 890, 209, 26, 737, 498,2589,1534,2590, 431,
+ 202, 88,1535, 356, 287,1107, 660,1149,2591, 381,1536, 986,1150, 445,1248,1151,
+ 974,2592,2593, 846,2594, 446, 953, 184,1249,1250, 727,2595, 923, 193, 883,2596,
+2597,2598, 102, 324, 539, 817,2599, 421,1041,2600, 832,2601, 94, 175, 197, 406,
+2602, 459,2603,2604,2605,2606,2607, 330, 555,2608,2609,2610, 706,1108, 389,2611,
+2612,2613,2614, 233,2615, 833, 558, 931, 954,1251,2616,2617,1537, 546,2618,2619,
+1009,2620,2621,2622,1538, 690,1328,2623, 955,2624,1539,2625,2626, 772,2627,2628,
+2629,2630,2631, 924, 648, 863, 603,2632,2633, 934,1540, 864, 865,2634, 642,1042,
+ 670,1190,2635,2636,2637,2638, 168,2639, 652, 873, 542,1054,1541,2640,2641,2642, # 512, 256
+)
+# fmt: on
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/euctwfreq.py b/env-llmeval/lib/python3.10/site-packages/chardet/euctwfreq.py
new file mode 100644
index 0000000000000000000000000000000000000000..4900ccc160a1dbf4de3a01c234735c21dd4417d6
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/euctwfreq.py
@@ -0,0 +1,388 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+# EUCTW frequency table
+# Converted from big5 work
+# by Taiwan's Mandarin Promotion Council
+#
+
+# 128 --> 0.42261
+# 256 --> 0.57851
+# 512 --> 0.74851
+# 1024 --> 0.89384
+# 2048 --> 0.97583
+#
+# Idea Distribution Ratio = 0.74851/(1-0.74851) =2.98
+# Random Distribution Ration = 512/(5401-512)=0.105
+#
+# Typical Distribution Ratio about 25% of Ideal one, still much higher than RDR
+
+EUCTW_TYPICAL_DISTRIBUTION_RATIO = 0.75
+
+# Char to FreqOrder table
+EUCTW_TABLE_SIZE = 5376
+
+# fmt: off
+EUCTW_CHAR_TO_FREQ_ORDER = (
+ 1, 1800, 1506, 255, 1431, 198, 9, 82, 6, 7310, 177, 202, 3615, 1256, 2808, 110, # 2742
+ 3735, 33, 3241, 261, 76, 44, 2113, 16, 2931, 2184, 1176, 659, 3868, 26, 3404, 2643, # 2758
+ 1198, 3869, 3313, 4060, 410, 2211, 302, 590, 361, 1963, 8, 204, 58, 4296, 7311, 1931, # 2774
+ 63, 7312, 7313, 317, 1614, 75, 222, 159, 4061, 2412, 1480, 7314, 3500, 3068, 224, 2809, # 2790
+ 3616, 3, 10, 3870, 1471, 29, 2774, 1135, 2852, 1939, 873, 130, 3242, 1123, 312, 7315, # 2806
+ 4297, 2051, 507, 252, 682, 7316, 142, 1914, 124, 206, 2932, 34, 3501, 3173, 64, 604, # 2822
+ 7317, 2494, 1976, 1977, 155, 1990, 645, 641, 1606, 7318, 3405, 337, 72, 406, 7319, 80, # 2838
+ 630, 238, 3174, 1509, 263, 939, 1092, 2644, 756, 1440, 1094, 3406, 449, 69, 2969, 591, # 2854
+ 179, 2095, 471, 115, 2034, 1843, 60, 50, 2970, 134, 806, 1868, 734, 2035, 3407, 180, # 2870
+ 995, 1607, 156, 537, 2893, 688, 7320, 319, 1305, 779, 2144, 514, 2374, 298, 4298, 359, # 2886
+ 2495, 90, 2707, 1338, 663, 11, 906, 1099, 2545, 20, 2436, 182, 532, 1716, 7321, 732, # 2902
+ 1376, 4062, 1311, 1420, 3175, 25, 2312, 1056, 113, 399, 382, 1949, 242, 3408, 2467, 529, # 2918
+ 3243, 475, 1447, 3617, 7322, 117, 21, 656, 810, 1297, 2295, 2329, 3502, 7323, 126, 4063, # 2934
+ 706, 456, 150, 613, 4299, 71, 1118, 2036, 4064, 145, 3069, 85, 835, 486, 2114, 1246, # 2950
+ 1426, 428, 727, 1285, 1015, 800, 106, 623, 303, 1281, 7324, 2127, 2354, 347, 3736, 221, # 2966
+ 3503, 3110, 7325, 1955, 1153, 4065, 83, 296, 1199, 3070, 192, 624, 93, 7326, 822, 1897, # 2982
+ 2810, 3111, 795, 2064, 991, 1554, 1542, 1592, 27, 43, 2853, 859, 139, 1456, 860, 4300, # 2998
+ 437, 712, 3871, 164, 2392, 3112, 695, 211, 3017, 2096, 195, 3872, 1608, 3504, 3505, 3618, # 3014
+ 3873, 234, 811, 2971, 2097, 3874, 2229, 1441, 3506, 1615, 2375, 668, 2076, 1638, 305, 228, # 3030
+ 1664, 4301, 467, 415, 7327, 262, 2098, 1593, 239, 108, 300, 200, 1033, 512, 1247, 2077, # 3046
+ 7328, 7329, 2173, 3176, 3619, 2673, 593, 845, 1062, 3244, 88, 1723, 2037, 3875, 1950, 212, # 3062
+ 266, 152, 149, 468, 1898, 4066, 4302, 77, 187, 7330, 3018, 37, 5, 2972, 7331, 3876, # 3078
+ 7332, 7333, 39, 2517, 4303, 2894, 3177, 2078, 55, 148, 74, 4304, 545, 483, 1474, 1029, # 3094
+ 1665, 217, 1869, 1531, 3113, 1104, 2645, 4067, 24, 172, 3507, 900, 3877, 3508, 3509, 4305, # 3110
+ 32, 1408, 2811, 1312, 329, 487, 2355, 2247, 2708, 784, 2674, 4, 3019, 3314, 1427, 1788, # 3126
+ 188, 109, 499, 7334, 3620, 1717, 1789, 888, 1217, 3020, 4306, 7335, 3510, 7336, 3315, 1520, # 3142
+ 3621, 3878, 196, 1034, 775, 7337, 7338, 929, 1815, 249, 439, 38, 7339, 1063, 7340, 794, # 3158
+ 3879, 1435, 2296, 46, 178, 3245, 2065, 7341, 2376, 7342, 214, 1709, 4307, 804, 35, 707, # 3174
+ 324, 3622, 1601, 2546, 140, 459, 4068, 7343, 7344, 1365, 839, 272, 978, 2257, 2572, 3409, # 3190
+ 2128, 1363, 3623, 1423, 697, 100, 3071, 48, 70, 1231, 495, 3114, 2193, 7345, 1294, 7346, # 3206
+ 2079, 462, 586, 1042, 3246, 853, 256, 988, 185, 2377, 3410, 1698, 434, 1084, 7347, 3411, # 3222
+ 314, 2615, 2775, 4308, 2330, 2331, 569, 2280, 637, 1816, 2518, 757, 1162, 1878, 1616, 3412, # 3238
+ 287, 1577, 2115, 768, 4309, 1671, 2854, 3511, 2519, 1321, 3737, 909, 2413, 7348, 4069, 933, # 3254
+ 3738, 7349, 2052, 2356, 1222, 4310, 765, 2414, 1322, 786, 4311, 7350, 1919, 1462, 1677, 2895, # 3270
+ 1699, 7351, 4312, 1424, 2437, 3115, 3624, 2590, 3316, 1774, 1940, 3413, 3880, 4070, 309, 1369, # 3286
+ 1130, 2812, 364, 2230, 1653, 1299, 3881, 3512, 3882, 3883, 2646, 525, 1085, 3021, 902, 2000, # 3302
+ 1475, 964, 4313, 421, 1844, 1415, 1057, 2281, 940, 1364, 3116, 376, 4314, 4315, 1381, 7, # 3318
+ 2520, 983, 2378, 336, 1710, 2675, 1845, 321, 3414, 559, 1131, 3022, 2742, 1808, 1132, 1313, # 3334
+ 265, 1481, 1857, 7352, 352, 1203, 2813, 3247, 167, 1089, 420, 2814, 776, 792, 1724, 3513, # 3350
+ 4071, 2438, 3248, 7353, 4072, 7354, 446, 229, 333, 2743, 901, 3739, 1200, 1557, 4316, 2647, # 3366
+ 1920, 395, 2744, 2676, 3740, 4073, 1835, 125, 916, 3178, 2616, 4317, 7355, 7356, 3741, 7357, # 3382
+ 7358, 7359, 4318, 3117, 3625, 1133, 2547, 1757, 3415, 1510, 2313, 1409, 3514, 7360, 2145, 438, # 3398
+ 2591, 2896, 2379, 3317, 1068, 958, 3023, 461, 311, 2855, 2677, 4074, 1915, 3179, 4075, 1978, # 3414
+ 383, 750, 2745, 2617, 4076, 274, 539, 385, 1278, 1442, 7361, 1154, 1964, 384, 561, 210, # 3430
+ 98, 1295, 2548, 3515, 7362, 1711, 2415, 1482, 3416, 3884, 2897, 1257, 129, 7363, 3742, 642, # 3446
+ 523, 2776, 2777, 2648, 7364, 141, 2231, 1333, 68, 176, 441, 876, 907, 4077, 603, 2592, # 3462
+ 710, 171, 3417, 404, 549, 18, 3118, 2393, 1410, 3626, 1666, 7365, 3516, 4319, 2898, 4320, # 3478
+ 7366, 2973, 368, 7367, 146, 366, 99, 871, 3627, 1543, 748, 807, 1586, 1185, 22, 2258, # 3494
+ 379, 3743, 3180, 7368, 3181, 505, 1941, 2618, 1991, 1382, 2314, 7369, 380, 2357, 218, 702, # 3510
+ 1817, 1248, 3418, 3024, 3517, 3318, 3249, 7370, 2974, 3628, 930, 3250, 3744, 7371, 59, 7372, # 3526
+ 585, 601, 4078, 497, 3419, 1112, 1314, 4321, 1801, 7373, 1223, 1472, 2174, 7374, 749, 1836, # 3542
+ 690, 1899, 3745, 1772, 3885, 1476, 429, 1043, 1790, 2232, 2116, 917, 4079, 447, 1086, 1629, # 3558
+ 7375, 556, 7376, 7377, 2020, 1654, 844, 1090, 105, 550, 966, 1758, 2815, 1008, 1782, 686, # 3574
+ 1095, 7378, 2282, 793, 1602, 7379, 3518, 2593, 4322, 4080, 2933, 2297, 4323, 3746, 980, 2496, # 3590
+ 544, 353, 527, 4324, 908, 2678, 2899, 7380, 381, 2619, 1942, 1348, 7381, 1341, 1252, 560, # 3606
+ 3072, 7382, 3420, 2856, 7383, 2053, 973, 886, 2080, 143, 4325, 7384, 7385, 157, 3886, 496, # 3622
+ 4081, 57, 840, 540, 2038, 4326, 4327, 3421, 2117, 1445, 970, 2259, 1748, 1965, 2081, 4082, # 3638
+ 3119, 1234, 1775, 3251, 2816, 3629, 773, 1206, 2129, 1066, 2039, 1326, 3887, 1738, 1725, 4083, # 3654
+ 279, 3120, 51, 1544, 2594, 423, 1578, 2130, 2066, 173, 4328, 1879, 7386, 7387, 1583, 264, # 3670
+ 610, 3630, 4329, 2439, 280, 154, 7388, 7389, 7390, 1739, 338, 1282, 3073, 693, 2857, 1411, # 3686
+ 1074, 3747, 2440, 7391, 4330, 7392, 7393, 1240, 952, 2394, 7394, 2900, 1538, 2679, 685, 1483, # 3702
+ 4084, 2468, 1436, 953, 4085, 2054, 4331, 671, 2395, 79, 4086, 2441, 3252, 608, 567, 2680, # 3718
+ 3422, 4087, 4088, 1691, 393, 1261, 1791, 2396, 7395, 4332, 7396, 7397, 7398, 7399, 1383, 1672, # 3734
+ 3748, 3182, 1464, 522, 1119, 661, 1150, 216, 675, 4333, 3888, 1432, 3519, 609, 4334, 2681, # 3750
+ 2397, 7400, 7401, 7402, 4089, 3025, 0, 7403, 2469, 315, 231, 2442, 301, 3319, 4335, 2380, # 3766
+ 7404, 233, 4090, 3631, 1818, 4336, 4337, 7405, 96, 1776, 1315, 2082, 7406, 257, 7407, 1809, # 3782
+ 3632, 2709, 1139, 1819, 4091, 2021, 1124, 2163, 2778, 1777, 2649, 7408, 3074, 363, 1655, 3183, # 3798
+ 7409, 2975, 7410, 7411, 7412, 3889, 1567, 3890, 718, 103, 3184, 849, 1443, 341, 3320, 2934, # 3814
+ 1484, 7413, 1712, 127, 67, 339, 4092, 2398, 679, 1412, 821, 7414, 7415, 834, 738, 351, # 3830
+ 2976, 2146, 846, 235, 1497, 1880, 418, 1992, 3749, 2710, 186, 1100, 2147, 2746, 3520, 1545, # 3846
+ 1355, 2935, 2858, 1377, 583, 3891, 4093, 2573, 2977, 7416, 1298, 3633, 1078, 2549, 3634, 2358, # 3862
+ 78, 3750, 3751, 267, 1289, 2099, 2001, 1594, 4094, 348, 369, 1274, 2194, 2175, 1837, 4338, # 3878
+ 1820, 2817, 3635, 2747, 2283, 2002, 4339, 2936, 2748, 144, 3321, 882, 4340, 3892, 2749, 3423, # 3894
+ 4341, 2901, 7417, 4095, 1726, 320, 7418, 3893, 3026, 788, 2978, 7419, 2818, 1773, 1327, 2859, # 3910
+ 3894, 2819, 7420, 1306, 4342, 2003, 1700, 3752, 3521, 2359, 2650, 787, 2022, 506, 824, 3636, # 3926
+ 534, 323, 4343, 1044, 3322, 2023, 1900, 946, 3424, 7421, 1778, 1500, 1678, 7422, 1881, 4344, # 3942
+ 165, 243, 4345, 3637, 2521, 123, 683, 4096, 764, 4346, 36, 3895, 1792, 589, 2902, 816, # 3958
+ 626, 1667, 3027, 2233, 1639, 1555, 1622, 3753, 3896, 7423, 3897, 2860, 1370, 1228, 1932, 891, # 3974
+ 2083, 2903, 304, 4097, 7424, 292, 2979, 2711, 3522, 691, 2100, 4098, 1115, 4347, 118, 662, # 3990
+ 7425, 611, 1156, 854, 2381, 1316, 2861, 2, 386, 515, 2904, 7426, 7427, 3253, 868, 2234, # 4006
+ 1486, 855, 2651, 785, 2212, 3028, 7428, 1040, 3185, 3523, 7429, 3121, 448, 7430, 1525, 7431, # 4022
+ 2164, 4348, 7432, 3754, 7433, 4099, 2820, 3524, 3122, 503, 818, 3898, 3123, 1568, 814, 676, # 4038
+ 1444, 306, 1749, 7434, 3755, 1416, 1030, 197, 1428, 805, 2821, 1501, 4349, 7435, 7436, 7437, # 4054
+ 1993, 7438, 4350, 7439, 7440, 2195, 13, 2779, 3638, 2980, 3124, 1229, 1916, 7441, 3756, 2131, # 4070
+ 7442, 4100, 4351, 2399, 3525, 7443, 2213, 1511, 1727, 1120, 7444, 7445, 646, 3757, 2443, 307, # 4086
+ 7446, 7447, 1595, 3186, 7448, 7449, 7450, 3639, 1113, 1356, 3899, 1465, 2522, 2523, 7451, 519, # 4102
+ 7452, 128, 2132, 92, 2284, 1979, 7453, 3900, 1512, 342, 3125, 2196, 7454, 2780, 2214, 1980, # 4118
+ 3323, 7455, 290, 1656, 1317, 789, 827, 2360, 7456, 3758, 4352, 562, 581, 3901, 7457, 401, # 4134
+ 4353, 2248, 94, 4354, 1399, 2781, 7458, 1463, 2024, 4355, 3187, 1943, 7459, 828, 1105, 4101, # 4150
+ 1262, 1394, 7460, 4102, 605, 4356, 7461, 1783, 2862, 7462, 2822, 819, 2101, 578, 2197, 2937, # 4166
+ 7463, 1502, 436, 3254, 4103, 3255, 2823, 3902, 2905, 3425, 3426, 7464, 2712, 2315, 7465, 7466, # 4182
+ 2332, 2067, 23, 4357, 193, 826, 3759, 2102, 699, 1630, 4104, 3075, 390, 1793, 1064, 3526, # 4198
+ 7467, 1579, 3076, 3077, 1400, 7468, 4105, 1838, 1640, 2863, 7469, 4358, 4359, 137, 4106, 598, # 4214
+ 3078, 1966, 780, 104, 974, 2938, 7470, 278, 899, 253, 402, 572, 504, 493, 1339, 7471, # 4230
+ 3903, 1275, 4360, 2574, 2550, 7472, 3640, 3029, 3079, 2249, 565, 1334, 2713, 863, 41, 7473, # 4246
+ 7474, 4361, 7475, 1657, 2333, 19, 463, 2750, 4107, 606, 7476, 2981, 3256, 1087, 2084, 1323, # 4262
+ 2652, 2982, 7477, 1631, 1623, 1750, 4108, 2682, 7478, 2864, 791, 2714, 2653, 2334, 232, 2416, # 4278
+ 7479, 2983, 1498, 7480, 2654, 2620, 755, 1366, 3641, 3257, 3126, 2025, 1609, 119, 1917, 3427, # 4294
+ 862, 1026, 4109, 7481, 3904, 3760, 4362, 3905, 4363, 2260, 1951, 2470, 7482, 1125, 817, 4110, # 4310
+ 4111, 3906, 1513, 1766, 2040, 1487, 4112, 3030, 3258, 2824, 3761, 3127, 7483, 7484, 1507, 7485, # 4326
+ 2683, 733, 40, 1632, 1106, 2865, 345, 4113, 841, 2524, 230, 4364, 2984, 1846, 3259, 3428, # 4342
+ 7486, 1263, 986, 3429, 7487, 735, 879, 254, 1137, 857, 622, 1300, 1180, 1388, 1562, 3907, # 4358
+ 3908, 2939, 967, 2751, 2655, 1349, 592, 2133, 1692, 3324, 2985, 1994, 4114, 1679, 3909, 1901, # 4374
+ 2185, 7488, 739, 3642, 2715, 1296, 1290, 7489, 4115, 2198, 2199, 1921, 1563, 2595, 2551, 1870, # 4390
+ 2752, 2986, 7490, 435, 7491, 343, 1108, 596, 17, 1751, 4365, 2235, 3430, 3643, 7492, 4366, # 4406
+ 294, 3527, 2940, 1693, 477, 979, 281, 2041, 3528, 643, 2042, 3644, 2621, 2782, 2261, 1031, # 4422
+ 2335, 2134, 2298, 3529, 4367, 367, 1249, 2552, 7493, 3530, 7494, 4368, 1283, 3325, 2004, 240, # 4438
+ 1762, 3326, 4369, 4370, 836, 1069, 3128, 474, 7495, 2148, 2525, 268, 3531, 7496, 3188, 1521, # 4454
+ 1284, 7497, 1658, 1546, 4116, 7498, 3532, 3533, 7499, 4117, 3327, 2684, 1685, 4118, 961, 1673, # 4470
+ 2622, 190, 2005, 2200, 3762, 4371, 4372, 7500, 570, 2497, 3645, 1490, 7501, 4373, 2623, 3260, # 4486
+ 1956, 4374, 584, 1514, 396, 1045, 1944, 7502, 4375, 1967, 2444, 7503, 7504, 4376, 3910, 619, # 4502
+ 7505, 3129, 3261, 215, 2006, 2783, 2553, 3189, 4377, 3190, 4378, 763, 4119, 3763, 4379, 7506, # 4518
+ 7507, 1957, 1767, 2941, 3328, 3646, 1174, 452, 1477, 4380, 3329, 3130, 7508, 2825, 1253, 2382, # 4534
+ 2186, 1091, 2285, 4120, 492, 7509, 638, 1169, 1824, 2135, 1752, 3911, 648, 926, 1021, 1324, # 4550
+ 4381, 520, 4382, 997, 847, 1007, 892, 4383, 3764, 2262, 1871, 3647, 7510, 2400, 1784, 4384, # 4566
+ 1952, 2942, 3080, 3191, 1728, 4121, 2043, 3648, 4385, 2007, 1701, 3131, 1551, 30, 2263, 4122, # 4582
+ 7511, 2026, 4386, 3534, 7512, 501, 7513, 4123, 594, 3431, 2165, 1821, 3535, 3432, 3536, 3192, # 4598
+ 829, 2826, 4124, 7514, 1680, 3132, 1225, 4125, 7515, 3262, 4387, 4126, 3133, 2336, 7516, 4388, # 4614
+ 4127, 7517, 3912, 3913, 7518, 1847, 2383, 2596, 3330, 7519, 4389, 374, 3914, 652, 4128, 4129, # 4630
+ 375, 1140, 798, 7520, 7521, 7522, 2361, 4390, 2264, 546, 1659, 138, 3031, 2445, 4391, 7523, # 4646
+ 2250, 612, 1848, 910, 796, 3765, 1740, 1371, 825, 3766, 3767, 7524, 2906, 2554, 7525, 692, # 4662
+ 444, 3032, 2624, 801, 4392, 4130, 7526, 1491, 244, 1053, 3033, 4131, 4132, 340, 7527, 3915, # 4678
+ 1041, 2987, 293, 1168, 87, 1357, 7528, 1539, 959, 7529, 2236, 721, 694, 4133, 3768, 219, # 4694
+ 1478, 644, 1417, 3331, 2656, 1413, 1401, 1335, 1389, 3916, 7530, 7531, 2988, 2362, 3134, 1825, # 4710
+ 730, 1515, 184, 2827, 66, 4393, 7532, 1660, 2943, 246, 3332, 378, 1457, 226, 3433, 975, # 4726
+ 3917, 2944, 1264, 3537, 674, 696, 7533, 163, 7534, 1141, 2417, 2166, 713, 3538, 3333, 4394, # 4742
+ 3918, 7535, 7536, 1186, 15, 7537, 1079, 1070, 7538, 1522, 3193, 3539, 276, 1050, 2716, 758, # 4758
+ 1126, 653, 2945, 3263, 7539, 2337, 889, 3540, 3919, 3081, 2989, 903, 1250, 4395, 3920, 3434, # 4774
+ 3541, 1342, 1681, 1718, 766, 3264, 286, 89, 2946, 3649, 7540, 1713, 7541, 2597, 3334, 2990, # 4790
+ 7542, 2947, 2215, 3194, 2866, 7543, 4396, 2498, 2526, 181, 387, 1075, 3921, 731, 2187, 3335, # 4806
+ 7544, 3265, 310, 313, 3435, 2299, 770, 4134, 54, 3034, 189, 4397, 3082, 3769, 3922, 7545, # 4822
+ 1230, 1617, 1849, 355, 3542, 4135, 4398, 3336, 111, 4136, 3650, 1350, 3135, 3436, 3035, 4137, # 4838
+ 2149, 3266, 3543, 7546, 2784, 3923, 3924, 2991, 722, 2008, 7547, 1071, 247, 1207, 2338, 2471, # 4854
+ 1378, 4399, 2009, 864, 1437, 1214, 4400, 373, 3770, 1142, 2216, 667, 4401, 442, 2753, 2555, # 4870
+ 3771, 3925, 1968, 4138, 3267, 1839, 837, 170, 1107, 934, 1336, 1882, 7548, 7549, 2118, 4139, # 4886
+ 2828, 743, 1569, 7550, 4402, 4140, 582, 2384, 1418, 3437, 7551, 1802, 7552, 357, 1395, 1729, # 4902
+ 3651, 3268, 2418, 1564, 2237, 7553, 3083, 3772, 1633, 4403, 1114, 2085, 4141, 1532, 7554, 482, # 4918
+ 2446, 4404, 7555, 7556, 1492, 833, 1466, 7557, 2717, 3544, 1641, 2829, 7558, 1526, 1272, 3652, # 4934
+ 4142, 1686, 1794, 416, 2556, 1902, 1953, 1803, 7559, 3773, 2785, 3774, 1159, 2316, 7560, 2867, # 4950
+ 4405, 1610, 1584, 3036, 2419, 2754, 443, 3269, 1163, 3136, 7561, 7562, 3926, 7563, 4143, 2499, # 4966
+ 3037, 4406, 3927, 3137, 2103, 1647, 3545, 2010, 1872, 4144, 7564, 4145, 431, 3438, 7565, 250, # 4982
+ 97, 81, 4146, 7566, 1648, 1850, 1558, 160, 848, 7567, 866, 740, 1694, 7568, 2201, 2830, # 4998
+ 3195, 4147, 4407, 3653, 1687, 950, 2472, 426, 469, 3196, 3654, 3655, 3928, 7569, 7570, 1188, # 5014
+ 424, 1995, 861, 3546, 4148, 3775, 2202, 2685, 168, 1235, 3547, 4149, 7571, 2086, 1674, 4408, # 5030
+ 3337, 3270, 220, 2557, 1009, 7572, 3776, 670, 2992, 332, 1208, 717, 7573, 7574, 3548, 2447, # 5046
+ 3929, 3338, 7575, 513, 7576, 1209, 2868, 3339, 3138, 4409, 1080, 7577, 7578, 7579, 7580, 2527, # 5062
+ 3656, 3549, 815, 1587, 3930, 3931, 7581, 3550, 3439, 3777, 1254, 4410, 1328, 3038, 1390, 3932, # 5078
+ 1741, 3933, 3778, 3934, 7582, 236, 3779, 2448, 3271, 7583, 7584, 3657, 3780, 1273, 3781, 4411, # 5094
+ 7585, 308, 7586, 4412, 245, 4413, 1851, 2473, 1307, 2575, 430, 715, 2136, 2449, 7587, 270, # 5110
+ 199, 2869, 3935, 7588, 3551, 2718, 1753, 761, 1754, 725, 1661, 1840, 4414, 3440, 3658, 7589, # 5126
+ 7590, 587, 14, 3272, 227, 2598, 326, 480, 2265, 943, 2755, 3552, 291, 650, 1883, 7591, # 5142
+ 1702, 1226, 102, 1547, 62, 3441, 904, 4415, 3442, 1164, 4150, 7592, 7593, 1224, 1548, 2756, # 5158
+ 391, 498, 1493, 7594, 1386, 1419, 7595, 2055, 1177, 4416, 813, 880, 1081, 2363, 566, 1145, # 5174
+ 4417, 2286, 1001, 1035, 2558, 2599, 2238, 394, 1286, 7596, 7597, 2068, 7598, 86, 1494, 1730, # 5190
+ 3936, 491, 1588, 745, 897, 2948, 843, 3340, 3937, 2757, 2870, 3273, 1768, 998, 2217, 2069, # 5206
+ 397, 1826, 1195, 1969, 3659, 2993, 3341, 284, 7599, 3782, 2500, 2137, 2119, 1903, 7600, 3938, # 5222
+ 2150, 3939, 4151, 1036, 3443, 1904, 114, 2559, 4152, 209, 1527, 7601, 7602, 2949, 2831, 2625, # 5238
+ 2385, 2719, 3139, 812, 2560, 7603, 3274, 7604, 1559, 737, 1884, 3660, 1210, 885, 28, 2686, # 5254
+ 3553, 3783, 7605, 4153, 1004, 1779, 4418, 7606, 346, 1981, 2218, 2687, 4419, 3784, 1742, 797, # 5270
+ 1642, 3940, 1933, 1072, 1384, 2151, 896, 3941, 3275, 3661, 3197, 2871, 3554, 7607, 2561, 1958, # 5286
+ 4420, 2450, 1785, 7608, 7609, 7610, 3942, 4154, 1005, 1308, 3662, 4155, 2720, 4421, 4422, 1528, # 5302
+ 2600, 161, 1178, 4156, 1982, 987, 4423, 1101, 4157, 631, 3943, 1157, 3198, 2420, 1343, 1241, # 5318
+ 1016, 2239, 2562, 372, 877, 2339, 2501, 1160, 555, 1934, 911, 3944, 7611, 466, 1170, 169, # 5334
+ 1051, 2907, 2688, 3663, 2474, 2994, 1182, 2011, 2563, 1251, 2626, 7612, 992, 2340, 3444, 1540, # 5350
+ 2721, 1201, 2070, 2401, 1996, 2475, 7613, 4424, 528, 1922, 2188, 1503, 1873, 1570, 2364, 3342, # 5366
+ 3276, 7614, 557, 1073, 7615, 1827, 3445, 2087, 2266, 3140, 3039, 3084, 767, 3085, 2786, 4425, # 5382
+ 1006, 4158, 4426, 2341, 1267, 2176, 3664, 3199, 778, 3945, 3200, 2722, 1597, 2657, 7616, 4427, # 5398
+ 7617, 3446, 7618, 7619, 7620, 3277, 2689, 1433, 3278, 131, 95, 1504, 3946, 723, 4159, 3141, # 5414
+ 1841, 3555, 2758, 2189, 3947, 2027, 2104, 3665, 7621, 2995, 3948, 1218, 7622, 3343, 3201, 3949, # 5430
+ 4160, 2576, 248, 1634, 3785, 912, 7623, 2832, 3666, 3040, 3786, 654, 53, 7624, 2996, 7625, # 5446
+ 1688, 4428, 777, 3447, 1032, 3950, 1425, 7626, 191, 820, 2120, 2833, 971, 4429, 931, 3202, # 5462
+ 135, 664, 783, 3787, 1997, 772, 2908, 1935, 3951, 3788, 4430, 2909, 3203, 282, 2723, 640, # 5478
+ 1372, 3448, 1127, 922, 325, 3344, 7627, 7628, 711, 2044, 7629, 7630, 3952, 2219, 2787, 1936, # 5494
+ 3953, 3345, 2220, 2251, 3789, 2300, 7631, 4431, 3790, 1258, 3279, 3954, 3204, 2138, 2950, 3955, # 5510
+ 3956, 7632, 2221, 258, 3205, 4432, 101, 1227, 7633, 3280, 1755, 7634, 1391, 3281, 7635, 2910, # 5526
+ 2056, 893, 7636, 7637, 7638, 1402, 4161, 2342, 7639, 7640, 3206, 3556, 7641, 7642, 878, 1325, # 5542
+ 1780, 2788, 4433, 259, 1385, 2577, 744, 1183, 2267, 4434, 7643, 3957, 2502, 7644, 684, 1024, # 5558
+ 4162, 7645, 472, 3557, 3449, 1165, 3282, 3958, 3959, 322, 2152, 881, 455, 1695, 1152, 1340, # 5574
+ 660, 554, 2153, 4435, 1058, 4436, 4163, 830, 1065, 3346, 3960, 4437, 1923, 7646, 1703, 1918, # 5590
+ 7647, 932, 2268, 122, 7648, 4438, 947, 677, 7649, 3791, 2627, 297, 1905, 1924, 2269, 4439, # 5606
+ 2317, 3283, 7650, 7651, 4164, 7652, 4165, 84, 4166, 112, 989, 7653, 547, 1059, 3961, 701, # 5622
+ 3558, 1019, 7654, 4167, 7655, 3450, 942, 639, 457, 2301, 2451, 993, 2951, 407, 851, 494, # 5638
+ 4440, 3347, 927, 7656, 1237, 7657, 2421, 3348, 573, 4168, 680, 921, 2911, 1279, 1874, 285, # 5654
+ 790, 1448, 1983, 719, 2167, 7658, 7659, 4441, 3962, 3963, 1649, 7660, 1541, 563, 7661, 1077, # 5670
+ 7662, 3349, 3041, 3451, 511, 2997, 3964, 3965, 3667, 3966, 1268, 2564, 3350, 3207, 4442, 4443, # 5686
+ 7663, 535, 1048, 1276, 1189, 2912, 2028, 3142, 1438, 1373, 2834, 2952, 1134, 2012, 7664, 4169, # 5702
+ 1238, 2578, 3086, 1259, 7665, 700, 7666, 2953, 3143, 3668, 4170, 7667, 4171, 1146, 1875, 1906, # 5718
+ 4444, 2601, 3967, 781, 2422, 132, 1589, 203, 147, 273, 2789, 2402, 898, 1786, 2154, 3968, # 5734
+ 3969, 7668, 3792, 2790, 7669, 7670, 4445, 4446, 7671, 3208, 7672, 1635, 3793, 965, 7673, 1804, # 5750
+ 2690, 1516, 3559, 1121, 1082, 1329, 3284, 3970, 1449, 3794, 65, 1128, 2835, 2913, 2759, 1590, # 5766
+ 3795, 7674, 7675, 12, 2658, 45, 976, 2579, 3144, 4447, 517, 2528, 1013, 1037, 3209, 7676, # 5782
+ 3796, 2836, 7677, 3797, 7678, 3452, 7679, 2602, 614, 1998, 2318, 3798, 3087, 2724, 2628, 7680, # 5798
+ 2580, 4172, 599, 1269, 7681, 1810, 3669, 7682, 2691, 3088, 759, 1060, 489, 1805, 3351, 3285, # 5814
+ 1358, 7683, 7684, 2386, 1387, 1215, 2629, 2252, 490, 7685, 7686, 4173, 1759, 2387, 2343, 7687, # 5830
+ 4448, 3799, 1907, 3971, 2630, 1806, 3210, 4449, 3453, 3286, 2760, 2344, 874, 7688, 7689, 3454, # 5846
+ 3670, 1858, 91, 2914, 3671, 3042, 3800, 4450, 7690, 3145, 3972, 2659, 7691, 3455, 1202, 1403, # 5862
+ 3801, 2954, 2529, 1517, 2503, 4451, 3456, 2504, 7692, 4452, 7693, 2692, 1885, 1495, 1731, 3973, # 5878
+ 2365, 4453, 7694, 2029, 7695, 7696, 3974, 2693, 1216, 237, 2581, 4174, 2319, 3975, 3802, 4454, # 5894
+ 4455, 2694, 3560, 3457, 445, 4456, 7697, 7698, 7699, 7700, 2761, 61, 3976, 3672, 1822, 3977, # 5910
+ 7701, 687, 2045, 935, 925, 405, 2660, 703, 1096, 1859, 2725, 4457, 3978, 1876, 1367, 2695, # 5926
+ 3352, 918, 2105, 1781, 2476, 334, 3287, 1611, 1093, 4458, 564, 3146, 3458, 3673, 3353, 945, # 5942
+ 2631, 2057, 4459, 7702, 1925, 872, 4175, 7703, 3459, 2696, 3089, 349, 4176, 3674, 3979, 4460, # 5958
+ 3803, 4177, 3675, 2155, 3980, 4461, 4462, 4178, 4463, 2403, 2046, 782, 3981, 400, 251, 4179, # 5974
+ 1624, 7704, 7705, 277, 3676, 299, 1265, 476, 1191, 3804, 2121, 4180, 4181, 1109, 205, 7706, # 5990
+ 2582, 1000, 2156, 3561, 1860, 7707, 7708, 7709, 4464, 7710, 4465, 2565, 107, 2477, 2157, 3982, # 6006
+ 3460, 3147, 7711, 1533, 541, 1301, 158, 753, 4182, 2872, 3562, 7712, 1696, 370, 1088, 4183, # 6022
+ 4466, 3563, 579, 327, 440, 162, 2240, 269, 1937, 1374, 3461, 968, 3043, 56, 1396, 3090, # 6038
+ 2106, 3288, 3354, 7713, 1926, 2158, 4467, 2998, 7714, 3564, 7715, 7716, 3677, 4468, 2478, 7717, # 6054
+ 2791, 7718, 1650, 4469, 7719, 2603, 7720, 7721, 3983, 2661, 3355, 1149, 3356, 3984, 3805, 3985, # 6070
+ 7722, 1076, 49, 7723, 951, 3211, 3289, 3290, 450, 2837, 920, 7724, 1811, 2792, 2366, 4184, # 6086
+ 1908, 1138, 2367, 3806, 3462, 7725, 3212, 4470, 1909, 1147, 1518, 2423, 4471, 3807, 7726, 4472, # 6102
+ 2388, 2604, 260, 1795, 3213, 7727, 7728, 3808, 3291, 708, 7729, 3565, 1704, 7730, 3566, 1351, # 6118
+ 1618, 3357, 2999, 1886, 944, 4185, 3358, 4186, 3044, 3359, 4187, 7731, 3678, 422, 413, 1714, # 6134
+ 3292, 500, 2058, 2345, 4188, 2479, 7732, 1344, 1910, 954, 7733, 1668, 7734, 7735, 3986, 2404, # 6150
+ 4189, 3567, 3809, 4190, 7736, 2302, 1318, 2505, 3091, 133, 3092, 2873, 4473, 629, 31, 2838, # 6166
+ 2697, 3810, 4474, 850, 949, 4475, 3987, 2955, 1732, 2088, 4191, 1496, 1852, 7737, 3988, 620, # 6182
+ 3214, 981, 1242, 3679, 3360, 1619, 3680, 1643, 3293, 2139, 2452, 1970, 1719, 3463, 2168, 7738, # 6198
+ 3215, 7739, 7740, 3361, 1828, 7741, 1277, 4476, 1565, 2047, 7742, 1636, 3568, 3093, 7743, 869, # 6214
+ 2839, 655, 3811, 3812, 3094, 3989, 3000, 3813, 1310, 3569, 4477, 7744, 7745, 7746, 1733, 558, # 6230
+ 4478, 3681, 335, 1549, 3045, 1756, 4192, 3682, 1945, 3464, 1829, 1291, 1192, 470, 2726, 2107, # 6246
+ 2793, 913, 1054, 3990, 7747, 1027, 7748, 3046, 3991, 4479, 982, 2662, 3362, 3148, 3465, 3216, # 6262
+ 3217, 1946, 2794, 7749, 571, 4480, 7750, 1830, 7751, 3570, 2583, 1523, 2424, 7752, 2089, 984, # 6278
+ 4481, 3683, 1959, 7753, 3684, 852, 923, 2795, 3466, 3685, 969, 1519, 999, 2048, 2320, 1705, # 6294
+ 7754, 3095, 615, 1662, 151, 597, 3992, 2405, 2321, 1049, 275, 4482, 3686, 4193, 568, 3687, # 6310
+ 3571, 2480, 4194, 3688, 7755, 2425, 2270, 409, 3218, 7756, 1566, 2874, 3467, 1002, 769, 2840, # 6326
+ 194, 2090, 3149, 3689, 2222, 3294, 4195, 628, 1505, 7757, 7758, 1763, 2177, 3001, 3993, 521, # 6342
+ 1161, 2584, 1787, 2203, 2406, 4483, 3994, 1625, 4196, 4197, 412, 42, 3096, 464, 7759, 2632, # 6358
+ 4484, 3363, 1760, 1571, 2875, 3468, 2530, 1219, 2204, 3814, 2633, 2140, 2368, 4485, 4486, 3295, # 6374
+ 1651, 3364, 3572, 7760, 7761, 3573, 2481, 3469, 7762, 3690, 7763, 7764, 2271, 2091, 460, 7765, # 6390
+ 4487, 7766, 3002, 962, 588, 3574, 289, 3219, 2634, 1116, 52, 7767, 3047, 1796, 7768, 7769, # 6406
+ 7770, 1467, 7771, 1598, 1143, 3691, 4198, 1984, 1734, 1067, 4488, 1280, 3365, 465, 4489, 1572, # 6422
+ 510, 7772, 1927, 2241, 1812, 1644, 3575, 7773, 4490, 3692, 7774, 7775, 2663, 1573, 1534, 7776, # 6438
+ 7777, 4199, 536, 1807, 1761, 3470, 3815, 3150, 2635, 7778, 7779, 7780, 4491, 3471, 2915, 1911, # 6454
+ 2796, 7781, 3296, 1122, 377, 3220, 7782, 360, 7783, 7784, 4200, 1529, 551, 7785, 2059, 3693, # 6470
+ 1769, 2426, 7786, 2916, 4201, 3297, 3097, 2322, 2108, 2030, 4492, 1404, 136, 1468, 1479, 672, # 6486
+ 1171, 3221, 2303, 271, 3151, 7787, 2762, 7788, 2049, 678, 2727, 865, 1947, 4493, 7789, 2013, # 6502
+ 3995, 2956, 7790, 2728, 2223, 1397, 3048, 3694, 4494, 4495, 1735, 2917, 3366, 3576, 7791, 3816, # 6518
+ 509, 2841, 2453, 2876, 3817, 7792, 7793, 3152, 3153, 4496, 4202, 2531, 4497, 2304, 1166, 1010, # 6534
+ 552, 681, 1887, 7794, 7795, 2957, 2958, 3996, 1287, 1596, 1861, 3154, 358, 453, 736, 175, # 6550
+ 478, 1117, 905, 1167, 1097, 7796, 1853, 1530, 7797, 1706, 7798, 2178, 3472, 2287, 3695, 3473, # 6566
+ 3577, 4203, 2092, 4204, 7799, 3367, 1193, 2482, 4205, 1458, 2190, 2205, 1862, 1888, 1421, 3298, # 6582
+ 2918, 3049, 2179, 3474, 595, 2122, 7800, 3997, 7801, 7802, 4206, 1707, 2636, 223, 3696, 1359, # 6598
+ 751, 3098, 183, 3475, 7803, 2797, 3003, 419, 2369, 633, 704, 3818, 2389, 241, 7804, 7805, # 6614
+ 7806, 838, 3004, 3697, 2272, 2763, 2454, 3819, 1938, 2050, 3998, 1309, 3099, 2242, 1181, 7807, # 6630
+ 1136, 2206, 3820, 2370, 1446, 4207, 2305, 4498, 7808, 7809, 4208, 1055, 2605, 484, 3698, 7810, # 6646
+ 3999, 625, 4209, 2273, 3368, 1499, 4210, 4000, 7811, 4001, 4211, 3222, 2274, 2275, 3476, 7812, # 6662
+ 7813, 2764, 808, 2606, 3699, 3369, 4002, 4212, 3100, 2532, 526, 3370, 3821, 4213, 955, 7814, # 6678
+ 1620, 4214, 2637, 2427, 7815, 1429, 3700, 1669, 1831, 994, 928, 7816, 3578, 1260, 7817, 7818, # 6694
+ 7819, 1948, 2288, 741, 2919, 1626, 4215, 2729, 2455, 867, 1184, 362, 3371, 1392, 7820, 7821, # 6710
+ 4003, 4216, 1770, 1736, 3223, 2920, 4499, 4500, 1928, 2698, 1459, 1158, 7822, 3050, 3372, 2877, # 6726
+ 1292, 1929, 2506, 2842, 3701, 1985, 1187, 2071, 2014, 2607, 4217, 7823, 2566, 2507, 2169, 3702, # 6742
+ 2483, 3299, 7824, 3703, 4501, 7825, 7826, 666, 1003, 3005, 1022, 3579, 4218, 7827, 4502, 1813, # 6758
+ 2253, 574, 3822, 1603, 295, 1535, 705, 3823, 4219, 283, 858, 417, 7828, 7829, 3224, 4503, # 6774
+ 4504, 3051, 1220, 1889, 1046, 2276, 2456, 4004, 1393, 1599, 689, 2567, 388, 4220, 7830, 2484, # 6790
+ 802, 7831, 2798, 3824, 2060, 1405, 2254, 7832, 4505, 3825, 2109, 1052, 1345, 3225, 1585, 7833, # 6806
+ 809, 7834, 7835, 7836, 575, 2730, 3477, 956, 1552, 1469, 1144, 2323, 7837, 2324, 1560, 2457, # 6822
+ 3580, 3226, 4005, 616, 2207, 3155, 2180, 2289, 7838, 1832, 7839, 3478, 4506, 7840, 1319, 3704, # 6838
+ 3705, 1211, 3581, 1023, 3227, 1293, 2799, 7841, 7842, 7843, 3826, 607, 2306, 3827, 762, 2878, # 6854
+ 1439, 4221, 1360, 7844, 1485, 3052, 7845, 4507, 1038, 4222, 1450, 2061, 2638, 4223, 1379, 4508, # 6870
+ 2585, 7846, 7847, 4224, 1352, 1414, 2325, 2921, 1172, 7848, 7849, 3828, 3829, 7850, 1797, 1451, # 6886
+ 7851, 7852, 7853, 7854, 2922, 4006, 4007, 2485, 2346, 411, 4008, 4009, 3582, 3300, 3101, 4509, # 6902
+ 1561, 2664, 1452, 4010, 1375, 7855, 7856, 47, 2959, 316, 7857, 1406, 1591, 2923, 3156, 7858, # 6918
+ 1025, 2141, 3102, 3157, 354, 2731, 884, 2224, 4225, 2407, 508, 3706, 726, 3583, 996, 2428, # 6934
+ 3584, 729, 7859, 392, 2191, 1453, 4011, 4510, 3707, 7860, 7861, 2458, 3585, 2608, 1675, 2800, # 6950
+ 919, 2347, 2960, 2348, 1270, 4511, 4012, 73, 7862, 7863, 647, 7864, 3228, 2843, 2255, 1550, # 6966
+ 1346, 3006, 7865, 1332, 883, 3479, 7866, 7867, 7868, 7869, 3301, 2765, 7870, 1212, 831, 1347, # 6982
+ 4226, 4512, 2326, 3830, 1863, 3053, 720, 3831, 4513, 4514, 3832, 7871, 4227, 7872, 7873, 4515, # 6998
+ 7874, 7875, 1798, 4516, 3708, 2609, 4517, 3586, 1645, 2371, 7876, 7877, 2924, 669, 2208, 2665, # 7014
+ 2429, 7878, 2879, 7879, 7880, 1028, 3229, 7881, 4228, 2408, 7882, 2256, 1353, 7883, 7884, 4518, # 7030
+ 3158, 518, 7885, 4013, 7886, 4229, 1960, 7887, 2142, 4230, 7888, 7889, 3007, 2349, 2350, 3833, # 7046
+ 516, 1833, 1454, 4014, 2699, 4231, 4519, 2225, 2610, 1971, 1129, 3587, 7890, 2766, 7891, 2961, # 7062
+ 1422, 577, 1470, 3008, 1524, 3373, 7892, 7893, 432, 4232, 3054, 3480, 7894, 2586, 1455, 2508, # 7078
+ 2226, 1972, 1175, 7895, 1020, 2732, 4015, 3481, 4520, 7896, 2733, 7897, 1743, 1361, 3055, 3482, # 7094
+ 2639, 4016, 4233, 4521, 2290, 895, 924, 4234, 2170, 331, 2243, 3056, 166, 1627, 3057, 1098, # 7110
+ 7898, 1232, 2880, 2227, 3374, 4522, 657, 403, 1196, 2372, 542, 3709, 3375, 1600, 4235, 3483, # 7126
+ 7899, 4523, 2767, 3230, 576, 530, 1362, 7900, 4524, 2533, 2666, 3710, 4017, 7901, 842, 3834, # 7142
+ 7902, 2801, 2031, 1014, 4018, 213, 2700, 3376, 665, 621, 4236, 7903, 3711, 2925, 2430, 7904, # 7158
+ 2431, 3302, 3588, 3377, 7905, 4237, 2534, 4238, 4525, 3589, 1682, 4239, 3484, 1380, 7906, 724, # 7174
+ 2277, 600, 1670, 7907, 1337, 1233, 4526, 3103, 2244, 7908, 1621, 4527, 7909, 651, 4240, 7910, # 7190
+ 1612, 4241, 2611, 7911, 2844, 7912, 2734, 2307, 3058, 7913, 716, 2459, 3059, 174, 1255, 2701, # 7206
+ 4019, 3590, 548, 1320, 1398, 728, 4020, 1574, 7914, 1890, 1197, 3060, 4021, 7915, 3061, 3062, # 7222
+ 3712, 3591, 3713, 747, 7916, 635, 4242, 4528, 7917, 7918, 7919, 4243, 7920, 7921, 4529, 7922, # 7238
+ 3378, 4530, 2432, 451, 7923, 3714, 2535, 2072, 4244, 2735, 4245, 4022, 7924, 1764, 4531, 7925, # 7254
+ 4246, 350, 7926, 2278, 2390, 2486, 7927, 4247, 4023, 2245, 1434, 4024, 488, 4532, 458, 4248, # 7270
+ 4025, 3715, 771, 1330, 2391, 3835, 2568, 3159, 2159, 2409, 1553, 2667, 3160, 4249, 7928, 2487, # 7286
+ 2881, 2612, 1720, 2702, 4250, 3379, 4533, 7929, 2536, 4251, 7930, 3231, 4252, 2768, 7931, 2015, # 7302
+ 2736, 7932, 1155, 1017, 3716, 3836, 7933, 3303, 2308, 201, 1864, 4253, 1430, 7934, 4026, 7935, # 7318
+ 7936, 7937, 7938, 7939, 4254, 1604, 7940, 414, 1865, 371, 2587, 4534, 4535, 3485, 2016, 3104, # 7334
+ 4536, 1708, 960, 4255, 887, 389, 2171, 1536, 1663, 1721, 7941, 2228, 4027, 2351, 2926, 1580, # 7350
+ 7942, 7943, 7944, 1744, 7945, 2537, 4537, 4538, 7946, 4539, 7947, 2073, 7948, 7949, 3592, 3380, # 7366
+ 2882, 4256, 7950, 4257, 2640, 3381, 2802, 673, 2703, 2460, 709, 3486, 4028, 3593, 4258, 7951, # 7382
+ 1148, 502, 634, 7952, 7953, 1204, 4540, 3594, 1575, 4541, 2613, 3717, 7954, 3718, 3105, 948, # 7398
+ 3232, 121, 1745, 3837, 1110, 7955, 4259, 3063, 2509, 3009, 4029, 3719, 1151, 1771, 3838, 1488, # 7414
+ 4030, 1986, 7956, 2433, 3487, 7957, 7958, 2093, 7959, 4260, 3839, 1213, 1407, 2803, 531, 2737, # 7430
+ 2538, 3233, 1011, 1537, 7960, 2769, 4261, 3106, 1061, 7961, 3720, 3721, 1866, 2883, 7962, 2017, # 7446
+ 120, 4262, 4263, 2062, 3595, 3234, 2309, 3840, 2668, 3382, 1954, 4542, 7963, 7964, 3488, 1047, # 7462
+ 2704, 1266, 7965, 1368, 4543, 2845, 649, 3383, 3841, 2539, 2738, 1102, 2846, 2669, 7966, 7967, # 7478
+ 1999, 7968, 1111, 3596, 2962, 7969, 2488, 3842, 3597, 2804, 1854, 3384, 3722, 7970, 7971, 3385, # 7494
+ 2410, 2884, 3304, 3235, 3598, 7972, 2569, 7973, 3599, 2805, 4031, 1460, 856, 7974, 3600, 7975, # 7510
+ 2885, 2963, 7976, 2886, 3843, 7977, 4264, 632, 2510, 875, 3844, 1697, 3845, 2291, 7978, 7979, # 7526
+ 4544, 3010, 1239, 580, 4545, 4265, 7980, 914, 936, 2074, 1190, 4032, 1039, 2123, 7981, 7982, # 7542
+ 7983, 3386, 1473, 7984, 1354, 4266, 3846, 7985, 2172, 3064, 4033, 915, 3305, 4267, 4268, 3306, # 7558
+ 1605, 1834, 7986, 2739, 398, 3601, 4269, 3847, 4034, 328, 1912, 2847, 4035, 3848, 1331, 4270, # 7574
+ 3011, 937, 4271, 7987, 3602, 4036, 4037, 3387, 2160, 4546, 3388, 524, 742, 538, 3065, 1012, # 7590
+ 7988, 7989, 3849, 2461, 7990, 658, 1103, 225, 3850, 7991, 7992, 4547, 7993, 4548, 7994, 3236, # 7606
+ 1243, 7995, 4038, 963, 2246, 4549, 7996, 2705, 3603, 3161, 7997, 7998, 2588, 2327, 7999, 4550, # 7622
+ 8000, 8001, 8002, 3489, 3307, 957, 3389, 2540, 2032, 1930, 2927, 2462, 870, 2018, 3604, 1746, # 7638
+ 2770, 2771, 2434, 2463, 8003, 3851, 8004, 3723, 3107, 3724, 3490, 3390, 3725, 8005, 1179, 3066, # 7654
+ 8006, 3162, 2373, 4272, 3726, 2541, 3163, 3108, 2740, 4039, 8007, 3391, 1556, 2542, 2292, 977, # 7670
+ 2887, 2033, 4040, 1205, 3392, 8008, 1765, 3393, 3164, 2124, 1271, 1689, 714, 4551, 3491, 8009, # 7686
+ 2328, 3852, 533, 4273, 3605, 2181, 617, 8010, 2464, 3308, 3492, 2310, 8011, 8012, 3165, 8013, # 7702
+ 8014, 3853, 1987, 618, 427, 2641, 3493, 3394, 8015, 8016, 1244, 1690, 8017, 2806, 4274, 4552, # 7718
+ 8018, 3494, 8019, 8020, 2279, 1576, 473, 3606, 4275, 3395, 972, 8021, 3607, 8022, 3067, 8023, # 7734
+ 8024, 4553, 4554, 8025, 3727, 4041, 4042, 8026, 153, 4555, 356, 8027, 1891, 2888, 4276, 2143, # 7750
+ 408, 803, 2352, 8028, 3854, 8029, 4277, 1646, 2570, 2511, 4556, 4557, 3855, 8030, 3856, 4278, # 7766
+ 8031, 2411, 3396, 752, 8032, 8033, 1961, 2964, 8034, 746, 3012, 2465, 8035, 4279, 3728, 698, # 7782
+ 4558, 1892, 4280, 3608, 2543, 4559, 3609, 3857, 8036, 3166, 3397, 8037, 1823, 1302, 4043, 2706, # 7798
+ 3858, 1973, 4281, 8038, 4282, 3167, 823, 1303, 1288, 1236, 2848, 3495, 4044, 3398, 774, 3859, # 7814
+ 8039, 1581, 4560, 1304, 2849, 3860, 4561, 8040, 2435, 2161, 1083, 3237, 4283, 4045, 4284, 344, # 7830
+ 1173, 288, 2311, 454, 1683, 8041, 8042, 1461, 4562, 4046, 2589, 8043, 8044, 4563, 985, 894, # 7846
+ 8045, 3399, 3168, 8046, 1913, 2928, 3729, 1988, 8047, 2110, 1974, 8048, 4047, 8049, 2571, 1194, # 7862
+ 425, 8050, 4564, 3169, 1245, 3730, 4285, 8051, 8052, 2850, 8053, 636, 4565, 1855, 3861, 760, # 7878
+ 1799, 8054, 4286, 2209, 1508, 4566, 4048, 1893, 1684, 2293, 8055, 8056, 8057, 4287, 4288, 2210, # 7894
+ 479, 8058, 8059, 832, 8060, 4049, 2489, 8061, 2965, 2490, 3731, 990, 3109, 627, 1814, 2642, # 7910
+ 4289, 1582, 4290, 2125, 2111, 3496, 4567, 8062, 799, 4291, 3170, 8063, 4568, 2112, 1737, 3013, # 7926
+ 1018, 543, 754, 4292, 3309, 1676, 4569, 4570, 4050, 8064, 1489, 8065, 3497, 8066, 2614, 2889, # 7942
+ 4051, 8067, 8068, 2966, 8069, 8070, 8071, 8072, 3171, 4571, 4572, 2182, 1722, 8073, 3238, 3239, # 7958
+ 1842, 3610, 1715, 481, 365, 1975, 1856, 8074, 8075, 1962, 2491, 4573, 8076, 2126, 3611, 3240, # 7974
+ 433, 1894, 2063, 2075, 8077, 602, 2741, 8078, 8079, 8080, 8081, 8082, 3014, 1628, 3400, 8083, # 7990
+ 3172, 4574, 4052, 2890, 4575, 2512, 8084, 2544, 2772, 8085, 8086, 8087, 3310, 4576, 2891, 8088, # 8006
+ 4577, 8089, 2851, 4578, 4579, 1221, 2967, 4053, 2513, 8090, 8091, 8092, 1867, 1989, 8093, 8094, # 8022
+ 8095, 1895, 8096, 8097, 4580, 1896, 4054, 318, 8098, 2094, 4055, 4293, 8099, 8100, 485, 8101, # 8038
+ 938, 3862, 553, 2670, 116, 8102, 3863, 3612, 8103, 3498, 2671, 2773, 3401, 3311, 2807, 8104, # 8054
+ 3613, 2929, 4056, 1747, 2930, 2968, 8105, 8106, 207, 8107, 8108, 2672, 4581, 2514, 8109, 3015, # 8070
+ 890, 3614, 3864, 8110, 1877, 3732, 3402, 8111, 2183, 2353, 3403, 1652, 8112, 8113, 8114, 941, # 8086
+ 2294, 208, 3499, 4057, 2019, 330, 4294, 3865, 2892, 2492, 3733, 4295, 8115, 8116, 8117, 8118, # 8102
+)
+# fmt: on
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/gb2312prober.py b/env-llmeval/lib/python3.10/site-packages/chardet/gb2312prober.py
new file mode 100644
index 0000000000000000000000000000000000000000..d423e7311e2fbd9a014de808c107e96ad11c66e5
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/gb2312prober.py
@@ -0,0 +1,47 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from .chardistribution import GB2312DistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import GB2312_SM_MODEL
+
+
+class GB2312Prober(MultiByteCharSetProber):
+ def __init__(self) -> None:
+ super().__init__()
+ self.coding_sm = CodingStateMachine(GB2312_SM_MODEL)
+ self.distribution_analyzer = GB2312DistributionAnalysis()
+ self.reset()
+
+ @property
+ def charset_name(self) -> str:
+ return "GB2312"
+
+ @property
+ def language(self) -> str:
+ return "Chinese"
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/hebrewprober.py b/env-llmeval/lib/python3.10/site-packages/chardet/hebrewprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..785d0057bcc0ea74a4b8d65ab7a0de78474bf892
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/hebrewprober.py
@@ -0,0 +1,316 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Shy Shalom
+# Portions created by the Initial Developer are Copyright (C) 2005
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Optional, Union
+
+from .charsetprober import CharSetProber
+from .enums import ProbingState
+from .sbcharsetprober import SingleByteCharSetProber
+
+# This prober doesn't actually recognize a language or a charset.
+# It is a helper prober for the use of the Hebrew model probers
+
+### General ideas of the Hebrew charset recognition ###
+#
+# Four main charsets exist in Hebrew:
+# "ISO-8859-8" - Visual Hebrew
+# "windows-1255" - Logical Hebrew
+# "ISO-8859-8-I" - Logical Hebrew
+# "x-mac-hebrew" - ?? Logical Hebrew ??
+#
+# Both "ISO" charsets use a completely identical set of code points, whereas
+# "windows-1255" and "x-mac-hebrew" are two different proper supersets of
+# these code points. windows-1255 defines additional characters in the range
+# 0x80-0x9F as some misc punctuation marks as well as some Hebrew-specific
+# diacritics and additional 'Yiddish' ligature letters in the range 0xc0-0xd6.
+# x-mac-hebrew defines similar additional code points but with a different
+# mapping.
+#
+# As far as an average Hebrew text with no diacritics is concerned, all four
+# charsets are identical with respect to code points. Meaning that for the
+# main Hebrew alphabet, all four map the same values to all 27 Hebrew letters
+# (including final letters).
+#
+# The dominant difference between these charsets is their directionality.
+# "Visual" directionality means that the text is ordered as if the renderer is
+# not aware of a BIDI rendering algorithm. The renderer sees the text and
+# draws it from left to right. The text itself when ordered naturally is read
+# backwards. A buffer of Visual Hebrew generally looks like so:
+# "[last word of first line spelled backwards] [whole line ordered backwards
+# and spelled backwards] [first word of first line spelled backwards]
+# [end of line] [last word of second line] ... etc' "
+# adding punctuation marks, numbers and English text to visual text is
+# naturally also "visual" and from left to right.
+#
+# "Logical" directionality means the text is ordered "naturally" according to
+# the order it is read. It is the responsibility of the renderer to display
+# the text from right to left. A BIDI algorithm is used to place general
+# punctuation marks, numbers and English text in the text.
+#
+# Texts in x-mac-hebrew are almost impossible to find on the Internet. From
+# what little evidence I could find, it seems that its general directionality
+# is Logical.
+#
+# To sum up all of the above, the Hebrew probing mechanism knows about two
+# charsets:
+# Visual Hebrew - "ISO-8859-8" - backwards text - Words and sentences are
+# backwards while line order is natural. For charset recognition purposes
+# the line order is unimportant (In fact, for this implementation, even
+# word order is unimportant).
+# Logical Hebrew - "windows-1255" - normal, naturally ordered text.
+#
+# "ISO-8859-8-I" is a subset of windows-1255 and doesn't need to be
+# specifically identified.
+# "x-mac-hebrew" is also identified as windows-1255. A text in x-mac-hebrew
+# that contain special punctuation marks or diacritics is displayed with
+# some unconverted characters showing as question marks. This problem might
+# be corrected using another model prober for x-mac-hebrew. Due to the fact
+# that x-mac-hebrew texts are so rare, writing another model prober isn't
+# worth the effort and performance hit.
+#
+#### The Prober ####
+#
+# The prober is divided between two SBCharSetProbers and a HebrewProber,
+# all of which are managed, created, fed data, inquired and deleted by the
+# SBCSGroupProber. The two SBCharSetProbers identify that the text is in
+# fact some kind of Hebrew, Logical or Visual. The final decision about which
+# one is it is made by the HebrewProber by combining final-letter scores
+# with the scores of the two SBCharSetProbers to produce a final answer.
+#
+# The SBCSGroupProber is responsible for stripping the original text of HTML
+# tags, English characters, numbers, low-ASCII punctuation characters, spaces
+# and new lines. It reduces any sequence of such characters to a single space.
+# The buffer fed to each prober in the SBCS group prober is pure text in
+# high-ASCII.
+# The two SBCharSetProbers (model probers) share the same language model:
+# Win1255Model.
+# The first SBCharSetProber uses the model normally as any other
+# SBCharSetProber does, to recognize windows-1255, upon which this model was
+# built. The second SBCharSetProber is told to make the pair-of-letter
+# lookup in the language model backwards. This in practice exactly simulates
+# a visual Hebrew model using the windows-1255 logical Hebrew model.
+#
+# The HebrewProber is not using any language model. All it does is look for
+# final-letter evidence suggesting the text is either logical Hebrew or visual
+# Hebrew. Disjointed from the model probers, the results of the HebrewProber
+# alone are meaningless. HebrewProber always returns 0.00 as confidence
+# since it never identifies a charset by itself. Instead, the pointer to the
+# HebrewProber is passed to the model probers as a helper "Name Prober".
+# When the Group prober receives a positive identification from any prober,
+# it asks for the name of the charset identified. If the prober queried is a
+# Hebrew model prober, the model prober forwards the call to the
+# HebrewProber to make the final decision. In the HebrewProber, the
+# decision is made according to the final-letters scores maintained and Both
+# model probers scores. The answer is returned in the form of the name of the
+# charset identified, either "windows-1255" or "ISO-8859-8".
+
+
+class HebrewProber(CharSetProber):
+ SPACE = 0x20
+ # windows-1255 / ISO-8859-8 code points of interest
+ FINAL_KAF = 0xEA
+ NORMAL_KAF = 0xEB
+ FINAL_MEM = 0xED
+ NORMAL_MEM = 0xEE
+ FINAL_NUN = 0xEF
+ NORMAL_NUN = 0xF0
+ FINAL_PE = 0xF3
+ NORMAL_PE = 0xF4
+ FINAL_TSADI = 0xF5
+ NORMAL_TSADI = 0xF6
+
+ # Minimum Visual vs Logical final letter score difference.
+ # If the difference is below this, don't rely solely on the final letter score
+ # distance.
+ MIN_FINAL_CHAR_DISTANCE = 5
+
+ # Minimum Visual vs Logical model score difference.
+ # If the difference is below this, don't rely at all on the model score
+ # distance.
+ MIN_MODEL_DISTANCE = 0.01
+
+ VISUAL_HEBREW_NAME = "ISO-8859-8"
+ LOGICAL_HEBREW_NAME = "windows-1255"
+
+ def __init__(self) -> None:
+ super().__init__()
+ self._final_char_logical_score = 0
+ self._final_char_visual_score = 0
+ self._prev = self.SPACE
+ self._before_prev = self.SPACE
+ self._logical_prober: Optional[SingleByteCharSetProber] = None
+ self._visual_prober: Optional[SingleByteCharSetProber] = None
+ self.reset()
+
+ def reset(self) -> None:
+ self._final_char_logical_score = 0
+ self._final_char_visual_score = 0
+ # The two last characters seen in the previous buffer,
+ # mPrev and mBeforePrev are initialized to space in order to simulate
+ # a word delimiter at the beginning of the data
+ self._prev = self.SPACE
+ self._before_prev = self.SPACE
+ # These probers are owned by the group prober.
+
+ def set_model_probers(
+ self,
+ logical_prober: SingleByteCharSetProber,
+ visual_prober: SingleByteCharSetProber,
+ ) -> None:
+ self._logical_prober = logical_prober
+ self._visual_prober = visual_prober
+
+ def is_final(self, c: int) -> bool:
+ return c in [
+ self.FINAL_KAF,
+ self.FINAL_MEM,
+ self.FINAL_NUN,
+ self.FINAL_PE,
+ self.FINAL_TSADI,
+ ]
+
+ def is_non_final(self, c: int) -> bool:
+ # The normal Tsadi is not a good Non-Final letter due to words like
+ # 'lechotet' (to chat) containing an apostrophe after the tsadi. This
+ # apostrophe is converted to a space in FilterWithoutEnglishLetters
+ # causing the Non-Final tsadi to appear at an end of a word even
+ # though this is not the case in the original text.
+ # The letters Pe and Kaf rarely display a related behavior of not being
+ # a good Non-Final letter. Words like 'Pop', 'Winamp' and 'Mubarak'
+ # for example legally end with a Non-Final Pe or Kaf. However, the
+ # benefit of these letters as Non-Final letters outweighs the damage
+ # since these words are quite rare.
+ return c in [self.NORMAL_KAF, self.NORMAL_MEM, self.NORMAL_NUN, self.NORMAL_PE]
+
+ def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+ # Final letter analysis for logical-visual decision.
+ # Look for evidence that the received buffer is either logical Hebrew
+ # or visual Hebrew.
+ # The following cases are checked:
+ # 1) A word longer than 1 letter, ending with a final letter. This is
+ # an indication that the text is laid out "naturally" since the
+ # final letter really appears at the end. +1 for logical score.
+ # 2) A word longer than 1 letter, ending with a Non-Final letter. In
+ # normal Hebrew, words ending with Kaf, Mem, Nun, Pe or Tsadi,
+ # should not end with the Non-Final form of that letter. Exceptions
+ # to this rule are mentioned above in isNonFinal(). This is an
+ # indication that the text is laid out backwards. +1 for visual
+ # score
+ # 3) A word longer than 1 letter, starting with a final letter. Final
+ # letters should not appear at the beginning of a word. This is an
+ # indication that the text is laid out backwards. +1 for visual
+ # score.
+ #
+ # The visual score and logical score are accumulated throughout the
+ # text and are finally checked against each other in GetCharSetName().
+ # No checking for final letters in the middle of words is done since
+ # that case is not an indication for either Logical or Visual text.
+ #
+ # We automatically filter out all 7-bit characters (replace them with
+ # spaces) so the word boundary detection works properly. [MAP]
+
+ if self.state == ProbingState.NOT_ME:
+ # Both model probers say it's not them. No reason to continue.
+ return ProbingState.NOT_ME
+
+ byte_str = self.filter_high_byte_only(byte_str)
+
+ for cur in byte_str:
+ if cur == self.SPACE:
+ # We stand on a space - a word just ended
+ if self._before_prev != self.SPACE:
+ # next-to-last char was not a space so self._prev is not a
+ # 1 letter word
+ if self.is_final(self._prev):
+ # case (1) [-2:not space][-1:final letter][cur:space]
+ self._final_char_logical_score += 1
+ elif self.is_non_final(self._prev):
+ # case (2) [-2:not space][-1:Non-Final letter][
+ # cur:space]
+ self._final_char_visual_score += 1
+ else:
+ # Not standing on a space
+ if (
+ (self._before_prev == self.SPACE)
+ and (self.is_final(self._prev))
+ and (cur != self.SPACE)
+ ):
+ # case (3) [-2:space][-1:final letter][cur:not space]
+ self._final_char_visual_score += 1
+ self._before_prev = self._prev
+ self._prev = cur
+
+ # Forever detecting, till the end or until both model probers return
+ # ProbingState.NOT_ME (handled above)
+ return ProbingState.DETECTING
+
+ @property
+ def charset_name(self) -> str:
+ assert self._logical_prober is not None
+ assert self._visual_prober is not None
+
+ # Make the decision: is it Logical or Visual?
+ # If the final letter score distance is dominant enough, rely on it.
+ finalsub = self._final_char_logical_score - self._final_char_visual_score
+ if finalsub >= self.MIN_FINAL_CHAR_DISTANCE:
+ return self.LOGICAL_HEBREW_NAME
+ if finalsub <= -self.MIN_FINAL_CHAR_DISTANCE:
+ return self.VISUAL_HEBREW_NAME
+
+ # It's not dominant enough, try to rely on the model scores instead.
+ modelsub = (
+ self._logical_prober.get_confidence() - self._visual_prober.get_confidence()
+ )
+ if modelsub > self.MIN_MODEL_DISTANCE:
+ return self.LOGICAL_HEBREW_NAME
+ if modelsub < -self.MIN_MODEL_DISTANCE:
+ return self.VISUAL_HEBREW_NAME
+
+ # Still no good, back to final letter distance, maybe it'll save the
+ # day.
+ if finalsub < 0.0:
+ return self.VISUAL_HEBREW_NAME
+
+ # (finalsub > 0 - Logical) or (don't know what to do) default to
+ # Logical.
+ return self.LOGICAL_HEBREW_NAME
+
+ @property
+ def language(self) -> str:
+ return "Hebrew"
+
+ @property
+ def state(self) -> ProbingState:
+ assert self._logical_prober is not None
+ assert self._visual_prober is not None
+
+ # Remain active as long as any of the model probers are active.
+ if (self._logical_prober.state == ProbingState.NOT_ME) and (
+ self._visual_prober.state == ProbingState.NOT_ME
+ ):
+ return ProbingState.NOT_ME
+ return ProbingState.DETECTING
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/johabfreq.py b/env-llmeval/lib/python3.10/site-packages/chardet/johabfreq.py
new file mode 100644
index 0000000000000000000000000000000000000000..c12969990d73388f61a6ab98fb4ee8f0f5cbc44f
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/johabfreq.py
@@ -0,0 +1,2382 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+# The frequency data itself is the same as euc-kr.
+# This is just a mapping table to euc-kr.
+
+JOHAB_TO_EUCKR_ORDER_TABLE = {
+ 0x8861: 0,
+ 0x8862: 1,
+ 0x8865: 2,
+ 0x8868: 3,
+ 0x8869: 4,
+ 0x886A: 5,
+ 0x886B: 6,
+ 0x8871: 7,
+ 0x8873: 8,
+ 0x8874: 9,
+ 0x8875: 10,
+ 0x8876: 11,
+ 0x8877: 12,
+ 0x8878: 13,
+ 0x8879: 14,
+ 0x887B: 15,
+ 0x887C: 16,
+ 0x887D: 17,
+ 0x8881: 18,
+ 0x8882: 19,
+ 0x8885: 20,
+ 0x8889: 21,
+ 0x8891: 22,
+ 0x8893: 23,
+ 0x8895: 24,
+ 0x8896: 25,
+ 0x8897: 26,
+ 0x88A1: 27,
+ 0x88A2: 28,
+ 0x88A5: 29,
+ 0x88A9: 30,
+ 0x88B5: 31,
+ 0x88B7: 32,
+ 0x88C1: 33,
+ 0x88C5: 34,
+ 0x88C9: 35,
+ 0x88E1: 36,
+ 0x88E2: 37,
+ 0x88E5: 38,
+ 0x88E8: 39,
+ 0x88E9: 40,
+ 0x88EB: 41,
+ 0x88F1: 42,
+ 0x88F3: 43,
+ 0x88F5: 44,
+ 0x88F6: 45,
+ 0x88F7: 46,
+ 0x88F8: 47,
+ 0x88FB: 48,
+ 0x88FC: 49,
+ 0x88FD: 50,
+ 0x8941: 51,
+ 0x8945: 52,
+ 0x8949: 53,
+ 0x8951: 54,
+ 0x8953: 55,
+ 0x8955: 56,
+ 0x8956: 57,
+ 0x8957: 58,
+ 0x8961: 59,
+ 0x8962: 60,
+ 0x8963: 61,
+ 0x8965: 62,
+ 0x8968: 63,
+ 0x8969: 64,
+ 0x8971: 65,
+ 0x8973: 66,
+ 0x8975: 67,
+ 0x8976: 68,
+ 0x8977: 69,
+ 0x897B: 70,
+ 0x8981: 71,
+ 0x8985: 72,
+ 0x8989: 73,
+ 0x8993: 74,
+ 0x8995: 75,
+ 0x89A1: 76,
+ 0x89A2: 77,
+ 0x89A5: 78,
+ 0x89A8: 79,
+ 0x89A9: 80,
+ 0x89AB: 81,
+ 0x89AD: 82,
+ 0x89B0: 83,
+ 0x89B1: 84,
+ 0x89B3: 85,
+ 0x89B5: 86,
+ 0x89B7: 87,
+ 0x89B8: 88,
+ 0x89C1: 89,
+ 0x89C2: 90,
+ 0x89C5: 91,
+ 0x89C9: 92,
+ 0x89CB: 93,
+ 0x89D1: 94,
+ 0x89D3: 95,
+ 0x89D5: 96,
+ 0x89D7: 97,
+ 0x89E1: 98,
+ 0x89E5: 99,
+ 0x89E9: 100,
+ 0x89F3: 101,
+ 0x89F6: 102,
+ 0x89F7: 103,
+ 0x8A41: 104,
+ 0x8A42: 105,
+ 0x8A45: 106,
+ 0x8A49: 107,
+ 0x8A51: 108,
+ 0x8A53: 109,
+ 0x8A55: 110,
+ 0x8A57: 111,
+ 0x8A61: 112,
+ 0x8A65: 113,
+ 0x8A69: 114,
+ 0x8A73: 115,
+ 0x8A75: 116,
+ 0x8A81: 117,
+ 0x8A82: 118,
+ 0x8A85: 119,
+ 0x8A88: 120,
+ 0x8A89: 121,
+ 0x8A8A: 122,
+ 0x8A8B: 123,
+ 0x8A90: 124,
+ 0x8A91: 125,
+ 0x8A93: 126,
+ 0x8A95: 127,
+ 0x8A97: 128,
+ 0x8A98: 129,
+ 0x8AA1: 130,
+ 0x8AA2: 131,
+ 0x8AA5: 132,
+ 0x8AA9: 133,
+ 0x8AB6: 134,
+ 0x8AB7: 135,
+ 0x8AC1: 136,
+ 0x8AD5: 137,
+ 0x8AE1: 138,
+ 0x8AE2: 139,
+ 0x8AE5: 140,
+ 0x8AE9: 141,
+ 0x8AF1: 142,
+ 0x8AF3: 143,
+ 0x8AF5: 144,
+ 0x8B41: 145,
+ 0x8B45: 146,
+ 0x8B49: 147,
+ 0x8B61: 148,
+ 0x8B62: 149,
+ 0x8B65: 150,
+ 0x8B68: 151,
+ 0x8B69: 152,
+ 0x8B6A: 153,
+ 0x8B71: 154,
+ 0x8B73: 155,
+ 0x8B75: 156,
+ 0x8B77: 157,
+ 0x8B81: 158,
+ 0x8BA1: 159,
+ 0x8BA2: 160,
+ 0x8BA5: 161,
+ 0x8BA8: 162,
+ 0x8BA9: 163,
+ 0x8BAB: 164,
+ 0x8BB1: 165,
+ 0x8BB3: 166,
+ 0x8BB5: 167,
+ 0x8BB7: 168,
+ 0x8BB8: 169,
+ 0x8BBC: 170,
+ 0x8C61: 171,
+ 0x8C62: 172,
+ 0x8C63: 173,
+ 0x8C65: 174,
+ 0x8C69: 175,
+ 0x8C6B: 176,
+ 0x8C71: 177,
+ 0x8C73: 178,
+ 0x8C75: 179,
+ 0x8C76: 180,
+ 0x8C77: 181,
+ 0x8C7B: 182,
+ 0x8C81: 183,
+ 0x8C82: 184,
+ 0x8C85: 185,
+ 0x8C89: 186,
+ 0x8C91: 187,
+ 0x8C93: 188,
+ 0x8C95: 189,
+ 0x8C96: 190,
+ 0x8C97: 191,
+ 0x8CA1: 192,
+ 0x8CA2: 193,
+ 0x8CA9: 194,
+ 0x8CE1: 195,
+ 0x8CE2: 196,
+ 0x8CE3: 197,
+ 0x8CE5: 198,
+ 0x8CE9: 199,
+ 0x8CF1: 200,
+ 0x8CF3: 201,
+ 0x8CF5: 202,
+ 0x8CF6: 203,
+ 0x8CF7: 204,
+ 0x8D41: 205,
+ 0x8D42: 206,
+ 0x8D45: 207,
+ 0x8D51: 208,
+ 0x8D55: 209,
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+ 0xBC62: 1697,
+ 0xBC65: 1698,
+ 0xBC67: 1699,
+ 0xBC69: 1700,
+ 0xBC6C: 1701,
+ 0xBC71: 1702,
+ 0xBC73: 1703,
+ 0xBC75: 1704,
+ 0xBC76: 1705,
+ 0xBC77: 1706,
+ 0xBC81: 1707,
+ 0xBC82: 1708,
+ 0xBC85: 1709,
+ 0xBC89: 1710,
+ 0xBC91: 1711,
+ 0xBC93: 1712,
+ 0xBC95: 1713,
+ 0xBC96: 1714,
+ 0xBC97: 1715,
+ 0xBCA1: 1716,
+ 0xBCA5: 1717,
+ 0xBCB7: 1718,
+ 0xBCE1: 1719,
+ 0xBCE2: 1720,
+ 0xBCE5: 1721,
+ 0xBCE9: 1722,
+ 0xBCF1: 1723,
+ 0xBCF3: 1724,
+ 0xBCF5: 1725,
+ 0xBCF6: 1726,
+ 0xBCF7: 1727,
+ 0xBD41: 1728,
+ 0xBD57: 1729,
+ 0xBD61: 1730,
+ 0xBD76: 1731,
+ 0xBDA1: 1732,
+ 0xBDA2: 1733,
+ 0xBDA5: 1734,
+ 0xBDA9: 1735,
+ 0xBDB1: 1736,
+ 0xBDB3: 1737,
+ 0xBDB5: 1738,
+ 0xBDB7: 1739,
+ 0xBDB9: 1740,
+ 0xBDC1: 1741,
+ 0xBDC2: 1742,
+ 0xBDC9: 1743,
+ 0xBDD6: 1744,
+ 0xBDE1: 1745,
+ 0xBDF6: 1746,
+ 0xBE41: 1747,
+ 0xBE45: 1748,
+ 0xBE49: 1749,
+ 0xBE51: 1750,
+ 0xBE53: 1751,
+ 0xBE77: 1752,
+ 0xBE81: 1753,
+ 0xBE82: 1754,
+ 0xBE85: 1755,
+ 0xBE89: 1756,
+ 0xBE91: 1757,
+ 0xBE93: 1758,
+ 0xBE97: 1759,
+ 0xBEA1: 1760,
+ 0xBEB6: 1761,
+ 0xBEB7: 1762,
+ 0xBEE1: 1763,
+ 0xBF41: 1764,
+ 0xBF61: 1765,
+ 0xBF71: 1766,
+ 0xBF75: 1767,
+ 0xBF77: 1768,
+ 0xBFA1: 1769,
+ 0xBFA2: 1770,
+ 0xBFA5: 1771,
+ 0xBFA9: 1772,
+ 0xBFB1: 1773,
+ 0xBFB3: 1774,
+ 0xBFB7: 1775,
+ 0xBFB8: 1776,
+ 0xBFBD: 1777,
+ 0xC061: 1778,
+ 0xC062: 1779,
+ 0xC065: 1780,
+ 0xC067: 1781,
+ 0xC069: 1782,
+ 0xC071: 1783,
+ 0xC073: 1784,
+ 0xC075: 1785,
+ 0xC076: 1786,
+ 0xC077: 1787,
+ 0xC078: 1788,
+ 0xC081: 1789,
+ 0xC082: 1790,
+ 0xC085: 1791,
+ 0xC089: 1792,
+ 0xC091: 1793,
+ 0xC093: 1794,
+ 0xC095: 1795,
+ 0xC096: 1796,
+ 0xC097: 1797,
+ 0xC0A1: 1798,
+ 0xC0A5: 1799,
+ 0xC0A7: 1800,
+ 0xC0A9: 1801,
+ 0xC0B1: 1802,
+ 0xC0B7: 1803,
+ 0xC0E1: 1804,
+ 0xC0E2: 1805,
+ 0xC0E5: 1806,
+ 0xC0E9: 1807,
+ 0xC0F1: 1808,
+ 0xC0F3: 1809,
+ 0xC0F5: 1810,
+ 0xC0F6: 1811,
+ 0xC0F7: 1812,
+ 0xC141: 1813,
+ 0xC142: 1814,
+ 0xC145: 1815,
+ 0xC149: 1816,
+ 0xC151: 1817,
+ 0xC153: 1818,
+ 0xC155: 1819,
+ 0xC157: 1820,
+ 0xC161: 1821,
+ 0xC165: 1822,
+ 0xC176: 1823,
+ 0xC181: 1824,
+ 0xC185: 1825,
+ 0xC197: 1826,
+ 0xC1A1: 1827,
+ 0xC1A2: 1828,
+ 0xC1A5: 1829,
+ 0xC1A9: 1830,
+ 0xC1B1: 1831,
+ 0xC1B3: 1832,
+ 0xC1B5: 1833,
+ 0xC1B7: 1834,
+ 0xC1C1: 1835,
+ 0xC1C5: 1836,
+ 0xC1C9: 1837,
+ 0xC1D7: 1838,
+ 0xC241: 1839,
+ 0xC245: 1840,
+ 0xC249: 1841,
+ 0xC251: 1842,
+ 0xC253: 1843,
+ 0xC255: 1844,
+ 0xC257: 1845,
+ 0xC261: 1846,
+ 0xC271: 1847,
+ 0xC281: 1848,
+ 0xC282: 1849,
+ 0xC285: 1850,
+ 0xC289: 1851,
+ 0xC291: 1852,
+ 0xC293: 1853,
+ 0xC295: 1854,
+ 0xC297: 1855,
+ 0xC2A1: 1856,
+ 0xC2B6: 1857,
+ 0xC2C1: 1858,
+ 0xC2C5: 1859,
+ 0xC2E1: 1860,
+ 0xC2E5: 1861,
+ 0xC2E9: 1862,
+ 0xC2F1: 1863,
+ 0xC2F3: 1864,
+ 0xC2F5: 1865,
+ 0xC2F7: 1866,
+ 0xC341: 1867,
+ 0xC345: 1868,
+ 0xC349: 1869,
+ 0xC351: 1870,
+ 0xC357: 1871,
+ 0xC361: 1872,
+ 0xC362: 1873,
+ 0xC365: 1874,
+ 0xC369: 1875,
+ 0xC371: 1876,
+ 0xC373: 1877,
+ 0xC375: 1878,
+ 0xC377: 1879,
+ 0xC3A1: 1880,
+ 0xC3A2: 1881,
+ 0xC3A5: 1882,
+ 0xC3A8: 1883,
+ 0xC3A9: 1884,
+ 0xC3AA: 1885,
+ 0xC3B1: 1886,
+ 0xC3B3: 1887,
+ 0xC3B5: 1888,
+ 0xC3B7: 1889,
+ 0xC461: 1890,
+ 0xC462: 1891,
+ 0xC465: 1892,
+ 0xC469: 1893,
+ 0xC471: 1894,
+ 0xC473: 1895,
+ 0xC475: 1896,
+ 0xC477: 1897,
+ 0xC481: 1898,
+ 0xC482: 1899,
+ 0xC485: 1900,
+ 0xC489: 1901,
+ 0xC491: 1902,
+ 0xC493: 1903,
+ 0xC495: 1904,
+ 0xC496: 1905,
+ 0xC497: 1906,
+ 0xC4A1: 1907,
+ 0xC4A2: 1908,
+ 0xC4B7: 1909,
+ 0xC4E1: 1910,
+ 0xC4E2: 1911,
+ 0xC4E5: 1912,
+ 0xC4E8: 1913,
+ 0xC4E9: 1914,
+ 0xC4F1: 1915,
+ 0xC4F3: 1916,
+ 0xC4F5: 1917,
+ 0xC4F6: 1918,
+ 0xC4F7: 1919,
+ 0xC541: 1920,
+ 0xC542: 1921,
+ 0xC545: 1922,
+ 0xC549: 1923,
+ 0xC551: 1924,
+ 0xC553: 1925,
+ 0xC555: 1926,
+ 0xC557: 1927,
+ 0xC561: 1928,
+ 0xC565: 1929,
+ 0xC569: 1930,
+ 0xC571: 1931,
+ 0xC573: 1932,
+ 0xC575: 1933,
+ 0xC576: 1934,
+ 0xC577: 1935,
+ 0xC581: 1936,
+ 0xC5A1: 1937,
+ 0xC5A2: 1938,
+ 0xC5A5: 1939,
+ 0xC5A9: 1940,
+ 0xC5B1: 1941,
+ 0xC5B3: 1942,
+ 0xC5B5: 1943,
+ 0xC5B7: 1944,
+ 0xC5C1: 1945,
+ 0xC5C2: 1946,
+ 0xC5C5: 1947,
+ 0xC5C9: 1948,
+ 0xC5D1: 1949,
+ 0xC5D7: 1950,
+ 0xC5E1: 1951,
+ 0xC5F7: 1952,
+ 0xC641: 1953,
+ 0xC649: 1954,
+ 0xC661: 1955,
+ 0xC681: 1956,
+ 0xC682: 1957,
+ 0xC685: 1958,
+ 0xC689: 1959,
+ 0xC691: 1960,
+ 0xC693: 1961,
+ 0xC695: 1962,
+ 0xC697: 1963,
+ 0xC6A1: 1964,
+ 0xC6A5: 1965,
+ 0xC6A9: 1966,
+ 0xC6B7: 1967,
+ 0xC6C1: 1968,
+ 0xC6D7: 1969,
+ 0xC6E1: 1970,
+ 0xC6E2: 1971,
+ 0xC6E5: 1972,
+ 0xC6E9: 1973,
+ 0xC6F1: 1974,
+ 0xC6F3: 1975,
+ 0xC6F5: 1976,
+ 0xC6F7: 1977,
+ 0xC741: 1978,
+ 0xC745: 1979,
+ 0xC749: 1980,
+ 0xC751: 1981,
+ 0xC761: 1982,
+ 0xC762: 1983,
+ 0xC765: 1984,
+ 0xC769: 1985,
+ 0xC771: 1986,
+ 0xC773: 1987,
+ 0xC777: 1988,
+ 0xC7A1: 1989,
+ 0xC7A2: 1990,
+ 0xC7A5: 1991,
+ 0xC7A9: 1992,
+ 0xC7B1: 1993,
+ 0xC7B3: 1994,
+ 0xC7B5: 1995,
+ 0xC7B7: 1996,
+ 0xC861: 1997,
+ 0xC862: 1998,
+ 0xC865: 1999,
+ 0xC869: 2000,
+ 0xC86A: 2001,
+ 0xC871: 2002,
+ 0xC873: 2003,
+ 0xC875: 2004,
+ 0xC876: 2005,
+ 0xC877: 2006,
+ 0xC881: 2007,
+ 0xC882: 2008,
+ 0xC885: 2009,
+ 0xC889: 2010,
+ 0xC891: 2011,
+ 0xC893: 2012,
+ 0xC895: 2013,
+ 0xC896: 2014,
+ 0xC897: 2015,
+ 0xC8A1: 2016,
+ 0xC8B7: 2017,
+ 0xC8E1: 2018,
+ 0xC8E2: 2019,
+ 0xC8E5: 2020,
+ 0xC8E9: 2021,
+ 0xC8EB: 2022,
+ 0xC8F1: 2023,
+ 0xC8F3: 2024,
+ 0xC8F5: 2025,
+ 0xC8F6: 2026,
+ 0xC8F7: 2027,
+ 0xC941: 2028,
+ 0xC942: 2029,
+ 0xC945: 2030,
+ 0xC949: 2031,
+ 0xC951: 2032,
+ 0xC953: 2033,
+ 0xC955: 2034,
+ 0xC957: 2035,
+ 0xC961: 2036,
+ 0xC965: 2037,
+ 0xC976: 2038,
+ 0xC981: 2039,
+ 0xC985: 2040,
+ 0xC9A1: 2041,
+ 0xC9A2: 2042,
+ 0xC9A5: 2043,
+ 0xC9A9: 2044,
+ 0xC9B1: 2045,
+ 0xC9B3: 2046,
+ 0xC9B5: 2047,
+ 0xC9B7: 2048,
+ 0xC9BC: 2049,
+ 0xC9C1: 2050,
+ 0xC9C5: 2051,
+ 0xC9E1: 2052,
+ 0xCA41: 2053,
+ 0xCA45: 2054,
+ 0xCA55: 2055,
+ 0xCA57: 2056,
+ 0xCA61: 2057,
+ 0xCA81: 2058,
+ 0xCA82: 2059,
+ 0xCA85: 2060,
+ 0xCA89: 2061,
+ 0xCA91: 2062,
+ 0xCA93: 2063,
+ 0xCA95: 2064,
+ 0xCA97: 2065,
+ 0xCAA1: 2066,
+ 0xCAB6: 2067,
+ 0xCAC1: 2068,
+ 0xCAE1: 2069,
+ 0xCAE2: 2070,
+ 0xCAE5: 2071,
+ 0xCAE9: 2072,
+ 0xCAF1: 2073,
+ 0xCAF3: 2074,
+ 0xCAF7: 2075,
+ 0xCB41: 2076,
+ 0xCB45: 2077,
+ 0xCB49: 2078,
+ 0xCB51: 2079,
+ 0xCB57: 2080,
+ 0xCB61: 2081,
+ 0xCB62: 2082,
+ 0xCB65: 2083,
+ 0xCB68: 2084,
+ 0xCB69: 2085,
+ 0xCB6B: 2086,
+ 0xCB71: 2087,
+ 0xCB73: 2088,
+ 0xCB75: 2089,
+ 0xCB81: 2090,
+ 0xCB85: 2091,
+ 0xCB89: 2092,
+ 0xCB91: 2093,
+ 0xCB93: 2094,
+ 0xCBA1: 2095,
+ 0xCBA2: 2096,
+ 0xCBA5: 2097,
+ 0xCBA9: 2098,
+ 0xCBB1: 2099,
+ 0xCBB3: 2100,
+ 0xCBB5: 2101,
+ 0xCBB7: 2102,
+ 0xCC61: 2103,
+ 0xCC62: 2104,
+ 0xCC63: 2105,
+ 0xCC65: 2106,
+ 0xCC69: 2107,
+ 0xCC6B: 2108,
+ 0xCC71: 2109,
+ 0xCC73: 2110,
+ 0xCC75: 2111,
+ 0xCC76: 2112,
+ 0xCC77: 2113,
+ 0xCC7B: 2114,
+ 0xCC81: 2115,
+ 0xCC82: 2116,
+ 0xCC85: 2117,
+ 0xCC89: 2118,
+ 0xCC91: 2119,
+ 0xCC93: 2120,
+ 0xCC95: 2121,
+ 0xCC96: 2122,
+ 0xCC97: 2123,
+ 0xCCA1: 2124,
+ 0xCCA2: 2125,
+ 0xCCE1: 2126,
+ 0xCCE2: 2127,
+ 0xCCE5: 2128,
+ 0xCCE9: 2129,
+ 0xCCF1: 2130,
+ 0xCCF3: 2131,
+ 0xCCF5: 2132,
+ 0xCCF6: 2133,
+ 0xCCF7: 2134,
+ 0xCD41: 2135,
+ 0xCD42: 2136,
+ 0xCD45: 2137,
+ 0xCD49: 2138,
+ 0xCD51: 2139,
+ 0xCD53: 2140,
+ 0xCD55: 2141,
+ 0xCD57: 2142,
+ 0xCD61: 2143,
+ 0xCD65: 2144,
+ 0xCD69: 2145,
+ 0xCD71: 2146,
+ 0xCD73: 2147,
+ 0xCD76: 2148,
+ 0xCD77: 2149,
+ 0xCD81: 2150,
+ 0xCD89: 2151,
+ 0xCD93: 2152,
+ 0xCD95: 2153,
+ 0xCDA1: 2154,
+ 0xCDA2: 2155,
+ 0xCDA5: 2156,
+ 0xCDA9: 2157,
+ 0xCDB1: 2158,
+ 0xCDB3: 2159,
+ 0xCDB5: 2160,
+ 0xCDB7: 2161,
+ 0xCDC1: 2162,
+ 0xCDD7: 2163,
+ 0xCE41: 2164,
+ 0xCE45: 2165,
+ 0xCE61: 2166,
+ 0xCE65: 2167,
+ 0xCE69: 2168,
+ 0xCE73: 2169,
+ 0xCE75: 2170,
+ 0xCE81: 2171,
+ 0xCE82: 2172,
+ 0xCE85: 2173,
+ 0xCE88: 2174,
+ 0xCE89: 2175,
+ 0xCE8B: 2176,
+ 0xCE91: 2177,
+ 0xCE93: 2178,
+ 0xCE95: 2179,
+ 0xCE97: 2180,
+ 0xCEA1: 2181,
+ 0xCEB7: 2182,
+ 0xCEE1: 2183,
+ 0xCEE5: 2184,
+ 0xCEE9: 2185,
+ 0xCEF1: 2186,
+ 0xCEF5: 2187,
+ 0xCF41: 2188,
+ 0xCF45: 2189,
+ 0xCF49: 2190,
+ 0xCF51: 2191,
+ 0xCF55: 2192,
+ 0xCF57: 2193,
+ 0xCF61: 2194,
+ 0xCF65: 2195,
+ 0xCF69: 2196,
+ 0xCF71: 2197,
+ 0xCF73: 2198,
+ 0xCF75: 2199,
+ 0xCFA1: 2200,
+ 0xCFA2: 2201,
+ 0xCFA5: 2202,
+ 0xCFA9: 2203,
+ 0xCFB1: 2204,
+ 0xCFB3: 2205,
+ 0xCFB5: 2206,
+ 0xCFB7: 2207,
+ 0xD061: 2208,
+ 0xD062: 2209,
+ 0xD065: 2210,
+ 0xD069: 2211,
+ 0xD06E: 2212,
+ 0xD071: 2213,
+ 0xD073: 2214,
+ 0xD075: 2215,
+ 0xD077: 2216,
+ 0xD081: 2217,
+ 0xD082: 2218,
+ 0xD085: 2219,
+ 0xD089: 2220,
+ 0xD091: 2221,
+ 0xD093: 2222,
+ 0xD095: 2223,
+ 0xD096: 2224,
+ 0xD097: 2225,
+ 0xD0A1: 2226,
+ 0xD0B7: 2227,
+ 0xD0E1: 2228,
+ 0xD0E2: 2229,
+ 0xD0E5: 2230,
+ 0xD0E9: 2231,
+ 0xD0EB: 2232,
+ 0xD0F1: 2233,
+ 0xD0F3: 2234,
+ 0xD0F5: 2235,
+ 0xD0F7: 2236,
+ 0xD141: 2237,
+ 0xD142: 2238,
+ 0xD145: 2239,
+ 0xD149: 2240,
+ 0xD151: 2241,
+ 0xD153: 2242,
+ 0xD155: 2243,
+ 0xD157: 2244,
+ 0xD161: 2245,
+ 0xD162: 2246,
+ 0xD165: 2247,
+ 0xD169: 2248,
+ 0xD171: 2249,
+ 0xD173: 2250,
+ 0xD175: 2251,
+ 0xD176: 2252,
+ 0xD177: 2253,
+ 0xD181: 2254,
+ 0xD185: 2255,
+ 0xD189: 2256,
+ 0xD193: 2257,
+ 0xD1A1: 2258,
+ 0xD1A2: 2259,
+ 0xD1A5: 2260,
+ 0xD1A9: 2261,
+ 0xD1AE: 2262,
+ 0xD1B1: 2263,
+ 0xD1B3: 2264,
+ 0xD1B5: 2265,
+ 0xD1B7: 2266,
+ 0xD1BB: 2267,
+ 0xD1C1: 2268,
+ 0xD1C2: 2269,
+ 0xD1C5: 2270,
+ 0xD1C9: 2271,
+ 0xD1D5: 2272,
+ 0xD1D7: 2273,
+ 0xD1E1: 2274,
+ 0xD1E2: 2275,
+ 0xD1E5: 2276,
+ 0xD1F5: 2277,
+ 0xD1F7: 2278,
+ 0xD241: 2279,
+ 0xD242: 2280,
+ 0xD245: 2281,
+ 0xD249: 2282,
+ 0xD253: 2283,
+ 0xD255: 2284,
+ 0xD257: 2285,
+ 0xD261: 2286,
+ 0xD265: 2287,
+ 0xD269: 2288,
+ 0xD273: 2289,
+ 0xD275: 2290,
+ 0xD281: 2291,
+ 0xD282: 2292,
+ 0xD285: 2293,
+ 0xD289: 2294,
+ 0xD28E: 2295,
+ 0xD291: 2296,
+ 0xD295: 2297,
+ 0xD297: 2298,
+ 0xD2A1: 2299,
+ 0xD2A5: 2300,
+ 0xD2A9: 2301,
+ 0xD2B1: 2302,
+ 0xD2B7: 2303,
+ 0xD2C1: 2304,
+ 0xD2C2: 2305,
+ 0xD2C5: 2306,
+ 0xD2C9: 2307,
+ 0xD2D7: 2308,
+ 0xD2E1: 2309,
+ 0xD2E2: 2310,
+ 0xD2E5: 2311,
+ 0xD2E9: 2312,
+ 0xD2F1: 2313,
+ 0xD2F3: 2314,
+ 0xD2F5: 2315,
+ 0xD2F7: 2316,
+ 0xD341: 2317,
+ 0xD342: 2318,
+ 0xD345: 2319,
+ 0xD349: 2320,
+ 0xD351: 2321,
+ 0xD355: 2322,
+ 0xD357: 2323,
+ 0xD361: 2324,
+ 0xD362: 2325,
+ 0xD365: 2326,
+ 0xD367: 2327,
+ 0xD368: 2328,
+ 0xD369: 2329,
+ 0xD36A: 2330,
+ 0xD371: 2331,
+ 0xD373: 2332,
+ 0xD375: 2333,
+ 0xD377: 2334,
+ 0xD37B: 2335,
+ 0xD381: 2336,
+ 0xD385: 2337,
+ 0xD389: 2338,
+ 0xD391: 2339,
+ 0xD393: 2340,
+ 0xD397: 2341,
+ 0xD3A1: 2342,
+ 0xD3A2: 2343,
+ 0xD3A5: 2344,
+ 0xD3A9: 2345,
+ 0xD3B1: 2346,
+ 0xD3B3: 2347,
+ 0xD3B5: 2348,
+ 0xD3B7: 2349,
+}
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/johabprober.py b/env-llmeval/lib/python3.10/site-packages/chardet/johabprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..d7364ba61eca930aa1c868abe3b322cceb995a6b
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/johabprober.py
@@ -0,0 +1,47 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from .chardistribution import JOHABDistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import JOHAB_SM_MODEL
+
+
+class JOHABProber(MultiByteCharSetProber):
+ def __init__(self) -> None:
+ super().__init__()
+ self.coding_sm = CodingStateMachine(JOHAB_SM_MODEL)
+ self.distribution_analyzer = JOHABDistributionAnalysis()
+ self.reset()
+
+ @property
+ def charset_name(self) -> str:
+ return "Johab"
+
+ @property
+ def language(self) -> str:
+ return "Korean"
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/jpcntx.py b/env-llmeval/lib/python3.10/site-packages/chardet/jpcntx.py
new file mode 100644
index 0000000000000000000000000000000000000000..2f53bdda09e92da38e31cac1a6d415f4670137f7
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/jpcntx.py
@@ -0,0 +1,238 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from typing import List, Tuple, Union
+
+# This is hiragana 2-char sequence table, the number in each cell represents its frequency category
+# fmt: off
+jp2_char_context = (
+ (0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1),
+ (2, 4, 0, 4, 0, 3, 0, 4, 0, 3, 4, 4, 4, 2, 4, 3, 3, 4, 3, 2, 3, 3, 4, 2, 3, 3, 3, 2, 4, 1, 4, 3, 3, 1, 5, 4, 3, 4, 3, 4, 3, 5, 3, 0, 3, 5, 4, 2, 0, 3, 1, 0, 3, 3, 0, 3, 3, 0, 1, 1, 0, 4, 3, 0, 3, 3, 0, 4, 0, 2, 0, 3, 5, 5, 5, 5, 4, 0, 4, 1, 0, 3, 4),
+ (0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2),
+ (0, 4, 0, 5, 0, 5, 0, 4, 0, 4, 5, 4, 4, 3, 5, 3, 5, 1, 5, 3, 4, 3, 4, 4, 3, 4, 3, 3, 4, 3, 5, 4, 4, 3, 5, 5, 3, 5, 5, 5, 3, 5, 5, 3, 4, 5, 5, 3, 1, 3, 2, 0, 3, 4, 0, 4, 2, 0, 4, 2, 1, 5, 3, 2, 3, 5, 0, 4, 0, 2, 0, 5, 4, 4, 5, 4, 5, 0, 4, 0, 0, 4, 4),
+ (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
+ (0, 3, 0, 4, 0, 3, 0, 3, 0, 4, 5, 4, 3, 3, 3, 3, 4, 3, 5, 4, 4, 3, 5, 4, 4, 3, 4, 3, 4, 4, 4, 4, 5, 3, 4, 4, 3, 4, 5, 5, 4, 5, 5, 1, 4, 5, 4, 3, 0, 3, 3, 1, 3, 3, 0, 4, 4, 0, 3, 3, 1, 5, 3, 3, 3, 5, 0, 4, 0, 3, 0, 4, 4, 3, 4, 3, 3, 0, 4, 1, 1, 3, 4),
+ (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
+ (0, 4, 0, 3, 0, 3, 0, 4, 0, 3, 4, 4, 3, 2, 2, 1, 2, 1, 3, 1, 3, 3, 3, 3, 3, 4, 3, 1, 3, 3, 5, 3, 3, 0, 4, 3, 0, 5, 4, 3, 3, 5, 4, 4, 3, 4, 4, 5, 0, 1, 2, 0, 1, 2, 0, 2, 2, 0, 1, 0, 0, 5, 2, 2, 1, 4, 0, 3, 0, 1, 0, 4, 4, 3, 5, 4, 3, 0, 2, 1, 0, 4, 3),
+ (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
+ (0, 3, 0, 5, 0, 4, 0, 2, 1, 4, 4, 2, 4, 1, 4, 2, 4, 2, 4, 3, 3, 3, 4, 3, 3, 3, 3, 1, 4, 2, 3, 3, 3, 1, 4, 4, 1, 1, 1, 4, 3, 3, 2, 0, 2, 4, 3, 2, 0, 3, 3, 0, 3, 1, 1, 0, 0, 0, 3, 3, 0, 4, 2, 2, 3, 4, 0, 4, 0, 3, 0, 4, 4, 5, 3, 4, 4, 0, 3, 0, 0, 1, 4),
+ (1, 4, 0, 4, 0, 4, 0, 4, 0, 3, 5, 4, 4, 3, 4, 3, 5, 4, 3, 3, 4, 3, 5, 4, 4, 4, 4, 3, 4, 2, 4, 3, 3, 1, 5, 4, 3, 2, 4, 5, 4, 5, 5, 4, 4, 5, 4, 4, 0, 3, 2, 2, 3, 3, 0, 4, 3, 1, 3, 2, 1, 4, 3, 3, 4, 5, 0, 3, 0, 2, 0, 4, 5, 5, 4, 5, 4, 0, 4, 0, 0, 5, 4),
+ (0, 5, 0, 5, 0, 4, 0, 3, 0, 4, 4, 3, 4, 3, 3, 3, 4, 0, 4, 4, 4, 3, 4, 3, 4, 3, 3, 1, 4, 2, 4, 3, 4, 0, 5, 4, 1, 4, 5, 4, 4, 5, 3, 2, 4, 3, 4, 3, 2, 4, 1, 3, 3, 3, 2, 3, 2, 0, 4, 3, 3, 4, 3, 3, 3, 4, 0, 4, 0, 3, 0, 4, 5, 4, 4, 4, 3, 0, 4, 1, 0, 1, 3),
+ (0, 3, 1, 4, 0, 3, 0, 2, 0, 3, 4, 4, 3, 1, 4, 2, 3, 3, 4, 3, 4, 3, 4, 3, 4, 4, 3, 2, 3, 1, 5, 4, 4, 1, 4, 4, 3, 5, 4, 4, 3, 5, 5, 4, 3, 4, 4, 3, 1, 2, 3, 1, 2, 2, 0, 3, 2, 0, 3, 1, 0, 5, 3, 3, 3, 4, 3, 3, 3, 3, 4, 4, 4, 4, 5, 4, 2, 0, 3, 3, 2, 4, 3),
+ (0, 2, 0, 3, 0, 1, 0, 1, 0, 0, 3, 2, 0, 0, 2, 0, 1, 0, 2, 1, 3, 3, 3, 1, 2, 3, 1, 0, 1, 0, 4, 2, 1, 1, 3, 3, 0, 4, 3, 3, 1, 4, 3, 3, 0, 3, 3, 2, 0, 0, 0, 0, 1, 0, 0, 2, 0, 0, 0, 0, 0, 4, 1, 0, 2, 3, 2, 2, 2, 1, 3, 3, 3, 4, 4, 3, 2, 0, 3, 1, 0, 3, 3),
+ (0, 4, 0, 4, 0, 3, 0, 3, 0, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 3, 4, 2, 4, 3, 4, 3, 3, 2, 4, 3, 4, 5, 4, 1, 4, 5, 3, 5, 4, 5, 3, 5, 4, 0, 3, 5, 5, 3, 1, 3, 3, 2, 2, 3, 0, 3, 4, 1, 3, 3, 2, 4, 3, 3, 3, 4, 0, 4, 0, 3, 0, 4, 5, 4, 4, 5, 3, 0, 4, 1, 0, 3, 4),
+ (0, 2, 0, 3, 0, 3, 0, 0, 0, 2, 2, 2, 1, 0, 1, 0, 0, 0, 3, 0, 3, 0, 3, 0, 1, 3, 1, 0, 3, 1, 3, 3, 3, 1, 3, 3, 3, 0, 1, 3, 1, 3, 4, 0, 0, 3, 1, 1, 0, 3, 2, 0, 0, 0, 0, 1, 3, 0, 1, 0, 0, 3, 3, 2, 0, 3, 0, 0, 0, 0, 0, 3, 4, 3, 4, 3, 3, 0, 3, 0, 0, 2, 3),
+ (2, 3, 0, 3, 0, 2, 0, 1, 0, 3, 3, 4, 3, 1, 3, 1, 1, 1, 3, 1, 4, 3, 4, 3, 3, 3, 0, 0, 3, 1, 5, 4, 3, 1, 4, 3, 2, 5, 5, 4, 4, 4, 4, 3, 3, 4, 4, 4, 0, 2, 1, 1, 3, 2, 0, 1, 2, 0, 0, 1, 0, 4, 1, 3, 3, 3, 0, 3, 0, 1, 0, 4, 4, 4, 5, 5, 3, 0, 2, 0, 0, 4, 4),
+ (0, 2, 0, 1, 0, 3, 1, 3, 0, 2, 3, 3, 3, 0, 3, 1, 0, 0, 3, 0, 3, 2, 3, 1, 3, 2, 1, 1, 0, 0, 4, 2, 1, 0, 2, 3, 1, 4, 3, 2, 0, 4, 4, 3, 1, 3, 1, 3, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 4, 1, 1, 1, 2, 0, 3, 0, 0, 0, 3, 4, 2, 4, 3, 2, 0, 1, 0, 0, 3, 3),
+ (0, 1, 0, 4, 0, 5, 0, 4, 0, 2, 4, 4, 2, 3, 3, 2, 3, 3, 5, 3, 3, 3, 4, 3, 4, 2, 3, 0, 4, 3, 3, 3, 4, 1, 4, 3, 2, 1, 5, 5, 3, 4, 5, 1, 3, 5, 4, 2, 0, 3, 3, 0, 1, 3, 0, 4, 2, 0, 1, 3, 1, 4, 3, 3, 3, 3, 0, 3, 0, 1, 0, 3, 4, 4, 4, 5, 5, 0, 3, 0, 1, 4, 5),
+ (0, 2, 0, 3, 0, 3, 0, 0, 0, 2, 3, 1, 3, 0, 4, 0, 1, 1, 3, 0, 3, 4, 3, 2, 3, 1, 0, 3, 3, 2, 3, 1, 3, 0, 2, 3, 0, 2, 1, 4, 1, 2, 2, 0, 0, 3, 3, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 0, 2, 2, 0, 3, 2, 1, 3, 3, 0, 2, 0, 2, 0, 0, 3, 3, 1, 2, 4, 0, 3, 0, 2, 2, 3),
+ (2, 4, 0, 5, 0, 4, 0, 4, 0, 2, 4, 4, 4, 3, 4, 3, 3, 3, 1, 2, 4, 3, 4, 3, 4, 4, 5, 0, 3, 3, 3, 3, 2, 0, 4, 3, 1, 4, 3, 4, 1, 4, 4, 3, 3, 4, 4, 3, 1, 2, 3, 0, 4, 2, 0, 4, 1, 0, 3, 3, 0, 4, 3, 3, 3, 4, 0, 4, 0, 2, 0, 3, 5, 3, 4, 5, 2, 0, 3, 0, 0, 4, 5),
+ (0, 3, 0, 4, 0, 1, 0, 1, 0, 1, 3, 2, 2, 1, 3, 0, 3, 0, 2, 0, 2, 0, 3, 0, 2, 0, 0, 0, 1, 0, 1, 1, 0, 0, 3, 1, 0, 0, 0, 4, 0, 3, 1, 0, 2, 1, 3, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 4, 2, 2, 3, 1, 0, 3, 0, 0, 0, 1, 4, 4, 4, 3, 0, 0, 4, 0, 0, 1, 4),
+ (1, 4, 1, 5, 0, 3, 0, 3, 0, 4, 5, 4, 4, 3, 5, 3, 3, 4, 4, 3, 4, 1, 3, 3, 3, 3, 2, 1, 4, 1, 5, 4, 3, 1, 4, 4, 3, 5, 4, 4, 3, 5, 4, 3, 3, 4, 4, 4, 0, 3, 3, 1, 2, 3, 0, 3, 1, 0, 3, 3, 0, 5, 4, 4, 4, 4, 4, 4, 3, 3, 5, 4, 4, 3, 3, 5, 4, 0, 3, 2, 0, 4, 4),
+ (0, 2, 0, 3, 0, 1, 0, 0, 0, 1, 3, 3, 3, 2, 4, 1, 3, 0, 3, 1, 3, 0, 2, 2, 1, 1, 0, 0, 2, 0, 4, 3, 1, 0, 4, 3, 0, 4, 4, 4, 1, 4, 3, 1, 1, 3, 3, 1, 0, 2, 0, 0, 1, 3, 0, 0, 0, 0, 2, 0, 0, 4, 3, 2, 4, 3, 5, 4, 3, 3, 3, 4, 3, 3, 4, 3, 3, 0, 2, 1, 0, 3, 3),
+ (0, 2, 0, 4, 0, 3, 0, 2, 0, 2, 5, 5, 3, 4, 4, 4, 4, 1, 4, 3, 3, 0, 4, 3, 4, 3, 1, 3, 3, 2, 4, 3, 0, 3, 4, 3, 0, 3, 4, 4, 2, 4, 4, 0, 4, 5, 3, 3, 2, 2, 1, 1, 1, 2, 0, 1, 5, 0, 3, 3, 2, 4, 3, 3, 3, 4, 0, 3, 0, 2, 0, 4, 4, 3, 5, 5, 0, 0, 3, 0, 2, 3, 3),
+ (0, 3, 0, 4, 0, 3, 0, 1, 0, 3, 4, 3, 3, 1, 3, 3, 3, 0, 3, 1, 3, 0, 4, 3, 3, 1, 1, 0, 3, 0, 3, 3, 0, 0, 4, 4, 0, 1, 5, 4, 3, 3, 5, 0, 3, 3, 4, 3, 0, 2, 0, 1, 1, 1, 0, 1, 3, 0, 1, 2, 1, 3, 3, 2, 3, 3, 0, 3, 0, 1, 0, 1, 3, 3, 4, 4, 1, 0, 1, 2, 2, 1, 3),
+ (0, 1, 0, 4, 0, 4, 0, 3, 0, 1, 3, 3, 3, 2, 3, 1, 1, 0, 3, 0, 3, 3, 4, 3, 2, 4, 2, 0, 1, 0, 4, 3, 2, 0, 4, 3, 0, 5, 3, 3, 2, 4, 4, 4, 3, 3, 3, 4, 0, 1, 3, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 4, 2, 3, 3, 3, 0, 3, 0, 0, 0, 4, 4, 4, 5, 3, 2, 0, 3, 3, 0, 3, 5),
+ (0, 2, 0, 3, 0, 0, 0, 3, 0, 1, 3, 0, 2, 0, 0, 0, 1, 0, 3, 1, 1, 3, 3, 0, 0, 3, 0, 0, 3, 0, 2, 3, 1, 0, 3, 1, 0, 3, 3, 2, 0, 4, 2, 2, 0, 2, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 2, 0, 1, 0, 1, 0, 0, 0, 1, 3, 1, 2, 0, 0, 0, 1, 0, 0, 1, 4),
+ (0, 3, 0, 3, 0, 5, 0, 1, 0, 2, 4, 3, 1, 3, 3, 2, 1, 1, 5, 2, 1, 0, 5, 1, 2, 0, 0, 0, 3, 3, 2, 2, 3, 2, 4, 3, 0, 0, 3, 3, 1, 3, 3, 0, 2, 5, 3, 4, 0, 3, 3, 0, 1, 2, 0, 2, 2, 0, 3, 2, 0, 2, 2, 3, 3, 3, 0, 2, 0, 1, 0, 3, 4, 4, 2, 5, 4, 0, 3, 0, 0, 3, 5),
+ (0, 3, 0, 3, 0, 3, 0, 1, 0, 3, 3, 3, 3, 0, 3, 0, 2, 0, 2, 1, 1, 0, 2, 0, 1, 0, 0, 0, 2, 1, 0, 0, 1, 0, 3, 2, 0, 0, 3, 3, 1, 2, 3, 1, 0, 3, 3, 0, 0, 1, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 2, 3, 1, 2, 3, 0, 3, 0, 1, 0, 3, 2, 1, 0, 4, 3, 0, 1, 1, 0, 3, 3),
+ (0, 4, 0, 5, 0, 3, 0, 3, 0, 4, 5, 5, 4, 3, 5, 3, 4, 3, 5, 3, 3, 2, 5, 3, 4, 4, 4, 3, 4, 3, 4, 5, 5, 3, 4, 4, 3, 4, 4, 5, 4, 4, 4, 3, 4, 5, 5, 4, 2, 3, 4, 2, 3, 4, 0, 3, 3, 1, 4, 3, 2, 4, 3, 3, 5, 5, 0, 3, 0, 3, 0, 5, 5, 5, 5, 4, 4, 0, 4, 0, 1, 4, 4),
+ (0, 4, 0, 4, 0, 3, 0, 3, 0, 3, 5, 4, 4, 2, 3, 2, 5, 1, 3, 2, 5, 1, 4, 2, 3, 2, 3, 3, 4, 3, 3, 3, 3, 2, 5, 4, 1, 3, 3, 5, 3, 4, 4, 0, 4, 4, 3, 1, 1, 3, 1, 0, 2, 3, 0, 2, 3, 0, 3, 0, 0, 4, 3, 1, 3, 4, 0, 3, 0, 2, 0, 4, 4, 4, 3, 4, 5, 0, 4, 0, 0, 3, 4),
+ (0, 3, 0, 3, 0, 3, 1, 2, 0, 3, 4, 4, 3, 3, 3, 0, 2, 2, 4, 3, 3, 1, 3, 3, 3, 1, 1, 0, 3, 1, 4, 3, 2, 3, 4, 4, 2, 4, 4, 4, 3, 4, 4, 3, 2, 4, 4, 3, 1, 3, 3, 1, 3, 3, 0, 4, 1, 0, 2, 2, 1, 4, 3, 2, 3, 3, 5, 4, 3, 3, 5, 4, 4, 3, 3, 0, 4, 0, 3, 2, 2, 4, 4),
+ (0, 2, 0, 1, 0, 0, 0, 0, 0, 1, 2, 1, 3, 0, 0, 0, 0, 0, 2, 0, 1, 2, 1, 0, 0, 1, 0, 0, 0, 0, 3, 0, 0, 1, 0, 1, 1, 3, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 2, 2, 0, 3, 4, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1),
+ (0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 4, 0, 4, 1, 4, 0, 3, 0, 4, 0, 3, 0, 4, 0, 3, 0, 3, 0, 4, 1, 5, 1, 4, 0, 0, 3, 0, 5, 0, 5, 2, 0, 1, 0, 0, 0, 2, 1, 4, 0, 1, 3, 0, 0, 3, 0, 0, 3, 1, 1, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0),
+ (1, 4, 0, 5, 0, 3, 0, 2, 0, 3, 5, 4, 4, 3, 4, 3, 5, 3, 4, 3, 3, 0, 4, 3, 3, 3, 3, 3, 3, 2, 4, 4, 3, 1, 3, 4, 4, 5, 4, 4, 3, 4, 4, 1, 3, 5, 4, 3, 3, 3, 1, 2, 2, 3, 3, 1, 3, 1, 3, 3, 3, 5, 3, 3, 4, 5, 0, 3, 0, 3, 0, 3, 4, 3, 4, 4, 3, 0, 3, 0, 2, 4, 3),
+ (0, 1, 0, 4, 0, 0, 0, 0, 0, 1, 4, 0, 4, 1, 4, 2, 4, 0, 3, 0, 1, 0, 1, 0, 0, 0, 0, 0, 2, 0, 3, 1, 1, 1, 0, 3, 0, 0, 0, 1, 2, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 3, 0, 0, 0, 0, 3, 2, 0, 2, 2, 0, 1, 0, 0, 0, 2, 3, 2, 3, 3, 0, 0, 0, 0, 2, 1, 0),
+ (0, 5, 1, 5, 0, 3, 0, 3, 0, 5, 4, 4, 5, 1, 5, 3, 3, 0, 4, 3, 4, 3, 5, 3, 4, 3, 3, 2, 4, 3, 4, 3, 3, 0, 3, 3, 1, 4, 4, 3, 4, 4, 4, 3, 4, 5, 5, 3, 2, 3, 1, 1, 3, 3, 1, 3, 1, 1, 3, 3, 2, 4, 5, 3, 3, 5, 0, 4, 0, 3, 0, 4, 4, 3, 5, 3, 3, 0, 3, 4, 0, 4, 3),
+ (0, 5, 0, 5, 0, 3, 0, 2, 0, 4, 4, 3, 5, 2, 4, 3, 3, 3, 4, 4, 4, 3, 5, 3, 5, 3, 3, 1, 4, 0, 4, 3, 3, 0, 3, 3, 0, 4, 4, 4, 4, 5, 4, 3, 3, 5, 5, 3, 2, 3, 1, 2, 3, 2, 0, 1, 0, 0, 3, 2, 2, 4, 4, 3, 1, 5, 0, 4, 0, 3, 0, 4, 3, 1, 3, 2, 1, 0, 3, 3, 0, 3, 3),
+ (0, 4, 0, 5, 0, 5, 0, 4, 0, 4, 5, 5, 5, 3, 4, 3, 3, 2, 5, 4, 4, 3, 5, 3, 5, 3, 4, 0, 4, 3, 4, 4, 3, 2, 4, 4, 3, 4, 5, 4, 4, 5, 5, 0, 3, 5, 5, 4, 1, 3, 3, 2, 3, 3, 1, 3, 1, 0, 4, 3, 1, 4, 4, 3, 4, 5, 0, 4, 0, 2, 0, 4, 3, 4, 4, 3, 3, 0, 4, 0, 0, 5, 5),
+ (0, 4, 0, 4, 0, 5, 0, 1, 1, 3, 3, 4, 4, 3, 4, 1, 3, 0, 5, 1, 3, 0, 3, 1, 3, 1, 1, 0, 3, 0, 3, 3, 4, 0, 4, 3, 0, 4, 4, 4, 3, 4, 4, 0, 3, 5, 4, 1, 0, 3, 0, 0, 2, 3, 0, 3, 1, 0, 3, 1, 0, 3, 2, 1, 3, 5, 0, 3, 0, 1, 0, 3, 2, 3, 3, 4, 4, 0, 2, 2, 0, 4, 4),
+ (2, 4, 0, 5, 0, 4, 0, 3, 0, 4, 5, 5, 4, 3, 5, 3, 5, 3, 5, 3, 5, 2, 5, 3, 4, 3, 3, 4, 3, 4, 5, 3, 2, 1, 5, 4, 3, 2, 3, 4, 5, 3, 4, 1, 2, 5, 4, 3, 0, 3, 3, 0, 3, 2, 0, 2, 3, 0, 4, 1, 0, 3, 4, 3, 3, 5, 0, 3, 0, 1, 0, 4, 5, 5, 5, 4, 3, 0, 4, 2, 0, 3, 5),
+ (0, 5, 0, 4, 0, 4, 0, 2, 0, 5, 4, 3, 4, 3, 4, 3, 3, 3, 4, 3, 4, 2, 5, 3, 5, 3, 4, 1, 4, 3, 4, 4, 4, 0, 3, 5, 0, 4, 4, 4, 4, 5, 3, 1, 3, 4, 5, 3, 3, 3, 3, 3, 3, 3, 0, 2, 2, 0, 3, 3, 2, 4, 3, 3, 3, 5, 3, 4, 1, 3, 3, 5, 3, 2, 0, 0, 0, 0, 4, 3, 1, 3, 3),
+ (0, 1, 0, 3, 0, 3, 0, 1, 0, 1, 3, 3, 3, 2, 3, 3, 3, 0, 3, 0, 0, 0, 3, 1, 3, 0, 0, 0, 2, 2, 2, 3, 0, 0, 3, 2, 0, 1, 2, 4, 1, 3, 3, 0, 0, 3, 3, 3, 0, 1, 0, 0, 2, 1, 0, 0, 3, 0, 3, 1, 0, 3, 0, 0, 1, 3, 0, 2, 0, 1, 0, 3, 3, 1, 3, 3, 0, 0, 1, 1, 0, 3, 3),
+ (0, 2, 0, 3, 0, 2, 1, 4, 0, 2, 2, 3, 1, 1, 3, 1, 1, 0, 2, 0, 3, 1, 2, 3, 1, 3, 0, 0, 1, 0, 4, 3, 2, 3, 3, 3, 1, 4, 2, 3, 3, 3, 3, 1, 0, 3, 1, 4, 0, 1, 1, 0, 1, 2, 0, 1, 1, 0, 1, 1, 0, 3, 1, 3, 2, 2, 0, 1, 0, 0, 0, 2, 3, 3, 3, 1, 0, 0, 0, 0, 0, 2, 3),
+ (0, 5, 0, 4, 0, 5, 0, 2, 0, 4, 5, 5, 3, 3, 4, 3, 3, 1, 5, 4, 4, 2, 4, 4, 4, 3, 4, 2, 4, 3, 5, 5, 4, 3, 3, 4, 3, 3, 5, 5, 4, 5, 5, 1, 3, 4, 5, 3, 1, 4, 3, 1, 3, 3, 0, 3, 3, 1, 4, 3, 1, 4, 5, 3, 3, 5, 0, 4, 0, 3, 0, 5, 3, 3, 1, 4, 3, 0, 4, 0, 1, 5, 3),
+ (0, 5, 0, 5, 0, 4, 0, 2, 0, 4, 4, 3, 4, 3, 3, 3, 3, 3, 5, 4, 4, 4, 4, 4, 4, 5, 3, 3, 5, 2, 4, 4, 4, 3, 4, 4, 3, 3, 4, 4, 5, 5, 3, 3, 4, 3, 4, 3, 3, 4, 3, 3, 3, 3, 1, 2, 2, 1, 4, 3, 3, 5, 4, 4, 3, 4, 0, 4, 0, 3, 0, 4, 4, 4, 4, 4, 1, 0, 4, 2, 0, 2, 4),
+ (0, 4, 0, 4, 0, 3, 0, 1, 0, 3, 5, 2, 3, 0, 3, 0, 2, 1, 4, 2, 3, 3, 4, 1, 4, 3, 3, 2, 4, 1, 3, 3, 3, 0, 3, 3, 0, 0, 3, 3, 3, 5, 3, 3, 3, 3, 3, 2, 0, 2, 0, 0, 2, 0, 0, 2, 0, 0, 1, 0, 0, 3, 1, 2, 2, 3, 0, 3, 0, 2, 0, 4, 4, 3, 3, 4, 1, 0, 3, 0, 0, 2, 4),
+ (0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 2, 0, 0, 0, 0, 0, 1, 0, 2, 0, 1, 0, 0, 0, 0, 0, 3, 1, 3, 0, 3, 2, 0, 0, 0, 1, 0, 3, 2, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 2, 0, 0, 0, 0, 0, 0, 2),
+ (0, 2, 1, 3, 0, 2, 0, 2, 0, 3, 3, 3, 3, 1, 3, 1, 3, 3, 3, 3, 3, 3, 4, 2, 2, 1, 2, 1, 4, 0, 4, 3, 1, 3, 3, 3, 2, 4, 3, 5, 4, 3, 3, 3, 3, 3, 3, 3, 0, 1, 3, 0, 2, 0, 0, 1, 0, 0, 1, 0, 0, 4, 2, 0, 2, 3, 0, 3, 3, 0, 3, 3, 4, 2, 3, 1, 4, 0, 1, 2, 0, 2, 3),
+ (0, 3, 0, 3, 0, 1, 0, 3, 0, 2, 3, 3, 3, 0, 3, 1, 2, 0, 3, 3, 2, 3, 3, 2, 3, 2, 3, 1, 3, 0, 4, 3, 2, 0, 3, 3, 1, 4, 3, 3, 2, 3, 4, 3, 1, 3, 3, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 4, 1, 1, 0, 3, 0, 3, 1, 0, 2, 3, 3, 3, 3, 3, 1, 0, 0, 2, 0, 3, 3),
+ (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 2, 0, 3, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 3, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 2, 0, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3),
+ (0, 2, 0, 3, 1, 3, 0, 3, 0, 2, 3, 3, 3, 1, 3, 1, 3, 1, 3, 1, 3, 3, 3, 1, 3, 0, 2, 3, 1, 1, 4, 3, 3, 2, 3, 3, 1, 2, 2, 4, 1, 3, 3, 0, 1, 4, 2, 3, 0, 1, 3, 0, 3, 0, 0, 1, 3, 0, 2, 0, 0, 3, 3, 2, 1, 3, 0, 3, 0, 2, 0, 3, 4, 4, 4, 3, 1, 0, 3, 0, 0, 3, 3),
+ (0, 2, 0, 1, 0, 2, 0, 0, 0, 1, 3, 2, 2, 1, 3, 0, 1, 1, 3, 0, 3, 2, 3, 1, 2, 0, 2, 0, 1, 1, 3, 3, 3, 0, 3, 3, 1, 1, 2, 3, 2, 3, 3, 1, 2, 3, 2, 0, 0, 1, 0, 0, 0, 0, 0, 0, 3, 0, 1, 0, 0, 2, 1, 2, 1, 3, 0, 3, 0, 0, 0, 3, 4, 4, 4, 3, 2, 0, 2, 0, 0, 2, 4),
+ (0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 3, 1, 0, 0, 0, 0, 0, 0, 0, 3),
+ (0, 3, 0, 3, 0, 2, 0, 3, 0, 3, 3, 3, 2, 3, 2, 2, 2, 0, 3, 1, 3, 3, 3, 2, 3, 3, 0, 0, 3, 0, 3, 2, 2, 0, 2, 3, 1, 4, 3, 4, 3, 3, 2, 3, 1, 5, 4, 4, 0, 3, 1, 2, 1, 3, 0, 3, 1, 1, 2, 0, 2, 3, 1, 3, 1, 3, 0, 3, 0, 1, 0, 3, 3, 4, 4, 2, 1, 0, 2, 1, 0, 2, 4),
+ (0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 4, 2, 5, 1, 4, 0, 2, 0, 2, 1, 3, 1, 4, 0, 2, 1, 0, 0, 2, 1, 4, 1, 1, 0, 3, 3, 0, 5, 1, 3, 2, 3, 3, 1, 0, 3, 2, 3, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 4, 0, 1, 0, 3, 0, 2, 0, 1, 0, 3, 3, 3, 4, 3, 3, 0, 0, 0, 0, 2, 3),
+ (0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 2, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0, 1, 0, 0, 0, 0, 0, 3),
+ (0, 1, 0, 3, 0, 4, 0, 3, 0, 2, 4, 3, 1, 0, 3, 2, 2, 1, 3, 1, 2, 2, 3, 1, 1, 1, 2, 1, 3, 0, 1, 2, 0, 1, 3, 2, 1, 3, 0, 5, 5, 1, 0, 0, 1, 3, 2, 1, 0, 3, 0, 0, 1, 0, 0, 0, 0, 0, 3, 4, 0, 1, 1, 1, 3, 2, 0, 2, 0, 1, 0, 2, 3, 3, 1, 2, 3, 0, 1, 0, 1, 0, 4),
+ (0, 0, 0, 1, 0, 3, 0, 3, 0, 2, 2, 1, 0, 0, 4, 0, 3, 0, 3, 1, 3, 0, 3, 0, 3, 0, 1, 0, 3, 0, 3, 1, 3, 0, 3, 3, 0, 0, 1, 2, 1, 1, 1, 0, 1, 2, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 1, 2, 0, 0, 2, 0, 0, 0, 0, 2, 3, 3, 3, 3, 0, 0, 0, 0, 1, 4),
+ (0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 3, 1, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 3, 0, 2, 0, 2, 3, 0, 0, 2, 2, 3, 1, 2, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 2, 0, 0, 0, 0, 2, 3),
+ (2, 4, 0, 5, 0, 5, 0, 4, 0, 3, 4, 3, 3, 3, 4, 3, 3, 3, 4, 3, 4, 4, 5, 4, 5, 5, 5, 2, 3, 0, 5, 5, 4, 1, 5, 4, 3, 1, 5, 4, 3, 4, 4, 3, 3, 4, 3, 3, 0, 3, 2, 0, 2, 3, 0, 3, 0, 0, 3, 3, 0, 5, 3, 2, 3, 3, 0, 3, 0, 3, 0, 3, 4, 5, 4, 5, 3, 0, 4, 3, 0, 3, 4),
+ (0, 3, 0, 3, 0, 3, 0, 3, 0, 3, 3, 4, 3, 2, 3, 2, 3, 0, 4, 3, 3, 3, 3, 3, 3, 3, 3, 0, 3, 2, 4, 3, 3, 1, 3, 4, 3, 4, 4, 4, 3, 4, 4, 3, 2, 4, 4, 1, 0, 2, 0, 0, 1, 1, 0, 2, 0, 0, 3, 1, 0, 5, 3, 2, 1, 3, 0, 3, 0, 1, 2, 4, 3, 2, 4, 3, 3, 0, 3, 2, 0, 4, 4),
+ (0, 3, 0, 3, 0, 1, 0, 0, 0, 1, 4, 3, 3, 2, 3, 1, 3, 1, 4, 2, 3, 2, 4, 2, 3, 4, 3, 0, 2, 2, 3, 3, 3, 0, 3, 3, 3, 0, 3, 4, 1, 3, 3, 0, 3, 4, 3, 3, 0, 1, 1, 0, 1, 0, 0, 0, 4, 0, 3, 0, 0, 3, 1, 2, 1, 3, 0, 4, 0, 1, 0, 4, 3, 3, 4, 3, 3, 0, 2, 0, 0, 3, 3),
+ (0, 3, 0, 4, 0, 1, 0, 3, 0, 3, 4, 3, 3, 0, 3, 3, 3, 1, 3, 1, 3, 3, 4, 3, 3, 3, 0, 0, 3, 1, 5, 3, 3, 1, 3, 3, 2, 5, 4, 3, 3, 4, 5, 3, 2, 5, 3, 4, 0, 1, 0, 0, 0, 0, 0, 2, 0, 0, 1, 1, 0, 4, 2, 2, 1, 3, 0, 3, 0, 2, 0, 4, 4, 3, 5, 3, 2, 0, 1, 1, 0, 3, 4),
+ (0, 5, 0, 4, 0, 5, 0, 2, 0, 4, 4, 3, 3, 2, 3, 3, 3, 1, 4, 3, 4, 1, 5, 3, 4, 3, 4, 0, 4, 2, 4, 3, 4, 1, 5, 4, 0, 4, 4, 4, 4, 5, 4, 1, 3, 5, 4, 2, 1, 4, 1, 1, 3, 2, 0, 3, 1, 0, 3, 2, 1, 4, 3, 3, 3, 4, 0, 4, 0, 3, 0, 4, 4, 4, 3, 3, 3, 0, 4, 2, 0, 3, 4),
+ (1, 4, 0, 4, 0, 3, 0, 1, 0, 3, 3, 3, 1, 1, 3, 3, 2, 2, 3, 3, 1, 0, 3, 2, 2, 1, 2, 0, 3, 1, 2, 1, 2, 0, 3, 2, 0, 2, 2, 3, 3, 4, 3, 0, 3, 3, 1, 2, 0, 1, 1, 3, 1, 2, 0, 0, 3, 0, 1, 1, 0, 3, 2, 2, 3, 3, 0, 3, 0, 0, 0, 2, 3, 3, 4, 3, 3, 0, 1, 0, 0, 1, 4),
+ (0, 4, 0, 4, 0, 4, 0, 0, 0, 3, 4, 4, 3, 1, 4, 2, 3, 2, 3, 3, 3, 1, 4, 3, 4, 0, 3, 0, 4, 2, 3, 3, 2, 2, 5, 4, 2, 1, 3, 4, 3, 4, 3, 1, 3, 3, 4, 2, 0, 2, 1, 0, 3, 3, 0, 0, 2, 0, 3, 1, 0, 4, 4, 3, 4, 3, 0, 4, 0, 1, 0, 2, 4, 4, 4, 4, 4, 0, 3, 2, 0, 3, 3),
+ (0, 0, 0, 1, 0, 4, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 3, 2, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 2),
+ (0, 2, 0, 3, 0, 4, 0, 4, 0, 1, 3, 3, 3, 0, 4, 0, 2, 1, 2, 1, 1, 1, 2, 0, 3, 1, 1, 0, 1, 0, 3, 1, 0, 0, 3, 3, 2, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 2, 0, 2, 2, 0, 3, 1, 0, 0, 1, 0, 1, 1, 0, 1, 2, 0, 3, 0, 0, 0, 0, 1, 0, 0, 3, 3, 4, 3, 1, 0, 1, 0, 3, 0, 2),
+ (0, 0, 0, 3, 0, 5, 0, 0, 0, 0, 1, 0, 2, 0, 3, 1, 0, 1, 3, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 4, 0, 0, 0, 2, 3, 0, 1, 4, 1, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 3, 0, 0, 0, 0, 0, 3),
+ (0, 2, 0, 5, 0, 5, 0, 1, 0, 2, 4, 3, 3, 2, 5, 1, 3, 2, 3, 3, 3, 0, 4, 1, 2, 0, 3, 0, 4, 0, 2, 2, 1, 1, 5, 3, 0, 0, 1, 4, 2, 3, 2, 0, 3, 3, 3, 2, 0, 2, 4, 1, 1, 2, 0, 1, 1, 0, 3, 1, 0, 1, 3, 1, 2, 3, 0, 2, 0, 0, 0, 1, 3, 5, 4, 4, 4, 0, 3, 0, 0, 1, 3),
+ (0, 4, 0, 5, 0, 4, 0, 4, 0, 4, 5, 4, 3, 3, 4, 3, 3, 3, 4, 3, 4, 4, 5, 3, 4, 5, 4, 2, 4, 2, 3, 4, 3, 1, 4, 4, 1, 3, 5, 4, 4, 5, 5, 4, 4, 5, 5, 5, 2, 3, 3, 1, 4, 3, 1, 3, 3, 0, 3, 3, 1, 4, 3, 4, 4, 4, 0, 3, 0, 4, 0, 3, 3, 4, 4, 5, 0, 0, 4, 3, 0, 4, 5),
+ (0, 4, 0, 4, 0, 3, 0, 3, 0, 3, 4, 4, 4, 3, 3, 2, 4, 3, 4, 3, 4, 3, 5, 3, 4, 3, 2, 1, 4, 2, 4, 4, 3, 1, 3, 4, 2, 4, 5, 5, 3, 4, 5, 4, 1, 5, 4, 3, 0, 3, 2, 2, 3, 2, 1, 3, 1, 0, 3, 3, 3, 5, 3, 3, 3, 5, 4, 4, 2, 3, 3, 4, 3, 3, 3, 2, 1, 0, 3, 2, 1, 4, 3),
+ (0, 4, 0, 5, 0, 4, 0, 3, 0, 3, 5, 5, 3, 2, 4, 3, 4, 0, 5, 4, 4, 1, 4, 4, 4, 3, 3, 3, 4, 3, 5, 5, 2, 3, 3, 4, 1, 2, 5, 5, 3, 5, 5, 2, 3, 5, 5, 4, 0, 3, 2, 0, 3, 3, 1, 1, 5, 1, 4, 1, 0, 4, 3, 2, 3, 5, 0, 4, 0, 3, 0, 5, 4, 3, 4, 3, 0, 0, 4, 1, 0, 4, 4),
+ (1, 3, 0, 4, 0, 2, 0, 2, 0, 2, 5, 5, 3, 3, 3, 3, 3, 0, 4, 2, 3, 4, 4, 4, 3, 4, 0, 0, 3, 4, 5, 4, 3, 3, 3, 3, 2, 5, 5, 4, 5, 5, 5, 4, 3, 5, 5, 5, 1, 3, 1, 0, 1, 0, 0, 3, 2, 0, 4, 2, 0, 5, 2, 3, 2, 4, 1, 3, 0, 3, 0, 4, 5, 4, 5, 4, 3, 0, 4, 2, 0, 5, 4),
+ (0, 3, 0, 4, 0, 5, 0, 3, 0, 3, 4, 4, 3, 2, 3, 2, 3, 3, 3, 3, 3, 2, 4, 3, 3, 2, 2, 0, 3, 3, 3, 3, 3, 1, 3, 3, 3, 0, 4, 4, 3, 4, 4, 1, 1, 4, 4, 2, 0, 3, 1, 0, 1, 1, 0, 4, 1, 0, 2, 3, 1, 3, 3, 1, 3, 4, 0, 3, 0, 1, 0, 3, 1, 3, 0, 0, 1, 0, 2, 0, 0, 4, 4),
+ (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
+ (0, 3, 0, 3, 0, 2, 0, 3, 0, 1, 5, 4, 3, 3, 3, 1, 4, 2, 1, 2, 3, 4, 4, 2, 4, 4, 5, 0, 3, 1, 4, 3, 4, 0, 4, 3, 3, 3, 2, 3, 2, 5, 3, 4, 3, 2, 2, 3, 0, 0, 3, 0, 2, 1, 0, 1, 2, 0, 0, 0, 0, 2, 1, 1, 3, 1, 0, 2, 0, 4, 0, 3, 4, 4, 4, 5, 2, 0, 2, 0, 0, 1, 3),
+ (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 4, 2, 1, 1, 0, 1, 0, 3, 2, 0, 0, 3, 1, 1, 1, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 1, 0, 0, 0, 2, 0, 0, 0, 1, 4, 0, 4, 2, 1, 0, 0, 0, 0, 0, 1),
+ (0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 3, 1, 0, 0, 0, 2, 0, 2, 1, 0, 0, 1, 2, 1, 0, 1, 1, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 3, 1, 0, 0, 0, 0, 0, 1, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 2),
+ (0, 4, 0, 4, 0, 4, 0, 3, 0, 4, 4, 3, 4, 2, 4, 3, 2, 0, 4, 4, 4, 3, 5, 3, 5, 3, 3, 2, 4, 2, 4, 3, 4, 3, 1, 4, 0, 2, 3, 4, 4, 4, 3, 3, 3, 4, 4, 4, 3, 4, 1, 3, 4, 3, 2, 1, 2, 1, 3, 3, 3, 4, 4, 3, 3, 5, 0, 4, 0, 3, 0, 4, 3, 3, 3, 2, 1, 0, 3, 0, 0, 3, 3),
+ (0, 4, 0, 3, 0, 3, 0, 3, 0, 3, 5, 5, 3, 3, 3, 3, 4, 3, 4, 3, 3, 3, 4, 4, 4, 3, 3, 3, 3, 4, 3, 5, 3, 3, 1, 3, 2, 4, 5, 5, 5, 5, 4, 3, 4, 5, 5, 3, 2, 2, 3, 3, 3, 3, 2, 3, 3, 1, 2, 3, 2, 4, 3, 3, 3, 4, 0, 4, 0, 2, 0, 4, 3, 2, 2, 1, 2, 0, 3, 0, 0, 4, 1),
+)
+# fmt: on
+
+
+class JapaneseContextAnalysis:
+ NUM_OF_CATEGORY = 6
+ DONT_KNOW = -1
+ ENOUGH_REL_THRESHOLD = 100
+ MAX_REL_THRESHOLD = 1000
+ MINIMUM_DATA_THRESHOLD = 4
+
+ def __init__(self) -> None:
+ self._total_rel = 0
+ self._rel_sample: List[int] = []
+ self._need_to_skip_char_num = 0
+ self._last_char_order = -1
+ self._done = False
+ self.reset()
+
+ def reset(self) -> None:
+ self._total_rel = 0 # total sequence received
+ # category counters, each integer counts sequence in its category
+ self._rel_sample = [0] * self.NUM_OF_CATEGORY
+ # if last byte in current buffer is not the last byte of a character,
+ # we need to know how many bytes to skip in next buffer
+ self._need_to_skip_char_num = 0
+ self._last_char_order = -1 # The order of previous char
+ # If this flag is set to True, detection is done and conclusion has
+ # been made
+ self._done = False
+
+ def feed(self, byte_str: Union[bytes, bytearray], num_bytes: int) -> None:
+ if self._done:
+ return
+
+ # The buffer we got is byte oriented, and a character may span in more than one
+ # buffers. In case the last one or two byte in last buffer is not
+ # complete, we record how many byte needed to complete that character
+ # and skip these bytes here. We can choose to record those bytes as
+ # well and analyse the character once it is complete, but since a
+ # character will not make much difference, by simply skipping
+ # this character will simply our logic and improve performance.
+ i = self._need_to_skip_char_num
+ while i < num_bytes:
+ order, char_len = self.get_order(byte_str[i : i + 2])
+ i += char_len
+ if i > num_bytes:
+ self._need_to_skip_char_num = i - num_bytes
+ self._last_char_order = -1
+ else:
+ if (order != -1) and (self._last_char_order != -1):
+ self._total_rel += 1
+ if self._total_rel > self.MAX_REL_THRESHOLD:
+ self._done = True
+ break
+ self._rel_sample[
+ jp2_char_context[self._last_char_order][order]
+ ] += 1
+ self._last_char_order = order
+
+ def got_enough_data(self) -> bool:
+ return self._total_rel > self.ENOUGH_REL_THRESHOLD
+
+ def get_confidence(self) -> float:
+ # This is just one way to calculate confidence. It works well for me.
+ if self._total_rel > self.MINIMUM_DATA_THRESHOLD:
+ return (self._total_rel - self._rel_sample[0]) / self._total_rel
+ return self.DONT_KNOW
+
+ def get_order(self, _: Union[bytes, bytearray]) -> Tuple[int, int]:
+ return -1, 1
+
+
+class SJISContextAnalysis(JapaneseContextAnalysis):
+ def __init__(self) -> None:
+ super().__init__()
+ self._charset_name = "SHIFT_JIS"
+
+ @property
+ def charset_name(self) -> str:
+ return self._charset_name
+
+ def get_order(self, byte_str: Union[bytes, bytearray]) -> Tuple[int, int]:
+ if not byte_str:
+ return -1, 1
+ # find out current char's byte length
+ first_char = byte_str[0]
+ if (0x81 <= first_char <= 0x9F) or (0xE0 <= first_char <= 0xFC):
+ char_len = 2
+ if (first_char == 0x87) or (0xFA <= first_char <= 0xFC):
+ self._charset_name = "CP932"
+ else:
+ char_len = 1
+
+ # return its order if it is hiragana
+ if len(byte_str) > 1:
+ second_char = byte_str[1]
+ if (first_char == 202) and (0x9F <= second_char <= 0xF1):
+ return second_char - 0x9F, char_len
+
+ return -1, char_len
+
+
+class EUCJPContextAnalysis(JapaneseContextAnalysis):
+ def get_order(self, byte_str: Union[bytes, bytearray]) -> Tuple[int, int]:
+ if not byte_str:
+ return -1, 1
+ # find out current char's byte length
+ first_char = byte_str[0]
+ if (first_char == 0x8E) or (0xA1 <= first_char <= 0xFE):
+ char_len = 2
+ elif first_char == 0x8F:
+ char_len = 3
+ else:
+ char_len = 1
+
+ # return its order if it is hiragana
+ if len(byte_str) > 1:
+ second_char = byte_str[1]
+ if (first_char == 0xA4) and (0xA1 <= second_char <= 0xF3):
+ return second_char - 0xA1, char_len
+
+ return -1, char_len
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/langgreekmodel.py b/env-llmeval/lib/python3.10/site-packages/chardet/langgreekmodel.py
new file mode 100644
index 0000000000000000000000000000000000000000..0471d8bb1891415468a7394e34b2fef58ad6e0b0
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/langgreekmodel.py
@@ -0,0 +1,4397 @@
+from chardet.sbcharsetprober import SingleByteCharSetModel
+
+# 3: Positive
+# 2: Likely
+# 1: Unlikely
+# 0: Negative
+
+GREEK_LANG_MODEL = {
+ 60: { # 'e'
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+ 1: 0, # 'α'
+ 29: 2, # 'β'
+ 20: 3, # 'γ'
+ 21: 2, # 'δ'
+ 3: 0, # 'ε'
+ 32: 0, # 'ζ'
+ 13: 0, # 'η'
+ 25: 3, # 'θ'
+ 5: 2, # 'ι'
+ 11: 0, # 'κ'
+ 16: 2, # 'λ'
+ 10: 3, # 'μ'
+ 6: 3, # 'ν'
+ 30: 0, # 'ξ'
+ 4: 0, # 'ο'
+ 9: 3, # 'π'
+ 8: 3, # 'ρ'
+ 14: 3, # 'ς'
+ 7: 3, # 'σ'
+ 2: 3, # 'τ'
+ 12: 0, # 'υ'
+ 28: 2, # 'φ'
+ 23: 2, # 'χ'
+ 42: 0, # 'ψ'
+ 24: 0, # 'ω'
+ 19: 0, # 'ό'
+ 26: 0, # 'ύ'
+ 27: 0, # 'ώ'
+ },
+ 19: { # 'ό'
+ 60: 0, # 'e'
+ 55: 0, # 'o'
+ 58: 0, # 't'
+ 36: 0, # '·'
+ 61: 0, # 'Ά'
+ 46: 0, # 'Έ'
+ 54: 0, # 'Ό'
+ 31: 0, # 'Α'
+ 51: 0, # 'Β'
+ 43: 0, # 'Γ'
+ 41: 0, # 'Δ'
+ 34: 0, # 'Ε'
+ 40: 0, # 'Η'
+ 52: 0, # 'Θ'
+ 47: 0, # 'Ι'
+ 44: 0, # 'Κ'
+ 53: 0, # 'Λ'
+ 38: 0, # 'Μ'
+ 49: 0, # 'Ν'
+ 59: 0, # 'Ξ'
+ 39: 0, # 'Ο'
+ 35: 0, # 'Π'
+ 48: 0, # 'Ρ'
+ 37: 0, # 'Σ'
+ 33: 0, # 'Τ'
+ 45: 0, # 'Υ'
+ 56: 0, # 'Φ'
+ 50: 0, # 'Χ'
+ 57: 0, # 'Ω'
+ 17: 0, # 'ά'
+ 18: 0, # 'έ'
+ 22: 0, # 'ή'
+ 15: 0, # 'ί'
+ 1: 0, # 'α'
+ 29: 3, # 'β'
+ 20: 3, # 'γ'
+ 21: 3, # 'δ'
+ 3: 1, # 'ε'
+ 32: 2, # 'ζ'
+ 13: 2, # 'η'
+ 25: 2, # 'θ'
+ 5: 2, # 'ι'
+ 11: 3, # 'κ'
+ 16: 3, # 'λ'
+ 10: 3, # 'μ'
+ 6: 3, # 'ν'
+ 30: 1, # 'ξ'
+ 4: 2, # 'ο'
+ 9: 3, # 'π'
+ 8: 3, # 'ρ'
+ 14: 3, # 'ς'
+ 7: 3, # 'σ'
+ 2: 3, # 'τ'
+ 12: 0, # 'υ'
+ 28: 2, # 'φ'
+ 23: 3, # 'χ'
+ 42: 2, # 'ψ'
+ 24: 0, # 'ω'
+ 19: 0, # 'ό'
+ 26: 0, # 'ύ'
+ 27: 0, # 'ώ'
+ },
+ 26: { # 'ύ'
+ 60: 0, # 'e'
+ 55: 0, # 'o'
+ 58: 0, # 't'
+ 36: 0, # '·'
+ 61: 0, # 'Ά'
+ 46: 0, # 'Έ'
+ 54: 0, # 'Ό'
+ 31: 0, # 'Α'
+ 51: 0, # 'Β'
+ 43: 0, # 'Γ'
+ 41: 0, # 'Δ'
+ 34: 0, # 'Ε'
+ 40: 0, # 'Η'
+ 52: 0, # 'Θ'
+ 47: 0, # 'Ι'
+ 44: 0, # 'Κ'
+ 53: 0, # 'Λ'
+ 38: 0, # 'Μ'
+ 49: 0, # 'Ν'
+ 59: 0, # 'Ξ'
+ 39: 0, # 'Ο'
+ 35: 0, # 'Π'
+ 48: 0, # 'Ρ'
+ 37: 0, # 'Σ'
+ 33: 0, # 'Τ'
+ 45: 0, # 'Υ'
+ 56: 0, # 'Φ'
+ 50: 0, # 'Χ'
+ 57: 0, # 'Ω'
+ 17: 0, # 'ά'
+ 18: 0, # 'έ'
+ 22: 0, # 'ή'
+ 15: 0, # 'ί'
+ 1: 2, # 'α'
+ 29: 2, # 'β'
+ 20: 2, # 'γ'
+ 21: 1, # 'δ'
+ 3: 3, # 'ε'
+ 32: 0, # 'ζ'
+ 13: 2, # 'η'
+ 25: 3, # 'θ'
+ 5: 0, # 'ι'
+ 11: 3, # 'κ'
+ 16: 3, # 'λ'
+ 10: 3, # 'μ'
+ 6: 3, # 'ν'
+ 30: 2, # 'ξ'
+ 4: 3, # 'ο'
+ 9: 3, # 'π'
+ 8: 3, # 'ρ'
+ 14: 3, # 'ς'
+ 7: 3, # 'σ'
+ 2: 3, # 'τ'
+ 12: 0, # 'υ'
+ 28: 2, # 'φ'
+ 23: 2, # 'χ'
+ 42: 2, # 'ψ'
+ 24: 2, # 'ω'
+ 19: 0, # 'ό'
+ 26: 0, # 'ύ'
+ 27: 0, # 'ώ'
+ },
+ 27: { # 'ώ'
+ 60: 0, # 'e'
+ 55: 0, # 'o'
+ 58: 0, # 't'
+ 36: 0, # '·'
+ 61: 0, # 'Ά'
+ 46: 0, # 'Έ'
+ 54: 0, # 'Ό'
+ 31: 0, # 'Α'
+ 51: 0, # 'Β'
+ 43: 0, # 'Γ'
+ 41: 0, # 'Δ'
+ 34: 0, # 'Ε'
+ 40: 0, # 'Η'
+ 52: 0, # 'Θ'
+ 47: 0, # 'Ι'
+ 44: 0, # 'Κ'
+ 53: 0, # 'Λ'
+ 38: 0, # 'Μ'
+ 49: 0, # 'Ν'
+ 59: 0, # 'Ξ'
+ 39: 0, # 'Ο'
+ 35: 0, # 'Π'
+ 48: 0, # 'Ρ'
+ 37: 0, # 'Σ'
+ 33: 0, # 'Τ'
+ 45: 0, # 'Υ'
+ 56: 0, # 'Φ'
+ 50: 0, # 'Χ'
+ 57: 0, # 'Ω'
+ 17: 0, # 'ά'
+ 18: 0, # 'έ'
+ 22: 0, # 'ή'
+ 15: 0, # 'ί'
+ 1: 0, # 'α'
+ 29: 1, # 'β'
+ 20: 0, # 'γ'
+ 21: 3, # 'δ'
+ 3: 0, # 'ε'
+ 32: 0, # 'ζ'
+ 13: 1, # 'η'
+ 25: 2, # 'θ'
+ 5: 2, # 'ι'
+ 11: 0, # 'κ'
+ 16: 2, # 'λ'
+ 10: 3, # 'μ'
+ 6: 3, # 'ν'
+ 30: 1, # 'ξ'
+ 4: 0, # 'ο'
+ 9: 2, # 'π'
+ 8: 3, # 'ρ'
+ 14: 3, # 'ς'
+ 7: 3, # 'σ'
+ 2: 3, # 'τ'
+ 12: 0, # 'υ'
+ 28: 1, # 'φ'
+ 23: 1, # 'χ'
+ 42: 0, # 'ψ'
+ 24: 0, # 'ω'
+ 19: 0, # 'ό'
+ 26: 0, # 'ύ'
+ 27: 0, # 'ώ'
+ },
+}
+
+# 255: Undefined characters that did not exist in training text
+# 254: Carriage/Return
+# 253: symbol (punctuation) that does not belong to word
+# 252: 0 - 9
+# 251: Control characters
+
+# Character Mapping Table(s):
+WINDOWS_1253_GREEK_CHAR_TO_ORDER = {
+ 0: 255, # '\x00'
+ 1: 255, # '\x01'
+ 2: 255, # '\x02'
+ 3: 255, # '\x03'
+ 4: 255, # '\x04'
+ 5: 255, # '\x05'
+ 6: 255, # '\x06'
+ 7: 255, # '\x07'
+ 8: 255, # '\x08'
+ 9: 255, # '\t'
+ 10: 254, # '\n'
+ 11: 255, # '\x0b'
+ 12: 255, # '\x0c'
+ 13: 254, # '\r'
+ 14: 255, # '\x0e'
+ 15: 255, # '\x0f'
+ 16: 255, # '\x10'
+ 17: 255, # '\x11'
+ 18: 255, # '\x12'
+ 19: 255, # '\x13'
+ 20: 255, # '\x14'
+ 21: 255, # '\x15'
+ 22: 255, # '\x16'
+ 23: 255, # '\x17'
+ 24: 255, # '\x18'
+ 25: 255, # '\x19'
+ 26: 255, # '\x1a'
+ 27: 255, # '\x1b'
+ 28: 255, # '\x1c'
+ 29: 255, # '\x1d'
+ 30: 255, # '\x1e'
+ 31: 255, # '\x1f'
+ 32: 253, # ' '
+ 33: 253, # '!'
+ 34: 253, # '"'
+ 35: 253, # '#'
+ 36: 253, # '$'
+ 37: 253, # '%'
+ 38: 253, # '&'
+ 39: 253, # "'"
+ 40: 253, # '('
+ 41: 253, # ')'
+ 42: 253, # '*'
+ 43: 253, # '+'
+ 44: 253, # ','
+ 45: 253, # '-'
+ 46: 253, # '.'
+ 47: 253, # '/'
+ 48: 252, # '0'
+ 49: 252, # '1'
+ 50: 252, # '2'
+ 51: 252, # '3'
+ 52: 252, # '4'
+ 53: 252, # '5'
+ 54: 252, # '6'
+ 55: 252, # '7'
+ 56: 252, # '8'
+ 57: 252, # '9'
+ 58: 253, # ':'
+ 59: 253, # ';'
+ 60: 253, # '<'
+ 61: 253, # '='
+ 62: 253, # '>'
+ 63: 253, # '?'
+ 64: 253, # '@'
+ 65: 82, # 'A'
+ 66: 100, # 'B'
+ 67: 104, # 'C'
+ 68: 94, # 'D'
+ 69: 98, # 'E'
+ 70: 101, # 'F'
+ 71: 116, # 'G'
+ 72: 102, # 'H'
+ 73: 111, # 'I'
+ 74: 187, # 'J'
+ 75: 117, # 'K'
+ 76: 92, # 'L'
+ 77: 88, # 'M'
+ 78: 113, # 'N'
+ 79: 85, # 'O'
+ 80: 79, # 'P'
+ 81: 118, # 'Q'
+ 82: 105, # 'R'
+ 83: 83, # 'S'
+ 84: 67, # 'T'
+ 85: 114, # 'U'
+ 86: 119, # 'V'
+ 87: 95, # 'W'
+ 88: 99, # 'X'
+ 89: 109, # 'Y'
+ 90: 188, # 'Z'
+ 91: 253, # '['
+ 92: 253, # '\\'
+ 93: 253, # ']'
+ 94: 253, # '^'
+ 95: 253, # '_'
+ 96: 253, # '`'
+ 97: 72, # 'a'
+ 98: 70, # 'b'
+ 99: 80, # 'c'
+ 100: 81, # 'd'
+ 101: 60, # 'e'
+ 102: 96, # 'f'
+ 103: 93, # 'g'
+ 104: 89, # 'h'
+ 105: 68, # 'i'
+ 106: 120, # 'j'
+ 107: 97, # 'k'
+ 108: 77, # 'l'
+ 109: 86, # 'm'
+ 110: 69, # 'n'
+ 111: 55, # 'o'
+ 112: 78, # 'p'
+ 113: 115, # 'q'
+ 114: 65, # 'r'
+ 115: 66, # 's'
+ 116: 58, # 't'
+ 117: 76, # 'u'
+ 118: 106, # 'v'
+ 119: 103, # 'w'
+ 120: 87, # 'x'
+ 121: 107, # 'y'
+ 122: 112, # 'z'
+ 123: 253, # '{'
+ 124: 253, # '|'
+ 125: 253, # '}'
+ 126: 253, # '~'
+ 127: 253, # '\x7f'
+ 128: 255, # '€'
+ 129: 255, # None
+ 130: 255, # '‚'
+ 131: 255, # 'ƒ'
+ 132: 255, # '„'
+ 133: 255, # '…'
+ 134: 255, # '†'
+ 135: 255, # '‡'
+ 136: 255, # None
+ 137: 255, # '‰'
+ 138: 255, # None
+ 139: 255, # '‹'
+ 140: 255, # None
+ 141: 255, # None
+ 142: 255, # None
+ 143: 255, # None
+ 144: 255, # None
+ 145: 255, # '‘'
+ 146: 255, # '’'
+ 147: 255, # '“'
+ 148: 255, # '”'
+ 149: 255, # '•'
+ 150: 255, # '–'
+ 151: 255, # '—'
+ 152: 255, # None
+ 153: 255, # '™'
+ 154: 255, # None
+ 155: 255, # '›'
+ 156: 255, # None
+ 157: 255, # None
+ 158: 255, # None
+ 159: 255, # None
+ 160: 253, # '\xa0'
+ 161: 233, # '΅'
+ 162: 61, # 'Ά'
+ 163: 253, # '£'
+ 164: 253, # '¤'
+ 165: 253, # '¥'
+ 166: 253, # '¦'
+ 167: 253, # '§'
+ 168: 253, # '¨'
+ 169: 253, # '©'
+ 170: 253, # None
+ 171: 253, # '«'
+ 172: 253, # '¬'
+ 173: 74, # '\xad'
+ 174: 253, # '®'
+ 175: 253, # '―'
+ 176: 253, # '°'
+ 177: 253, # '±'
+ 178: 253, # '²'
+ 179: 253, # '³'
+ 180: 247, # '΄'
+ 181: 253, # 'µ'
+ 182: 253, # '¶'
+ 183: 36, # '·'
+ 184: 46, # 'Έ'
+ 185: 71, # 'Ή'
+ 186: 73, # 'Ί'
+ 187: 253, # '»'
+ 188: 54, # 'Ό'
+ 189: 253, # '½'
+ 190: 108, # 'Ύ'
+ 191: 123, # 'Ώ'
+ 192: 110, # 'ΐ'
+ 193: 31, # 'Α'
+ 194: 51, # 'Β'
+ 195: 43, # 'Γ'
+ 196: 41, # 'Δ'
+ 197: 34, # 'Ε'
+ 198: 91, # 'Ζ'
+ 199: 40, # 'Η'
+ 200: 52, # 'Θ'
+ 201: 47, # 'Ι'
+ 202: 44, # 'Κ'
+ 203: 53, # 'Λ'
+ 204: 38, # 'Μ'
+ 205: 49, # 'Ν'
+ 206: 59, # 'Ξ'
+ 207: 39, # 'Ο'
+ 208: 35, # 'Π'
+ 209: 48, # 'Ρ'
+ 210: 250, # None
+ 211: 37, # 'Σ'
+ 212: 33, # 'Τ'
+ 213: 45, # 'Υ'
+ 214: 56, # 'Φ'
+ 215: 50, # 'Χ'
+ 216: 84, # 'Ψ'
+ 217: 57, # 'Ω'
+ 218: 120, # 'Ϊ'
+ 219: 121, # 'Ϋ'
+ 220: 17, # 'ά'
+ 221: 18, # 'έ'
+ 222: 22, # 'ή'
+ 223: 15, # 'ί'
+ 224: 124, # 'ΰ'
+ 225: 1, # 'α'
+ 226: 29, # 'β'
+ 227: 20, # 'γ'
+ 228: 21, # 'δ'
+ 229: 3, # 'ε'
+ 230: 32, # 'ζ'
+ 231: 13, # 'η'
+ 232: 25, # 'θ'
+ 233: 5, # 'ι'
+ 234: 11, # 'κ'
+ 235: 16, # 'λ'
+ 236: 10, # 'μ'
+ 237: 6, # 'ν'
+ 238: 30, # 'ξ'
+ 239: 4, # 'ο'
+ 240: 9, # 'π'
+ 241: 8, # 'ρ'
+ 242: 14, # 'ς'
+ 243: 7, # 'σ'
+ 244: 2, # 'τ'
+ 245: 12, # 'υ'
+ 246: 28, # 'φ'
+ 247: 23, # 'χ'
+ 248: 42, # 'ψ'
+ 249: 24, # 'ω'
+ 250: 64, # 'ϊ'
+ 251: 75, # 'ϋ'
+ 252: 19, # 'ό'
+ 253: 26, # 'ύ'
+ 254: 27, # 'ώ'
+ 255: 253, # None
+}
+
+WINDOWS_1253_GREEK_MODEL = SingleByteCharSetModel(
+ charset_name="windows-1253",
+ language="Greek",
+ char_to_order_map=WINDOWS_1253_GREEK_CHAR_TO_ORDER,
+ language_model=GREEK_LANG_MODEL,
+ typical_positive_ratio=0.982851,
+ keep_ascii_letters=False,
+ alphabet="ΆΈΉΊΌΎΏΑΒΓΔΕΖΗΘΙΚΛΜΝΞΟΠΡΣΤΥΦΧΨΩάέήίαβγδεζηθικλμνξοπρςστυφχψωόύώ",
+)
+
+ISO_8859_7_GREEK_CHAR_TO_ORDER = {
+ 0: 255, # '\x00'
+ 1: 255, # '\x01'
+ 2: 255, # '\x02'
+ 3: 255, # '\x03'
+ 4: 255, # '\x04'
+ 5: 255, # '\x05'
+ 6: 255, # '\x06'
+ 7: 255, # '\x07'
+ 8: 255, # '\x08'
+ 9: 255, # '\t'
+ 10: 254, # '\n'
+ 11: 255, # '\x0b'
+ 12: 255, # '\x0c'
+ 13: 254, # '\r'
+ 14: 255, # '\x0e'
+ 15: 255, # '\x0f'
+ 16: 255, # '\x10'
+ 17: 255, # '\x11'
+ 18: 255, # '\x12'
+ 19: 255, # '\x13'
+ 20: 255, # '\x14'
+ 21: 255, # '\x15'
+ 22: 255, # '\x16'
+ 23: 255, # '\x17'
+ 24: 255, # '\x18'
+ 25: 255, # '\x19'
+ 26: 255, # '\x1a'
+ 27: 255, # '\x1b'
+ 28: 255, # '\x1c'
+ 29: 255, # '\x1d'
+ 30: 255, # '\x1e'
+ 31: 255, # '\x1f'
+ 32: 253, # ' '
+ 33: 253, # '!'
+ 34: 253, # '"'
+ 35: 253, # '#'
+ 36: 253, # '$'
+ 37: 253, # '%'
+ 38: 253, # '&'
+ 39: 253, # "'"
+ 40: 253, # '('
+ 41: 253, # ')'
+ 42: 253, # '*'
+ 43: 253, # '+'
+ 44: 253, # ','
+ 45: 253, # '-'
+ 46: 253, # '.'
+ 47: 253, # '/'
+ 48: 252, # '0'
+ 49: 252, # '1'
+ 50: 252, # '2'
+ 51: 252, # '3'
+ 52: 252, # '4'
+ 53: 252, # '5'
+ 54: 252, # '6'
+ 55: 252, # '7'
+ 56: 252, # '8'
+ 57: 252, # '9'
+ 58: 253, # ':'
+ 59: 253, # ';'
+ 60: 253, # '<'
+ 61: 253, # '='
+ 62: 253, # '>'
+ 63: 253, # '?'
+ 64: 253, # '@'
+ 65: 82, # 'A'
+ 66: 100, # 'B'
+ 67: 104, # 'C'
+ 68: 94, # 'D'
+ 69: 98, # 'E'
+ 70: 101, # 'F'
+ 71: 116, # 'G'
+ 72: 102, # 'H'
+ 73: 111, # 'I'
+ 74: 187, # 'J'
+ 75: 117, # 'K'
+ 76: 92, # 'L'
+ 77: 88, # 'M'
+ 78: 113, # 'N'
+ 79: 85, # 'O'
+ 80: 79, # 'P'
+ 81: 118, # 'Q'
+ 82: 105, # 'R'
+ 83: 83, # 'S'
+ 84: 67, # 'T'
+ 85: 114, # 'U'
+ 86: 119, # 'V'
+ 87: 95, # 'W'
+ 88: 99, # 'X'
+ 89: 109, # 'Y'
+ 90: 188, # 'Z'
+ 91: 253, # '['
+ 92: 253, # '\\'
+ 93: 253, # ']'
+ 94: 253, # '^'
+ 95: 253, # '_'
+ 96: 253, # '`'
+ 97: 72, # 'a'
+ 98: 70, # 'b'
+ 99: 80, # 'c'
+ 100: 81, # 'd'
+ 101: 60, # 'e'
+ 102: 96, # 'f'
+ 103: 93, # 'g'
+ 104: 89, # 'h'
+ 105: 68, # 'i'
+ 106: 120, # 'j'
+ 107: 97, # 'k'
+ 108: 77, # 'l'
+ 109: 86, # 'm'
+ 110: 69, # 'n'
+ 111: 55, # 'o'
+ 112: 78, # 'p'
+ 113: 115, # 'q'
+ 114: 65, # 'r'
+ 115: 66, # 's'
+ 116: 58, # 't'
+ 117: 76, # 'u'
+ 118: 106, # 'v'
+ 119: 103, # 'w'
+ 120: 87, # 'x'
+ 121: 107, # 'y'
+ 122: 112, # 'z'
+ 123: 253, # '{'
+ 124: 253, # '|'
+ 125: 253, # '}'
+ 126: 253, # '~'
+ 127: 253, # '\x7f'
+ 128: 255, # '\x80'
+ 129: 255, # '\x81'
+ 130: 255, # '\x82'
+ 131: 255, # '\x83'
+ 132: 255, # '\x84'
+ 133: 255, # '\x85'
+ 134: 255, # '\x86'
+ 135: 255, # '\x87'
+ 136: 255, # '\x88'
+ 137: 255, # '\x89'
+ 138: 255, # '\x8a'
+ 139: 255, # '\x8b'
+ 140: 255, # '\x8c'
+ 141: 255, # '\x8d'
+ 142: 255, # '\x8e'
+ 143: 255, # '\x8f'
+ 144: 255, # '\x90'
+ 145: 255, # '\x91'
+ 146: 255, # '\x92'
+ 147: 255, # '\x93'
+ 148: 255, # '\x94'
+ 149: 255, # '\x95'
+ 150: 255, # '\x96'
+ 151: 255, # '\x97'
+ 152: 255, # '\x98'
+ 153: 255, # '\x99'
+ 154: 255, # '\x9a'
+ 155: 255, # '\x9b'
+ 156: 255, # '\x9c'
+ 157: 255, # '\x9d'
+ 158: 255, # '\x9e'
+ 159: 255, # '\x9f'
+ 160: 253, # '\xa0'
+ 161: 233, # '‘'
+ 162: 90, # '’'
+ 163: 253, # '£'
+ 164: 253, # '€'
+ 165: 253, # '₯'
+ 166: 253, # '¦'
+ 167: 253, # '§'
+ 168: 253, # '¨'
+ 169: 253, # '©'
+ 170: 253, # 'ͺ'
+ 171: 253, # '«'
+ 172: 253, # '¬'
+ 173: 74, # '\xad'
+ 174: 253, # None
+ 175: 253, # '―'
+ 176: 253, # '°'
+ 177: 253, # '±'
+ 178: 253, # '²'
+ 179: 253, # '³'
+ 180: 247, # '΄'
+ 181: 248, # '΅'
+ 182: 61, # 'Ά'
+ 183: 36, # '·'
+ 184: 46, # 'Έ'
+ 185: 71, # 'Ή'
+ 186: 73, # 'Ί'
+ 187: 253, # '»'
+ 188: 54, # 'Ό'
+ 189: 253, # '½'
+ 190: 108, # 'Ύ'
+ 191: 123, # 'Ώ'
+ 192: 110, # 'ΐ'
+ 193: 31, # 'Α'
+ 194: 51, # 'Β'
+ 195: 43, # 'Γ'
+ 196: 41, # 'Δ'
+ 197: 34, # 'Ε'
+ 198: 91, # 'Ζ'
+ 199: 40, # 'Η'
+ 200: 52, # 'Θ'
+ 201: 47, # 'Ι'
+ 202: 44, # 'Κ'
+ 203: 53, # 'Λ'
+ 204: 38, # 'Μ'
+ 205: 49, # 'Ν'
+ 206: 59, # 'Ξ'
+ 207: 39, # 'Ο'
+ 208: 35, # 'Π'
+ 209: 48, # 'Ρ'
+ 210: 250, # None
+ 211: 37, # 'Σ'
+ 212: 33, # 'Τ'
+ 213: 45, # 'Υ'
+ 214: 56, # 'Φ'
+ 215: 50, # 'Χ'
+ 216: 84, # 'Ψ'
+ 217: 57, # 'Ω'
+ 218: 120, # 'Ϊ'
+ 219: 121, # 'Ϋ'
+ 220: 17, # 'ά'
+ 221: 18, # 'έ'
+ 222: 22, # 'ή'
+ 223: 15, # 'ί'
+ 224: 124, # 'ΰ'
+ 225: 1, # 'α'
+ 226: 29, # 'β'
+ 227: 20, # 'γ'
+ 228: 21, # 'δ'
+ 229: 3, # 'ε'
+ 230: 32, # 'ζ'
+ 231: 13, # 'η'
+ 232: 25, # 'θ'
+ 233: 5, # 'ι'
+ 234: 11, # 'κ'
+ 235: 16, # 'λ'
+ 236: 10, # 'μ'
+ 237: 6, # 'ν'
+ 238: 30, # 'ξ'
+ 239: 4, # 'ο'
+ 240: 9, # 'π'
+ 241: 8, # 'ρ'
+ 242: 14, # 'ς'
+ 243: 7, # 'σ'
+ 244: 2, # 'τ'
+ 245: 12, # 'υ'
+ 246: 28, # 'φ'
+ 247: 23, # 'χ'
+ 248: 42, # 'ψ'
+ 249: 24, # 'ω'
+ 250: 64, # 'ϊ'
+ 251: 75, # 'ϋ'
+ 252: 19, # 'ό'
+ 253: 26, # 'ύ'
+ 254: 27, # 'ώ'
+ 255: 253, # None
+}
+
+ISO_8859_7_GREEK_MODEL = SingleByteCharSetModel(
+ charset_name="ISO-8859-7",
+ language="Greek",
+ char_to_order_map=ISO_8859_7_GREEK_CHAR_TO_ORDER,
+ language_model=GREEK_LANG_MODEL,
+ typical_positive_ratio=0.982851,
+ keep_ascii_letters=False,
+ alphabet="ΆΈΉΊΌΎΏΑΒΓΔΕΖΗΘΙΚΛΜΝΞΟΠΡΣΤΥΦΧΨΩάέήίαβγδεζηθικλμνξοπρςστυφχψωόύώ",
+)
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/langhebrewmodel.py b/env-llmeval/lib/python3.10/site-packages/chardet/langhebrewmodel.py
new file mode 100644
index 0000000000000000000000000000000000000000..86b3c5e64558ea9cd8ed4a4b603a8799fb2312e6
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/langhebrewmodel.py
@@ -0,0 +1,4380 @@
+from chardet.sbcharsetprober import SingleByteCharSetModel
+
+# 3: Positive
+# 2: Likely
+# 1: Unlikely
+# 0: Negative
+
+HEBREW_LANG_MODEL = {
+ 50: { # 'a'
+ 50: 0, # 'a'
+ 60: 1, # 'c'
+ 61: 1, # 'd'
+ 42: 1, # 'e'
+ 53: 1, # 'i'
+ 56: 2, # 'l'
+ 54: 2, # 'n'
+ 49: 0, # 'o'
+ 51: 2, # 'r'
+ 43: 1, # 's'
+ 44: 2, # 't'
+ 63: 1, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 0, # 'א'
+ 8: 0, # 'ב'
+ 20: 0, # 'ג'
+ 16: 0, # 'ד'
+ 3: 1, # 'ה'
+ 2: 0, # 'ו'
+ 24: 0, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 0, # 'י'
+ 25: 0, # 'ך'
+ 15: 0, # 'כ'
+ 4: 0, # 'ל'
+ 11: 0, # 'ם'
+ 6: 1, # 'מ'
+ 23: 0, # 'ן'
+ 12: 0, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 0, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 0, # 'צ'
+ 17: 1, # 'ק'
+ 7: 0, # 'ר'
+ 10: 1, # 'ש'
+ 5: 0, # 'ת'
+ 32: 0, # '–'
+ 52: 1, # '’'
+ 47: 0, # '“'
+ 46: 1, # '”'
+ 58: 0, # '†'
+ 40: 1, # '…'
+ },
+ 60: { # 'c'
+ 50: 1, # 'a'
+ 60: 1, # 'c'
+ 61: 0, # 'd'
+ 42: 1, # 'e'
+ 53: 1, # 'i'
+ 56: 1, # 'l'
+ 54: 0, # 'n'
+ 49: 1, # 'o'
+ 51: 1, # 'r'
+ 43: 1, # 's'
+ 44: 2, # 't'
+ 63: 1, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 1, # 'א'
+ 8: 0, # 'ב'
+ 20: 0, # 'ג'
+ 16: 0, # 'ד'
+ 3: 1, # 'ה'
+ 2: 0, # 'ו'
+ 24: 0, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 0, # 'י'
+ 25: 0, # 'ך'
+ 15: 0, # 'כ'
+ 4: 0, # 'ל'
+ 11: 0, # 'ם'
+ 6: 1, # 'מ'
+ 23: 0, # 'ן'
+ 12: 1, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 0, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 0, # 'צ'
+ 17: 0, # 'ק'
+ 7: 0, # 'ר'
+ 10: 0, # 'ש'
+ 5: 0, # 'ת'
+ 32: 0, # '–'
+ 52: 0, # '’'
+ 47: 0, # '“'
+ 46: 1, # '”'
+ 58: 0, # '†'
+ 40: 1, # '…'
+ },
+ 61: { # 'd'
+ 50: 1, # 'a'
+ 60: 0, # 'c'
+ 61: 1, # 'd'
+ 42: 1, # 'e'
+ 53: 1, # 'i'
+ 56: 1, # 'l'
+ 54: 1, # 'n'
+ 49: 2, # 'o'
+ 51: 1, # 'r'
+ 43: 1, # 's'
+ 44: 0, # 't'
+ 63: 1, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 0, # 'א'
+ 8: 0, # 'ב'
+ 20: 0, # 'ג'
+ 16: 0, # 'ד'
+ 3: 1, # 'ה'
+ 2: 0, # 'ו'
+ 24: 0, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 0, # 'י'
+ 25: 0, # 'ך'
+ 15: 0, # 'כ'
+ 4: 0, # 'ל'
+ 11: 0, # 'ם'
+ 6: 0, # 'מ'
+ 23: 0, # 'ן'
+ 12: 0, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 0, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 0, # 'צ'
+ 17: 0, # 'ק'
+ 7: 0, # 'ר'
+ 10: 0, # 'ש'
+ 5: 0, # 'ת'
+ 32: 1, # '–'
+ 52: 1, # '’'
+ 47: 0, # '“'
+ 46: 1, # '”'
+ 58: 0, # '†'
+ 40: 1, # '…'
+ },
+ 42: { # 'e'
+ 50: 1, # 'a'
+ 60: 1, # 'c'
+ 61: 2, # 'd'
+ 42: 1, # 'e'
+ 53: 1, # 'i'
+ 56: 2, # 'l'
+ 54: 2, # 'n'
+ 49: 1, # 'o'
+ 51: 2, # 'r'
+ 43: 2, # 's'
+ 44: 2, # 't'
+ 63: 1, # 'u'
+ 34: 1, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 0, # 'א'
+ 8: 0, # 'ב'
+ 20: 0, # 'ג'
+ 16: 0, # 'ד'
+ 3: 0, # 'ה'
+ 2: 0, # 'ו'
+ 24: 0, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 0, # 'י'
+ 25: 0, # 'ך'
+ 15: 0, # 'כ'
+ 4: 0, # 'ל'
+ 11: 0, # 'ם'
+ 6: 0, # 'מ'
+ 23: 0, # 'ן'
+ 12: 0, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 1, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 0, # 'צ'
+ 17: 0, # 'ק'
+ 7: 0, # 'ר'
+ 10: 0, # 'ש'
+ 5: 0, # 'ת'
+ 32: 1, # '–'
+ 52: 2, # '’'
+ 47: 0, # '“'
+ 46: 1, # '”'
+ 58: 0, # '†'
+ 40: 1, # '…'
+ },
+ 53: { # 'i'
+ 50: 1, # 'a'
+ 60: 2, # 'c'
+ 61: 1, # 'd'
+ 42: 1, # 'e'
+ 53: 0, # 'i'
+ 56: 1, # 'l'
+ 54: 2, # 'n'
+ 49: 2, # 'o'
+ 51: 1, # 'r'
+ 43: 2, # 's'
+ 44: 2, # 't'
+ 63: 1, # 'u'
+ 34: 0, # '\xa0'
+ 55: 1, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 0, # 'א'
+ 8: 0, # 'ב'
+ 20: 0, # 'ג'
+ 16: 0, # 'ד'
+ 3: 0, # 'ה'
+ 2: 0, # 'ו'
+ 24: 0, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 0, # 'י'
+ 25: 0, # 'ך'
+ 15: 0, # 'כ'
+ 4: 0, # 'ל'
+ 11: 0, # 'ם'
+ 6: 0, # 'מ'
+ 23: 0, # 'ן'
+ 12: 0, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 0, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 0, # 'צ'
+ 17: 0, # 'ק'
+ 7: 0, # 'ר'
+ 10: 0, # 'ש'
+ 5: 0, # 'ת'
+ 32: 0, # '–'
+ 52: 1, # '’'
+ 47: 0, # '“'
+ 46: 0, # '”'
+ 58: 0, # '†'
+ 40: 0, # '…'
+ },
+ 56: { # 'l'
+ 50: 1, # 'a'
+ 60: 1, # 'c'
+ 61: 1, # 'd'
+ 42: 2, # 'e'
+ 53: 2, # 'i'
+ 56: 2, # 'l'
+ 54: 1, # 'n'
+ 49: 1, # 'o'
+ 51: 0, # 'r'
+ 43: 1, # 's'
+ 44: 1, # 't'
+ 63: 1, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 0, # 'א'
+ 8: 0, # 'ב'
+ 20: 0, # 'ג'
+ 16: 0, # 'ד'
+ 3: 0, # 'ה'
+ 2: 0, # 'ו'
+ 24: 0, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 0, # 'י'
+ 25: 0, # 'ך'
+ 15: 0, # 'כ'
+ 4: 0, # 'ל'
+ 11: 0, # 'ם'
+ 6: 0, # 'מ'
+ 23: 0, # 'ן'
+ 12: 0, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 0, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 0, # 'צ'
+ 17: 0, # 'ק'
+ 7: 0, # 'ר'
+ 10: 0, # 'ש'
+ 5: 0, # 'ת'
+ 32: 0, # '–'
+ 52: 1, # '’'
+ 47: 0, # '“'
+ 46: 1, # '”'
+ 58: 0, # '†'
+ 40: 1, # '…'
+ },
+ 54: { # 'n'
+ 50: 1, # 'a'
+ 60: 1, # 'c'
+ 61: 1, # 'd'
+ 42: 1, # 'e'
+ 53: 1, # 'i'
+ 56: 1, # 'l'
+ 54: 1, # 'n'
+ 49: 1, # 'o'
+ 51: 0, # 'r'
+ 43: 1, # 's'
+ 44: 2, # 't'
+ 63: 1, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 0, # 'א'
+ 8: 0, # 'ב'
+ 20: 0, # 'ג'
+ 16: 0, # 'ד'
+ 3: 1, # 'ה'
+ 2: 0, # 'ו'
+ 24: 0, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 0, # 'י'
+ 25: 0, # 'ך'
+ 15: 0, # 'כ'
+ 4: 0, # 'ל'
+ 11: 0, # 'ם'
+ 6: 0, # 'מ'
+ 23: 0, # 'ן'
+ 12: 0, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 0, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 0, # 'צ'
+ 17: 0, # 'ק'
+ 7: 0, # 'ר'
+ 10: 0, # 'ש'
+ 5: 0, # 'ת'
+ 32: 0, # '–'
+ 52: 2, # '’'
+ 47: 0, # '“'
+ 46: 1, # '”'
+ 58: 0, # '†'
+ 40: 1, # '…'
+ },
+ 49: { # 'o'
+ 50: 1, # 'a'
+ 60: 1, # 'c'
+ 61: 1, # 'd'
+ 42: 1, # 'e'
+ 53: 1, # 'i'
+ 56: 1, # 'l'
+ 54: 2, # 'n'
+ 49: 1, # 'o'
+ 51: 2, # 'r'
+ 43: 1, # 's'
+ 44: 1, # 't'
+ 63: 1, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 0, # 'א'
+ 8: 0, # 'ב'
+ 20: 0, # 'ג'
+ 16: 0, # 'ד'
+ 3: 0, # 'ה'
+ 2: 0, # 'ו'
+ 24: 0, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 0, # 'י'
+ 25: 0, # 'ך'
+ 15: 0, # 'כ'
+ 4: 0, # 'ל'
+ 11: 0, # 'ם'
+ 6: 0, # 'מ'
+ 23: 0, # 'ן'
+ 12: 0, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 0, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 0, # 'צ'
+ 17: 0, # 'ק'
+ 7: 0, # 'ר'
+ 10: 0, # 'ש'
+ 5: 0, # 'ת'
+ 32: 0, # '–'
+ 52: 1, # '’'
+ 47: 0, # '“'
+ 46: 1, # '”'
+ 58: 0, # '†'
+ 40: 1, # '…'
+ },
+ 51: { # 'r'
+ 50: 2, # 'a'
+ 60: 1, # 'c'
+ 61: 1, # 'd'
+ 42: 2, # 'e'
+ 53: 1, # 'i'
+ 56: 1, # 'l'
+ 54: 1, # 'n'
+ 49: 2, # 'o'
+ 51: 1, # 'r'
+ 43: 1, # 's'
+ 44: 1, # 't'
+ 63: 1, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 0, # 'א'
+ 8: 0, # 'ב'
+ 20: 0, # 'ג'
+ 16: 0, # 'ד'
+ 3: 0, # 'ה'
+ 2: 0, # 'ו'
+ 24: 0, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 0, # 'י'
+ 25: 0, # 'ך'
+ 15: 0, # 'כ'
+ 4: 0, # 'ל'
+ 11: 0, # 'ם'
+ 6: 0, # 'מ'
+ 23: 0, # 'ן'
+ 12: 0, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 0, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 0, # 'צ'
+ 17: 0, # 'ק'
+ 7: 0, # 'ר'
+ 10: 0, # 'ש'
+ 5: 0, # 'ת'
+ 32: 0, # '–'
+ 52: 2, # '’'
+ 47: 0, # '“'
+ 46: 1, # '”'
+ 58: 0, # '†'
+ 40: 1, # '…'
+ },
+ 43: { # 's'
+ 50: 1, # 'a'
+ 60: 1, # 'c'
+ 61: 0, # 'd'
+ 42: 2, # 'e'
+ 53: 1, # 'i'
+ 56: 1, # 'l'
+ 54: 1, # 'n'
+ 49: 1, # 'o'
+ 51: 1, # 'r'
+ 43: 1, # 's'
+ 44: 2, # 't'
+ 63: 1, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 0, # 'א'
+ 8: 0, # 'ב'
+ 20: 0, # 'ג'
+ 16: 0, # 'ד'
+ 3: 0, # 'ה'
+ 2: 0, # 'ו'
+ 24: 0, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 0, # 'י'
+ 25: 0, # 'ך'
+ 15: 0, # 'כ'
+ 4: 0, # 'ל'
+ 11: 0, # 'ם'
+ 6: 0, # 'מ'
+ 23: 0, # 'ן'
+ 12: 0, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 0, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 0, # 'צ'
+ 17: 0, # 'ק'
+ 7: 0, # 'ר'
+ 10: 0, # 'ש'
+ 5: 0, # 'ת'
+ 32: 0, # '–'
+ 52: 1, # '’'
+ 47: 0, # '“'
+ 46: 2, # '”'
+ 58: 0, # '†'
+ 40: 2, # '…'
+ },
+ 44: { # 't'
+ 50: 1, # 'a'
+ 60: 1, # 'c'
+ 61: 0, # 'd'
+ 42: 2, # 'e'
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+ 17: 3, # 'ק'
+ 7: 3, # 'ר'
+ 10: 3, # 'ש'
+ 5: 3, # 'ת'
+ 32: 0, # '–'
+ 52: 0, # '’'
+ 47: 0, # '“'
+ 46: 1, # '”'
+ 58: 0, # '†'
+ 40: 2, # '…'
+ },
+ 10: { # 'ש'
+ 50: 0, # 'a'
+ 60: 0, # 'c'
+ 61: 0, # 'd'
+ 42: 0, # 'e'
+ 53: 0, # 'i'
+ 56: 0, # 'l'
+ 54: 0, # 'n'
+ 49: 0, # 'o'
+ 51: 0, # 'r'
+ 43: 0, # 's'
+ 44: 0, # 't'
+ 63: 0, # 'u'
+ 34: 1, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 1, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 1, # 'ִ'
+ 37: 1, # 'ֵ'
+ 36: 1, # 'ֶ'
+ 31: 1, # 'ַ'
+ 29: 1, # 'ָ'
+ 35: 1, # 'ֹ'
+ 62: 1, # 'ֻ'
+ 28: 2, # 'ּ'
+ 38: 3, # 'ׁ'
+ 45: 2, # 'ׂ'
+ 9: 3, # 'א'
+ 8: 3, # 'ב'
+ 20: 3, # 'ג'
+ 16: 3, # 'ד'
+ 3: 3, # 'ה'
+ 2: 3, # 'ו'
+ 24: 2, # 'ז'
+ 14: 3, # 'ח'
+ 22: 3, # 'ט'
+ 1: 3, # 'י'
+ 25: 3, # 'ך'
+ 15: 3, # 'כ'
+ 4: 3, # 'ל'
+ 11: 3, # 'ם'
+ 6: 3, # 'מ'
+ 23: 2, # 'ן'
+ 12: 3, # 'נ'
+ 19: 2, # 'ס'
+ 13: 3, # 'ע'
+ 26: 2, # 'ף'
+ 18: 3, # 'פ'
+ 27: 1, # 'ץ'
+ 21: 2, # 'צ'
+ 17: 3, # 'ק'
+ 7: 3, # 'ר'
+ 10: 3, # 'ש'
+ 5: 3, # 'ת'
+ 32: 0, # '–'
+ 52: 0, # '’'
+ 47: 0, # '“'
+ 46: 1, # '”'
+ 58: 0, # '†'
+ 40: 1, # '…'
+ },
+ 5: { # 'ת'
+ 50: 0, # 'a'
+ 60: 0, # 'c'
+ 61: 0, # 'd'
+ 42: 0, # 'e'
+ 53: 0, # 'i'
+ 56: 0, # 'l'
+ 54: 0, # 'n'
+ 49: 0, # 'o'
+ 51: 0, # 'r'
+ 43: 0, # 's'
+ 44: 0, # 't'
+ 63: 0, # 'u'
+ 34: 1, # '\xa0'
+ 55: 0, # '´'
+ 48: 1, # '¼'
+ 39: 1, # '½'
+ 57: 0, # '¾'
+ 30: 2, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 2, # 'ִ'
+ 37: 2, # 'ֵ'
+ 36: 2, # 'ֶ'
+ 31: 2, # 'ַ'
+ 29: 2, # 'ָ'
+ 35: 1, # 'ֹ'
+ 62: 1, # 'ֻ'
+ 28: 2, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 3, # 'א'
+ 8: 3, # 'ב'
+ 20: 3, # 'ג'
+ 16: 2, # 'ד'
+ 3: 3, # 'ה'
+ 2: 3, # 'ו'
+ 24: 2, # 'ז'
+ 14: 3, # 'ח'
+ 22: 2, # 'ט'
+ 1: 3, # 'י'
+ 25: 2, # 'ך'
+ 15: 3, # 'כ'
+ 4: 3, # 'ל'
+ 11: 3, # 'ם'
+ 6: 3, # 'מ'
+ 23: 3, # 'ן'
+ 12: 3, # 'נ'
+ 19: 2, # 'ס'
+ 13: 3, # 'ע'
+ 26: 2, # 'ף'
+ 18: 3, # 'פ'
+ 27: 1, # 'ץ'
+ 21: 2, # 'צ'
+ 17: 3, # 'ק'
+ 7: 3, # 'ר'
+ 10: 3, # 'ש'
+ 5: 3, # 'ת'
+ 32: 1, # '–'
+ 52: 1, # '’'
+ 47: 0, # '“'
+ 46: 0, # '”'
+ 58: 0, # '†'
+ 40: 2, # '…'
+ },
+ 32: { # '–'
+ 50: 0, # 'a'
+ 60: 0, # 'c'
+ 61: 0, # 'd'
+ 42: 0, # 'e'
+ 53: 0, # 'i'
+ 56: 0, # 'l'
+ 54: 1, # 'n'
+ 49: 0, # 'o'
+ 51: 0, # 'r'
+ 43: 0, # 's'
+ 44: 0, # 't'
+ 63: 0, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 1, # 'א'
+ 8: 1, # 'ב'
+ 20: 1, # 'ג'
+ 16: 1, # 'ד'
+ 3: 1, # 'ה'
+ 2: 1, # 'ו'
+ 24: 0, # 'ז'
+ 14: 1, # 'ח'
+ 22: 0, # 'ט'
+ 1: 1, # 'י'
+ 25: 0, # 'ך'
+ 15: 1, # 'כ'
+ 4: 1, # 'ל'
+ 11: 0, # 'ם'
+ 6: 1, # 'מ'
+ 23: 0, # 'ן'
+ 12: 0, # 'נ'
+ 19: 1, # 'ס'
+ 13: 1, # 'ע'
+ 26: 0, # 'ף'
+ 18: 1, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 1, # 'צ'
+ 17: 0, # 'ק'
+ 7: 1, # 'ר'
+ 10: 1, # 'ש'
+ 5: 1, # 'ת'
+ 32: 0, # '–'
+ 52: 0, # '’'
+ 47: 0, # '“'
+ 46: 0, # '”'
+ 58: 0, # '†'
+ 40: 0, # '…'
+ },
+ 52: { # '’'
+ 50: 1, # 'a'
+ 60: 0, # 'c'
+ 61: 1, # 'd'
+ 42: 1, # 'e'
+ 53: 1, # 'i'
+ 56: 1, # 'l'
+ 54: 0, # 'n'
+ 49: 0, # 'o'
+ 51: 1, # 'r'
+ 43: 2, # 's'
+ 44: 2, # 't'
+ 63: 1, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 0, # 'א'
+ 8: 0, # 'ב'
+ 20: 0, # 'ג'
+ 16: 0, # 'ד'
+ 3: 0, # 'ה'
+ 2: 1, # 'ו'
+ 24: 0, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 0, # 'י'
+ 25: 0, # 'ך'
+ 15: 0, # 'כ'
+ 4: 0, # 'ל'
+ 11: 0, # 'ם'
+ 6: 1, # 'מ'
+ 23: 0, # 'ן'
+ 12: 0, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 0, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 0, # 'צ'
+ 17: 0, # 'ק'
+ 7: 0, # 'ר'
+ 10: 0, # 'ש'
+ 5: 1, # 'ת'
+ 32: 0, # '–'
+ 52: 0, # '’'
+ 47: 0, # '“'
+ 46: 0, # '”'
+ 58: 0, # '†'
+ 40: 0, # '…'
+ },
+ 47: { # '“'
+ 50: 1, # 'a'
+ 60: 1, # 'c'
+ 61: 1, # 'd'
+ 42: 1, # 'e'
+ 53: 1, # 'i'
+ 56: 1, # 'l'
+ 54: 1, # 'n'
+ 49: 1, # 'o'
+ 51: 1, # 'r'
+ 43: 1, # 's'
+ 44: 1, # 't'
+ 63: 1, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 2, # 'א'
+ 8: 1, # 'ב'
+ 20: 1, # 'ג'
+ 16: 1, # 'ד'
+ 3: 1, # 'ה'
+ 2: 1, # 'ו'
+ 24: 1, # 'ז'
+ 14: 1, # 'ח'
+ 22: 1, # 'ט'
+ 1: 1, # 'י'
+ 25: 0, # 'ך'
+ 15: 1, # 'כ'
+ 4: 1, # 'ל'
+ 11: 0, # 'ם'
+ 6: 1, # 'מ'
+ 23: 0, # 'ן'
+ 12: 1, # 'נ'
+ 19: 1, # 'ס'
+ 13: 1, # 'ע'
+ 26: 0, # 'ף'
+ 18: 1, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 1, # 'צ'
+ 17: 1, # 'ק'
+ 7: 1, # 'ר'
+ 10: 1, # 'ש'
+ 5: 1, # 'ת'
+ 32: 0, # '–'
+ 52: 0, # '’'
+ 47: 0, # '“'
+ 46: 0, # '”'
+ 58: 0, # '†'
+ 40: 0, # '…'
+ },
+ 46: { # '”'
+ 50: 0, # 'a'
+ 60: 0, # 'c'
+ 61: 0, # 'd'
+ 42: 0, # 'e'
+ 53: 0, # 'i'
+ 56: 0, # 'l'
+ 54: 0, # 'n'
+ 49: 0, # 'o'
+ 51: 0, # 'r'
+ 43: 0, # 's'
+ 44: 1, # 't'
+ 63: 0, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 1, # 'א'
+ 8: 1, # 'ב'
+ 20: 1, # 'ג'
+ 16: 0, # 'ד'
+ 3: 0, # 'ה'
+ 2: 0, # 'ו'
+ 24: 0, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 1, # 'י'
+ 25: 0, # 'ך'
+ 15: 1, # 'כ'
+ 4: 1, # 'ל'
+ 11: 0, # 'ם'
+ 6: 1, # 'מ'
+ 23: 0, # 'ן'
+ 12: 0, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 0, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 1, # 'צ'
+ 17: 0, # 'ק'
+ 7: 1, # 'ר'
+ 10: 0, # 'ש'
+ 5: 0, # 'ת'
+ 32: 0, # '–'
+ 52: 0, # '’'
+ 47: 0, # '“'
+ 46: 0, # '”'
+ 58: 0, # '†'
+ 40: 0, # '…'
+ },
+ 58: { # '†'
+ 50: 0, # 'a'
+ 60: 0, # 'c'
+ 61: 0, # 'd'
+ 42: 0, # 'e'
+ 53: 0, # 'i'
+ 56: 0, # 'l'
+ 54: 0, # 'n'
+ 49: 0, # 'o'
+ 51: 0, # 'r'
+ 43: 0, # 's'
+ 44: 0, # 't'
+ 63: 0, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 0, # 'א'
+ 8: 0, # 'ב'
+ 20: 0, # 'ג'
+ 16: 0, # 'ד'
+ 3: 0, # 'ה'
+ 2: 0, # 'ו'
+ 24: 0, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 0, # 'י'
+ 25: 0, # 'ך'
+ 15: 0, # 'כ'
+ 4: 0, # 'ל'
+ 11: 0, # 'ם'
+ 6: 0, # 'מ'
+ 23: 0, # 'ן'
+ 12: 0, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 0, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 0, # 'צ'
+ 17: 0, # 'ק'
+ 7: 0, # 'ר'
+ 10: 0, # 'ש'
+ 5: 0, # 'ת'
+ 32: 0, # '–'
+ 52: 0, # '’'
+ 47: 0, # '“'
+ 46: 0, # '”'
+ 58: 2, # '†'
+ 40: 0, # '…'
+ },
+ 40: { # '…'
+ 50: 1, # 'a'
+ 60: 1, # 'c'
+ 61: 1, # 'd'
+ 42: 1, # 'e'
+ 53: 1, # 'i'
+ 56: 0, # 'l'
+ 54: 1, # 'n'
+ 49: 0, # 'o'
+ 51: 1, # 'r'
+ 43: 1, # 's'
+ 44: 1, # 't'
+ 63: 0, # 'u'
+ 34: 0, # '\xa0'
+ 55: 0, # '´'
+ 48: 0, # '¼'
+ 39: 0, # '½'
+ 57: 0, # '¾'
+ 30: 0, # 'ְ'
+ 59: 0, # 'ֱ'
+ 41: 0, # 'ֲ'
+ 33: 0, # 'ִ'
+ 37: 0, # 'ֵ'
+ 36: 0, # 'ֶ'
+ 31: 0, # 'ַ'
+ 29: 0, # 'ָ'
+ 35: 0, # 'ֹ'
+ 62: 0, # 'ֻ'
+ 28: 0, # 'ּ'
+ 38: 0, # 'ׁ'
+ 45: 0, # 'ׂ'
+ 9: 1, # 'א'
+ 8: 0, # 'ב'
+ 20: 0, # 'ג'
+ 16: 0, # 'ד'
+ 3: 1, # 'ה'
+ 2: 1, # 'ו'
+ 24: 1, # 'ז'
+ 14: 0, # 'ח'
+ 22: 0, # 'ט'
+ 1: 1, # 'י'
+ 25: 0, # 'ך'
+ 15: 1, # 'כ'
+ 4: 1, # 'ל'
+ 11: 0, # 'ם'
+ 6: 1, # 'מ'
+ 23: 0, # 'ן'
+ 12: 1, # 'נ'
+ 19: 0, # 'ס'
+ 13: 0, # 'ע'
+ 26: 0, # 'ף'
+ 18: 1, # 'פ'
+ 27: 0, # 'ץ'
+ 21: 0, # 'צ'
+ 17: 0, # 'ק'
+ 7: 1, # 'ר'
+ 10: 1, # 'ש'
+ 5: 1, # 'ת'
+ 32: 0, # '–'
+ 52: 0, # '’'
+ 47: 0, # '“'
+ 46: 1, # '”'
+ 58: 0, # '†'
+ 40: 2, # '…'
+ },
+}
+
+# 255: Undefined characters that did not exist in training text
+# 254: Carriage/Return
+# 253: symbol (punctuation) that does not belong to word
+# 252: 0 - 9
+# 251: Control characters
+
+# Character Mapping Table(s):
+WINDOWS_1255_HEBREW_CHAR_TO_ORDER = {
+ 0: 255, # '\x00'
+ 1: 255, # '\x01'
+ 2: 255, # '\x02'
+ 3: 255, # '\x03'
+ 4: 255, # '\x04'
+ 5: 255, # '\x05'
+ 6: 255, # '\x06'
+ 7: 255, # '\x07'
+ 8: 255, # '\x08'
+ 9: 255, # '\t'
+ 10: 254, # '\n'
+ 11: 255, # '\x0b'
+ 12: 255, # '\x0c'
+ 13: 254, # '\r'
+ 14: 255, # '\x0e'
+ 15: 255, # '\x0f'
+ 16: 255, # '\x10'
+ 17: 255, # '\x11'
+ 18: 255, # '\x12'
+ 19: 255, # '\x13'
+ 20: 255, # '\x14'
+ 21: 255, # '\x15'
+ 22: 255, # '\x16'
+ 23: 255, # '\x17'
+ 24: 255, # '\x18'
+ 25: 255, # '\x19'
+ 26: 255, # '\x1a'
+ 27: 255, # '\x1b'
+ 28: 255, # '\x1c'
+ 29: 255, # '\x1d'
+ 30: 255, # '\x1e'
+ 31: 255, # '\x1f'
+ 32: 253, # ' '
+ 33: 253, # '!'
+ 34: 253, # '"'
+ 35: 253, # '#'
+ 36: 253, # '$'
+ 37: 253, # '%'
+ 38: 253, # '&'
+ 39: 253, # "'"
+ 40: 253, # '('
+ 41: 253, # ')'
+ 42: 253, # '*'
+ 43: 253, # '+'
+ 44: 253, # ','
+ 45: 253, # '-'
+ 46: 253, # '.'
+ 47: 253, # '/'
+ 48: 252, # '0'
+ 49: 252, # '1'
+ 50: 252, # '2'
+ 51: 252, # '3'
+ 52: 252, # '4'
+ 53: 252, # '5'
+ 54: 252, # '6'
+ 55: 252, # '7'
+ 56: 252, # '8'
+ 57: 252, # '9'
+ 58: 253, # ':'
+ 59: 253, # ';'
+ 60: 253, # '<'
+ 61: 253, # '='
+ 62: 253, # '>'
+ 63: 253, # '?'
+ 64: 253, # '@'
+ 65: 69, # 'A'
+ 66: 91, # 'B'
+ 67: 79, # 'C'
+ 68: 80, # 'D'
+ 69: 92, # 'E'
+ 70: 89, # 'F'
+ 71: 97, # 'G'
+ 72: 90, # 'H'
+ 73: 68, # 'I'
+ 74: 111, # 'J'
+ 75: 112, # 'K'
+ 76: 82, # 'L'
+ 77: 73, # 'M'
+ 78: 95, # 'N'
+ 79: 85, # 'O'
+ 80: 78, # 'P'
+ 81: 121, # 'Q'
+ 82: 86, # 'R'
+ 83: 71, # 'S'
+ 84: 67, # 'T'
+ 85: 102, # 'U'
+ 86: 107, # 'V'
+ 87: 84, # 'W'
+ 88: 114, # 'X'
+ 89: 103, # 'Y'
+ 90: 115, # 'Z'
+ 91: 253, # '['
+ 92: 253, # '\\'
+ 93: 253, # ']'
+ 94: 253, # '^'
+ 95: 253, # '_'
+ 96: 253, # '`'
+ 97: 50, # 'a'
+ 98: 74, # 'b'
+ 99: 60, # 'c'
+ 100: 61, # 'd'
+ 101: 42, # 'e'
+ 102: 76, # 'f'
+ 103: 70, # 'g'
+ 104: 64, # 'h'
+ 105: 53, # 'i'
+ 106: 105, # 'j'
+ 107: 93, # 'k'
+ 108: 56, # 'l'
+ 109: 65, # 'm'
+ 110: 54, # 'n'
+ 111: 49, # 'o'
+ 112: 66, # 'p'
+ 113: 110, # 'q'
+ 114: 51, # 'r'
+ 115: 43, # 's'
+ 116: 44, # 't'
+ 117: 63, # 'u'
+ 118: 81, # 'v'
+ 119: 77, # 'w'
+ 120: 98, # 'x'
+ 121: 75, # 'y'
+ 122: 108, # 'z'
+ 123: 253, # '{'
+ 124: 253, # '|'
+ 125: 253, # '}'
+ 126: 253, # '~'
+ 127: 253, # '\x7f'
+ 128: 124, # '€'
+ 129: 202, # None
+ 130: 203, # '‚'
+ 131: 204, # 'ƒ'
+ 132: 205, # '„'
+ 133: 40, # '…'
+ 134: 58, # '†'
+ 135: 206, # '‡'
+ 136: 207, # 'ˆ'
+ 137: 208, # '‰'
+ 138: 209, # None
+ 139: 210, # '‹'
+ 140: 211, # None
+ 141: 212, # None
+ 142: 213, # None
+ 143: 214, # None
+ 144: 215, # None
+ 145: 83, # '‘'
+ 146: 52, # '’'
+ 147: 47, # '“'
+ 148: 46, # '”'
+ 149: 72, # '•'
+ 150: 32, # '–'
+ 151: 94, # '—'
+ 152: 216, # '˜'
+ 153: 113, # '™'
+ 154: 217, # None
+ 155: 109, # '›'
+ 156: 218, # None
+ 157: 219, # None
+ 158: 220, # None
+ 159: 221, # None
+ 160: 34, # '\xa0'
+ 161: 116, # '¡'
+ 162: 222, # '¢'
+ 163: 118, # '£'
+ 164: 100, # '₪'
+ 165: 223, # '¥'
+ 166: 224, # '¦'
+ 167: 117, # '§'
+ 168: 119, # '¨'
+ 169: 104, # '©'
+ 170: 125, # '×'
+ 171: 225, # '«'
+ 172: 226, # '¬'
+ 173: 87, # '\xad'
+ 174: 99, # '®'
+ 175: 227, # '¯'
+ 176: 106, # '°'
+ 177: 122, # '±'
+ 178: 123, # '²'
+ 179: 228, # '³'
+ 180: 55, # '´'
+ 181: 229, # 'µ'
+ 182: 230, # '¶'
+ 183: 101, # '·'
+ 184: 231, # '¸'
+ 185: 232, # '¹'
+ 186: 120, # '÷'
+ 187: 233, # '»'
+ 188: 48, # '¼'
+ 189: 39, # '½'
+ 190: 57, # '¾'
+ 191: 234, # '¿'
+ 192: 30, # 'ְ'
+ 193: 59, # 'ֱ'
+ 194: 41, # 'ֲ'
+ 195: 88, # 'ֳ'
+ 196: 33, # 'ִ'
+ 197: 37, # 'ֵ'
+ 198: 36, # 'ֶ'
+ 199: 31, # 'ַ'
+ 200: 29, # 'ָ'
+ 201: 35, # 'ֹ'
+ 202: 235, # None
+ 203: 62, # 'ֻ'
+ 204: 28, # 'ּ'
+ 205: 236, # 'ֽ'
+ 206: 126, # '־'
+ 207: 237, # 'ֿ'
+ 208: 238, # '׀'
+ 209: 38, # 'ׁ'
+ 210: 45, # 'ׂ'
+ 211: 239, # '׃'
+ 212: 240, # 'װ'
+ 213: 241, # 'ױ'
+ 214: 242, # 'ײ'
+ 215: 243, # '׳'
+ 216: 127, # '״'
+ 217: 244, # None
+ 218: 245, # None
+ 219: 246, # None
+ 220: 247, # None
+ 221: 248, # None
+ 222: 249, # None
+ 223: 250, # None
+ 224: 9, # 'א'
+ 225: 8, # 'ב'
+ 226: 20, # 'ג'
+ 227: 16, # 'ד'
+ 228: 3, # 'ה'
+ 229: 2, # 'ו'
+ 230: 24, # 'ז'
+ 231: 14, # 'ח'
+ 232: 22, # 'ט'
+ 233: 1, # 'י'
+ 234: 25, # 'ך'
+ 235: 15, # 'כ'
+ 236: 4, # 'ל'
+ 237: 11, # 'ם'
+ 238: 6, # 'מ'
+ 239: 23, # 'ן'
+ 240: 12, # 'נ'
+ 241: 19, # 'ס'
+ 242: 13, # 'ע'
+ 243: 26, # 'ף'
+ 244: 18, # 'פ'
+ 245: 27, # 'ץ'
+ 246: 21, # 'צ'
+ 247: 17, # 'ק'
+ 248: 7, # 'ר'
+ 249: 10, # 'ש'
+ 250: 5, # 'ת'
+ 251: 251, # None
+ 252: 252, # None
+ 253: 128, # '\u200e'
+ 254: 96, # '\u200f'
+ 255: 253, # None
+}
+
+WINDOWS_1255_HEBREW_MODEL = SingleByteCharSetModel(
+ charset_name="windows-1255",
+ language="Hebrew",
+ char_to_order_map=WINDOWS_1255_HEBREW_CHAR_TO_ORDER,
+ language_model=HEBREW_LANG_MODEL,
+ typical_positive_ratio=0.984004,
+ keep_ascii_letters=False,
+ alphabet="אבגדהוזחטיךכלםמןנסעףפץצקרשתװױײ",
+)
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/langthaimodel.py b/env-llmeval/lib/python3.10/site-packages/chardet/langthaimodel.py
new file mode 100644
index 0000000000000000000000000000000000000000..883fdb1eafea7c7122846bdd478da800375a55bd
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/langthaimodel.py
@@ -0,0 +1,4380 @@
+from chardet.sbcharsetprober import SingleByteCharSetModel
+
+# 3: Positive
+# 2: Likely
+# 1: Unlikely
+# 0: Negative
+
+THAI_LANG_MODEL = {
+ 5: { # 'ก'
+ 5: 2, # 'ก'
+ 30: 2, # 'ข'
+ 24: 2, # 'ค'
+ 8: 2, # 'ง'
+ 26: 2, # 'จ'
+ 52: 0, # 'ฉ'
+ 34: 1, # 'ช'
+ 51: 1, # 'ซ'
+ 47: 0, # 'ญ'
+ 58: 3, # 'ฎ'
+ 57: 2, # 'ฏ'
+ 49: 0, # 'ฐ'
+ 53: 0, # 'ฑ'
+ 55: 0, # 'ฒ'
+ 43: 2, # 'ณ'
+ 20: 2, # 'ด'
+ 19: 3, # 'ต'
+ 44: 0, # 'ถ'
+ 14: 2, # 'ท'
+ 48: 0, # 'ธ'
+ 3: 2, # 'น'
+ 17: 1, # 'บ'
+ 25: 2, # 'ป'
+ 39: 1, # 'ผ'
+ 62: 1, # 'ฝ'
+ 31: 1, # 'พ'
+ 54: 0, # 'ฟ'
+ 45: 1, # 'ภ'
+ 9: 2, # 'ม'
+ 16: 1, # 'ย'
+ 2: 3, # 'ร'
+ 61: 2, # 'ฤ'
+ 15: 3, # 'ล'
+ 12: 3, # 'ว'
+ 42: 2, # 'ศ'
+ 46: 3, # 'ษ'
+ 18: 2, # 'ส'
+ 21: 2, # 'ห'
+ 4: 3, # 'อ'
+ 63: 1, # 'ฯ'
+ 22: 2, # 'ะ'
+ 10: 3, # 'ั'
+ 1: 3, # 'า'
+ 36: 3, # 'ำ'
+ 23: 3, # 'ิ'
+ 13: 3, # 'ี'
+ 40: 0, # 'ึ'
+ 27: 2, # 'ื'
+ 32: 2, # 'ุ'
+ 35: 1, # 'ู'
+ 11: 2, # 'เ'
+ 28: 2, # 'แ'
+ 41: 1, # 'โ'
+ 29: 1, # 'ใ'
+ 33: 2, # 'ไ'
+ 50: 1, # 'ๆ'
+ 37: 3, # '็'
+ 6: 3, # '่'
+ 7: 3, # '้'
+ 38: 2, # '์'
+ 56: 0, # '๑'
+ 59: 0, # '๒'
+ 60: 0, # '๕'
+ },
+ 30: { # 'ข'
+ 5: 1, # 'ก'
+ 30: 0, # 'ข'
+ 24: 1, # 'ค'
+ 8: 1, # 'ง'
+ 26: 1, # 'จ'
+ 52: 0, # 'ฉ'
+ 34: 0, # 'ช'
+ 51: 0, # 'ซ'
+ 47: 0, # 'ญ'
+ 58: 0, # 'ฎ'
+ 57: 0, # 'ฏ'
+ 49: 0, # 'ฐ'
+ 53: 0, # 'ฑ'
+ 55: 0, # 'ฒ'
+ 43: 2, # 'ณ'
+ 20: 0, # 'ด'
+ 19: 2, # 'ต'
+ 44: 0, # 'ถ'
+ 14: 1, # 'ท'
+ 48: 0, # 'ธ'
+ 3: 2, # 'น'
+ 17: 1, # 'บ'
+ 25: 1, # 'ป'
+ 39: 0, # 'ผ'
+ 62: 0, # 'ฝ'
+ 31: 0, # 'พ'
+ 54: 0, # 'ฟ'
+ 45: 0, # 'ภ'
+ 9: 0, # 'ม'
+ 16: 2, # 'ย'
+ 2: 1, # 'ร'
+ 61: 0, # 'ฤ'
+ 15: 0, # 'ล'
+ 12: 2, # 'ว'
+ 42: 0, # 'ศ'
+ 46: 0, # 'ษ'
+ 18: 1, # 'ส'
+ 21: 1, # 'ห'
+ 4: 3, # 'อ'
+ 63: 0, # 'ฯ'
+ 22: 0, # 'ะ'
+ 10: 3, # 'ั'
+ 1: 3, # 'า'
+ 36: 0, # 'ำ'
+ 23: 0, # 'ิ'
+ 13: 2, # 'ี'
+ 40: 3, # 'ึ'
+ 27: 1, # 'ื'
+ 32: 1, # 'ุ'
+ 35: 0, # 'ู'
+ 11: 0, # 'เ'
+ 28: 0, # 'แ'
+ 41: 0, # 'โ'
+ 29: 1, # 'ใ'
+ 33: 0, # 'ไ'
+ 50: 0, # 'ๆ'
+ 37: 1, # '็'
+ 6: 2, # '่'
+ 7: 3, # '้'
+ 38: 1, # '์'
+ 56: 0, # '๑'
+ 59: 0, # '๒'
+ 60: 0, # '๕'
+ },
+ 24: { # 'ค'
+ 5: 0, # 'ก'
+ 30: 0, # 'ข'
+ 24: 2, # 'ค'
+ 8: 2, # 'ง'
+ 26: 0, # 'จ'
+ 52: 0, # 'ฉ'
+ 34: 0, # 'ช'
+ 51: 0, # 'ซ'
+ 47: 0, # 'ญ'
+ 58: 0, # 'ฎ'
+ 57: 0, # 'ฏ'
+ 49: 0, # 'ฐ'
+ 53: 0, # 'ฑ'
+ 55: 0, # 'ฒ'
+ 43: 2, # 'ณ'
+ 20: 2, # 'ด'
+ 19: 2, # 'ต'
+ 44: 0, # 'ถ'
+ 14: 1, # 'ท'
+ 48: 0, # 'ธ'
+ 3: 3, # 'น'
+ 17: 0, # 'บ'
+ 25: 1, # 'ป'
+ 39: 0, # 'ผ'
+ 62: 0, # 'ฝ'
+ 31: 0, # 'พ'
+ 54: 0, # 'ฟ'
+ 45: 0, # 'ภ'
+ 9: 2, # 'ม'
+ 16: 2, # 'ย'
+ 2: 3, # 'ร'
+ 61: 0, # 'ฤ'
+ 15: 3, # 'ล'
+ 12: 3, # 'ว'
+ 42: 0, # 'ศ'
+ 46: 0, # 'ษ'
+ 18: 1, # 'ส'
+ 21: 0, # 'ห'
+ 4: 2, # 'อ'
+ 63: 0, # 'ฯ'
+ 22: 2, # 'ะ'
+ 10: 3, # 'ั'
+ 1: 2, # 'า'
+ 36: 3, # 'ำ'
+ 23: 3, # 'ิ'
+ 13: 2, # 'ี'
+ 40: 0, # 'ึ'
+ 27: 3, # 'ื'
+ 32: 3, # 'ุ'
+ 35: 2, # 'ู'
+ 11: 1, # 'เ'
+ 28: 0, # 'แ'
+ 41: 3, # 'โ'
+ 29: 0, # 'ใ'
+ 33: 0, # 'ไ'
+ 50: 0, # 'ๆ'
+ 37: 1, # '็'
+ 6: 3, # '่'
+ 7: 3, # '้'
+ 38: 3, # '์'
+ 56: 0, # '๑'
+ 59: 0, # '๒'
+ 60: 0, # '๕'
+ },
+ 8: { # 'ง'
+ 5: 3, # 'ก'
+ 30: 2, # 'ข'
+ 24: 3, # 'ค'
+ 8: 2, # 'ง'
+ 26: 2, # 'จ'
+ 52: 1, # 'ฉ'
+ 34: 2, # 'ช'
+ 51: 1, # 'ซ'
+ 47: 0, # 'ญ'
+ 58: 0, # 'ฎ'
+ 57: 0, # 'ฏ'
+ 49: 0, # 'ฐ'
+ 53: 0, # 'ฑ'
+ 55: 0, # 'ฒ'
+ 43: 0, # 'ณ'
+ 20: 2, # 'ด'
+ 19: 2, # 'ต'
+ 44: 1, # 'ถ'
+ 14: 3, # 'ท'
+ 48: 1, # 'ธ'
+ 3: 3, # 'น'
+ 17: 2, # 'บ'
+ 25: 2, # 'ป'
+ 39: 2, # 'ผ'
+ 62: 1, # 'ฝ'
+ 31: 2, # 'พ'
+ 54: 0, # 'ฟ'
+ 45: 1, # 'ภ'
+ 9: 2, # 'ม'
+ 16: 1, # 'ย'
+ 2: 2, # 'ร'
+ 61: 0, # 'ฤ'
+ 15: 2, # 'ล'
+ 12: 2, # 'ว'
+ 42: 2, # 'ศ'
+ 46: 1, # 'ษ'
+ 18: 3, # 'ส'
+ 21: 3, # 'ห'
+ 4: 2, # 'อ'
+ 63: 0, # 'ฯ'
+ 22: 0, # 'ะ'
+ 10: 1, # 'ั'
+ 1: 3, # 'า'
+ 36: 0, # 'ำ'
+ 23: 2, # 'ิ'
+ 13: 1, # 'ี'
+ 40: 0, # 'ึ'
+ 27: 1, # 'ื'
+ 32: 1, # 'ุ'
+ 35: 0, # 'ู'
+ 11: 3, # 'เ'
+ 28: 2, # 'แ'
+ 41: 1, # 'โ'
+ 29: 2, # 'ใ'
+ 33: 2, # 'ไ'
+ 50: 3, # 'ๆ'
+ 37: 0, # '็'
+ 6: 2, # '่'
+ 7: 0, # '้'
+ 38: 0, # '์'
+ 56: 0, # '๑'
+ 59: 0, # '๒'
+ 60: 0, # '๕'
+ },
+ 26: { # 'จ'
+ 5: 2, # 'ก'
+ 30: 1, # 'ข'
+ 24: 0, # 'ค'
+ 8: 2, # 'ง'
+ 26: 3, # 'จ'
+ 52: 0, # 'ฉ'
+ 34: 0, # 'ช'
+ 51: 0, # 'ซ'
+ 47: 0, # 'ญ'
+ 58: 0, # 'ฎ'
+ 57: 0, # 'ฏ'
+ 49: 0, # 'ฐ'
+ 53: 0, # 'ฑ'
+ 55: 0, # 'ฒ'
+ 43: 0, # 'ณ'
+ 20: 2, # 'ด'
+ 19: 1, # 'ต'
+ 44: 1, # 'ถ'
+ 14: 2, # 'ท'
+ 48: 0, # 'ธ'
+ 3: 3, # 'น'
+ 17: 1, # 'บ'
+ 25: 0, # 'ป'
+ 39: 0, # 'ผ'
+ 62: 0, # 'ฝ'
+ 31: 1, # 'พ'
+ 54: 0, # 'ฟ'
+ 45: 0, # 'ภ'
+ 9: 1, # 'ม'
+ 16: 1, # 'ย'
+ 2: 3, # 'ร'
+ 61: 0, # 'ฤ'
+ 15: 0, # 'ล'
+ 12: 1, # 'ว'
+ 42: 0, # 'ศ'
+ 46: 0, # 'ษ'
+ 18: 2, # 'ส'
+ 21: 1, # 'ห'
+ 4: 2, # 'อ'
+ 63: 0, # 'ฯ'
+ 22: 3, # 'ะ'
+ 10: 3, # 'ั'
+ 1: 3, # 'า'
+ 36: 3, # 'ำ'
+ 23: 2, # 'ิ'
+ 13: 1, # 'ี'
+ 40: 3, # 'ึ'
+ 27: 1, # 'ื'
+ 32: 3, # 'ุ'
+ 35: 2, # 'ู'
+ 11: 1, # 'เ'
+ 28: 1, # 'แ'
+ 41: 0, # 'โ'
+ 29: 1, # 'ใ'
+ 33: 1, # 'ไ'
+ 50: 0, # 'ๆ'
+ 37: 0, # '็'
+ 6: 2, # '่'
+ 7: 2, # '้'
+ 38: 0, # '์'
+ 56: 0, # '๑'
+ 59: 0, # '๒'
+ 60: 0, # '๕'
+ },
+ 52: { # 'ฉ'
+ 5: 0, # 'ก'
+ 30: 0, # 'ข'
+ 24: 0, # 'ค'
+ 8: 0, # 'ง'
+ 26: 0, # 'จ'
+ 52: 0, # 'ฉ'
+ 34: 0, # 'ช'
+ 51: 0, # 'ซ'
+ 47: 0, # 'ญ'
+ 58: 0, # 'ฎ'
+ 57: 0, # 'ฏ'
+ 49: 0, # 'ฐ'
+ 53: 0, # 'ฑ'
+ 55: 0, # 'ฒ'
+ 43: 0, # 'ณ'
+ 20: 0, # 'ด'
+ 19: 0, # 'ต'
+ 44: 0, # 'ถ'
+ 14: 0, # 'ท'
+ 48: 0, # 'ธ'
+ 3: 0, # 'น'
+ 17: 3, # 'บ'
+ 25: 0, # 'ป'
+ 39: 0, # 'ผ'
+ 62: 0, # 'ฝ'
+ 31: 3, # 'พ'
+ 54: 0, # 'ฟ'
+ 45: 0, # 'ภ'
+ 9: 1, # 'ม'
+ 16: 1, # 'ย'
+ 2: 0, # 'ร'
+ 61: 0, # 'ฤ'
+ 15: 2, # 'ล'
+ 12: 1, # 'ว'
+ 42: 0, # 'ศ'
+ 46: 0, # 'ษ'
+ 18: 0, # 'ส'
+ 21: 0, # 'ห'
+ 4: 0, # 'อ'
+ 63: 0, # 'ฯ'
+ 22: 1, # 'ะ'
+ 10: 1, # 'ั'
+ 1: 1, # 'า'
+ 36: 0, # 'ำ'
+ 23: 1, # 'ิ'
+ 13: 1, # 'ี'
+ 40: 0, # 'ึ'
+ 27: 0, # 'ื'
+ 32: 1, # 'ุ'
+ 35: 0, # 'ู'
+ 11: 0, # 'เ'
+ 28: 0, # 'แ'
+ 41: 0, # 'โ'
+ 29: 0, # 'ใ'
+ 33: 0, # 'ไ'
+ 50: 0, # 'ๆ'
+ 37: 0, # '็'
+ 6: 0, # '่'
+ 7: 0, # '้'
+ 38: 0, # '์'
+ 56: 0, # '๑'
+ 59: 0, # '๒'
+ 60: 0, # '๕'
+ },
+ 34: { # 'ช'
+ 5: 1, # 'ก'
+ 30: 0, # 'ข'
+ 24: 0, # 'ค'
+ 8: 1, # 'ง'
+ 26: 0, # 'จ'
+ 52: 0, # 'ฉ'
+ 34: 0, # 'ช'
+ 51: 0, # 'ซ'
+ 47: 1, # 'ญ'
+ 58: 0, # 'ฎ'
+ 57: 0, # 'ฏ'
+ 49: 0, # 'ฐ'
+ 53: 0, # 'ฑ'
+ 55: 0, # 'ฒ'
+ 43: 0, # 'ณ'
+ 20: 0, # 'ด'
+ 19: 0, # 'ต'
+ 44: 0, # 'ถ'
+ 14: 1, # 'ท'
+ 48: 0, # 'ธ'
+ 3: 3, # 'น'
+ 17: 2, # 'บ'
+ 25: 0, # 'ป'
+ 39: 0, # 'ผ'
+ 62: 0, # 'ฝ'
+ 31: 0, # 'พ'
+ 54: 0, # 'ฟ'
+ 45: 0, # 'ภ'
+ 9: 2, # 'ม'
+ 16: 1, # 'ย'
+ 2: 1, # 'ร'
+ 61: 0, # 'ฤ'
+ 15: 0, # 'ล'
+ 12: 1, # 'ว'
+ 42: 0, # 'ศ'
+ 46: 0, # 'ษ'
+ 18: 0, # 'ส'
+ 21: 0, # 'ห'
+ 4: 2, # 'อ'
+ 63: 0, # 'ฯ'
+ 22: 0, # 'ะ'
+ 10: 2, # 'ั'
+ 1: 3, # 'า'
+ 36: 1, # 'ำ'
+ 23: 3, # 'ิ'
+ 13: 2, # 'ี'
+ 40: 0, # 'ึ'
+ 27: 3, # 'ื'
+ 32: 3, # 'ุ'
+ 35: 1, # 'ู'
+ 11: 0, # 'เ'
+ 28: 0, # 'แ'
+ 41: 0, # 'โ'
+ 29: 0, # 'ใ'
+ 33: 0, # 'ไ'
+ 50: 0, # 'ๆ'
+ 37: 1, # '็'
+ 6: 3, # '่'
+ 7: 3, # '้'
+ 38: 0, # '์'
+ 56: 0, # '๑'
+ 59: 0, # '๒'
+ 60: 0, # '๕'
+ },
+ 51: { # 'ซ'
+ 5: 0, # 'ก'
+ 30: 0, # 'ข'
+ 24: 0, # 'ค'
+ 8: 0, # 'ง'
+ 26: 0, # 'จ'
+ 52: 0, # 'ฉ'
+ 34: 0, # 'ช'
+ 51: 0, # 'ซ'
+ 47: 0, # 'ญ'
+ 58: 0, # 'ฎ'
+ 57: 0, # 'ฏ'
+ 49: 0, # 'ฐ'
+ 53: 0, # 'ฑ'
+ 55: 0, # 'ฒ'
+ 43: 0, # 'ณ'
+ 20: 0, # 'ด'
+ 19: 0, # 'ต'
+ 44: 0, # 'ถ'
+ 14: 0, # 'ท'
+ 48: 0, # 'ธ'
+ 3: 1, # 'น'
+ 17: 0, # 'บ'
+ 25: 0, # 'ป'
+ 39: 0, # 'ผ'
+ 62: 0, # 'ฝ'
+ 31: 0, # 'พ'
+ 54: 0, # 'ฟ'
+ 45: 0, # 'ภ'
+ 9: 0, # 'ม'
+ 16: 0, # 'ย'
+ 2: 0, # 'ร'
+ 61: 0, # 'ฤ'
+ 15: 1, # 'ล'
+ 12: 0, # 'ว'
+ 42: 0, # 'ศ'
+ 46: 0, # 'ษ'
+ 18: 1, # 'ส'
+ 21: 0, # 'ห'
+ 4: 2, # 'อ'
+ 63: 0, # 'ฯ'
+ 22: 0, # 'ะ'
+ 10: 1, # 'ั'
+ 1: 1, # 'า'
+ 36: 0, # 'ำ'
+ 23: 1, # 'ิ'
+ 13: 2, # 'ี'
+ 40: 3, # 'ึ'
+ 27: 2, # 'ื'
+ 32: 1, # 'ุ'
+ 35: 1, # 'ู'
+ 11: 1, # 'เ'
+ 28: 0, # 'แ'
+ 41: 0, # 'โ'
+ 29: 0, # 'ใ'
+ 33: 0, # 'ไ'
+ 50: 0, # 'ๆ'
+ 37: 1, # '็'
+ 6: 1, # '่'
+ 7: 2, # '้'
+ 38: 1, # '์'
+ 56: 0, # '๑'
+ 59: 0, # '๒'
+ 60: 0, # '๕'
+ },
+ 47: { # 'ญ'
+ 5: 1, # 'ก'
+ 30: 1, # 'ข'
+ 24: 0, # 'ค'
+ 8: 0, # 'ง'
+ 26: 0, # 'จ'
+ 52: 0, # 'ฉ'
+ 34: 1, # 'ช'
+ 51: 0, # 'ซ'
+ 47: 3, # 'ญ'
+ 58: 0, # 'ฎ'
+ 57: 0, # 'ฏ'
+ 49: 0, # 'ฐ'
+ 53: 0, # 'ฑ'
+ 55: 0, # 'ฒ'
+ 43: 0, # 'ณ'
+ 20: 0, # 'ด'
+ 19: 0, # 'ต'
+ 44: 0, # 'ถ'
+ 14: 1, # 'ท'
+ 48: 0, # 'ธ'
+ 3: 0, # 'น'
+ 17: 1, # 'บ'
+ 25: 1, # 'ป'
+ 39: 0, # 'ผ'
+ 62: 0, # 'ฝ'
+ 31: 0, # 'พ'
+ 54: 0, # 'ฟ'
+ 45: 0, # 'ภ'
+ 9: 1, # 'ม'
+ 16: 0, # 'ย'
+ 2: 0, # 'ร'
+ 61: 0, # 'ฤ'
+ 15: 1, # 'ล'
+ 12: 0, # 'ว'
+ 42: 0, # 'ศ'
+ 46: 0, # 'ษ'
+ 18: 1, # 'ส'
+ 21: 2, # 'ห'
+ 4: 1, # 'อ'
+ 63: 0, # 'ฯ'
+ 22: 1, # 'ะ'
+ 10: 2, # 'ั'
+ 1: 3, # 'า'
+ 36: 0, # 'ำ'
+ 23: 1, # 'ิ'
+ 13: 1, # 'ี'
+ 40: 0, # 'ึ'
+ 27: 0, # 'ื'
+ 32: 0, # 'ุ'
+ 35: 0, # 'ู'
+ 11: 1, # 'เ'
+ 28: 1, # 'แ'
+ 41: 0, # 'โ'
+ 29: 1, # 'ใ'
+ 33: 0, # 'ไ'
+ 50: 1, # 'ๆ'
+ 37: 0, # '็'
+ 6: 2, # '่'
+ 7: 0, # '้'
+ 38: 0, # '์'
+ 56: 0, # '๑'
+ 59: 0, # '๒'
+ 60: 0, # '๕'
+ },
+ 58: { # 'ฎ'
+ 5: 2, # 'ก'
+ 30: 0, # 'ข'
+ 24: 0, # 'ค'
+ 8: 0, # 'ง'
+ 26: 0, # 'จ'
+ 52: 0, # 'ฉ'
+ 34: 0, # 'ช'
+ 51: 0, # 'ซ'
+ 47: 0, # 'ญ'
+ 58: 0, # 'ฎ'
+ 57: 0, # 'ฏ'
+ 49: 0, # 'ฐ'
+ 53: 0, # 'ฑ'
+ 55: 0, # 'ฒ'
+ 43: 0, # 'ณ'
+ 20: 0, # 'ด'
+ 19: 0, # 'ต'
+ 44: 0, # 'ถ'
+ 14: 0, # 'ท'
+ 48: 0, # 'ธ'
+ 3: 0, # 'น'
+ 17: 0, # 'บ'
+ 25: 0, # 'ป'
+ 39: 0, # 'ผ'
+ 62: 0, # 'ฝ'
+ 31: 0, # 'พ'
+ 54: 0, # 'ฟ'
+ 45: 0, # 'ภ'
+ 9: 0, # 'ม'
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+ },
+}
+
+# 255: Undefined characters that did not exist in training text
+# 254: Carriage/Return
+# 253: symbol (punctuation) that does not belong to word
+# 252: 0 - 9
+# 251: Control characters
+
+# Character Mapping Table(s):
+TIS_620_THAI_CHAR_TO_ORDER = {
+ 0: 255, # '\x00'
+ 1: 255, # '\x01'
+ 2: 255, # '\x02'
+ 3: 255, # '\x03'
+ 4: 255, # '\x04'
+ 5: 255, # '\x05'
+ 6: 255, # '\x06'
+ 7: 255, # '\x07'
+ 8: 255, # '\x08'
+ 9: 255, # '\t'
+ 10: 254, # '\n'
+ 11: 255, # '\x0b'
+ 12: 255, # '\x0c'
+ 13: 254, # '\r'
+ 14: 255, # '\x0e'
+ 15: 255, # '\x0f'
+ 16: 255, # '\x10'
+ 17: 255, # '\x11'
+ 18: 255, # '\x12'
+ 19: 255, # '\x13'
+ 20: 255, # '\x14'
+ 21: 255, # '\x15'
+ 22: 255, # '\x16'
+ 23: 255, # '\x17'
+ 24: 255, # '\x18'
+ 25: 255, # '\x19'
+ 26: 255, # '\x1a'
+ 27: 255, # '\x1b'
+ 28: 255, # '\x1c'
+ 29: 255, # '\x1d'
+ 30: 255, # '\x1e'
+ 31: 255, # '\x1f'
+ 32: 253, # ' '
+ 33: 253, # '!'
+ 34: 253, # '"'
+ 35: 253, # '#'
+ 36: 253, # '$'
+ 37: 253, # '%'
+ 38: 253, # '&'
+ 39: 253, # "'"
+ 40: 253, # '('
+ 41: 253, # ')'
+ 42: 253, # '*'
+ 43: 253, # '+'
+ 44: 253, # ','
+ 45: 253, # '-'
+ 46: 253, # '.'
+ 47: 253, # '/'
+ 48: 252, # '0'
+ 49: 252, # '1'
+ 50: 252, # '2'
+ 51: 252, # '3'
+ 52: 252, # '4'
+ 53: 252, # '5'
+ 54: 252, # '6'
+ 55: 252, # '7'
+ 56: 252, # '8'
+ 57: 252, # '9'
+ 58: 253, # ':'
+ 59: 253, # ';'
+ 60: 253, # '<'
+ 61: 253, # '='
+ 62: 253, # '>'
+ 63: 253, # '?'
+ 64: 253, # '@'
+ 65: 182, # 'A'
+ 66: 106, # 'B'
+ 67: 107, # 'C'
+ 68: 100, # 'D'
+ 69: 183, # 'E'
+ 70: 184, # 'F'
+ 71: 185, # 'G'
+ 72: 101, # 'H'
+ 73: 94, # 'I'
+ 74: 186, # 'J'
+ 75: 187, # 'K'
+ 76: 108, # 'L'
+ 77: 109, # 'M'
+ 78: 110, # 'N'
+ 79: 111, # 'O'
+ 80: 188, # 'P'
+ 81: 189, # 'Q'
+ 82: 190, # 'R'
+ 83: 89, # 'S'
+ 84: 95, # 'T'
+ 85: 112, # 'U'
+ 86: 113, # 'V'
+ 87: 191, # 'W'
+ 88: 192, # 'X'
+ 89: 193, # 'Y'
+ 90: 194, # 'Z'
+ 91: 253, # '['
+ 92: 253, # '\\'
+ 93: 253, # ']'
+ 94: 253, # '^'
+ 95: 253, # '_'
+ 96: 253, # '`'
+ 97: 64, # 'a'
+ 98: 72, # 'b'
+ 99: 73, # 'c'
+ 100: 114, # 'd'
+ 101: 74, # 'e'
+ 102: 115, # 'f'
+ 103: 116, # 'g'
+ 104: 102, # 'h'
+ 105: 81, # 'i'
+ 106: 201, # 'j'
+ 107: 117, # 'k'
+ 108: 90, # 'l'
+ 109: 103, # 'm'
+ 110: 78, # 'n'
+ 111: 82, # 'o'
+ 112: 96, # 'p'
+ 113: 202, # 'q'
+ 114: 91, # 'r'
+ 115: 79, # 's'
+ 116: 84, # 't'
+ 117: 104, # 'u'
+ 118: 105, # 'v'
+ 119: 97, # 'w'
+ 120: 98, # 'x'
+ 121: 92, # 'y'
+ 122: 203, # 'z'
+ 123: 253, # '{'
+ 124: 253, # '|'
+ 125: 253, # '}'
+ 126: 253, # '~'
+ 127: 253, # '\x7f'
+ 128: 209, # '\x80'
+ 129: 210, # '\x81'
+ 130: 211, # '\x82'
+ 131: 212, # '\x83'
+ 132: 213, # '\x84'
+ 133: 88, # '\x85'
+ 134: 214, # '\x86'
+ 135: 215, # '\x87'
+ 136: 216, # '\x88'
+ 137: 217, # '\x89'
+ 138: 218, # '\x8a'
+ 139: 219, # '\x8b'
+ 140: 220, # '\x8c'
+ 141: 118, # '\x8d'
+ 142: 221, # '\x8e'
+ 143: 222, # '\x8f'
+ 144: 223, # '\x90'
+ 145: 224, # '\x91'
+ 146: 99, # '\x92'
+ 147: 85, # '\x93'
+ 148: 83, # '\x94'
+ 149: 225, # '\x95'
+ 150: 226, # '\x96'
+ 151: 227, # '\x97'
+ 152: 228, # '\x98'
+ 153: 229, # '\x99'
+ 154: 230, # '\x9a'
+ 155: 231, # '\x9b'
+ 156: 232, # '\x9c'
+ 157: 233, # '\x9d'
+ 158: 234, # '\x9e'
+ 159: 235, # '\x9f'
+ 160: 236, # None
+ 161: 5, # 'ก'
+ 162: 30, # 'ข'
+ 163: 237, # 'ฃ'
+ 164: 24, # 'ค'
+ 165: 238, # 'ฅ'
+ 166: 75, # 'ฆ'
+ 167: 8, # 'ง'
+ 168: 26, # 'จ'
+ 169: 52, # 'ฉ'
+ 170: 34, # 'ช'
+ 171: 51, # 'ซ'
+ 172: 119, # 'ฌ'
+ 173: 47, # 'ญ'
+ 174: 58, # 'ฎ'
+ 175: 57, # 'ฏ'
+ 176: 49, # 'ฐ'
+ 177: 53, # 'ฑ'
+ 178: 55, # 'ฒ'
+ 179: 43, # 'ณ'
+ 180: 20, # 'ด'
+ 181: 19, # 'ต'
+ 182: 44, # 'ถ'
+ 183: 14, # 'ท'
+ 184: 48, # 'ธ'
+ 185: 3, # 'น'
+ 186: 17, # 'บ'
+ 187: 25, # 'ป'
+ 188: 39, # 'ผ'
+ 189: 62, # 'ฝ'
+ 190: 31, # 'พ'
+ 191: 54, # 'ฟ'
+ 192: 45, # 'ภ'
+ 193: 9, # 'ม'
+ 194: 16, # 'ย'
+ 195: 2, # 'ร'
+ 196: 61, # 'ฤ'
+ 197: 15, # 'ล'
+ 198: 239, # 'ฦ'
+ 199: 12, # 'ว'
+ 200: 42, # 'ศ'
+ 201: 46, # 'ษ'
+ 202: 18, # 'ส'
+ 203: 21, # 'ห'
+ 204: 76, # 'ฬ'
+ 205: 4, # 'อ'
+ 206: 66, # 'ฮ'
+ 207: 63, # 'ฯ'
+ 208: 22, # 'ะ'
+ 209: 10, # 'ั'
+ 210: 1, # 'า'
+ 211: 36, # 'ำ'
+ 212: 23, # 'ิ'
+ 213: 13, # 'ี'
+ 214: 40, # 'ึ'
+ 215: 27, # 'ื'
+ 216: 32, # 'ุ'
+ 217: 35, # 'ู'
+ 218: 86, # 'ฺ'
+ 219: 240, # None
+ 220: 241, # None
+ 221: 242, # None
+ 222: 243, # None
+ 223: 244, # '฿'
+ 224: 11, # 'เ'
+ 225: 28, # 'แ'
+ 226: 41, # 'โ'
+ 227: 29, # 'ใ'
+ 228: 33, # 'ไ'
+ 229: 245, # 'ๅ'
+ 230: 50, # 'ๆ'
+ 231: 37, # '็'
+ 232: 6, # '่'
+ 233: 7, # '้'
+ 234: 67, # '๊'
+ 235: 77, # '๋'
+ 236: 38, # '์'
+ 237: 93, # 'ํ'
+ 238: 246, # '๎'
+ 239: 247, # '๏'
+ 240: 68, # '๐'
+ 241: 56, # '๑'
+ 242: 59, # '๒'
+ 243: 65, # '๓'
+ 244: 69, # '๔'
+ 245: 60, # '๕'
+ 246: 70, # '๖'
+ 247: 80, # '๗'
+ 248: 71, # '๘'
+ 249: 87, # '๙'
+ 250: 248, # '๚'
+ 251: 249, # '๛'
+ 252: 250, # None
+ 253: 251, # None
+ 254: 252, # None
+ 255: 253, # None
+}
+
+TIS_620_THAI_MODEL = SingleByteCharSetModel(
+ charset_name="TIS-620",
+ language="Thai",
+ char_to_order_map=TIS_620_THAI_CHAR_TO_ORDER,
+ language_model=THAI_LANG_MODEL,
+ typical_positive_ratio=0.926386,
+ keep_ascii_letters=False,
+ alphabet="กขฃคฅฆงจฉชซฌญฎฏฐฑฒณดตถทธนบปผฝพฟภมยรฤลฦวศษสหฬอฮฯะัาำิีึืฺุู฿เแโใไๅๆ็่้๊๋์ํ๎๏๐๑๒๓๔๕๖๗๘๙๚๛",
+)
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/macromanprober.py b/env-llmeval/lib/python3.10/site-packages/chardet/macromanprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..1425d10ecaa59a9e49b73cea2b8b4747de73f6b5
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/macromanprober.py
@@ -0,0 +1,162 @@
+######################## BEGIN LICENSE BLOCK ########################
+# This code was modified from latin1prober.py by Rob Speer .
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Rob Speer - adapt to MacRoman encoding
+# Mark Pilgrim - port to Python
+# Shy Shalom - original C code
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from typing import List, Union
+
+from .charsetprober import CharSetProber
+from .enums import ProbingState
+
+FREQ_CAT_NUM = 4
+
+UDF = 0 # undefined
+OTH = 1 # other
+ASC = 2 # ascii capital letter
+ASS = 3 # ascii small letter
+ACV = 4 # accent capital vowel
+ACO = 5 # accent capital other
+ASV = 6 # accent small vowel
+ASO = 7 # accent small other
+ODD = 8 # character that is unlikely to appear
+CLASS_NUM = 9 # total classes
+
+# The change from Latin1 is that we explicitly look for extended characters
+# that are infrequently-occurring symbols, and consider them to always be
+# improbable. This should let MacRoman get out of the way of more likely
+# encodings in most situations.
+
+# fmt: off
+MacRoman_CharToClass = (
+ OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 00 - 07
+ OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 08 - 0F
+ OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 10 - 17
+ OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 18 - 1F
+ OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 20 - 27
+ OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 28 - 2F
+ OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 30 - 37
+ OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 38 - 3F
+ OTH, ASC, ASC, ASC, ASC, ASC, ASC, ASC, # 40 - 47
+ ASC, ASC, ASC, ASC, ASC, ASC, ASC, ASC, # 48 - 4F
+ ASC, ASC, ASC, ASC, ASC, ASC, ASC, ASC, # 50 - 57
+ ASC, ASC, ASC, OTH, OTH, OTH, OTH, OTH, # 58 - 5F
+ OTH, ASS, ASS, ASS, ASS, ASS, ASS, ASS, # 60 - 67
+ ASS, ASS, ASS, ASS, ASS, ASS, ASS, ASS, # 68 - 6F
+ ASS, ASS, ASS, ASS, ASS, ASS, ASS, ASS, # 70 - 77
+ ASS, ASS, ASS, OTH, OTH, OTH, OTH, OTH, # 78 - 7F
+ ACV, ACV, ACO, ACV, ACO, ACV, ACV, ASV, # 80 - 87
+ ASV, ASV, ASV, ASV, ASV, ASO, ASV, ASV, # 88 - 8F
+ ASV, ASV, ASV, ASV, ASV, ASV, ASO, ASV, # 90 - 97
+ ASV, ASV, ASV, ASV, ASV, ASV, ASV, ASV, # 98 - 9F
+ OTH, OTH, OTH, OTH, OTH, OTH, OTH, ASO, # A0 - A7
+ OTH, OTH, ODD, ODD, OTH, OTH, ACV, ACV, # A8 - AF
+ OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # B0 - B7
+ OTH, OTH, OTH, OTH, OTH, OTH, ASV, ASV, # B8 - BF
+ OTH, OTH, ODD, OTH, ODD, OTH, OTH, OTH, # C0 - C7
+ OTH, OTH, OTH, ACV, ACV, ACV, ACV, ASV, # C8 - CF
+ OTH, OTH, OTH, OTH, OTH, OTH, OTH, ODD, # D0 - D7
+ ASV, ACV, ODD, OTH, OTH, OTH, OTH, OTH, # D8 - DF
+ OTH, OTH, OTH, OTH, OTH, ACV, ACV, ACV, # E0 - E7
+ ACV, ACV, ACV, ACV, ACV, ACV, ACV, ACV, # E8 - EF
+ ODD, ACV, ACV, ACV, ACV, ASV, ODD, ODD, # F0 - F7
+ ODD, ODD, ODD, ODD, ODD, ODD, ODD, ODD, # F8 - FF
+)
+
+# 0 : illegal
+# 1 : very unlikely
+# 2 : normal
+# 3 : very likely
+MacRomanClassModel = (
+# UDF OTH ASC ASS ACV ACO ASV ASO ODD
+ 0, 0, 0, 0, 0, 0, 0, 0, 0, # UDF
+ 0, 3, 3, 3, 3, 3, 3, 3, 1, # OTH
+ 0, 3, 3, 3, 3, 3, 3, 3, 1, # ASC
+ 0, 3, 3, 3, 1, 1, 3, 3, 1, # ASS
+ 0, 3, 3, 3, 1, 2, 1, 2, 1, # ACV
+ 0, 3, 3, 3, 3, 3, 3, 3, 1, # ACO
+ 0, 3, 1, 3, 1, 1, 1, 3, 1, # ASV
+ 0, 3, 1, 3, 1, 1, 3, 3, 1, # ASO
+ 0, 1, 1, 1, 1, 1, 1, 1, 1, # ODD
+)
+# fmt: on
+
+
+class MacRomanProber(CharSetProber):
+ def __init__(self) -> None:
+ super().__init__()
+ self._last_char_class = OTH
+ self._freq_counter: List[int] = []
+ self.reset()
+
+ def reset(self) -> None:
+ self._last_char_class = OTH
+ self._freq_counter = [0] * FREQ_CAT_NUM
+
+ # express the prior that MacRoman is a somewhat rare encoding;
+ # this can be done by starting out in a slightly improbable state
+ # that must be overcome
+ self._freq_counter[2] = 10
+
+ super().reset()
+
+ @property
+ def charset_name(self) -> str:
+ return "MacRoman"
+
+ @property
+ def language(self) -> str:
+ return ""
+
+ def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+ byte_str = self.remove_xml_tags(byte_str)
+ for c in byte_str:
+ char_class = MacRoman_CharToClass[c]
+ freq = MacRomanClassModel[(self._last_char_class * CLASS_NUM) + char_class]
+ if freq == 0:
+ self._state = ProbingState.NOT_ME
+ break
+ self._freq_counter[freq] += 1
+ self._last_char_class = char_class
+
+ return self.state
+
+ def get_confidence(self) -> float:
+ if self.state == ProbingState.NOT_ME:
+ return 0.01
+
+ total = sum(self._freq_counter)
+ confidence = (
+ 0.0
+ if total < 0.01
+ else (self._freq_counter[3] - self._freq_counter[1] * 20.0) / total
+ )
+ confidence = max(confidence, 0.0)
+ # lower the confidence of MacRoman so that other more accurate
+ # detector can take priority.
+ confidence *= 0.73
+ return confidence
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/mbcharsetprober.py b/env-llmeval/lib/python3.10/site-packages/chardet/mbcharsetprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..666307e8fe0608c69f2b6578a49794e1e20a139a
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/mbcharsetprober.py
@@ -0,0 +1,95 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+# Shy Shalom - original C code
+# Proofpoint, Inc.
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Optional, Union
+
+from .chardistribution import CharDistributionAnalysis
+from .charsetprober import CharSetProber
+from .codingstatemachine import CodingStateMachine
+from .enums import LanguageFilter, MachineState, ProbingState
+
+
+class MultiByteCharSetProber(CharSetProber):
+ """
+ MultiByteCharSetProber
+ """
+
+ def __init__(self, lang_filter: LanguageFilter = LanguageFilter.NONE) -> None:
+ super().__init__(lang_filter=lang_filter)
+ self.distribution_analyzer: Optional[CharDistributionAnalysis] = None
+ self.coding_sm: Optional[CodingStateMachine] = None
+ self._last_char = bytearray(b"\0\0")
+
+ def reset(self) -> None:
+ super().reset()
+ if self.coding_sm:
+ self.coding_sm.reset()
+ if self.distribution_analyzer:
+ self.distribution_analyzer.reset()
+ self._last_char = bytearray(b"\0\0")
+
+ def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+ assert self.coding_sm is not None
+ assert self.distribution_analyzer is not None
+
+ for i, byte in enumerate(byte_str):
+ coding_state = self.coding_sm.next_state(byte)
+ if coding_state == MachineState.ERROR:
+ self.logger.debug(
+ "%s %s prober hit error at byte %s",
+ self.charset_name,
+ self.language,
+ i,
+ )
+ self._state = ProbingState.NOT_ME
+ break
+ if coding_state == MachineState.ITS_ME:
+ self._state = ProbingState.FOUND_IT
+ break
+ if coding_state == MachineState.START:
+ char_len = self.coding_sm.get_current_charlen()
+ if i == 0:
+ self._last_char[1] = byte
+ self.distribution_analyzer.feed(self._last_char, char_len)
+ else:
+ self.distribution_analyzer.feed(byte_str[i - 1 : i + 1], char_len)
+
+ self._last_char[0] = byte_str[-1]
+
+ if self.state == ProbingState.DETECTING:
+ if self.distribution_analyzer.got_enough_data() and (
+ self.get_confidence() > self.SHORTCUT_THRESHOLD
+ ):
+ self._state = ProbingState.FOUND_IT
+
+ return self.state
+
+ def get_confidence(self) -> float:
+ assert self.distribution_analyzer is not None
+ return self.distribution_analyzer.get_confidence()
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/mbcsgroupprober.py b/env-llmeval/lib/python3.10/site-packages/chardet/mbcsgroupprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..6cb9cc7b3bc751fbb5a54ba06eaaf953bf14ed8d
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/mbcsgroupprober.py
@@ -0,0 +1,57 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+# Shy Shalom - original C code
+# Proofpoint, Inc.
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from .big5prober import Big5Prober
+from .charsetgroupprober import CharSetGroupProber
+from .cp949prober import CP949Prober
+from .enums import LanguageFilter
+from .eucjpprober import EUCJPProber
+from .euckrprober import EUCKRProber
+from .euctwprober import EUCTWProber
+from .gb2312prober import GB2312Prober
+from .johabprober import JOHABProber
+from .sjisprober import SJISProber
+from .utf8prober import UTF8Prober
+
+
+class MBCSGroupProber(CharSetGroupProber):
+ def __init__(self, lang_filter: LanguageFilter = LanguageFilter.NONE) -> None:
+ super().__init__(lang_filter=lang_filter)
+ self.probers = [
+ UTF8Prober(),
+ SJISProber(),
+ EUCJPProber(),
+ GB2312Prober(),
+ EUCKRProber(),
+ CP949Prober(),
+ Big5Prober(),
+ EUCTWProber(),
+ JOHABProber(),
+ ]
+ self.reset()
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/mbcssm.py b/env-llmeval/lib/python3.10/site-packages/chardet/mbcssm.py
new file mode 100644
index 0000000000000000000000000000000000000000..7bbe97e6665356327814e2b797ffcc5724974a46
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/mbcssm.py
@@ -0,0 +1,661 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from .codingstatemachinedict import CodingStateMachineDict
+from .enums import MachineState
+
+# BIG5
+
+# fmt: off
+BIG5_CLS = (
+ 1, 1, 1, 1, 1, 1, 1, 1, # 00 - 07 #allow 0x00 as legal value
+ 1, 1, 1, 1, 1, 1, 0, 0, # 08 - 0f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 10 - 17
+ 1, 1, 1, 0, 1, 1, 1, 1, # 18 - 1f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 20 - 27
+ 1, 1, 1, 1, 1, 1, 1, 1, # 28 - 2f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 30 - 37
+ 1, 1, 1, 1, 1, 1, 1, 1, # 38 - 3f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 40 - 47
+ 2, 2, 2, 2, 2, 2, 2, 2, # 48 - 4f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 50 - 57
+ 2, 2, 2, 2, 2, 2, 2, 2, # 58 - 5f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 60 - 67
+ 2, 2, 2, 2, 2, 2, 2, 2, # 68 - 6f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 70 - 77
+ 2, 2, 2, 2, 2, 2, 2, 1, # 78 - 7f
+ 4, 4, 4, 4, 4, 4, 4, 4, # 80 - 87
+ 4, 4, 4, 4, 4, 4, 4, 4, # 88 - 8f
+ 4, 4, 4, 4, 4, 4, 4, 4, # 90 - 97
+ 4, 4, 4, 4, 4, 4, 4, 4, # 98 - 9f
+ 4, 3, 3, 3, 3, 3, 3, 3, # a0 - a7
+ 3, 3, 3, 3, 3, 3, 3, 3, # a8 - af
+ 3, 3, 3, 3, 3, 3, 3, 3, # b0 - b7
+ 3, 3, 3, 3, 3, 3, 3, 3, # b8 - bf
+ 3, 3, 3, 3, 3, 3, 3, 3, # c0 - c7
+ 3, 3, 3, 3, 3, 3, 3, 3, # c8 - cf
+ 3, 3, 3, 3, 3, 3, 3, 3, # d0 - d7
+ 3, 3, 3, 3, 3, 3, 3, 3, # d8 - df
+ 3, 3, 3, 3, 3, 3, 3, 3, # e0 - e7
+ 3, 3, 3, 3, 3, 3, 3, 3, # e8 - ef
+ 3, 3, 3, 3, 3, 3, 3, 3, # f0 - f7
+ 3, 3, 3, 3, 3, 3, 3, 0 # f8 - ff
+)
+
+BIG5_ST = (
+ MachineState.ERROR,MachineState.START,MachineState.START, 3,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#00-07
+ MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,#08-0f
+ MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START#10-17
+)
+# fmt: on
+
+BIG5_CHAR_LEN_TABLE = (0, 1, 1, 2, 0)
+
+BIG5_SM_MODEL: CodingStateMachineDict = {
+ "class_table": BIG5_CLS,
+ "class_factor": 5,
+ "state_table": BIG5_ST,
+ "char_len_table": BIG5_CHAR_LEN_TABLE,
+ "name": "Big5",
+}
+
+# CP949
+# fmt: off
+CP949_CLS = (
+ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, # 00 - 0f
+ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, # 10 - 1f
+ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, # 20 - 2f
+ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, # 30 - 3f
+ 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, # 40 - 4f
+ 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 1, 1, 1, 1, 1, # 50 - 5f
+ 1, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, # 60 - 6f
+ 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 1, 1, 1, 1, 1, # 70 - 7f
+ 0, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, # 80 - 8f
+ 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, # 90 - 9f
+ 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, # a0 - af
+ 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, # b0 - bf
+ 7, 7, 7, 7, 7, 7, 9, 2, 2, 3, 2, 2, 2, 2, 2, 2, # c0 - cf
+ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, # d0 - df
+ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, # e0 - ef
+ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, # f0 - ff
+)
+
+CP949_ST = (
+#cls= 0 1 2 3 4 5 6 7 8 9 # previous state =
+ MachineState.ERROR,MachineState.START, 3,MachineState.ERROR,MachineState.START,MachineState.START, 4, 5,MachineState.ERROR, 6, # MachineState.START
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR, # MachineState.ERROR
+ MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME, # MachineState.ITS_ME
+ MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START, # 3
+ MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START, # 4
+ MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START, # 5
+ MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START, # 6
+)
+# fmt: on
+
+CP949_CHAR_LEN_TABLE = (0, 1, 2, 0, 1, 1, 2, 2, 0, 2)
+
+CP949_SM_MODEL: CodingStateMachineDict = {
+ "class_table": CP949_CLS,
+ "class_factor": 10,
+ "state_table": CP949_ST,
+ "char_len_table": CP949_CHAR_LEN_TABLE,
+ "name": "CP949",
+}
+
+# EUC-JP
+# fmt: off
+EUCJP_CLS = (
+ 4, 4, 4, 4, 4, 4, 4, 4, # 00 - 07
+ 4, 4, 4, 4, 4, 4, 5, 5, # 08 - 0f
+ 4, 4, 4, 4, 4, 4, 4, 4, # 10 - 17
+ 4, 4, 4, 5, 4, 4, 4, 4, # 18 - 1f
+ 4, 4, 4, 4, 4, 4, 4, 4, # 20 - 27
+ 4, 4, 4, 4, 4, 4, 4, 4, # 28 - 2f
+ 4, 4, 4, 4, 4, 4, 4, 4, # 30 - 37
+ 4, 4, 4, 4, 4, 4, 4, 4, # 38 - 3f
+ 4, 4, 4, 4, 4, 4, 4, 4, # 40 - 47
+ 4, 4, 4, 4, 4, 4, 4, 4, # 48 - 4f
+ 4, 4, 4, 4, 4, 4, 4, 4, # 50 - 57
+ 4, 4, 4, 4, 4, 4, 4, 4, # 58 - 5f
+ 4, 4, 4, 4, 4, 4, 4, 4, # 60 - 67
+ 4, 4, 4, 4, 4, 4, 4, 4, # 68 - 6f
+ 4, 4, 4, 4, 4, 4, 4, 4, # 70 - 77
+ 4, 4, 4, 4, 4, 4, 4, 4, # 78 - 7f
+ 5, 5, 5, 5, 5, 5, 5, 5, # 80 - 87
+ 5, 5, 5, 5, 5, 5, 1, 3, # 88 - 8f
+ 5, 5, 5, 5, 5, 5, 5, 5, # 90 - 97
+ 5, 5, 5, 5, 5, 5, 5, 5, # 98 - 9f
+ 5, 2, 2, 2, 2, 2, 2, 2, # a0 - a7
+ 2, 2, 2, 2, 2, 2, 2, 2, # a8 - af
+ 2, 2, 2, 2, 2, 2, 2, 2, # b0 - b7
+ 2, 2, 2, 2, 2, 2, 2, 2, # b8 - bf
+ 2, 2, 2, 2, 2, 2, 2, 2, # c0 - c7
+ 2, 2, 2, 2, 2, 2, 2, 2, # c8 - cf
+ 2, 2, 2, 2, 2, 2, 2, 2, # d0 - d7
+ 2, 2, 2, 2, 2, 2, 2, 2, # d8 - df
+ 0, 0, 0, 0, 0, 0, 0, 0, # e0 - e7
+ 0, 0, 0, 0, 0, 0, 0, 0, # e8 - ef
+ 0, 0, 0, 0, 0, 0, 0, 0, # f0 - f7
+ 0, 0, 0, 0, 0, 0, 0, 5 # f8 - ff
+)
+
+EUCJP_ST = (
+ 3, 4, 3, 5,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#00-07
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+ MachineState.ITS_ME,MachineState.ITS_ME,MachineState.START,MachineState.ERROR,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#10-17
+ MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR, 3,MachineState.ERROR,#18-1f
+ 3,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START#20-27
+)
+# fmt: on
+
+EUCJP_CHAR_LEN_TABLE = (2, 2, 2, 3, 1, 0)
+
+EUCJP_SM_MODEL: CodingStateMachineDict = {
+ "class_table": EUCJP_CLS,
+ "class_factor": 6,
+ "state_table": EUCJP_ST,
+ "char_len_table": EUCJP_CHAR_LEN_TABLE,
+ "name": "EUC-JP",
+}
+
+# EUC-KR
+# fmt: off
+EUCKR_CLS = (
+ 1, 1, 1, 1, 1, 1, 1, 1, # 00 - 07
+ 1, 1, 1, 1, 1, 1, 0, 0, # 08 - 0f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 10 - 17
+ 1, 1, 1, 0, 1, 1, 1, 1, # 18 - 1f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 20 - 27
+ 1, 1, 1, 1, 1, 1, 1, 1, # 28 - 2f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 30 - 37
+ 1, 1, 1, 1, 1, 1, 1, 1, # 38 - 3f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 40 - 47
+ 1, 1, 1, 1, 1, 1, 1, 1, # 48 - 4f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 50 - 57
+ 1, 1, 1, 1, 1, 1, 1, 1, # 58 - 5f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 60 - 67
+ 1, 1, 1, 1, 1, 1, 1, 1, # 68 - 6f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 70 - 77
+ 1, 1, 1, 1, 1, 1, 1, 1, # 78 - 7f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 80 - 87
+ 0, 0, 0, 0, 0, 0, 0, 0, # 88 - 8f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 90 - 97
+ 0, 0, 0, 0, 0, 0, 0, 0, # 98 - 9f
+ 0, 2, 2, 2, 2, 2, 2, 2, # a0 - a7
+ 2, 2, 2, 2, 2, 3, 3, 3, # a8 - af
+ 2, 2, 2, 2, 2, 2, 2, 2, # b0 - b7
+ 2, 2, 2, 2, 2, 2, 2, 2, # b8 - bf
+ 2, 2, 2, 2, 2, 2, 2, 2, # c0 - c7
+ 2, 3, 2, 2, 2, 2, 2, 2, # c8 - cf
+ 2, 2, 2, 2, 2, 2, 2, 2, # d0 - d7
+ 2, 2, 2, 2, 2, 2, 2, 2, # d8 - df
+ 2, 2, 2, 2, 2, 2, 2, 2, # e0 - e7
+ 2, 2, 2, 2, 2, 2, 2, 2, # e8 - ef
+ 2, 2, 2, 2, 2, 2, 2, 2, # f0 - f7
+ 2, 2, 2, 2, 2, 2, 2, 0 # f8 - ff
+)
+
+EUCKR_ST = (
+ MachineState.ERROR,MachineState.START, 3,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#00-07
+ MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START #08-0f
+)
+# fmt: on
+
+EUCKR_CHAR_LEN_TABLE = (0, 1, 2, 0)
+
+EUCKR_SM_MODEL: CodingStateMachineDict = {
+ "class_table": EUCKR_CLS,
+ "class_factor": 4,
+ "state_table": EUCKR_ST,
+ "char_len_table": EUCKR_CHAR_LEN_TABLE,
+ "name": "EUC-KR",
+}
+
+# JOHAB
+# fmt: off
+JOHAB_CLS = (
+ 4,4,4,4,4,4,4,4, # 00 - 07
+ 4,4,4,4,4,4,0,0, # 08 - 0f
+ 4,4,4,4,4,4,4,4, # 10 - 17
+ 4,4,4,0,4,4,4,4, # 18 - 1f
+ 4,4,4,4,4,4,4,4, # 20 - 27
+ 4,4,4,4,4,4,4,4, # 28 - 2f
+ 4,3,3,3,3,3,3,3, # 30 - 37
+ 3,3,3,3,3,3,3,3, # 38 - 3f
+ 3,1,1,1,1,1,1,1, # 40 - 47
+ 1,1,1,1,1,1,1,1, # 48 - 4f
+ 1,1,1,1,1,1,1,1, # 50 - 57
+ 1,1,1,1,1,1,1,1, # 58 - 5f
+ 1,1,1,1,1,1,1,1, # 60 - 67
+ 1,1,1,1,1,1,1,1, # 68 - 6f
+ 1,1,1,1,1,1,1,1, # 70 - 77
+ 1,1,1,1,1,1,1,2, # 78 - 7f
+ 6,6,6,6,8,8,8,8, # 80 - 87
+ 8,8,8,8,8,8,8,8, # 88 - 8f
+ 8,7,7,7,7,7,7,7, # 90 - 97
+ 7,7,7,7,7,7,7,7, # 98 - 9f
+ 7,7,7,7,7,7,7,7, # a0 - a7
+ 7,7,7,7,7,7,7,7, # a8 - af
+ 7,7,7,7,7,7,7,7, # b0 - b7
+ 7,7,7,7,7,7,7,7, # b8 - bf
+ 7,7,7,7,7,7,7,7, # c0 - c7
+ 7,7,7,7,7,7,7,7, # c8 - cf
+ 7,7,7,7,5,5,5,5, # d0 - d7
+ 5,9,9,9,9,9,9,5, # d8 - df
+ 9,9,9,9,9,9,9,9, # e0 - e7
+ 9,9,9,9,9,9,9,9, # e8 - ef
+ 9,9,9,9,9,9,9,9, # f0 - f7
+ 9,9,5,5,5,5,5,0 # f8 - ff
+)
+
+JOHAB_ST = (
+# cls = 0 1 2 3 4 5 6 7 8 9
+ MachineState.ERROR ,MachineState.START ,MachineState.START ,MachineState.START ,MachineState.START ,MachineState.ERROR ,MachineState.ERROR ,3 ,3 ,4 , # MachineState.START
+ MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME, # MachineState.ITS_ME
+ MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR , # MachineState.ERROR
+ MachineState.ERROR ,MachineState.START ,MachineState.START ,MachineState.ERROR ,MachineState.ERROR ,MachineState.START ,MachineState.START ,MachineState.START ,MachineState.START ,MachineState.START , # 3
+ MachineState.ERROR ,MachineState.START ,MachineState.ERROR ,MachineState.START ,MachineState.ERROR ,MachineState.START ,MachineState.ERROR ,MachineState.START ,MachineState.ERROR ,MachineState.START , # 4
+)
+# fmt: on
+
+JOHAB_CHAR_LEN_TABLE = (0, 1, 1, 1, 1, 0, 0, 2, 2, 2)
+
+JOHAB_SM_MODEL: CodingStateMachineDict = {
+ "class_table": JOHAB_CLS,
+ "class_factor": 10,
+ "state_table": JOHAB_ST,
+ "char_len_table": JOHAB_CHAR_LEN_TABLE,
+ "name": "Johab",
+}
+
+# EUC-TW
+# fmt: off
+EUCTW_CLS = (
+ 2, 2, 2, 2, 2, 2, 2, 2, # 00 - 07
+ 2, 2, 2, 2, 2, 2, 0, 0, # 08 - 0f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 10 - 17
+ 2, 2, 2, 0, 2, 2, 2, 2, # 18 - 1f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 20 - 27
+ 2, 2, 2, 2, 2, 2, 2, 2, # 28 - 2f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 30 - 37
+ 2, 2, 2, 2, 2, 2, 2, 2, # 38 - 3f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 40 - 47
+ 2, 2, 2, 2, 2, 2, 2, 2, # 48 - 4f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 50 - 57
+ 2, 2, 2, 2, 2, 2, 2, 2, # 58 - 5f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 60 - 67
+ 2, 2, 2, 2, 2, 2, 2, 2, # 68 - 6f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 70 - 77
+ 2, 2, 2, 2, 2, 2, 2, 2, # 78 - 7f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 80 - 87
+ 0, 0, 0, 0, 0, 0, 6, 0, # 88 - 8f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 90 - 97
+ 0, 0, 0, 0, 0, 0, 0, 0, # 98 - 9f
+ 0, 3, 4, 4, 4, 4, 4, 4, # a0 - a7
+ 5, 5, 1, 1, 1, 1, 1, 1, # a8 - af
+ 1, 1, 1, 1, 1, 1, 1, 1, # b0 - b7
+ 1, 1, 1, 1, 1, 1, 1, 1, # b8 - bf
+ 1, 1, 3, 1, 3, 3, 3, 3, # c0 - c7
+ 3, 3, 3, 3, 3, 3, 3, 3, # c8 - cf
+ 3, 3, 3, 3, 3, 3, 3, 3, # d0 - d7
+ 3, 3, 3, 3, 3, 3, 3, 3, # d8 - df
+ 3, 3, 3, 3, 3, 3, 3, 3, # e0 - e7
+ 3, 3, 3, 3, 3, 3, 3, 3, # e8 - ef
+ 3, 3, 3, 3, 3, 3, 3, 3, # f0 - f7
+ 3, 3, 3, 3, 3, 3, 3, 0 # f8 - ff
+)
+
+EUCTW_ST = (
+ MachineState.ERROR,MachineState.ERROR,MachineState.START, 3, 3, 3, 4,MachineState.ERROR,#00-07
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+ MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,MachineState.START,MachineState.ERROR,#10-17
+ MachineState.START,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#18-1f
+ 5,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.ERROR,MachineState.START,MachineState.START,#20-27
+ MachineState.START,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START #28-2f
+)
+# fmt: on
+
+EUCTW_CHAR_LEN_TABLE = (0, 0, 1, 2, 2, 2, 3)
+
+EUCTW_SM_MODEL: CodingStateMachineDict = {
+ "class_table": EUCTW_CLS,
+ "class_factor": 7,
+ "state_table": EUCTW_ST,
+ "char_len_table": EUCTW_CHAR_LEN_TABLE,
+ "name": "x-euc-tw",
+}
+
+# GB2312
+# fmt: off
+GB2312_CLS = (
+ 1, 1, 1, 1, 1, 1, 1, 1, # 00 - 07
+ 1, 1, 1, 1, 1, 1, 0, 0, # 08 - 0f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 10 - 17
+ 1, 1, 1, 0, 1, 1, 1, 1, # 18 - 1f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 20 - 27
+ 1, 1, 1, 1, 1, 1, 1, 1, # 28 - 2f
+ 3, 3, 3, 3, 3, 3, 3, 3, # 30 - 37
+ 3, 3, 1, 1, 1, 1, 1, 1, # 38 - 3f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 40 - 47
+ 2, 2, 2, 2, 2, 2, 2, 2, # 48 - 4f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 50 - 57
+ 2, 2, 2, 2, 2, 2, 2, 2, # 58 - 5f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 60 - 67
+ 2, 2, 2, 2, 2, 2, 2, 2, # 68 - 6f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 70 - 77
+ 2, 2, 2, 2, 2, 2, 2, 4, # 78 - 7f
+ 5, 6, 6, 6, 6, 6, 6, 6, # 80 - 87
+ 6, 6, 6, 6, 6, 6, 6, 6, # 88 - 8f
+ 6, 6, 6, 6, 6, 6, 6, 6, # 90 - 97
+ 6, 6, 6, 6, 6, 6, 6, 6, # 98 - 9f
+ 6, 6, 6, 6, 6, 6, 6, 6, # a0 - a7
+ 6, 6, 6, 6, 6, 6, 6, 6, # a8 - af
+ 6, 6, 6, 6, 6, 6, 6, 6, # b0 - b7
+ 6, 6, 6, 6, 6, 6, 6, 6, # b8 - bf
+ 6, 6, 6, 6, 6, 6, 6, 6, # c0 - c7
+ 6, 6, 6, 6, 6, 6, 6, 6, # c8 - cf
+ 6, 6, 6, 6, 6, 6, 6, 6, # d0 - d7
+ 6, 6, 6, 6, 6, 6, 6, 6, # d8 - df
+ 6, 6, 6, 6, 6, 6, 6, 6, # e0 - e7
+ 6, 6, 6, 6, 6, 6, 6, 6, # e8 - ef
+ 6, 6, 6, 6, 6, 6, 6, 6, # f0 - f7
+ 6, 6, 6, 6, 6, 6, 6, 0 # f8 - ff
+)
+
+GB2312_ST = (
+ MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START, 3,MachineState.ERROR,#00-07
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+ MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,MachineState.ERROR,MachineState.START,#10-17
+ 4,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#18-1f
+ MachineState.ERROR,MachineState.ERROR, 5,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ERROR,#20-27
+ MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START #28-2f
+)
+# fmt: on
+
+# To be accurate, the length of class 6 can be either 2 or 4.
+# But it is not necessary to discriminate between the two since
+# it is used for frequency analysis only, and we are validating
+# each code range there as well. So it is safe to set it to be
+# 2 here.
+GB2312_CHAR_LEN_TABLE = (0, 1, 1, 1, 1, 1, 2)
+
+GB2312_SM_MODEL: CodingStateMachineDict = {
+ "class_table": GB2312_CLS,
+ "class_factor": 7,
+ "state_table": GB2312_ST,
+ "char_len_table": GB2312_CHAR_LEN_TABLE,
+ "name": "GB2312",
+}
+
+# Shift_JIS
+# fmt: off
+SJIS_CLS = (
+ 1, 1, 1, 1, 1, 1, 1, 1, # 00 - 07
+ 1, 1, 1, 1, 1, 1, 0, 0, # 08 - 0f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 10 - 17
+ 1, 1, 1, 0, 1, 1, 1, 1, # 18 - 1f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 20 - 27
+ 1, 1, 1, 1, 1, 1, 1, 1, # 28 - 2f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 30 - 37
+ 1, 1, 1, 1, 1, 1, 1, 1, # 38 - 3f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 40 - 47
+ 2, 2, 2, 2, 2, 2, 2, 2, # 48 - 4f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 50 - 57
+ 2, 2, 2, 2, 2, 2, 2, 2, # 58 - 5f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 60 - 67
+ 2, 2, 2, 2, 2, 2, 2, 2, # 68 - 6f
+ 2, 2, 2, 2, 2, 2, 2, 2, # 70 - 77
+ 2, 2, 2, 2, 2, 2, 2, 1, # 78 - 7f
+ 3, 3, 3, 3, 3, 2, 2, 3, # 80 - 87
+ 3, 3, 3, 3, 3, 3, 3, 3, # 88 - 8f
+ 3, 3, 3, 3, 3, 3, 3, 3, # 90 - 97
+ 3, 3, 3, 3, 3, 3, 3, 3, # 98 - 9f
+ #0xa0 is illegal in sjis encoding, but some pages does
+ #contain such byte. We need to be more error forgiven.
+ 2, 2, 2, 2, 2, 2, 2, 2, # a0 - a7
+ 2, 2, 2, 2, 2, 2, 2, 2, # a8 - af
+ 2, 2, 2, 2, 2, 2, 2, 2, # b0 - b7
+ 2, 2, 2, 2, 2, 2, 2, 2, # b8 - bf
+ 2, 2, 2, 2, 2, 2, 2, 2, # c0 - c7
+ 2, 2, 2, 2, 2, 2, 2, 2, # c8 - cf
+ 2, 2, 2, 2, 2, 2, 2, 2, # d0 - d7
+ 2, 2, 2, 2, 2, 2, 2, 2, # d8 - df
+ 3, 3, 3, 3, 3, 3, 3, 3, # e0 - e7
+ 3, 3, 3, 3, 3, 4, 4, 4, # e8 - ef
+ 3, 3, 3, 3, 3, 3, 3, 3, # f0 - f7
+ 3, 3, 3, 3, 3, 0, 0, 0, # f8 - ff
+)
+
+SJIS_ST = (
+ MachineState.ERROR,MachineState.START,MachineState.START, 3,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#00-07
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+ MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START #10-17
+)
+# fmt: on
+
+SJIS_CHAR_LEN_TABLE = (0, 1, 1, 2, 0, 0)
+
+SJIS_SM_MODEL: CodingStateMachineDict = {
+ "class_table": SJIS_CLS,
+ "class_factor": 6,
+ "state_table": SJIS_ST,
+ "char_len_table": SJIS_CHAR_LEN_TABLE,
+ "name": "Shift_JIS",
+}
+
+# UCS2-BE
+# fmt: off
+UCS2BE_CLS = (
+ 0, 0, 0, 0, 0, 0, 0, 0, # 00 - 07
+ 0, 0, 1, 0, 0, 2, 0, 0, # 08 - 0f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 10 - 17
+ 0, 0, 0, 3, 0, 0, 0, 0, # 18 - 1f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 20 - 27
+ 0, 3, 3, 3, 3, 3, 0, 0, # 28 - 2f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 30 - 37
+ 0, 0, 0, 0, 0, 0, 0, 0, # 38 - 3f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 40 - 47
+ 0, 0, 0, 0, 0, 0, 0, 0, # 48 - 4f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 50 - 57
+ 0, 0, 0, 0, 0, 0, 0, 0, # 58 - 5f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 60 - 67
+ 0, 0, 0, 0, 0, 0, 0, 0, # 68 - 6f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 70 - 77
+ 0, 0, 0, 0, 0, 0, 0, 0, # 78 - 7f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 80 - 87
+ 0, 0, 0, 0, 0, 0, 0, 0, # 88 - 8f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 90 - 97
+ 0, 0, 0, 0, 0, 0, 0, 0, # 98 - 9f
+ 0, 0, 0, 0, 0, 0, 0, 0, # a0 - a7
+ 0, 0, 0, 0, 0, 0, 0, 0, # a8 - af
+ 0, 0, 0, 0, 0, 0, 0, 0, # b0 - b7
+ 0, 0, 0, 0, 0, 0, 0, 0, # b8 - bf
+ 0, 0, 0, 0, 0, 0, 0, 0, # c0 - c7
+ 0, 0, 0, 0, 0, 0, 0, 0, # c8 - cf
+ 0, 0, 0, 0, 0, 0, 0, 0, # d0 - d7
+ 0, 0, 0, 0, 0, 0, 0, 0, # d8 - df
+ 0, 0, 0, 0, 0, 0, 0, 0, # e0 - e7
+ 0, 0, 0, 0, 0, 0, 0, 0, # e8 - ef
+ 0, 0, 0, 0, 0, 0, 0, 0, # f0 - f7
+ 0, 0, 0, 0, 0, 0, 4, 5 # f8 - ff
+)
+
+UCS2BE_ST = (
+ 5, 7, 7,MachineState.ERROR, 4, 3,MachineState.ERROR,MachineState.ERROR,#00-07
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+ MachineState.ITS_ME,MachineState.ITS_ME, 6, 6, 6, 6,MachineState.ERROR,MachineState.ERROR,#10-17
+ 6, 6, 6, 6, 6,MachineState.ITS_ME, 6, 6,#18-1f
+ 6, 6, 6, 6, 5, 7, 7,MachineState.ERROR,#20-27
+ 5, 8, 6, 6,MachineState.ERROR, 6, 6, 6,#28-2f
+ 6, 6, 6, 6,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START #30-37
+)
+# fmt: on
+
+UCS2BE_CHAR_LEN_TABLE = (2, 2, 2, 0, 2, 2)
+
+UCS2BE_SM_MODEL: CodingStateMachineDict = {
+ "class_table": UCS2BE_CLS,
+ "class_factor": 6,
+ "state_table": UCS2BE_ST,
+ "char_len_table": UCS2BE_CHAR_LEN_TABLE,
+ "name": "UTF-16BE",
+}
+
+# UCS2-LE
+# fmt: off
+UCS2LE_CLS = (
+ 0, 0, 0, 0, 0, 0, 0, 0, # 00 - 07
+ 0, 0, 1, 0, 0, 2, 0, 0, # 08 - 0f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 10 - 17
+ 0, 0, 0, 3, 0, 0, 0, 0, # 18 - 1f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 20 - 27
+ 0, 3, 3, 3, 3, 3, 0, 0, # 28 - 2f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 30 - 37
+ 0, 0, 0, 0, 0, 0, 0, 0, # 38 - 3f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 40 - 47
+ 0, 0, 0, 0, 0, 0, 0, 0, # 48 - 4f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 50 - 57
+ 0, 0, 0, 0, 0, 0, 0, 0, # 58 - 5f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 60 - 67
+ 0, 0, 0, 0, 0, 0, 0, 0, # 68 - 6f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 70 - 77
+ 0, 0, 0, 0, 0, 0, 0, 0, # 78 - 7f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 80 - 87
+ 0, 0, 0, 0, 0, 0, 0, 0, # 88 - 8f
+ 0, 0, 0, 0, 0, 0, 0, 0, # 90 - 97
+ 0, 0, 0, 0, 0, 0, 0, 0, # 98 - 9f
+ 0, 0, 0, 0, 0, 0, 0, 0, # a0 - a7
+ 0, 0, 0, 0, 0, 0, 0, 0, # a8 - af
+ 0, 0, 0, 0, 0, 0, 0, 0, # b0 - b7
+ 0, 0, 0, 0, 0, 0, 0, 0, # b8 - bf
+ 0, 0, 0, 0, 0, 0, 0, 0, # c0 - c7
+ 0, 0, 0, 0, 0, 0, 0, 0, # c8 - cf
+ 0, 0, 0, 0, 0, 0, 0, 0, # d0 - d7
+ 0, 0, 0, 0, 0, 0, 0, 0, # d8 - df
+ 0, 0, 0, 0, 0, 0, 0, 0, # e0 - e7
+ 0, 0, 0, 0, 0, 0, 0, 0, # e8 - ef
+ 0, 0, 0, 0, 0, 0, 0, 0, # f0 - f7
+ 0, 0, 0, 0, 0, 0, 4, 5 # f8 - ff
+)
+
+UCS2LE_ST = (
+ 6, 6, 7, 6, 4, 3,MachineState.ERROR,MachineState.ERROR,#00-07
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+ MachineState.ITS_ME,MachineState.ITS_ME, 5, 5, 5,MachineState.ERROR,MachineState.ITS_ME,MachineState.ERROR,#10-17
+ 5, 5, 5,MachineState.ERROR, 5,MachineState.ERROR, 6, 6,#18-1f
+ 7, 6, 8, 8, 5, 5, 5,MachineState.ERROR,#20-27
+ 5, 5, 5,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR, 5, 5,#28-2f
+ 5, 5, 5,MachineState.ERROR, 5,MachineState.ERROR,MachineState.START,MachineState.START #30-37
+)
+# fmt: on
+
+UCS2LE_CHAR_LEN_TABLE = (2, 2, 2, 2, 2, 2)
+
+UCS2LE_SM_MODEL: CodingStateMachineDict = {
+ "class_table": UCS2LE_CLS,
+ "class_factor": 6,
+ "state_table": UCS2LE_ST,
+ "char_len_table": UCS2LE_CHAR_LEN_TABLE,
+ "name": "UTF-16LE",
+}
+
+# UTF-8
+# fmt: off
+UTF8_CLS = (
+ 1, 1, 1, 1, 1, 1, 1, 1, # 00 - 07 #allow 0x00 as a legal value
+ 1, 1, 1, 1, 1, 1, 0, 0, # 08 - 0f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 10 - 17
+ 1, 1, 1, 0, 1, 1, 1, 1, # 18 - 1f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 20 - 27
+ 1, 1, 1, 1, 1, 1, 1, 1, # 28 - 2f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 30 - 37
+ 1, 1, 1, 1, 1, 1, 1, 1, # 38 - 3f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 40 - 47
+ 1, 1, 1, 1, 1, 1, 1, 1, # 48 - 4f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 50 - 57
+ 1, 1, 1, 1, 1, 1, 1, 1, # 58 - 5f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 60 - 67
+ 1, 1, 1, 1, 1, 1, 1, 1, # 68 - 6f
+ 1, 1, 1, 1, 1, 1, 1, 1, # 70 - 77
+ 1, 1, 1, 1, 1, 1, 1, 1, # 78 - 7f
+ 2, 2, 2, 2, 3, 3, 3, 3, # 80 - 87
+ 4, 4, 4, 4, 4, 4, 4, 4, # 88 - 8f
+ 4, 4, 4, 4, 4, 4, 4, 4, # 90 - 97
+ 4, 4, 4, 4, 4, 4, 4, 4, # 98 - 9f
+ 5, 5, 5, 5, 5, 5, 5, 5, # a0 - a7
+ 5, 5, 5, 5, 5, 5, 5, 5, # a8 - af
+ 5, 5, 5, 5, 5, 5, 5, 5, # b0 - b7
+ 5, 5, 5, 5, 5, 5, 5, 5, # b8 - bf
+ 0, 0, 6, 6, 6, 6, 6, 6, # c0 - c7
+ 6, 6, 6, 6, 6, 6, 6, 6, # c8 - cf
+ 6, 6, 6, 6, 6, 6, 6, 6, # d0 - d7
+ 6, 6, 6, 6, 6, 6, 6, 6, # d8 - df
+ 7, 8, 8, 8, 8, 8, 8, 8, # e0 - e7
+ 8, 8, 8, 8, 8, 9, 8, 8, # e8 - ef
+ 10, 11, 11, 11, 11, 11, 11, 11, # f0 - f7
+ 12, 13, 13, 13, 14, 15, 0, 0 # f8 - ff
+)
+
+UTF8_ST = (
+ MachineState.ERROR,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR, 12, 10,#00-07
+ 9, 11, 8, 7, 6, 5, 4, 3,#08-0f
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#10-17
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#18-1f
+ MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#20-27
+ MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#28-2f
+ MachineState.ERROR,MachineState.ERROR, 5, 5, 5, 5,MachineState.ERROR,MachineState.ERROR,#30-37
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#38-3f
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR, 5, 5, 5,MachineState.ERROR,MachineState.ERROR,#40-47
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#48-4f
+ MachineState.ERROR,MachineState.ERROR, 7, 7, 7, 7,MachineState.ERROR,MachineState.ERROR,#50-57
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#58-5f
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR, 7, 7,MachineState.ERROR,MachineState.ERROR,#60-67
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#68-6f
+ MachineState.ERROR,MachineState.ERROR, 9, 9, 9, 9,MachineState.ERROR,MachineState.ERROR,#70-77
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#78-7f
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR, 9,MachineState.ERROR,MachineState.ERROR,#80-87
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#88-8f
+ MachineState.ERROR,MachineState.ERROR, 12, 12, 12, 12,MachineState.ERROR,MachineState.ERROR,#90-97
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#98-9f
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR, 12,MachineState.ERROR,MachineState.ERROR,#a0-a7
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#a8-af
+ MachineState.ERROR,MachineState.ERROR, 12, 12, 12,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#b0-b7
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#b8-bf
+ MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,#c0-c7
+ MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR #c8-cf
+)
+# fmt: on
+
+UTF8_CHAR_LEN_TABLE = (0, 1, 0, 0, 0, 0, 2, 3, 3, 3, 4, 4, 5, 5, 6, 6)
+
+UTF8_SM_MODEL: CodingStateMachineDict = {
+ "class_table": UTF8_CLS,
+ "class_factor": 16,
+ "state_table": UTF8_ST,
+ "char_len_table": UTF8_CHAR_LEN_TABLE,
+ "name": "UTF-8",
+}
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/metadata/languages.py b/env-llmeval/lib/python3.10/site-packages/chardet/metadata/languages.py
new file mode 100644
index 0000000000000000000000000000000000000000..eb40c5f0c8526208d434d762855d23079dc68b36
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/metadata/languages.py
@@ -0,0 +1,352 @@
+"""
+Metadata about languages used by our model training code for our
+SingleByteCharSetProbers. Could be used for other things in the future.
+
+This code is based on the language metadata from the uchardet project.
+"""
+
+from string import ascii_letters
+from typing import List, Optional
+
+# TODO: Add Ukrainian (KOI8-U)
+
+
+class Language:
+ """Metadata about a language useful for training models
+
+ :ivar name: The human name for the language, in English.
+ :type name: str
+ :ivar iso_code: 2-letter ISO 639-1 if possible, 3-letter ISO code otherwise,
+ or use another catalog as a last resort.
+ :type iso_code: str
+ :ivar use_ascii: Whether or not ASCII letters should be included in trained
+ models.
+ :type use_ascii: bool
+ :ivar charsets: The charsets we want to support and create data for.
+ :type charsets: list of str
+ :ivar alphabet: The characters in the language's alphabet. If `use_ascii` is
+ `True`, you only need to add those not in the ASCII set.
+ :type alphabet: str
+ :ivar wiki_start_pages: The Wikipedia pages to start from if we're crawling
+ Wikipedia for training data.
+ :type wiki_start_pages: list of str
+ """
+
+ def __init__(
+ self,
+ name: Optional[str] = None,
+ iso_code: Optional[str] = None,
+ use_ascii: bool = True,
+ charsets: Optional[List[str]] = None,
+ alphabet: Optional[str] = None,
+ wiki_start_pages: Optional[List[str]] = None,
+ ) -> None:
+ super().__init__()
+ self.name = name
+ self.iso_code = iso_code
+ self.use_ascii = use_ascii
+ self.charsets = charsets
+ if self.use_ascii:
+ if alphabet:
+ alphabet += ascii_letters
+ else:
+ alphabet = ascii_letters
+ elif not alphabet:
+ raise ValueError("Must supply alphabet if use_ascii is False")
+ self.alphabet = "".join(sorted(set(alphabet))) if alphabet else None
+ self.wiki_start_pages = wiki_start_pages
+
+ def __repr__(self) -> str:
+ param_str = ", ".join(
+ f"{k}={v!r}" for k, v in self.__dict__.items() if not k.startswith("_")
+ )
+ return f"{self.__class__.__name__}({param_str})"
+
+
+LANGUAGES = {
+ "Arabic": Language(
+ name="Arabic",
+ iso_code="ar",
+ use_ascii=False,
+ # We only support encodings that use isolated
+ # forms, because the current recommendation is
+ # that the rendering system handles presentation
+ # forms. This means we purposefully skip IBM864.
+ charsets=["ISO-8859-6", "WINDOWS-1256", "CP720", "CP864"],
+ alphabet="ءآأؤإئابةتثجحخدذرزسشصضطظعغػؼؽؾؿـفقكلمنهوىيًٌٍَُِّ",
+ wiki_start_pages=["الصفحة_الرئيسية"],
+ ),
+ "Belarusian": Language(
+ name="Belarusian",
+ iso_code="be",
+ use_ascii=False,
+ charsets=["ISO-8859-5", "WINDOWS-1251", "IBM866", "MacCyrillic"],
+ alphabet="АБВГДЕЁЖЗІЙКЛМНОПРСТУЎФХЦЧШЫЬЭЮЯабвгдеёжзійклмнопрстуўфхцчшыьэюяʼ",
+ wiki_start_pages=["Галоўная_старонка"],
+ ),
+ "Bulgarian": Language(
+ name="Bulgarian",
+ iso_code="bg",
+ use_ascii=False,
+ charsets=["ISO-8859-5", "WINDOWS-1251", "IBM855"],
+ alphabet="АБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЬЮЯабвгдежзийклмнопрстуфхцчшщъьюя",
+ wiki_start_pages=["Начална_страница"],
+ ),
+ "Czech": Language(
+ name="Czech",
+ iso_code="cz",
+ use_ascii=True,
+ charsets=["ISO-8859-2", "WINDOWS-1250"],
+ alphabet="áčďéěíňóřšťúůýžÁČĎÉĚÍŇÓŘŠŤÚŮÝŽ",
+ wiki_start_pages=["Hlavní_strana"],
+ ),
+ "Danish": Language(
+ name="Danish",
+ iso_code="da",
+ use_ascii=True,
+ charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+ alphabet="æøåÆØÅ",
+ wiki_start_pages=["Forside"],
+ ),
+ "German": Language(
+ name="German",
+ iso_code="de",
+ use_ascii=True,
+ charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+ alphabet="äöüßẞÄÖÜ",
+ wiki_start_pages=["Wikipedia:Hauptseite"],
+ ),
+ "Greek": Language(
+ name="Greek",
+ iso_code="el",
+ use_ascii=False,
+ charsets=["ISO-8859-7", "WINDOWS-1253"],
+ alphabet="αβγδεζηθικλμνξοπρσςτυφχψωάέήίόύώΑΒΓΔΕΖΗΘΙΚΛΜΝΞΟΠΡΣΣΤΥΦΧΨΩΆΈΉΊΌΎΏ",
+ wiki_start_pages=["Πύλη:Κύρια"],
+ ),
+ "English": Language(
+ name="English",
+ iso_code="en",
+ use_ascii=True,
+ charsets=["ISO-8859-1", "WINDOWS-1252", "MacRoman"],
+ wiki_start_pages=["Main_Page"],
+ ),
+ "Esperanto": Language(
+ name="Esperanto",
+ iso_code="eo",
+ # Q, W, X, and Y not used at all
+ use_ascii=False,
+ charsets=["ISO-8859-3"],
+ alphabet="abcĉdefgĝhĥijĵklmnoprsŝtuŭvzABCĈDEFGĜHĤIJĴKLMNOPRSŜTUŬVZ",
+ wiki_start_pages=["Vikipedio:Ĉefpaĝo"],
+ ),
+ "Spanish": Language(
+ name="Spanish",
+ iso_code="es",
+ use_ascii=True,
+ charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+ alphabet="ñáéíóúüÑÁÉÍÓÚÜ",
+ wiki_start_pages=["Wikipedia:Portada"],
+ ),
+ "Estonian": Language(
+ name="Estonian",
+ iso_code="et",
+ use_ascii=False,
+ charsets=["ISO-8859-4", "ISO-8859-13", "WINDOWS-1257"],
+ # C, F, Š, Q, W, X, Y, Z, Ž are only for
+ # loanwords
+ alphabet="ABDEGHIJKLMNOPRSTUVÕÄÖÜabdeghijklmnoprstuvõäöü",
+ wiki_start_pages=["Esileht"],
+ ),
+ "Finnish": Language(
+ name="Finnish",
+ iso_code="fi",
+ use_ascii=True,
+ charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+ alphabet="ÅÄÖŠŽåäöšž",
+ wiki_start_pages=["Wikipedia:Etusivu"],
+ ),
+ "French": Language(
+ name="French",
+ iso_code="fr",
+ use_ascii=True,
+ charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+ alphabet="œàâçèéîïùûêŒÀÂÇÈÉÎÏÙÛÊ",
+ wiki_start_pages=["Wikipédia:Accueil_principal", "Bœuf (animal)"],
+ ),
+ "Hebrew": Language(
+ name="Hebrew",
+ iso_code="he",
+ use_ascii=False,
+ charsets=["ISO-8859-8", "WINDOWS-1255"],
+ alphabet="אבגדהוזחטיךכלםמןנסעףפץצקרשתװױײ",
+ wiki_start_pages=["עמוד_ראשי"],
+ ),
+ "Croatian": Language(
+ name="Croatian",
+ iso_code="hr",
+ # Q, W, X, Y are only used for foreign words.
+ use_ascii=False,
+ charsets=["ISO-8859-2", "WINDOWS-1250"],
+ alphabet="abcčćdđefghijklmnoprsštuvzžABCČĆDĐEFGHIJKLMNOPRSŠTUVZŽ",
+ wiki_start_pages=["Glavna_stranica"],
+ ),
+ "Hungarian": Language(
+ name="Hungarian",
+ iso_code="hu",
+ # Q, W, X, Y are only used for foreign words.
+ use_ascii=False,
+ charsets=["ISO-8859-2", "WINDOWS-1250"],
+ alphabet="abcdefghijklmnoprstuvzáéíóöőúüűABCDEFGHIJKLMNOPRSTUVZÁÉÍÓÖŐÚÜŰ",
+ wiki_start_pages=["Kezdőlap"],
+ ),
+ "Italian": Language(
+ name="Italian",
+ iso_code="it",
+ use_ascii=True,
+ charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+ alphabet="ÀÈÉÌÒÓÙàèéìòóù",
+ wiki_start_pages=["Pagina_principale"],
+ ),
+ "Lithuanian": Language(
+ name="Lithuanian",
+ iso_code="lt",
+ use_ascii=False,
+ charsets=["ISO-8859-13", "WINDOWS-1257", "ISO-8859-4"],
+ # Q, W, and X not used at all
+ alphabet="AĄBCČDEĘĖFGHIĮYJKLMNOPRSŠTUŲŪVZŽaąbcčdeęėfghiįyjklmnoprsštuųūvzž",
+ wiki_start_pages=["Pagrindinis_puslapis"],
+ ),
+ "Latvian": Language(
+ name="Latvian",
+ iso_code="lv",
+ use_ascii=False,
+ charsets=["ISO-8859-13", "WINDOWS-1257", "ISO-8859-4"],
+ # Q, W, X, Y are only for loanwords
+ alphabet="AĀBCČDEĒFGĢHIĪJKĶLĻMNŅOPRSŠTUŪVZŽaābcčdeēfgģhiījkķlļmnņoprsštuūvzž",
+ wiki_start_pages=["Sākumlapa"],
+ ),
+ "Macedonian": Language(
+ name="Macedonian",
+ iso_code="mk",
+ use_ascii=False,
+ charsets=["ISO-8859-5", "WINDOWS-1251", "MacCyrillic", "IBM855"],
+ alphabet="АБВГДЃЕЖЗЅИЈКЛЉМНЊОПРСТЌУФХЦЧЏШабвгдѓежзѕијклљмнњопрстќуфхцчџш",
+ wiki_start_pages=["Главна_страница"],
+ ),
+ "Dutch": Language(
+ name="Dutch",
+ iso_code="nl",
+ use_ascii=True,
+ charsets=["ISO-8859-1", "WINDOWS-1252", "MacRoman"],
+ wiki_start_pages=["Hoofdpagina"],
+ ),
+ "Polish": Language(
+ name="Polish",
+ iso_code="pl",
+ # Q and X are only used for foreign words.
+ use_ascii=False,
+ charsets=["ISO-8859-2", "WINDOWS-1250"],
+ alphabet="AĄBCĆDEĘFGHIJKLŁMNŃOÓPRSŚTUWYZŹŻaąbcćdeęfghijklłmnńoóprsśtuwyzźż",
+ wiki_start_pages=["Wikipedia:Strona_główna"],
+ ),
+ "Portuguese": Language(
+ name="Portuguese",
+ iso_code="pt",
+ use_ascii=True,
+ charsets=["ISO-8859-1", "ISO-8859-15", "WINDOWS-1252", "MacRoman"],
+ alphabet="ÁÂÃÀÇÉÊÍÓÔÕÚáâãàçéêíóôõú",
+ wiki_start_pages=["Wikipédia:Página_principal"],
+ ),
+ "Romanian": Language(
+ name="Romanian",
+ iso_code="ro",
+ use_ascii=True,
+ charsets=["ISO-8859-2", "WINDOWS-1250"],
+ alphabet="ăâîșțĂÂÎȘȚ",
+ wiki_start_pages=["Pagina_principală"],
+ ),
+ "Russian": Language(
+ name="Russian",
+ iso_code="ru",
+ use_ascii=False,
+ charsets=[
+ "ISO-8859-5",
+ "WINDOWS-1251",
+ "KOI8-R",
+ "MacCyrillic",
+ "IBM866",
+ "IBM855",
+ ],
+ alphabet="абвгдеёжзийклмнопрстуфхцчшщъыьэюяАБВГДЕЁЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯ",
+ wiki_start_pages=["Заглавная_страница"],
+ ),
+ "Slovak": Language(
+ name="Slovak",
+ iso_code="sk",
+ use_ascii=True,
+ charsets=["ISO-8859-2", "WINDOWS-1250"],
+ alphabet="áäčďéíĺľňóôŕšťúýžÁÄČĎÉÍĹĽŇÓÔŔŠŤÚÝŽ",
+ wiki_start_pages=["Hlavná_stránka"],
+ ),
+ "Slovene": Language(
+ name="Slovene",
+ iso_code="sl",
+ # Q, W, X, Y are only used for foreign words.
+ use_ascii=False,
+ charsets=["ISO-8859-2", "WINDOWS-1250"],
+ alphabet="abcčdefghijklmnoprsštuvzžABCČDEFGHIJKLMNOPRSŠTUVZŽ",
+ wiki_start_pages=["Glavna_stran"],
+ ),
+ # Serbian can be written in both Latin and Cyrillic, but there's no
+ # simple way to get the Latin alphabet pages from Wikipedia through
+ # the API, so for now we just support Cyrillic.
+ "Serbian": Language(
+ name="Serbian",
+ iso_code="sr",
+ alphabet="АБВГДЂЕЖЗИЈКЛЉМНЊОПРСТЋУФХЦЧЏШабвгдђежзијклљмнњопрстћуфхцчџш",
+ charsets=["ISO-8859-5", "WINDOWS-1251", "MacCyrillic", "IBM855"],
+ wiki_start_pages=["Главна_страна"],
+ ),
+ "Thai": Language(
+ name="Thai",
+ iso_code="th",
+ use_ascii=False,
+ charsets=["ISO-8859-11", "TIS-620", "CP874"],
+ alphabet="กขฃคฅฆงจฉชซฌญฎฏฐฑฒณดตถทธนบปผฝพฟภมยรฤลฦวศษสหฬอฮฯะัาำิีึืฺุู฿เแโใไๅๆ็่้๊๋์ํ๎๏๐๑๒๓๔๕๖๗๘๙๚๛",
+ wiki_start_pages=["หน้าหลัก"],
+ ),
+ "Turkish": Language(
+ name="Turkish",
+ iso_code="tr",
+ # Q, W, and X are not used by Turkish
+ use_ascii=False,
+ charsets=["ISO-8859-3", "ISO-8859-9", "WINDOWS-1254"],
+ alphabet="abcçdefgğhıijklmnoöprsştuüvyzâîûABCÇDEFGĞHIİJKLMNOÖPRSŞTUÜVYZÂÎÛ",
+ wiki_start_pages=["Ana_Sayfa"],
+ ),
+ "Vietnamese": Language(
+ name="Vietnamese",
+ iso_code="vi",
+ use_ascii=False,
+ # Windows-1258 is the only common 8-bit
+ # Vietnamese encoding supported by Python.
+ # From Wikipedia:
+ # For systems that lack support for Unicode,
+ # dozens of 8-bit Vietnamese code pages are
+ # available.[1] The most common are VISCII
+ # (TCVN 5712:1993), VPS, and Windows-1258.[3]
+ # Where ASCII is required, such as when
+ # ensuring readability in plain text e-mail,
+ # Vietnamese letters are often encoded
+ # according to Vietnamese Quoted-Readable
+ # (VIQR) or VSCII Mnemonic (VSCII-MNEM),[4]
+ # though usage of either variable-width
+ # scheme has declined dramatically following
+ # the adoption of Unicode on the World Wide
+ # Web.
+ charsets=["WINDOWS-1258"],
+ alphabet="aăâbcdđeêghiklmnoôơpqrstuưvxyAĂÂBCDĐEÊGHIKLMNOÔƠPQRSTUƯVXY",
+ wiki_start_pages=["Chữ_Quốc_ngữ"],
+ ),
+}
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/py.typed b/env-llmeval/lib/python3.10/site-packages/chardet/py.typed
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/resultdict.py b/env-llmeval/lib/python3.10/site-packages/chardet/resultdict.py
new file mode 100644
index 0000000000000000000000000000000000000000..7d36e64c467ca8d9cadc88ab03da71faf1aa8abb
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/resultdict.py
@@ -0,0 +1,16 @@
+from typing import TYPE_CHECKING, Optional
+
+if TYPE_CHECKING:
+ # TypedDict was introduced in Python 3.8.
+ #
+ # TODO: Remove the else block and TYPE_CHECKING check when dropping support
+ # for Python 3.7.
+ from typing import TypedDict
+
+ class ResultDict(TypedDict):
+ encoding: Optional[str]
+ confidence: float
+ language: Optional[str]
+
+else:
+ ResultDict = dict
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/sbcharsetprober.py b/env-llmeval/lib/python3.10/site-packages/chardet/sbcharsetprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..0ffbcdd2c3e21b68566c88a3f05239447489df84
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/sbcharsetprober.py
@@ -0,0 +1,162 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+# Shy Shalom - original C code
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Dict, List, NamedTuple, Optional, Union
+
+from .charsetprober import CharSetProber
+from .enums import CharacterCategory, ProbingState, SequenceLikelihood
+
+
+class SingleByteCharSetModel(NamedTuple):
+ charset_name: str
+ language: str
+ char_to_order_map: Dict[int, int]
+ language_model: Dict[int, Dict[int, int]]
+ typical_positive_ratio: float
+ keep_ascii_letters: bool
+ alphabet: str
+
+
+class SingleByteCharSetProber(CharSetProber):
+ SAMPLE_SIZE = 64
+ SB_ENOUGH_REL_THRESHOLD = 1024 # 0.25 * SAMPLE_SIZE^2
+ POSITIVE_SHORTCUT_THRESHOLD = 0.95
+ NEGATIVE_SHORTCUT_THRESHOLD = 0.05
+
+ def __init__(
+ self,
+ model: SingleByteCharSetModel,
+ is_reversed: bool = False,
+ name_prober: Optional[CharSetProber] = None,
+ ) -> None:
+ super().__init__()
+ self._model = model
+ # TRUE if we need to reverse every pair in the model lookup
+ self._reversed = is_reversed
+ # Optional auxiliary prober for name decision
+ self._name_prober = name_prober
+ self._last_order = 255
+ self._seq_counters: List[int] = []
+ self._total_seqs = 0
+ self._total_char = 0
+ self._control_char = 0
+ self._freq_char = 0
+ self.reset()
+
+ def reset(self) -> None:
+ super().reset()
+ # char order of last character
+ self._last_order = 255
+ self._seq_counters = [0] * SequenceLikelihood.get_num_categories()
+ self._total_seqs = 0
+ self._total_char = 0
+ self._control_char = 0
+ # characters that fall in our sampling range
+ self._freq_char = 0
+
+ @property
+ def charset_name(self) -> Optional[str]:
+ if self._name_prober:
+ return self._name_prober.charset_name
+ return self._model.charset_name
+
+ @property
+ def language(self) -> Optional[str]:
+ if self._name_prober:
+ return self._name_prober.language
+ return self._model.language
+
+ def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+ # TODO: Make filter_international_words keep things in self.alphabet
+ if not self._model.keep_ascii_letters:
+ byte_str = self.filter_international_words(byte_str)
+ else:
+ byte_str = self.remove_xml_tags(byte_str)
+ if not byte_str:
+ return self.state
+ char_to_order_map = self._model.char_to_order_map
+ language_model = self._model.language_model
+ for char in byte_str:
+ order = char_to_order_map.get(char, CharacterCategory.UNDEFINED)
+ # XXX: This was SYMBOL_CAT_ORDER before, with a value of 250, but
+ # CharacterCategory.SYMBOL is actually 253, so we use CONTROL
+ # to make it closer to the original intent. The only difference
+ # is whether or not we count digits and control characters for
+ # _total_char purposes.
+ if order < CharacterCategory.CONTROL:
+ self._total_char += 1
+ if order < self.SAMPLE_SIZE:
+ self._freq_char += 1
+ if self._last_order < self.SAMPLE_SIZE:
+ self._total_seqs += 1
+ if not self._reversed:
+ lm_cat = language_model[self._last_order][order]
+ else:
+ lm_cat = language_model[order][self._last_order]
+ self._seq_counters[lm_cat] += 1
+ self._last_order = order
+
+ charset_name = self._model.charset_name
+ if self.state == ProbingState.DETECTING:
+ if self._total_seqs > self.SB_ENOUGH_REL_THRESHOLD:
+ confidence = self.get_confidence()
+ if confidence > self.POSITIVE_SHORTCUT_THRESHOLD:
+ self.logger.debug(
+ "%s confidence = %s, we have a winner", charset_name, confidence
+ )
+ self._state = ProbingState.FOUND_IT
+ elif confidence < self.NEGATIVE_SHORTCUT_THRESHOLD:
+ self.logger.debug(
+ "%s confidence = %s, below negative shortcut threshold %s",
+ charset_name,
+ confidence,
+ self.NEGATIVE_SHORTCUT_THRESHOLD,
+ )
+ self._state = ProbingState.NOT_ME
+
+ return self.state
+
+ def get_confidence(self) -> float:
+ r = 0.01
+ if self._total_seqs > 0:
+ r = (
+ (
+ self._seq_counters[SequenceLikelihood.POSITIVE]
+ + 0.25 * self._seq_counters[SequenceLikelihood.LIKELY]
+ )
+ / self._total_seqs
+ / self._model.typical_positive_ratio
+ )
+ # The more control characters (proportionnaly to the size
+ # of the text), the less confident we become in the current
+ # charset.
+ r = r * (self._total_char - self._control_char) / self._total_char
+ r = r * self._freq_char / self._total_char
+ if r >= 1.0:
+ r = 0.99
+ return r
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/sbcsgroupprober.py b/env-llmeval/lib/python3.10/site-packages/chardet/sbcsgroupprober.py
new file mode 100644
index 0000000000000000000000000000000000000000..890ae8465c5b0ad2a5f99464fe5f5c0be49809f1
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/sbcsgroupprober.py
@@ -0,0 +1,88 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+# Shy Shalom - original C code
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from .charsetgroupprober import CharSetGroupProber
+from .hebrewprober import HebrewProber
+from .langbulgarianmodel import ISO_8859_5_BULGARIAN_MODEL, WINDOWS_1251_BULGARIAN_MODEL
+from .langgreekmodel import ISO_8859_7_GREEK_MODEL, WINDOWS_1253_GREEK_MODEL
+from .langhebrewmodel import WINDOWS_1255_HEBREW_MODEL
+
+# from .langhungarianmodel import (ISO_8859_2_HUNGARIAN_MODEL,
+# WINDOWS_1250_HUNGARIAN_MODEL)
+from .langrussianmodel import (
+ IBM855_RUSSIAN_MODEL,
+ IBM866_RUSSIAN_MODEL,
+ ISO_8859_5_RUSSIAN_MODEL,
+ KOI8_R_RUSSIAN_MODEL,
+ MACCYRILLIC_RUSSIAN_MODEL,
+ WINDOWS_1251_RUSSIAN_MODEL,
+)
+from .langthaimodel import TIS_620_THAI_MODEL
+from .langturkishmodel import ISO_8859_9_TURKISH_MODEL
+from .sbcharsetprober import SingleByteCharSetProber
+
+
+class SBCSGroupProber(CharSetGroupProber):
+ def __init__(self) -> None:
+ super().__init__()
+ hebrew_prober = HebrewProber()
+ logical_hebrew_prober = SingleByteCharSetProber(
+ WINDOWS_1255_HEBREW_MODEL, is_reversed=False, name_prober=hebrew_prober
+ )
+ # TODO: See if using ISO-8859-8 Hebrew model works better here, since
+ # it's actually the visual one
+ visual_hebrew_prober = SingleByteCharSetProber(
+ WINDOWS_1255_HEBREW_MODEL, is_reversed=True, name_prober=hebrew_prober
+ )
+ hebrew_prober.set_model_probers(logical_hebrew_prober, visual_hebrew_prober)
+ # TODO: ORDER MATTERS HERE. I changed the order vs what was in master
+ # and several tests failed that did not before. Some thought
+ # should be put into the ordering, and we should consider making
+ # order not matter here, because that is very counter-intuitive.
+ self.probers = [
+ SingleByteCharSetProber(WINDOWS_1251_RUSSIAN_MODEL),
+ SingleByteCharSetProber(KOI8_R_RUSSIAN_MODEL),
+ SingleByteCharSetProber(ISO_8859_5_RUSSIAN_MODEL),
+ SingleByteCharSetProber(MACCYRILLIC_RUSSIAN_MODEL),
+ SingleByteCharSetProber(IBM866_RUSSIAN_MODEL),
+ SingleByteCharSetProber(IBM855_RUSSIAN_MODEL),
+ SingleByteCharSetProber(ISO_8859_7_GREEK_MODEL),
+ SingleByteCharSetProber(WINDOWS_1253_GREEK_MODEL),
+ SingleByteCharSetProber(ISO_8859_5_BULGARIAN_MODEL),
+ SingleByteCharSetProber(WINDOWS_1251_BULGARIAN_MODEL),
+ # TODO: Restore Hungarian encodings (iso-8859-2 and windows-1250)
+ # after we retrain model.
+ # SingleByteCharSetProber(ISO_8859_2_HUNGARIAN_MODEL),
+ # SingleByteCharSetProber(WINDOWS_1250_HUNGARIAN_MODEL),
+ SingleByteCharSetProber(TIS_620_THAI_MODEL),
+ SingleByteCharSetProber(ISO_8859_9_TURKISH_MODEL),
+ hebrew_prober,
+ logical_hebrew_prober,
+ visual_hebrew_prober,
+ ]
+ self.reset()
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/universaldetector.py b/env-llmeval/lib/python3.10/site-packages/chardet/universaldetector.py
new file mode 100644
index 0000000000000000000000000000000000000000..30c441dc28ee327076a850b1d3c88a9a2c8f04f0
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/universaldetector.py
@@ -0,0 +1,362 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+# Shy Shalom - original C code
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+"""
+Module containing the UniversalDetector detector class, which is the primary
+class a user of ``chardet`` should use.
+
+:author: Mark Pilgrim (initial port to Python)
+:author: Shy Shalom (original C code)
+:author: Dan Blanchard (major refactoring for 3.0)
+:author: Ian Cordasco
+"""
+
+
+import codecs
+import logging
+import re
+from typing import List, Optional, Union
+
+from .charsetgroupprober import CharSetGroupProber
+from .charsetprober import CharSetProber
+from .enums import InputState, LanguageFilter, ProbingState
+from .escprober import EscCharSetProber
+from .latin1prober import Latin1Prober
+from .macromanprober import MacRomanProber
+from .mbcsgroupprober import MBCSGroupProber
+from .resultdict import ResultDict
+from .sbcsgroupprober import SBCSGroupProber
+from .utf1632prober import UTF1632Prober
+
+
+class UniversalDetector:
+ """
+ The ``UniversalDetector`` class underlies the ``chardet.detect`` function
+ and coordinates all of the different charset probers.
+
+ To get a ``dict`` containing an encoding and its confidence, you can simply
+ run:
+
+ .. code::
+
+ u = UniversalDetector()
+ u.feed(some_bytes)
+ u.close()
+ detected = u.result
+
+ """
+
+ MINIMUM_THRESHOLD = 0.20
+ HIGH_BYTE_DETECTOR = re.compile(b"[\x80-\xFF]")
+ ESC_DETECTOR = re.compile(b"(\033|~{)")
+ WIN_BYTE_DETECTOR = re.compile(b"[\x80-\x9F]")
+ ISO_WIN_MAP = {
+ "iso-8859-1": "Windows-1252",
+ "iso-8859-2": "Windows-1250",
+ "iso-8859-5": "Windows-1251",
+ "iso-8859-6": "Windows-1256",
+ "iso-8859-7": "Windows-1253",
+ "iso-8859-8": "Windows-1255",
+ "iso-8859-9": "Windows-1254",
+ "iso-8859-13": "Windows-1257",
+ }
+ # Based on https://encoding.spec.whatwg.org/#names-and-labels
+ # but altered to match Python names for encodings and remove mappings
+ # that break tests.
+ LEGACY_MAP = {
+ "ascii": "Windows-1252",
+ "iso-8859-1": "Windows-1252",
+ "tis-620": "ISO-8859-11",
+ "iso-8859-9": "Windows-1254",
+ "gb2312": "GB18030",
+ "euc-kr": "CP949",
+ "utf-16le": "UTF-16",
+ }
+
+ def __init__(
+ self,
+ lang_filter: LanguageFilter = LanguageFilter.ALL,
+ should_rename_legacy: bool = False,
+ ) -> None:
+ self._esc_charset_prober: Optional[EscCharSetProber] = None
+ self._utf1632_prober: Optional[UTF1632Prober] = None
+ self._charset_probers: List[CharSetProber] = []
+ self.result: ResultDict = {
+ "encoding": None,
+ "confidence": 0.0,
+ "language": None,
+ }
+ self.done = False
+ self._got_data = False
+ self._input_state = InputState.PURE_ASCII
+ self._last_char = b""
+ self.lang_filter = lang_filter
+ self.logger = logging.getLogger(__name__)
+ self._has_win_bytes = False
+ self.should_rename_legacy = should_rename_legacy
+ self.reset()
+
+ @property
+ def input_state(self) -> int:
+ return self._input_state
+
+ @property
+ def has_win_bytes(self) -> bool:
+ return self._has_win_bytes
+
+ @property
+ def charset_probers(self) -> List[CharSetProber]:
+ return self._charset_probers
+
+ def reset(self) -> None:
+ """
+ Reset the UniversalDetector and all of its probers back to their
+ initial states. This is called by ``__init__``, so you only need to
+ call this directly in between analyses of different documents.
+ """
+ self.result = {"encoding": None, "confidence": 0.0, "language": None}
+ self.done = False
+ self._got_data = False
+ self._has_win_bytes = False
+ self._input_state = InputState.PURE_ASCII
+ self._last_char = b""
+ if self._esc_charset_prober:
+ self._esc_charset_prober.reset()
+ if self._utf1632_prober:
+ self._utf1632_prober.reset()
+ for prober in self._charset_probers:
+ prober.reset()
+
+ def feed(self, byte_str: Union[bytes, bytearray]) -> None:
+ """
+ Takes a chunk of a document and feeds it through all of the relevant
+ charset probers.
+
+ After calling ``feed``, you can check the value of the ``done``
+ attribute to see if you need to continue feeding the
+ ``UniversalDetector`` more data, or if it has made a prediction
+ (in the ``result`` attribute).
+
+ .. note::
+ You should always call ``close`` when you're done feeding in your
+ document if ``done`` is not already ``True``.
+ """
+ if self.done:
+ return
+
+ if not byte_str:
+ return
+
+ if not isinstance(byte_str, bytearray):
+ byte_str = bytearray(byte_str)
+
+ # First check for known BOMs, since these are guaranteed to be correct
+ if not self._got_data:
+ # If the data starts with BOM, we know it is UTF
+ if byte_str.startswith(codecs.BOM_UTF8):
+ # EF BB BF UTF-8 with BOM
+ self.result = {
+ "encoding": "UTF-8-SIG",
+ "confidence": 1.0,
+ "language": "",
+ }
+ elif byte_str.startswith((codecs.BOM_UTF32_LE, codecs.BOM_UTF32_BE)):
+ # FF FE 00 00 UTF-32, little-endian BOM
+ # 00 00 FE FF UTF-32, big-endian BOM
+ self.result = {"encoding": "UTF-32", "confidence": 1.0, "language": ""}
+ elif byte_str.startswith(b"\xFE\xFF\x00\x00"):
+ # FE FF 00 00 UCS-4, unusual octet order BOM (3412)
+ self.result = {
+ # TODO: This encoding is not supported by Python. Should remove?
+ "encoding": "X-ISO-10646-UCS-4-3412",
+ "confidence": 1.0,
+ "language": "",
+ }
+ elif byte_str.startswith(b"\x00\x00\xFF\xFE"):
+ # 00 00 FF FE UCS-4, unusual octet order BOM (2143)
+ self.result = {
+ # TODO: This encoding is not supported by Python. Should remove?
+ "encoding": "X-ISO-10646-UCS-4-2143",
+ "confidence": 1.0,
+ "language": "",
+ }
+ elif byte_str.startswith((codecs.BOM_LE, codecs.BOM_BE)):
+ # FF FE UTF-16, little endian BOM
+ # FE FF UTF-16, big endian BOM
+ self.result = {"encoding": "UTF-16", "confidence": 1.0, "language": ""}
+
+ self._got_data = True
+ if self.result["encoding"] is not None:
+ self.done = True
+ return
+
+ # If none of those matched and we've only see ASCII so far, check
+ # for high bytes and escape sequences
+ if self._input_state == InputState.PURE_ASCII:
+ if self.HIGH_BYTE_DETECTOR.search(byte_str):
+ self._input_state = InputState.HIGH_BYTE
+ elif (
+ self._input_state == InputState.PURE_ASCII
+ and self.ESC_DETECTOR.search(self._last_char + byte_str)
+ ):
+ self._input_state = InputState.ESC_ASCII
+
+ self._last_char = byte_str[-1:]
+
+ # next we will look to see if it is appears to be either a UTF-16 or
+ # UTF-32 encoding
+ if not self._utf1632_prober:
+ self._utf1632_prober = UTF1632Prober()
+
+ if self._utf1632_prober.state == ProbingState.DETECTING:
+ if self._utf1632_prober.feed(byte_str) == ProbingState.FOUND_IT:
+ self.result = {
+ "encoding": self._utf1632_prober.charset_name,
+ "confidence": self._utf1632_prober.get_confidence(),
+ "language": "",
+ }
+ self.done = True
+ return
+
+ # If we've seen escape sequences, use the EscCharSetProber, which
+ # uses a simple state machine to check for known escape sequences in
+ # HZ and ISO-2022 encodings, since those are the only encodings that
+ # use such sequences.
+ if self._input_state == InputState.ESC_ASCII:
+ if not self._esc_charset_prober:
+ self._esc_charset_prober = EscCharSetProber(self.lang_filter)
+ if self._esc_charset_prober.feed(byte_str) == ProbingState.FOUND_IT:
+ self.result = {
+ "encoding": self._esc_charset_prober.charset_name,
+ "confidence": self._esc_charset_prober.get_confidence(),
+ "language": self._esc_charset_prober.language,
+ }
+ self.done = True
+ # If we've seen high bytes (i.e., those with values greater than 127),
+ # we need to do more complicated checks using all our multi-byte and
+ # single-byte probers that are left. The single-byte probers
+ # use character bigram distributions to determine the encoding, whereas
+ # the multi-byte probers use a combination of character unigram and
+ # bigram distributions.
+ elif self._input_state == InputState.HIGH_BYTE:
+ if not self._charset_probers:
+ self._charset_probers = [MBCSGroupProber(self.lang_filter)]
+ # If we're checking non-CJK encodings, use single-byte prober
+ if self.lang_filter & LanguageFilter.NON_CJK:
+ self._charset_probers.append(SBCSGroupProber())
+ self._charset_probers.append(Latin1Prober())
+ self._charset_probers.append(MacRomanProber())
+ for prober in self._charset_probers:
+ if prober.feed(byte_str) == ProbingState.FOUND_IT:
+ self.result = {
+ "encoding": prober.charset_name,
+ "confidence": prober.get_confidence(),
+ "language": prober.language,
+ }
+ self.done = True
+ break
+ if self.WIN_BYTE_DETECTOR.search(byte_str):
+ self._has_win_bytes = True
+
+ def close(self) -> ResultDict:
+ """
+ Stop analyzing the current document and come up with a final
+ prediction.
+
+ :returns: The ``result`` attribute, a ``dict`` with the keys
+ `encoding`, `confidence`, and `language`.
+ """
+ # Don't bother with checks if we're already done
+ if self.done:
+ return self.result
+ self.done = True
+
+ if not self._got_data:
+ self.logger.debug("no data received!")
+
+ # Default to ASCII if it is all we've seen so far
+ elif self._input_state == InputState.PURE_ASCII:
+ self.result = {"encoding": "ascii", "confidence": 1.0, "language": ""}
+
+ # If we have seen non-ASCII, return the best that met MINIMUM_THRESHOLD
+ elif self._input_state == InputState.HIGH_BYTE:
+ prober_confidence = None
+ max_prober_confidence = 0.0
+ max_prober = None
+ for prober in self._charset_probers:
+ if not prober:
+ continue
+ prober_confidence = prober.get_confidence()
+ if prober_confidence > max_prober_confidence:
+ max_prober_confidence = prober_confidence
+ max_prober = prober
+ if max_prober and (max_prober_confidence > self.MINIMUM_THRESHOLD):
+ charset_name = max_prober.charset_name
+ assert charset_name is not None
+ lower_charset_name = charset_name.lower()
+ confidence = max_prober.get_confidence()
+ # Use Windows encoding name instead of ISO-8859 if we saw any
+ # extra Windows-specific bytes
+ if lower_charset_name.startswith("iso-8859"):
+ if self._has_win_bytes:
+ charset_name = self.ISO_WIN_MAP.get(
+ lower_charset_name, charset_name
+ )
+ # Rename legacy encodings with superset encodings if asked
+ if self.should_rename_legacy:
+ charset_name = self.LEGACY_MAP.get(
+ (charset_name or "").lower(), charset_name
+ )
+ self.result = {
+ "encoding": charset_name,
+ "confidence": confidence,
+ "language": max_prober.language,
+ }
+
+ # Log all prober confidences if none met MINIMUM_THRESHOLD
+ if self.logger.getEffectiveLevel() <= logging.DEBUG:
+ if self.result["encoding"] is None:
+ self.logger.debug("no probers hit minimum threshold")
+ for group_prober in self._charset_probers:
+ if not group_prober:
+ continue
+ if isinstance(group_prober, CharSetGroupProber):
+ for prober in group_prober.probers:
+ self.logger.debug(
+ "%s %s confidence = %s",
+ prober.charset_name,
+ prober.language,
+ prober.get_confidence(),
+ )
+ else:
+ self.logger.debug(
+ "%s %s confidence = %s",
+ group_prober.charset_name,
+ group_prober.language,
+ group_prober.get_confidence(),
+ )
+ return self.result
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/utf1632prober.py b/env-llmeval/lib/python3.10/site-packages/chardet/utf1632prober.py
new file mode 100644
index 0000000000000000000000000000000000000000..6bdec63d6867928bf73a7e513f60cee8f49ca050
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/utf1632prober.py
@@ -0,0 +1,225 @@
+######################## BEGIN LICENSE BLOCK ########################
+#
+# Contributor(s):
+# Jason Zavaglia
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+from typing import List, Union
+
+from .charsetprober import CharSetProber
+from .enums import ProbingState
+
+
+class UTF1632Prober(CharSetProber):
+ """
+ This class simply looks for occurrences of zero bytes, and infers
+ whether the file is UTF16 or UTF32 (low-endian or big-endian)
+ For instance, files looking like ( \0 \0 \0 [nonzero] )+
+ have a good probability to be UTF32BE. Files looking like ( \0 [nonzero] )+
+ may be guessed to be UTF16BE, and inversely for little-endian varieties.
+ """
+
+ # how many logical characters to scan before feeling confident of prediction
+ MIN_CHARS_FOR_DETECTION = 20
+ # a fixed constant ratio of expected zeros or non-zeros in modulo-position.
+ EXPECTED_RATIO = 0.94
+
+ def __init__(self) -> None:
+ super().__init__()
+ self.position = 0
+ self.zeros_at_mod = [0] * 4
+ self.nonzeros_at_mod = [0] * 4
+ self._state = ProbingState.DETECTING
+ self.quad = [0, 0, 0, 0]
+ self.invalid_utf16be = False
+ self.invalid_utf16le = False
+ self.invalid_utf32be = False
+ self.invalid_utf32le = False
+ self.first_half_surrogate_pair_detected_16be = False
+ self.first_half_surrogate_pair_detected_16le = False
+ self.reset()
+
+ def reset(self) -> None:
+ super().reset()
+ self.position = 0
+ self.zeros_at_mod = [0] * 4
+ self.nonzeros_at_mod = [0] * 4
+ self._state = ProbingState.DETECTING
+ self.invalid_utf16be = False
+ self.invalid_utf16le = False
+ self.invalid_utf32be = False
+ self.invalid_utf32le = False
+ self.first_half_surrogate_pair_detected_16be = False
+ self.first_half_surrogate_pair_detected_16le = False
+ self.quad = [0, 0, 0, 0]
+
+ @property
+ def charset_name(self) -> str:
+ if self.is_likely_utf32be():
+ return "utf-32be"
+ if self.is_likely_utf32le():
+ return "utf-32le"
+ if self.is_likely_utf16be():
+ return "utf-16be"
+ if self.is_likely_utf16le():
+ return "utf-16le"
+ # default to something valid
+ return "utf-16"
+
+ @property
+ def language(self) -> str:
+ return ""
+
+ def approx_32bit_chars(self) -> float:
+ return max(1.0, self.position / 4.0)
+
+ def approx_16bit_chars(self) -> float:
+ return max(1.0, self.position / 2.0)
+
+ def is_likely_utf32be(self) -> bool:
+ approx_chars = self.approx_32bit_chars()
+ return approx_chars >= self.MIN_CHARS_FOR_DETECTION and (
+ self.zeros_at_mod[0] / approx_chars > self.EXPECTED_RATIO
+ and self.zeros_at_mod[1] / approx_chars > self.EXPECTED_RATIO
+ and self.zeros_at_mod[2] / approx_chars > self.EXPECTED_RATIO
+ and self.nonzeros_at_mod[3] / approx_chars > self.EXPECTED_RATIO
+ and not self.invalid_utf32be
+ )
+
+ def is_likely_utf32le(self) -> bool:
+ approx_chars = self.approx_32bit_chars()
+ return approx_chars >= self.MIN_CHARS_FOR_DETECTION and (
+ self.nonzeros_at_mod[0] / approx_chars > self.EXPECTED_RATIO
+ and self.zeros_at_mod[1] / approx_chars > self.EXPECTED_RATIO
+ and self.zeros_at_mod[2] / approx_chars > self.EXPECTED_RATIO
+ and self.zeros_at_mod[3] / approx_chars > self.EXPECTED_RATIO
+ and not self.invalid_utf32le
+ )
+
+ def is_likely_utf16be(self) -> bool:
+ approx_chars = self.approx_16bit_chars()
+ return approx_chars >= self.MIN_CHARS_FOR_DETECTION and (
+ (self.nonzeros_at_mod[1] + self.nonzeros_at_mod[3]) / approx_chars
+ > self.EXPECTED_RATIO
+ and (self.zeros_at_mod[0] + self.zeros_at_mod[2]) / approx_chars
+ > self.EXPECTED_RATIO
+ and not self.invalid_utf16be
+ )
+
+ def is_likely_utf16le(self) -> bool:
+ approx_chars = self.approx_16bit_chars()
+ return approx_chars >= self.MIN_CHARS_FOR_DETECTION and (
+ (self.nonzeros_at_mod[0] + self.nonzeros_at_mod[2]) / approx_chars
+ > self.EXPECTED_RATIO
+ and (self.zeros_at_mod[1] + self.zeros_at_mod[3]) / approx_chars
+ > self.EXPECTED_RATIO
+ and not self.invalid_utf16le
+ )
+
+ def validate_utf32_characters(self, quad: List[int]) -> None:
+ """
+ Validate if the quad of bytes is valid UTF-32.
+
+ UTF-32 is valid in the range 0x00000000 - 0x0010FFFF
+ excluding 0x0000D800 - 0x0000DFFF
+
+ https://en.wikipedia.org/wiki/UTF-32
+ """
+ if (
+ quad[0] != 0
+ or quad[1] > 0x10
+ or (quad[0] == 0 and quad[1] == 0 and 0xD8 <= quad[2] <= 0xDF)
+ ):
+ self.invalid_utf32be = True
+ if (
+ quad[3] != 0
+ or quad[2] > 0x10
+ or (quad[3] == 0 and quad[2] == 0 and 0xD8 <= quad[1] <= 0xDF)
+ ):
+ self.invalid_utf32le = True
+
+ def validate_utf16_characters(self, pair: List[int]) -> None:
+ """
+ Validate if the pair of bytes is valid UTF-16.
+
+ UTF-16 is valid in the range 0x0000 - 0xFFFF excluding 0xD800 - 0xFFFF
+ with an exception for surrogate pairs, which must be in the range
+ 0xD800-0xDBFF followed by 0xDC00-0xDFFF
+
+ https://en.wikipedia.org/wiki/UTF-16
+ """
+ if not self.first_half_surrogate_pair_detected_16be:
+ if 0xD8 <= pair[0] <= 0xDB:
+ self.first_half_surrogate_pair_detected_16be = True
+ elif 0xDC <= pair[0] <= 0xDF:
+ self.invalid_utf16be = True
+ else:
+ if 0xDC <= pair[0] <= 0xDF:
+ self.first_half_surrogate_pair_detected_16be = False
+ else:
+ self.invalid_utf16be = True
+
+ if not self.first_half_surrogate_pair_detected_16le:
+ if 0xD8 <= pair[1] <= 0xDB:
+ self.first_half_surrogate_pair_detected_16le = True
+ elif 0xDC <= pair[1] <= 0xDF:
+ self.invalid_utf16le = True
+ else:
+ if 0xDC <= pair[1] <= 0xDF:
+ self.first_half_surrogate_pair_detected_16le = False
+ else:
+ self.invalid_utf16le = True
+
+ def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+ for c in byte_str:
+ mod4 = self.position % 4
+ self.quad[mod4] = c
+ if mod4 == 3:
+ self.validate_utf32_characters(self.quad)
+ self.validate_utf16_characters(self.quad[0:2])
+ self.validate_utf16_characters(self.quad[2:4])
+ if c == 0:
+ self.zeros_at_mod[mod4] += 1
+ else:
+ self.nonzeros_at_mod[mod4] += 1
+ self.position += 1
+ return self.state
+
+ @property
+ def state(self) -> ProbingState:
+ if self._state in {ProbingState.NOT_ME, ProbingState.FOUND_IT}:
+ # terminal, decided states
+ return self._state
+ if self.get_confidence() > 0.80:
+ self._state = ProbingState.FOUND_IT
+ elif self.position > 4 * 1024:
+ # if we get to 4kb into the file, and we can't conclude it's UTF,
+ # let's give up
+ self._state = ProbingState.NOT_ME
+ return self._state
+
+ def get_confidence(self) -> float:
+ return (
+ 0.85
+ if (
+ self.is_likely_utf16le()
+ or self.is_likely_utf16be()
+ or self.is_likely_utf32le()
+ or self.is_likely_utf32be()
+ )
+ else 0.00
+ )
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/utf8prober.py b/env-llmeval/lib/python3.10/site-packages/chardet/utf8prober.py
new file mode 100644
index 0000000000000000000000000000000000000000..d96354d97c2195320d0acc1717a5876eafbea2af
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/utf8prober.py
@@ -0,0 +1,82 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+# Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301 USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Union
+
+from .charsetprober import CharSetProber
+from .codingstatemachine import CodingStateMachine
+from .enums import MachineState, ProbingState
+from .mbcssm import UTF8_SM_MODEL
+
+
+class UTF8Prober(CharSetProber):
+ ONE_CHAR_PROB = 0.5
+
+ def __init__(self) -> None:
+ super().__init__()
+ self.coding_sm = CodingStateMachine(UTF8_SM_MODEL)
+ self._num_mb_chars = 0
+ self.reset()
+
+ def reset(self) -> None:
+ super().reset()
+ self.coding_sm.reset()
+ self._num_mb_chars = 0
+
+ @property
+ def charset_name(self) -> str:
+ return "utf-8"
+
+ @property
+ def language(self) -> str:
+ return ""
+
+ def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+ for c in byte_str:
+ coding_state = self.coding_sm.next_state(c)
+ if coding_state == MachineState.ERROR:
+ self._state = ProbingState.NOT_ME
+ break
+ if coding_state == MachineState.ITS_ME:
+ self._state = ProbingState.FOUND_IT
+ break
+ if coding_state == MachineState.START:
+ if self.coding_sm.get_current_charlen() >= 2:
+ self._num_mb_chars += 1
+
+ if self.state == ProbingState.DETECTING:
+ if self.get_confidence() > self.SHORTCUT_THRESHOLD:
+ self._state = ProbingState.FOUND_IT
+
+ return self.state
+
+ def get_confidence(self) -> float:
+ unlike = 0.99
+ if self._num_mb_chars < 6:
+ unlike *= self.ONE_CHAR_PROB**self._num_mb_chars
+ return 1.0 - unlike
+ return unlike
diff --git a/env-llmeval/lib/python3.10/site-packages/chardet/version.py b/env-llmeval/lib/python3.10/site-packages/chardet/version.py
new file mode 100644
index 0000000000000000000000000000000000000000..19dd01e030156d04171bac727474595fba305864
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/chardet/version.py
@@ -0,0 +1,9 @@
+"""
+This module exists only to simplify retrieving the version number of chardet
+from within setuptools and from chardet subpackages.
+
+:author: Dan Blanchard (dan.blanchard@gmail.com)
+"""
+
+__version__ = "5.2.0"
+VERSION = __version__.split(".")
diff --git a/env-llmeval/lib/python3.10/site-packages/datasets-2.18.0.dist-info/INSTALLER b/env-llmeval/lib/python3.10/site-packages/datasets-2.18.0.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/datasets-2.18.0.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/env-llmeval/lib/python3.10/site-packages/datasets-2.18.0.dist-info/RECORD b/env-llmeval/lib/python3.10/site-packages/datasets-2.18.0.dist-info/RECORD
new file mode 100644
index 0000000000000000000000000000000000000000..4354b90d95dca1a609eb37ea243f2e371802e397
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/datasets-2.18.0.dist-info/RECORD
@@ -0,0 +1,266 @@
+../../../bin/datasets-cli,sha256=0T7eo6jxX7Q6jTzRsQFa-IoZHIQNbFMRN5X2xr9QLJI,255
+datasets-2.18.0.dist-info/AUTHORS,sha256=L0FBY23tCNHLmvsOKAbumHn8WZZIK98sH53JYxhAchU,327
+datasets-2.18.0.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
+datasets-2.18.0.dist-info/LICENSE,sha256=z8d0m5b2O9McPEK1xHG_dWgUBT6EfBDz6wA0F7xSPTA,11358
+datasets-2.18.0.dist-info/METADATA,sha256=iofh0c59MukgtcdWyBnwPSLwiNuoo_seBOvfpf2GODk,20140
+datasets-2.18.0.dist-info/RECORD,,
+datasets-2.18.0.dist-info/WHEEL,sha256=pkctZYzUS4AYVn6dJ-7367OJZivF2e8RA9b_ZBjif18,92
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new file mode 100644
index 0000000000000000000000000000000000000000..1f37c02f2eb2e26b306202feaccb31e522b8b169
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/datasets-2.18.0.dist-info/WHEEL
@@ -0,0 +1,5 @@
+Wheel-Version: 1.0
+Generator: bdist_wheel (0.40.0)
+Root-Is-Purelib: true
+Tag: py3-none-any
+
diff --git a/env-llmeval/lib/python3.10/site-packages/datasets-2.18.0.dist-info/top_level.txt b/env-llmeval/lib/python3.10/site-packages/datasets-2.18.0.dist-info/top_level.txt
new file mode 100644
index 0000000000000000000000000000000000000000..aee11b288aa3e6803c53bde002f7594c44497f5b
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/datasets-2.18.0.dist-info/top_level.txt
@@ -0,0 +1 @@
+datasets
diff --git a/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/AUTHORS.txt b/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/AUTHORS.txt
new file mode 100644
index 0000000000000000000000000000000000000000..88b904760b5f8950189dd1c2c30da8fb3b22374f
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/AUTHORS.txt
@@ -0,0 +1,31 @@
+Numexpr was initially written by David Cooke, and extended to more
+types by Tim Hochberg.
+
+Francesc Alted contributed support for booleans and simple-precision
+floating point types, efficient strided and unaligned array operations
+and multi-threading code.
+
+Ivan Vilata contributed support for strings.
+
+Gregor Thalhammer implemented the support for Intel VML (Vector Math
+Library).
+
+Mark Wiebe added support for the new iterator in NumPy, which allows
+for better performance in more scenarios (like broadcasting,
+fortran-ordered or non-native byte orderings).
+
+Gaëtan de Menten contributed important bug fixes and speed
+enhancements.
+
+Antonio Valentino contributed the port to Python 3.
+
+Google Inc. contributed bug fixes.
+
+David Cox improved readability of the Readme.
+
+Robert A. McLeod contributed bug fixes and ported the documentation to
+numexpr.readthedocs.io. He has served as the maintainer of the package
+since 2016 to 2023.
+
+Teng Liu fixed many bugs, and in particular, contributed valuable fixes
+to the new regex sanitizer for expressions.
diff --git a/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/INSTALLER b/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/INSTALLER
new file mode 100644
index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/INSTALLER
@@ -0,0 +1 @@
+pip
diff --git a/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/LICENSE.txt b/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/LICENSE.txt
new file mode 100644
index 0000000000000000000000000000000000000000..de9a582603ca6aa895136e2b118443e9397897da
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/LICENSE.txt
@@ -0,0 +1,21 @@
+Copyright (c) 2007,2008 David M. Cooke
+Copyright (c) 2009,2010 Francesc Alted
+Copyright (c) 2011- See AUTHORS.txt
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.
diff --git a/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/METADATA b/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/METADATA
new file mode 100644
index 0000000000000000000000000000000000000000..eed663cf8b60f10356bdeff476d6307d6d1bc8b2
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/METADATA
@@ -0,0 +1,212 @@
+Metadata-Version: 2.1
+Name: numexpr
+Version: 2.10.0
+Summary: Fast numerical expression evaluator for NumPy
+Home-page: https://github.com/pydata/numexpr
+Author: David M. Cooke, Francesc Alted, and others
+Maintainer: Francesc Alted
+Maintainer-email: faltet@gmail.com
+License: MIT
+Classifier: Development Status :: 6 - Mature
+Classifier: Intended Audience :: Financial and Insurance Industry
+Classifier: Intended Audience :: Science/Research
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Operating System :: Microsoft :: Windows
+Classifier: Operating System :: POSIX
+Classifier: Operating System :: MacOS
+Requires-Python: >=3.9
+Description-Content-Type: text/x-rst
+License-File: LICENSE.txt
+License-File: AUTHORS.txt
+Requires-Dist: numpy >=1.19.3
+
+======================================================
+NumExpr: Fast numerical expression evaluator for NumPy
+======================================================
+
+:Author: David M. Cooke, Francesc Alted, and others.
+:Maintainer: Francesc Alted
+:Contact: faltet@gmail.com
+:URL: https://github.com/pydata/numexpr
+:Documentation: http://numexpr.readthedocs.io/en/latest/
+:GitHub Actions: |actions|
+:PyPi: |version|
+:DOI: |doi|
+:readthedocs: |docs|
+
+.. |actions| image:: https://github.com/pydata/numexpr/workflows/Build/badge.svg
+ :target: https://github.com/pydata/numexpr/actions
+.. |travis| image:: https://travis-ci.org/pydata/numexpr.png?branch=master
+ :target: https://travis-ci.org/pydata/numexpr
+.. |docs| image:: https://readthedocs.org/projects/numexpr/badge/?version=latest
+ :target: http://numexpr.readthedocs.io/en/latest
+.. |doi| image:: https://zenodo.org/badge/doi/10.5281/zenodo.2483274.svg
+ :target: https://doi.org/10.5281/zenodo.2483274
+.. |version| image:: https://img.shields.io/pypi/v/numexpr
+ :target: https://pypi.python.org/pypi/numexpr
+
+
+What is NumExpr?
+----------------
+
+NumExpr is a fast numerical expression evaluator for NumPy. With it,
+expressions that operate on arrays (like :code:`'3*a+4*b'`) are accelerated
+and use less memory than doing the same calculation in Python.
+
+In addition, its multi-threaded capabilities can make use of all your
+cores -- which generally results in substantial performance scaling compared
+to NumPy.
+
+Last but not least, numexpr can make use of Intel's VML (Vector Math
+Library, normally integrated in its Math Kernel Library, or MKL).
+This allows further acceleration of transcendent expressions.
+
+
+How NumExpr achieves high performance
+-------------------------------------
+
+The main reason why NumExpr achieves better performance than NumPy is
+that it avoids allocating memory for intermediate results. This
+results in better cache utilization and reduces memory access in
+general. Due to this, NumExpr works best with large arrays.
+
+NumExpr parses expressions into its own op-codes that are then used by
+an integrated computing virtual machine. The array operands are split
+into small chunks that easily fit in the cache of the CPU and passed
+to the virtual machine. The virtual machine then applies the
+operations on each chunk. It's worth noting that all temporaries and
+constants in the expression are also chunked. Chunks are distributed among
+the available cores of the CPU, resulting in highly parallelized code
+execution.
+
+The result is that NumExpr can get the most of your machine computing
+capabilities for array-wise computations. Common speed-ups with regard
+to NumPy are usually between 0.95x (for very simple expressions like
+:code:`'a + 1'`) and 4x (for relatively complex ones like :code:`'a*b-4.1*a > 2.5*b'`),
+although much higher speed-ups can be achieved for some functions and complex
+math operations (up to 15x in some cases).
+
+NumExpr performs best on matrices that are too large to fit in L1 CPU cache.
+In order to get a better idea on the different speed-ups that can be achieved
+on your platform, run the provided benchmarks.
+
+Installation
+------------
+
+From wheels
+^^^^^^^^^^^
+
+NumExpr is available for install via `pip` for a wide range of platforms and
+Python versions (which may be browsed at: https://pypi.org/project/numexpr/#files).
+Installation can be performed as::
+
+ pip install numexpr
+
+If you are using the Anaconda or Miniconda distribution of Python you may prefer
+to use the `conda` package manager in this case::
+
+ conda install numexpr
+
+From Source
+^^^^^^^^^^^
+
+On most \*nix systems your compilers will already be present. However if you
+are using a virtual environment with a substantially newer version of Python than
+your system Python you may be prompted to install a new version of `gcc` or `clang`.
+
+For Windows, you will need to install the Microsoft Visual C++ Build Tools
+(which are free) first. The version depends on which version of Python you have
+installed:
+
+https://wiki.python.org/moin/WindowsCompilers
+
+For Python 3.6+ simply installing the latest version of MSVC build tools should
+be sufficient. Note that wheels found via pip do not include MKL support. Wheels
+available via `conda` will have MKL, if the MKL backend is used for NumPy.
+
+See `requirements.txt` for the required version of NumPy.
+
+NumExpr is built in the standard Python way::
+
+ python setup.py build install
+
+You can test `numexpr` with::
+
+ python -c "import numexpr; numexpr.test()"
+
+Do not test NumExpr in the source directory or you will generate import errors.
+
+Enable Intel® MKL support
+^^^^^^^^^^^^^^^^^^^^^^^^^
+
+NumExpr includes support for Intel's MKL library. This may provide better
+performance on Intel architectures, mainly when evaluating transcendental
+functions (trigonometrical, exponential, ...).
+
+If you have Intel's MKL, copy the `site.cfg.example` that comes with the
+distribution to `site.cfg` and edit the latter file to provide correct paths to
+the MKL libraries in your system. After doing this, you can proceed with the
+usual building instructions listed above.
+
+Pay attention to the messages during the building process in order to know
+whether MKL has been detected or not. Finally, you can check the speed-ups on
+your machine by running the `bench/vml_timing.py` script (you can play with
+different parameters to the `set_vml_accuracy_mode()` and `set_vml_num_threads()`
+functions in the script so as to see how it would affect performance).
+
+Usage
+-----
+
+::
+
+ >>> import numpy as np
+ >>> import numexpr as ne
+
+ >>> a = np.arange(1e6) # Choose large arrays for better speedups
+ >>> b = np.arange(1e6)
+
+ >>> ne.evaluate("a + 1") # a simple expression
+ array([ 1.00000000e+00, 2.00000000e+00, 3.00000000e+00, ...,
+ 9.99998000e+05, 9.99999000e+05, 1.00000000e+06])
+
+ >>> ne.evaluate("a * b - 4.1 * a > 2.5 * b") # a more complex one
+ array([False, False, False, ..., True, True, True], dtype=bool)
+
+ >>> ne.evaluate("sin(a) + arcsinh(a/b)") # you can also use functions
+ array([ NaN, 1.72284457, 1.79067101, ..., 1.09567006,
+ 0.17523598, -0.09597844])
+
+ >>> s = np.array([b'abba', b'abbb', b'abbcdef'])
+ >>> ne.evaluate("b'abba' == s") # string arrays are supported too
+ array([ True, False, False], dtype=bool)
+
+
+Documentation
+-------------
+
+Please see the official documentation at `numexpr.readthedocs.io `_.
+Included is a user guide, benchmark results, and the reference API.
+
+
+Authors
+-------
+
+Please see `AUTHORS.txt `_.
+
+
+License
+-------
+
+NumExpr is distributed under the `MIT `_ license.
+
+
+.. Local Variables:
+.. mode: text
+.. coding: utf-8
+.. fill-column: 70
+.. End:
diff --git a/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/RECORD b/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/RECORD
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diff --git a/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/WHEEL b/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/WHEEL
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+Tag: cp310-cp310-manylinux_2_17_x86_64
+Tag: cp310-cp310-manylinux2014_x86_64
+
diff --git a/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/top_level.txt b/env-llmeval/lib/python3.10/site-packages/numexpr-2.10.0.dist-info/top_level.txt
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diff --git a/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/__init__.py b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..a7655a013c6cf3fca754086fdeb29b806220d5e4
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/__init__.py
@@ -0,0 +1,9 @@
+"""
+core.array_algos is for algorithms that operate on ndarray and ExtensionArray.
+These should:
+
+- Assume that any Index, Series, or DataFrame objects have already been unwrapped.
+- Assume that any list arguments have already been cast to ndarray/EA.
+- Not depend on Index, Series, or DataFrame, nor import any of these.
+- May dispatch to ExtensionArray methods, but should not import from core.arrays.
+"""
diff --git a/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/__pycache__/datetimelike_accumulations.cpython-310.pyc b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/__pycache__/datetimelike_accumulations.cpython-310.pyc
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diff --git a/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/datetimelike_accumulations.py b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/datetimelike_accumulations.py
new file mode 100644
index 0000000000000000000000000000000000000000..825fe60ee6cf88a2186a5f501c8696cecaf2657d
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/datetimelike_accumulations.py
@@ -0,0 +1,67 @@
+"""
+datetimelke_accumulations.py is for accumulations of datetimelike extension arrays
+"""
+
+from __future__ import annotations
+
+from typing import Callable
+
+import numpy as np
+
+from pandas._libs import iNaT
+
+from pandas.core.dtypes.missing import isna
+
+
+def _cum_func(
+ func: Callable,
+ values: np.ndarray,
+ *,
+ skipna: bool = True,
+):
+ """
+ Accumulations for 1D datetimelike arrays.
+
+ Parameters
+ ----------
+ func : np.cumsum, np.maximum.accumulate, np.minimum.accumulate
+ values : np.ndarray
+ Numpy array with the values (can be of any dtype that support the
+ operation). Values is changed is modified inplace.
+ skipna : bool, default True
+ Whether to skip NA.
+ """
+ try:
+ fill_value = {
+ np.maximum.accumulate: np.iinfo(np.int64).min,
+ np.cumsum: 0,
+ np.minimum.accumulate: np.iinfo(np.int64).max,
+ }[func]
+ except KeyError:
+ raise ValueError(f"No accumulation for {func} implemented on BaseMaskedArray")
+
+ mask = isna(values)
+ y = values.view("i8")
+ y[mask] = fill_value
+
+ if not skipna:
+ mask = np.maximum.accumulate(mask)
+
+ result = func(y)
+ result[mask] = iNaT
+
+ if values.dtype.kind in "mM":
+ return result.view(values.dtype.base)
+ return result
+
+
+def cumsum(values: np.ndarray, *, skipna: bool = True) -> np.ndarray:
+ return _cum_func(np.cumsum, values, skipna=skipna)
+
+
+def cummin(values: np.ndarray, *, skipna: bool = True):
+ return _cum_func(np.minimum.accumulate, values, skipna=skipna)
+
+
+def cummax(values: np.ndarray, *, skipna: bool = True):
+ return _cum_func(np.maximum.accumulate, values, skipna=skipna)
diff --git a/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/masked_accumulations.py b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/masked_accumulations.py
new file mode 100644
index 0000000000000000000000000000000000000000..ad9e96d398a242dc64de2018b749fd2dbca7ed78
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/masked_accumulations.py
@@ -0,0 +1,90 @@
+"""
+masked_accumulations.py is for accumulation algorithms using a mask-based approach
+for missing values.
+"""
+
+from __future__ import annotations
+
+from typing import (
+ TYPE_CHECKING,
+ Callable,
+)
+
+import numpy as np
+
+if TYPE_CHECKING:
+ from pandas._typing import npt
+
+
+def _cum_func(
+ func: Callable,
+ values: np.ndarray,
+ mask: npt.NDArray[np.bool_],
+ *,
+ skipna: bool = True,
+):
+ """
+ Accumulations for 1D masked array.
+
+ We will modify values in place to replace NAs with the appropriate fill value.
+
+ Parameters
+ ----------
+ func : np.cumsum, np.cumprod, np.maximum.accumulate, np.minimum.accumulate
+ values : np.ndarray
+ Numpy array with the values (can be of any dtype that support the
+ operation).
+ mask : np.ndarray
+ Boolean numpy array (True values indicate missing values).
+ skipna : bool, default True
+ Whether to skip NA.
+ """
+ dtype_info: np.iinfo | np.finfo
+ if values.dtype.kind == "f":
+ dtype_info = np.finfo(values.dtype.type)
+ elif values.dtype.kind in "iu":
+ dtype_info = np.iinfo(values.dtype.type)
+ elif values.dtype.kind == "b":
+ # Max value of bool is 1, but since we are setting into a boolean
+ # array, 255 is fine as well. Min value has to be 0 when setting
+ # into the boolean array.
+ dtype_info = np.iinfo(np.uint8)
+ else:
+ raise NotImplementedError(
+ f"No masked accumulation defined for dtype {values.dtype.type}"
+ )
+ try:
+ fill_value = {
+ np.cumprod: 1,
+ np.maximum.accumulate: dtype_info.min,
+ np.cumsum: 0,
+ np.minimum.accumulate: dtype_info.max,
+ }[func]
+ except KeyError:
+ raise NotImplementedError(
+ f"No accumulation for {func} implemented on BaseMaskedArray"
+ )
+
+ values[mask] = fill_value
+
+ if not skipna:
+ mask = np.maximum.accumulate(mask)
+
+ values = func(values)
+ return values, mask
+
+
+def cumsum(values: np.ndarray, mask: npt.NDArray[np.bool_], *, skipna: bool = True):
+ return _cum_func(np.cumsum, values, mask, skipna=skipna)
+
+
+def cumprod(values: np.ndarray, mask: npt.NDArray[np.bool_], *, skipna: bool = True):
+ return _cum_func(np.cumprod, values, mask, skipna=skipna)
+
+
+def cummin(values: np.ndarray, mask: npt.NDArray[np.bool_], *, skipna: bool = True):
+ return _cum_func(np.minimum.accumulate, values, mask, skipna=skipna)
+
+
+def cummax(values: np.ndarray, mask: npt.NDArray[np.bool_], *, skipna: bool = True):
+ return _cum_func(np.maximum.accumulate, values, mask, skipna=skipna)
diff --git a/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/masked_reductions.py b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/masked_reductions.py
new file mode 100644
index 0000000000000000000000000000000000000000..335fa1afc0f4e39956a05b567dcc98f0b98c66e3
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/masked_reductions.py
@@ -0,0 +1,197 @@
+"""
+masked_reductions.py is for reduction algorithms using a mask-based approach
+for missing values.
+"""
+from __future__ import annotations
+
+from typing import (
+ TYPE_CHECKING,
+ Callable,
+)
+import warnings
+
+import numpy as np
+
+from pandas._libs import missing as libmissing
+
+from pandas.core.nanops import check_below_min_count
+
+if TYPE_CHECKING:
+ from pandas._typing import (
+ AxisInt,
+ npt,
+ )
+
+
+def _reductions(
+ func: Callable,
+ values: np.ndarray,
+ mask: npt.NDArray[np.bool_],
+ *,
+ skipna: bool = True,
+ min_count: int = 0,
+ axis: AxisInt | None = None,
+ **kwargs,
+):
+ """
+ Sum, mean or product for 1D masked array.
+
+ Parameters
+ ----------
+ func : np.sum or np.prod
+ values : np.ndarray
+ Numpy array with the values (can be of any dtype that support the
+ operation).
+ mask : np.ndarray[bool]
+ Boolean numpy array (True values indicate missing values).
+ skipna : bool, default True
+ Whether to skip NA.
+ min_count : int, default 0
+ The required number of valid values to perform the operation. If fewer than
+ ``min_count`` non-NA values are present the result will be NA.
+ axis : int, optional, default None
+ """
+ if not skipna:
+ if mask.any() or check_below_min_count(values.shape, None, min_count):
+ return libmissing.NA
+ else:
+ return func(values, axis=axis, **kwargs)
+ else:
+ if check_below_min_count(values.shape, mask, min_count) and (
+ axis is None or values.ndim == 1
+ ):
+ return libmissing.NA
+
+ return func(values, where=~mask, axis=axis, **kwargs)
+
+
+def sum(
+ values: np.ndarray,
+ mask: npt.NDArray[np.bool_],
+ *,
+ skipna: bool = True,
+ min_count: int = 0,
+ axis: AxisInt | None = None,
+):
+ return _reductions(
+ np.sum, values=values, mask=mask, skipna=skipna, min_count=min_count, axis=axis
+ )
+
+
+def prod(
+ values: np.ndarray,
+ mask: npt.NDArray[np.bool_],
+ *,
+ skipna: bool = True,
+ min_count: int = 0,
+ axis: AxisInt | None = None,
+):
+ return _reductions(
+ np.prod, values=values, mask=mask, skipna=skipna, min_count=min_count, axis=axis
+ )
+
+
+def _minmax(
+ func: Callable,
+ values: np.ndarray,
+ mask: npt.NDArray[np.bool_],
+ *,
+ skipna: bool = True,
+ axis: AxisInt | None = None,
+):
+ """
+ Reduction for 1D masked array.
+
+ Parameters
+ ----------
+ func : np.min or np.max
+ values : np.ndarray
+ Numpy array with the values (can be of any dtype that support the
+ operation).
+ mask : np.ndarray[bool]
+ Boolean numpy array (True values indicate missing values).
+ skipna : bool, default True
+ Whether to skip NA.
+ axis : int, optional, default None
+ """
+ if not skipna:
+ if mask.any() or not values.size:
+ # min/max with empty array raise in numpy, pandas returns NA
+ return libmissing.NA
+ else:
+ return func(values, axis=axis)
+ else:
+ subset = values[~mask]
+ if subset.size:
+ return func(subset, axis=axis)
+ else:
+ # min/max with empty array raise in numpy, pandas returns NA
+ return libmissing.NA
+
+
+def min(
+ values: np.ndarray,
+ mask: npt.NDArray[np.bool_],
+ *,
+ skipna: bool = True,
+ axis: AxisInt | None = None,
+):
+ return _minmax(np.min, values=values, mask=mask, skipna=skipna, axis=axis)
+
+
+def max(
+ values: np.ndarray,
+ mask: npt.NDArray[np.bool_],
+ *,
+ skipna: bool = True,
+ axis: AxisInt | None = None,
+):
+ return _minmax(np.max, values=values, mask=mask, skipna=skipna, axis=axis)
+
+
+def mean(
+ values: np.ndarray,
+ mask: npt.NDArray[np.bool_],
+ *,
+ skipna: bool = True,
+ axis: AxisInt | None = None,
+):
+ if not values.size or mask.all():
+ return libmissing.NA
+ return _reductions(np.mean, values=values, mask=mask, skipna=skipna, axis=axis)
+
+
+def var(
+ values: np.ndarray,
+ mask: npt.NDArray[np.bool_],
+ *,
+ skipna: bool = True,
+ axis: AxisInt | None = None,
+ ddof: int = 1,
+):
+ if not values.size or mask.all():
+ return libmissing.NA
+
+ with warnings.catch_warnings():
+ warnings.simplefilter("ignore", RuntimeWarning)
+ return _reductions(
+ np.var, values=values, mask=mask, skipna=skipna, axis=axis, ddof=ddof
+ )
+
+
+def std(
+ values: np.ndarray,
+ mask: npt.NDArray[np.bool_],
+ *,
+ skipna: bool = True,
+ axis: AxisInt | None = None,
+ ddof: int = 1,
+):
+ if not values.size or mask.all():
+ return libmissing.NA
+
+ with warnings.catch_warnings():
+ warnings.simplefilter("ignore", RuntimeWarning)
+ return _reductions(
+ np.std, values=values, mask=mask, skipna=skipna, axis=axis, ddof=ddof
+ )
diff --git a/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/putmask.py b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/putmask.py
new file mode 100644
index 0000000000000000000000000000000000000000..f65d2d20e028e36b35a397d8ac973f184ce1412c
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/putmask.py
@@ -0,0 +1,149 @@
+"""
+EA-compatible analogue to np.putmask
+"""
+from __future__ import annotations
+
+from typing import (
+ TYPE_CHECKING,
+ Any,
+)
+
+import numpy as np
+
+from pandas._libs import lib
+
+from pandas.core.dtypes.cast import infer_dtype_from
+from pandas.core.dtypes.common import is_list_like
+
+from pandas.core.arrays import ExtensionArray
+
+if TYPE_CHECKING:
+ from pandas._typing import (
+ ArrayLike,
+ npt,
+ )
+
+ from pandas import MultiIndex
+
+
+def putmask_inplace(values: ArrayLike, mask: npt.NDArray[np.bool_], value: Any) -> None:
+ """
+ ExtensionArray-compatible implementation of np.putmask. The main
+ difference is we do not handle repeating or truncating like numpy.
+
+ Parameters
+ ----------
+ values: np.ndarray or ExtensionArray
+ mask : np.ndarray[bool]
+ We assume extract_bool_array has already been called.
+ value : Any
+ """
+
+ if (
+ not isinstance(values, np.ndarray)
+ or (values.dtype == object and not lib.is_scalar(value))
+ # GH#43424: np.putmask raises TypeError if we cannot cast between types with
+ # rule = "safe", a stricter guarantee we may not have here
+ or (
+ isinstance(value, np.ndarray) and not np.can_cast(value.dtype, values.dtype)
+ )
+ ):
+ # GH#19266 using np.putmask gives unexpected results with listlike value
+ # along with object dtype
+ if is_list_like(value) and len(value) == len(values):
+ values[mask] = value[mask]
+ else:
+ values[mask] = value
+ else:
+ # GH#37833 np.putmask is more performant than __setitem__
+ np.putmask(values, mask, value)
+
+
+def putmask_without_repeat(
+ values: np.ndarray, mask: npt.NDArray[np.bool_], new: Any
+) -> None:
+ """
+ np.putmask will truncate or repeat if `new` is a listlike with
+ len(new) != len(values). We require an exact match.
+
+ Parameters
+ ----------
+ values : np.ndarray
+ mask : np.ndarray[bool]
+ new : Any
+ """
+ if getattr(new, "ndim", 0) >= 1:
+ new = new.astype(values.dtype, copy=False)
+
+ # TODO: this prob needs some better checking for 2D cases
+ nlocs = mask.sum()
+ if nlocs > 0 and is_list_like(new) and getattr(new, "ndim", 1) == 1:
+ shape = np.shape(new)
+ # np.shape compat for if setitem_datetimelike_compat
+ # changed arraylike to list e.g. test_where_dt64_2d
+ if nlocs == shape[-1]:
+ # GH#30567
+ # If length of ``new`` is less than the length of ``values``,
+ # `np.putmask` would first repeat the ``new`` array and then
+ # assign the masked values hence produces incorrect result.
+ # `np.place` on the other hand uses the ``new`` values at it is
+ # to place in the masked locations of ``values``
+ np.place(values, mask, new)
+ # i.e. values[mask] = new
+ elif mask.shape[-1] == shape[-1] or shape[-1] == 1:
+ np.putmask(values, mask, new)
+ else:
+ raise ValueError("cannot assign mismatch length to masked array")
+ else:
+ np.putmask(values, mask, new)
+
+
+def validate_putmask(
+ values: ArrayLike | MultiIndex, mask: np.ndarray
+) -> tuple[npt.NDArray[np.bool_], bool]:
+ """
+ Validate mask and check if this putmask operation is a no-op.
+ """
+ mask = extract_bool_array(mask)
+ if mask.shape != values.shape:
+ raise ValueError("putmask: mask and data must be the same size")
+
+ noop = not mask.any()
+ return mask, noop
+
+
+def extract_bool_array(mask: ArrayLike) -> npt.NDArray[np.bool_]:
+ """
+ If we have a SparseArray or BooleanArray, convert it to ndarray[bool].
+ """
+ if isinstance(mask, ExtensionArray):
+ # We could have BooleanArray, Sparse[bool], ...
+ # Except for BooleanArray, this is equivalent to just
+ # np.asarray(mask, dtype=bool)
+ mask = mask.to_numpy(dtype=bool, na_value=False)
+
+ mask = np.asarray(mask, dtype=bool)
+ return mask
+
+
+def setitem_datetimelike_compat(values: np.ndarray, num_set: int, other):
+ """
+ Parameters
+ ----------
+ values : np.ndarray
+ num_set : int
+ For putmask, this is mask.sum()
+ other : Any
+ """
+ if values.dtype == object:
+ dtype, _ = infer_dtype_from(other)
+
+ if lib.is_np_dtype(dtype, "mM"):
+ # https://github.com/numpy/numpy/issues/12550
+ # timedelta64 will incorrectly cast to int
+ if not is_list_like(other):
+ other = [other] * num_set
+ else:
+ other = list(other)
+
+ return other
diff --git a/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/quantile.py b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/quantile.py
new file mode 100644
index 0000000000000000000000000000000000000000..5c933294fb944f04dd3e9a64e4731ea4349254f9
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/quantile.py
@@ -0,0 +1,226 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import numpy as np
+
+from pandas.core.dtypes.missing import (
+ isna,
+ na_value_for_dtype,
+)
+
+if TYPE_CHECKING:
+ from pandas._typing import (
+ ArrayLike,
+ Scalar,
+ npt,
+ )
+
+
+def quantile_compat(
+ values: ArrayLike, qs: npt.NDArray[np.float64], interpolation: str
+) -> ArrayLike:
+ """
+ Compute the quantiles of the given values for each quantile in `qs`.
+
+ Parameters
+ ----------
+ values : np.ndarray or ExtensionArray
+ qs : np.ndarray[float64]
+ interpolation : str
+
+ Returns
+ -------
+ np.ndarray or ExtensionArray
+ """
+ if isinstance(values, np.ndarray):
+ fill_value = na_value_for_dtype(values.dtype, compat=False)
+ mask = isna(values)
+ return quantile_with_mask(values, mask, fill_value, qs, interpolation)
+ else:
+ return values._quantile(qs, interpolation)
+
+
+def quantile_with_mask(
+ values: np.ndarray,
+ mask: npt.NDArray[np.bool_],
+ fill_value,
+ qs: npt.NDArray[np.float64],
+ interpolation: str,
+) -> np.ndarray:
+ """
+ Compute the quantiles of the given values for each quantile in `qs`.
+
+ Parameters
+ ----------
+ values : np.ndarray
+ For ExtensionArray, this is _values_for_factorize()[0]
+ mask : np.ndarray[bool]
+ mask = isna(values)
+ For ExtensionArray, this is computed before calling _value_for_factorize
+ fill_value : Scalar
+ The value to interpret fill NA entries with
+ For ExtensionArray, this is _values_for_factorize()[1]
+ qs : np.ndarray[float64]
+ interpolation : str
+ Type of interpolation
+
+ Returns
+ -------
+ np.ndarray
+
+ Notes
+ -----
+ Assumes values is already 2D. For ExtensionArray this means np.atleast_2d
+ has been called on _values_for_factorize()[0]
+
+ Quantile is computed along axis=1.
+ """
+ assert values.shape == mask.shape
+ if values.ndim == 1:
+ # unsqueeze, operate, re-squeeze
+ values = np.atleast_2d(values)
+ mask = np.atleast_2d(mask)
+ res_values = quantile_with_mask(values, mask, fill_value, qs, interpolation)
+ return res_values[0]
+
+ assert values.ndim == 2
+
+ is_empty = values.shape[1] == 0
+
+ if is_empty:
+ # create the array of na_values
+ # 2d len(values) * len(qs)
+ flat = np.array([fill_value] * len(qs))
+ result = np.repeat(flat, len(values)).reshape(len(values), len(qs))
+ else:
+ result = _nanpercentile(
+ values,
+ qs * 100.0,
+ na_value=fill_value,
+ mask=mask,
+ interpolation=interpolation,
+ )
+
+ result = np.asarray(result)
+ result = result.T
+
+ return result
+
+
+def _nanpercentile_1d(
+ values: np.ndarray,
+ mask: npt.NDArray[np.bool_],
+ qs: npt.NDArray[np.float64],
+ na_value: Scalar,
+ interpolation: str,
+) -> Scalar | np.ndarray:
+ """
+ Wrapper for np.percentile that skips missing values, specialized to
+ 1-dimensional case.
+
+ Parameters
+ ----------
+ values : array over which to find quantiles
+ mask : ndarray[bool]
+ locations in values that should be considered missing
+ qs : np.ndarray[float64] of quantile indices to find
+ na_value : scalar
+ value to return for empty or all-null values
+ interpolation : str
+
+ Returns
+ -------
+ quantiles : scalar or array
+ """
+ # mask is Union[ExtensionArray, ndarray]
+ values = values[~mask]
+
+ if len(values) == 0:
+ # Can't pass dtype=values.dtype here bc we might have na_value=np.nan
+ # with values.dtype=int64 see test_quantile_empty
+ # equiv: 'np.array([na_value] * len(qs))' but much faster
+ return np.full(len(qs), na_value)
+
+ return np.percentile(
+ values,
+ qs,
+ # error: No overload variant of "percentile" matches argument
+ # types "ndarray[Any, Any]", "ndarray[Any, dtype[floating[_64Bit]]]"
+ # , "Dict[str, str]" [call-overload]
+ method=interpolation, # type: ignore[call-overload]
+ )
+
+
+def _nanpercentile(
+ values: np.ndarray,
+ qs: npt.NDArray[np.float64],
+ *,
+ na_value,
+ mask: npt.NDArray[np.bool_],
+ interpolation: str,
+):
+ """
+ Wrapper for np.percentile that skips missing values.
+
+ Parameters
+ ----------
+ values : np.ndarray[ndim=2] over which to find quantiles
+ qs : np.ndarray[float64] of quantile indices to find
+ na_value : scalar
+ value to return for empty or all-null values
+ mask : np.ndarray[bool]
+ locations in values that should be considered missing
+ interpolation : str
+
+ Returns
+ -------
+ quantiles : scalar or array
+ """
+
+ if values.dtype.kind in "mM":
+ # need to cast to integer to avoid rounding errors in numpy
+ result = _nanpercentile(
+ values.view("i8"),
+ qs=qs,
+ na_value=na_value.view("i8"),
+ mask=mask,
+ interpolation=interpolation,
+ )
+
+ # Note: we have to do `astype` and not view because in general we
+ # have float result at this point, not i8
+ return result.astype(values.dtype)
+
+ if mask.any():
+ # Caller is responsible for ensuring mask shape match
+ assert mask.shape == values.shape
+ result = [
+ _nanpercentile_1d(val, m, qs, na_value, interpolation=interpolation)
+ for (val, m) in zip(list(values), list(mask))
+ ]
+ if values.dtype.kind == "f":
+ # preserve itemsize
+ result = np.asarray(result, dtype=values.dtype).T
+ else:
+ result = np.asarray(result).T
+ if (
+ result.dtype != values.dtype
+ and not mask.all()
+ and (result == result.astype(values.dtype, copy=False)).all()
+ ):
+ # mask.all() will never get cast back to int
+ # e.g. values id integer dtype and result is floating dtype,
+ # only cast back to integer dtype if result values are all-integer.
+ result = result.astype(values.dtype, copy=False)
+ return result
+ else:
+ return np.percentile(
+ values,
+ qs,
+ axis=1,
+ # error: No overload variant of "percentile" matches argument types
+ # "ndarray[Any, Any]", "ndarray[Any, dtype[floating[_64Bit]]]",
+ # "int", "Dict[str, str]" [call-overload]
+ method=interpolation, # type: ignore[call-overload]
+ )
diff --git a/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/replace.py b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/replace.py
new file mode 100644
index 0000000000000000000000000000000000000000..5f377276be480ec4d01c8cd1671fa95f9504c7c6
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/replace.py
@@ -0,0 +1,152 @@
+"""
+Methods used by Block.replace and related methods.
+"""
+from __future__ import annotations
+
+import operator
+import re
+from re import Pattern
+from typing import (
+ TYPE_CHECKING,
+ Any,
+)
+
+import numpy as np
+
+from pandas.core.dtypes.common import (
+ is_bool,
+ is_re,
+ is_re_compilable,
+)
+from pandas.core.dtypes.missing import isna
+
+if TYPE_CHECKING:
+ from pandas._typing import (
+ ArrayLike,
+ Scalar,
+ npt,
+ )
+
+
+def should_use_regex(regex: bool, to_replace: Any) -> bool:
+ """
+ Decide whether to treat `to_replace` as a regular expression.
+ """
+ if is_re(to_replace):
+ regex = True
+
+ regex = regex and is_re_compilable(to_replace)
+
+ # Don't use regex if the pattern is empty.
+ regex = regex and re.compile(to_replace).pattern != ""
+ return regex
+
+
+def compare_or_regex_search(
+ a: ArrayLike, b: Scalar | Pattern, regex: bool, mask: npt.NDArray[np.bool_]
+) -> ArrayLike:
+ """
+ Compare two array-like inputs of the same shape or two scalar values
+
+ Calls operator.eq or re.search, depending on regex argument. If regex is
+ True, perform an element-wise regex matching.
+
+ Parameters
+ ----------
+ a : array-like
+ b : scalar or regex pattern
+ regex : bool
+ mask : np.ndarray[bool]
+
+ Returns
+ -------
+ mask : array-like of bool
+ """
+ if isna(b):
+ return ~mask
+
+ def _check_comparison_types(
+ result: ArrayLike | bool, a: ArrayLike, b: Scalar | Pattern
+ ):
+ """
+ Raises an error if the two arrays (a,b) cannot be compared.
+ Otherwise, returns the comparison result as expected.
+ """
+ if is_bool(result) and isinstance(a, np.ndarray):
+ type_names = [type(a).__name__, type(b).__name__]
+
+ type_names[0] = f"ndarray(dtype={a.dtype})"
+
+ raise TypeError(
+ f"Cannot compare types {repr(type_names[0])} and {repr(type_names[1])}"
+ )
+
+ if not regex or not should_use_regex(regex, b):
+ # TODO: should use missing.mask_missing?
+ op = lambda x: operator.eq(x, b)
+ else:
+ op = np.vectorize(
+ lambda x: bool(re.search(b, x))
+ if isinstance(x, str) and isinstance(b, (str, Pattern))
+ else False
+ )
+
+ # GH#32621 use mask to avoid comparing to NAs
+ if isinstance(a, np.ndarray):
+ a = a[mask]
+
+ result = op(a)
+
+ if isinstance(result, np.ndarray) and mask is not None:
+ # The shape of the mask can differ to that of the result
+ # since we may compare only a subset of a's or b's elements
+ tmp = np.zeros(mask.shape, dtype=np.bool_)
+ np.place(tmp, mask, result)
+ result = tmp
+
+ _check_comparison_types(result, a, b)
+ return result
+
+
+def replace_regex(
+ values: ArrayLike, rx: re.Pattern, value, mask: npt.NDArray[np.bool_] | None
+) -> None:
+ """
+ Parameters
+ ----------
+ values : ArrayLike
+ Object dtype.
+ rx : re.Pattern
+ value : Any
+ mask : np.ndarray[bool], optional
+
+ Notes
+ -----
+ Alters values in-place.
+ """
+
+ # deal with replacing values with objects (strings) that match but
+ # whose replacement is not a string (numeric, nan, object)
+ if isna(value) or not isinstance(value, str):
+
+ def re_replacer(s):
+ if is_re(rx) and isinstance(s, str):
+ return value if rx.search(s) is not None else s
+ else:
+ return s
+
+ else:
+ # value is guaranteed to be a string here, s can be either a string
+ # or null if it's null it gets returned
+ def re_replacer(s):
+ if is_re(rx) and isinstance(s, str):
+ return rx.sub(value, s)
+ else:
+ return s
+
+ f = np.vectorize(re_replacer, otypes=[np.object_])
+
+ if mask is None:
+ values[:] = f(values)
+ else:
+ values[mask] = f(values[mask])
diff --git a/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/transforms.py b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/transforms.py
new file mode 100644
index 0000000000000000000000000000000000000000..ec67244949e3db92cc811b19cdfcd5d1dd2b4de8
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/pandas/core/array_algos/transforms.py
@@ -0,0 +1,50 @@
+"""
+transforms.py is for shape-preserving functions.
+"""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import numpy as np
+
+if TYPE_CHECKING:
+ from pandas._typing import (
+ AxisInt,
+ Scalar,
+ )
+
+
+def shift(
+ values: np.ndarray, periods: int, axis: AxisInt, fill_value: Scalar
+) -> np.ndarray:
+ new_values = values
+
+ if periods == 0 or values.size == 0:
+ return new_values.copy()
+
+ # make sure array sent to np.roll is c_contiguous
+ f_ordered = values.flags.f_contiguous
+ if f_ordered:
+ new_values = new_values.T
+ axis = new_values.ndim - axis - 1
+
+ if new_values.size:
+ new_values = np.roll(
+ new_values,
+ np.intp(periods),
+ axis=axis,
+ )
+
+ axis_indexer = [slice(None)] * values.ndim
+ if periods > 0:
+ axis_indexer[axis] = slice(None, periods)
+ else:
+ axis_indexer[axis] = slice(periods, None)
+ new_values[tuple(axis_indexer)] = fill_value
+
+ # restore original order
+ if f_ordered:
+ new_values = new_values.T
+
+ return new_values
diff --git a/env-llmeval/lib/python3.10/site-packages/pandas/core/strings/__init__.py b/env-llmeval/lib/python3.10/site-packages/pandas/core/strings/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ce75f768c5d1dcd8586264fe1faf756d5d5e94
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/pandas/core/strings/__init__.py
@@ -0,0 +1,28 @@
+"""
+Implementation of pandas.Series.str and its interface.
+
+* strings.accessor.StringMethods : Accessor for Series.str
+* strings.base.BaseStringArrayMethods: Mixin ABC for EAs to implement str methods
+
+Most methods on the StringMethods accessor follow the pattern:
+
+ 1. extract the array from the series (or index)
+ 2. Call that array's implementation of the string method
+ 3. Wrap the result (in a Series, index, or DataFrame)
+
+Pandas extension arrays implementing string methods should inherit from
+pandas.core.strings.base.BaseStringArrayMethods. This is an ABC defining
+the various string methods. To avoid namespace clashes and pollution,
+these are prefixed with `_str_`. So ``Series.str.upper()`` calls
+``Series.array._str_upper()``. The interface isn't currently public
+to other string extension arrays.
+"""
+# Pandas current implementation is in ObjectStringArrayMixin. This is designed
+# to work on object-dtype ndarrays.
+#
+# BaseStringArrayMethods
+# - ObjectStringArrayMixin
+# - StringArray
+# - NumpyExtensionArray
+# - Categorical
+# - ArrowStringArray
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diff --git a/env-llmeval/lib/python3.10/site-packages/pandas/core/strings/accessor.py b/env-llmeval/lib/python3.10/site-packages/pandas/core/strings/accessor.py
new file mode 100644
index 0000000000000000000000000000000000000000..da10a12d02ae40a147812d1158d256543cc2492e
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/pandas/core/strings/accessor.py
@@ -0,0 +1,3543 @@
+from __future__ import annotations
+
+import codecs
+from functools import wraps
+import re
+from typing import (
+ TYPE_CHECKING,
+ Callable,
+ Literal,
+ cast,
+)
+import warnings
+
+import numpy as np
+
+from pandas._libs import lib
+from pandas._typing import (
+ AlignJoin,
+ DtypeObj,
+ F,
+ Scalar,
+ npt,
+)
+from pandas.util._decorators import Appender
+from pandas.util._exceptions import find_stack_level
+
+from pandas.core.dtypes.common import (
+ ensure_object,
+ is_bool_dtype,
+ is_integer,
+ is_list_like,
+ is_object_dtype,
+ is_re,
+)
+from pandas.core.dtypes.dtypes import (
+ ArrowDtype,
+ CategoricalDtype,
+)
+from pandas.core.dtypes.generic import (
+ ABCDataFrame,
+ ABCIndex,
+ ABCMultiIndex,
+ ABCSeries,
+)
+from pandas.core.dtypes.missing import isna
+
+from pandas.core.arrays import ExtensionArray
+from pandas.core.base import NoNewAttributesMixin
+from pandas.core.construction import extract_array
+
+if TYPE_CHECKING:
+ from collections.abc import (
+ Hashable,
+ Iterator,
+ )
+
+ from pandas import (
+ DataFrame,
+ Index,
+ Series,
+ )
+
+_shared_docs: dict[str, str] = {}
+_cpython_optimized_encoders = (
+ "utf-8",
+ "utf8",
+ "latin-1",
+ "latin1",
+ "iso-8859-1",
+ "mbcs",
+ "ascii",
+)
+_cpython_optimized_decoders = _cpython_optimized_encoders + ("utf-16", "utf-32")
+
+
+def forbid_nonstring_types(
+ forbidden: list[str] | None, name: str | None = None
+) -> Callable[[F], F]:
+ """
+ Decorator to forbid specific types for a method of StringMethods.
+
+ For calling `.str.{method}` on a Series or Index, it is necessary to first
+ initialize the :class:`StringMethods` object, and then call the method.
+ However, different methods allow different input types, and so this can not
+ be checked during :meth:`StringMethods.__init__`, but must be done on a
+ per-method basis. This decorator exists to facilitate this process, and
+ make it explicit which (inferred) types are disallowed by the method.
+
+ :meth:`StringMethods.__init__` allows the *union* of types its different
+ methods allow (after skipping NaNs; see :meth:`StringMethods._validate`),
+ namely: ['string', 'empty', 'bytes', 'mixed', 'mixed-integer'].
+
+ The default string types ['string', 'empty'] are allowed for all methods.
+ For the additional types ['bytes', 'mixed', 'mixed-integer'], each method
+ then needs to forbid the types it is not intended for.
+
+ Parameters
+ ----------
+ forbidden : list-of-str or None
+ List of forbidden non-string types, may be one or more of
+ `['bytes', 'mixed', 'mixed-integer']`.
+ name : str, default None
+ Name of the method to use in the error message. By default, this is
+ None, in which case the name from the method being wrapped will be
+ copied. However, for working with further wrappers (like _pat_wrapper
+ and _noarg_wrapper), it is necessary to specify the name.
+
+ Returns
+ -------
+ func : wrapper
+ The method to which the decorator is applied, with an added check that
+ enforces the inferred type to not be in the list of forbidden types.
+
+ Raises
+ ------
+ TypeError
+ If the inferred type of the underlying data is in `forbidden`.
+ """
+ # deal with None
+ forbidden = [] if forbidden is None else forbidden
+
+ allowed_types = {"string", "empty", "bytes", "mixed", "mixed-integer"} - set(
+ forbidden
+ )
+
+ def _forbid_nonstring_types(func: F) -> F:
+ func_name = func.__name__ if name is None else name
+
+ @wraps(func)
+ def wrapper(self, *args, **kwargs):
+ if self._inferred_dtype not in allowed_types:
+ msg = (
+ f"Cannot use .str.{func_name} with values of "
+ f"inferred dtype '{self._inferred_dtype}'."
+ )
+ raise TypeError(msg)
+ return func(self, *args, **kwargs)
+
+ wrapper.__name__ = func_name
+ return cast(F, wrapper)
+
+ return _forbid_nonstring_types
+
+
+def _map_and_wrap(name: str | None, docstring: str | None):
+ @forbid_nonstring_types(["bytes"], name=name)
+ def wrapper(self):
+ result = getattr(self._data.array, f"_str_{name}")()
+ return self._wrap_result(
+ result, returns_string=name not in ("isnumeric", "isdecimal")
+ )
+
+ wrapper.__doc__ = docstring
+ return wrapper
+
+
+class StringMethods(NoNewAttributesMixin):
+ """
+ Vectorized string functions for Series and Index.
+
+ NAs stay NA unless handled otherwise by a particular method.
+ Patterned after Python's string methods, with some inspiration from
+ R's stringr package.
+
+ Examples
+ --------
+ >>> s = pd.Series(["A_Str_Series"])
+ >>> s
+ 0 A_Str_Series
+ dtype: object
+
+ >>> s.str.split("_")
+ 0 [A, Str, Series]
+ dtype: object
+
+ >>> s.str.replace("_", "")
+ 0 AStrSeries
+ dtype: object
+ """
+
+ # Note: see the docstring in pandas.core.strings.__init__
+ # for an explanation of the implementation.
+ # TODO: Dispatch all the methods
+ # Currently the following are not dispatched to the array
+ # * cat
+ # * extractall
+
+ def __init__(self, data) -> None:
+ from pandas.core.arrays.string_ import StringDtype
+
+ self._inferred_dtype = self._validate(data)
+ self._is_categorical = isinstance(data.dtype, CategoricalDtype)
+ self._is_string = isinstance(data.dtype, StringDtype)
+ self._data = data
+
+ self._index = self._name = None
+ if isinstance(data, ABCSeries):
+ self._index = data.index
+ self._name = data.name
+
+ # ._values.categories works for both Series/Index
+ self._parent = data._values.categories if self._is_categorical else data
+ # save orig to blow up categoricals to the right type
+ self._orig = data
+ self._freeze()
+
+ @staticmethod
+ def _validate(data):
+ """
+ Auxiliary function for StringMethods, infers and checks dtype of data.
+
+ This is a "first line of defence" at the creation of the StringMethods-
+ object, and just checks that the dtype is in the
+ *union* of the allowed types over all string methods below; this
+ restriction is then refined on a per-method basis using the decorator
+ @forbid_nonstring_types (more info in the corresponding docstring).
+
+ This really should exclude all series/index with any non-string values,
+ but that isn't practical for performance reasons until we have a str
+ dtype (GH 9343 / 13877)
+
+ Parameters
+ ----------
+ data : The content of the Series
+
+ Returns
+ -------
+ dtype : inferred dtype of data
+ """
+ if isinstance(data, ABCMultiIndex):
+ raise AttributeError(
+ "Can only use .str accessor with Index, not MultiIndex"
+ )
+
+ # see _libs/lib.pyx for list of inferred types
+ allowed_types = ["string", "empty", "bytes", "mixed", "mixed-integer"]
+
+ data = extract_array(data)
+
+ values = getattr(data, "categories", data) # categorical / normal
+
+ inferred_dtype = lib.infer_dtype(values, skipna=True)
+
+ if inferred_dtype not in allowed_types:
+ raise AttributeError("Can only use .str accessor with string values!")
+ return inferred_dtype
+
+ def __getitem__(self, key):
+ result = self._data.array._str_getitem(key)
+ return self._wrap_result(result)
+
+ def __iter__(self) -> Iterator:
+ raise TypeError(f"'{type(self).__name__}' object is not iterable")
+
+ def _wrap_result(
+ self,
+ result,
+ name=None,
+ expand: bool | None = None,
+ fill_value=np.nan,
+ returns_string: bool = True,
+ returns_bool: bool = False,
+ dtype=None,
+ ):
+ from pandas import (
+ Index,
+ MultiIndex,
+ )
+
+ if not hasattr(result, "ndim") or not hasattr(result, "dtype"):
+ if isinstance(result, ABCDataFrame):
+ result = result.__finalize__(self._orig, name="str")
+ return result
+ assert result.ndim < 3
+
+ # We can be wrapping a string / object / categorical result, in which
+ # case we'll want to return the same dtype as the input.
+ # Or we can be wrapping a numeric output, in which case we don't want
+ # to return a StringArray.
+ # Ideally the array method returns the right array type.
+ if expand is None:
+ # infer from ndim if expand is not specified
+ expand = result.ndim != 1
+ elif expand is True and not isinstance(self._orig, ABCIndex):
+ # required when expand=True is explicitly specified
+ # not needed when inferred
+ if isinstance(result.dtype, ArrowDtype):
+ import pyarrow as pa
+
+ from pandas.compat import pa_version_under11p0
+
+ from pandas.core.arrays.arrow.array import ArrowExtensionArray
+
+ value_lengths = pa.compute.list_value_length(result._pa_array)
+ max_len = pa.compute.max(value_lengths).as_py()
+ min_len = pa.compute.min(value_lengths).as_py()
+ if result._hasna:
+ # ArrowExtensionArray.fillna doesn't work for list scalars
+ result = ArrowExtensionArray(
+ result._pa_array.fill_null([None] * max_len)
+ )
+ if min_len < max_len:
+ # append nulls to each scalar list element up to max_len
+ if not pa_version_under11p0:
+ result = ArrowExtensionArray(
+ pa.compute.list_slice(
+ result._pa_array,
+ start=0,
+ stop=max_len,
+ return_fixed_size_list=True,
+ )
+ )
+ else:
+ all_null = np.full(max_len, fill_value=None, dtype=object)
+ values = result.to_numpy()
+ new_values = []
+ for row in values:
+ if len(row) < max_len:
+ nulls = all_null[: max_len - len(row)]
+ row = np.append(row, nulls)
+ new_values.append(row)
+ pa_type = result._pa_array.type
+ result = ArrowExtensionArray(pa.array(new_values, type=pa_type))
+ if name is not None:
+ labels = name
+ else:
+ labels = range(max_len)
+ result = (
+ pa.compute.list_flatten(result._pa_array)
+ .to_numpy()
+ .reshape(len(result), max_len)
+ )
+ result = {
+ label: ArrowExtensionArray(pa.array(res))
+ for label, res in zip(labels, result.T)
+ }
+ elif is_object_dtype(result):
+
+ def cons_row(x):
+ if is_list_like(x):
+ return x
+ else:
+ return [x]
+
+ result = [cons_row(x) for x in result]
+ if result and not self._is_string:
+ # propagate nan values to match longest sequence (GH 18450)
+ max_len = max(len(x) for x in result)
+ result = [
+ x * max_len if len(x) == 0 or x[0] is np.nan else x
+ for x in result
+ ]
+
+ if not isinstance(expand, bool):
+ raise ValueError("expand must be True or False")
+
+ if expand is False:
+ # if expand is False, result should have the same name
+ # as the original otherwise specified
+ if name is None:
+ name = getattr(result, "name", None)
+ if name is None:
+ # do not use logical or, _orig may be a DataFrame
+ # which has "name" column
+ name = self._orig.name
+
+ # Wait until we are sure result is a Series or Index before
+ # checking attributes (GH 12180)
+ if isinstance(self._orig, ABCIndex):
+ # if result is a boolean np.array, return the np.array
+ # instead of wrapping it into a boolean Index (GH 8875)
+ if is_bool_dtype(result):
+ return result
+
+ if expand:
+ result = list(result)
+ out: Index = MultiIndex.from_tuples(result, names=name)
+ if out.nlevels == 1:
+ # We had all tuples of length-one, which are
+ # better represented as a regular Index.
+ out = out.get_level_values(0)
+ return out
+ else:
+ return Index(result, name=name, dtype=dtype)
+ else:
+ index = self._orig.index
+ # This is a mess.
+ _dtype: DtypeObj | str | None = dtype
+ vdtype = getattr(result, "dtype", None)
+ if self._is_string:
+ if is_bool_dtype(vdtype):
+ _dtype = result.dtype
+ elif returns_string:
+ _dtype = self._orig.dtype
+ else:
+ _dtype = vdtype
+ elif vdtype is not None:
+ _dtype = vdtype
+
+ if expand:
+ cons = self._orig._constructor_expanddim
+ result = cons(result, columns=name, index=index, dtype=_dtype)
+ else:
+ # Must be a Series
+ cons = self._orig._constructor
+ result = cons(result, name=name, index=index, dtype=_dtype)
+ result = result.__finalize__(self._orig, method="str")
+ if name is not None and result.ndim == 1:
+ # __finalize__ might copy over the original name, but we may
+ # want the new name (e.g. str.extract).
+ result.name = name
+ return result
+
+ def _get_series_list(self, others):
+ """
+ Auxiliary function for :meth:`str.cat`. Turn potentially mixed input
+ into a list of Series (elements without an index must match the length
+ of the calling Series/Index).
+
+ Parameters
+ ----------
+ others : Series, DataFrame, np.ndarray, list-like or list-like of
+ Objects that are either Series, Index or np.ndarray (1-dim).
+
+ Returns
+ -------
+ list of Series
+ Others transformed into list of Series.
+ """
+ from pandas import (
+ DataFrame,
+ Series,
+ )
+
+ # self._orig is either Series or Index
+ idx = self._orig if isinstance(self._orig, ABCIndex) else self._orig.index
+
+ # Generally speaking, all objects without an index inherit the index
+ # `idx` of the calling Series/Index - i.e. must have matching length.
+ # Objects with an index (i.e. Series/Index/DataFrame) keep their own.
+ if isinstance(others, ABCSeries):
+ return [others]
+ elif isinstance(others, ABCIndex):
+ return [Series(others, index=idx, dtype=others.dtype)]
+ elif isinstance(others, ABCDataFrame):
+ return [others[x] for x in others]
+ elif isinstance(others, np.ndarray) and others.ndim == 2:
+ others = DataFrame(others, index=idx)
+ return [others[x] for x in others]
+ elif is_list_like(others, allow_sets=False):
+ try:
+ others = list(others) # ensure iterators do not get read twice etc
+ except TypeError:
+ # e.g. ser.str, raise below
+ pass
+ else:
+ # in case of list-like `others`, all elements must be
+ # either Series/Index/np.ndarray (1-dim)...
+ if all(
+ isinstance(x, (ABCSeries, ABCIndex, ExtensionArray))
+ or (isinstance(x, np.ndarray) and x.ndim == 1)
+ for x in others
+ ):
+ los: list[Series] = []
+ while others: # iterate through list and append each element
+ los = los + self._get_series_list(others.pop(0))
+ return los
+ # ... or just strings
+ elif all(not is_list_like(x) for x in others):
+ return [Series(others, index=idx)]
+ raise TypeError(
+ "others must be Series, Index, DataFrame, np.ndarray "
+ "or list-like (either containing only strings or "
+ "containing only objects of type Series/Index/"
+ "np.ndarray[1-dim])"
+ )
+
+ @forbid_nonstring_types(["bytes", "mixed", "mixed-integer"])
+ def cat(
+ self,
+ others=None,
+ sep: str | None = None,
+ na_rep=None,
+ join: AlignJoin = "left",
+ ) -> str | Series | Index:
+ """
+ Concatenate strings in the Series/Index with given separator.
+
+ If `others` is specified, this function concatenates the Series/Index
+ and elements of `others` element-wise.
+ If `others` is not passed, then all values in the Series/Index are
+ concatenated into a single string with a given `sep`.
+
+ Parameters
+ ----------
+ others : Series, Index, DataFrame, np.ndarray or list-like
+ Series, Index, DataFrame, np.ndarray (one- or two-dimensional) and
+ other list-likes of strings must have the same length as the
+ calling Series/Index, with the exception of indexed objects (i.e.
+ Series/Index/DataFrame) if `join` is not None.
+
+ If others is a list-like that contains a combination of Series,
+ Index or np.ndarray (1-dim), then all elements will be unpacked and
+ must satisfy the above criteria individually.
+
+ If others is None, the method returns the concatenation of all
+ strings in the calling Series/Index.
+ sep : str, default ''
+ The separator between the different elements/columns. By default
+ the empty string `''` is used.
+ na_rep : str or None, default None
+ Representation that is inserted for all missing values:
+
+ - If `na_rep` is None, and `others` is None, missing values in the
+ Series/Index are omitted from the result.
+ - If `na_rep` is None, and `others` is not None, a row containing a
+ missing value in any of the columns (before concatenation) will
+ have a missing value in the result.
+ join : {'left', 'right', 'outer', 'inner'}, default 'left'
+ Determines the join-style between the calling Series/Index and any
+ Series/Index/DataFrame in `others` (objects without an index need
+ to match the length of the calling Series/Index). To disable
+ alignment, use `.values` on any Series/Index/DataFrame in `others`.
+
+ Returns
+ -------
+ str, Series or Index
+ If `others` is None, `str` is returned, otherwise a `Series/Index`
+ (same type as caller) of objects is returned.
+
+ See Also
+ --------
+ split : Split each string in the Series/Index.
+ join : Join lists contained as elements in the Series/Index.
+
+ Examples
+ --------
+ When not passing `others`, all values are concatenated into a single
+ string:
+
+ >>> s = pd.Series(['a', 'b', np.nan, 'd'])
+ >>> s.str.cat(sep=' ')
+ 'a b d'
+
+ By default, NA values in the Series are ignored. Using `na_rep`, they
+ can be given a representation:
+
+ >>> s.str.cat(sep=' ', na_rep='?')
+ 'a b ? d'
+
+ If `others` is specified, corresponding values are concatenated with
+ the separator. Result will be a Series of strings.
+
+ >>> s.str.cat(['A', 'B', 'C', 'D'], sep=',')
+ 0 a,A
+ 1 b,B
+ 2 NaN
+ 3 d,D
+ dtype: object
+
+ Missing values will remain missing in the result, but can again be
+ represented using `na_rep`
+
+ >>> s.str.cat(['A', 'B', 'C', 'D'], sep=',', na_rep='-')
+ 0 a,A
+ 1 b,B
+ 2 -,C
+ 3 d,D
+ dtype: object
+
+ If `sep` is not specified, the values are concatenated without
+ separation.
+
+ >>> s.str.cat(['A', 'B', 'C', 'D'], na_rep='-')
+ 0 aA
+ 1 bB
+ 2 -C
+ 3 dD
+ dtype: object
+
+ Series with different indexes can be aligned before concatenation. The
+ `join`-keyword works as in other methods.
+
+ >>> t = pd.Series(['d', 'a', 'e', 'c'], index=[3, 0, 4, 2])
+ >>> s.str.cat(t, join='left', na_rep='-')
+ 0 aa
+ 1 b-
+ 2 -c
+ 3 dd
+ dtype: object
+ >>>
+ >>> s.str.cat(t, join='outer', na_rep='-')
+ 0 aa
+ 1 b-
+ 2 -c
+ 3 dd
+ 4 -e
+ dtype: object
+ >>>
+ >>> s.str.cat(t, join='inner', na_rep='-')
+ 0 aa
+ 2 -c
+ 3 dd
+ dtype: object
+ >>>
+ >>> s.str.cat(t, join='right', na_rep='-')
+ 3 dd
+ 0 aa
+ 4 -e
+ 2 -c
+ dtype: object
+
+ For more examples, see :ref:`here `.
+ """
+ # TODO: dispatch
+ from pandas import (
+ Index,
+ Series,
+ concat,
+ )
+
+ if isinstance(others, str):
+ raise ValueError("Did you mean to supply a `sep` keyword?")
+ if sep is None:
+ sep = ""
+
+ if isinstance(self._orig, ABCIndex):
+ data = Series(self._orig, index=self._orig, dtype=self._orig.dtype)
+ else: # Series
+ data = self._orig
+
+ # concatenate Series/Index with itself if no "others"
+ if others is None:
+ # error: Incompatible types in assignment (expression has type
+ # "ndarray", variable has type "Series")
+ data = ensure_object(data) # type: ignore[assignment]
+ na_mask = isna(data)
+ if na_rep is None and na_mask.any():
+ return sep.join(data[~na_mask])
+ elif na_rep is not None and na_mask.any():
+ return sep.join(np.where(na_mask, na_rep, data))
+ else:
+ return sep.join(data)
+
+ try:
+ # turn anything in "others" into lists of Series
+ others = self._get_series_list(others)
+ except ValueError as err: # do not catch TypeError raised by _get_series_list
+ raise ValueError(
+ "If `others` contains arrays or lists (or other "
+ "list-likes without an index), these must all be "
+ "of the same length as the calling Series/Index."
+ ) from err
+
+ # align if required
+ if any(not data.index.equals(x.index) for x in others):
+ # Need to add keys for uniqueness in case of duplicate columns
+ others = concat(
+ others,
+ axis=1,
+ join=(join if join == "inner" else "outer"),
+ keys=range(len(others)),
+ sort=False,
+ copy=False,
+ )
+ data, others = data.align(others, join=join)
+ others = [others[x] for x in others] # again list of Series
+
+ all_cols = [ensure_object(x) for x in [data] + others]
+ na_masks = np.array([isna(x) for x in all_cols])
+ union_mask = np.logical_or.reduce(na_masks, axis=0)
+
+ if na_rep is None and union_mask.any():
+ # no na_rep means NaNs for all rows where any column has a NaN
+ # only necessary if there are actually any NaNs
+ result = np.empty(len(data), dtype=object)
+ np.putmask(result, union_mask, np.nan)
+
+ not_masked = ~union_mask
+ result[not_masked] = cat_safe([x[not_masked] for x in all_cols], sep)
+ elif na_rep is not None and union_mask.any():
+ # fill NaNs with na_rep in case there are actually any NaNs
+ all_cols = [
+ np.where(nm, na_rep, col) for nm, col in zip(na_masks, all_cols)
+ ]
+ result = cat_safe(all_cols, sep)
+ else:
+ # no NaNs - can just concatenate
+ result = cat_safe(all_cols, sep)
+
+ out: Index | Series
+ if isinstance(self._orig.dtype, CategoricalDtype):
+ # We need to infer the new categories.
+ dtype = self._orig.dtype.categories.dtype
+ else:
+ dtype = self._orig.dtype
+ if isinstance(self._orig, ABCIndex):
+ # add dtype for case that result is all-NA
+ if isna(result).all():
+ dtype = object # type: ignore[assignment]
+
+ out = Index(result, dtype=dtype, name=self._orig.name)
+ else: # Series
+ res_ser = Series(
+ result, dtype=dtype, index=data.index, name=self._orig.name, copy=False
+ )
+ out = res_ser.__finalize__(self._orig, method="str_cat")
+ return out
+
+ _shared_docs[
+ "str_split"
+ ] = r"""
+ Split strings around given separator/delimiter.
+
+ Splits the string in the Series/Index from the %(side)s,
+ at the specified delimiter string.
+
+ Parameters
+ ----------
+ pat : str%(pat_regex)s, optional
+ %(pat_description)s.
+ If not specified, split on whitespace.
+ n : int, default -1 (all)
+ Limit number of splits in output.
+ ``None``, 0 and -1 will be interpreted as return all splits.
+ expand : bool, default False
+ Expand the split strings into separate columns.
+
+ - If ``True``, return DataFrame/MultiIndex expanding dimensionality.
+ - If ``False``, return Series/Index, containing lists of strings.
+ %(regex_argument)s
+ Returns
+ -------
+ Series, Index, DataFrame or MultiIndex
+ Type matches caller unless ``expand=True`` (see Notes).
+ %(raises_split)s
+ See Also
+ --------
+ Series.str.split : Split strings around given separator/delimiter.
+ Series.str.rsplit : Splits string around given separator/delimiter,
+ starting from the right.
+ Series.str.join : Join lists contained as elements in the Series/Index
+ with passed delimiter.
+ str.split : Standard library version for split.
+ str.rsplit : Standard library version for rsplit.
+
+ Notes
+ -----
+ The handling of the `n` keyword depends on the number of found splits:
+
+ - If found splits > `n`, make first `n` splits only
+ - If found splits <= `n`, make all splits
+ - If for a certain row the number of found splits < `n`,
+ append `None` for padding up to `n` if ``expand=True``
+
+ If using ``expand=True``, Series and Index callers return DataFrame and
+ MultiIndex objects, respectively.
+ %(regex_pat_note)s
+ Examples
+ --------
+ >>> s = pd.Series(
+ ... [
+ ... "this is a regular sentence",
+ ... "https://docs.python.org/3/tutorial/index.html",
+ ... np.nan
+ ... ]
+ ... )
+ >>> s
+ 0 this is a regular sentence
+ 1 https://docs.python.org/3/tutorial/index.html
+ 2 NaN
+ dtype: object
+
+ In the default setting, the string is split by whitespace.
+
+ >>> s.str.split()
+ 0 [this, is, a, regular, sentence]
+ 1 [https://docs.python.org/3/tutorial/index.html]
+ 2 NaN
+ dtype: object
+
+ Without the `n` parameter, the outputs of `rsplit` and `split`
+ are identical.
+
+ >>> s.str.rsplit()
+ 0 [this, is, a, regular, sentence]
+ 1 [https://docs.python.org/3/tutorial/index.html]
+ 2 NaN
+ dtype: object
+
+ The `n` parameter can be used to limit the number of splits on the
+ delimiter. The outputs of `split` and `rsplit` are different.
+
+ >>> s.str.split(n=2)
+ 0 [this, is, a regular sentence]
+ 1 [https://docs.python.org/3/tutorial/index.html]
+ 2 NaN
+ dtype: object
+
+ >>> s.str.rsplit(n=2)
+ 0 [this is a, regular, sentence]
+ 1 [https://docs.python.org/3/tutorial/index.html]
+ 2 NaN
+ dtype: object
+
+ The `pat` parameter can be used to split by other characters.
+
+ >>> s.str.split(pat="/")
+ 0 [this is a regular sentence]
+ 1 [https:, , docs.python.org, 3, tutorial, index...
+ 2 NaN
+ dtype: object
+
+ When using ``expand=True``, the split elements will expand out into
+ separate columns. If NaN is present, it is propagated throughout
+ the columns during the split.
+
+ >>> s.str.split(expand=True)
+ 0 1 2 3 4
+ 0 this is a regular sentence
+ 1 https://docs.python.org/3/tutorial/index.html None None None None
+ 2 NaN NaN NaN NaN NaN
+
+ For slightly more complex use cases like splitting the html document name
+ from a url, a combination of parameter settings can be used.
+
+ >>> s.str.rsplit("/", n=1, expand=True)
+ 0 1
+ 0 this is a regular sentence None
+ 1 https://docs.python.org/3/tutorial index.html
+ 2 NaN NaN
+ %(regex_examples)s"""
+
+ @Appender(
+ _shared_docs["str_split"]
+ % {
+ "side": "beginning",
+ "pat_regex": " or compiled regex",
+ "pat_description": "String or regular expression to split on",
+ "regex_argument": """
+ regex : bool, default None
+ Determines if the passed-in pattern is a regular expression:
+
+ - If ``True``, assumes the passed-in pattern is a regular expression
+ - If ``False``, treats the pattern as a literal string.
+ - If ``None`` and `pat` length is 1, treats `pat` as a literal string.
+ - If ``None`` and `pat` length is not 1, treats `pat` as a regular expression.
+ - Cannot be set to False if `pat` is a compiled regex
+
+ .. versionadded:: 1.4.0
+ """,
+ "raises_split": """
+ Raises
+ ------
+ ValueError
+ * if `regex` is False and `pat` is a compiled regex
+ """,
+ "regex_pat_note": """
+ Use of `regex =False` with a `pat` as a compiled regex will raise an error.
+ """,
+ "method": "split",
+ "regex_examples": r"""
+ Remember to escape special characters when explicitly using regular expressions.
+
+ >>> s = pd.Series(["foo and bar plus baz"])
+ >>> s.str.split(r"and|plus", expand=True)
+ 0 1 2
+ 0 foo bar baz
+
+ Regular expressions can be used to handle urls or file names.
+ When `pat` is a string and ``regex=None`` (the default), the given `pat` is compiled
+ as a regex only if ``len(pat) != 1``.
+
+ >>> s = pd.Series(['foojpgbar.jpg'])
+ >>> s.str.split(r".", expand=True)
+ 0 1
+ 0 foojpgbar jpg
+
+ >>> s.str.split(r"\.jpg", expand=True)
+ 0 1
+ 0 foojpgbar
+
+ When ``regex=True``, `pat` is interpreted as a regex
+
+ >>> s.str.split(r"\.jpg", regex=True, expand=True)
+ 0 1
+ 0 foojpgbar
+
+ A compiled regex can be passed as `pat`
+
+ >>> import re
+ >>> s.str.split(re.compile(r"\.jpg"), expand=True)
+ 0 1
+ 0 foojpgbar
+
+ When ``regex=False``, `pat` is interpreted as the string itself
+
+ >>> s.str.split(r"\.jpg", regex=False, expand=True)
+ 0
+ 0 foojpgbar.jpg
+ """,
+ }
+ )
+ @forbid_nonstring_types(["bytes"])
+ def split(
+ self,
+ pat: str | re.Pattern | None = None,
+ *,
+ n=-1,
+ expand: bool = False,
+ regex: bool | None = None,
+ ):
+ if regex is False and is_re(pat):
+ raise ValueError(
+ "Cannot use a compiled regex as replacement pattern with regex=False"
+ )
+ if is_re(pat):
+ regex = True
+ result = self._data.array._str_split(pat, n, expand, regex)
+ if self._data.dtype == "category":
+ dtype = self._data.dtype.categories.dtype
+ else:
+ dtype = object if self._data.dtype == object else None
+ return self._wrap_result(
+ result, expand=expand, returns_string=expand, dtype=dtype
+ )
+
+ @Appender(
+ _shared_docs["str_split"]
+ % {
+ "side": "end",
+ "pat_regex": "",
+ "pat_description": "String to split on",
+ "regex_argument": "",
+ "raises_split": "",
+ "regex_pat_note": "",
+ "method": "rsplit",
+ "regex_examples": "",
+ }
+ )
+ @forbid_nonstring_types(["bytes"])
+ def rsplit(self, pat=None, *, n=-1, expand: bool = False):
+ result = self._data.array._str_rsplit(pat, n=n)
+ dtype = object if self._data.dtype == object else None
+ return self._wrap_result(
+ result, expand=expand, returns_string=expand, dtype=dtype
+ )
+
+ _shared_docs[
+ "str_partition"
+ ] = """
+ Split the string at the %(side)s occurrence of `sep`.
+
+ This method splits the string at the %(side)s occurrence of `sep`,
+ and returns 3 elements containing the part before the separator,
+ the separator itself, and the part after the separator.
+ If the separator is not found, return %(return)s.
+
+ Parameters
+ ----------
+ sep : str, default whitespace
+ String to split on.
+ expand : bool, default True
+ If True, return DataFrame/MultiIndex expanding dimensionality.
+ If False, return Series/Index.
+
+ Returns
+ -------
+ DataFrame/MultiIndex or Series/Index of objects
+
+ See Also
+ --------
+ %(also)s
+ Series.str.split : Split strings around given separators.
+ str.partition : Standard library version.
+
+ Examples
+ --------
+
+ >>> s = pd.Series(['Linda van der Berg', 'George Pitt-Rivers'])
+ >>> s
+ 0 Linda van der Berg
+ 1 George Pitt-Rivers
+ dtype: object
+
+ >>> s.str.partition()
+ 0 1 2
+ 0 Linda van der Berg
+ 1 George Pitt-Rivers
+
+ To partition by the last space instead of the first one:
+
+ >>> s.str.rpartition()
+ 0 1 2
+ 0 Linda van der Berg
+ 1 George Pitt-Rivers
+
+ To partition by something different than a space:
+
+ >>> s.str.partition('-')
+ 0 1 2
+ 0 Linda van der Berg
+ 1 George Pitt - Rivers
+
+ To return a Series containing tuples instead of a DataFrame:
+
+ >>> s.str.partition('-', expand=False)
+ 0 (Linda van der Berg, , )
+ 1 (George Pitt, -, Rivers)
+ dtype: object
+
+ Also available on indices:
+
+ >>> idx = pd.Index(['X 123', 'Y 999'])
+ >>> idx
+ Index(['X 123', 'Y 999'], dtype='object')
+
+ Which will create a MultiIndex:
+
+ >>> idx.str.partition()
+ MultiIndex([('X', ' ', '123'),
+ ('Y', ' ', '999')],
+ )
+
+ Or an index with tuples with ``expand=False``:
+
+ >>> idx.str.partition(expand=False)
+ Index([('X', ' ', '123'), ('Y', ' ', '999')], dtype='object')
+ """
+
+ @Appender(
+ _shared_docs["str_partition"]
+ % {
+ "side": "first",
+ "return": "3 elements containing the string itself, followed by two "
+ "empty strings",
+ "also": "rpartition : Split the string at the last occurrence of `sep`.",
+ }
+ )
+ @forbid_nonstring_types(["bytes"])
+ def partition(self, sep: str = " ", expand: bool = True):
+ result = self._data.array._str_partition(sep, expand)
+ if self._data.dtype == "category":
+ dtype = self._data.dtype.categories.dtype
+ else:
+ dtype = object if self._data.dtype == object else None
+ return self._wrap_result(
+ result, expand=expand, returns_string=expand, dtype=dtype
+ )
+
+ @Appender(
+ _shared_docs["str_partition"]
+ % {
+ "side": "last",
+ "return": "3 elements containing two empty strings, followed by the "
+ "string itself",
+ "also": "partition : Split the string at the first occurrence of `sep`.",
+ }
+ )
+ @forbid_nonstring_types(["bytes"])
+ def rpartition(self, sep: str = " ", expand: bool = True):
+ result = self._data.array._str_rpartition(sep, expand)
+ if self._data.dtype == "category":
+ dtype = self._data.dtype.categories.dtype
+ else:
+ dtype = object if self._data.dtype == object else None
+ return self._wrap_result(
+ result, expand=expand, returns_string=expand, dtype=dtype
+ )
+
+ def get(self, i):
+ """
+ Extract element from each component at specified position or with specified key.
+
+ Extract element from lists, tuples, dict, or strings in each element in the
+ Series/Index.
+
+ Parameters
+ ----------
+ i : int or hashable dict label
+ Position or key of element to extract.
+
+ Returns
+ -------
+ Series or Index
+
+ Examples
+ --------
+ >>> s = pd.Series(["String",
+ ... (1, 2, 3),
+ ... ["a", "b", "c"],
+ ... 123,
+ ... -456,
+ ... {1: "Hello", "2": "World"}])
+ >>> s
+ 0 String
+ 1 (1, 2, 3)
+ 2 [a, b, c]
+ 3 123
+ 4 -456
+ 5 {1: 'Hello', '2': 'World'}
+ dtype: object
+
+ >>> s.str.get(1)
+ 0 t
+ 1 2
+ 2 b
+ 3 NaN
+ 4 NaN
+ 5 Hello
+ dtype: object
+
+ >>> s.str.get(-1)
+ 0 g
+ 1 3
+ 2 c
+ 3 NaN
+ 4 NaN
+ 5 None
+ dtype: object
+
+ Return element with given key
+
+ >>> s = pd.Series([{"name": "Hello", "value": "World"},
+ ... {"name": "Goodbye", "value": "Planet"}])
+ >>> s.str.get('name')
+ 0 Hello
+ 1 Goodbye
+ dtype: object
+ """
+ result = self._data.array._str_get(i)
+ return self._wrap_result(result)
+
+ @forbid_nonstring_types(["bytes"])
+ def join(self, sep: str):
+ """
+ Join lists contained as elements in the Series/Index with passed delimiter.
+
+ If the elements of a Series are lists themselves, join the content of these
+ lists using the delimiter passed to the function.
+ This function is an equivalent to :meth:`str.join`.
+
+ Parameters
+ ----------
+ sep : str
+ Delimiter to use between list entries.
+
+ Returns
+ -------
+ Series/Index: object
+ The list entries concatenated by intervening occurrences of the
+ delimiter.
+
+ Raises
+ ------
+ AttributeError
+ If the supplied Series contains neither strings nor lists.
+
+ See Also
+ --------
+ str.join : Standard library version of this method.
+ Series.str.split : Split strings around given separator/delimiter.
+
+ Notes
+ -----
+ If any of the list items is not a string object, the result of the join
+ will be `NaN`.
+
+ Examples
+ --------
+ Example with a list that contains non-string elements.
+
+ >>> s = pd.Series([['lion', 'elephant', 'zebra'],
+ ... [1.1, 2.2, 3.3],
+ ... ['cat', np.nan, 'dog'],
+ ... ['cow', 4.5, 'goat'],
+ ... ['duck', ['swan', 'fish'], 'guppy']])
+ >>> s
+ 0 [lion, elephant, zebra]
+ 1 [1.1, 2.2, 3.3]
+ 2 [cat, nan, dog]
+ 3 [cow, 4.5, goat]
+ 4 [duck, [swan, fish], guppy]
+ dtype: object
+
+ Join all lists using a '-'. The lists containing object(s) of types other
+ than str will produce a NaN.
+
+ >>> s.str.join('-')
+ 0 lion-elephant-zebra
+ 1 NaN
+ 2 NaN
+ 3 NaN
+ 4 NaN
+ dtype: object
+ """
+ result = self._data.array._str_join(sep)
+ return self._wrap_result(result)
+
+ @forbid_nonstring_types(["bytes"])
+ def contains(
+ self, pat, case: bool = True, flags: int = 0, na=None, regex: bool = True
+ ):
+ r"""
+ Test if pattern or regex is contained within a string of a Series or Index.
+
+ Return boolean Series or Index based on whether a given pattern or regex is
+ contained within a string of a Series or Index.
+
+ Parameters
+ ----------
+ pat : str
+ Character sequence or regular expression.
+ case : bool, default True
+ If True, case sensitive.
+ flags : int, default 0 (no flags)
+ Flags to pass through to the re module, e.g. re.IGNORECASE.
+ na : scalar, optional
+ Fill value for missing values. The default depends on dtype of the
+ array. For object-dtype, ``numpy.nan`` is used. For ``StringDtype``,
+ ``pandas.NA`` is used.
+ regex : bool, default True
+ If True, assumes the pat is a regular expression.
+
+ If False, treats the pat as a literal string.
+
+ Returns
+ -------
+ Series or Index of boolean values
+ A Series or Index of boolean values indicating whether the
+ given pattern is contained within the string of each element
+ of the Series or Index.
+
+ See Also
+ --------
+ match : Analogous, but stricter, relying on re.match instead of re.search.
+ Series.str.startswith : Test if the start of each string element matches a
+ pattern.
+ Series.str.endswith : Same as startswith, but tests the end of string.
+
+ Examples
+ --------
+ Returning a Series of booleans using only a literal pattern.
+
+ >>> s1 = pd.Series(['Mouse', 'dog', 'house and parrot', '23', np.nan])
+ >>> s1.str.contains('og', regex=False)
+ 0 False
+ 1 True
+ 2 False
+ 3 False
+ 4 NaN
+ dtype: object
+
+ Returning an Index of booleans using only a literal pattern.
+
+ >>> ind = pd.Index(['Mouse', 'dog', 'house and parrot', '23.0', np.nan])
+ >>> ind.str.contains('23', regex=False)
+ Index([False, False, False, True, nan], dtype='object')
+
+ Specifying case sensitivity using `case`.
+
+ >>> s1.str.contains('oG', case=True, regex=True)
+ 0 False
+ 1 False
+ 2 False
+ 3 False
+ 4 NaN
+ dtype: object
+
+ Specifying `na` to be `False` instead of `NaN` replaces NaN values
+ with `False`. If Series or Index does not contain NaN values
+ the resultant dtype will be `bool`, otherwise, an `object` dtype.
+
+ >>> s1.str.contains('og', na=False, regex=True)
+ 0 False
+ 1 True
+ 2 False
+ 3 False
+ 4 False
+ dtype: bool
+
+ Returning 'house' or 'dog' when either expression occurs in a string.
+
+ >>> s1.str.contains('house|dog', regex=True)
+ 0 False
+ 1 True
+ 2 True
+ 3 False
+ 4 NaN
+ dtype: object
+
+ Ignoring case sensitivity using `flags` with regex.
+
+ >>> import re
+ >>> s1.str.contains('PARROT', flags=re.IGNORECASE, regex=True)
+ 0 False
+ 1 False
+ 2 True
+ 3 False
+ 4 NaN
+ dtype: object
+
+ Returning any digit using regular expression.
+
+ >>> s1.str.contains('\\d', regex=True)
+ 0 False
+ 1 False
+ 2 False
+ 3 True
+ 4 NaN
+ dtype: object
+
+ Ensure `pat` is a not a literal pattern when `regex` is set to True.
+ Note in the following example one might expect only `s2[1]` and `s2[3]` to
+ return `True`. However, '.0' as a regex matches any character
+ followed by a 0.
+
+ >>> s2 = pd.Series(['40', '40.0', '41', '41.0', '35'])
+ >>> s2.str.contains('.0', regex=True)
+ 0 True
+ 1 True
+ 2 False
+ 3 True
+ 4 False
+ dtype: bool
+ """
+ if regex and re.compile(pat).groups:
+ warnings.warn(
+ "This pattern is interpreted as a regular expression, and has "
+ "match groups. To actually get the groups, use str.extract.",
+ UserWarning,
+ stacklevel=find_stack_level(),
+ )
+
+ result = self._data.array._str_contains(pat, case, flags, na, regex)
+ return self._wrap_result(result, fill_value=na, returns_string=False)
+
+ @forbid_nonstring_types(["bytes"])
+ def match(self, pat: str, case: bool = True, flags: int = 0, na=None):
+ """
+ Determine if each string starts with a match of a regular expression.
+
+ Parameters
+ ----------
+ pat : str
+ Character sequence.
+ case : bool, default True
+ If True, case sensitive.
+ flags : int, default 0 (no flags)
+ Regex module flags, e.g. re.IGNORECASE.
+ na : scalar, optional
+ Fill value for missing values. The default depends on dtype of the
+ array. For object-dtype, ``numpy.nan`` is used. For ``StringDtype``,
+ ``pandas.NA`` is used.
+
+ Returns
+ -------
+ Series/Index/array of boolean values
+
+ See Also
+ --------
+ fullmatch : Stricter matching that requires the entire string to match.
+ contains : Analogous, but less strict, relying on re.search instead of
+ re.match.
+ extract : Extract matched groups.
+
+ Examples
+ --------
+ >>> ser = pd.Series(["horse", "eagle", "donkey"])
+ >>> ser.str.match("e")
+ 0 False
+ 1 True
+ 2 False
+ dtype: bool
+ """
+ result = self._data.array._str_match(pat, case=case, flags=flags, na=na)
+ return self._wrap_result(result, fill_value=na, returns_string=False)
+
+ @forbid_nonstring_types(["bytes"])
+ def fullmatch(self, pat, case: bool = True, flags: int = 0, na=None):
+ """
+ Determine if each string entirely matches a regular expression.
+
+ Parameters
+ ----------
+ pat : str
+ Character sequence or regular expression.
+ case : bool, default True
+ If True, case sensitive.
+ flags : int, default 0 (no flags)
+ Regex module flags, e.g. re.IGNORECASE.
+ na : scalar, optional
+ Fill value for missing values. The default depends on dtype of the
+ array. For object-dtype, ``numpy.nan`` is used. For ``StringDtype``,
+ ``pandas.NA`` is used.
+
+ Returns
+ -------
+ Series/Index/array of boolean values
+
+ See Also
+ --------
+ match : Similar, but also returns `True` when only a *prefix* of the string
+ matches the regular expression.
+ extract : Extract matched groups.
+
+ Examples
+ --------
+ >>> ser = pd.Series(["cat", "duck", "dove"])
+ >>> ser.str.fullmatch(r'd.+')
+ 0 False
+ 1 True
+ 2 True
+ dtype: bool
+ """
+ result = self._data.array._str_fullmatch(pat, case=case, flags=flags, na=na)
+ return self._wrap_result(result, fill_value=na, returns_string=False)
+
+ @forbid_nonstring_types(["bytes"])
+ def replace(
+ self,
+ pat: str | re.Pattern,
+ repl: str | Callable,
+ n: int = -1,
+ case: bool | None = None,
+ flags: int = 0,
+ regex: bool = False,
+ ):
+ r"""
+ Replace each occurrence of pattern/regex in the Series/Index.
+
+ Equivalent to :meth:`str.replace` or :func:`re.sub`, depending on
+ the regex value.
+
+ Parameters
+ ----------
+ pat : str or compiled regex
+ String can be a character sequence or regular expression.
+ repl : str or callable
+ Replacement string or a callable. The callable is passed the regex
+ match object and must return a replacement string to be used.
+ See :func:`re.sub`.
+ n : int, default -1 (all)
+ Number of replacements to make from start.
+ case : bool, default None
+ Determines if replace is case sensitive:
+
+ - If True, case sensitive (the default if `pat` is a string)
+ - Set to False for case insensitive
+ - Cannot be set if `pat` is a compiled regex.
+
+ flags : int, default 0 (no flags)
+ Regex module flags, e.g. re.IGNORECASE. Cannot be set if `pat` is a compiled
+ regex.
+ regex : bool, default False
+ Determines if the passed-in pattern is a regular expression:
+
+ - If True, assumes the passed-in pattern is a regular expression.
+ - If False, treats the pattern as a literal string
+ - Cannot be set to False if `pat` is a compiled regex or `repl` is
+ a callable.
+
+ Returns
+ -------
+ Series or Index of object
+ A copy of the object with all matching occurrences of `pat` replaced by
+ `repl`.
+
+ Raises
+ ------
+ ValueError
+ * if `regex` is False and `repl` is a callable or `pat` is a compiled
+ regex
+ * if `pat` is a compiled regex and `case` or `flags` is set
+
+ Notes
+ -----
+ When `pat` is a compiled regex, all flags should be included in the
+ compiled regex. Use of `case`, `flags`, or `regex=False` with a compiled
+ regex will raise an error.
+
+ Examples
+ --------
+ When `pat` is a string and `regex` is True, the given `pat`
+ is compiled as a regex. When `repl` is a string, it replaces matching
+ regex patterns as with :meth:`re.sub`. NaN value(s) in the Series are
+ left as is:
+
+ >>> pd.Series(['foo', 'fuz', np.nan]).str.replace('f.', 'ba', regex=True)
+ 0 bao
+ 1 baz
+ 2 NaN
+ dtype: object
+
+ When `pat` is a string and `regex` is False, every `pat` is replaced with
+ `repl` as with :meth:`str.replace`:
+
+ >>> pd.Series(['f.o', 'fuz', np.nan]).str.replace('f.', 'ba', regex=False)
+ 0 bao
+ 1 fuz
+ 2 NaN
+ dtype: object
+
+ When `repl` is a callable, it is called on every `pat` using
+ :func:`re.sub`. The callable should expect one positional argument
+ (a regex object) and return a string.
+
+ To get the idea:
+
+ >>> pd.Series(['foo', 'fuz', np.nan]).str.replace('f', repr, regex=True)
+ 0 oo
+ 1 uz
+ 2 NaN
+ dtype: object
+
+ Reverse every lowercase alphabetic word:
+
+ >>> repl = lambda m: m.group(0)[::-1]
+ >>> ser = pd.Series(['foo 123', 'bar baz', np.nan])
+ >>> ser.str.replace(r'[a-z]+', repl, regex=True)
+ 0 oof 123
+ 1 rab zab
+ 2 NaN
+ dtype: object
+
+ Using regex groups (extract second group and swap case):
+
+ >>> pat = r"(?P\w+) (?P\w+) (?P\w+)"
+ >>> repl = lambda m: m.group('two').swapcase()
+ >>> ser = pd.Series(['One Two Three', 'Foo Bar Baz'])
+ >>> ser.str.replace(pat, repl, regex=True)
+ 0 tWO
+ 1 bAR
+ dtype: object
+
+ Using a compiled regex with flags
+
+ >>> import re
+ >>> regex_pat = re.compile(r'FUZ', flags=re.IGNORECASE)
+ >>> pd.Series(['foo', 'fuz', np.nan]).str.replace(regex_pat, 'bar', regex=True)
+ 0 foo
+ 1 bar
+ 2 NaN
+ dtype: object
+ """
+ # Check whether repl is valid (GH 13438, GH 15055)
+ if not (isinstance(repl, str) or callable(repl)):
+ raise TypeError("repl must be a string or callable")
+
+ is_compiled_re = is_re(pat)
+ if regex or regex is None:
+ if is_compiled_re and (case is not None or flags != 0):
+ raise ValueError(
+ "case and flags cannot be set when pat is a compiled regex"
+ )
+
+ elif is_compiled_re:
+ raise ValueError(
+ "Cannot use a compiled regex as replacement pattern with regex=False"
+ )
+ elif callable(repl):
+ raise ValueError("Cannot use a callable replacement when regex=False")
+
+ if case is None:
+ case = True
+
+ result = self._data.array._str_replace(
+ pat, repl, n=n, case=case, flags=flags, regex=regex
+ )
+ return self._wrap_result(result)
+
+ @forbid_nonstring_types(["bytes"])
+ def repeat(self, repeats):
+ """
+ Duplicate each string in the Series or Index.
+
+ Parameters
+ ----------
+ repeats : int or sequence of int
+ Same value for all (int) or different value per (sequence).
+
+ Returns
+ -------
+ Series or pandas.Index
+ Series or Index of repeated string objects specified by
+ input parameter repeats.
+
+ Examples
+ --------
+ >>> s = pd.Series(['a', 'b', 'c'])
+ >>> s
+ 0 a
+ 1 b
+ 2 c
+ dtype: object
+
+ Single int repeats string in Series
+
+ >>> s.str.repeat(repeats=2)
+ 0 aa
+ 1 bb
+ 2 cc
+ dtype: object
+
+ Sequence of int repeats corresponding string in Series
+
+ >>> s.str.repeat(repeats=[1, 2, 3])
+ 0 a
+ 1 bb
+ 2 ccc
+ dtype: object
+ """
+ result = self._data.array._str_repeat(repeats)
+ return self._wrap_result(result)
+
+ @forbid_nonstring_types(["bytes"])
+ def pad(
+ self,
+ width: int,
+ side: Literal["left", "right", "both"] = "left",
+ fillchar: str = " ",
+ ):
+ """
+ Pad strings in the Series/Index up to width.
+
+ Parameters
+ ----------
+ width : int
+ Minimum width of resulting string; additional characters will be filled
+ with character defined in `fillchar`.
+ side : {'left', 'right', 'both'}, default 'left'
+ Side from which to fill resulting string.
+ fillchar : str, default ' '
+ Additional character for filling, default is whitespace.
+
+ Returns
+ -------
+ Series or Index of object
+ Returns Series or Index with minimum number of char in object.
+
+ See Also
+ --------
+ Series.str.rjust : Fills the left side of strings with an arbitrary
+ character. Equivalent to ``Series.str.pad(side='left')``.
+ Series.str.ljust : Fills the right side of strings with an arbitrary
+ character. Equivalent to ``Series.str.pad(side='right')``.
+ Series.str.center : Fills both sides of strings with an arbitrary
+ character. Equivalent to ``Series.str.pad(side='both')``.
+ Series.str.zfill : Pad strings in the Series/Index by prepending '0'
+ character. Equivalent to ``Series.str.pad(side='left', fillchar='0')``.
+
+ Examples
+ --------
+ >>> s = pd.Series(["caribou", "tiger"])
+ >>> s
+ 0 caribou
+ 1 tiger
+ dtype: object
+
+ >>> s.str.pad(width=10)
+ 0 caribou
+ 1 tiger
+ dtype: object
+
+ >>> s.str.pad(width=10, side='right', fillchar='-')
+ 0 caribou---
+ 1 tiger-----
+ dtype: object
+
+ >>> s.str.pad(width=10, side='both', fillchar='-')
+ 0 -caribou--
+ 1 --tiger---
+ dtype: object
+ """
+ if not isinstance(fillchar, str):
+ msg = f"fillchar must be a character, not {type(fillchar).__name__}"
+ raise TypeError(msg)
+
+ if len(fillchar) != 1:
+ raise TypeError("fillchar must be a character, not str")
+
+ if not is_integer(width):
+ msg = f"width must be of integer type, not {type(width).__name__}"
+ raise TypeError(msg)
+
+ result = self._data.array._str_pad(width, side=side, fillchar=fillchar)
+ return self._wrap_result(result)
+
+ _shared_docs[
+ "str_pad"
+ ] = """
+ Pad %(side)s side of strings in the Series/Index.
+
+ Equivalent to :meth:`str.%(method)s`.
+
+ Parameters
+ ----------
+ width : int
+ Minimum width of resulting string; additional characters will be filled
+ with ``fillchar``.
+ fillchar : str
+ Additional character for filling, default is whitespace.
+
+ Returns
+ -------
+ Series/Index of objects.
+
+ Examples
+ --------
+ For Series.str.center:
+
+ >>> ser = pd.Series(['dog', 'bird', 'mouse'])
+ >>> ser.str.center(8, fillchar='.')
+ 0 ..dog...
+ 1 ..bird..
+ 2 .mouse..
+ dtype: object
+
+ For Series.str.ljust:
+
+ >>> ser = pd.Series(['dog', 'bird', 'mouse'])
+ >>> ser.str.ljust(8, fillchar='.')
+ 0 dog.....
+ 1 bird....
+ 2 mouse...
+ dtype: object
+
+ For Series.str.rjust:
+
+ >>> ser = pd.Series(['dog', 'bird', 'mouse'])
+ >>> ser.str.rjust(8, fillchar='.')
+ 0 .....dog
+ 1 ....bird
+ 2 ...mouse
+ dtype: object
+ """
+
+ @Appender(_shared_docs["str_pad"] % {"side": "left and right", "method": "center"})
+ @forbid_nonstring_types(["bytes"])
+ def center(self, width: int, fillchar: str = " "):
+ return self.pad(width, side="both", fillchar=fillchar)
+
+ @Appender(_shared_docs["str_pad"] % {"side": "right", "method": "ljust"})
+ @forbid_nonstring_types(["bytes"])
+ def ljust(self, width: int, fillchar: str = " "):
+ return self.pad(width, side="right", fillchar=fillchar)
+
+ @Appender(_shared_docs["str_pad"] % {"side": "left", "method": "rjust"})
+ @forbid_nonstring_types(["bytes"])
+ def rjust(self, width: int, fillchar: str = " "):
+ return self.pad(width, side="left", fillchar=fillchar)
+
+ @forbid_nonstring_types(["bytes"])
+ def zfill(self, width: int):
+ """
+ Pad strings in the Series/Index by prepending '0' characters.
+
+ Strings in the Series/Index are padded with '0' characters on the
+ left of the string to reach a total string length `width`. Strings
+ in the Series/Index with length greater or equal to `width` are
+ unchanged.
+
+ Parameters
+ ----------
+ width : int
+ Minimum length of resulting string; strings with length less
+ than `width` be prepended with '0' characters.
+
+ Returns
+ -------
+ Series/Index of objects.
+
+ See Also
+ --------
+ Series.str.rjust : Fills the left side of strings with an arbitrary
+ character.
+ Series.str.ljust : Fills the right side of strings with an arbitrary
+ character.
+ Series.str.pad : Fills the specified sides of strings with an arbitrary
+ character.
+ Series.str.center : Fills both sides of strings with an arbitrary
+ character.
+
+ Notes
+ -----
+ Differs from :meth:`str.zfill` which has special handling
+ for '+'/'-' in the string.
+
+ Examples
+ --------
+ >>> s = pd.Series(['-1', '1', '1000', 10, np.nan])
+ >>> s
+ 0 -1
+ 1 1
+ 2 1000
+ 3 10
+ 4 NaN
+ dtype: object
+
+ Note that ``10`` and ``NaN`` are not strings, therefore they are
+ converted to ``NaN``. The minus sign in ``'-1'`` is treated as a
+ special character and the zero is added to the right of it
+ (:meth:`str.zfill` would have moved it to the left). ``1000``
+ remains unchanged as it is longer than `width`.
+
+ >>> s.str.zfill(3)
+ 0 -01
+ 1 001
+ 2 1000
+ 3 NaN
+ 4 NaN
+ dtype: object
+ """
+ if not is_integer(width):
+ msg = f"width must be of integer type, not {type(width).__name__}"
+ raise TypeError(msg)
+ f = lambda x: x.zfill(width)
+ result = self._data.array._str_map(f)
+ return self._wrap_result(result)
+
+ def slice(self, start=None, stop=None, step=None):
+ """
+ Slice substrings from each element in the Series or Index.
+
+ Parameters
+ ----------
+ start : int, optional
+ Start position for slice operation.
+ stop : int, optional
+ Stop position for slice operation.
+ step : int, optional
+ Step size for slice operation.
+
+ Returns
+ -------
+ Series or Index of object
+ Series or Index from sliced substring from original string object.
+
+ See Also
+ --------
+ Series.str.slice_replace : Replace a slice with a string.
+ Series.str.get : Return element at position.
+ Equivalent to `Series.str.slice(start=i, stop=i+1)` with `i`
+ being the position.
+
+ Examples
+ --------
+ >>> s = pd.Series(["koala", "dog", "chameleon"])
+ >>> s
+ 0 koala
+ 1 dog
+ 2 chameleon
+ dtype: object
+
+ >>> s.str.slice(start=1)
+ 0 oala
+ 1 og
+ 2 hameleon
+ dtype: object
+
+ >>> s.str.slice(start=-1)
+ 0 a
+ 1 g
+ 2 n
+ dtype: object
+
+ >>> s.str.slice(stop=2)
+ 0 ko
+ 1 do
+ 2 ch
+ dtype: object
+
+ >>> s.str.slice(step=2)
+ 0 kaa
+ 1 dg
+ 2 caeen
+ dtype: object
+
+ >>> s.str.slice(start=0, stop=5, step=3)
+ 0 kl
+ 1 d
+ 2 cm
+ dtype: object
+
+ Equivalent behaviour to:
+
+ >>> s.str[0:5:3]
+ 0 kl
+ 1 d
+ 2 cm
+ dtype: object
+ """
+ result = self._data.array._str_slice(start, stop, step)
+ return self._wrap_result(result)
+
+ @forbid_nonstring_types(["bytes"])
+ def slice_replace(self, start=None, stop=None, repl=None):
+ """
+ Replace a positional slice of a string with another value.
+
+ Parameters
+ ----------
+ start : int, optional
+ Left index position to use for the slice. If not specified (None),
+ the slice is unbounded on the left, i.e. slice from the start
+ of the string.
+ stop : int, optional
+ Right index position to use for the slice. If not specified (None),
+ the slice is unbounded on the right, i.e. slice until the
+ end of the string.
+ repl : str, optional
+ String for replacement. If not specified (None), the sliced region
+ is replaced with an empty string.
+
+ Returns
+ -------
+ Series or Index
+ Same type as the original object.
+
+ See Also
+ --------
+ Series.str.slice : Just slicing without replacement.
+
+ Examples
+ --------
+ >>> s = pd.Series(['a', 'ab', 'abc', 'abdc', 'abcde'])
+ >>> s
+ 0 a
+ 1 ab
+ 2 abc
+ 3 abdc
+ 4 abcde
+ dtype: object
+
+ Specify just `start`, meaning replace `start` until the end of the
+ string with `repl`.
+
+ >>> s.str.slice_replace(1, repl='X')
+ 0 aX
+ 1 aX
+ 2 aX
+ 3 aX
+ 4 aX
+ dtype: object
+
+ Specify just `stop`, meaning the start of the string to `stop` is replaced
+ with `repl`, and the rest of the string is included.
+
+ >>> s.str.slice_replace(stop=2, repl='X')
+ 0 X
+ 1 X
+ 2 Xc
+ 3 Xdc
+ 4 Xcde
+ dtype: object
+
+ Specify `start` and `stop`, meaning the slice from `start` to `stop` is
+ replaced with `repl`. Everything before or after `start` and `stop` is
+ included as is.
+
+ >>> s.str.slice_replace(start=1, stop=3, repl='X')
+ 0 aX
+ 1 aX
+ 2 aX
+ 3 aXc
+ 4 aXde
+ dtype: object
+ """
+ result = self._data.array._str_slice_replace(start, stop, repl)
+ return self._wrap_result(result)
+
+ def decode(self, encoding, errors: str = "strict"):
+ """
+ Decode character string in the Series/Index using indicated encoding.
+
+ Equivalent to :meth:`str.decode` in python2 and :meth:`bytes.decode` in
+ python3.
+
+ Parameters
+ ----------
+ encoding : str
+ errors : str, optional
+
+ Returns
+ -------
+ Series or Index
+
+ Examples
+ --------
+ For Series:
+
+ >>> ser = pd.Series([b'cow', b'123', b'()'])
+ >>> ser.str.decode('ascii')
+ 0 cow
+ 1 123
+ 2 ()
+ dtype: object
+ """
+ # TODO: Add a similar _bytes interface.
+ if encoding in _cpython_optimized_decoders:
+ # CPython optimized implementation
+ f = lambda x: x.decode(encoding, errors)
+ else:
+ decoder = codecs.getdecoder(encoding)
+ f = lambda x: decoder(x, errors)[0]
+ arr = self._data.array
+ # assert isinstance(arr, (StringArray,))
+ result = arr._str_map(f)
+ return self._wrap_result(result)
+
+ @forbid_nonstring_types(["bytes"])
+ def encode(self, encoding, errors: str = "strict"):
+ """
+ Encode character string in the Series/Index using indicated encoding.
+
+ Equivalent to :meth:`str.encode`.
+
+ Parameters
+ ----------
+ encoding : str
+ errors : str, optional
+
+ Returns
+ -------
+ Series/Index of objects
+
+ Examples
+ --------
+ >>> ser = pd.Series(['cow', '123', '()'])
+ >>> ser.str.encode(encoding='ascii')
+ 0 b'cow'
+ 1 b'123'
+ 2 b'()'
+ dtype: object
+ """
+ result = self._data.array._str_encode(encoding, errors)
+ return self._wrap_result(result, returns_string=False)
+
+ _shared_docs[
+ "str_strip"
+ ] = r"""
+ Remove %(position)s characters.
+
+ Strip whitespaces (including newlines) or a set of specified characters
+ from each string in the Series/Index from %(side)s.
+ Replaces any non-strings in Series with NaNs.
+ Equivalent to :meth:`str.%(method)s`.
+
+ Parameters
+ ----------
+ to_strip : str or None, default None
+ Specifying the set of characters to be removed.
+ All combinations of this set of characters will be stripped.
+ If None then whitespaces are removed.
+
+ Returns
+ -------
+ Series or Index of object
+
+ See Also
+ --------
+ Series.str.strip : Remove leading and trailing characters in Series/Index.
+ Series.str.lstrip : Remove leading characters in Series/Index.
+ Series.str.rstrip : Remove trailing characters in Series/Index.
+
+ Examples
+ --------
+ >>> s = pd.Series(['1. Ant. ', '2. Bee!\n', '3. Cat?\t', np.nan, 10, True])
+ >>> s
+ 0 1. Ant.
+ 1 2. Bee!\n
+ 2 3. Cat?\t
+ 3 NaN
+ 4 10
+ 5 True
+ dtype: object
+
+ >>> s.str.strip()
+ 0 1. Ant.
+ 1 2. Bee!
+ 2 3. Cat?
+ 3 NaN
+ 4 NaN
+ 5 NaN
+ dtype: object
+
+ >>> s.str.lstrip('123.')
+ 0 Ant.
+ 1 Bee!\n
+ 2 Cat?\t
+ 3 NaN
+ 4 NaN
+ 5 NaN
+ dtype: object
+
+ >>> s.str.rstrip('.!? \n\t')
+ 0 1. Ant
+ 1 2. Bee
+ 2 3. Cat
+ 3 NaN
+ 4 NaN
+ 5 NaN
+ dtype: object
+
+ >>> s.str.strip('123.!? \n\t')
+ 0 Ant
+ 1 Bee
+ 2 Cat
+ 3 NaN
+ 4 NaN
+ 5 NaN
+ dtype: object
+ """
+
+ @Appender(
+ _shared_docs["str_strip"]
+ % {
+ "side": "left and right sides",
+ "method": "strip",
+ "position": "leading and trailing",
+ }
+ )
+ @forbid_nonstring_types(["bytes"])
+ def strip(self, to_strip=None):
+ result = self._data.array._str_strip(to_strip)
+ return self._wrap_result(result)
+
+ @Appender(
+ _shared_docs["str_strip"]
+ % {"side": "left side", "method": "lstrip", "position": "leading"}
+ )
+ @forbid_nonstring_types(["bytes"])
+ def lstrip(self, to_strip=None):
+ result = self._data.array._str_lstrip(to_strip)
+ return self._wrap_result(result)
+
+ @Appender(
+ _shared_docs["str_strip"]
+ % {"side": "right side", "method": "rstrip", "position": "trailing"}
+ )
+ @forbid_nonstring_types(["bytes"])
+ def rstrip(self, to_strip=None):
+ result = self._data.array._str_rstrip(to_strip)
+ return self._wrap_result(result)
+
+ _shared_docs[
+ "str_removefix"
+ ] = r"""
+ Remove a %(side)s from an object series.
+
+ If the %(side)s is not present, the original string will be returned.
+
+ Parameters
+ ----------
+ %(side)s : str
+ Remove the %(side)s of the string.
+
+ Returns
+ -------
+ Series/Index: object
+ The Series or Index with given %(side)s removed.
+
+ See Also
+ --------
+ Series.str.remove%(other_side)s : Remove a %(other_side)s from an object series.
+
+ Examples
+ --------
+ >>> s = pd.Series(["str_foo", "str_bar", "no_prefix"])
+ >>> s
+ 0 str_foo
+ 1 str_bar
+ 2 no_prefix
+ dtype: object
+ >>> s.str.removeprefix("str_")
+ 0 foo
+ 1 bar
+ 2 no_prefix
+ dtype: object
+
+ >>> s = pd.Series(["foo_str", "bar_str", "no_suffix"])
+ >>> s
+ 0 foo_str
+ 1 bar_str
+ 2 no_suffix
+ dtype: object
+ >>> s.str.removesuffix("_str")
+ 0 foo
+ 1 bar
+ 2 no_suffix
+ dtype: object
+ """
+
+ @Appender(
+ _shared_docs["str_removefix"] % {"side": "prefix", "other_side": "suffix"}
+ )
+ @forbid_nonstring_types(["bytes"])
+ def removeprefix(self, prefix: str):
+ result = self._data.array._str_removeprefix(prefix)
+ return self._wrap_result(result)
+
+ @Appender(
+ _shared_docs["str_removefix"] % {"side": "suffix", "other_side": "prefix"}
+ )
+ @forbid_nonstring_types(["bytes"])
+ def removesuffix(self, suffix: str):
+ result = self._data.array._str_removesuffix(suffix)
+ return self._wrap_result(result)
+
+ @forbid_nonstring_types(["bytes"])
+ def wrap(self, width: int, **kwargs):
+ r"""
+ Wrap strings in Series/Index at specified line width.
+
+ This method has the same keyword parameters and defaults as
+ :class:`textwrap.TextWrapper`.
+
+ Parameters
+ ----------
+ width : int
+ Maximum line width.
+ expand_tabs : bool, optional
+ If True, tab characters will be expanded to spaces (default: True).
+ replace_whitespace : bool, optional
+ If True, each whitespace character (as defined by string.whitespace)
+ remaining after tab expansion will be replaced by a single space
+ (default: True).
+ drop_whitespace : bool, optional
+ If True, whitespace that, after wrapping, happens to end up at the
+ beginning or end of a line is dropped (default: True).
+ break_long_words : bool, optional
+ If True, then words longer than width will be broken in order to ensure
+ that no lines are longer than width. If it is false, long words will
+ not be broken, and some lines may be longer than width (default: True).
+ break_on_hyphens : bool, optional
+ If True, wrapping will occur preferably on whitespace and right after
+ hyphens in compound words, as it is customary in English. If false,
+ only whitespaces will be considered as potentially good places for line
+ breaks, but you need to set break_long_words to false if you want truly
+ insecable words (default: True).
+
+ Returns
+ -------
+ Series or Index
+
+ Notes
+ -----
+ Internally, this method uses a :class:`textwrap.TextWrapper` instance with
+ default settings. To achieve behavior matching R's stringr library str_wrap
+ function, use the arguments:
+
+ - expand_tabs = False
+ - replace_whitespace = True
+ - drop_whitespace = True
+ - break_long_words = False
+ - break_on_hyphens = False
+
+ Examples
+ --------
+ >>> s = pd.Series(['line to be wrapped', 'another line to be wrapped'])
+ >>> s.str.wrap(12)
+ 0 line to be\nwrapped
+ 1 another line\nto be\nwrapped
+ dtype: object
+ """
+ result = self._data.array._str_wrap(width, **kwargs)
+ return self._wrap_result(result)
+
+ @forbid_nonstring_types(["bytes"])
+ def get_dummies(self, sep: str = "|"):
+ """
+ Return DataFrame of dummy/indicator variables for Series.
+
+ Each string in Series is split by sep and returned as a DataFrame
+ of dummy/indicator variables.
+
+ Parameters
+ ----------
+ sep : str, default "|"
+ String to split on.
+
+ Returns
+ -------
+ DataFrame
+ Dummy variables corresponding to values of the Series.
+
+ See Also
+ --------
+ get_dummies : Convert categorical variable into dummy/indicator
+ variables.
+
+ Examples
+ --------
+ >>> pd.Series(['a|b', 'a', 'a|c']).str.get_dummies()
+ a b c
+ 0 1 1 0
+ 1 1 0 0
+ 2 1 0 1
+
+ >>> pd.Series(['a|b', np.nan, 'a|c']).str.get_dummies()
+ a b c
+ 0 1 1 0
+ 1 0 0 0
+ 2 1 0 1
+ """
+ # we need to cast to Series of strings as only that has all
+ # methods available for making the dummies...
+ result, name = self._data.array._str_get_dummies(sep)
+ return self._wrap_result(
+ result,
+ name=name,
+ expand=True,
+ returns_string=False,
+ )
+
+ @forbid_nonstring_types(["bytes"])
+ def translate(self, table):
+ """
+ Map all characters in the string through the given mapping table.
+
+ Equivalent to standard :meth:`str.translate`.
+
+ Parameters
+ ----------
+ table : dict
+ Table is a mapping of Unicode ordinals to Unicode ordinals, strings, or
+ None. Unmapped characters are left untouched.
+ Characters mapped to None are deleted. :meth:`str.maketrans` is a
+ helper function for making translation tables.
+
+ Returns
+ -------
+ Series or Index
+
+ Examples
+ --------
+ >>> ser = pd.Series(["El niño", "Françoise"])
+ >>> mytable = str.maketrans({'ñ': 'n', 'ç': 'c'})
+ >>> ser.str.translate(mytable)
+ 0 El nino
+ 1 Francoise
+ dtype: object
+ """
+ result = self._data.array._str_translate(table)
+ dtype = object if self._data.dtype == "object" else None
+ return self._wrap_result(result, dtype=dtype)
+
+ @forbid_nonstring_types(["bytes"])
+ def count(self, pat, flags: int = 0):
+ r"""
+ Count occurrences of pattern in each string of the Series/Index.
+
+ This function is used to count the number of times a particular regex
+ pattern is repeated in each of the string elements of the
+ :class:`~pandas.Series`.
+
+ Parameters
+ ----------
+ pat : str
+ Valid regular expression.
+ flags : int, default 0, meaning no flags
+ Flags for the `re` module. For a complete list, `see here
+ `_.
+ **kwargs
+ For compatibility with other string methods. Not used.
+
+ Returns
+ -------
+ Series or Index
+ Same type as the calling object containing the integer counts.
+
+ See Also
+ --------
+ re : Standard library module for regular expressions.
+ str.count : Standard library version, without regular expression support.
+
+ Notes
+ -----
+ Some characters need to be escaped when passing in `pat`.
+ eg. ``'$'`` has a special meaning in regex and must be escaped when
+ finding this literal character.
+
+ Examples
+ --------
+ >>> s = pd.Series(['A', 'B', 'Aaba', 'Baca', np.nan, 'CABA', 'cat'])
+ >>> s.str.count('a')
+ 0 0.0
+ 1 0.0
+ 2 2.0
+ 3 2.0
+ 4 NaN
+ 5 0.0
+ 6 1.0
+ dtype: float64
+
+ Escape ``'$'`` to find the literal dollar sign.
+
+ >>> s = pd.Series(['$', 'B', 'Aab$', '$$ca', 'C$B$', 'cat'])
+ >>> s.str.count('\\$')
+ 0 1
+ 1 0
+ 2 1
+ 3 2
+ 4 2
+ 5 0
+ dtype: int64
+
+ This is also available on Index
+
+ >>> pd.Index(['A', 'A', 'Aaba', 'cat']).str.count('a')
+ Index([0, 0, 2, 1], dtype='int64')
+ """
+ result = self._data.array._str_count(pat, flags)
+ return self._wrap_result(result, returns_string=False)
+
+ @forbid_nonstring_types(["bytes"])
+ def startswith(
+ self, pat: str | tuple[str, ...], na: Scalar | None = None
+ ) -> Series | Index:
+ """
+ Test if the start of each string element matches a pattern.
+
+ Equivalent to :meth:`str.startswith`.
+
+ Parameters
+ ----------
+ pat : str or tuple[str, ...]
+ Character sequence or tuple of strings. Regular expressions are not
+ accepted.
+ na : object, default NaN
+ Object shown if element tested is not a string. The default depends
+ on dtype of the array. For object-dtype, ``numpy.nan`` is used.
+ For ``StringDtype``, ``pandas.NA`` is used.
+
+ Returns
+ -------
+ Series or Index of bool
+ A Series of booleans indicating whether the given pattern matches
+ the start of each string element.
+
+ See Also
+ --------
+ str.startswith : Python standard library string method.
+ Series.str.endswith : Same as startswith, but tests the end of string.
+ Series.str.contains : Tests if string element contains a pattern.
+
+ Examples
+ --------
+ >>> s = pd.Series(['bat', 'Bear', 'cat', np.nan])
+ >>> s
+ 0 bat
+ 1 Bear
+ 2 cat
+ 3 NaN
+ dtype: object
+
+ >>> s.str.startswith('b')
+ 0 True
+ 1 False
+ 2 False
+ 3 NaN
+ dtype: object
+
+ >>> s.str.startswith(('b', 'B'))
+ 0 True
+ 1 True
+ 2 False
+ 3 NaN
+ dtype: object
+
+ Specifying `na` to be `False` instead of `NaN`.
+
+ >>> s.str.startswith('b', na=False)
+ 0 True
+ 1 False
+ 2 False
+ 3 False
+ dtype: bool
+ """
+ if not isinstance(pat, (str, tuple)):
+ msg = f"expected a string or tuple, not {type(pat).__name__}"
+ raise TypeError(msg)
+ result = self._data.array._str_startswith(pat, na=na)
+ return self._wrap_result(result, returns_string=False)
+
+ @forbid_nonstring_types(["bytes"])
+ def endswith(
+ self, pat: str | tuple[str, ...], na: Scalar | None = None
+ ) -> Series | Index:
+ """
+ Test if the end of each string element matches a pattern.
+
+ Equivalent to :meth:`str.endswith`.
+
+ Parameters
+ ----------
+ pat : str or tuple[str, ...]
+ Character sequence or tuple of strings. Regular expressions are not
+ accepted.
+ na : object, default NaN
+ Object shown if element tested is not a string. The default depends
+ on dtype of the array. For object-dtype, ``numpy.nan`` is used.
+ For ``StringDtype``, ``pandas.NA`` is used.
+
+ Returns
+ -------
+ Series or Index of bool
+ A Series of booleans indicating whether the given pattern matches
+ the end of each string element.
+
+ See Also
+ --------
+ str.endswith : Python standard library string method.
+ Series.str.startswith : Same as endswith, but tests the start of string.
+ Series.str.contains : Tests if string element contains a pattern.
+
+ Examples
+ --------
+ >>> s = pd.Series(['bat', 'bear', 'caT', np.nan])
+ >>> s
+ 0 bat
+ 1 bear
+ 2 caT
+ 3 NaN
+ dtype: object
+
+ >>> s.str.endswith('t')
+ 0 True
+ 1 False
+ 2 False
+ 3 NaN
+ dtype: object
+
+ >>> s.str.endswith(('t', 'T'))
+ 0 True
+ 1 False
+ 2 True
+ 3 NaN
+ dtype: object
+
+ Specifying `na` to be `False` instead of `NaN`.
+
+ >>> s.str.endswith('t', na=False)
+ 0 True
+ 1 False
+ 2 False
+ 3 False
+ dtype: bool
+ """
+ if not isinstance(pat, (str, tuple)):
+ msg = f"expected a string or tuple, not {type(pat).__name__}"
+ raise TypeError(msg)
+ result = self._data.array._str_endswith(pat, na=na)
+ return self._wrap_result(result, returns_string=False)
+
+ @forbid_nonstring_types(["bytes"])
+ def findall(self, pat, flags: int = 0):
+ """
+ Find all occurrences of pattern or regular expression in the Series/Index.
+
+ Equivalent to applying :func:`re.findall` to all the elements in the
+ Series/Index.
+
+ Parameters
+ ----------
+ pat : str
+ Pattern or regular expression.
+ flags : int, default 0
+ Flags from ``re`` module, e.g. `re.IGNORECASE` (default is 0, which
+ means no flags).
+
+ Returns
+ -------
+ Series/Index of lists of strings
+ All non-overlapping matches of pattern or regular expression in each
+ string of this Series/Index.
+
+ See Also
+ --------
+ count : Count occurrences of pattern or regular expression in each string
+ of the Series/Index.
+ extractall : For each string in the Series, extract groups from all matches
+ of regular expression and return a DataFrame with one row for each
+ match and one column for each group.
+ re.findall : The equivalent ``re`` function to all non-overlapping matches
+ of pattern or regular expression in string, as a list of strings.
+
+ Examples
+ --------
+ >>> s = pd.Series(['Lion', 'Monkey', 'Rabbit'])
+
+ The search for the pattern 'Monkey' returns one match:
+
+ >>> s.str.findall('Monkey')
+ 0 []
+ 1 [Monkey]
+ 2 []
+ dtype: object
+
+ On the other hand, the search for the pattern 'MONKEY' doesn't return any
+ match:
+
+ >>> s.str.findall('MONKEY')
+ 0 []
+ 1 []
+ 2 []
+ dtype: object
+
+ Flags can be added to the pattern or regular expression. For instance,
+ to find the pattern 'MONKEY' ignoring the case:
+
+ >>> import re
+ >>> s.str.findall('MONKEY', flags=re.IGNORECASE)
+ 0 []
+ 1 [Monkey]
+ 2 []
+ dtype: object
+
+ When the pattern matches more than one string in the Series, all matches
+ are returned:
+
+ >>> s.str.findall('on')
+ 0 [on]
+ 1 [on]
+ 2 []
+ dtype: object
+
+ Regular expressions are supported too. For instance, the search for all the
+ strings ending with the word 'on' is shown next:
+
+ >>> s.str.findall('on$')
+ 0 [on]
+ 1 []
+ 2 []
+ dtype: object
+
+ If the pattern is found more than once in the same string, then a list of
+ multiple strings is returned:
+
+ >>> s.str.findall('b')
+ 0 []
+ 1 []
+ 2 [b, b]
+ dtype: object
+ """
+ result = self._data.array._str_findall(pat, flags)
+ return self._wrap_result(result, returns_string=False)
+
+ @forbid_nonstring_types(["bytes"])
+ def extract(
+ self, pat: str, flags: int = 0, expand: bool = True
+ ) -> DataFrame | Series | Index:
+ r"""
+ Extract capture groups in the regex `pat` as columns in a DataFrame.
+
+ For each subject string in the Series, extract groups from the
+ first match of regular expression `pat`.
+
+ Parameters
+ ----------
+ pat : str
+ Regular expression pattern with capturing groups.
+ flags : int, default 0 (no flags)
+ Flags from the ``re`` module, e.g. ``re.IGNORECASE``, that
+ modify regular expression matching for things like case,
+ spaces, etc. For more details, see :mod:`re`.
+ expand : bool, default True
+ If True, return DataFrame with one column per capture group.
+ If False, return a Series/Index if there is one capture group
+ or DataFrame if there are multiple capture groups.
+
+ Returns
+ -------
+ DataFrame or Series or Index
+ A DataFrame with one row for each subject string, and one
+ column for each group. Any capture group names in regular
+ expression pat will be used for column names; otherwise
+ capture group numbers will be used. The dtype of each result
+ column is always object, even when no match is found. If
+ ``expand=False`` and pat has only one capture group, then
+ return a Series (if subject is a Series) or Index (if subject
+ is an Index).
+
+ See Also
+ --------
+ extractall : Returns all matches (not just the first match).
+
+ Examples
+ --------
+ A pattern with two groups will return a DataFrame with two columns.
+ Non-matches will be NaN.
+
+ >>> s = pd.Series(['a1', 'b2', 'c3'])
+ >>> s.str.extract(r'([ab])(\d)')
+ 0 1
+ 0 a 1
+ 1 b 2
+ 2 NaN NaN
+
+ A pattern may contain optional groups.
+
+ >>> s.str.extract(r'([ab])?(\d)')
+ 0 1
+ 0 a 1
+ 1 b 2
+ 2 NaN 3
+
+ Named groups will become column names in the result.
+
+ >>> s.str.extract(r'(?P[ab])(?P\d)')
+ letter digit
+ 0 a 1
+ 1 b 2
+ 2 NaN NaN
+
+ A pattern with one group will return a DataFrame with one column
+ if expand=True.
+
+ >>> s.str.extract(r'[ab](\d)', expand=True)
+ 0
+ 0 1
+ 1 2
+ 2 NaN
+
+ A pattern with one group will return a Series if expand=False.
+
+ >>> s.str.extract(r'[ab](\d)', expand=False)
+ 0 1
+ 1 2
+ 2 NaN
+ dtype: object
+ """
+ from pandas import DataFrame
+
+ if not isinstance(expand, bool):
+ raise ValueError("expand must be True or False")
+
+ regex = re.compile(pat, flags=flags)
+ if regex.groups == 0:
+ raise ValueError("pattern contains no capture groups")
+
+ if not expand and regex.groups > 1 and isinstance(self._data, ABCIndex):
+ raise ValueError("only one regex group is supported with Index")
+
+ obj = self._data
+ result_dtype = _result_dtype(obj)
+
+ returns_df = regex.groups > 1 or expand
+
+ if returns_df:
+ name = None
+ columns = _get_group_names(regex)
+
+ if obj.array.size == 0:
+ result = DataFrame(columns=columns, dtype=result_dtype)
+
+ else:
+ result_list = self._data.array._str_extract(
+ pat, flags=flags, expand=returns_df
+ )
+
+ result_index: Index | None
+ if isinstance(obj, ABCSeries):
+ result_index = obj.index
+ else:
+ result_index = None
+
+ result = DataFrame(
+ result_list, columns=columns, index=result_index, dtype=result_dtype
+ )
+
+ else:
+ name = _get_single_group_name(regex)
+ result = self._data.array._str_extract(pat, flags=flags, expand=returns_df)
+ return self._wrap_result(result, name=name, dtype=result_dtype)
+
+ @forbid_nonstring_types(["bytes"])
+ def extractall(self, pat, flags: int = 0) -> DataFrame:
+ r"""
+ Extract capture groups in the regex `pat` as columns in DataFrame.
+
+ For each subject string in the Series, extract groups from all
+ matches of regular expression pat. When each subject string in the
+ Series has exactly one match, extractall(pat).xs(0, level='match')
+ is the same as extract(pat).
+
+ Parameters
+ ----------
+ pat : str
+ Regular expression pattern with capturing groups.
+ flags : int, default 0 (no flags)
+ A ``re`` module flag, for example ``re.IGNORECASE``. These allow
+ to modify regular expression matching for things like case, spaces,
+ etc. Multiple flags can be combined with the bitwise OR operator,
+ for example ``re.IGNORECASE | re.MULTILINE``.
+
+ Returns
+ -------
+ DataFrame
+ A ``DataFrame`` with one row for each match, and one column for each
+ group. Its rows have a ``MultiIndex`` with first levels that come from
+ the subject ``Series``. The last level is named 'match' and indexes the
+ matches in each item of the ``Series``. Any capture group names in
+ regular expression pat will be used for column names; otherwise capture
+ group numbers will be used.
+
+ See Also
+ --------
+ extract : Returns first match only (not all matches).
+
+ Examples
+ --------
+ A pattern with one group will return a DataFrame with one column.
+ Indices with no matches will not appear in the result.
+
+ >>> s = pd.Series(["a1a2", "b1", "c1"], index=["A", "B", "C"])
+ >>> s.str.extractall(r"[ab](\d)")
+ 0
+ match
+ A 0 1
+ 1 2
+ B 0 1
+
+ Capture group names are used for column names of the result.
+
+ >>> s.str.extractall(r"[ab](?P\d)")
+ digit
+ match
+ A 0 1
+ 1 2
+ B 0 1
+
+ A pattern with two groups will return a DataFrame with two columns.
+
+ >>> s.str.extractall(r"(?P[ab])(?P\d)")
+ letter digit
+ match
+ A 0 a 1
+ 1 a 2
+ B 0 b 1
+
+ Optional groups that do not match are NaN in the result.
+
+ >>> s.str.extractall(r"(?P[ab])?(?P\d)")
+ letter digit
+ match
+ A 0 a 1
+ 1 a 2
+ B 0 b 1
+ C 0 NaN 1
+ """
+ # TODO: dispatch
+ return str_extractall(self._orig, pat, flags)
+
+ _shared_docs[
+ "find"
+ ] = """
+ Return %(side)s indexes in each strings in the Series/Index.
+
+ Each of returned indexes corresponds to the position where the
+ substring is fully contained between [start:end]. Return -1 on
+ failure. Equivalent to standard :meth:`str.%(method)s`.
+
+ Parameters
+ ----------
+ sub : str
+ Substring being searched.
+ start : int
+ Left edge index.
+ end : int
+ Right edge index.
+
+ Returns
+ -------
+ Series or Index of int.
+
+ See Also
+ --------
+ %(also)s
+
+ Examples
+ --------
+ For Series.str.find:
+
+ >>> ser = pd.Series(["cow_", "duck_", "do_ve"])
+ >>> ser.str.find("_")
+ 0 3
+ 1 4
+ 2 2
+ dtype: int64
+
+ For Series.str.rfind:
+
+ >>> ser = pd.Series(["_cow_", "duck_", "do_v_e"])
+ >>> ser.str.rfind("_")
+ 0 4
+ 1 4
+ 2 4
+ dtype: int64
+ """
+
+ @Appender(
+ _shared_docs["find"]
+ % {
+ "side": "lowest",
+ "method": "find",
+ "also": "rfind : Return highest indexes in each strings.",
+ }
+ )
+ @forbid_nonstring_types(["bytes"])
+ def find(self, sub, start: int = 0, end=None):
+ if not isinstance(sub, str):
+ msg = f"expected a string object, not {type(sub).__name__}"
+ raise TypeError(msg)
+
+ result = self._data.array._str_find(sub, start, end)
+ return self._wrap_result(result, returns_string=False)
+
+ @Appender(
+ _shared_docs["find"]
+ % {
+ "side": "highest",
+ "method": "rfind",
+ "also": "find : Return lowest indexes in each strings.",
+ }
+ )
+ @forbid_nonstring_types(["bytes"])
+ def rfind(self, sub, start: int = 0, end=None):
+ if not isinstance(sub, str):
+ msg = f"expected a string object, not {type(sub).__name__}"
+ raise TypeError(msg)
+
+ result = self._data.array._str_rfind(sub, start=start, end=end)
+ return self._wrap_result(result, returns_string=False)
+
+ @forbid_nonstring_types(["bytes"])
+ def normalize(self, form):
+ """
+ Return the Unicode normal form for the strings in the Series/Index.
+
+ For more information on the forms, see the
+ :func:`unicodedata.normalize`.
+
+ Parameters
+ ----------
+ form : {'NFC', 'NFKC', 'NFD', 'NFKD'}
+ Unicode form.
+
+ Returns
+ -------
+ Series/Index of objects
+
+ Examples
+ --------
+ >>> ser = pd.Series(['ñ'])
+ >>> ser.str.normalize('NFC') == ser.str.normalize('NFD')
+ 0 False
+ dtype: bool
+ """
+ result = self._data.array._str_normalize(form)
+ return self._wrap_result(result)
+
+ _shared_docs[
+ "index"
+ ] = """
+ Return %(side)s indexes in each string in Series/Index.
+
+ Each of the returned indexes corresponds to the position where the
+ substring is fully contained between [start:end]. This is the same
+ as ``str.%(similar)s`` except instead of returning -1, it raises a
+ ValueError when the substring is not found. Equivalent to standard
+ ``str.%(method)s``.
+
+ Parameters
+ ----------
+ sub : str
+ Substring being searched.
+ start : int
+ Left edge index.
+ end : int
+ Right edge index.
+
+ Returns
+ -------
+ Series or Index of object
+
+ See Also
+ --------
+ %(also)s
+
+ Examples
+ --------
+ For Series.str.index:
+
+ >>> ser = pd.Series(["horse", "eagle", "donkey"])
+ >>> ser.str.index("e")
+ 0 4
+ 1 0
+ 2 4
+ dtype: int64
+
+ For Series.str.rindex:
+
+ >>> ser = pd.Series(["Deer", "eagle", "Sheep"])
+ >>> ser.str.rindex("e")
+ 0 2
+ 1 4
+ 2 3
+ dtype: int64
+ """
+
+ @Appender(
+ _shared_docs["index"]
+ % {
+ "side": "lowest",
+ "similar": "find",
+ "method": "index",
+ "also": "rindex : Return highest indexes in each strings.",
+ }
+ )
+ @forbid_nonstring_types(["bytes"])
+ def index(self, sub, start: int = 0, end=None):
+ if not isinstance(sub, str):
+ msg = f"expected a string object, not {type(sub).__name__}"
+ raise TypeError(msg)
+
+ result = self._data.array._str_index(sub, start=start, end=end)
+ return self._wrap_result(result, returns_string=False)
+
+ @Appender(
+ _shared_docs["index"]
+ % {
+ "side": "highest",
+ "similar": "rfind",
+ "method": "rindex",
+ "also": "index : Return lowest indexes in each strings.",
+ }
+ )
+ @forbid_nonstring_types(["bytes"])
+ def rindex(self, sub, start: int = 0, end=None):
+ if not isinstance(sub, str):
+ msg = f"expected a string object, not {type(sub).__name__}"
+ raise TypeError(msg)
+
+ result = self._data.array._str_rindex(sub, start=start, end=end)
+ return self._wrap_result(result, returns_string=False)
+
+ def len(self):
+ """
+ Compute the length of each element in the Series/Index.
+
+ The element may be a sequence (such as a string, tuple or list) or a collection
+ (such as a dictionary).
+
+ Returns
+ -------
+ Series or Index of int
+ A Series or Index of integer values indicating the length of each
+ element in the Series or Index.
+
+ See Also
+ --------
+ str.len : Python built-in function returning the length of an object.
+ Series.size : Returns the length of the Series.
+
+ Examples
+ --------
+ Returns the length (number of characters) in a string. Returns the
+ number of entries for dictionaries, lists or tuples.
+
+ >>> s = pd.Series(['dog',
+ ... '',
+ ... 5,
+ ... {'foo' : 'bar'},
+ ... [2, 3, 5, 7],
+ ... ('one', 'two', 'three')])
+ >>> s
+ 0 dog
+ 1
+ 2 5
+ 3 {'foo': 'bar'}
+ 4 [2, 3, 5, 7]
+ 5 (one, two, three)
+ dtype: object
+ >>> s.str.len()
+ 0 3.0
+ 1 0.0
+ 2 NaN
+ 3 1.0
+ 4 4.0
+ 5 3.0
+ dtype: float64
+ """
+ result = self._data.array._str_len()
+ return self._wrap_result(result, returns_string=False)
+
+ _shared_docs[
+ "casemethods"
+ ] = """
+ Convert strings in the Series/Index to %(type)s.
+ %(version)s
+ Equivalent to :meth:`str.%(method)s`.
+
+ Returns
+ -------
+ Series or Index of object
+
+ See Also
+ --------
+ Series.str.lower : Converts all characters to lowercase.
+ Series.str.upper : Converts all characters to uppercase.
+ Series.str.title : Converts first character of each word to uppercase and
+ remaining to lowercase.
+ Series.str.capitalize : Converts first character to uppercase and
+ remaining to lowercase.
+ Series.str.swapcase : Converts uppercase to lowercase and lowercase to
+ uppercase.
+ Series.str.casefold: Removes all case distinctions in the string.
+
+ Examples
+ --------
+ >>> s = pd.Series(['lower', 'CAPITALS', 'this is a sentence', 'SwApCaSe'])
+ >>> s
+ 0 lower
+ 1 CAPITALS
+ 2 this is a sentence
+ 3 SwApCaSe
+ dtype: object
+
+ >>> s.str.lower()
+ 0 lower
+ 1 capitals
+ 2 this is a sentence
+ 3 swapcase
+ dtype: object
+
+ >>> s.str.upper()
+ 0 LOWER
+ 1 CAPITALS
+ 2 THIS IS A SENTENCE
+ 3 SWAPCASE
+ dtype: object
+
+ >>> s.str.title()
+ 0 Lower
+ 1 Capitals
+ 2 This Is A Sentence
+ 3 Swapcase
+ dtype: object
+
+ >>> s.str.capitalize()
+ 0 Lower
+ 1 Capitals
+ 2 This is a sentence
+ 3 Swapcase
+ dtype: object
+
+ >>> s.str.swapcase()
+ 0 LOWER
+ 1 capitals
+ 2 THIS IS A SENTENCE
+ 3 sWaPcAsE
+ dtype: object
+ """
+ # Types:
+ # cases:
+ # upper, lower, title, capitalize, swapcase, casefold
+ # boolean:
+ # isalpha, isnumeric isalnum isdigit isdecimal isspace islower isupper istitle
+ # _doc_args holds dict of strings to use in substituting casemethod docs
+ _doc_args: dict[str, dict[str, str]] = {}
+ _doc_args["lower"] = {"type": "lowercase", "method": "lower", "version": ""}
+ _doc_args["upper"] = {"type": "uppercase", "method": "upper", "version": ""}
+ _doc_args["title"] = {"type": "titlecase", "method": "title", "version": ""}
+ _doc_args["capitalize"] = {
+ "type": "be capitalized",
+ "method": "capitalize",
+ "version": "",
+ }
+ _doc_args["swapcase"] = {
+ "type": "be swapcased",
+ "method": "swapcase",
+ "version": "",
+ }
+ _doc_args["casefold"] = {
+ "type": "be casefolded",
+ "method": "casefold",
+ "version": "",
+ }
+
+ @Appender(_shared_docs["casemethods"] % _doc_args["lower"])
+ @forbid_nonstring_types(["bytes"])
+ def lower(self):
+ result = self._data.array._str_lower()
+ return self._wrap_result(result)
+
+ @Appender(_shared_docs["casemethods"] % _doc_args["upper"])
+ @forbid_nonstring_types(["bytes"])
+ def upper(self):
+ result = self._data.array._str_upper()
+ return self._wrap_result(result)
+
+ @Appender(_shared_docs["casemethods"] % _doc_args["title"])
+ @forbid_nonstring_types(["bytes"])
+ def title(self):
+ result = self._data.array._str_title()
+ return self._wrap_result(result)
+
+ @Appender(_shared_docs["casemethods"] % _doc_args["capitalize"])
+ @forbid_nonstring_types(["bytes"])
+ def capitalize(self):
+ result = self._data.array._str_capitalize()
+ return self._wrap_result(result)
+
+ @Appender(_shared_docs["casemethods"] % _doc_args["swapcase"])
+ @forbid_nonstring_types(["bytes"])
+ def swapcase(self):
+ result = self._data.array._str_swapcase()
+ return self._wrap_result(result)
+
+ @Appender(_shared_docs["casemethods"] % _doc_args["casefold"])
+ @forbid_nonstring_types(["bytes"])
+ def casefold(self):
+ result = self._data.array._str_casefold()
+ return self._wrap_result(result)
+
+ _shared_docs[
+ "ismethods"
+ ] = """
+ Check whether all characters in each string are %(type)s.
+
+ This is equivalent to running the Python string method
+ :meth:`str.%(method)s` for each element of the Series/Index. If a string
+ has zero characters, ``False`` is returned for that check.
+
+ Returns
+ -------
+ Series or Index of bool
+ Series or Index of boolean values with the same length as the original
+ Series/Index.
+
+ See Also
+ --------
+ Series.str.isalpha : Check whether all characters are alphabetic.
+ Series.str.isnumeric : Check whether all characters are numeric.
+ Series.str.isalnum : Check whether all characters are alphanumeric.
+ Series.str.isdigit : Check whether all characters are digits.
+ Series.str.isdecimal : Check whether all characters are decimal.
+ Series.str.isspace : Check whether all characters are whitespace.
+ Series.str.islower : Check whether all characters are lowercase.
+ Series.str.isupper : Check whether all characters are uppercase.
+ Series.str.istitle : Check whether all characters are titlecase.
+
+ Examples
+ --------
+ **Checks for Alphabetic and Numeric Characters**
+
+ >>> s1 = pd.Series(['one', 'one1', '1', ''])
+
+ >>> s1.str.isalpha()
+ 0 True
+ 1 False
+ 2 False
+ 3 False
+ dtype: bool
+
+ >>> s1.str.isnumeric()
+ 0 False
+ 1 False
+ 2 True
+ 3 False
+ dtype: bool
+
+ >>> s1.str.isalnum()
+ 0 True
+ 1 True
+ 2 True
+ 3 False
+ dtype: bool
+
+ Note that checks against characters mixed with any additional punctuation
+ or whitespace will evaluate to false for an alphanumeric check.
+
+ >>> s2 = pd.Series(['A B', '1.5', '3,000'])
+ >>> s2.str.isalnum()
+ 0 False
+ 1 False
+ 2 False
+ dtype: bool
+
+ **More Detailed Checks for Numeric Characters**
+
+ There are several different but overlapping sets of numeric characters that
+ can be checked for.
+
+ >>> s3 = pd.Series(['23', '³', '⅕', ''])
+
+ The ``s3.str.isdecimal`` method checks for characters used to form numbers
+ in base 10.
+
+ >>> s3.str.isdecimal()
+ 0 True
+ 1 False
+ 2 False
+ 3 False
+ dtype: bool
+
+ The ``s.str.isdigit`` method is the same as ``s3.str.isdecimal`` but also
+ includes special digits, like superscripted and subscripted digits in
+ unicode.
+
+ >>> s3.str.isdigit()
+ 0 True
+ 1 True
+ 2 False
+ 3 False
+ dtype: bool
+
+ The ``s.str.isnumeric`` method is the same as ``s3.str.isdigit`` but also
+ includes other characters that can represent quantities such as unicode
+ fractions.
+
+ >>> s3.str.isnumeric()
+ 0 True
+ 1 True
+ 2 True
+ 3 False
+ dtype: bool
+
+ **Checks for Whitespace**
+
+ >>> s4 = pd.Series([' ', '\\t\\r\\n ', ''])
+ >>> s4.str.isspace()
+ 0 True
+ 1 True
+ 2 False
+ dtype: bool
+
+ **Checks for Character Case**
+
+ >>> s5 = pd.Series(['leopard', 'Golden Eagle', 'SNAKE', ''])
+
+ >>> s5.str.islower()
+ 0 True
+ 1 False
+ 2 False
+ 3 False
+ dtype: bool
+
+ >>> s5.str.isupper()
+ 0 False
+ 1 False
+ 2 True
+ 3 False
+ dtype: bool
+
+ The ``s5.str.istitle`` method checks for whether all words are in title
+ case (whether only the first letter of each word is capitalized). Words are
+ assumed to be as any sequence of non-numeric characters separated by
+ whitespace characters.
+
+ >>> s5.str.istitle()
+ 0 False
+ 1 True
+ 2 False
+ 3 False
+ dtype: bool
+ """
+ _doc_args["isalnum"] = {"type": "alphanumeric", "method": "isalnum"}
+ _doc_args["isalpha"] = {"type": "alphabetic", "method": "isalpha"}
+ _doc_args["isdigit"] = {"type": "digits", "method": "isdigit"}
+ _doc_args["isspace"] = {"type": "whitespace", "method": "isspace"}
+ _doc_args["islower"] = {"type": "lowercase", "method": "islower"}
+ _doc_args["isupper"] = {"type": "uppercase", "method": "isupper"}
+ _doc_args["istitle"] = {"type": "titlecase", "method": "istitle"}
+ _doc_args["isnumeric"] = {"type": "numeric", "method": "isnumeric"}
+ _doc_args["isdecimal"] = {"type": "decimal", "method": "isdecimal"}
+ # force _noarg_wrapper return type with dtype=np.dtype(bool) (GH 29624)
+
+ isalnum = _map_and_wrap(
+ "isalnum", docstring=_shared_docs["ismethods"] % _doc_args["isalnum"]
+ )
+ isalpha = _map_and_wrap(
+ "isalpha", docstring=_shared_docs["ismethods"] % _doc_args["isalpha"]
+ )
+ isdigit = _map_and_wrap(
+ "isdigit", docstring=_shared_docs["ismethods"] % _doc_args["isdigit"]
+ )
+ isspace = _map_and_wrap(
+ "isspace", docstring=_shared_docs["ismethods"] % _doc_args["isspace"]
+ )
+ islower = _map_and_wrap(
+ "islower", docstring=_shared_docs["ismethods"] % _doc_args["islower"]
+ )
+ isupper = _map_and_wrap(
+ "isupper", docstring=_shared_docs["ismethods"] % _doc_args["isupper"]
+ )
+ istitle = _map_and_wrap(
+ "istitle", docstring=_shared_docs["ismethods"] % _doc_args["istitle"]
+ )
+ isnumeric = _map_and_wrap(
+ "isnumeric", docstring=_shared_docs["ismethods"] % _doc_args["isnumeric"]
+ )
+ isdecimal = _map_and_wrap(
+ "isdecimal", docstring=_shared_docs["ismethods"] % _doc_args["isdecimal"]
+ )
+
+
+def cat_safe(list_of_columns: list[npt.NDArray[np.object_]], sep: str):
+ """
+ Auxiliary function for :meth:`str.cat`.
+
+ Same signature as cat_core, but handles TypeErrors in concatenation, which
+ happen if the arrays in list_of columns have the wrong dtypes or content.
+
+ Parameters
+ ----------
+ list_of_columns : list of numpy arrays
+ List of arrays to be concatenated with sep;
+ these arrays may not contain NaNs!
+ sep : string
+ The separator string for concatenating the columns.
+
+ Returns
+ -------
+ nd.array
+ The concatenation of list_of_columns with sep.
+ """
+ try:
+ result = cat_core(list_of_columns, sep)
+ except TypeError:
+ # if there are any non-string values (wrong dtype or hidden behind
+ # object dtype), np.sum will fail; catch and return with better message
+ for column in list_of_columns:
+ dtype = lib.infer_dtype(column, skipna=True)
+ if dtype not in ["string", "empty"]:
+ raise TypeError(
+ "Concatenation requires list-likes containing only "
+ "strings (or missing values). Offending values found in "
+ f"column {dtype}"
+ ) from None
+ return result
+
+
+def cat_core(list_of_columns: list, sep: str):
+ """
+ Auxiliary function for :meth:`str.cat`
+
+ Parameters
+ ----------
+ list_of_columns : list of numpy arrays
+ List of arrays to be concatenated with sep;
+ these arrays may not contain NaNs!
+ sep : string
+ The separator string for concatenating the columns.
+
+ Returns
+ -------
+ nd.array
+ The concatenation of list_of_columns with sep.
+ """
+ if sep == "":
+ # no need to interleave sep if it is empty
+ arr_of_cols = np.asarray(list_of_columns, dtype=object)
+ return np.sum(arr_of_cols, axis=0)
+ list_with_sep = [sep] * (2 * len(list_of_columns) - 1)
+ list_with_sep[::2] = list_of_columns
+ arr_with_sep = np.asarray(list_with_sep, dtype=object)
+ return np.sum(arr_with_sep, axis=0)
+
+
+def _result_dtype(arr):
+ # workaround #27953
+ # ideally we just pass `dtype=arr.dtype` unconditionally, but this fails
+ # when the list of values is empty.
+ from pandas.core.arrays.string_ import StringDtype
+
+ if isinstance(arr.dtype, (ArrowDtype, StringDtype)):
+ return arr.dtype
+ return object
+
+
+def _get_single_group_name(regex: re.Pattern) -> Hashable:
+ if regex.groupindex:
+ return next(iter(regex.groupindex))
+ else:
+ return None
+
+
+def _get_group_names(regex: re.Pattern) -> list[Hashable]:
+ """
+ Get named groups from compiled regex.
+
+ Unnamed groups are numbered.
+
+ Parameters
+ ----------
+ regex : compiled regex
+
+ Returns
+ -------
+ list of column labels
+ """
+ names = {v: k for k, v in regex.groupindex.items()}
+ return [names.get(1 + i, i) for i in range(regex.groups)]
+
+
+def str_extractall(arr, pat, flags: int = 0) -> DataFrame:
+ regex = re.compile(pat, flags=flags)
+ # the regex must contain capture groups.
+ if regex.groups == 0:
+ raise ValueError("pattern contains no capture groups")
+
+ if isinstance(arr, ABCIndex):
+ arr = arr.to_series().reset_index(drop=True).astype(arr.dtype)
+
+ columns = _get_group_names(regex)
+ match_list = []
+ index_list = []
+ is_mi = arr.index.nlevels > 1
+
+ for subject_key, subject in arr.items():
+ if isinstance(subject, str):
+ if not is_mi:
+ subject_key = (subject_key,)
+
+ for match_i, match_tuple in enumerate(regex.findall(subject)):
+ if isinstance(match_tuple, str):
+ match_tuple = (match_tuple,)
+ na_tuple = [np.nan if group == "" else group for group in match_tuple]
+ match_list.append(na_tuple)
+ result_key = tuple(subject_key + (match_i,))
+ index_list.append(result_key)
+
+ from pandas import MultiIndex
+
+ index = MultiIndex.from_tuples(index_list, names=arr.index.names + ["match"])
+ dtype = _result_dtype(arr)
+
+ result = arr._constructor_expanddim(
+ match_list, index=index, columns=columns, dtype=dtype
+ )
+ return result
diff --git a/env-llmeval/lib/python3.10/site-packages/pandas/core/strings/object_array.py b/env-llmeval/lib/python3.10/site-packages/pandas/core/strings/object_array.py
new file mode 100644
index 0000000000000000000000000000000000000000..0029beccc40a8d3a671802c7d68fab21612704e9
--- /dev/null
+++ b/env-llmeval/lib/python3.10/site-packages/pandas/core/strings/object_array.py
@@ -0,0 +1,497 @@
+from __future__ import annotations
+
+import functools
+import re
+import textwrap
+from typing import (
+ TYPE_CHECKING,
+ Callable,
+ Literal,
+ cast,
+)
+import unicodedata
+
+import numpy as np
+
+from pandas._libs import lib
+import pandas._libs.missing as libmissing
+import pandas._libs.ops as libops
+
+from pandas.core.dtypes.missing import isna
+
+from pandas.core.strings.base import BaseStringArrayMethods
+
+if TYPE_CHECKING:
+ from collections.abc import Sequence
+
+ from pandas._typing import (
+ NpDtype,
+ Scalar,
+ )
+
+ from pandas import Series
+
+
+class ObjectStringArrayMixin(BaseStringArrayMethods):
+ """
+ String Methods operating on object-dtype ndarrays.
+ """
+
+ _str_na_value = np.nan
+
+ def __len__(self) -> int:
+ # For typing, _str_map relies on the object being sized.
+ raise NotImplementedError
+
+ def _str_map(
+ self, f, na_value=None, dtype: NpDtype | None = None, convert: bool = True
+ ):
+ """
+ Map a callable over valid elements of the array.
+
+ Parameters
+ ----------
+ f : Callable
+ A function to call on each non-NA element.
+ na_value : Scalar, optional
+ The value to set for NA values. Might also be used for the
+ fill value if the callable `f` raises an exception.
+ This defaults to ``self._str_na_value`` which is ``np.nan``
+ for object-dtype and Categorical and ``pd.NA`` for StringArray.
+ dtype : Dtype, optional
+ The dtype of the result array.
+ convert : bool, default True
+ Whether to call `maybe_convert_objects` on the resulting ndarray
+ """
+ if dtype is None:
+ dtype = np.dtype("object")
+ if na_value is None:
+ na_value = self._str_na_value
+
+ if not len(self):
+ return np.array([], dtype=dtype)
+
+ arr = np.asarray(self, dtype=object)
+ mask = isna(arr)
+ map_convert = convert and not np.all(mask)
+ try:
+ result = lib.map_infer_mask(arr, f, mask.view(np.uint8), map_convert)
+ except (TypeError, AttributeError) as err:
+ # Reraise the exception if callable `f` got wrong number of args.
+ # The user may want to be warned by this, instead of getting NaN
+ p_err = (
+ r"((takes)|(missing)) (?(2)from \d+ to )?\d+ "
+ r"(?(3)required )positional arguments?"
+ )
+
+ if len(err.args) >= 1 and re.search(p_err, err.args[0]):
+ # FIXME: this should be totally avoidable
+ raise err
+
+ def g(x):
+ # This type of fallback behavior can be removed once
+ # we remove object-dtype .str accessor.
+ try:
+ return f(x)
+ except (TypeError, AttributeError):
+ return na_value
+
+ return self._str_map(g, na_value=na_value, dtype=dtype)
+ if not isinstance(result, np.ndarray):
+ return result
+ if na_value is not np.nan:
+ np.putmask(result, mask, na_value)
+ if convert and result.dtype == object:
+ result = lib.maybe_convert_objects(result)
+ return result
+
+ def _str_count(self, pat, flags: int = 0):
+ regex = re.compile(pat, flags=flags)
+ f = lambda x: len(regex.findall(x))
+ return self._str_map(f, dtype="int64")
+
+ def _str_pad(
+ self,
+ width: int,
+ side: Literal["left", "right", "both"] = "left",
+ fillchar: str = " ",
+ ):
+ if side == "left":
+ f = lambda x: x.rjust(width, fillchar)
+ elif side == "right":
+ f = lambda x: x.ljust(width, fillchar)
+ elif side == "both":
+ f = lambda x: x.center(width, fillchar)
+ else: # pragma: no cover
+ raise ValueError("Invalid side")
+ return self._str_map(f)
+
+ def _str_contains(
+ self, pat, case: bool = True, flags: int = 0, na=np.nan, regex: bool = True
+ ):
+ if regex:
+ if not case:
+ flags |= re.IGNORECASE
+
+ pat = re.compile(pat, flags=flags)
+
+ f = lambda x: pat.search(x) is not None
+ else:
+ if case:
+ f = lambda x: pat in x
+ else:
+ upper_pat = pat.upper()
+ f = lambda x: upper_pat in x.upper()
+ return self._str_map(f, na, dtype=np.dtype("bool"))
+
+ def _str_startswith(self, pat, na=None):
+ f = lambda x: x.startswith(pat)
+ return self._str_map(f, na_value=na, dtype=np.dtype(bool))
+
+ def _str_endswith(self, pat, na=None):
+ f = lambda x: x.endswith(pat)
+ return self._str_map(f, na_value=na, dtype=np.dtype(bool))
+
+ def _str_replace(
+ self,
+ pat: str | re.Pattern,
+ repl: str | Callable,
+ n: int = -1,
+ case: bool = True,
+ flags: int = 0,
+ regex: bool = True,
+ ):
+ if case is False:
+ # add case flag, if provided
+ flags |= re.IGNORECASE
+
+ if regex or flags or callable(repl):
+ if not isinstance(pat, re.Pattern):
+ if regex is False:
+ pat = re.escape(pat)
+ pat = re.compile(pat, flags=flags)
+
+ n = n if n >= 0 else 0
+ f = lambda x: pat.sub(repl=repl, string=x, count=n)
+ else:
+ f = lambda x: x.replace(pat, repl, n)
+
+ return self._str_map(f, dtype=str)
+
+ def _str_repeat(self, repeats: int | Sequence[int]):
+ if lib.is_integer(repeats):
+ rint = cast(int, repeats)
+
+ def scalar_rep(x):
+ try:
+ return bytes.__mul__(x, rint)
+ except TypeError:
+ return str.__mul__(x, rint)
+
+ return self._str_map(scalar_rep, dtype=str)
+ else:
+ from pandas.core.arrays.string_ import BaseStringArray
+
+ def rep(x, r):
+ if x is libmissing.NA:
+ return x
+ try:
+ return bytes.__mul__(x, r)
+ except TypeError:
+ return str.__mul__(x, r)
+
+ result = libops.vec_binop(
+ np.asarray(self),
+ np.asarray(repeats, dtype=object),
+ rep,
+ )
+ if isinstance(self, BaseStringArray):
+ # Not going through map, so we have to do this here.
+ result = type(self)._from_sequence(result, dtype=self.dtype)
+ return result
+
+ def _str_match(
+ self, pat: str, case: bool = True, flags: int = 0, na: Scalar | None = None
+ ):
+ if not case:
+ flags |= re.IGNORECASE
+
+ regex = re.compile(pat, flags=flags)
+
+ f = lambda x: regex.match(x) is not None
+ return self._str_map(f, na_value=na, dtype=np.dtype(bool))
+
+ def _str_fullmatch(
+ self,
+ pat: str | re.Pattern,
+ case: bool = True,
+ flags: int = 0,
+ na: Scalar | None = None,
+ ):
+ if not case:
+ flags |= re.IGNORECASE
+
+ regex = re.compile(pat, flags=flags)
+
+ f = lambda x: regex.fullmatch(x) is not None
+ return self._str_map(f, na_value=na, dtype=np.dtype(bool))
+
+ def _str_encode(self, encoding, errors: str = "strict"):
+ f = lambda x: x.encode(encoding, errors=errors)
+ return self._str_map(f, dtype=object)
+
+ def _str_find(self, sub, start: int = 0, end=None):
+ return self._str_find_(sub, start, end, side="left")
+
+ def _str_rfind(self, sub, start: int = 0, end=None):
+ return self._str_find_(sub, start, end, side="right")
+
+ def _str_find_(self, sub, start, end, side):
+ if side == "left":
+ method = "find"
+ elif side == "right":
+ method = "rfind"
+ else: # pragma: no cover
+ raise ValueError("Invalid side")
+
+ if end is None:
+ f = lambda x: getattr(x, method)(sub, start)
+ else:
+ f = lambda x: getattr(x, method)(sub, start, end)
+ return self._str_map(f, dtype="int64")
+
+ def _str_findall(self, pat, flags: int = 0):
+ regex = re.compile(pat, flags=flags)
+ return self._str_map(regex.findall, dtype="object")
+
+ def _str_get(self, i):
+ def f(x):
+ if isinstance(x, dict):
+ return x.get(i)
+ elif len(x) > i >= -len(x):
+ return x[i]
+ return self._str_na_value
+
+ return self._str_map(f)
+
+ def _str_index(self, sub, start: int = 0, end=None):
+ if end:
+ f = lambda x: x.index(sub, start, end)
+ else:
+ f = lambda x: x.index(sub, start, end)
+ return self._str_map(f, dtype="int64")
+
+ def _str_rindex(self, sub, start: int = 0, end=None):
+ if end:
+ f = lambda x: x.rindex(sub, start, end)
+ else:
+ f = lambda x: x.rindex(sub, start, end)
+ return self._str_map(f, dtype="int64")
+
+ def _str_join(self, sep: str):
+ return self._str_map(sep.join)
+
+ def _str_partition(self, sep: str, expand):
+ result = self._str_map(lambda x: x.partition(sep), dtype="object")
+ return result
+
+ def _str_rpartition(self, sep: str, expand):
+ return self._str_map(lambda x: x.rpartition(sep), dtype="object")
+
+ def _str_len(self):
+ return self._str_map(len, dtype="int64")
+
+ def _str_slice(self, start=None, stop=None, step=None):
+ obj = slice(start, stop, step)
+ return self._str_map(lambda x: x[obj])
+
+ def _str_slice_replace(self, start=None, stop=None, repl=None):
+ if repl is None:
+ repl = ""
+
+ def f(x):
+ if x[start:stop] == "":
+ local_stop = start
+ else:
+ local_stop = stop
+ y = ""
+ if start is not None:
+ y += x[:start]
+ y += repl
+ if stop is not None:
+ y += x[local_stop:]
+ return y
+
+ return self._str_map(f)
+
+ def _str_split(
+ self,
+ pat: str | re.Pattern | None = None,
+ n=-1,
+ expand: bool = False,
+ regex: bool | None = None,
+ ):
+ if pat is None:
+ if n is None or n == 0:
+ n = -1
+ f = lambda x: x.split(pat, n)
+ else:
+ new_pat: str | re.Pattern
+ if regex is True or isinstance(pat, re.Pattern):
+ new_pat = re.compile(pat)
+ elif regex is False:
+ new_pat = pat
+ # regex is None so link to old behavior #43563
+ else:
+ if len(pat) == 1:
+ new_pat = pat
+ else:
+ new_pat = re.compile(pat)
+
+ if isinstance(new_pat, re.Pattern):
+ if n is None or n == -1:
+ n = 0
+ f = lambda x: new_pat.split(x, maxsplit=n)
+ else:
+ if n is None or n == 0:
+ n = -1
+ f = lambda x: x.split(pat, n)
+ return self._str_map(f, dtype=object)
+
+ def _str_rsplit(self, pat=None, n=-1):
+ if n is None or n == 0:
+ n = -1
+ f = lambda x: x.rsplit(pat, n)
+ return self._str_map(f, dtype="object")
+
+ def _str_translate(self, table):
+ return self._str_map(lambda x: x.translate(table))
+
+ def _str_wrap(self, width: int, **kwargs):
+ kwargs["width"] = width
+ tw = textwrap.TextWrapper(**kwargs)
+ return self._str_map(lambda s: "\n".join(tw.wrap(s)))
+
+ def _str_get_dummies(self, sep: str = "|"):
+ from pandas import Series
+
+ arr = Series(self).fillna("")
+ try:
+ arr = sep + arr + sep
+ except (TypeError, NotImplementedError):
+ arr = sep + arr.astype(str) + sep
+
+ tags: set[str] = set()
+ for ts in Series(arr, copy=False).str.split(sep):
+ tags.update(ts)
+ tags2 = sorted(tags - {""})
+
+ dummies = np.empty((len(arr), len(tags2)), dtype=np.int64)
+
+ def _isin(test_elements: str, element: str) -> bool:
+ return element in test_elements
+
+ for i, t in enumerate(tags2):
+ pat = sep + t + sep
+ dummies[:, i] = lib.map_infer(
+ arr.to_numpy(), functools.partial(_isin, element=pat)
+ )
+ return dummies, tags2
+
+ def _str_upper(self):
+ return self._str_map(lambda x: x.upper())
+
+ def _str_isalnum(self):
+ return self._str_map(str.isalnum, dtype="bool")
+
+ def _str_isalpha(self):
+ return self._str_map(str.isalpha, dtype="bool")
+
+ def _str_isdecimal(self):
+ return self._str_map(str.isdecimal, dtype="bool")
+
+ def _str_isdigit(self):
+ return self._str_map(str.isdigit, dtype="bool")
+
+ def _str_islower(self):
+ return self._str_map(str.islower, dtype="bool")
+
+ def _str_isnumeric(self):
+ return self._str_map(str.isnumeric, dtype="bool")
+
+ def _str_isspace(self):
+ return self._str_map(str.isspace, dtype="bool")
+
+ def _str_istitle(self):
+ return self._str_map(str.istitle, dtype="bool")
+
+ def _str_isupper(self):
+ return self._str_map(str.isupper, dtype="bool")
+
+ def _str_capitalize(self):
+ return self._str_map(str.capitalize)
+
+ def _str_casefold(self):
+ return self._str_map(str.casefold)
+
+ def _str_title(self):
+ return self._str_map(str.title)
+
+ def _str_swapcase(self):
+ return self._str_map(str.swapcase)
+
+ def _str_lower(self):
+ return self._str_map(str.lower)
+
+ def _str_normalize(self, form):
+ f = lambda x: unicodedata.normalize(form, x)
+ return self._str_map(f)
+
+ def _str_strip(self, to_strip=None):
+ return self._str_map(lambda x: x.strip(to_strip))
+
+ def _str_lstrip(self, to_strip=None):
+ return self._str_map(lambda x: x.lstrip(to_strip))
+
+ def _str_rstrip(self, to_strip=None):
+ return self._str_map(lambda x: x.rstrip(to_strip))
+
+ def _str_removeprefix(self, prefix: str) -> Series:
+ # outstanding question on whether to use native methods for users on Python 3.9+
+ # https://github.com/pandas-dev/pandas/pull/39226#issuecomment-836719770,
+ # in which case we could do return self._str_map(str.removeprefix)
+
+ def removeprefix(text: str) -> str:
+ if text.startswith(prefix):
+ return text[len(prefix) :]
+ return text
+
+ return self._str_map(removeprefix)
+
+ def _str_removesuffix(self, suffix: str) -> Series:
+ return self._str_map(lambda x: x.removesuffix(suffix))
+
+ def _str_extract(self, pat: str, flags: int = 0, expand: bool = True):
+ regex = re.compile(pat, flags=flags)
+ na_value = self._str_na_value
+
+ if not expand:
+
+ def g(x):
+ m = regex.search(x)
+ return m.groups()[0] if m else na_value
+
+ return self._str_map(g, convert=False)
+
+ empty_row = [na_value] * regex.groups
+
+ def f(x):
+ if not isinstance(x, str):
+ return empty_row
+ m = regex.search(x)
+ if m:
+ return [na_value if item is None else item for item in m.groups()]
+ else:
+ return empty_row
+
+ return [f(val) for val in np.asarray(self)]
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