peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/pyarrow
/tests
/test_json.py
# Licensed to the Apache Software Foundation (ASF) under one | |
# or more contributor license agreements. See the NOTICE file | |
# distributed with this work for additional information | |
# regarding copyright ownership. The ASF licenses this file | |
# to you under the Apache License, Version 2.0 (the | |
# "License"); you may not use this file except in compliance | |
# with the License. You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, | |
# software distributed under the License is distributed on an | |
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | |
# KIND, either express or implied. See the License for the | |
# specific language governing permissions and limitations | |
# under the License. | |
from collections import OrderedDict | |
from decimal import Decimal | |
import io | |
import itertools | |
import json | |
import string | |
import unittest | |
import numpy as np | |
import pytest | |
import pyarrow as pa | |
from pyarrow.json import read_json, ReadOptions, ParseOptions | |
def generate_col_names(): | |
# 'a', 'b'... 'z', then 'aa', 'ab'... | |
letters = string.ascii_lowercase | |
yield from letters | |
for first in letters: | |
for second in letters: | |
yield first + second | |
def make_random_json(num_cols=2, num_rows=10, linesep='\r\n'): | |
arr = np.random.RandomState(42).randint(0, 1000, size=(num_cols, num_rows)) | |
col_names = list(itertools.islice(generate_col_names(), num_cols)) | |
lines = [] | |
for row in arr.T: | |
json_obj = OrderedDict([(k, int(v)) for (k, v) in zip(col_names, row)]) | |
lines.append(json.dumps(json_obj)) | |
data = linesep.join(lines).encode() | |
columns = [pa.array(col, type=pa.int64()) for col in arr] | |
expected = pa.Table.from_arrays(columns, col_names) | |
return data, expected | |
def check_options_class_pickling(cls, pickler, **attr_values): | |
opts = cls(**attr_values) | |
new_opts = pickler.loads(pickler.dumps(opts, | |
protocol=pickler.HIGHEST_PROTOCOL)) | |
for name, value in attr_values.items(): | |
assert getattr(new_opts, name) == value | |
def test_read_options(pickle_module): | |
cls = ReadOptions | |
opts = cls() | |
assert opts.block_size > 0 | |
opts.block_size = 12345 | |
assert opts.block_size == 12345 | |
assert opts.use_threads is True | |
opts.use_threads = False | |
assert opts.use_threads is False | |
opts = cls(block_size=1234, use_threads=False) | |
assert opts.block_size == 1234 | |
assert opts.use_threads is False | |
check_options_class_pickling(cls, pickler=pickle_module, | |
block_size=1234, | |
use_threads=False) | |
def test_parse_options(pickle_module): | |
cls = ParseOptions | |
opts = cls() | |
assert opts.newlines_in_values is False | |
assert opts.explicit_schema is None | |
opts.newlines_in_values = True | |
assert opts.newlines_in_values is True | |
schema = pa.schema([pa.field('foo', pa.int32())]) | |
opts.explicit_schema = schema | |
assert opts.explicit_schema == schema | |
assert opts.unexpected_field_behavior == "infer" | |
for value in ["ignore", "error", "infer"]: | |
opts.unexpected_field_behavior = value | |
assert opts.unexpected_field_behavior == value | |
with pytest.raises(ValueError): | |
opts.unexpected_field_behavior = "invalid-value" | |
check_options_class_pickling(cls, pickler=pickle_module, | |
explicit_schema=schema, | |
newlines_in_values=False, | |
unexpected_field_behavior="ignore") | |
class BaseTestJSONRead: | |
def read_bytes(self, b, **kwargs): | |
return self.read_json(pa.py_buffer(b), **kwargs) | |
def check_names(self, table, names): | |
assert table.num_columns == len(names) | |
assert [c.name for c in table.columns] == names | |
def test_file_object(self): | |
data = b'{"a": 1, "b": 2}\n' | |
expected_data = {'a': [1], 'b': [2]} | |
bio = io.BytesIO(data) | |
table = self.read_json(bio) | |
assert table.to_pydict() == expected_data | |
# Text files not allowed | |
sio = io.StringIO(data.decode()) | |
with pytest.raises(TypeError): | |
self.read_json(sio) | |
def test_block_sizes(self): | |
rows = b'{"a": 1}\n{"a": 2}\n{"a": 3}' | |
read_options = ReadOptions() | |
parse_options = ParseOptions() | |
for data in [rows, rows + b'\n']: | |
for newlines_in_values in [False, True]: | |
parse_options.newlines_in_values = newlines_in_values | |
read_options.block_size = 4 | |
with pytest.raises(ValueError, | |
match="try to increase block size"): | |
self.read_bytes(data, read_options=read_options, | |
parse_options=parse_options) | |
# Validate reader behavior with various block sizes. | |
# There used to be bugs in this area. | |
for block_size in range(9, 20): | |
read_options.block_size = block_size | |
table = self.read_bytes(data, read_options=read_options, | |
parse_options=parse_options) | |
assert table.to_pydict() == {'a': [1, 2, 3]} | |
def test_no_newline_at_end(self): | |
rows = b'{"a": 1,"b": 2, "c": 3}\n{"a": 4,"b": 5, "c": 6}' | |
table = self.read_bytes(rows) | |
assert table.to_pydict() == { | |
'a': [1, 4], | |
'b': [2, 5], | |
'c': [3, 6], | |
} | |
def test_simple_ints(self): | |
# Infer integer columns | |
rows = b'{"a": 1,"b": 2, "c": 3}\n{"a": 4,"b": 5, "c": 6}\n' | |
table = self.read_bytes(rows) | |
schema = pa.schema([('a', pa.int64()), | |
('b', pa.int64()), | |
('c', pa.int64())]) | |
assert table.schema == schema | |
assert table.to_pydict() == { | |
'a': [1, 4], | |
'b': [2, 5], | |
'c': [3, 6], | |
} | |
def test_simple_varied(self): | |
# Infer various kinds of data | |
rows = (b'{"a": 1,"b": 2, "c": "3", "d": false}\n' | |
b'{"a": 4.0, "b": -5, "c": "foo", "d": true}\n') | |
table = self.read_bytes(rows) | |
schema = pa.schema([('a', pa.float64()), | |
('b', pa.int64()), | |
('c', pa.string()), | |
('d', pa.bool_())]) | |
assert table.schema == schema | |
assert table.to_pydict() == { | |
'a': [1.0, 4.0], | |
'b': [2, -5], | |
'c': ["3", "foo"], | |
'd': [False, True], | |
} | |
def test_simple_nulls(self): | |
# Infer various kinds of data, with nulls | |
rows = (b'{"a": 1, "b": 2, "c": null, "d": null, "e": null}\n' | |
b'{"a": null, "b": -5, "c": "foo", "d": null, "e": true}\n' | |
b'{"a": 4.5, "b": null, "c": "nan", "d": null,"e": false}\n') | |
table = self.read_bytes(rows) | |
schema = pa.schema([('a', pa.float64()), | |
('b', pa.int64()), | |
('c', pa.string()), | |
('d', pa.null()), | |
('e', pa.bool_())]) | |
assert table.schema == schema | |
assert table.to_pydict() == { | |
'a': [1.0, None, 4.5], | |
'b': [2, -5, None], | |
'c': [None, "foo", "nan"], | |
'd': [None, None, None], | |
'e': [None, True, False], | |
} | |
def test_empty_lists(self): | |
# ARROW-10955: Infer list(null) | |
rows = b'{"a": []}' | |
table = self.read_bytes(rows) | |
schema = pa.schema([('a', pa.list_(pa.null()))]) | |
assert table.schema == schema | |
assert table.to_pydict() == {'a': [[]]} | |
def test_empty_rows(self): | |
rows = b'{}\n{}\n' | |
table = self.read_bytes(rows) | |
schema = pa.schema([]) | |
assert table.schema == schema | |
assert table.num_columns == 0 | |
assert table.num_rows == 2 | |
def test_reconcile_across_blocks(self): | |
# ARROW-12065: reconciling inferred types across blocks | |
first_row = b'{ }\n' | |
read_options = ReadOptions(block_size=len(first_row)) | |
for next_rows, expected_pylist in [ | |
(b'{"a": 0}', [None, 0]), | |
(b'{"a": []}', [None, []]), | |
(b'{"a": []}\n{"a": [[1]]}', [None, [], [[1]]]), | |
(b'{"a": {}}', [None, {}]), | |
(b'{"a": {}}\n{"a": {"b": {"c": 1}}}', | |
[None, {"b": None}, {"b": {"c": 1}}]), | |
]: | |
table = self.read_bytes(first_row + next_rows, | |
read_options=read_options) | |
expected = {"a": expected_pylist} | |
assert table.to_pydict() == expected | |
# Check that the issue was exercised | |
assert table.column("a").num_chunks > 1 | |
def test_explicit_schema_decimal(self): | |
rows = (b'{"a": 1}\n' | |
b'{"a": 1.45}\n' | |
b'{"a": -23.456}\n' | |
b'{}\n') | |
expected = { | |
'a': [Decimal("1"), Decimal("1.45"), Decimal("-23.456"), None], | |
} | |
for type_factory in (pa.decimal128, pa.decimal256): | |
schema = pa.schema([('a', type_factory(9, 4))]) | |
opts = ParseOptions(explicit_schema=schema) | |
table = self.read_bytes(rows, parse_options=opts) | |
assert table.schema == schema | |
assert table.to_pydict() == expected | |
def test_explicit_schema_with_unexpected_behaviour(self): | |
# infer by default | |
rows = (b'{"foo": "bar", "num": 0}\n' | |
b'{"foo": "baz", "num": 1}\n') | |
schema = pa.schema([ | |
('foo', pa.binary()) | |
]) | |
opts = ParseOptions(explicit_schema=schema) | |
table = self.read_bytes(rows, parse_options=opts) | |
assert table.schema == pa.schema([ | |
('foo', pa.binary()), | |
('num', pa.int64()) | |
]) | |
assert table.to_pydict() == { | |
'foo': [b'bar', b'baz'], | |
'num': [0, 1], | |
} | |
# ignore the unexpected fields | |
opts = ParseOptions(explicit_schema=schema, | |
unexpected_field_behavior="ignore") | |
table = self.read_bytes(rows, parse_options=opts) | |
assert table.schema == pa.schema([ | |
('foo', pa.binary()), | |
]) | |
assert table.to_pydict() == { | |
'foo': [b'bar', b'baz'], | |
} | |
# raise error | |
opts = ParseOptions(explicit_schema=schema, | |
unexpected_field_behavior="error") | |
with pytest.raises(pa.ArrowInvalid, | |
match="JSON parse error: unexpected field"): | |
self.read_bytes(rows, parse_options=opts) | |
def test_small_random_json(self): | |
data, expected = make_random_json(num_cols=2, num_rows=10) | |
table = self.read_bytes(data) | |
assert table.schema == expected.schema | |
assert table.equals(expected) | |
assert table.to_pydict() == expected.to_pydict() | |
def test_load_large_json(self): | |
data, expected = make_random_json(num_cols=2, num_rows=100100) | |
# set block size is 10MB | |
read_options = ReadOptions(block_size=1024*1024*10) | |
table = self.read_bytes(data, read_options=read_options) | |
assert table.num_rows == 100100 | |
assert expected.num_rows == 100100 | |
def test_stress_block_sizes(self): | |
# Test a number of small block sizes to stress block stitching | |
data_base, expected = make_random_json(num_cols=2, num_rows=100) | |
read_options = ReadOptions() | |
parse_options = ParseOptions() | |
for data in [data_base, data_base.rstrip(b'\r\n')]: | |
for newlines_in_values in [False, True]: | |
parse_options.newlines_in_values = newlines_in_values | |
for block_size in [22, 23, 37]: | |
read_options.block_size = block_size | |
table = self.read_bytes(data, read_options=read_options, | |
parse_options=parse_options) | |
assert table.schema == expected.schema | |
if not table.equals(expected): | |
# Better error output | |
assert table.to_pydict() == expected.to_pydict() | |
class TestSerialJSONRead(BaseTestJSONRead, unittest.TestCase): | |
def read_json(self, *args, **kwargs): | |
read_options = kwargs.setdefault('read_options', ReadOptions()) | |
read_options.use_threads = False | |
table = read_json(*args, **kwargs) | |
table.validate(full=True) | |
return table | |
class TestParallelJSONRead(BaseTestJSONRead, unittest.TestCase): | |
def read_json(self, *args, **kwargs): | |
read_options = kwargs.setdefault('read_options', ReadOptions()) | |
read_options.use_threads = True | |
table = read_json(*args, **kwargs) | |
table.validate(full=True) | |
return table | |