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b03b85560632c7d285f2936c1fc7df527781f42d
| 2,100 |
py
|
Python
|
scripts/scraper.py
|
jhKessler/Tagesschau-Analysis
|
40490b13fa2f3e5cf3bd4b5f4f46b5bf72ab9899
|
[
"MIT"
] | null | null | null |
scripts/scraper.py
|
jhKessler/Tagesschau-Analysis
|
40490b13fa2f3e5cf3bd4b5f4f46b5bf72ab9899
|
[
"MIT"
] | null | null | null |
scripts/scraper.py
|
jhKessler/Tagesschau-Analysis
|
40490b13fa2f3e5cf3bd4b5f4f46b5bf72ab9899
|
[
"MIT"
] | null | null | null |
#
# scraper for getting the data from article descriptions
#
import time
import datetime
import requests
import pandas as pd
from tqdm import tqdm
from bs4 import BeautifulSoup
DATE_FORMAT = "%d/%m/%Y"
ARCHIVE_URL = "https://www.tagesschau.de/multimedia/video/videoarchiv2~_date-"
SECOND_DELAY = 1
# dates
first_description = datetime.date(year=2013, month=4, day=22)
today = datetime.date.today()
current_date = first_description
# list for storing articles
all_articles = []
def update_progress_bar(pbar: tqdm, current_date: datetime.datetime) -> None:
"""Update Progress bar"""
pbar.update(1)
estimated_time = round(((today - current_date).days * (SECOND_DELAY+0.3)) / 60)
pbar.set_description(f"Scraping articles: Date:{current_date.strftime(DATE_FORMAT)}, Articles: {len(all_articles)}, Estimated time left: {round(estimated_time, 2)} min")
# init progressbar
total_days = (today - first_description).days
print(total_days)
progress_bar = tqdm(total=total_days)
update_progress_bar(progress_bar, current_date)
# loop over days
while current_date <= today:
date_string = current_date.strftime("%Y%m%d")
# format url to right form
url_string = f"{ARCHIVE_URL}{date_string}.html"
# request html and scrape it for the datapoints
response = requests.get(url_string).text
soup = BeautifulSoup(response, 'html.parser')
# save articles
article_teasers = list(soup.findAll(class_="teasertext"))
titles = soup.findAll(class_="headline")
dates_and_times = list(soup.findAll(class_="dachzeile"))
for title, date_and_time, article, in zip(titles, dates_and_times, article_teasers):
all_articles.append([current_date.strftime(DATE_FORMAT), article.text, title.text, date_and_time.text])
# go to next day
current_date = current_date + datetime.timedelta(days=1)
# sleep
time.sleep(SECOND_DELAY)
update_progress_bar(progress_bar, current_date)
# format data
article_df = pd.DataFrame(all_articles, columns=["date", "article", "title", "time_text"])
article_df.to_excel("data/raw.xlsx", index=False)
| 32.307692 | 173 | 0.739524 |
afd6664432eb837b50bee769a174cb19c16d821f
| 329 |
py
|
Python
|
server/bumf/api/views/auth.py
|
bumfiness/bumf
|
71c404c0a8f804b8f0e127df3de6d8916db4c660
|
[
"Apache-2.0"
] | 6 |
2017-01-07T17:59:46.000Z
|
2017-02-10T13:19:46.000Z
|
server/bumf/api/views/auth.py
|
rixx/bumf
|
71c404c0a8f804b8f0e127df3de6d8916db4c660
|
[
"Apache-2.0"
] | null | null | null |
server/bumf/api/views/auth.py
|
rixx/bumf
|
71c404c0a8f804b8f0e127df3de6d8916db4c660
|
[
"Apache-2.0"
] | null | null | null |
from rest_framework import mixins, permissions, viewsets
from bumf.api.serializers import UserSerializer
from bumf.core.models import User
class UserView(mixins.CreateModelMixin, viewsets.GenericViewSet):
queryset = User.objects.none()
permission_classes = [permissions.AllowAny]
serializer_class = UserSerializer
| 29.909091 | 65 | 0.808511 |
a566fd8c43c862cab7e4250aec18c8b8495f8ba7
| 84 |
py
|
Python
|
Python/if-else.py
|
bunny8469/Hello-World
|
722b5961cbcd9b2c2eec2cb6aa700eaa451e008b
|
[
"MIT"
] | 133 |
2021-01-15T16:29:40.000Z
|
2022-03-21T16:35:42.000Z
|
Python/if-else.py
|
bunny8469/Hello-World
|
722b5961cbcd9b2c2eec2cb6aa700eaa451e008b
|
[
"MIT"
] | 117 |
2021-01-17T08:54:22.000Z
|
2022-01-17T16:38:11.000Z
|
Python/if-else.py
|
bunny8469/Hello-World
|
722b5961cbcd9b2c2eec2cb6aa700eaa451e008b
|
[
"MIT"
] | 146 |
2021-01-15T12:57:19.000Z
|
2022-03-15T20:10:23.000Z
|
t=int(input())
if t>=1:
print("bigger than 1")
else:
print("smaller than 1")
| 16.8 | 27 | 0.595238 |
a57d7dab18bdfa799114ea56df3d758834aa2120
| 407 |
py
|
Python
|
setup.py
|
raicheff/flask-spf
|
abfeb35bde6235be80aacdfdcfce71f40421ed91
|
[
"MIT"
] | null | null | null |
setup.py
|
raicheff/flask-spf
|
abfeb35bde6235be80aacdfdcfce71f40421ed91
|
[
"MIT"
] | null | null | null |
setup.py
|
raicheff/flask-spf
|
abfeb35bde6235be80aacdfdcfce71f40421ed91
|
[
"MIT"
] | null | null | null |
#
# Flask-SPF
#
# Copyright (C) 2017 Boris Raicheff
# All rights reserved
#
from setuptools import find_packages, setup
setup(
name='Flask-SPF',
version='0.1.0',
description='Flask-SPF',
author='Boris Raicheff',
author_email='[email protected]',
url='https://github.com/raicheff/flask-spf',
install_requires=('flask', 'beautifulsoup4'),
py_modules=('flask_spf',),
)
# EOF
| 16.28 | 49 | 0.660934 |
3cef0e52a2048eb5b25bb85af93f0adab276a41b
| 631 |
py
|
Python
|
finbyz_dashboard/finbyz_dashboard/dashboard_overrides/install_fixtures.py
|
finbyz/finbyz_dashboard
|
9c58ab7bccf589bc010d0e5bf95b20cadd4d71f0
|
[
"MIT"
] | 1 |
2021-11-19T05:27:11.000Z
|
2021-11-19T05:27:11.000Z
|
finbyz_dashboard/finbyz_dashboard/dashboard_overrides/install_fixtures.py
|
finbyz/finbyz_dashboard
|
9c58ab7bccf589bc010d0e5bf95b20cadd4d71f0
|
[
"MIT"
] | null | null | null |
finbyz_dashboard/finbyz_dashboard/dashboard_overrides/install_fixtures.py
|
finbyz/finbyz_dashboard
|
9c58ab7bccf589bc010d0e5bf95b20cadd4d71f0
|
[
"MIT"
] | 2 |
2021-08-21T10:41:38.000Z
|
2021-11-19T05:27:13.000Z
|
# Copyright (c) 2015, Frappe Technologies Pvt. Ltd. and Contributors
# License: GNU General Public License v3. See license.txt
from __future__ import unicode_literals
import frappe
from frappe import _
from frappe.desk.doctype.global_search_settings.global_search_settings import update_global_search_doctypes
# Finbyz CHanges Import
from finbyz_dashboard.finbyz_dashboard.dashboard_overrides.dashboard_utils import sync_dashboards
def install():
update_genders()
update_salutations()
update_global_search_doctypes()
setup_email_linking()
# Finbyz CHanges START
sync_dashboards()
# Finbyz CHanges END
add_unsubscribe()
| 30.047619 | 107 | 0.835182 |
055dbd21f9914f317100d134cb4bb20c0c841ad9
| 14,731 |
py
|
Python
|
official/cv/fastscnn/infer/sdk/main.py
|
leelige/mindspore
|
5199e05ba3888963473f2b07da3f7bca5b9ef6dc
|
[
"Apache-2.0"
] | 77 |
2021-10-15T08:32:37.000Z
|
2022-03-30T13:09:11.000Z
|
official/cv/fastscnn/infer/sdk/main.py
|
leelige/mindspore
|
5199e05ba3888963473f2b07da3f7bca5b9ef6dc
|
[
"Apache-2.0"
] | 3 |
2021-10-30T14:44:57.000Z
|
2022-02-14T06:57:57.000Z
|
official/cv/fastscnn/infer/sdk/main.py
|
leelige/mindspore
|
5199e05ba3888963473f2b07da3f7bca5b9ef6dc
|
[
"Apache-2.0"
] | 24 |
2021-10-15T08:32:45.000Z
|
2022-03-24T18:45:20.000Z
|
'''
The scripts to execute sdk infer
'''
# Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed 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.
# ============================================================================
import argparse
import os
import time
import numpy as np
import PIL.Image as Image
from tabulate import tabulate
import MxpiDataType_pb2 as MxpiDataType
from StreamManagerApi import StreamManagerApi, InProtobufVector, \
MxProtobufIn, StringVector
def parse_args():
"""set and check parameters."""
parser = argparse.ArgumentParser(description="FastSCNN process")
parser.add_argument("--pipeline", type=str, default=None, help="SDK infer pipeline")
parser.add_argument("--image_path", type=str, default=None, help="root path of image")
parser.add_argument('--image_width', default=768, type=int, help='image width')
parser.add_argument('--image_height', default=768, type=int, help='image height')
parser.add_argument('--save_mask', default=1, type=int, help='0 for False, 1 for True')
parser.add_argument('--mask_result_path', default='./mask_result', type=str,
help='the folder to save the semantic mask images')
args_opt = parser.parse_args()
return args_opt
def send_source_data(appsrc_id, tensor, stream_name, stream_manager):
"""
Construct the input of the stream,
send inputs data to a specified stream based on streamName.
Returns:
bool: send data success or not
"""
tensor_package_list = MxpiDataType.MxpiTensorPackageList()
tensor_package = tensor_package_list.tensorPackageVec.add()
array_bytes = tensor.tobytes()
tensor_vec = tensor_package.tensorVec.add()
tensor_vec.deviceId = 0
tensor_vec.memType = 0
for i in tensor.shape:
tensor_vec.tensorShape.append(i)
tensor_vec.dataStr = array_bytes
tensor_vec.tensorDataSize = len(array_bytes)
key = "appsrc{}".format(appsrc_id).encode('utf-8')
protobuf_vec = InProtobufVector()
protobuf = MxProtobufIn()
protobuf.key = key
protobuf.type = b'MxTools.MxpiTensorPackageList'
protobuf.protobuf = tensor_package_list.SerializeToString()
protobuf_vec.push_back(protobuf)
ret = stream_manager.SendProtobuf(stream_name, appsrc_id, protobuf_vec)
if ret < 0:
print("Failed to send data to stream.")
return False
return True
cityspallete = [
128, 64, 128,
244, 35, 232,
70, 70, 70,
102, 102, 156,
190, 153, 153,
153, 153, 153,
250, 170, 30,
220, 220, 0,
107, 142, 35,
152, 251, 152,
0, 130, 180,
220, 20, 60,
255, 0, 0,
0, 0, 142,
0, 0, 70,
0, 60, 100,
0, 80, 100,
0, 0, 230,
119, 11, 32,
]
classes = ('road', 'sidewalk', 'building', 'wall', 'fence', 'pole', 'traffic light',
'traffic sign', 'vegetation', 'terrain', 'sky', 'person', 'rider', 'car',
'truck', 'bus', 'train', 'motorcycle', 'bicycle')
valid_classes = [7, 8, 11, 12, 13, 17, 19, 20, 21, 22,
23, 24, 25, 26, 27, 28, 31, 32, 33]
_key = np.array([-1, -1, -1, -1, -1, -1,
-1, -1, 0, 1, -1, -1,
2, 3, 4, -1, -1, -1,
5, -1, 6, 7, 8, 9,
10, 11, 12, 13, 14, 15,
-1, -1, 16, 17, 18])
_mapping = np.array(range(-1, len(_key) - 1)).astype('int32')
def _get_city_pairs(folder, split='train'):
'''_get_city_pairs'''
def get_path_pairs(img_folder, mask_folder):
img_paths = []
mask_paths = []
for root, _, files in os.walk(img_folder):
for filename in files:
if filename.startswith('._'):
continue
if filename.endswith('.png'):
imgpath = os.path.join(root, filename)
foldername = os.path.basename(os.path.dirname(imgpath))
maskname = filename.replace('leftImg8bit', 'gtFine_labelIds')
maskpath = os.path.join(mask_folder, foldername, maskname)
if os.path.isfile(imgpath) and os.path.isfile(maskpath):
img_paths.append(imgpath)
mask_paths.append(maskpath)
else:
print('cannot find the mask or image:', imgpath, maskpath)
print('Found {} images in the folder {}'.format(len(img_paths), img_folder))
return img_paths, mask_paths
if split in ('train', 'val'):
img_folder = os.path.join(folder, 'leftImg8bit' + os.sep + split)
mask_folder = os.path.join(folder, 'gtFine' + os.sep + split)
img_paths, mask_paths = get_path_pairs(img_folder, mask_folder)
return img_paths, mask_paths
assert split == 'trainval'
print('trainval set')
train_img_folder = os.path.join(folder, 'leftImg8bit' + os.sep + 'train')
train_mask_folder = os.path.join(folder, 'gtFine' + os.sep + 'train')
val_img_folder = os.path.join(folder, 'leftImg8bit' + os.sep + 'val')
val_mask_folder = os.path.join(folder, 'gtFine' + os.sep + 'val')
train_img_paths, train_mask_paths = get_path_pairs(train_img_folder, train_mask_folder)
val_img_paths, val_mask_paths = get_path_pairs(val_img_folder, val_mask_folder)
img_paths = train_img_paths + val_img_paths
mask_paths = train_mask_paths + val_mask_paths
return img_paths, mask_paths
def _val_sync_transform(outsize, img, mask):
'''_val_sync_transform'''
short_size = min(outsize)
w, h = img.size
if w > h:
oh = short_size
ow = int(1.0 * w * oh / h)
else:
ow = short_size
oh = int(1.0 * h * ow / w)
img = img.resize((ow, oh), Image.BILINEAR)
mask = mask.resize((ow, oh), Image.NEAREST)
# center crop
w, h = img.size
x1 = int(round((w - outsize[1]) / 2.))
y1 = int(round((h - outsize[0]) / 2.))
img = img.crop((x1, y1, x1 + outsize[1], y1 + outsize[0]))
mask = mask.crop((x1, y1, x1 + outsize[1], y1 + outsize[0]))
# final transform
img, mask = np.array(img), _mask_transform(mask)
return img, mask
def _class_to_index(mask):
# assert the value
values = np.unique(mask)
for value in values:
assert value in _mapping
index = np.digitize(mask.ravel(), _mapping, right=True)
return _key[index].reshape(mask.shape)
def _mask_transform(mask):
target = _class_to_index(np.array(mask).astype('int32'))
return np.array(target).astype('int32')
class SegmentationMetric():
"""Computes pixAcc and mIoU metric scores
"""
def __init__(self, nclass):
super(SegmentationMetric, self).__init__()
self.nclass = nclass
self.reset()
def update(self, preds, labels):
"""Updates the internal evaluation result.
Parameters
----------
labels : 'NumpyArray' or list of `NumpyArray`
The labels of the data.
preds : 'NumpyArray' or list of `NumpyArray`
Predicted values.
"""
def evaluate_worker(self, pred, label):
correct, labeled = batch_pix_accuracy(pred, label)
inter, union = batch_intersection_union(pred, label, self.nclass)
self.total_correct += correct
self.total_label += labeled
self.total_inter += inter
self.total_union += union
evaluate_worker(self, preds, labels)
def get(self, return_category_iou=False):
"""Gets the current evaluation result.
Returns
-------
metrics : tuple of float
pixAcc and mIoU
"""
# remove np.spacing(1)
pixAcc = 1.0 * self.total_correct / (2.220446049250313e-16 + self.total_label)
IoU = 1.0 * self.total_inter / (2.220446049250313e-16 + self.total_union)
mIoU = IoU.mean().item()
if return_category_iou:
return pixAcc, mIoU, IoU
return pixAcc, mIoU
def reset(self):
"""Resets the internal evaluation result to initial state."""
self.total_inter = np.zeros(self.nclass)
self.total_union = np.zeros(self.nclass)
self.total_correct = 0
self.total_label = 0
def batch_pix_accuracy(output, target):
"""PixAcc"""
# inputs are numpy array, output 4D NCHW where 'C' means label classes, target 3D NHW
predict = np.argmax(output.astype(np.int64), 1) + 1
target = target.astype(np.int64) + 1
pixel_labeled = (target > 0).sum()
pixel_correct = ((predict == target) * (target > 0)).sum()
assert pixel_correct <= pixel_labeled, "Correct area should be smaller than Labeled"
return pixel_correct, pixel_labeled
def batch_intersection_union(output, target, nclass):
"""mIoU"""
# inputs are numpy array, output 4D, target 3D
mini = 1
maxi = nclass
nbins = nclass
predict = np.argmax(output.astype(np.float32), 1) + 1
target = target.astype(np.float32) + 1
predict = predict.astype(np.float32) * (target > 0).astype(np.float32)
intersection = predict * (predict == target).astype(np.float32)
# areas of intersection and union
# element 0 in intersection occur the main difference from np.bincount. set boundary to -1 is necessary.
area_inter, _ = np.histogram(intersection, bins=nbins, range=(mini, maxi))
area_pred, _ = np.histogram(predict, bins=nbins, range=(mini, maxi))
area_lab, _ = np.histogram(target, bins=nbins, range=(mini, maxi))
area_union = area_pred + area_lab - area_inter
assert (area_inter > area_union).sum() == 0, "Intersection area should be smaller than Union area"
return area_inter.astype(np.float32), area_union.astype(np.float32)
def main():
"""
read pipeline and do infer
"""
args = parse_args()
# init stream manager
stream_manager_api = StreamManagerApi()
ret = stream_manager_api.InitManager()
if ret != 0:
print("Failed to init Stream manager, ret=%s" % str(ret))
return
# create streams by pipeline config file
with open(os.path.realpath(args.pipeline), 'rb') as f:
pipeline_str = f.read()
ret = stream_manager_api.CreateMultipleStreams(pipeline_str)
if ret != 0:
print("Failed to create Stream, ret=%s" % str(ret))
return
stream_name = b'fastscnn'
infer_total_time = 0
assert os.path.exists(args.image_path), "Please put dataset in " + str(args.image_path)
images, mask_paths = _get_city_pairs(args.image_path, 'val')
assert len(images) == len(mask_paths)
if not images:
raise RuntimeError("Found 0 images in subfolders of:" + args.image_path + "\n")
if args.save_mask and not os.path.exists(args.mask_result_path):
os.makedirs(args.mask_result_path)
metric = SegmentationMetric(19)
metric.reset()
for index in range(len(images)):
image_name = images[index].split(os.sep)[-1].split(".")[0] # get the name of image file
print("Processing ---> ", image_name)
img = Image.open(images[index]).convert('RGB')
mask = Image.open(mask_paths[index])
img, mask = _val_sync_transform((args.image_height, args.image_width), img, mask)
img = img.astype(np.float32)
mask = mask.astype(np.int32)
mean = [0.485, 0.456, 0.406]
std = [0.229, 0.224, 0.225]
img = img.transpose((2, 0, 1))#HWC->CHW
for channel, _ in enumerate(img):
# Normalization
img[channel] /= 255
img[channel] -= mean[channel]
img[channel] /= std[channel]
img = np.expand_dims(img, 0)#NCHW
mask = np.expand_dims(mask, 0)#NHW
if not send_source_data(0, img, stream_name, stream_manager_api):
return
# Obtain the inference result by specifying streamName and uniqueId.
key_vec = StringVector()
key_vec.push_back(b'modelInfer')
start_time = time.time()
infer_result = stream_manager_api.GetProtobuf(stream_name, 0, key_vec)
infer_total_time += time.time() - start_time
if infer_result.size() == 0:
print("inferResult is null")
return
if infer_result[0].errorCode != 0:
print("GetProtobuf error. errorCode=%d" % (infer_result[0].errorCode))
return
result = MxpiDataType.MxpiTensorPackageList()
result.ParseFromString(infer_result[0].messageBuf)
res = np.frombuffer(result.tensorPackageVec[0].tensorVec[0].dataStr, dtype='<f4')
mask_image = res.reshape(1, 19, args.image_height, args.image_width)
metric.update(mask_image, mask)
pixAcc, mIoU = metric.get()
print("[EVAL] Sample: {:d}, pixAcc: {:.3f}, mIoU: {:.3f}".format(index + 1, pixAcc * 100, mIoU * 100))
if args.save_mask:
output = np.argmax(mask_image[0], axis=0)
out_img = Image.fromarray(output.astype('uint8'))
out_img.putpalette(cityspallete)
outname = str(image_name) + '.png'
out_img.save(os.path.join(args.mask_result_path, outname))
pixAcc, mIoU, category_iou = metric.get(return_category_iou=True)
print('End validation pixAcc: {:.3f}, mIoU: {:.3f}'.format(pixAcc * 100, mIoU * 100))
txtName = os.path.join(args.mask_result_path, "eval_results.txt")
with open(txtName, "w") as f:
string = 'validation pixAcc:' + str(pixAcc * 100) + ', mIoU:' + str(mIoU * 100)
f.write(string)
f.write('\n')
headers = ['class id', 'class name', 'iou']
table = []
for i, cls_name in enumerate(classes):
table.append([cls_name, category_iou[i]])
string = 'class name: ' + cls_name + ' iou: ' + str(category_iou[i]) + '\n'
f.write(string)
print('Category iou: \n {}'.format(tabulate(table, headers, \
tablefmt='grid', showindex="always", numalign='center', stralign='center')))
print("Testing finished....")
print("=======================================")
print("The total time of inference is {} s".format(infer_total_time))
print("=======================================")
# destroy streams
stream_manager_api.DestroyAllStreams()
if __name__ == '__main__':
main()
| 39.282667 | 110 | 0.621003 |
f93f27538f5cdd1b46073b7e5bfef848372aeb0c
| 6,498 |
py
|
Python
|
fahrplanauskunft-vvs.py
|
wienand/fahrplanauskunft-vvs
|
ca595e2f51af1d00ea8db463d9fc3390c51c5741
|
[
"MIT"
] | 1 |
2018-11-27T15:31:40.000Z
|
2018-11-27T15:31:40.000Z
|
fahrplanauskunft-vvs.py
|
wienand/fahrplanauskunft-vvs
|
ca595e2f51af1d00ea8db463d9fc3390c51c5741
|
[
"MIT"
] | null | null | null |
fahrplanauskunft-vvs.py
|
wienand/fahrplanauskunft-vvs
|
ca595e2f51af1d00ea8db463d9fc3390c51c5741
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
import collections
import datetime
import json
import os
import urllib
from flask import Flask, request
port = int(os.environ.get("PORT", 5000))
runsAtHeroku = port != 5000
app = Flask(__name__)
@app.route('/', methods=['GET', 'POST'])
def queryVVS():
intent = request.json['request']['intent']
slots = {key.lower(): data['value'] for key, data in intent['slots'].items() if 'value' in data}
if intent['name'] == 'GetDepartures':
result = getDepartures(**slots)
elif intent['name'] == 'GetConnection':
result = getConnection(**slots)
return json.dumps(result)
def getConnection(source='Am Kriegsbergturm', target='Hauptbahnhof', time=None, date=None):
url = 'http://mobil.vvs.de/jqm/controller/XSLT_TRIP_REQUEST2?outputFormat=JSON&type_destination=stop&type_origin=stop&useRealtime=1&name_origin=%s&name_destination=%s' \
% (urllib.quote_plus(source.encode('utf8')), urllib.quote_plus(target.encode('utf8')))
if time:
url += '&itdTime=%s' % time.replace(':', '')
if date:
url += '&itdDate=%s' % date.replace('-', '')
response = urllib.urlopen(url)
response = json.loads(response.read().decode('latin1'))
trips = []
now = datetime.datetime.now()
for trip in response['trips'] or []:
hours, minutes = (int(x) for x in trip['duration'].split(':'))
tripText = 'Fahrzeit'
if hours:
tripText += ' %d Stunden und' % hours
tripText += ' %d Minuten' % minutes
interchanges = int(trip['interchange'])
if interchanges:
if interchanges == 1:
tripText += ' bei einem Umstieg'
else:
tripText += ' bei %d Umstiegen' % interchanges
firstLeg = True
for leg in trip['legs']:
if firstLeg:
firstLeg = False
dateTime = leg['points'][0]['dateTime']
departureTime = datetime.datetime.strptime(dateTime.get('rtDate', dateTime['date']) + ' ' + dateTime.get('rtTime', dateTime['time']), '%d.%m.%Y %H:%M')
minutesTillDeparture = (departureTime - now).total_seconds() / 60
if runsAtHeroku:
minutesTillDeparture -= 60
if minutesTillDeparture < 0.5 or minutesTillDeparture > 60:
tripText += ' mit %s in Richtung %s ab %s Uhr bis %s' % (leg['mode']['name'], leg['mode']['destination'].split(' (')[0], dateTime.get('rtTime', dateTime['time']), leg['points'][-1]['name'])
elif minutesTillDeparture > 0.5:
tripText += ' mit %s in Richtung %s in %d Minuten bis %s' % (leg['mode']['name'], leg['mode']['destination'].split(' (')[0], minutesTillDeparture, leg['points'][-1]['name'])
else:
dateTime = leg['points'][0]['dateTime']
departureTime = datetime.datetime.strptime(dateTime.get('rtDate', dateTime['date']) + ' ' + dateTime.get('rtTime', dateTime['time']), '%d.%m.%Y %H:%M')
minutesForInterchange = (departureTime - lastArrivalTime).total_seconds() / 60
tripText += ', dann in %d Minuten umsteigen in %s Richtung %s bis %s' % (minutesForInterchange, leg['mode']['name'], leg['mode']['destination'].split(' (')[0], leg['points'][-1]['name'])
dateTime = leg['points'][-1]['dateTime']
lastArrivalTime = datetime.datetime.strptime(dateTime.get('rtDate', dateTime['date']) + ' ' + dateTime.get('rtTime', dateTime['time']), '%d.%m.%Y %H:%M')
trips.append(tripText)
result = {
"version" : "1.0",
"sessionAttributes": {},
"response" : {
"outputSpeech" : {
"type": "PlainText",
"text": ". ".join(trips)
},
"shouldEndSession": True
}
}
return result
def getDepartures(stop='Am Kriegsbergturm', time=None, date=None):
url = 'http://mobile.vvs.de/jqm/controller/XSLT_DM_REQUEST?limit=20&mode=direct&type_dm=stop&useRealtime=1&outputFormat=JSON&name_dm=%s' % stop
if time:
url += '&itdTime=%s' % time.replace(':', '')
if date:
url += '&itdDate=%s' % date.replace('-', '')
response = urllib.urlopen(url)
response = json.loads(response.read().decode('latin1'))
departures = collections.defaultdict(list)
for departure in response['departureList'] or []:
departures[(departure['servingLine']['name'], departure['servingLine']['number'], departure['servingLine']['direction'].split(' (')[0])].append(departure)
parts = []
now = datetime.datetime.now()
for (name, tag, direction), departureList in departures.items():
minutes = []
times = []
for departure in departureList:
departureTime = departure.get('realDateTime', departure['dateTime'])
departureTime = {key: int(departureTime[key]) for key in ('hour', 'month', 'year', 'day', 'minute')}
minutesTillDeparture = (datetime.datetime(**departureTime) - now).total_seconds() / 60
if runsAtHeroku:
minutesTillDeparture -= 60
if minutesTillDeparture < 0.5 or minutesTillDeparture > 60:
times += ['%d:%02d' % (departureTime['hour'], departureTime['minute'])]
elif minutesTillDeparture > 0.5:
minutes += ['%d' % minutesTillDeparture]
if len(minutes) + len(times) > 2:
break
if len(minutes) > 1:
minutes = ', '.join(minutes[:-1]) + ' und ' + minutes[-1]
else:
minutes = ''.join(minutes)
if len(times) > 1:
times = ', '.join(times[:-1]) + ' und ' + times[-1]
else:
times = ''.join(times)
part = '%s %s Richtung %s ' % (name, tag, direction)
if minutes:
part += "in %s Minuten" % minutes
if times:
if minutes:
part += ' und '
part += "um %s Uhr" % times
parts.append(part)
result = {
"version" : "1.0",
"sessionAttributes": {},
"response" : {
"outputSpeech" : {
"type": "PlainText",
"text": " und ".join(parts)
},
"shouldEndSession": True
}
}
return result
if __name__ == '__main__':
if runsAtHeroku:
app.run(host='0.0.0.0', port=port)
else:
app.run(debug=True)
| 43.905405 | 209 | 0.554786 |
fd25ba81163d883a65a07de03662e866968a9ede
| 57 |
py
|
Python
|
Python/Books/Learning-Programming-with-Python.Tamim-Shahriar-Subeen/chapter-005/pg-5.1-check-turtle.py
|
shihab4t/Books-Code
|
b637b6b2ad42e11faf87d29047311160fe3b2490
|
[
"Unlicense"
] | null | null | null |
Python/Books/Learning-Programming-with-Python.Tamim-Shahriar-Subeen/chapter-005/pg-5.1-check-turtle.py
|
shihab4t/Books-Code
|
b637b6b2ad42e11faf87d29047311160fe3b2490
|
[
"Unlicense"
] | null | null | null |
Python/Books/Learning-Programming-with-Python.Tamim-Shahriar-Subeen/chapter-005/pg-5.1-check-turtle.py
|
shihab4t/Books-Code
|
b637b6b2ad42e11faf87d29047311160fe3b2490
|
[
"Unlicense"
] | null | null | null |
import turtle
turtle.forward(100)
turtle.exitonclick()
| 9.5 | 20 | 0.789474 |
fd308d7dbc333d082e34f58aff0ed51ad0791375
| 439 |
py
|
Python
|
exercises/pt/test_02_02_01.py
|
tuanducdesign/spacy-course
|
f8d092c5fa2997fccb3f367d174dce8667932b3d
|
[
"MIT"
] | null | null | null |
exercises/pt/test_02_02_01.py
|
tuanducdesign/spacy-course
|
f8d092c5fa2997fccb3f367d174dce8667932b3d
|
[
"MIT"
] | null | null | null |
exercises/pt/test_02_02_01.py
|
tuanducdesign/spacy-course
|
f8d092c5fa2997fccb3f367d174dce8667932b3d
|
[
"MIT"
] | null | null | null |
def test():
assert gato_hash == nlp.vocab.strings["gato"], "Você atribuiu o código hash corretamente?"
assert 'nlp.vocab.strings["gato"]' in __solution__, "Você selecionou a string corretamente?"
assert gato_string == "gato", "Você selecionou a string corretamente?"
assert (
"nlp.vocab.strings[gato_hash]" in __solution__
), "Você obteve a string a partir do código hash?"
__msg__.good("Ótimo trabalho!")
| 43.9 | 96 | 0.697039 |
bd2ef38a0612241d1de44edb38334800ba3dd48e
| 251 |
py
|
Python
|
Chapter2_Python/01-Variables.py
|
olebause/TensorFlow2
|
70fcb7c85c7ead0dc4f88ffa35be5f2eb93e618e
|
[
"MIT"
] | 11 |
2020-10-12T14:06:31.000Z
|
2022-02-22T09:16:32.000Z
|
Chapter2_Basics/Variables.py
|
franneck94/UdemyPythonIntro
|
4895a91a04eedce7d59b61bf12e5aa209fe60f85
|
[
"MIT"
] | 1 |
2020-12-21T15:29:20.000Z
|
2022-01-15T12:06:09.000Z
|
Chapter2_Basics/Variables.py
|
franneck94/UdemyPythonIntro
|
4895a91a04eedce7d59b61bf12e5aa209fe60f85
|
[
"MIT"
] | 8 |
2020-10-29T07:53:49.000Z
|
2022-03-17T11:01:20.000Z
|
# 1. var names cannot contain whitespaces
# 2. var names cannot start with a number
my_age = 27 # int
price = 0.5 # float
my_name_is_jan = True # bool
my_name_is_peter = False # bool
my_name = "Jan Schaffranek" # str
print(my_age)
print(price)
| 20.916667 | 41 | 0.713147 |
2f9999fb7e0a0ffa1363366f7c683a7fee0c73f2
| 240 |
py
|
Python
|
exercises/pt/solution_03_03.py
|
tuanducdesign/spacy-course
|
f8d092c5fa2997fccb3f367d174dce8667932b3d
|
[
"MIT"
] | null | null | null |
exercises/pt/solution_03_03.py
|
tuanducdesign/spacy-course
|
f8d092c5fa2997fccb3f367d174dce8667932b3d
|
[
"MIT"
] | null | null | null |
exercises/pt/solution_03_03.py
|
tuanducdesign/spacy-course
|
f8d092c5fa2997fccb3f367d174dce8667932b3d
|
[
"MIT"
] | null | null | null |
import spacy
# Carregue o fluxo de procesamento en_core_web_sm
nlp = spacy.load("pt_core_news_sm")
# Imprima o nome dos componentes do fluxo
print(nlp.pipe_names)
# Imprima as informações das tuplas (name, component)
print(nlp.pipeline)
| 21.818182 | 53 | 0.7875 |
f1b47f048a9998081bfd0ddeb605e84241c854d2
| 330 |
py
|
Python
|
pusta2/config.py
|
EE/flexdb
|
08a80b9e56201e678ef055af27bdefa6d52bcbf5
|
[
"MIT"
] | null | null | null |
pusta2/config.py
|
EE/flexdb
|
08a80b9e56201e678ef055af27bdefa6d52bcbf5
|
[
"MIT"
] | null | null | null |
pusta2/config.py
|
EE/flexdb
|
08a80b9e56201e678ef055af27bdefa6d52bcbf5
|
[
"MIT"
] | null | null | null |
app_name = "pusta2"
prefix_url = "pusta2"
static_files = {
'js': {
'pusta2/js/': ['main.js', ]
},
'css': {
'pusta2/css/': ['main.css', ]
},
'html': {
'pusta2/html/': ['index.html', ]
}
}
permissions = {
"edit": "Editing actualy nothing.",
"sample1": "sample1longversion",
}
| 18.333333 | 40 | 0.487879 |
7b075b0059651433f0f15cf456c5036b91957e78
| 38 |
py
|
Python
|
Python/Books/Learning-Programming-with-Python.Tamim-Shahriar-Subeen/chapter-006/ph-6.16-list-with-maltiple-range.py
|
shihab4t/Books-Code
|
b637b6b2ad42e11faf87d29047311160fe3b2490
|
[
"Unlicense"
] | null | null | null |
Python/Books/Learning-Programming-with-Python.Tamim-Shahriar-Subeen/chapter-006/ph-6.16-list-with-maltiple-range.py
|
shihab4t/Books-Code
|
b637b6b2ad42e11faf87d29047311160fe3b2490
|
[
"Unlicense"
] | null | null | null |
Python/Books/Learning-Programming-with-Python.Tamim-Shahriar-Subeen/chapter-006/ph-6.16-list-with-maltiple-range.py
|
shihab4t/Books-Code
|
b637b6b2ad42e11faf87d29047311160fe3b2490
|
[
"Unlicense"
] | null | null | null |
li = list(range(2, 21, 2))
print(li)
| 9.5 | 26 | 0.578947 |
c8a7cac846d8b813597b47640cc31911b8185e4a
| 3,308 |
py
|
Python
|
projekte_ss2017/Minensuche_Benjamin/field.py
|
krother/python_abv_zedat
|
1e2e1fe16da6612c470f06f519cd053c567e0611
|
[
"MIT"
] | 1 |
2019-03-04T20:09:26.000Z
|
2019-03-04T20:09:26.000Z
|
projekte_ss2017/Minensuche_Benjamin/field.py
|
krother/python_abv_zedat
|
1e2e1fe16da6612c470f06f519cd053c567e0611
|
[
"MIT"
] | null | null | null |
projekte_ss2017/Minensuche_Benjamin/field.py
|
krother/python_abv_zedat
|
1e2e1fe16da6612c470f06f519cd053c567e0611
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
Created on Mon Jul 31 22:06:35 2017
@author: Benny
"""
import random as rnd
def printField(field):
'''printField printes the Minesweeperfield'''
for row in range(len(field)):
print()
for col in range(len(field[0])):
print(field[row][col], end = "")
class Field:
'''Field is a class for gameboards specially for Minesweeper'''
def __init__(self, height, width, p):
self.height = height
self.width = width
self.p = p
self.emptyfield = self.generateField()
self.minedfield = self.mineplanting()
self.solution = self.generateSolution()
def generateField(self):
'''generateField generates an empty (with 0 filled) Field'''
gamefield = []
for height in range(self.height):
row = []
for width in range(self.width):
row.append(0)
gamefield.append(row)
return gamefield
def mineplanting(self):
'''mineplanting plants randomly a given number of mines in a new field with the
objects height and width'''
minelist = []
field = []
while len(minelist) < self.p:
mine_x = rnd.randint(0, self.width-1)
mine_y = rnd.randint(0, self.height-1)
if not (mine_x, mine_y) in minelist:
minelist.append( (mine_x, mine_y) )
for height in range(self.height):
row = []
for width in range(self.width):
if (width, height) in minelist:
row.append("*")
else:
row.append(0)
field.append(row)
return field
def generateSolution(self):
'''generateSolution generates the solution to the field, with the field
as model'''
solution = self.generateField()
for height in range(self.height):
row = solution[height]
for width in range(self.width):
if self.minedfield[height][width] == '*':
row[width] = '*'
else:
if height == 0: h = (0,1)
elif height == self.height-1: h = (0,-1)
else: h = (-1,0,1)
if width == 0: b = (0,1)
elif width == self.width-1: b = (0,-1)
else: b = (-1,0,1)
for i in h:
for j in b:
if self.minedfield[height+i][width+j] == '*':
row[width] += 1
if row[width] == 0:
row[width] = '.'
return solution
if __name__ == "__main__":
gameBoard = Field(5, 10, 5)
printField(gameBoard.emptyfield)
print("\n")
printField(gameBoard.minedfield)
print("\n")
printField(gameBoard.solution)
| 30.915888 | 88 | 0.441959 |
c8ba9141db4d8766c1713040f5459df594f79e19
| 277 |
py
|
Python
|
src/terracotta.py
|
magistersart/ZTC_fork
|
ce72734ea575d9846b5b81f3efbfd14fa1f7e532
|
[
"PostgreSQL"
] | null | null | null |
src/terracotta.py
|
magistersart/ZTC_fork
|
ce72734ea575d9846b5b81f3efbfd14fa1f7e532
|
[
"PostgreSQL"
] | null | null | null |
src/terracotta.py
|
magistersart/ZTC_fork
|
ce72734ea575d9846b5b81f3efbfd14fa1f7e532
|
[
"PostgreSQL"
] | null | null | null |
#!/usr/bin/python
# pylint: disable=W0142
"""
terracotta.* scripts item
This file is part of ZTC and distributed under GNU GPL v.3
Copyright (c) 2011 Vladimir Rusinov]
"""
from ztc.java.terracotta import JMXTerracotta
j = JMXTerracotta()
m = j.args[0]
j.get(m, *j.args[1:])
| 18.466667 | 58 | 0.714801 |
a80e4fd7647e2b2049ab30c37ad79eba0682f08f
| 2,743 |
py
|
Python
|
simple-tensorflow-demo/4.demos/3.backPropagationTest.py
|
crackedcd/Intern.MT
|
36398837af377a7e1c4edd7cbb15eabecd2c3103
|
[
"MIT"
] | 1 |
2019-07-05T03:42:17.000Z
|
2019-07-05T03:42:17.000Z
|
simple-tensorflow-demo/4.demos/3.backPropagationTest.py
|
crackedcd/Intern.MT
|
36398837af377a7e1c4edd7cbb15eabecd2c3103
|
[
"MIT"
] | null | null | null |
simple-tensorflow-demo/4.demos/3.backPropagationTest.py
|
crackedcd/Intern.MT
|
36398837af377a7e1c4edd7cbb15eabecd2c3103
|
[
"MIT"
] | 1 |
2019-06-24T05:56:55.000Z
|
2019-06-24T05:56:55.000Z
|
"""
损失函数 loss
预测值(predict)(y)与已知答案(target)(y_)的差距
均方误差 MSE mean-square error
MSE(y, y_) = sigma ((y - y_)^2 / n)
loss = tf.reduce_mean(tf.square(y, y_))
反向传播 BP back propagation
为训练模型参数, 在所有参数上用梯度下降, 使NN模型在训练数据上的损失最小.
train_step = tf.train.GradientDescentOptimizer(learning_rate).minimize(loss)
train_step = tf.train.MomentumOptimizer(learning_rate, momentum).minimize(loss)
train_step = tf.train.AdamOptimizer(learning_rate).minimize(loss)
学习率 LR learning rate
学习率 大 学习率 小
学习速度 快 慢
使用时间点 刚开始训练时 一定轮数过后
副作用 1.易损失值爆炸; 2.易振荡. 1.易过拟合; 2.收敛速度慢.
刚开始训练时: 学习率以 0.01 ~ 0.001 为宜.
一定轮数过后: 逐渐减缓.
接近训练结束: 学习速率的衰减应该在100倍以上.
"""
import tensorflow as tf
import numpy as np
def back_propagation_test():
# 训练次数
steps = 3000
# 每次喂入数据数量
batch_size = 8
# 随机种子
seed = 8731
# 基于seed产生随机数
rng = np.random.RandomState(seed)
# 生成32组重量和体积作为输入数据集, 32行2列的矩阵
mat_x = rng.rand(32, 2)
mat_y = []
# print(mat_x)
# 假设"体积 + 重量 < 1"的零件合格, 构造mat_y. 从X中取出一行, 判断如果两者的和小于1, 给Y赋值1, 否则赋值0.
# 神经网络判断的依据是"数据"和"概率", 它并不知道人为标注y是0或1的方法.
# pythonic code: mat_y = [[int(x0 + x1 < 1)] for (x0, x1) in mat_x]
for x0, x1 in mat_x:
if x0 + x1 < 1:
mat_y.append([1])
else:
mat_y.append([0])
# print(mat_y)
# 前向传播
x = tf.placeholder(tf.float32, shape=(None, 2))
y_ = tf.placeholder(tf.float32, shape=(None, 1))
w1 = tf.Variable(tf.random_normal([2, 3], stddev=1, seed=1))
w2 = tf.Variable(tf.random_normal([3, 1], stddev=1, seed=1))
a = tf.matmul(x, w1)
y = tf.matmul(a, w2)
# 反向传播
loss = tf.reduce_mean(tf.square(y - y_))
lr = 0.001
train_step = tf.train.GradientDescentOptimizer(lr).minimize(loss)
# 训练
with tf.Session() as sess:
init_op = tf.global_variables_initializer()
sess.run(init_op)
# 输出未训练的参数取值
print("训练前的结果")
print(sess.run(w1))
print(sess.run(w2))
for i in range(steps):
# 数据集只有32个(行), 所以对32取余, 让start在数据集范围内, i * batch_size让每次训练跨度batch_size个数据
start = (i * batch_size) % 32
end = start + batch_size
feeds = {
x: mat_x[start:end],
y_: mat_y[start:end]
}
# 每次循环中, 代入输入特征(data)和标准答案(target)
sess.run(train_step, feed_dict=feeds)
if i % 500 == 0:
total_loss = sess.run(loss, feed_dict={x: mat_x, y_: mat_y})
print("在%d次训练后, 损失为%g" % (i, total_loss))
print("训练后的结果")
print(sess.run(w1))
print(sess.run(w2))
return None
if __name__ == '__main__':
back_propagation_test()
| 27.158416 | 85 | 0.582574 |
93b61103d8019f377a14047dd0b12051d80f41d7
| 637 |
py
|
Python
|
py/test/test_inception_v2.py
|
zjZSTU/GoogLeNet
|
a0801e45006d34b4901a8834397961ce17f24e2e
|
[
"Apache-2.0"
] | 1 |
2021-04-18T15:36:33.000Z
|
2021-04-18T15:36:33.000Z
|
py/test/test_inception_v2.py
|
zjZSTU/GoogLeNet
|
a0801e45006d34b4901a8834397961ce17f24e2e
|
[
"Apache-2.0"
] | null | null | null |
py/test/test_inception_v2.py
|
zjZSTU/GoogLeNet
|
a0801e45006d34b4901a8834397961ce17f24e2e
|
[
"Apache-2.0"
] | 3 |
2020-07-10T11:45:52.000Z
|
2022-01-15T08:46:14.000Z
|
# -*- coding: utf-8 -*-
"""
@date: 2020/4/9 下午11:37
@file: test_inception_v2.py
@author: zj
@description:
"""
import torch
import models.inception_v2 as inception
def test():
model_googlenet = inception.Inception_v2(num_classes=1000)
# print(model_googlenet)
# 训练阶段
model_googlenet.train()
data = torch.randn((1, 3, 299, 299))
outputs, aux = model_googlenet.forward(data)
print(outputs.shape)
print(aux.shape)
# 测试阶段
model_googlenet.eval()
data = torch.randn((1, 3, 299, 299))
outputs = model_googlenet.forward(data)
print(outputs.shape)
if __name__ == '__main__':
test()
| 18.735294 | 62 | 0.660911 |
27a9c70335e5cc4b5a56e709850c0d0067a0b822
| 5,917 |
py
|
Python
|
BruteForce/Wordpress.py
|
Zusyaku/Termux-And-Lali-Linux-V2
|
b1a1b0841d22d4bf2cc7932b72716d55f070871e
|
[
"Apache-2.0"
] | 2 |
2021-11-17T03:35:03.000Z
|
2021-12-08T06:00:31.000Z
|
BruteForce/Wordpress.py
|
Zusyaku/Termux-And-Lali-Linux-V2
|
b1a1b0841d22d4bf2cc7932b72716d55f070871e
|
[
"Apache-2.0"
] | null | null | null |
BruteForce/Wordpress.py
|
Zusyaku/Termux-And-Lali-Linux-V2
|
b1a1b0841d22d4bf2cc7932b72716d55f070871e
|
[
"Apache-2.0"
] | 2 |
2021-11-05T18:07:48.000Z
|
2022-02-24T21:25:07.000Z
|
# uncompyle6 version 2.11.5
# Python bytecode 2.7 (62211)
# Decompiled from: Python 2.7.18 (default, Apr 20 2020, 20:30:41)
# [GCC 9.3.0]
# Embedded file name: BruteForce\Wordpress.py
import requests
import re
import threading
import time
import json
from Exploits import printModule
from Tools import shellupload
r = '\x1b[31m'
g = '\x1b[32m'
y = '\x1b[33m'
b = '\x1b[34m'
m = '\x1b[35m'
c = '\x1b[36m'
w = '\x1b[37m'
Headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:72.0) Gecko/20100101 Firefox/72.0'}
passwords = open('files/DefaultPasswords_Wordpress.txt', 'r').read().splitlines()
class Wordpress(object):
def __init__(self):
self.flag = 0
self.password = passwords
def Run(self, site, users):
try:
thread = []
for username in users:
if self.flag == 1:
break
for passwd in self.password:
t = threading.Thread(target=self.BruteForce, args=(
site, passwd, username))
if self.flag == 1:
break
else:
t.start()
thread.append(t)
time.sleep(0.08)
for j in thread:
j.join()
if self.flag == 0:
return printModule.returnNo(site, 'N/A', 'Wordpress Bruteforce', 'Wordpress')
return printModule.returnYes(site, 'N/A', 'Wordpress Bruteforce', 'Wordpress')
except:
return printModule.returnNo(site, 'N/A', 'Wordpress Bruteforce', 'Wordpress')
def UserName_Enumeration(self, site):
users = []
session = requests.session()
for i in range(10):
try:
GETSource = session.get('http://' + site + '/?author={}'.format(str(i + 1)), timeout=7, headers=Headers)
find = re.findall('/author/(.*)/"', str(GETSource.content))
username = find[0]
if '/feed' in str(username):
find = re.findall('/author/(.*)/feed/"', str(GETSource.content))
username2 = find[0]
users.append(str(username2))
else:
users.append(str(username))
except:
pass
if not len(users) == 0:
pass
else:
for i in range(10):
try:
GETSource2 = session.get('http://' + site + '/wp-json/wp/v2/users/' + str(i + 1), timeout=7, headers=Headers)
__InFo = json.loads(str(GETSource2.content))
if 'id' not in str(__InFo):
pass
else:
try:
users.append(str(__InFo['slug']))
except:
pass
except:
pass
if not len(users) == 0:
pass
else:
try:
GETSource3 = session.get('http://' + site + '/author-sitemap.xml', timeout=7, headers=Headers)
yost = re.findall('(<loc>(.*?)</loc>)\\s', GETSource3.content)
for user in yost:
users.append(str(user[1].split('/')[4]))
except:
pass
if not len(users) == 0:
pass
else:
users.append('admin')
return self.Run(site, users)
def BruteForce(self, site, passwd, username):
try:
sess = requests.session()
Headersz = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:72.0) Gecko/20100101 Firefox/72.0'
}
sess.get('http://' + site + '', timeout=10, headers=Headersz)
source = sess.get('http://' + site + '/wp-login.php', timeout=10, headers=Headersz).content
WpSubmitValue = re.findall('class="button button-primary button-large" value="(.*)"', str(source))[0]
WpRedirctTo = re.findall('name="redirect_to" value="(.*)"', str(source))[0]
if 'Log In' in WpSubmitValue:
WpSubmitValue = 'Log+In'
else:
WpSubmitValue = WpSubmitValue
Headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:72.0) Gecko/20100101 Firefox/72.0','Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',
'Accept-Language': 'en-US,en;q=0.5',
'Accept-Encoding': 'gzip, deflate',
'Referer': 'http://{}'.format(site),
'Content-Type': 'application/x-www-form-urlencoded',
'Origin': 'http://{}'.format(site),
'Connection': 'keep-alive',
'Upgrade-Insecure-Requests': '1',
'Sec-Fetch-Dest': 'document',
'Sec-Fetch-Mode': 'navigate',
'Sec-Fetch-Site': 'same-origin',
'Sec-Fetch-User': '?1'
}
post = {'log': username,
'pwd': passwd,
'wp-submit': WpSubmitValue,
'redirect_to': WpRedirctTo,
'testcookie': '1'
}
url = site + '/wp-login.php'
sess.post('http://' + url, data=post, headers=Headers, timeout=10)
G = sess.get('http://' + site + '/wp-admin/', timeout=10, headers=Headersz)
if '_logged' in str(sess.cookies) and 'dashboard' in str(G.content):
with open('result/Wordpress_Hacked.txt', 'a') as writer:
writer.write('http://' + site + '/wp-login.php' + '\n Username: {}'.format(username) + '\n Password: ' + passwd + '\n-----------------------------------------\n')
shellupload.UploadshellWordpress(site, sess)
self.flag = 1
except:
pass
| 39.97973 | 205 | 0.488085 |
e3879e265593ab018ada0842a7f018865afdb065
| 792 |
py
|
Python
|
ryu/app/otherApp/getFlowTab.py
|
yuesir137/SDN-CLB
|
58b12a9412cffdf2945440528b1885c8899edd08
|
[
"Apache-2.0"
] | null | null | null |
ryu/app/otherApp/getFlowTab.py
|
yuesir137/SDN-CLB
|
58b12a9412cffdf2945440528b1885c8899edd08
|
[
"Apache-2.0"
] | null | null | null |
ryu/app/otherApp/getFlowTab.py
|
yuesir137/SDN-CLB
|
58b12a9412cffdf2945440528b1885c8899edd08
|
[
"Apache-2.0"
] | null | null | null |
import os
import time
local=1
while True:
tables=os.popen('sudo ovs-ofctl dump-flows s{}'.format(local)).readlines()[1:]
minPacketN=100
minPort=-1
for table in tables:
print(table)
details=table.split(',')
# print(details)
if len(details)>9:
duration=details[1][10:-1]
print(duration)
n_packets=details[3][11:]
print(n_packets)
packetRate=int(n_packets)/float(duration)
print(packetRate)
srcIP=details[10][7:]
print(srcIP)
dstIP=details[11][7:]
print(dstIP)
port=details[12][7:]
print(port)
if n_packets<minPacketN:
minPacketN=n_packets
minPort=port
time.sleep(1)
| 27.310345 | 82 | 0.539141 |
4750a43892925cea105fadd9b59420a1313f7f95
| 3,566 |
py
|
Python
|
Python/calculator_gui.py
|
saurabhpal007/hacktoberfest2021-1
|
5abad37ab426a7b34fc7bcd98ded885fd6ce02ef
|
[
"CC0-1.0"
] | 81 |
2021-10-01T13:19:13.000Z
|
2021-10-06T08:43:35.000Z
|
Python/calculator_gui.py
|
saurabhpal007/hacktoberfest2021-1
|
5abad37ab426a7b34fc7bcd98ded885fd6ce02ef
|
[
"CC0-1.0"
] | 67 |
2021-10-01T13:43:46.000Z
|
2021-10-06T13:55:49.000Z
|
Python/calculator_gui.py
|
saurabhpal007/hacktoberfest2021-1
|
5abad37ab426a7b34fc7bcd98ded885fd6ce02ef
|
[
"CC0-1.0"
] | 394 |
2021-10-01T11:55:24.000Z
|
2021-10-06T13:45:57.000Z
|
from tkinter import *
import parser
from math import factorial
root = Tk()
root.title("Calculator")
i=0
def get_variables(num):
global i
display.insert(i,num)
i+=1
def perhitungan():
entire_string = display.get()
try:
a = parser.expr(entire_string).compile()
result = eval(a)
clear_all()
display.insert(0,result)
except Exception:
clear_all()
display.insert(0,"Error")
def get_operation(operator):
global i
length = len(operator)
display.insert(i,operator)
i+=length
def clear_all():
display.delete(0,END)
def undo():
entire_string = display.get()
if len(entire_string):
new_string = entire_string[:-1]
clear_all()
display.insert(0,new_string)
else:
clear_all()
display.insert(0,"Error")
def fact():
entire_string = display.get()
try:
result = factorial(int(entire_string))
clear_all()
display.insert(0,result)
except Exception:
clear_all()
display.insert(0,"Error")
display = Entry(root)
display.grid(row=1,columnspan=6,sticky=N+E+W+S)
Button(root,text="1",command = lambda : get_variables(1)).grid(row=2,column=0, sticky=N+S+E+W)
Button(root,text="2",command = lambda : get_variables(2)).grid(row=2,column=1, sticky=N+S+E+W)
Button(root,text="3",command = lambda : get_variables(3)).grid(row=2,column=2, sticky=N+S+E+W)
Button(root,text="4",command = lambda : get_variables(4)).grid(row=3,column=0, sticky=N+S+E+W)
Button(root,text="5",command = lambda : get_variables(5)).grid(row=3,column=1, sticky=N+S+E+W)
Button(root,text="6",command = lambda : get_variables(6)).grid(row=3,column=2, sticky=N+S+E+W)
Button(root,text="7",command = lambda : get_variables(7)).grid(row=4,column=0, sticky=N+S+E+W)
Button(root,text="8",command = lambda : get_variables(8)).grid(row=4,column=1, sticky=N+S+E+W)
Button(root,text="9",command = lambda : get_variables(9)).grid(row=4,column=2, sticky=N+S+E+W)
Button(root,text="AC",command = lambda : clear_all()).grid(row=5,column=0, sticky=N+S+E+W)
Button(root,text="0",command = lambda : get_variables(0)).grid(row=5,column=1, sticky=N+S+E+W)
Button(root,text=" .",command = lambda : get_variables(".")).grid(row=5,column=2, sticky=N+S+E+W)
Button(root,text="+",command = lambda : get_operation("+")).grid(row=2,column=3, sticky=N+S+E+W)
Button(root,text="-",command = lambda : get_operation("-")).grid(row=3,column=3, sticky=N+S+E+W)
Button(root,text="*",command = lambda : get_operation("*")).grid(row=4,column=3, sticky=N+S+E+W)
Button(root,text="/",command = lambda : get_operation("//")).grid(row=5,column=3, sticky=N+S+E+W)
Button(root,text="pi",command = lambda : get_operation("*3.14")).grid(row=2,column=4, sticky=N+S+E+W)
Button(root,text="%",command = lambda : get_operation("%")).grid(row=3,column=4, sticky=N+S+E+W)
Button(root,text="(",command = lambda : get_operation("(")).grid(row=4,column=4, sticky=N+S+E+W)
Button(root,text="exp",command = lambda : get_operation("**")).grid(row=5,column=4, sticky=N+S+E+W)
Button(root,text="<-",command = lambda : undo()).grid(row=2,column=5, sticky=N+S+E+W)
Button(root,text="x!",command = lambda : fact()).grid(row=3,column=5, sticky=N+S+E+W)
Button(root,text=")",command = lambda : get_operation(")")).grid(row=4,column=5, sticky=N+S+E+W)
Button(root,text="^2",command = lambda : get_operation("**2")).grid(row=5,column=5, sticky=N+S+E+W)
Button(root,text="=",command = lambda : perhitungan()).grid(columnspan=6, sticky=N+S+E+W)
root.mainloop()
| 42.452381 | 101 | 0.660404 |
47c46d3061e5499818d18eca27a7cbab630d6878
| 396 |
py
|
Python
|
exercises/zh/exc_04_10.py
|
Jette16/spacy-course
|
32df0c8f6192de6c9daba89740a28c0537e4d6a0
|
[
"MIT"
] | 2,085 |
2019-04-17T13:10:40.000Z
|
2022-03-30T21:51:46.000Z
|
exercises/zh/exc_04_10.py
|
Jette16/spacy-course
|
32df0c8f6192de6c9daba89740a28c0537e4d6a0
|
[
"MIT"
] | 79 |
2019-04-18T14:42:55.000Z
|
2022-03-07T08:15:43.000Z
|
exercises/zh/exc_04_10.py
|
Jette16/spacy-course
|
32df0c8f6192de6c9daba89740a28c0537e4d6a0
|
[
"MIT"
] | 361 |
2019-04-17T13:34:32.000Z
|
2022-03-28T04:42:45.000Z
|
TRAINING_DATA = [
(
"我去年去了西安，那里的城墙很壮观！",
{"entities": [(4, 5, "TOURIST_DESTINATION")]},
),
(
"人一辈子一定要去一趟巴黎，但那里的埃菲尔铁塔有点无趣。",
{"entities": [(5, 6, "TOURIST_DESTINATION")]},
),
(
"深圳也有个巴黎的埃菲尔铁塔，哈哈哈",
{"entities": []}
),
(
"北京很适合暑假去：长城、故宫，还有各种好吃的小吃！",
{"entities": [(0, 1, "TOURIST_DESTINATION")]},
),
]
| 20.842105 | 54 | 0.467172 |
d089f978def3108a932d726df6fa2d43634cb62e
| 5,448 |
py
|
Python
|
contrib/华为云垃圾分类大赛心得与案例-GitLD/src_Xception_all_aug+TTA/data_gen.py
|
huaweicloud/ModelArts-Lab
|
75d06fb70d81469cc23cd422200877ce443866be
|
[
"Apache-2.0"
] | 1,045 |
2019-05-09T02:50:43.000Z
|
2022-03-31T06:22:11.000Z
|
contrib/华为云垃圾分类大赛心得与案例-GitLD/src_Xception_all_aug+TTA/data_gen.py
|
huaweicloud/ModelArts-Lab
|
75d06fb70d81469cc23cd422200877ce443866be
|
[
"Apache-2.0"
] | 1,468 |
2019-05-16T00:48:18.000Z
|
2022-03-08T04:12:44.000Z
|
contrib/华为云垃圾分类大赛心得与案例-GitLD/src_Xception_all_aug+TTA/data_gen.py
|
huaweicloud/ModelArts-Lab
|
75d06fb70d81469cc23cd422200877ce443866be
|
[
"Apache-2.0"
] | 1,077 |
2019-05-09T02:50:53.000Z
|
2022-03-27T11:05:32.000Z
|
# -*- coding: utf-8 -*-
import os
import math
import codecs
import random
import numpy as np
from glob import glob
from PIL import Image
from keras.utils import np_utils, Sequence
from sklearn.model_selection import train_test_split
class BaseSequence(Sequence):
"""
基础的数据流生成器，每次迭代返回一个batch
BaseSequence可直接用于fit_generator的generator参数
fit_generator会将BaseSequence再次封装为一个多进程的数据流生成器
而且能保证在多进程下的一个epoch中不会重复取相同的样本
"""
def __init__(self, img_paths, labels, batch_size, img_size):
assert len(img_paths) == len(labels), "len(img_paths) must equal to len(lables)"
assert img_size[0] == img_size[1], "img_size[0] must equal to img_size[1]"
self.x_y = np.hstack((np.array(img_paths).reshape(len(img_paths), 1), np.array(labels)))
self.batch_size = batch_size
self.img_size = img_size
def __len__(self):
return math.ceil(len(self.x_y) / self.batch_size)
@staticmethod
def center_img(img, size=None, fill_value=255):
"""
center img in a square background
"""
h, w = img.shape[:2]
if size is None:
size = max(h, w)
shape = (size, size) + img.shape[2:]
background = np.full(shape, fill_value, np.uint8)
center_x = (size - w) // 2
center_y = (size - h) // 2
background[center_y:center_y + h, center_x:center_x + w] = img
return background
def preprocess_img(self, img_path):
"""
image preprocessing
you can add your special preprocess method here
"""
img = Image.open(img_path)
img = img.resize((self.img_size[0], self.img_size[0]))
img = img.convert('RGB')
img = np.array(img)
img = img[:, :, ::-1]
return img
def __getitem__(self, idx):
batch_x = self.x_y[idx * self.batch_size: (idx + 1) * self.batch_size, 0]
batch_y = self.x_y[idx * self.batch_size: (idx + 1) * self.batch_size, 1:]
batch_x = np.array([self.preprocess_img(img_path) for img_path in batch_x])
batch_y = np.array(batch_y).astype(np.float32)
return batch_x, batch_y
def on_epoch_end(self):
"""Method called at the end of every epoch.
"""
np.random.shuffle(self.x_y)
def data_flow(train_data_dir, batch_size, num_classes, input_size): # need modify
label_files = glob(os.path.join(train_data_dir, '*.txt'))
random.shuffle(label_files)
img_paths = []
labels = []
for index, file_path in enumerate(label_files):
with codecs.open(file_path, 'r', 'utf-8') as f:
line = f.readline()
line_split = line.strip().split(', ')
if len(line_split) != 2:
print('%s contain error lable' % os.path.basename(file_path))
continue
img_name = line_split[0]
label = int(line_split[1])
img_paths.append(os.path.join(train_data_dir, img_name))
labels.append(label)
labels = np_utils.to_categorical(labels, num_classes)
train_img_paths, validation_img_paths, train_labels, validation_labels = \
train_test_split(img_paths, labels, test_size=0.2, random_state=0)
print('total samples: %d, training samples: %d, validation samples: %d' % (len(img_paths), len(train_img_paths), len(validation_img_paths)))
train_sequence = BaseSequence(train_img_paths, train_labels, batch_size, [input_size, input_size])
validation_sequence = BaseSequence(validation_img_paths, validation_labels, batch_size, [input_size, input_size])
# # 构造多进程的数据流生成器
# train_enqueuer = OrderedEnqueuer(train_sequence, use_multiprocessing=True, shuffle=True)
# validation_enqueuer = OrderedEnqueuer(validation_sequence, use_multiprocessing=True, shuffle=True)
#
# # 启动数据生成器
# n_cpu = multiprocessing.cpu_count()
# train_enqueuer.start(workers=int(n_cpu * 0.7), max_queue_size=10)
# validation_enqueuer.start(workers=1, max_queue_size=10)
# train_data_generator = train_enqueuer.get()
# validation_data_generator = validation_enqueuer.get()
# return train_enqueuer, validation_enqueuer, train_data_generator, validation_data_generator
return train_sequence, validation_sequence
if __name__ == '__main__':
# train_enqueuer, validation_enqueuer, train_data_generator, validation_data_generator = data_flow(dog_cat_data_path, batch_size)
# for i in range(10):
# train_data_batch = next(train_data_generator)
# train_enqueuer.stop()
# validation_enqueuer.stop()
train_sequence, validation_sequence = data_flow(train_data_dir, batch_size)
batch_data, bacth_label = train_sequence.__getitem__(5)
label_name = ['cat', 'dog']
for index, data in enumerate(batch_data):
img = Image.fromarray(data[:, :, ::-1])
img.save('./debug/%d_%s.jpg' % (index, label_name[int(bacth_label[index][1])]))
train_sequence.on_epoch_end()
batch_data, bacth_label = train_sequence.__getitem__(5)
for index, data in enumerate(batch_data):
img = Image.fromarray(data[:, :, ::-1])
img.save('./debug/%d_2_%s.jpg' % (index, label_name[int(bacth_label[index][1])]))
train_sequence.on_epoch_end()
batch_data, bacth_label = train_sequence.__getitem__(5)
for index, data in enumerate(batch_data):
img = Image.fromarray(data[:, :, ::-1])
img.save('./debug/%d_3_%s.jpg' % (index, label_name[int(bacth_label[index][1])]))
print('end')
| 41.272727 | 144 | 0.672173 |
d0a0e3262a093befa973a8e125897b334151be59
| 1,047 |
py
|
Python
|
018-C127-WebScraping/main.py
|
somePythonProgrammer/PythonCode
|
fb2b2245db631cefd916a960768f411969b0e78f
|
[
"MIT"
] | 2 |
2021-09-28T13:55:20.000Z
|
2021-11-15T10:08:49.000Z
|
018-C127-WebScraping/main.py
|
somePythonProgrammer/PythonCode
|
fb2b2245db631cefd916a960768f411969b0e78f
|
[
"MIT"
] | null | null | null |
018-C127-WebScraping/main.py
|
somePythonProgrammer/PythonCode
|
fb2b2245db631cefd916a960768f411969b0e78f
|
[
"MIT"
] | 1 |
2022-01-20T03:02:20.000Z
|
2022-01-20T03:02:20.000Z
|
from selenium import webdriver
from bs4 import BeautifulSoup
import time
import csv
START_URL = "https://en.wikipedia.org/wiki/List_of_brightest_stars_and_other_record_stars"
browser = webdriver.Chrome("chromedriver.exe")
browser.get(START_URL)
time.sleep(3)
def scrape():
headers = ["vmag", "name", "bayer", "distance_ly", "spectral_class", "mass", "radius", "luminosity"]
star_data = []
soup = BeautifulSoup(browser.page_source, "html.parser")
table = soup.find_all("table", attrs={"class", "wikitable sortable jquery-tablesorter"})[0]
for row in table.find_all("tr"):
cols = row.find_all("td")
if len(cols) == 0:
continue
star_data.append([col.text.strip() for col in cols])
with open("stars.csv", "w") as f:
csvwriter = csv.writer(f)
csvwriter.writerow(headers)
# use for loop to write each row of data to csv
for row in star_data:
try:
csvwriter.writerow(row)
except:
pass
scrape()
exit()
| 29.914286 | 104 | 0.636103 |
ef7372b2f45a71a889cf69edf89aa0ccd564cb51
| 5,955 |
py
|
Python
|
AntColonyOptimizer.py
|
siej88/FuzzyACO
|
989a58049c8417cd023cfc312fb99d2649333ca7
|
[
"MIT"
] | null | null | null |
AntColonyOptimizer.py
|
siej88/FuzzyACO
|
989a58049c8417cd023cfc312fb99d2649333ca7
|
[
"MIT"
] | null | null | null |
AntColonyOptimizer.py
|
siej88/FuzzyACO
|
989a58049c8417cd023cfc312fb99d2649333ca7
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
UNIVERSIDAD DE CONCEPCION
Departamento de Ingenieria Informatica y
Ciencias de la Computacion
Memoria de Titulo Ingenieria Civil Informatica
DETECCION DE BORDES EN IMAGENES DGGE USANDO UN
SISTEMA HIBRIDO ACO CON LOGICA DIFUSA
Autor: Sebastian Ignacio Espinoza Jimenez
Patrocinante: Maria Angelica Pinninghoff Junemann
"""
import numpy as N
import MathTools as mat
class AntColonyOptimizer(object):
"""Ant Colony Optimization Engine"""
def __init__(self):
"""AntColonyOptimizer AntColonyOptimizer()"""
self._pheromoneMatrix = None
self._imageFlag = False
def hasPheromoneMatrix(self):
"""bool hasPheromoneMatrix()"""
return self._imageFlag
def getPheromoneMatrix(self):
"""numpy.array getPheromoneMatrix()"""
return N.copy(self._pheromoneMatrix)
def generatePheromoneMatrix(self, imageMatrix, heuristicMatrix, parameterSet):
"""numpy.array generatePheromoneMatrix(
numpy.array imageMatrix, numpy.array heuristicMatrix, dict parameterSet)"""
antMovementMode = parameterSet['antMovementMode']
antCount = parameterSet['antCount']
cycleCount = parameterSet['cycleCount']
stepCount = parameterSet['stepCount']
alpha = parameterSet['alpha']
beta = parameterSet['beta']
delta = parameterSet['delta']
tuning = parameterSet['tuning']
rho = parameterSet['rho']
psi = parameterSet['psi']
mathTools = mat.MathTools()
pheromoneMatrix = self._generateInitialPheromoneMatrix(N.copy(imageMatrix))
matrixHeight = heuristicMatrix.shape[0]
matrixWidth = heuristicMatrix.shape[1]
indexes = list(N.ndindex(matrixHeight, matrixWidth))
N.random.shuffle(indexes)
antSet = indexes[0:antCount]
initialPheromoneMatrix = N.copy(pheromoneMatrix)
heuristiqMatrix = N.copy(heuristicMatrix)
heuristiqMatrix[N.where(heuristiqMatrix == 0)] = 1e-10
for cycle in xrange(cycleCount):
N.random.shuffle(antSet)
antPrevious = list(antSet)
for i in xrange(antCount):
for step in xrange(stepCount):
x = antSet[i][0]
y = antSet[i][1]
dx = antPrevious[i][0] - x
dy = antPrevious[i][1] - y
top = x > 0
bottom = x < matrixHeight - 1
left = y > 0
right = y < matrixWidth - 1
heuristicWindow = heuristiqMatrix[x-top:x+bottom+1, y-left:y+right+1]
pheromoneWindow = pheromoneMatrix[x-top:x+bottom+1, y-left:y+right+1]
mask = float(heuristicWindow[top, left])
heuristicWindow[top, left] = 2.
minHeuristic = N.min(heuristicWindow)
heuristicWindow[top, left] = -2.
maxHeuristic = N.max(heuristicWindow)
heuristicWindow[top, left] = mask
if (maxHeuristic - minHeuristic > delta):
alpha -= tuning
beta += tuning
else:
alpha += tuning
beta -= tuning
probabilityMatrix = N.power(pheromoneWindow, alpha)*N.power(heuristicWindow, beta)
probabilityMatrix[top, left] = -2.
probabilityMatrix[top + dx, left + dy] = -2.
if antMovementMode == 1:
maxProbability = N.max(probabilityMatrix)
indexes = N.where(probabilityMatrix == maxProbability)
randomIndex = N.random.randint(indexes[0].shape[0])
newIndex = (indexes[0][randomIndex], indexes[1][randomIndex])
else:
indexes = N.where(probabilityMatrix >= 0)
probabilityArray = probabilityMatrix[indexes]
summationArray = N.cumsum(probabilityArray)
randomValue = N.random.rand(1)*summationArray[summationArray.shape[0] - 1]
probabilityIndex = N.where(summationArray >= randomValue[0])
probabilityValue = probabilityArray[probabilityIndex][0]
newIndex = N.where(probabilityMatrix == probabilityValue)
randomIndex = N.random.randint(newIndex[0].shape[0])
newIndex = (newIndex[0][randomIndex], newIndex[1][randomIndex])
newX = x+newIndex[0]-top
newY = y+newIndex[1]-left
antPrevious[i] = (x, y)
antSet[i] = (newX, newY)
pheromone = pheromoneMatrix[x,y]
heuristic = heuristiqMatrix[x,y]
pheromoneMatrix[x,y] = (1-rho)*pheromone + rho*heuristic
pheromoneMatrix = (1-psi)*pheromoneMatrix + psi*initialPheromoneMatrix
pheromoneMatrix = mathTools.normalize(pheromoneMatrix)
self._pheromoneMatrix = N.copy(pheromoneMatrix)
self._imageFlag = True
return pheromoneMatrix
def _generateInitialPheromoneMatrix(self, inputMatrix):
"""numpy.array _generateInitialPheromoneMatrix(numpy.array inputMatrix)"""
mathTools = mat.MathTools()
gaussianMatrix = mathTools.gaussianFilter(inputMatrix)
gradientMatrix = mathTools.gradient(gaussianMatrix)
laplacianMatrix = mathTools.gradient(gradientMatrix)
initialPheromoneMatrix = gradientMatrix-laplacianMatrix
initialPheromoneMatrix = mathTools.normalize(initialPheromoneMatrix)
return initialPheromoneMatrix
| 48.024194 | 105 | 0.573468 |
ef994720ea2a999f0b5e3dfb0c277052b19ae51f
| 534 |
py
|
Python
|
Packs/CommonScripts/Scripts/Cut/Cut_test.py
|
diCagri/content
|
c532c50b213e6dddb8ae6a378d6d09198e08fc9f
|
[
"MIT"
] | 799 |
2016-08-02T06:43:14.000Z
|
2022-03-31T11:10:11.000Z
|
Packs/CommonScripts/Scripts/Cut/Cut_test.py
|
diCagri/content
|
c532c50b213e6dddb8ae6a378d6d09198e08fc9f
|
[
"MIT"
] | 9,317 |
2016-08-07T19:00:51.000Z
|
2022-03-31T21:56:04.000Z
|
Packs/CommonScripts/Scripts/Cut/Cut_test.py
|
diCagri/content
|
c532c50b213e6dddb8ae6a378d6d09198e08fc9f
|
[
"MIT"
] | 1,297 |
2016-08-04T13:59:00.000Z
|
2022-03-31T23:43:06.000Z
|
from Cut import cut
import pytest
@pytest.mark.parametrize('value,delimiter,fields,expected', [
('A-B-C-D-E', '-', '1,5', 'A-E'),
('a,ב,c', ',', '2,3', 'ב,c'),
])
def test_cut(value, delimiter, fields, expected):
"""
Given:
Case 1: A-B-C-D-E to split by - from char 1 to 5
Case 2: a,ב,c to split by , from char 2 to 3
When:
Running Cut
Then:
Case 1: Ensure A-E is returned
Case 2: Ensure ב,c is returned
"""
assert cut(value, fields, delimiter) == expected
| 22.25 | 61 | 0.558052 |
329062c006761cb11d903f71c24e59c1e35e6910
| 3,731 |
py
|
Python
|
extractTool/extractTool/similar.py
|
corneliazy/Geosoftware2
|
8604c79c58a61b84c602f16b5f1e74e30dfcbd0e
|
[
"MIT"
] | null | null | null |
extractTool/extractTool/similar.py
|
corneliazy/Geosoftware2
|
8604c79c58a61b84c602f16b5f1e74e30dfcbd0e
|
[
"MIT"
] | 47 |
2018-11-13T13:55:01.000Z
|
2019-09-16T13:38:11.000Z
|
extractTool/extractTool/similar.py
|
corneliazy/Geosoftware2
|
8604c79c58a61b84c602f16b5f1e74e30dfcbd0e
|
[
"MIT"
] | 4 |
2018-11-27T12:36:51.000Z
|
2020-10-14T18:07:04.000Z
|
import math
import detailebenen
import click
# import typ
# Beispielkoordinaten
# bbox1 = [5.8663155, 47.270111, 15.041932 , 55.099159]
# bbox2 = [7.5234, 52.0326, 7.7556, 52.152]
# def mastersim(filepath):
# bbox1 = detailebenen(filepath) blabla Hier muessen die Bboxen berechet werden
# bbox2 = detailebee(filepath) blabla also detailebenen Aufrufen
# sim = aehnlickeit(bbox1, bbox2)
# Hier muss typ.py
# input1 = typ.getTyp(filepath)
# input2 = typ.getTyp(filepath)
# whatDataType(input1, input2, sim)
"""returns the new calculated similarity score
:param input1: filepath from a file
:param input2: filepath from a file
:param imput3: similarity score from two bounding boxes
"""
def whatDataType(input1, input2, sim):
if input1 == "raster" and input2 == "raster":
click.echo("These files are rasterdata")
return sim
if input1 == "vector" and input2 == "vector":
click.echo("These files are vectordata")
return sim
if input1 == "raster" and input2 == "vector" or input1 == "vector" and input2 == "raster":
click.echo("These files are not the same datatype")
sim = sim*5/4
if sim > 1:
sim = 1
return sim
"""
Function to calculate the similarity score
:param bbox1: Bounding Box from a file
:param bbox2: Bounding Box from a file
:returns: similarity score from the two Bounding Boxes
"""
def aehnlickeit (bbox1,bbox2):
if isinstance(bbox1[0], float) and isinstance(bbox1[1], float) and isinstance(bbox1[2], float) and isinstance(bbox1[3], float):
if isinstance(bbox2[0], float) and isinstance(bbox2[1], float) and isinstance(bbox2[2], float) and isinstance(bbox2[3], float):
if distance(bbox1,bbox2) < 20000:
simdis = distance(bbox1,bbox2)/20000
else:
simdis = 1
if abs(area(bbox1) - area(bbox2)) < 1000000:
simA = (abs(area(bbox1) - area(bbox2)))/1000000
else:
simA = 1
sim = (2 * simdis + simA)/3
print(sim)
return sim
else:
return None
"""
Function to calculate the mean latitude
:param list:
:returns: the mean Latitude
"""
def meanLatitude (list):
lat = (list[3]+list[1])/2
return lat
"""
Function to calculate the mean longitude
:param list:
:returns: the mean Longitude
"""
def meanLongitude (list):
lon = (list[2]+list[0])/2
return lon
"""
Function to calculate the latitude
:param list:
:returns: the Latitude
"""
def width (list):
x = (list[2]-list[0])*111.3 * (math.cos(meanLatitude(list)*math.pi/180))
return x
"""
Function to calculate the mean longitude
:param list:
:returns: the longitude
"""
def length (list):
y =(list[3]-list[1])*111.3
return y
"""
Function to calculate area
:param list:
:returns: the area
"""
def area (list):
A = width(list) * length(list)
return A
"""
auxiliary calculation
:param bbox1: Bounding Box from a file
:param bbox2: Bounding Box from a file
:returns: the cosinus
"""
def lawOfCosines(bbox1,bbox2):
cos = math.sin((meanLatitude(bbox1) * math.pi/180))*math.sin((meanLatitude(bbox2)*math.pi/180)) + math.cos((meanLatitude(bbox1)*math.pi/180)) * math.cos((meanLatitude(bbox2)*math.pi/180)) * math.cos((meanLongitude(bbox1)*math.pi/180)-(meanLongitude(bbox2)*math.pi/180))
return cos
"""
function to calculate the distace between two Bounding Boxes
:param bbox1: Bounding Box from a file
:param bbox2: Bounding Box from a file
:returns: the distance
"""
def distance(bbox1,bbox2):
dist = math.acos(lawOfCosines(bbox1,bbox2)) * 6378.388
return dist
if __name__ == '__main__':
aehnlickeit(bbox1, bbox2)
| 28.480916 | 273 | 0.654248 |
08c0a7cb786a0eb7250f9d1fe3bd7eb0533d2522
| 600 |
py
|
Python
|
0009palindrome-number.py
|
meat00/my-leetcode-python
|
8312de396b29e1d6dd54a65f87fa0511eb400faa
|
[
"MIT"
] | null | null | null |
0009palindrome-number.py
|
meat00/my-leetcode-python
|
8312de396b29e1d6dd54a65f87fa0511eb400faa
|
[
"MIT"
] | null | null | null |
0009palindrome-number.py
|
meat00/my-leetcode-python
|
8312de396b29e1d6dd54a65f87fa0511eb400faa
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
class Solution():
def isPalindrome(self, x: int) -> bool:
'''
注意特殊情况
1. x小于0
2. 最后一位为0
3. x为0
'''
if x < 0 or (x % 10 == 0 and x != 0):
return False
rev = 0
while x > rev:
rev = rev * 10 + x % 10
x = x // 10
print("rev:%d,x:%d" %(rev, x))
return x == rev or rev // 10 == x
if __name__ == "__main__":
s = Solution()
test = [0, 121, 10, -121]
for x in test:
ret = s.isPalindrome(x)
print(ret)
| 22.222222 | 45 | 0.416667 |
de3b2bf4d4c0e709ae15751a616c74112bddc8e9
| 1,804 |
py
|
Python
|
resources/mechanics_lib/Ant.py
|
PRECISE/ROSLab
|
2a6a295b71d4c73bc5c6ae2ec0330274afa31d0d
|
[
"Apache-2.0"
] | 7 |
2016-01-20T02:33:00.000Z
|
2021-02-04T04:06:57.000Z
|
resources/mechanics_lib/Ant.py
|
PRECISE/ROSLab
|
2a6a295b71d4c73bc5c6ae2ec0330274afa31d0d
|
[
"Apache-2.0"
] | null | null | null |
resources/mechanics_lib/Ant.py
|
PRECISE/ROSLab
|
2a6a295b71d4c73bc5c6ae2ec0330274afa31d0d
|
[
"Apache-2.0"
] | 3 |
2016-10-05T07:20:30.000Z
|
2017-11-20T10:36:50.000Z
|
from api.component import Component
class Ant(Component):
def defComponents(self):
self.addSubcomponent("brain", "Brains", inherit=True, prefix=None)
self.addSubcomponent("front", "LegPair", inherit=True, prefix=None)
self.addSubcomponent("back", "LegPair", inherit=True, prefix=None)
def defParameters(self):
self.delParameter("width")
def defConstraints(self):
self.addConstraint(("front", "width"), ("brain", "servo"), "x[0].getParameter('width') + \
x[1].getParameter('motorheight') * 2")
self.addConstraint(("back", "width"), ("brain", "servo"), "x[0].getParameter('width') + \
x[1].getParameter('motorheight') * 2")
def defConnections(self):
self.addConnection(("brain", "botright"),
("front", "topedge.1"),
"Fold",
angle=-180)
self.addConnection(("brain", "topleft"),
("back", "topedge.1"),
"Fold",
angle=-180)
self.addConnection(("front", "botedge.2"),
("back", "topedge.3"),
"Tab",
name="tabfront", depth=9)
self.addConnection(("back", "botedge.2"),
("front", "topedge.3"),
"Tab",
name="tabback", depth=9)
if __name__ == "__main__":
f = Ant()
f.toYaml("output/ant.yaml")
from utils.dimensions import tgy1370a, proMini
f.setParameter("servo", tgy1370a)
f.setParameter("brain", proMini)
f.setParameter("length", 48)
f.setParameter("height", 25)
f.setParameter("leg.beamwidth", 10)
f.makeOutput("output/ant", display=True)
| 37.583333 | 101 | 0.517738 |
dec08e4b05b41dd81d160d7e41ed3c728b977af9
| 1,383 |
py
|
Python
|
python/oneflow/utils/vision/__init__.py
|
wangyuyue/oneflow
|
0a71c22fe8355392acc8dc0e301589faee4c4832
|
[
"Apache-2.0"
] | 3,285 |
2020-07-31T05:51:22.000Z
|
2022-03-31T15:20:16.000Z
|
python/oneflow/utils/vision/__init__.py
|
wangyuyue/oneflow
|
0a71c22fe8355392acc8dc0e301589faee4c4832
|
[
"Apache-2.0"
] | 2,417 |
2020-07-31T06:28:58.000Z
|
2022-03-31T23:04:14.000Z
|
python/oneflow/utils/vision/__init__.py
|
wangyuyue/oneflow
|
0a71c22fe8355392acc8dc0e301589faee4c4832
|
[
"Apache-2.0"
] | 520 |
2020-07-31T05:52:42.000Z
|
2022-03-29T02:38:11.000Z
|
"""
Copyright 2020 The OneFlow Authors. All rights reserved.
Licensed 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 oneflow.utils.vision import datasets
from oneflow.utils.vision import transforms
_image_backend = "PIL"
def set_image_backend(backend):
"""
Specifies the package used to load images.
Args:
backend (string): Name of the image backend. one of {'PIL', 'accimage'}.
The :mod:`accimage` package uses the Intel IPP library. It is
generally faster than PIL, but does not support as many operations.
"""
global _image_backend
if backend not in ["PIL", "accimage"]:
raise ValueError(
"Invalid backend '{}'. Options are 'PIL' and 'accimage'".format(backend)
)
_image_backend = backend
def get_image_backend():
"""
Gets the name of the package used to load images
"""
return _image_backend
| 32.162791 | 84 | 0.710774 |
72181adc745c56619ee60682e9432eea3a374283
| 92 |
py
|
Python
|
2015/02/nurse-injury-rates/graphic_config.py
|
nprapps/graphics-archive
|
97b0ef326b46a959df930f5522d325e537f7a655
|
[
"FSFAP"
] | 14 |
2015-05-08T13:41:51.000Z
|
2021-02-24T12:34:55.000Z
|
2015/02/nurse-injury-rates/graphic_config.py
|
nprapps/graphics-archive
|
97b0ef326b46a959df930f5522d325e537f7a655
|
[
"FSFAP"
] | null | null | null |
2015/02/nurse-injury-rates/graphic_config.py
|
nprapps/graphics-archive
|
97b0ef326b46a959df930f5522d325e537f7a655
|
[
"FSFAP"
] | 7 |
2015-04-04T04:45:54.000Z
|
2021-02-18T11:12:48.000Z
|
#!/usr/bin/env python
COPY_GOOGLE_DOC_KEY = '1assIFoHbgfYcQ-OdFmm2q7ia2VaGQwrdZ5NmhoKImOk'
| 23 | 68 | 0.836957 |
a0f19af25be558d43e8977913bf66c771223f953
| 1,121 |
py
|
Python
|
Lab_02/fib.py
|
SadequrRahman/advance-SoC
|
35da93adfcdb1b4ec740cb44ffc54d9c8cc7adc4
|
[
"BSD-4-Clause-UC"
] | null | null | null |
Lab_02/fib.py
|
SadequrRahman/advance-SoC
|
35da93adfcdb1b4ec740cb44ffc54d9c8cc7adc4
|
[
"BSD-4-Clause-UC"
] | null | null | null |
Lab_02/fib.py
|
SadequrRahman/advance-SoC
|
35da93adfcdb1b4ec740cb44ffc54d9c8cc7adc4
|
[
"BSD-4-Clause-UC"
] | null | null | null |
#
# Copyright (C) 2019 Mohammad Sadequr Rahman <[email protected]>
#
# This file is part of Advance SoC Design Lab Soultion.
#
# SoC Design Lab Soultion can not be copied and/or distributed without the express
# permission of Mohammad Sadequr Rahman
#
# File: fib.py
# This is a pymtl fibonacci gloden algorithm implementation in pymtl3.
#
# Outputs:
# out -> output of the block. contain fibonacci result fo 'n'
#
from pymtl3 import *
class add(Component):
def construct(s, Type):
s.inl = InPort (Type)
s.inr = InPort (Type)
s.out = OutPort(Type)
@s.update
def add():
s.out = s.inl + s.inr
class Fib( Component ):
def construct(s, dType, n):
#s.in_ = InPort(dType)
s.out = OutPort(dType)
if n < 2 :
s.out //= dType(n)
return
else:
s.t1 = n - 1
s.t2 = n - 2
s.l = Fib(dType, s.t1)
s.r = Fib(dType, s.t2)
s.f = add(dType)
s.f.inl //= s.l.out
s.f.inr //= s.r.out
s.f.out //= s.out
return
| 21.557692 | 82 | 0.540589 |
261e85d58df7266cfd7e58e24f7b48125975f239
| 1,171 |
py
|
Python
|
chemolab/core/unicode.py
|
MeleiDigitalMedia/ChemoLab
|
b27421a836d76de88b23845f6c808d4429925702
|
[
"MIT"
] | null | null | null |
chemolab/core/unicode.py
|
MeleiDigitalMedia/ChemoLab
|
b27421a836d76de88b23845f6c808d4429925702
|
[
"MIT"
] | null | null | null |
chemolab/core/unicode.py
|
MeleiDigitalMedia/ChemoLab
|
b27421a836d76de88b23845f6c808d4429925702
|
[
"MIT"
] | null | null | null |
class SubScript():
"""Creates an instance of SubScript"""
def __init__(self):
self.NUM_0 = u'\u2080'
self.NUM_1 = u'\u2081'
self.NUM_2 = u'\u2082'
self.NUM_3 = u'\u2083'
self.NUM_4 = u'\u2084'
self.NUM_5 = u'\u2085'
self.NUM_6 = u'\u2086'
self.NUM_7 = u'\u2087'
self.NUM_8 = u'\u2088'
self.NUM_9 = u'\u2089'
self.PLUS = u'\u208a'
self.MINUS = u'\u208b'
self.EQUALS = u'\u208c'
self.L_PAR = u'\u208d'
self.R_PAR = u'\u208e'
class SuperScript():
"""Creates an instance of SuperScript"""
def __init__(self):
self.NUM_0 = u'\u2070'
self.NUM_1 = u'\u00b9'
self.NUM_2 = u'\u00b2'
self.NUM_3 = u'\u00b3'
self.NUM_4 = u'\u2074'
self.NUM_5 = u'\u2075'
self.NUM_6 = u'\u2076'
self.NUM_7 = u'\u2077'
self.NUM_8 = u'\u2078'
self.NUM_9 = u'\u2079'
self.PLUS = u'\u207a'
self.MINUS = u'\u207b'
self.EQUALS = u'\u207c'
self.L_PAR = u'\u207d'
self.R_PAR = u'\u207e'
| 31.648649 | 45 | 0.485056 |
26bb10f45a5b4f95ec9fcb604d781837ada01030
| 345 |
py
|
Python
|
init.py
|
two-doges/tpf
|
a98f68fba40b3f07ce0ef14f6ca982e915ee3e07
|
[
"MIT"
] | 2 |
2018-03-04T13:36:22.000Z
|
2018-03-04T13:36:33.000Z
|
init.py
|
two-doges/tpf
|
a98f68fba40b3f07ce0ef14f6ca982e915ee3e07
|
[
"MIT"
] | null | null | null |
init.py
|
two-doges/tpf
|
a98f68fba40b3f07ce0ef14f6ca982e915ee3e07
|
[
"MIT"
] | null | null | null |
import os
import sys
sys.path.append("..")
import dataoper
def initall():
pat = "devhost"
fp = open("devdata.py","w+")
s = str(os.getcwd())
fp.write('dir = '+'"'+s+'/'+pat+'"'+'\n')
fp.write('pos = '+'"'+s+'/'+"devdata"+'"')
dataoper.make_table(pat)
if __name__ == "__main__":
dataoper.delete_table()
initall()
| 20.294118 | 46 | 0.553623 |
90320414d5545b38764cd72587480188bd9c886c
| 422 |
py
|
Python
|
python/en/_numpy/organize_this/test_numpy.Quickstart_tutorial-03.py
|
aimldl/coding
|
70ddbfaa454ab92fd072ee8dc614ecc330b34a70
|
[
"MIT"
] | null | null | null |
python/en/_numpy/organize_this/test_numpy.Quickstart_tutorial-03.py
|
aimldl/coding
|
70ddbfaa454ab92fd072ee8dc614ecc330b34a70
|
[
"MIT"
] | null | null | null |
python/en/_numpy/organize_this/test_numpy.Quickstart_tutorial-03.py
|
aimldl/coding
|
70ddbfaa454ab92fd072ee8dc614ecc330b34a70
|
[
"MIT"
] | null | null | null |
"""
test_numpy.Quickstart_tutorial-03.py
* References
Quickstart tutorial
https://docs.scipy.org/doc/numpy/user/quickstart.html
TODO: Start from
A frequent error consists in calling array with multiple numeric
"""
import numpy as np
a = np.array( [2,3,4] )
"""
>>> a
array([2, 3, 4])
>>> a.dtype
dtype('int64')
>>> a.dtype.name
'int64'
"""
b = np.array( [1.2, 3.5, 5.1] )
"""
>>> b.dtype
dtype('float64')
"""
| 14.066667 | 65 | 0.63981 |
840e3e92339d6c3635dffee4c74621caca209267
| 94 |
py
|
Python
|
python_lessons/freecodecamp_python/014_dict_object_d_for_in_print.py
|
1986MMartin/coding-sections-markus
|
e13be32e5d83e69250ecfb3c76a04ee48a320607
|
[
"Apache-2.0"
] | null | null | null |
python_lessons/freecodecamp_python/014_dict_object_d_for_in_print.py
|
1986MMartin/coding-sections-markus
|
e13be32e5d83e69250ecfb3c76a04ee48a320607
|
[
"Apache-2.0"
] | null | null | null |
python_lessons/freecodecamp_python/014_dict_object_d_for_in_print.py
|
1986MMartin/coding-sections-markus
|
e13be32e5d83e69250ecfb3c76a04ee48a320607
|
[
"Apache-2.0"
] | null | null | null |
d = dict()
d['quincy'] = 1
d['beau'] = 5
d['kris'] = 9
for (k,i) in d.items():
print(k, i)
| 15.666667 | 23 | 0.478723 |
4b974cf32caa7c6b6283e803dcfb8044ee9063ed
| 9,140 |
py
|
Python
|
SAC2018/SAC.py
|
Wen2chao/RL-Algorithm-
|
6cb31f2e02a90fceef498c7ee46a4d06eb976005
|
[
"MIT"
] | 19 |
2020-06-09T07:48:10.000Z
|
2022-03-27T04:52:36.000Z
|
SAC2018/SAC.py
|
Wen2chao/RL-Algorithm-
|
6cb31f2e02a90fceef498c7ee46a4d06eb976005
|
[
"MIT"
] | 1 |
2020-09-17T07:39:35.000Z
|
2021-08-02T02:31:52.000Z
|
SAC2018/SAC.py
|
Wen2chao/RL-Algorithm-
|
6cb31f2e02a90fceef498c7ee46a4d06eb976005
|
[
"MIT"
] | 12 |
2020-03-28T08:19:26.000Z
|
2022-03-21T11:08:08.000Z
|
import gym
import torch
import random
import torch.nn as nn
import collections
import numpy as np
import torch.nn.functional as F
import torch.optim as optim
import matplotlib.pyplot as plt
from torch.distributions import Normal
class ReplayBeffer():
def __init__(self, buffer_maxlen):
self.buffer = collections.deque(maxlen=buffer_maxlen)
def push(self, data):
self.buffer.append(data)
def sample(self, batch_size):
state_list = []
action_list = []
reward_list = []
next_state_list = []
done_list = []
batch = random.sample(self.buffer, batch_size)
for experience in batch:
s, a, r, n_s, d = experience
# state, action, reward, next_state, done
state_list.append(s)
action_list.append(a)
reward_list.append(r)
next_state_list.append(n_s)
done_list.append(d)
return torch.FloatTensor(state_list).to(device), \
torch.FloatTensor(action_list).to(device), \
torch.FloatTensor(reward_list).unsqueeze(-1).to(device), \
torch.FloatTensor(next_state_list).to(device), \
torch.FloatTensor(done_list).unsqueeze(-1).to(device)
def buffer_len(self):
return len(self.buffer)
# Value Net
class ValueNet(nn.Module):
def __init__(self, state_dim, edge=3e-3):
super(ValueNet, self).__init__()
self.linear1 = nn.Linear(state_dim, 256)
self.linear2 = nn.Linear(256, 256)
self.linear3 = nn.Linear(256, 1)
self.linear3.weight.data.uniform_(-edge, edge)
self.linear3.bias.data.uniform_(-edge, edge)
def forward(self, state):
x = F.relu(self.linear1(state))
x = F.relu(self.linear2(x))
x = self.linear3(x)
return x
# Soft Q Net
class SoftQNet(nn.Module):
def __init__(self, state_dim, action_dim, edge=3e-3):
super(SoftQNet, self).__init__()
self.linear1 = nn.Linear(state_dim + action_dim, 256)
self.linear2 = nn.Linear(256, 256)
self.linear3 = nn.Linear(256, 1)
self.linear3.weight.data.uniform_(-edge, edge)
self.linear3.bias.data.uniform_(-edge, edge)
def forward(self, state, action):
x = torch.cat([state, action], 1)
x = F.relu(self.linear1(x))
x = F.relu(self.linear2(x))
x = self.linear3(x)
return x
# Policy Net
class PolicyNet(nn.Module):
def __init__(self, state_dim, action_dim, log_std_min=-20, log_std_max=2, edge=3e-3):
super(PolicyNet, self).__init__()
self.log_std_min = log_std_min
self.log_std_max = log_std_max
self.linear1 = nn.Linear(state_dim, 256)
self.linear2 = nn.Linear(256, 256)
self.mean_linear = nn.Linear(256, action_dim)
self.mean_linear.weight.data.uniform_(-edge, edge)
self.mean_linear.bias.data.uniform_(-edge, edge)
self.log_std_linear = nn.Linear(256, action_dim)
self.log_std_linear.weight.data.uniform_(-edge, edge)
self.log_std_linear.bias.data.uniform_(-edge, edge)
def forward(self, state):
x = F.relu(self.linear1(state))
x = F.relu(self.linear2(x))
mean = self.mean_linear(x)
log_std = self.log_std_linear(x)
log_std = torch.clamp(log_std, self.log_std_min, self.log_std_max)
return mean, log_std
def action(self, state):
state = torch.FloatTensor(state).to(device)
mean, log_std = self.forward(state)
std = log_std.exp()
normal = Normal(mean, std)
z = normal.sample()
action = torch.tanh(z).detach().cpu().numpy()
return action
# Use re-parameterization tick
def evaluate(self, state, epsilon=1e-6):
mean, log_std = self.forward(state)
std = log_std.exp()
normal = Normal(mean, std)
noise = Normal(0, 1)
z = noise.sample()
action = torch.tanh(mean + std * z.to(device))
log_prob = normal.log_prob(mean + std * z.to(device)) - torch.log(1 - action.pow(2) + epsilon)
return action, log_prob
class SAC:
def __init__(self, env, gamma, tau, buffer_maxlen, value_lr, q_lr, policy_lr):
self.env = env
self.state_dim = env.observation_space.shape[0]
self.action_dim = env.action_space.shape[0]
# hyperparameters
self.gamma = gamma
self.tau = tau
# initialize networks
self.value_net = ValueNet(self.state_dim).to(device)
self.target_value_net = ValueNet(self.state_dim).to(device)
self.q1_net = SoftQNet(self.state_dim, self.action_dim).to(device)
self.q2_net = SoftQNet(self.state_dim, self.action_dim).to(device)
self.policy_net = PolicyNet(self.state_dim, self.action_dim).to(device)
# Load the target value network parameters
for target_param, param in zip(self.target_value_net.parameters(), self.value_net.parameters()):
target_param.data.copy_(self.tau * param + (1 - self.tau) * target_param)
# Initialize the optimizer
self.value_optimizer = optim.Adam(self.value_net.parameters(), lr=value_lr)
self.q1_optimizer = optim.Adam(self.q1_net.parameters(), lr=q_lr)
self.q2_optimizer = optim.Adam(self.q2_net.parameters(), lr=q_lr)
self.policy_optimizer = optim.Adam(self.policy_net.parameters(), lr=policy_lr)
# Initialize thebuffer
self.buffer = ReplayBeffer(buffer_maxlen)
def get_action(self, state):
action = self.policy_net.action(state)
return action
def update(self, batch_size):
state, action, reward, next_state, done = self.buffer.sample(batch_size)
new_action, log_prob = self.policy_net.evaluate(state)
# V value loss
value = self.value_net(state)
new_q1_value = self.q1_net(state, new_action)
new_q2_value = self.q2_net(state, new_action)
next_value = torch.min(new_q1_value, new_q2_value) - log_prob
value_loss = F.mse_loss(value, next_value.detach())
# Soft q loss
q1_value = self.q1_net(state, action)
q2_value = self.q2_net(state, action)
target_value = self.target_value_net(next_state)
target_q_value = reward + done * self.gamma * target_value
q1_value_loss = F.mse_loss(q1_value, target_q_value.detach())
q2_value_loss = F.mse_loss(q2_value, target_q_value.detach())
# Policy loss
policy_loss = (log_prob - torch.min(new_q1_value, new_q2_value)).mean()
# Update Policy
self.policy_optimizer.zero_grad()
policy_loss.backward()
self.policy_optimizer.step()
# Update v
self.value_optimizer.zero_grad()
value_loss.backward()
self.value_optimizer.step()
# Update Soft q
self.q1_optimizer.zero_grad()
self.q2_optimizer.zero_grad()
q1_value_loss.backward()
q2_value_loss.backward()
self.q1_optimizer.step()
self.q2_optimizer.step()
# Update target networks
for target_param, param in zip(self.target_value_net.parameters(), self.value_net.parameters()):
target_param.data.copy_(self.tau * param + (1 - self.tau) * target_param)
def main(env, agent, Episode, batch_size):
Return = []
action_range = [env.action_space.low, env.action_space.high]
for episode in range(Episode):
score = 0
state = env.reset()
for i in range(300):
action = agent.get_action(state)
# action output range[-1,1],expand to allowable range
action_in = action * (action_range[1] - action_range[0]) / 2.0 + (action_range[1] + action_range[0]) / 2.0
next_state, reward, done, _ = env.step(action_in)
done_mask = 0.0 if done else 1.0
agent.buffer.push((state, action, reward, next_state, done_mask))
state = next_state
score += reward
if done:
break
if agent.buffer.buffer_len() > 500:
agent.update(batch_size)
print("episode:{}, Return:{}, buffer_capacity:{}".format(episode, score, agent.buffer.buffer_len()))
Return.append(score)
score = 0
env.close()
plt.plot(Return)
plt.ylabel('Return')
plt.xlabel("Episode")
plt.grid(True)
plt.show()
if __name__ == '__main__':
env = gym.make("Pendulum-v0")
device = torch.device("cuda:1" if torch.cuda.is_available() else "cpu")
# Params
tau = 0.01
gamma = 0.99
q_lr = 3e-3
value_lr = 3e-3
policy_lr = 3e-3
buffer_maxlen = 50000
Episode = 100
batch_size = 128
agent = SAC(env, gamma, tau, buffer_maxlen, value_lr, q_lr, policy_lr)
main(env, agent, Episode, batch_size)
| 33.726937 | 121 | 0.609409 |
4b165c49280c7f812571921ae83d0c505571bf4d
| 10,637 |
py
|
Python
|
GZP_GTO_QGIS/INSTALLATION/GeoTaskOrganizer/gto_remote.py
|
msgis/swwat-gzp-template
|
080afbe9d49fb34ed60ba45654383d9cfca01e24
|
[
"MIT"
] | 3 |
2019-06-18T15:28:09.000Z
|
2019-07-11T07:31:45.000Z
|
GZP_GTO_QGIS/INSTALLATION/GeoTaskOrganizer/gto_remote.py
|
msgis/swwat-gzp-template
|
080afbe9d49fb34ed60ba45654383d9cfca01e24
|
[
"MIT"
] | 2 |
2019-07-11T14:03:25.000Z
|
2021-02-08T16:14:04.000Z
|
GZP_GTO_QGIS/INSTALLATION/GeoTaskOrganizer/gto_remote.py
|
msgis/swwat-gzp-template
|
080afbe9d49fb34ed60ba45654383d9cfca01e24
|
[
"MIT"
] | 1 |
2019-06-12T11:07:37.000Z
|
2019-06-12T11:07:37.000Z
|
#!/usr/bin/python
# -*- coding: utf-8 -*-
from builtins import str
from PyQt5.QtCore import Qt,QObject,QFileSystemWatcher
#from PyQt5.QtGui import *
import os
import json
import io
from qgis.core import QgsProject,QgsFeatureRequest
from .gto_info import gtoInfo
class gtoRemote(QObject):
def __init__(self, gtomain, parent = None):
try:
super(gtoRemote, self).__init__(parent)
self.gtomain = gtomain
self.iface = gtomain.iface
self.debug = gtomain.debug
self.info = gtoInfo(self)
self.fs_watcher =None
if 'remote_watch_file' in gtomain.settings:
remote_watch_path = gtomain.settings.get('remote_watch_file',None)
if remote_watch_path is not None and remote_watch_path != "":
remote_watch_path = self.gtomain.helper.getFilePath(remote_watch_path)
self.remote_watch_file = os.path.basename(remote_watch_path)
self.remote_watch_dir = os.path.dirname(remote_watch_path)
if self.debug: self.info.log("Watching:",self.remote_watch_dir)
if not os.path.exists(self.remote_watch_dir):
os.makedirs(self.remote_watch_dir)
if self.debug: self.info.log("Created:",self.remote_watch_dir)
self.paths = [self.remote_watch_dir]
self.fs_watcher = QFileSystemWatcher(self.paths)
#if file already exists
self.directory_changed(self.paths[0])
self.fs_watcher.directoryChanged.connect(self.directory_changed)
self.fs_watcher.fileChanged.connect(self.file_changed)
except Exception as e:
self.info.err(e)
def unload(self):
try:
if self.fs_watcher is not None:
self.fs_watcher.directoryChanged.disconnect()
self.fs_watcher.fileChanged.disconnect()
self.fs_watcher = None
except Exception as e:
self.info.err(e)
def directory_changed(self,path):
try:
if self.debug: self.info.log('Directory Changed: %s' % path)
for f in os.listdir(path):
#self.info.log(os.listdir(path))
#if (self.debug and f.lower().endswith(".json")) or f.lower() == self.remote_watch_file.lower():
if f.lower() == self.remote_watch_file.lower():
if self.debug: self.info.log("Execute",f.lower())
self.fs_watcher.blockSignals(True)
self.excuteCommand(path,f)
self.fs_watcher.blockSignals(False)
except Exception as e:
self.info.err(e)
def file_changed(self,path):
try:
if self.debug: self.info.log('File Changed: %s' % path)
except Exception as e:
self.info.err(e)
def excuteCommand(self,path,f):
try:
if self.debug: self.info.log('excute command')
filename = path + '/' + f
#time.sleep(0.5)
f = io.open(filename, encoding='utf-8')
jdata = json.load(f)
f.close()
res = True
for cmd in jdata['commands']:
if self.debug: self.info.log(cmd)
method = getattr(self, cmd['ecommand'])
res = res and (method(self.gtomain, self.debug, **cmd['config']))
if self.debug: self.info.log('result:', res)
if res:
os.remove(filename)
except Exception as e:
self.info.err(e)
def writeRemoteFile(self,jdata,prefix = ''):
try:
if self.debug: self.info.log('writeRemoteFile:', 'data:', jdata)
remotefile = self.gtomain.settings['remote_file']
remotefile = self.gtomain.helper.getFilePath(remotefile, True)
remotefile = '%s%s' % (remotefile,prefix)
if self.debug: self.info.log("remotefile",remotefile)
# write the file
# from io import StringIO
# io = StringIO()
# json.dump(jdata,io,ensure_ascii=False, sort_keys=True,indent=4)
# io.close()
with open(remotefile, 'w',encoding='utf8') as outfile:
sort =True
#simplejson.dump(jdata, outfile,ensure_ascii=False, sort_keys=sort,indent=4)#,encoding='utf8')#.encode('utf8')
json.dump(jdata, outfile, ensure_ascii=False, sort_keys=sort, indent=4) # ,encoding='utf8')#.encode('utf8')
# import pickle
# with open(remotefile, 'wb') as f:
# pickle.dump(jdata,f)
#activate/start remote app
if self.debug: self.info.log('writeRemoteFile:', 'settings:', self.gtomain.settings)
remote_app_file = self.gtomain.settings['remote_app_file']
remote_app_title = self.gtomain.settings['remote_app_title']
if os.name == 'nt':
try:
from .gto_windows import ActivateApp
ActivateApp(self.gtomain, self.debug, remote_app_title, remote_app_file)
except Exception as e:
self.info.err(e)
else:
os.startfile(remote_app_file)
except Exception as e:
self.info.err(e)
def getLayerByName(self,layername):
try:
layers = QgsProject.instance().mapLayersByName(layername)
if layers:
return layers[0]# duplicte names => take the first
else:
return None
except Exception as e:
self.info.err(e)
def getFeatures(self, gtoobj, debug, **kwargs):
try:
if self.debug: self.info.log('getFeatures:', 'parameters:', kwargs)
layername = kwargs['objectclass']
layer = self.getLayerByName(layername)
request = QgsFeatureRequest()
if 'whereclause' in kwargs:
whereclause = kwargs['whereclause']
request.setFilterExpression(whereclause)
elif 'attribute' in kwargs:
attribute = kwargs['attribute']
values = kwargs['data']
expr_in = ''
for v in values:
expr_in = expr_in + '%s ,' % str(v)
expr_in = expr_in[:-1]
expr = '"' + attribute + '" IN (%s)' % expr_in
if self.debug: self.info.log("expr: %s" % expr)
request.setFilterExpression(expr)
features = layer.getFeatures(request)
ids = [f.id() for f in features]
if self.debug: self.info.log("res from request ids:",layer, ids)
return layer, ids
except Exception as e:
gtoobj.info.err(e)
def ZOOMTOFEATURESET(self,gtoobj,debug,**kwargs):
try:
scale = kwargs.get('scale',0)
iface = gtoobj.iface
layer, ids = self.getFeatures(gtoobj,debug,**kwargs)
iface.setActiveLayer(layer)
prj = QgsProject.instance()
prj.layerTreeRoot().findLayer(layer.id()).setItemVisibilityCheckedParentRecursive(True)
#legend.setCurrentLayer(layer)
#legend.setLayerVisible(layer, True)
layer.selectByIds(ids)
iface.mapCanvas().zoomToSelected()
if scale > 0:
iface.mapCanvas().zoomScale(scale)
return True
except Exception as e:
gtoobj.info.err(e)
def SETSELECTSET(self,gtoobj,debug,**kwargs):
try:
iface = gtoobj.iface
layer, ids = self.getFeatures(gtoobj,debug,**kwargs)
layer.removeSelection()
layer.selectByIds(ids)
self.iface.mapCanvas().refresh()
return True
except Exception as e:
gtoobj.info.err(e)
def GETCOORDINATE(self,gtoobj,debug,**kwargs):
try:
objclass = kwargs['objectclass']
id = kwargs['id']
esubcommand = kwargs['esubcommand']
iface = gtoobj.iface
from qgis.gui import QgsMapToolEmitPoint
# create tool
prevTool = iface.mapCanvas().mapTool()
curTool = QgsMapToolEmitPoint(iface.mapCanvas())
def on_click(coordinate, clickedMouseButton):
if debug: gtoobj.info.log("Coordinate:", coordinate)
if clickedMouseButton == Qt.LeftButton:
if esubcommand == 'GETCOORDINATE_ID':
#jdata = {"commands": [{"ecommand": "SETCOORDINATE", "config": {"esubcommand": "SETCOORDINATE_ID","objectclass": objclass.encode('utf8'),"id":id, "x": round( coordinate.x(),3),"y":round(coordinate.y(),3)}}]}
jdata = {"commands": [{"ecommand": "SETCOORDINATE",
"config": {"esubcommand": "SETCOORDINATE_ID",
"objectclass": objclass, "id": id,
"x": round(coordinate.x(), 3),
"y": round(coordinate.y(), 3)}}]}
self.writeRemoteFile(jdata)
if debug: self.info.log("Set prev tool:", prevTool.toolName())
if prevTool is curTool:
iface.mapCanvas().setMapTool(None)
else:
iface.mapCanvas().setMapTool(prevTool)
else:
if debug: self.info.log('Unknown esubcommand:',esubcommand)
def tool_changed(tool): # another tool was activated
iface.mapCanvas().mapToolSet.disconnect(tool_changed)
#curTool.deleteLater()
curTool.canvasClicked.connect(on_click)
iface.mapCanvas().setMapTool(curTool)
iface.mapCanvas().mapToolSet.connect(tool_changed)
return True
except Exception as e:
gtoobj.info.err(e)
def getSelectedFeatures(self,gtoobj, debug, layer,attribute):
try:
data = []
for f in layer.selectedFeatures():
val = f[attribute]
try:
if int(val) == val: val = int(val)
except:
pass
data.append("%s" % str(val))
return data
except Exception as e:
gtoobj.info.err(e)
| 42.043478 | 231 | 0.540378 |
4b2694efc137f8ec6d32dfa08a19037c42e42cdd
| 3,457 |
py
|
Python
|
accounts/forms.py
|
JanakiRaman-2002/Arre-yaar
|
c0b44ca1f8884a09116241dcd0bf7cfcee3b785d
|
[
"Apache-2.0"
] | null | null | null |
accounts/forms.py
|
JanakiRaman-2002/Arre-yaar
|
c0b44ca1f8884a09116241dcd0bf7cfcee3b785d
|
[
"Apache-2.0"
] | null | null | null |
accounts/forms.py
|
JanakiRaman-2002/Arre-yaar
|
c0b44ca1f8884a09116241dcd0bf7cfcee3b785d
|
[
"Apache-2.0"
] | null | null | null |
from django import forms
from django.contrib.auth.models import User
from django.contrib.auth.forms import UserCreationForm,AuthenticationForm
from django.forms.widgets import TextInput, Textarea
from .models import *
class UserForm(forms.Form):
# class Meta:
# model = User
# fields = ('username','email','password1','password2')
username = forms.CharField(max_length=50, required=True, widget=forms.TextInput(
attrs= {
'class': "u-border-1 u-border-grey-30 u-custom-font u-font-montserrat u-input u-input-rectangle u-radius-17 u-white",
'placeholder': "Enter an Username",
'id':"name-e91f",
'name':"usernameda"
}
))
email = forms.CharField(max_length=50, required=True, widget = forms.TextInput(
attrs = {
'class':"u-border-1 u-border-grey-30 u-custom-font u-font-montserrat u-input u-input-rectangle u-radius-17 u-white",
'name':"email",
'id':"email-e91f",
'placeholder':"Enter a valid email address",
'type':"email"
}
))
password1 = forms.CharField(required=True, widget = forms.PasswordInput(
attrs= {
'placeholder':"Enter a password",
'id':"text-e114",
'name':"pass1",
'class':"u-border-1 u-border-grey-30 u-custom-font u-font-montserrat u-input u-input-rectangle u-radius-17 u-white"
}
))
password2 = forms.CharField(required=True, widget = forms.PasswordInput(
attrs= {
'placeholder':"Confirm Password",
'id':"text-e114",
'name':"pass1",
'class':"u-border-1 u-border-grey-30 u-custom-font u-font-montserrat u-input u-input-rectangle u-radius-17 u-white"
}
))
class CustomerForm(forms.Form):
address = forms.CharField(required=True, widget = forms.Textarea(
attrs= {
'rows':"4",
'cols':"50",
'id':"textarea-6b48",
'name':"address",
'class':"u-border-1 u-border-grey-30 u-custom-font u-font-montserrat u-input u-input-rectangle u-radius-17 u-white",
'placeholder':'Enter Delivery Address'
}
))
phone_no = forms.CharField(required = True, widget= forms.TextInput(
attrs = {
'pattern':"\+?\d{0,3}[\s\(\-]?([0-9]{2,3})[\s\)\-]?([\s\-]?)([0-9]{3})[\s\-]?([0-9]{2})[\s\-]?([0-9]{2})",
'placeholder':"Enter your phone number",
'id':"phone-d55a",
'name':"phone",
'class':"u-border-1 u-border-grey-30 u-custom-font u-font-montserrat u-input u-input-rectangle u-radius-17 u-white"
}
))
class Loginform(AuthenticationForm):
username = forms.CharField(widget = forms.TextInput(
attrs = {
'placeholder':"Enter Username",
'id':"name-e91f",
'name':"usernameda",
'class':"u-border-1 u-border-grey-30 u-custom-font u-font-montserrat u-input u-input-rectangle u-radius-17 u-white",
'required':"required"
}))
password = forms.CharField(widget = forms.PasswordInput(
attrs = {
'placeholder':"Enter Password",
'id':"text-6e34",
'name':"passwordda",
'class':"u-border-1 u-border-grey-30 u-custom-font u-font-montserrat u-input u-input-rectangle u-radius-17 u-white",
'required':"required"
}))
| 41.650602 | 129 | 0.57304 |
8ad3d7138e5cc42b191ab7f7b90915eb7d6894bf
| 1,090 |
py
|
Python
|
research/cv/SRGAN/src/loss/psnr_loss.py
|
leelige/mindspore
|
5199e05ba3888963473f2b07da3f7bca5b9ef6dc
|
[
"Apache-2.0"
] | 77 |
2021-10-15T08:32:37.000Z
|
2022-03-30T13:09:11.000Z
|
research/cv/SRGAN/src/loss/psnr_loss.py
|
leelige/mindspore
|
5199e05ba3888963473f2b07da3f7bca5b9ef6dc
|
[
"Apache-2.0"
] | 3 |
2021-10-30T14:44:57.000Z
|
2022-02-14T06:57:57.000Z
|
research/cv/SRGAN/src/loss/psnr_loss.py
|
leelige/mindspore
|
5199e05ba3888963473f2b07da3f7bca5b9ef6dc
|
[
"Apache-2.0"
] | 24 |
2021-10-15T08:32:45.000Z
|
2022-03-24T18:45:20.000Z
|
# Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed 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.
# ============================================================================
"""PSNRLOSS"""
import mindspore.nn as nn
class PSNRLoss(nn.Cell):
"""Loss for srresnet"""
def __init__(self, generator):
super(PSNRLoss, self).__init__()
self.generator = generator
self.pixel_criterion = nn.MSELoss()
def construct(self, HR_img, LR_img):
hr = HR_img
sr = self.generator(LR_img)
psnr_loss = self.pixel_criterion(hr, sr)
return psnr_loss
| 35.16129 | 78 | 0.658716 |
6ae2efdb4e7a2f5616ad6b4dce2044e09d204517
| 3,293 |
py
|
Python
|
research/inference.py
|
jieming2002/models-quiz8
|
421dc407a10444cab4bd88c25599077acca96bdb
|
[
"Apache-2.0"
] | null | null | null |
research/inference.py
|
jieming2002/models-quiz8
|
421dc407a10444cab4bd88c25599077acca96bdb
|
[
"Apache-2.0"
] | null | null | null |
research/inference.py
|
jieming2002/models-quiz8
|
421dc407a10444cab4bd88c25599077acca96bdb
|
[
"Apache-2.0"
] | null | null | null |
import argparse
import os
import numpy as np
import tensorflow as tf
from matplotlib import pyplot as plt
from PIL import Image
from utils import visualization_utils as vis_util
from utils import label_map_util
if tf.__version__ < '1.4.0':
raise ImportError('Please upgrade your tensorflow installation to v1.4.* or later!')
NUM_CLASSES = 5
def parse_args(check=True):
parser = argparse.ArgumentParser()
parser.add_argument('--output_dir', type=str, required=True)
parser.add_argument('--dataset_dir', type=str, required=True)
FLAGS, unparsed = parser.parse_known_args()
return FLAGS, unparsed
if __name__ == '__main__':
FLAGS, unparsed = parse_args()
PATH_TO_CKPT = os.path.join(FLAGS.output_dir, 'exported_graphs/frozen_inference_graph.pb')
PATH_TO_LABELS = os.path.join(FLAGS.dataset_dir, 'labels_items.txt')
detection_graph = tf.Graph()
with detection_graph.as_default():
od_graph_def = tf.GraphDef()
with tf.gfile.GFile(PATH_TO_CKPT, 'rb') as fid:
serialized_graph = fid.read()
od_graph_def.ParseFromString(serialized_graph)
tf.import_graph_def(od_graph_def, name='')
label_map = label_map_util.load_labelmap(PATH_TO_LABELS)
categories = label_map_util.convert_label_map_to_categories(label_map, max_num_classes=NUM_CLASSES, use_display_name=True)
category_index = label_map_util.create_category_index(categories)
def load_image_into_numpy_array(image):
(im_width, im_height) = image.size
return np.array(image.getdata()).reshape(
(im_height, im_width, 3)).astype(np.uint8)
test_img_path = os.path.join(FLAGS.dataset_dir, 'test.jpg')
with detection_graph.as_default():
with tf.Session(graph=detection_graph) as sess:
image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
detection_boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
detection_scores = detection_graph.get_tensor_by_name('detection_scores:0')
detection_classes = detection_graph.get_tensor_by_name('detection_classes:0')
num_detections = detection_graph.get_tensor_by_name('num_detections:0')
image = Image.open(test_img_path)
image_np = load_image_into_numpy_array(image)
image_np_expanded = np.expand_dims(image_np, axis=0)
(boxes, scores, classes, num) = sess.run(
[detection_boxes, detection_scores, detection_classes, num_detections],
feed_dict={image_tensor: image_np_expanded})
print('skye boxes=', boxes)
# scores[0][0] = 0.99 # Output.png 上面没有预测结果信息. 准确率太低？是的。最后的框是会有个准确率阈值的。
print('skye scores=',scores)
print('skye classes=', classes)
print('skye category_index=', category_index)
image_np = vis_util.visualize_boxes_and_labels_on_image_array(
image_np,
np.squeeze(boxes),
np.squeeze(classes).astype(np.int32),
np.squeeze(scores),
category_index,
use_normalized_coordinates=True,
line_thickness=8)
plt.imsave(os.path.join(FLAGS.output_dir, 'output.png'), image_np)
| 41.1625 | 126 | 0.683875 |
0aa1c7468484eee02456915485470e6e25a46577
| 5,918 |
py
|
Python
|
tests/test_tokenization_bart.py
|
zyxdSTU/pytorch-pretrained-BERT
|
5ec89489dd66302023821f2d27e109861e9f593d
|
[
"Apache-2.0"
] | 4 |
2021-01-15T20:20:47.000Z
|
2021-11-14T18:33:42.000Z
|
tests/test_tokenization_bart.py
|
yym6472/transformers
|
abd01205561e5caec167c1fbb20bccea24d7ba46
|
[
"Apache-2.0"
] | 1 |
2021-09-15T09:20:01.000Z
|
2022-03-02T17:16:01.000Z
|
tests/test_tokenization_bart.py
|
yym6472/transformers
|
abd01205561e5caec167c1fbb20bccea24d7ba46
|
[
"Apache-2.0"
] | 3 |
2021-04-26T08:01:16.000Z
|
2022-03-23T04:47:56.000Z
|
import json
import os
import unittest
from transformers import BartTokenizer, BartTokenizerFast, BatchEncoding
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
from transformers.tokenization_roberta import VOCAB_FILES_NAMES
from .test_tokenization_common import TokenizerTesterMixin
class TestTokenizationBart(TokenizerTesterMixin, unittest.TestCase):
tokenizer_class = BartTokenizer
rust_tokenizer_class = BartTokenizerFast
test_rust_tokenizer = True
def setUp(self):
super().setUp()
vocab = [
"l",
"o",
"w",
"e",
"r",
"s",
"t",
"i",
"d",
"n",
"\u0120",
"\u0120l",
"\u0120n",
"\u0120lo",
"\u0120low",
"er",
"\u0120lowest",
"\u0120newer",
"\u0120wider",
"<unk>",
]
vocab_tokens = dict(zip(vocab, range(len(vocab))))
merges = ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
self.special_tokens_map = {"unk_token": "<unk>"}
self.vocab_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"])
self.merges_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["merges_file"])
with open(self.vocab_file, "w", encoding="utf-8") as fp:
fp.write(json.dumps(vocab_tokens) + "\n")
with open(self.merges_file, "w", encoding="utf-8") as fp:
fp.write("\n".join(merges))
def get_tokenizer(self, **kwargs):
kwargs.update(self.special_tokens_map)
return self.tokenizer_class.from_pretrained(self.tmpdirname, **kwargs)
def get_rust_tokenizer(self, **kwargs):
kwargs.update(self.special_tokens_map)
return BartTokenizerFast.from_pretrained(self.tmpdirname, **kwargs)
def get_input_output_texts(self, tokenizer):
return "lower newer", "lower newer"
@cached_property
def default_tokenizer(self):
return BartTokenizer.from_pretrained("facebook/bart-large")
@cached_property
def default_tokenizer_fast(self):
return BartTokenizerFast.from_pretrained("facebook/bart-large")
@require_torch
def test_prepare_seq2seq_batch(self):
src_text = ["A long paragraph for summarization.", "Another paragraph for summarization."]
tgt_text = [
"Summary of the text.",
"Another summary.",
]
expected_src_tokens = [0, 250, 251, 17818, 13, 39186, 1938, 4, 2]
for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
batch = tokenizer.prepare_seq2seq_batch(
src_text, tgt_texts=tgt_text, max_length=len(expected_src_tokens), return_tensors="pt"
)
self.assertIsInstance(batch, BatchEncoding)
self.assertEqual((2, 9), batch.input_ids.shape)
self.assertEqual((2, 9), batch.attention_mask.shape)
result = batch.input_ids.tolist()[0]
self.assertListEqual(expected_src_tokens, result)
# Test that special tokens are reset
# Test Prepare Seq
@require_torch
def test_seq2seq_batch_empty_target_text(self):
src_text = ["A long paragraph for summarization.", "Another paragraph for summarization."]
for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
batch = tokenizer.prepare_seq2seq_batch(src_text, return_tensors="pt")
# check if input_ids are returned and no labels
self.assertIn("input_ids", batch)
self.assertIn("attention_mask", batch)
self.assertNotIn("labels", batch)
self.assertNotIn("decoder_attention_mask", batch)
@require_torch
def test_seq2seq_batch_max_target_length(self):
src_text = ["A long paragraph for summarization.", "Another paragraph for summarization."]
tgt_text = [
"Summary of the text.",
"Another summary.",
]
for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
batch = tokenizer.prepare_seq2seq_batch(
src_text, tgt_texts=tgt_text, max_target_length=32, padding="max_length", return_tensors="pt"
)
self.assertEqual(32, batch["labels"].shape[1])
# test None max_target_length
batch = tokenizer.prepare_seq2seq_batch(
src_text, tgt_texts=tgt_text, max_length=32, padding="max_length", return_tensors="pt"
)
self.assertEqual(32, batch["labels"].shape[1])
@require_torch
def test_seq2seq_batch_not_longer_than_maxlen(self):
for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
batch = tokenizer.prepare_seq2seq_batch(
["I am a small frog" * 1024, "I am a small frog"], return_tensors="pt"
)
self.assertIsInstance(batch, BatchEncoding)
self.assertEqual(batch.input_ids.shape, (2, 1024))
@require_torch
def test_special_tokens(self):
src_text = ["A long paragraph for summarization."]
tgt_text = [
"Summary of the text.",
]
for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
batch = tokenizer.prepare_seq2seq_batch(src_text, tgt_texts=tgt_text, return_tensors="pt")
input_ids = batch["input_ids"]
labels = batch["labels"]
self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item())
self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item())
self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item())
self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item())
| 39.986486 | 109 | 0.628929 |
0abc761c4d0f1015b3d182238014d8363430208c
| 693 |
py
|
Python
|
old/baxter_test.py
|
YoshimitsuMatsutaIe/hoge_flow_test
|
22e2e2ce043a3107bd06449f6f9958641293e414
|
[
"MIT"
] | null | null | null |
old/baxter_test.py
|
YoshimitsuMatsutaIe/hoge_flow_test
|
22e2e2ce043a3107bd06449f6f9958641293e414
|
[
"MIT"
] | null | null | null |
old/baxter_test.py
|
YoshimitsuMatsutaIe/hoge_flow_test
|
22e2e2ce043a3107bd06449f6f9958641293e414
|
[
"MIT"
] | null | null | null |
"""baxter関連をテストする"""
import numpy as np
from math import cos, sin, tan, pi
#import itertools
import csv
import matplotlib.pyplot as plt
import matplotlib.animation as anm
from mpl_toolkits.mplot3d import Axes3D
#import matplotlib.patches as patches
#from matplotlib.font_manager import FontProperties
#fp = FontProperties(fname=r'C:\WINDOWS\Fonts\Arial.ttf', size=14)
import time
# from baxter_utils_2 import *
# from baxter_utils import *
import baxter_utils_3
BaxterKinema = baxter_utils_3.BaxterKinematics3(
L = 278e-3,
h = 64e-3,
H = 1104e-3,
L0 = 270.35e-3,
L1 = 69e-3,
L2 = 364.35e-3,
L3 = 69e-3,
L4 = 374.29e-3,
L5 = 10e-3,
L6 = 368.3e-3
)
| 21 | 66 | 0.702742 |
7c7cc5d03503a565bf1f10598b682a71e75a2d48
| 2,955 |
py
|
Python
|
events/views.py
|
rocky-roll-call/rrc-backend
|
02e8e11c3dab7661e48650e2e861a4a97788a4ce
|
[
"MIT"
] | null | null | null |
events/views.py
|
rocky-roll-call/rrc-backend
|
02e8e11c3dab7661e48650e2e861a4a97788a4ce
|
[
"MIT"
] | null | null | null |
events/views.py
|
rocky-roll-call/rrc-backend
|
02e8e11c3dab7661e48650e2e861a4a97788a4ce
|
[
"MIT"
] | null | null | null |
"""
Event API Views
"""
# django
from django.shortcuts import get_object_or_404
# library
from rest_framework import generics
from rest_framework.exceptions import ValidationError
# app
from casts.models import Cast
from casts.permissions import IsManagerOrReadOnly
from users.models import Profile
from .models import Event, Casting
from .serializers import CastingSerializer, EventSerializer
class EventListCreate(generics.ListCreateAPIView):
"""List available events or create a new one"""
queryset = Event.objects.all()
serializer_class = EventSerializer
permission_classes = (IsManagerOrReadOnly,)
def perform_create(self, serializer):
cast = get_object_or_404(Cast, pk=self.request.data["cast"])
self.check_object_permissions(self.request, cast)
serializer.save(cast=cast)
class EventRetrieveUpdateDestroy(generics.RetrieveUpdateDestroyAPIView):
"""Retrieve, update, or delete an event"""
queryset = Event.objects.all()
serializer_class = EventSerializer
permission_classes = (IsManagerOrReadOnly,)
def perform_update(self, serializer):
if "cast" in self.request.data:
raise ValidationError(
"You cannot change the cast after an event has been created"
)
serializer.save()
class CastingListCreate(generics.ListCreateAPIView):
"""List available events or create a new one"""
serializer_class = CastingSerializer
permission_classes = (IsManagerOrReadOnly,)
def get_queryset(self):
return Casting.objects.filter(event=self.kwargs["pk"])
def perform_create(self, serializer):
event = get_object_or_404(Event, pk=self.kwargs["pk"])
self.check_object_permissions(self.request, event)
if "profile" in self.request.data:
profile = get_object_or_404(Profile, pk=self.request.data["profile"])
if not event.cast.is_member(profile):
raise ValidationError(f"{profile} is not a member of {event.cast}")
serializer.save(event=event, profile=profile)
serializer.save(event=event)
class CastingRetrieveUpdateDestroy(generics.RetrieveUpdateDestroyAPIView):
"""Retrieve, update, or delete an event casting"""
queryset = Casting.objects.all()
serializer_class = CastingSerializer
permission_classes = (IsManagerOrReadOnly,)
def perform_update(self, serializer):
if "event" in self.request.data:
raise ValidationError(
"You cannot change the event after a casting has been created"
)
if "profile" in self.request.data:
profile = get_object_or_404(Profile, pk=self.request.data["profile"])
cast = self.get_object().event.cast
if not cast.is_member(profile):
raise ValidationError(f"{profile} is not a member of {cast}")
serializer.save(profile=profile)
serializer.save()
| 33.965517 | 83 | 0.698816 |
7cc242f60c16ba220614e43c292406585aa58ed9
| 408 |
py
|
Python
|
Algorithms/Sorting/InsertionSort/insertion_sort.py
|
Nidita/Data-Structures-Algorithms
|
7b5198c8d37e9a70dd0885c6eef6dddd9d85d74a
|
[
"MIT"
] | 26 |
2019-07-17T11:05:43.000Z
|
2022-02-06T08:31:40.000Z
|
Algorithms/Sorting/InsertionSort/insertion_sort.py
|
Nidita/Data-Structures-Algorithms
|
7b5198c8d37e9a70dd0885c6eef6dddd9d85d74a
|
[
"MIT"
] | 7 |
2019-07-16T19:52:25.000Z
|
2022-01-08T08:03:44.000Z
|
Algorithms/Sorting/InsertionSort/insertion_sort.py
|
Nidita/Data-Structures-Algorithms
|
7b5198c8d37e9a70dd0885c6eef6dddd9d85d74a
|
[
"MIT"
] | 19 |
2020-01-14T02:44:28.000Z
|
2021-12-27T17:31:59.000Z
|
def insertion_sort(arr):
for i in range(1, len(arr)):
key = arr[i]
j = i - 1
while(j>=0 and arr[j]>key):
arr[j+1]=arr[j]
j = j - 1
arr[j+1] = key
return arr
def main():
arr = [6, 5, 8, 9, 3, 1, 4, 7, 2]
sorted_arr = insertion_sort(arr)
for i in sorted_arr:
print(i, end=" ")
if __name__ == "__main__":
main()
| 20.4 | 37 | 0.458333 |
7cd061d6e0313657c5bd26a9b8283e3bedc8bf98
| 1,648 |
py
|
Python
|
etl/transforms/primitives/df/restructure.py
|
cloud-cds/cds-stack
|
d68a1654d4f604369a071f784cdb5c42fc855d6e
|
[
"Apache-2.0"
] | 6 |
2018-06-27T00:09:55.000Z
|
2019-03-07T14:06:53.000Z
|
etl/transforms/primitives/df/restructure.py
|
cloud-cds/cds-stack
|
d68a1654d4f604369a071f784cdb5c42fc855d6e
|
[
"Apache-2.0"
] | 3 |
2021-03-31T18:37:46.000Z
|
2021-06-01T21:49:41.000Z
|
etl/transforms/primitives/df/restructure.py
|
cloud-cds/cds-stack
|
d68a1654d4f604369a071f784cdb5c42fc855d6e
|
[
"Apache-2.0"
] | 3 |
2020-01-24T16:40:49.000Z
|
2021-09-30T02:28:55.000Z
|
import etl.transforms.primitives.df.pandas_utils as pandas_utils
import pandas as pd
import numpy as np
import logging
def select_columns(df, selection_dict):
try:
df = df[list(selection_dict.keys())]\
.rename(index=str, columns=selection_dict)\
.reset_index(drop=True)
except KeyError as e:
for col in selection_dict.values():
df[col] = np.nan
return df
def unlist(df, unlist_col):
return pandas_utils.unlistify_pandas_column(df, unlist_col)
def extract(df, dict_column, selection_dict):
def fill_none(val):
if val is None or str(val) == 'nan':
return {}
return val
df[dict_column] = df[dict_column].apply(fill_none)
new_cols = pd.DataFrame(df[dict_column].tolist())
new_cols = select_columns(new_cols, selection_dict)
old_cols = df.drop(dict_column, axis=1)
return pd.concat([old_cols, new_cols], axis=1)
def concat_str(df, new_col, col_1, col_2, drop_original=True):
df[new_col] = df[col_1].str.cat(df[col_2], sep=' ')
if drop_original:
df.drop([col_1, col_2], axis=1, inplace=True)
return df
import random
def make_null_time_midnight(df):
df['time'] = df['time'].apply(lambda x: '12:00 AM' if x is None else x)
return df
def extract_id_from_list(df, id_column, id_type):
def get_id(id_list):
for x in id_list:
if x.get('Type') == id_type:
return str(x['ID'])
logging.error('Could not find an ID. Throwing away row.')
return 'Invalid ID'
df[id_column] = df[id_column].apply(get_id)
return df[~(df[id_column] == 'Invalid ID')]
| 32.313725 | 75 | 0.652913 |
86a6b22c2d771d5bbbd8c2ebed050c8c9fd2e1e6
| 2,560 |
py
|
Python
|
exercises/networking_selfpaced/networking-workshop/collections/ansible_collections/community/general/scripts/inventory/lxc_inventory.py
|
tr3ck3r/linklight
|
5060f624c235ecf46cb62cefcc6bddc6bf8ca3e7
|
[
"MIT"
] | null | null | null |
exercises/networking_selfpaced/networking-workshop/collections/ansible_collections/community/general/scripts/inventory/lxc_inventory.py
|
tr3ck3r/linklight
|
5060f624c235ecf46cb62cefcc6bddc6bf8ca3e7
|
[
"MIT"
] | null | null | null |
exercises/networking_selfpaced/networking-workshop/collections/ansible_collections/community/general/scripts/inventory/lxc_inventory.py
|
tr3ck3r/linklight
|
5060f624c235ecf46cb62cefcc6bddc6bf8ca3e7
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
#
# (c) 2015-16 Florian Haas, hastexo Professional Services GmbH
# <[email protected]>
# Based in part on:
# libvirt_lxc.py, (c) 2013, Michael Scherer <[email protected]>
#
# This file is part of Ansible,
#
# Ansible is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Ansible 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 General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Ansible. If not, see <http://www.gnu.org/licenses/>.
"""
Ansible inventory script for LXC containers. Requires Python
bindings for LXC API.
In LXC, containers can be grouped by setting the lxc.group option,
which may be found more than once in a container's
configuration. So, we enumerate all containers, fetch their list
of groups, and then build the dictionary in the way Ansible expects
it.
"""
from __future__ import print_function
import sys
import lxc
import json
def build_dict():
"""Returns a dictionary keyed to the defined LXC groups. All
containers, including the ones not in any group, are included in the
"all" group."""
# Enumerate all containers, and list the groups they are in. Also,
# implicitly add every container to the 'all' group.
containers = dict([(c,
['all'] +
(lxc.Container(c).get_config_item('lxc.group') or []))
for c in lxc.list_containers()])
# Extract the groups, flatten the list, and remove duplicates
groups = set(sum([g for g in containers.values()], []))
# Create a dictionary for each group (including the 'all' group
return dict([(g, {'hosts': [k for k, v in containers.items() if g in v],
'vars': {'ansible_connection': 'lxc'}}) for g in groups])
def main(argv):
"""Returns a JSON dictionary as expected by Ansible"""
result = build_dict()
if len(argv) == 2 and argv[1] == '--list':
json.dump(result, sys.stdout)
elif len(argv) == 3 and argv[1] == '--host':
json.dump({'ansible_connection': 'lxc'}, sys.stdout)
else:
print("Need an argument, either --list or --host <host>", file=sys.stderr)
if __name__ == '__main__':
main(sys.argv)
| 36.056338 | 82 | 0.678516 |
d4954ea39c55d5e1eb404391d9b9f35a36d9d496
| 2,079 |
py
|
Python
|
oldp/utils/test_utils.py
|
ImgBotApp/oldp
|
575dc6f711dde3470d910e21c9440ee9b79a69ed
|
[
"MIT"
] | 3 |
2020-06-27T08:19:35.000Z
|
2020-12-27T17:46:02.000Z
|
oldp/utils/test_utils.py
|
ImgBotApp/oldp
|
575dc6f711dde3470d910e21c9440ee9b79a69ed
|
[
"MIT"
] | null | null | null |
oldp/utils/test_utils.py
|
ImgBotApp/oldp
|
575dc6f711dde3470d910e21c9440ee9b79a69ed
|
[
"MIT"
] | null | null | null |
import logging
import os
from unittest import TestCase
from django.conf import settings
logger = logging.getLogger(__name__)
class TestCaseHelper(object):
resource_dir = None
@staticmethod
def get_app_root_dir():
return os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
def get_resource_dir(self):
# return os.path.join(os.path.dirname(os.path.realpath(__file__)), 'resources')
return self.resource_dir
def get_resource(self, file_name):
return os.path.join(self.get_resource_dir(), file_name)
def get_resource_as_string(self, file_name):
with open(self.get_resource(file_name), 'r') as f:
return f.read()
def assert_items_equal(self, expected, actual, msg, debug=False):
if debug:
logger.debug('Expected:\t%s\nActual:\t%s' % (sorted(expected), sorted(actual)))
TestCase().assertTrue(len(expected) == len(actual) and sorted(expected) == sorted(actual), msg)
# @staticmethod
# def get_log_level():
# return get_log_level_from_env('OLDP_TEST_LOG_LEVEL', 'debug')
def mysql_only_test(fn):
"""Use this decorator for tests (e.g. DataErrors, IntegrityErrors) that apply only with MySQL (not SQLite)"""
def modified_fn(x):
if settings.DATABASES['default']['ENGINE'] != 'django.db.backends.mysql':
logger.warning('Skip test (DB is not MySQL): %s' % fn.__name__)
else:
return fn(x)
return modified_fn
def web_test(fn):
"""Use this decorator for tests that interact with external websites"""
def modified_fn(x):
if not settings.TEST_WITH_WEB:
logger.warning('Skip test (without web): %s' % fn.__name__)
else:
return fn(x)
return modified_fn
def es_test(fn):
"""Use this decorator for tests that require Elasticsearch"""
def modified_fn(x):
if not settings.TEST_WITH_ES:
logger.warning('Skip test (without Elasticsearch): %s' % fn.__name__)
else:
return fn(x)
return modified_fn
| 29.7 | 113 | 0.658009 |
d4da6651eaa60ead25c4d44b2f69a592b2f35122
| 10,794 |
py
|
Python
|
tests/model/test_game.py
|
jonashellmann/informaticup21-team-chillow
|
f2e519af0a5d9a9368d62556703cfb1066ebb58f
|
[
"MIT"
] | 3 |
2021-01-17T23:32:07.000Z
|
2022-01-30T14:49:16.000Z
|
tests/model/test_game.py
|
jonashellmann/informaticup21-team-chillow
|
f2e519af0a5d9a9368d62556703cfb1066ebb58f
|
[
"MIT"
] | 2 |
2021-01-17T13:37:56.000Z
|
2021-04-14T12:28:49.000Z
|
tests/model/test_game.py
|
jonashellmann/informaticup21-team-chillow
|
f2e519af0a5d9a9368d62556703cfb1066ebb58f
|
[
"MIT"
] | 2 |
2021-04-02T14:53:38.000Z
|
2021-04-20T11:10:17.000Z
|
import unittest
from datetime import datetime, timezone
import tests
from chillow.model.cell import Cell
from chillow.model.direction import Direction
from chillow.model.game import Game
from chillow.model.player import Player
from chillow.exceptions import WrongGameWidthException, WrongGameHeightException, OwnPlayerMissingException, \
PlayerPositionException, PlayerWithGivenIdNotAvailableException
from chillow.service.data_loader import JSONDataLoader
class GameTest(unittest.TestCase):
def test_examines_your_player_after_creation(self):
player1 = Player(1, 0, 1, Direction.up, 0, True, "Name 1")
player2 = Player(2, 1, 0, Direction.up, 0, True, "Name 2")
player3 = Player(3, 0, 0, Direction.up, 0, True, "Name 3")
players = [player1, player2, player3]
cells = [[Cell([player3]), Cell([player2])], [Cell([player1]), Cell()]]
game = Game(2, 2, cells, players, 2, True, datetime.now())
self.assertEqual(game.you, player2)
def test_raise_exception_on_non_existing_own_player(self):
player1 = Player(1, 0, 1, Direction.up, 0, True, "Name 1")
player3 = Player(3, 0, 0, Direction.up, 0, True, "Name 3")
players = [player1, player3]
cells = [[Cell([player3]), Cell([])], [Cell([player1]), Cell()]]
with self.assertRaises(OwnPlayerMissingException):
Game(2, 2, cells, players, 2, True, datetime.now())
def test_raise_exception_on_wrong_player_position(self):
player1 = Player(1, 1, 1, Direction.up, 0, True, "Name 1")
player2 = Player(2, 0, 0, Direction.up, 0, True, "Name 2")
player3 = Player(3, 0, 1, Direction.up, 0, True, "Name 3")
players = [player1, player2, player3]
cells = [[Cell([player2]), Cell([player3])], [Cell(), Cell([player1])]]
with self.assertRaises(PlayerPositionException):
Game(2, 2, cells, players, 2, True, datetime.now())
def test_dont_raise_exception_on_wrong_inactive_player_position(self):
player1 = Player(1, 1, 1, Direction.up, 0, False, "Name 1")
player2 = Player(2, 1, 0, Direction.up, 0, True, "Name 2")
player3 = Player(3, 0, 1, Direction.up, 0, True, "Name 3")
players = [player1, player2, player3]
cells = [[Cell([]), Cell([player2])], [Cell([player3]), Cell([player3])]]
game = Game(2, 2, cells, players, 2, True, datetime.now())
self.assertEqual(game.you, player2)
def test_raise_exception_on_wrong_width(self):
cells = [
[
Cell()
],
[
Cell(), Cell()
]
]
with self.assertRaises(WrongGameWidthException):
Game(2, 2, cells, [], 0, True, datetime.now())
def test_raise_exception_on_wrong_height(self):
cells = [
[
Cell(), Cell()
]
]
with self.assertRaises(WrongGameHeightException):
Game(2, 2, cells, [], 0, True, datetime.now())
def test_find_winner_in_ended_game(self):
player1 = Player(1, 0, 0, Direction.up, 0, False, "Name")
player2 = Player(1, 1, 0, Direction.up, 0, True, "Name")
cells = [[Cell([player1]), Cell([player2])]]
game = Game(2, 1, cells, [player1, player2], 1, False, datetime.now())
result = game.get_winner()
self.assertEqual(player2, result)
def test_raise_exception_for_winner_in_running_game(self):
player = Player(1, 0, 0, Direction.up, 0, True, "Name")
cells = [[Cell([player]), Cell()]]
game = Game(2, 1, cells, [player], 1, True, datetime.now())
with self.assertRaises(Exception):
game.get_winner()
def test_return_no_winner_in_ended_game(self):
player1 = Player(1, 0, 0, Direction.up, 0, False, "Name")
player2 = Player(1, 1, 0, Direction.up, 0, False, "Name")
cells = [[Cell([player1]), Cell([player2])]]
game = Game(2, 1, cells, [player1, player2], 1, False, datetime.now())
result = game.get_winner()
self.assertEqual(None, result)
def test_player_with_id_should_be_returned(self):
player1 = Player(1, 0, 0, Direction.up, 0, True, "Name")
player2 = Player(2, 1, 0, Direction.up, 0, True, "Name")
cells = [[Cell([player1]), Cell([player2])]]
game = Game(2, 1, cells, [player1, player2], 1, True, datetime.now())
self.assertEqual(player1, game.get_player_by_id(1))
def test_raise_exception_when_player_id_invalid(self):
player1 = Player(1, 1, 0, Direction.up, 0, True, "Name")
player2 = Player(2, 0, 0, Direction.up, 0, True, "Name")
cells = [[Cell([player2]), Cell([player1])]]
game = Game(2, 1, cells, [player1, player2], 1, True, datetime.now())
with self.assertRaises(PlayerWithGivenIdNotAvailableException):
game.get_player_by_id(100)
def test_return_all_other_players(self):
player1 = Player(1, 1, 1, Direction.up, 0, True, "Name 1")
player2 = Player(2, 1, 0, Direction.up, 0, True, "Name 2")
player3 = Player(3, 0, 0, Direction.up, 0, True, "Name 3")
players = [player1, player2, player3]
cells = [[Cell([player3]), Cell([player2])], [Cell([]), Cell([player1])]]
game = Game(2, 2, cells, players, 2, True, datetime.now())
result = game.get_other_player_ids(player2)
self.assertEqual([1, 3], result)
def test_return_all_other_active_players(self):
player1 = Player(1, 1, 1, Direction.up, 0, True, "Name 1")
player2 = Player(2, 1, 0, Direction.up, 0, False, "Name 2")
player3 = Player(3, 0, 0, Direction.up, 0, True, "Name 3")
players = [player1, player2, player3]
cells = [[Cell([player3]), Cell([player2])], [Cell([]), Cell([player1])]]
game = Game(2, 2, cells, players, 1, True, datetime.now())
result = game.get_other_player_ids(player1, check_active=True)
self.assertEqual([3], result)
def test_return_all_players_except_one_within_distance_1(self):
player1 = Player(1, 3, 3, Direction.up, 0, True, "Name 1")
player2 = Player(2, 1, 3, Direction.up, 0, True, "Name 2")
player3 = Player(3, 0, 0, Direction.up, 0, True, "Name 3")
players = [player1, player2, player3]
cells = [
[Cell([player3]), Cell(), Cell(), Cell(), Cell()],
[Cell(), Cell(), Cell(), Cell(), Cell()],
[Cell(), Cell(), Cell(), Cell(), Cell()],
[Cell(), Cell([player2]), Cell(), Cell([player1]), Cell()],
[Cell(), Cell(), Cell(), Cell(), Cell()]
]
game = Game(5, 5, cells, players, 1, True, datetime.now())
result = game.get_other_player_ids(player1, 2)
self.assertEqual([2], result)
def test_return_all_players_except_one_within_distance_2(self):
player1 = Player(1, 4, 4, Direction.up, 0, True, "Name 1")
player2 = Player(2, 2, 3, Direction.up, 0, True, "Name 2")
player3 = Player(3, 1, 4, Direction.up, 0, True, "Name 3")
players = [player1, player2, player3]
cells = [
[Cell(), Cell(), Cell(), Cell(), Cell()],
[Cell(), Cell(), Cell(), Cell(), Cell()],
[Cell(), Cell(), Cell(), Cell(), Cell()],
[Cell(), Cell(), Cell([player2]), Cell(), Cell()],
[Cell(), Cell([player3]), Cell([player2]), Cell(), Cell([player1])]
]
game = Game(5, 5, cells, players, 1, True, datetime.now())
result = game.get_other_player_ids(player1, 3)
self.assertEqual([2], result)
def test_return_no_player_who_is_not_reachable(self):
player1 = Player(1, 4, 4, Direction.up, 0, True, "Name 1")
player2 = Player(2, 2, 3, Direction.up, 0, True, "Name 2")
player3 = Player(3, 1, 4, Direction.up, 0, True, "Name 3")
players = [player1, player2, player3]
cells = [
[Cell(), Cell(), Cell([player2]), Cell(), Cell()],
[Cell(), Cell(), Cell([player2]), Cell(), Cell()],
[Cell(), Cell(), Cell([player2]), Cell(), Cell()],
[Cell(), Cell(), Cell([player2]), Cell(), Cell()],
[Cell(), Cell([player3]), Cell([player2]), Cell(), Cell([player1])]
]
game = Game(5, 5, cells, players, 1, True, datetime.now())
result = game.get_other_player_ids(player1, 3)
self.assertEqual([2], result)
def test_translate_cell_matrix_to_pathfinding_matrix_should_be_correct(self):
player1 = Player(1, 0, 0, Direction.up, 1, True, "")
player2 = Player(2, 0, 1, Direction.down, 3, True, "")
players = [player1, player2]
cells = [[Cell([player1]), Cell()],
[Cell([player2]), Cell()],
[Cell(), Cell()]]
game = Game(2, 3, cells, players, 2, True, datetime.now())
expected_matrix = [[0, 1],
[0, 1],
[1, 1]]
matrix = game.translate_cell_matrix_to_pathfinding_matrix()
self.assertEqual(matrix, expected_matrix)
def test_copying_a_game_should_return_same_game_but_different_identity(self):
player1 = Player(1, 1, 1, Direction.up, 0, True, "Name")
player2 = Player(2, 1, 0, Direction.up, 0, True, "Name2")
player3 = Player(3, 0, 0, Direction.up, 0, True, "Name3")
players = [player1, player2, player3]
cells = [[Cell([player3]), Cell([player2])], [Cell([]), Cell([player1])]]
game = Game(2, 2, cells, players, 2, True, datetime.now())
result = game.copy()
self.assertEqual(game, result)
self.assertNotEqual(id(game), id(result))
def test_normalize_game_deadline_1(self):
server_time = datetime(2020, 11, 20, 10, 33, 11, 0, timezone.utc)
own_time = datetime(2020, 11, 20, 10, 33, 12, 941748, timezone.utc)
game = JSONDataLoader().load(tests.read_test_file("model/game_1.json"))
game.deadline = datetime(2020, 11, 20, 10, 33, 18, 0, timezone.utc)
expected = datetime(2020, 11, 20, 10, 33, 19, 941748, timezone.utc)
game.normalize_deadline(server_time, own_time)
self.assertEqual(expected, game.deadline)
def test_normalize_game_deadline_2(self):
server_time = datetime(2020, 11, 20, 10, 33, 12, 941748, timezone.utc)
own_time = datetime(2020, 11, 20, 10, 33, 11, 0, timezone.utc)
game = JSONDataLoader().load(tests.read_test_file("model/game_1.json"))
game.deadline = datetime(2020, 11, 20, 10, 33, 18, 941748, timezone.utc)
expected = datetime(2020, 11, 20, 10, 33, 17, 0, timezone.utc)
game.normalize_deadline(server_time, own_time)
self.assertEqual(expected, game.deadline)
| 42.496063 | 110 | 0.592459 |
078c756cad7cad8808fa355832f4361f48528673
| 3,423 |
py
|
Python
|
src/onegov/translator_directory/app.py
|
politbuero-kampagnen/onegov-cloud
|
20148bf321b71f617b64376fe7249b2b9b9c4aa9
|
[
"MIT"
] | null | null | null |
src/onegov/translator_directory/app.py
|
politbuero-kampagnen/onegov-cloud
|
20148bf321b71f617b64376fe7249b2b9b9c4aa9
|
[
"MIT"
] | null | null | null |
src/onegov/translator_directory/app.py
|
politbuero-kampagnen/onegov-cloud
|
20148bf321b71f617b64376fe7249b2b9b9c4aa9
|
[
"MIT"
] | null | null | null |
from datetime import datetime
from sqlalchemy.orm import object_session
from onegov.core import utils
from onegov.core.crypto import random_token
from onegov.file.utils import as_fileintent, extension_for_content_type, \
content_type_from_fileobj
from onegov.gis import Coordinates
from onegov.translator_directory.initial_content import create_new_organisation
from onegov.org import OrgApp
from onegov.org.app import get_common_asset as default_common_asset
from onegov.org.app import get_i18n_localedirs as get_org_i18n_localedirs
from onegov.translator_directory.models.voucher import TranslatorVoucherFile
from onegov.translator_directory.request import TranslatorAppRequest
from onegov.translator_directory.theme import TranslatorDirectoryTheme
class TranslatorDirectoryApp(OrgApp):
send_daily_ticket_statistics = False
request_class = TranslatorAppRequest
def es_may_use_private_search(self, request):
return request.is_admin
def configure_organisation(self, **cfg):
cfg.setdefault('enable_user_registration', False)
cfg.setdefault('enable_yubikey', False)
cfg.setdefault('disable_password_reset', False)
super().configure_organisation(**cfg)
@property
def coordinates(self):
return self.org.meta.get('translator_directory_home') or Coordinates()
@coordinates.setter
def coordinates(self, value):
self.org.meta['translator_directory_home'] = value or {}
@property
def voucher_excel(self):
return object_session(self.org).query(TranslatorVoucherFile).first()
@property
def voucher_excel_file(self):
return self.voucher_excel and self.voucher_excel.reference.file
@voucher_excel_file.setter
def voucher_excel_file(self, value):
content_type = extension_for_content_type(
content_type_from_fileobj(value)
) or 'xls'
year = datetime.now().year
filename = f'abrechnungsvorlage_{year}.{content_type}'
if self.voucher_excel:
self.voucher_excel.reference = as_fileintent(value, filename)
self.voucher_excel.name = filename
else:
file = TranslatorVoucherFile(id=random_token())
file.reference = as_fileintent(value, filename)
file.name = filename
session = object_session(self.org)
session.add(file)
session.flush()
@TranslatorDirectoryApp.template_directory()
def get_template_directory():
return 'templates'
@TranslatorDirectoryApp.static_directory()
def get_static_directory():
return 'static'
@TranslatorDirectoryApp.setting(section='core', name='theme')
def get_theme():
return TranslatorDirectoryTheme()
@TranslatorDirectoryApp.setting(section='org', name='create_new_organisation')
def get_create_new_organisation_factory():
return create_new_organisation
@TranslatorDirectoryApp.setting(section='i18n', name='localedirs')
def get_i18n_localedirs():
mine = utils.module_path('onegov.translator_directory', 'locale')
return [mine] + get_org_i18n_localedirs()
@TranslatorDirectoryApp.webasset_path()
def get_js_path():
return 'assets/js'
@TranslatorDirectoryApp.webasset_output()
def get_webasset_output():
return 'assets/bundles'
@TranslatorDirectoryApp.webasset('common')
def get_common_asset():
yield from default_common_asset()
yield 'translator_directory.js'
| 31.694444 | 79 | 0.752848 |
07b99f525071369ad8a8683e936de85bf118cf18
| 2,964 |
py
|
Python
|
Examples/terminal/demo_all/demo-all.py
|
andino-systems/andinopy
|
28fc09fbdd67dd690b9b3f80f03a05c342c777e1
|
[
"Apache-2.0"
] | null | null | null |
Examples/terminal/demo_all/demo-all.py
|
andino-systems/andinopy
|
28fc09fbdd67dd690b9b3f80f03a05c342c777e1
|
[
"Apache-2.0"
] | null | null | null |
Examples/terminal/demo_all/demo-all.py
|
andino-systems/andinopy
|
28fc09fbdd67dd690b9b3f80f03a05c342c777e1
|
[
"Apache-2.0"
] | null | null | null |
import time
from andinopy import andinoterminal
import logging
class TerminalDemo:
terminal: andinoterminal = None
_last_keyboard: str = ""
_last_rfid: str = ""
def __init__(self):
print("initializing Terminal")
self.terminal = andinoterminal()
self.terminal.rfid_keyboard_instance.on_function_button = self.on_function_button
self.terminal.rfid_keyboard_instance.on_keyboard_button = self.on_keyboard_button
self.terminal.rfid_keyboard_instance.on_rfid_string = self.on_rfid_string
self.terminal.display_instance.on_display_touch = self.on_display_touch
self.terminal.andinoio_instance.on_input_functions = \
[self.input_pin for i in range(len(self.terminal.andinoio_instance.inputs_counter))]
def __get_counters(self):
return self.terminal.andinoio_instance.inputs_counter
def __get_relays(self):
return self.terminal.andinoio_instance.relays_status
def update_terminal(self):
print("updating Display")
ctr = self.__get_counters()
for i in range(len(ctr)):
self.terminal.display_instance.set_text(f"input{i + 1}", ctr[i])
rel_stats = ["on" if i == 1 else "off" for i in self.__get_relays()]
for j in range(len(rel_stats)):
self.terminal.display_instance.set_text(f"rel{j + 1}", rel_stats[j])
self.terminal.display_instance.set_attr(f"rel{j + 1}", "pco", 1346 if rel_stats[j] == "on" else 43300)
self.terminal.display_instance.set_text(f"rfidtxt", self._last_rfid)
self.terminal.display_instance.set_text(f"keybrtxt", self._last_keyboard)
def start(self):
print("starting")
self.terminal.start()
self.terminal.rfid_keyboard_instance.buzz_display(500)
def input_pin(self):
print("pin pressed")
self.update_terminal()
def on_function_button(self, btn: str):
print(f"Function Button: {btn}")
self._last_keyboard = f"Keyboard Function Button: {btn}"
self.update_terminal()
def on_keyboard_button(self, btn: str):
print(f"Keyboard Button: {btn}")
self._last_keyboard = f"Keyboard Button: {btn}"
self.update_terminal()
def on_rfid_string(self, rfid: str):
print(f"RFID: {rfid}")
self._last_rfid = rfid
self.update_terminal()
def on_display_touch(self, text: bytearray):
print(f"Display Touch: {str(text)}")
if text[:4] == b'e\x00\x17\x01':
self.terminal.rfid_keyboard_instance.buzz_display(500)
if __name__ == "__main__":
log = logging.getLogger("andinopy")
log.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
ch.setFormatter(formatter)
log.addHandler(ch)
demo = TerminalDemo()
demo.start()
while True:
time.sleep(1)
| 34.870588 | 114 | 0.67139 |
ed3c21f001a4067d79b6c959360144742570c9bb
| 1,687 |
py
|
Python
|
MzituCrawler/spiders/zipaiSpiders.py
|
yeming1001/-MzituCrawler
|
3e3dad298734658266fb4c12cd863be73eb4f4a2
|
[
"Apache-2.0"
] | 1 |
2018-02-09T05:36:06.000Z
|
2018-02-09T05:36:06.000Z
|
MzituCrawler/spiders/zipaiSpiders.py
|
yeming1001/-MzituCrawler
|
3e3dad298734658266fb4c12cd863be73eb4f4a2
|
[
"Apache-2.0"
] | null | null | null |
MzituCrawler/spiders/zipaiSpiders.py
|
yeming1001/-MzituCrawler
|
3e3dad298734658266fb4c12cd863be73eb4f4a2
|
[
"Apache-2.0"
] | 1 |
2017-03-30T07:44:49.000Z
|
2017-03-30T07:44:49.000Z
|
from scrapy.selector import Selector
import scrapy
from MzituCrawler.items import MzituZiPaicrawlerItem
# 妹子图自拍爬虫
class ZipaiSiders(scrapy.Spider):
name = 'mzitu.zipai'
allowed_domains = ['www.mzitu.com']
base_url = 'http://www.mzitu.com/zipai/comment-page-{}#comments'
start_urls = ['http://www.mzitu.com/zipai']
custom_settings = {
'ITEM_PIPELINES': {'MzituCrawler.pipelines.MzituCrawlerZiPaiImagePipeline': 300,}
}
def parse(self, response):
selector = Selector(response=response)
page_count = selector.xpath(
'//div[@class="main"]/div[@class="main-content"]/div[@class="postlist"]/div[@id="comments"]/div[@class="pagenavi-cm"]/span[@class="page-numbers current"]/text()').extract_first()
self.log(u'自拍总共%s页'%page_count)
for i in range(1,int(page_count)+1):
self.log(u'当前解析第%d页'%i)
url = self.base_url.format(str(i))
yield scrapy.Request(url=url,callback=self.parse_every_page)
def parse_every_page(self, response):
selector = Selector(response=response)
comments = selector.xpath('//div[@class="main"]/div[@class="main-content"]/div[@class="postlist"]/div[@id="comments"]/ul')
item = MzituZiPaicrawlerItem()
li_list = comments.xpath('./li')
for li in li_list:
url = li.xpath('./div[@class="comment-body"]/p/img/@src').extract_first()
title = li.xpath('./div[@class="comment-body"]/p/img/@alt').extract_first()
self.log(u'alt:%s' % title)
self.log(u'url:%s' % url)
item['image_urls'] = [url]
item['image_title'] = title
yield item
| 35.145833 | 186 | 0.623592 |
92bb6c6e0a379cb864cc9e018d8b94120804e425
| 1,843 |
py
|
Python
|
python_first_step/partialsum/partialsum.py
|
cartellefo/projet
|
23c67e847b415fb47f71e830b89a227fffed109b
|
[
"MIT"
] | null | null | null |
python_first_step/partialsum/partialsum.py
|
cartellefo/projet
|
23c67e847b415fb47f71e830b89a227fffed109b
|
[
"MIT"
] | null | null | null |
python_first_step/partialsum/partialsum.py
|
cartellefo/projet
|
23c67e847b415fb47f71e830b89a227fffed109b
|
[
"MIT"
] | null | null | null |
import time
import numpy as np
import numpy .linalg as nl
import random
import matplotlib.pyplot as plt
import sys
# Iteration über sämtliche Argumente:
for eachArg in sys.argv:
print(eachArg)
#t1 = np.linspace(1,5,10)
#t2 = np.linspace(1,5,20)
#plt.plot(t1,t2)
#(t1, t1, ’r -- ’,t1, t1++2, (bs, t2,np.log(t2)**3), 'g^-')
#plt.show()
# # n = 15
# # A = np .random.rand ( 1, n )
# Aprime = A.transpose()
# print(A)
# i = 0
# while i < 10:
# # uu= yield _do()
# uu = random.randint(1,10)
# print(uu)
# time.sleep(1)
# i=i+1
# #r = random.randint(1,10)
# #rint(r)
# X = np.random.rand(5,2)
# print(X)
# #print("le produit est ",n)
# def fill_tab(tab,int):
# for index in len(tab) : tab[index] = 0
# # print(tab)
# i=0
# su = 0
# N = 3
# while i < N:
# su = su + 1./(i*i)
# print(su)
# i=i+1
def partialsum(n_max) :
# summe des carre
print(n_max)
S=0
sums=[]
for i in range(1, n_max,1) :
S+= 1/(i*i)
sums.append(S)
return(sums)
n_max= int(sys.argv[1])
r= partialsum(n_max)
#x=np.linspace(1,n_max,n_max)
#ssum =plt.plot(np.sqrt(x),'r',marker='.',linestyle='-',linewidth=1.5,markersize=1,markeredgecolor='red', label='ssum')
psum = plt.plot(r,'g',marker='.',linestyle='-',linewidth=1,markersize=1.5,markeredgecolor='b',color='green', label='psum')
plt.ylabel("partialsum")
plt.xlabel("integer values to partial sum")
plt.title("graph to Partialsumm and trigonomeric fonction")
plt.legend()
plt.show()
# if __name__=='__main__':
# import sys
# if len(sys.argv)==1:
# try:
# partialsum=int(sys.argv[0])
# y=int(sys.argv[1])
# partialsum(n_max)
# except ValueError:
# print('the arguments is interger')
| 20.252747 | 122 | 0.560499 |
92c46a523a0d0e121e5938ce9c1fe6fda06192d6
| 1,488 |
py
|
Python
|
20-fs-ias-lec/groups/07-14-logCtrl/src/logStore/appconn/kotlin_connection.py
|
Kyrus1999/BACnet
|
5be8e1377252166041bcd0b066cce5b92b077d06
|
[
"MIT"
] | 8 |
2020-03-17T21:12:18.000Z
|
2021-12-12T15:55:54.000Z
|
20-fs-ias-lec/groups/07-14-logCtrl/src/logStore/appconn/kotlin_connection.py
|
Kyrus1999/BACnet
|
5be8e1377252166041bcd0b066cce5b92b077d06
|
[
"MIT"
] | 2 |
2021-07-19T06:18:43.000Z
|
2022-02-10T12:17:58.000Z
|
20-fs-ias-lec/groups/07-14-logCtrl/src/logStore/appconn/kotlin_connection.py
|
Kyrus1999/BACnet
|
5be8e1377252166041bcd0b066cce5b92b077d06
|
[
"MIT"
] | 25 |
2020-03-20T09:32:45.000Z
|
2021-07-18T18:12:59.000Z
|
from .connection import Function
class KotlinFunction(Function):
"""Connection to the group kotlin to insert and output the chat elements"""
def __init__(self):
super(KotlinFunction, self).__init__()
def insert_data(self, cbor):
"""adds a new chat element as cbor
@:parameter event: The new cbor event to be added
@:returns 1 if successful, -1 if any error occurred
"""
self.insert_event(cbor)
def get_usernames_and_feed_id(self):
"""Get all current usernames with the corresponding feed id
@:returns a list with all Kotlin usernames and the corresponding feed id
"""
return self._handler.get_usernames_and_feed_id()
def get_all_entries_by_feed_id(self, feed_id):
"""Get all elements with the corresponding feed id, thus all events of a user
@:parameter feed_id: the feed id of a user
@:returns a list of all Kotlin entries with the correct feed id
"""
return self._handler.get_all_entries_by_feed_id(feed_id)
def get_all_kotlin_events(self):
"""Get all existing kotlin elements that are in the database
@:returns a list of all Kotlin entries
"""
return self._handler.get_all_kotlin_events()
def get_last_kotlin_event(self):
"""Get only the last added kotlin element
@:returns a only the last Kotlin entry as cbor
"""
return self._handler.get_last_kotlin_event()
| 32.347826 | 85 | 0.670699 |
13068e620cee3b753c5b140b987eded2ed8c4625
| 3,847 |
py
|
Python
|
lib/tinyxml2/setversion.py
|
tokosattila/HomeEinkBadge
|
786e9314ef8119d968048ec77956f4fb7804082f
|
[
"Unlicense"
] | null | null | null |
lib/tinyxml2/setversion.py
|
tokosattila/HomeEinkBadge
|
786e9314ef8119d968048ec77956f4fb7804082f
|
[
"Unlicense"
] | null | null | null |
lib/tinyxml2/setversion.py
|
tokosattila/HomeEinkBadge
|
786e9314ef8119d968048ec77956f4fb7804082f
|
[
"Unlicense"
] | null | null | null |
# Python program to set the version.
##############################################
import re
import sys
import optparse
def fileProcess( name, lineFunction ):
filestream = open( name, 'r' )
if filestream.closed:
print( "file " + name + " not open." )
return
output = ""
print( "--- Processing " + name + " ---------" )
while 1:
line = filestream.readline()
if not line: break
output += lineFunction( line )
filestream.close()
if not output: return # basic error checking
print( "Writing file " + name )
filestream = open( name, "w" );
filestream.write( output );
filestream.close()
def echoInput( line ):
return line
parser = optparse.OptionParser( "usage: %prog major minor build" )
(options, args) = parser.parse_args()
if len(args) != 3:
parser.error( "incorrect number of arguments" );
major = args[0]
minor = args[1]
build = args[2]
versionStr = major + "." + minor + "." + build
print ("Setting dox,tinyxml2.h")
print ("Version: " + major + "." + minor + "." + build)
#### Write the tinyxml.h ####
def engineRule( line ):
matchMajor = "static const int TIXML2_MAJOR_VERSION"
matchMinor = "static const int TIXML2_MINOR_VERSION"
matchBuild = "static const int TIXML2_PATCH_VERSION"
if line[0:len(matchMajor)] == matchMajor:
print( "1)tinyxml2.h Major found" )
return matchMajor + " = " + major + ";\n"
elif line[0:len(matchMinor)] == matchMinor:
print( "2)tinyxml2.h Minor found" )
return matchMinor + " = " + minor + ";\n"
elif line[0:len(matchBuild)] == matchBuild:
print( "3)tinyxml2.h Build found" )
return matchBuild + " = " + build + ";\n"
else:
return line;
fileProcess( "tinyxml2.h", engineRule )
def macroVersionRule( line ):
matchMajor = "#define TINYXML2_MAJOR_VERSION"
matchMinor = "#define TINYXML2_MINOR_VERSION"
matchBuild = "#define TINYXML2_PATCH_VERSION"
if line[0:len(matchMajor)] == matchMajor:
print( "1)macro Major found" )
return matchMajor + " " + major + "\n"
elif line[0:len(matchMinor)] == matchMinor:
print( "2)macro Minor found" )
return matchMinor + " " + minor + "\n"
elif line[0:len(matchBuild)] == matchBuild:
print( "3)macro Build found" )
return matchBuild + " " + build + "\n"
else:
return line;
fileProcess("tinyxml2.h", macroVersionRule)
#### Write the dox ####
def doxRule( line ):
match = "PROJECT_NUMBER"
if line[0:len( match )] == match:
print( "dox project found" )
return "PROJECT_NUMBER = " + major + "." + minor + "." + build + "\n"
else:
return line;
fileProcess( "dox", doxRule )
#### Write the CMakeLists.txt ####
def cmakeRule1( line ):
matchVersion = "set(GENERIC_LIB_VERSION"
if line[0:len(matchVersion)] == matchVersion:
print( "1)tinyxml2.h Major found" )
return matchVersion + " \"" + major + "." + minor + "." + build + "\")" + "\n"
else:
return line;
fileProcess( "CMakeLists.txt", cmakeRule1 )
def cmakeRule2( line ):
matchSoversion = "set(GENERIC_LIB_SOVERSION"
if line[0:len(matchSoversion)] == matchSoversion:
print( "1)tinyxml2.h Major found" )
return matchSoversion + " \"" + major + "\")" + "\n"
else:
return line;
fileProcess( "CMakeLists.txt", cmakeRule2 )
def mesonRule(line):
match = re.search(r"(\s*version) : '(\d+.\d+.\d+)',", line)
if match:
print("1)meson.build version found.")
return "{} : '{}.{}.{}',\n".format(match.group(1), major, minor, build)
return line
fileProcess("meson.build", mesonRule)
print( "Release note:" )
print( '1. Build. g++ -Wall -DTINYXML2_DEBUG tinyxml2.cpp xmltest.cpp -o gccxmltest.exe' )
print( '2. Commit. git commit -am"setting the version to ' + versionStr + '"' )
print( '3. Tag. git tag ' + versionStr )
print( ' OR git tag -a ' + versionStr + ' -m [tag message]' )
print( 'Remember to "git push" both code and tag. For the tag:' )
print( 'git push origin [tagname]')
| 24.980519 | 92 | 0.639199 |
1356129dc0abaeb018a9096112b5fdcb2597e545
| 1,024 |
py
|
Python
|
frappe-bench/apps/erpnext/erpnext/patches/v4_2/repost_sle_for_si_with_no_warehouse.py
|
Semicheche/foa_frappe_docker
|
a186b65d5e807dd4caf049e8aeb3620a799c1225
|
[
"MIT"
] | 1 |
2021-04-29T14:55:29.000Z
|
2021-04-29T14:55:29.000Z
|
frappe-bench/apps/erpnext/erpnext/patches/v4_2/repost_sle_for_si_with_no_warehouse.py
|
Semicheche/foa_frappe_docker
|
a186b65d5e807dd4caf049e8aeb3620a799c1225
|
[
"MIT"
] | null | null | null |
frappe-bench/apps/erpnext/erpnext/patches/v4_2/repost_sle_for_si_with_no_warehouse.py
|
Semicheche/foa_frappe_docker
|
a186b65d5e807dd4caf049e8aeb3620a799c1225
|
[
"MIT"
] | 1 |
2021-04-29T14:39:01.000Z
|
2021-04-29T14:39:01.000Z
|
# Copyright (c) 2013, Web Notes Technologies Pvt. Ltd. and Contributors
# License: GNU General Public License v3. See license.txt
from __future__ import print_function, unicode_literals
import frappe
from erpnext.stock.stock_ledger import NegativeStockError
def execute():
si_list = frappe.db.sql("""select distinct si.name
from `tabSales Invoice Item` si_item, `tabSales Invoice` si
where si.name = si_item.parent and si.modified > '2015-02-16' and si.docstatus=1
and ifnull(si_item.warehouse, '') = '' and ifnull(si.update_stock, 0) = 1
order by posting_date, posting_time""", as_dict=1)
failed_list = []
for si in si_list:
try:
si_doc = frappe.get_doc("Sales Invoice", si.name)
si_doc.docstatus = 2
si_doc.on_cancel()
si_doc.docstatus = 1
si_doc.set_missing_item_details()
si_doc.on_submit()
frappe.db.commit()
except:
failed_list.append(si.name)
frappe.local.stockledger_exceptions = None
frappe.db.rollback()
print("Failed to repost: ", failed_list)
| 30.117647 | 83 | 0.723633 |
138d7bc4b0520e3a2db37c0f407ede225496a386
| 388 |
py
|
Python
|
Django/ballon/migrations/0002_auto_20180827_2341.py
|
ballon3/GRAD
|
c630e32272fe34ead590c04d8360169e02be87f1
|
[
"MIT"
] | null | null | null |
Django/ballon/migrations/0002_auto_20180827_2341.py
|
ballon3/GRAD
|
c630e32272fe34ead590c04d8360169e02be87f1
|
[
"MIT"
] | null | null | null |
Django/ballon/migrations/0002_auto_20180827_2341.py
|
ballon3/GRAD
|
c630e32272fe34ead590c04d8360169e02be87f1
|
[
"MIT"
] | null | null | null |
# Generated by Django 2.1 on 2018-08-28 06:41
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('ballon', '0001_initial'),
]
operations = [
migrations.RemoveField(
model_name='resume',
name='category',
),
migrations.DeleteModel(
name='Category',
),
]
| 18.47619 | 45 | 0.556701 |
16570c371b0050e20e4bd40f17bb05001dc4a9ef
| 65 |
py
|
Python
|
Programming Languages/Python/Theory/100_Python_Exercises/Exercises/Exercise 1/1.py
|
jaswinder9051998/Resources
|
fd468af37bf24ca57555d153ee64693c018e822e
|
[
"MIT"
] | 101 |
2021-12-20T11:57:11.000Z
|
2022-03-23T09:49:13.000Z
|
50-Python-Exercises/Exercises/Exercise 1/1.py
|
kuwarkapur/Hacktoberfest-2022
|
efaafeba5ce51d8d2e2d94c6326cc20bff946f17
|
[
"MIT"
] | 4 |
2022-01-12T11:55:56.000Z
|
2022-02-12T04:53:33.000Z
|
50-Python-Exercises/Exercises/Exercise 1/1.py
|
kuwarkapur/Hacktoberfest-2022
|
efaafeba5ce51d8d2e2d94c6326cc20bff946f17
|
[
"MIT"
] | 38 |
2022-01-12T11:56:16.000Z
|
2022-03-23T10:07:52.000Z
|
#What will this script produce?
#A: 3
a = 1
a = 2
a = 3
print(a)
| 9.285714 | 31 | 0.6 |
169285c1ac74a7a129c46f31b711141ae326ac5b
| 6,780 |
py
|
Python
|
core/execute.py
|
littlecharacter/AutoWork
|
feebb8459f889b7a9165073be8fd44ba544cbb35
|
[
"Apache-2.0"
] | null | null | null |
core/execute.py
|
littlecharacter/AutoWork
|
feebb8459f889b7a9165073be8fd44ba544cbb35
|
[
"Apache-2.0"
] | null | null | null |
core/execute.py
|
littlecharacter/AutoWork
|
feebb8459f889b7a9165073be8fd44ba544cbb35
|
[
"Apache-2.0"
] | null | null | null |
import os
import time
import copy
import threading
from queue import Queue
from core.orm import *
import cv2
import pyautogui
import pyperclip
import pyscreeze
import subprocess
import platform
pyautogui.FAILSAFE = False
IMG_PATH = '../img/'
run_flag = Queue(1)
run_work = {}
stop_signal = Queue(1)
class WorkThread(threading.Thread):
def __init__(self, threadID, name):
threading.Thread.__init__(self)
self.threadID = threadID
self.name = name
self.wid = None
# 把要执行的代码写到run函数里面 线程在创建后会直接运行run函数
def run(self):
try:
run_flag.put_nowait(self)
global run_work
run_work['wid'] = self.wid
flow_dict = get_special_data(self.wid, FLOW_FILENAME)
flow_dict['flow'] = sorted(flow_dict['flow'], key=lambda x: x['order'])
flow_item_list = copy.deepcopy(flow_dict['flow'])
monitor_item_list = []
monitor_dict = get_special_data(self.wid, MONITOR_FILENAME)
if monitor_dict:
monitor_item_list = monitor_dict['monitor']
while True:
if stop_signal.full():
break
# 执行流程
if not flow_item_list:
flow_item_list = copy.deepcopy(flow_dict['flow'])
flow_item = flow_item_list[0]
if execute(self, flow_item['op_type'], flow_item['op_content']):
flow_item_list.remove(flow_item)
# 执行监控
if monitor_item_list:
for monitor_item in monitor_item_list:
execute(self, monitor_item['op_type'], monitor_item['op_content'])
time.sleep(1)
except:
pass
@unique
class OperateTypeEnum(Enum):
LEFT_CLICK = {'code': 1, 'desc': '单击'}
DOUBLE_CLICK = {'code': 2, 'desc': '双击'}
RIGHT_CLICK = {'code': 3, 'desc': '右击'}
LEFT_CLICK_IMG = {'code': 4, 'desc': '单击图片'}
DOUBLE_CLICK_IMG = {'code': 5, 'desc': '双击图片'}
KEY_PRESS = {'code': 6, 'desc': '按键'}
HOT_KEY = {'code': 7, 'desc': '热键'}
KEY_MAP = {'code': 8, 'desc': '快捷键'}
INPUT = {'code': 9, 'desc': '输入'}
OPEN_APP = {'code': 10, 'desc': '打开APP'}
@staticmethod
def get_enum(code):
for e in OperateTypeEnum:
if code == e.value['code']:
return e
def code(self):
return self.value['code']
def desc(self):
return self.value['desc']
def execute(self, op_type, op_content):
print(op_content)
op_type_enum = OperateTypeEnum.get_enum(op_type)
# 1-单击
if op_type_enum == OperateTypeEnum.LEFT_CLICK:
position = op_content.split(",")
x, y = pyautogui.position()
pyautogui.moveTo(x=x+int(position[0]), y=y+int(position[1]), duration=0.25)
pyautogui.click()
return True
# 2-双击
elif op_type_enum == OperateTypeEnum.DOUBLE_CLICK:
position = op_content.split(",")
x, y = pyautogui.position()
pyautogui.moveTo(x=x + int(position[0]), y=y + int(position[1]), duration=0.25)
pyautogui.doubleClick()
return True
# 3-右击
elif op_type_enum == OperateTypeEnum.RIGHT_CLICK:
position = op_content.split(",")
x, y = pyautogui.position()
pyautogui.moveTo(x=x + int(position[0]), y=y + int(position[1]), duration=0.25)
pyautogui.rightClick()
return True
# 4-单击图片
elif op_type_enum == OperateTypeEnum.LEFT_CLICK_IMG:
return click_img(self.wid, op_content, 1)
# 5-单击图片
elif op_type_enum == OperateTypeEnum.DOUBLE_CLICK_IMG:
return click_img(self.wid, op_content, 2)
# 6-按键
elif op_type_enum == OperateTypeEnum.KEY_PRESS:
pyautogui.press(op_content)
return True
# 7-热键
elif op_type_enum == OperateTypeEnum.HOT_KEY:
keys = op_content.split(",")
pyautogui.hotkey(keys[0], keys[1])
return True
# 8-快捷键
elif op_type_enum == OperateTypeEnum.KEY_MAP:
keys = op_content.split("+")
for key in keys[0:-1]:
pyautogui.keyDown(key)
pyautogui.press(keys[-1])
keys.reverse()
for key in keys[1:]:
pyautogui.keyUp(key)
return True
# 9-输入
elif op_type_enum == OperateTypeEnum.INPUT:
pyperclip.copy(op_content)
time.sleep(0.5)
if platform.system().lower() == 'windows':
pyautogui.hotkey('ctrl', 'v')
else:
pyautogui.hotkey('command', 'v')
return True
# 10-打开APP
elif op_type_enum == OperateTypeEnum.OPEN_APP:
if platform.system().lower() == 'windows':
subprocess.Popen(op_content)
else:
os.system(f'open \"{op_content}\"')
return True
return False
def click_img(wid, op_content, click_num):
# 初始化目录
if not os.path.exists(IMG_PATH):
os.makedirs(IMG_PATH)
if not os.path.exists(f"{IMG_PATH}/{wid}/"):
os.makedirs(f"{IMG_PATH}/{wid}/")
# 屏幕缩放系数 mac缩放是2 windows一般是1
screenScale = pyautogui.screenshot().size[0] / pyautogui.size()[0]
# print(pyautogui.size())
# print(f"屏幕缩放系数：{screenScale}")
# 事先读取按钮截图
img_path = f"{IMG_PATH}/{wid}/{op_content}"
target = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)
if target is None:
print("未找到目标图片")
return
targetHeight, targetWidth = target.shape[:2]
# 先截图
screenshot = pyscreeze.screenshot(f"{IMG_PATH}/screenshot.png")
# 读取图片 灰色会快
source = cv2.imread(f"{IMG_PATH}/screenshot.png", cv2.IMREAD_GRAYSCALE)
# sourceHeight, sourceWidth = source.shape[:2]
# 先缩放屏幕截图(本程序中无需缩放，因为截图就是原图)
# sourceScale = cv2.resize(source, (int(sourceWidth / screenScale), int(sourceHeight / screenScale)), interpolation=cv2.INTER_AREA)
# print(sourceScale.shape[:2])
# 匹配图片
matchResult = cv2.matchTemplate(source, target, cv2.TM_CCOEFF_NORMED)
minVal, maxVal, minLoc, maxLoc = cv2.minMaxLoc(matchResult)
# print(f"minVal:{minVal},maxVal:{maxVal},minLoc:{minLoc},maxLoc:{maxLoc}")
if maxVal >= 0.8:
# 计算出中心点(因为截图就是原图，所以这里要缩放)
tagHalfW = int(targetWidth / screenScale / 2)
tagHalfH = int(targetHeight / screenScale / 2)
tagCenterX = maxLoc[0] / screenScale + tagHalfW
tagCenterY = maxLoc[1] / screenScale + tagHalfH
# 左键点击屏幕上的这个位置
print(f"tagCenterX:{tagCenterX},tagCenterY:{tagCenterY}")
# pyautogui.click(tagCenterX, tagCenterY, button='left')
pyautogui.moveTo(x=tagCenterX, y=tagCenterY, duration=0.25)
if click_num == 1:
pyautogui.click()
elif click_num == 2:
pyautogui.doubleClick()
return True
print(f"没有匹配到{op_content}")
return False
| 33.235294 | 135 | 0.604277 |
1696bcdc44faf9716acc2873aabb989ef4b6baca
| 1,521 |
py
|
Python
|
deprecated/fleet_x/examples/bert_app.py
|
hutuxian/FleetX
|
843c7aa33f5a14680becf058a3aaf0327eefafd4
|
[
"Apache-2.0"
] | 170 |
2020-08-12T12:07:01.000Z
|
2022-03-07T02:38:26.000Z
|
deprecated/fleet_x/examples/bert_app.py
|
hutuxian/FleetX
|
843c7aa33f5a14680becf058a3aaf0327eefafd4
|
[
"Apache-2.0"
] | 195 |
2020-08-13T03:22:15.000Z
|
2022-03-30T07:40:25.000Z
|
deprecated/fleet_x/examples/bert_app.py
|
hutuxian/FleetX
|
843c7aa33f5a14680becf058a3aaf0327eefafd4
|
[
"Apache-2.0"
] | 67 |
2020-08-14T02:07:46.000Z
|
2022-03-28T10:05:33.000Z
|
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed 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.
import paddle
import fleetx as X
import paddle.distributed.fleet as fleet
paddle.enable_static()
fleet.init(is_collective=True)
configs = X.parse_train_configs()
model = X.applications.BertBase()
downloader = X.utils.Downloader()
local_path = downloader.download_from_bos(
fs_yaml='https://fleet.bj.bcebos.com/small_datasets/yaml_example/wiki_cn.yaml',
local_path='./data')
loader = model.get_train_dataloader(data_dir=local_path)
dist_strategy = fleet.DistributedStrategy()
dist_strategy.amp = True
learning_rate = X.utils.linear_warmup_decay(configs.lr, 4000, 1000000)
clip = paddle.fluid.clip.GradientClipByGlobalNorm(clip_norm=1.0)
optimizer = paddle.fluid.optimizer.Adam(
learning_rate=learning_rate, grad_clip=clip)
optimizer = fleet.distributed_optimizer(optimizer, strategy=dist_strategy)
optimizer.minimize(model.loss)
trainer = X.MultiGPUTrainer()
trainer.fit(model, loader, epoch=1)
| 37.097561 | 83 | 0.788297 |
bcaddff8d887bb1fd1c11d78ed87b7479ca2753e
| 2,714 |
py
|
Python
|
build/cpp/verify_runtime_deps.py
|
opensource-assist/fuschia
|
66646c55b3d0b36aae90a4b6706b87f1a6261935
|
[
"BSD-3-Clause"
] | null | null | null |
build/cpp/verify_runtime_deps.py
|
opensource-assist/fuschia
|
66646c55b3d0b36aae90a4b6706b87f1a6261935
|
[
"BSD-3-Clause"
] | null | null | null |
build/cpp/verify_runtime_deps.py
|
opensource-assist/fuschia
|
66646c55b3d0b36aae90a4b6706b87f1a6261935
|
[
"BSD-3-Clause"
] | null | null | null |
#!/usr/bin/env python2.7
# Copyright 2018 The Fuchsia Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import argparse
import json
import os
import sys
def has_packaged_file(needed_file, deps):
"""Returns true if the given file could be found in the given deps."""
for dep in deps:
for file in dep['files']:
if needed_file == os.path.normpath(file['source']):
return True
return False
def has_missing_files(runtime_files, package_deps):
"""Returns true if a runtime file is missing from the given deps."""
has_missing_files = False
for file in runtime_files:
# Some libraries are only known to GN as ABI stubs, whereas the real
# runtime dependency is generated in parallel as a ".so.impl" file.
if (not has_packaged_file(file, package_deps) and
not has_packaged_file('%s.impl' % file, package_deps)):
print('No package dependency generates %s' % file)
has_missing_files = True
return has_missing_files
def main():
parser = argparse.ArgumentParser(
"Verifies a prebuilt library's runtime dependencies")
parser.add_argument(
'--root-build-dir',
help='Path to the root build directory',
required=True)
parser.add_argument(
'--runtime-deps-file',
help='Path to the list of runtime deps',
required=True)
parser.add_argument(
'--manifest',
help='Path to the target\'s SDK manifest file',
required=True)
parser.add_argument(
'--stamp', help='Path to the stamp file to generate', required=True)
args = parser.parse_args()
# Read the list of runtime dependencies generated by GN.
def normalize_dep(dep):
return os.path.normpath(os.path.join(args.root_build_dir, dep.strip()))
with open(args.runtime_deps_file, 'r') as runtime_deps_file:
runtime_files = map(normalize_dep, runtime_deps_file.readlines())
# Read the list of package dependencies for the library's SDK incarnation.
with open(args.manifest, 'r') as manifest_file:
manifest = json.load(manifest_file)
atom_id = manifest['ids'][0]
def find_atom(id):
return next(a for a in manifest['atoms'] if a['id'] == id)
atom = find_atom(atom_id)
deps = map(lambda a: find_atom(a), atom['deps'])
deps += [atom]
# Check whether all runtime files are available for packaging.
if has_missing_files(runtime_files, deps):
return 1
with open(args.stamp, 'w') as stamp:
stamp.write('Success!')
if __name__ == '__main__':
sys.exit(main())
| 33.097561 | 79 | 0.660648 |
d5c48ed1b49eda67aaff43b79819a2e01281381f
| 925 |
py
|
Python
|
Python/zzz_training_challenge/Python_Challenge/solutions/ch05_datastructures/util/ListUtils.py
|
Kreijeck/learning
|
eaffee08e61f2a34e01eb8f9f04519aac633f48c
|
[
"MIT"
] | null | null | null |
Python/zzz_training_challenge/Python_Challenge/solutions/ch05_datastructures/util/ListUtils.py
|
Kreijeck/learning
|
eaffee08e61f2a34e01eb8f9f04519aac633f48c
|
[
"MIT"
] | null | null | null |
Python/zzz_training_challenge/Python_Challenge/solutions/ch05_datastructures/util/ListUtils.py
|
Kreijeck/learning
|
eaffee08e61f2a34e01eb8f9f04519aac633f48c
|
[
"MIT"
] | null | null | null |
# Beispielprogramm für das Buch "Python Challenge"
#
# Copyright 2020 by Michael Inden
def swap(values, first, second):
value1 = values[first]
value2 = values[second]
values[first] = value2
values[second] = value1
def swap(values, first, second):
tmp = values[first]
values[first] = values[second]
values[second] = tmp
def find(values, search_for):
for i in range(len(values)):
if values[i] == search_for:
return i
return -1
def find(values, search_for):
pos = 0
while pos < len(values) and not values[pos] == search_for:
pos += 1
# i >= len(values) or values[i] == searchFor
return -1 if pos >= len(values) else pos
def find_with_enumerate(values, search_for):
for i, value in enumerate(values):
if value == search_for:
return i
return -1
def main():
pass
if __name__ == "__main__":
main()
| 18.137255 | 62 | 0.617297 |
e6cf49e5934c0be95398f25368e771acb43175b6
| 1,440 |
py
|
Python
|
ebenezer/atencion/migrations/0009_level.py
|
davrv93/ebenezer-backend
|
d3db4dafd9a8c35bea9f32afe2be1dd451f64298
|
[
"Apache-2.0"
] | null | null | null |
ebenezer/atencion/migrations/0009_level.py
|
davrv93/ebenezer-backend
|
d3db4dafd9a8c35bea9f32afe2be1dd451f64298
|
[
"Apache-2.0"
] | 3 |
2020-02-11T23:15:00.000Z
|
2021-06-10T20:52:17.000Z
|
ebenezer/atencion/migrations/0009_level.py
|
davrv93/ebenezer-backend
|
d3db4dafd9a8c35bea9f32afe2be1dd451f64298
|
[
"Apache-2.0"
] | null | null | null |
# Generated by Django 2.1.2 on 2018-10-05 13:43
from django.db import migrations, models
import django.db.models.deletion
import mptt.fields
import uuid
class Migration(migrations.Migration):
dependencies = [
('atencion', '0008_typeoflevel'),
]
operations = [
migrations.CreateModel(
name='Level',
fields=[
('id', models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False)),
('name', models.CharField(max_length=50, unique=True)),
('description', models.TextField(blank=True, null=True)),
('lft', models.PositiveIntegerField(db_index=True, editable=False)),
('rght', models.PositiveIntegerField(db_index=True, editable=False)),
('tree_id', models.PositiveIntegerField(db_index=True, editable=False)),
('level', models.PositiveIntegerField(db_index=True, editable=False)),
('parent', mptt.fields.TreeForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='children', to='atencion.Level')),
('type_of_level', models.ForeignKey(db_column='type_of_level_id', on_delete=django.db.models.deletion.CASCADE, related_name='level_type_of_level_set', to='atencion.TypeOfLevel')),
],
options={
'abstract': False,
},
),
]
| 42.352941 | 195 | 0.629861 |
fc006934a13cf8982d1cb7088c731a90c14873bf
| 2,965 |
py
|
Python
|
Co-Simulation/Sumo/sumo-1.7.0/tools/traci/storage.py
|
uruzahe/carla
|
940c2ab23cce1eda1ef66de35f66b42d40865fb1
|
[
"MIT"
] | 4 |
2020-11-13T02:35:56.000Z
|
2021-03-29T20:15:54.000Z
|
Co-Simulation/Sumo/sumo-1.7.0/tools/traci/storage.py
|
uruzahe/carla
|
940c2ab23cce1eda1ef66de35f66b42d40865fb1
|
[
"MIT"
] | 9 |
2020-12-09T02:12:39.000Z
|
2021-02-18T00:15:28.000Z
|
Co-Simulation/Sumo/sumo-1.7.0/tools/traci/storage.py
|
uruzahe/carla
|
940c2ab23cce1eda1ef66de35f66b42d40865fb1
|
[
"MIT"
] | 1 |
2020-11-20T19:31:26.000Z
|
2020-11-20T19:31:26.000Z
|
# -*- coding: utf-8 -*-
# Eclipse SUMO, Simulation of Urban MObility; see https://eclipse.org/sumo
# Copyright (C) 2008-2020 German Aerospace Center (DLR) and others.
# This program and the accompanying materials are made available under the
# terms of the Eclipse Public License 2.0 which is available at
# https://www.eclipse.org/legal/epl-2.0/
# This Source Code may also be made available under the following Secondary
# Licenses when the conditions for such availability set forth in the Eclipse
# Public License 2.0 are satisfied: GNU General Public License, version 2
# or later which is available at
# https://www.gnu.org/licenses/old-licenses/gpl-2.0-standalone.html
# SPDX-License-Identifier: EPL-2.0 OR GPL-2.0-or-later
# @file storage.py
# @author Michael Behrisch
# @author Lena Kalleske
# @author Mario Krumnow
# @author Daniel Krajzewicz
# @author Jakob Erdmann
# @date 2008-10-09
from __future__ import print_function
from __future__ import absolute_import
import struct
from . import constants as tc
_DEBUG = False
class Storage:
def __init__(self, content):
self._content = content
self._pos = 0
def read(self, format):
oldPos = self._pos
self._pos += struct.calcsize(format)
return struct.unpack(format, self._content[oldPos:self._pos])
def readInt(self):
return self.read("!i")[0]
def readTypedInt(self):
t, i = self.read("!Bi")
assert(t == tc.TYPE_INTEGER)
return i
def readDouble(self):
return self.read("!d")[0]
def readTypedDouble(self):
t, d = self.read("!Bd")
assert(t == tc.TYPE_DOUBLE)
return d
def readLength(self):
length = self.read("!B")[0]
if length > 0:
return length
return self.read("!i")[0]
def readString(self):
length = self.read("!i")[0]
return str(self.read("!%ss" % length)[0].decode("latin1"))
def readTypedString(self):
t = self.read("!B")[0]
assert t == tc.TYPE_STRING, "expected TYPE_STRING (%02x), found %02x." % (tc.TYPE_STRING, t)
return self.readString()
def readStringList(self):
n = self.read("!i")[0]
return tuple([self.readString() for i in range(n)])
def readTypedStringList(self):
t = self.read("!B")[0]
assert(t == tc.TYPE_STRINGLIST)
return self.readStringList()
def readShape(self):
length = self.readLength()
return tuple([self.read("!dd") for i in range(length)])
def readCompound(self, expectedSize=None):
t, s = self.read("!Bi")
assert(t == tc.TYPE_COMPOUND)
assert(expectedSize is None or s == expectedSize)
return s
def ready(self):
return self._pos < len(self._content)
def printDebug(self):
if _DEBUG:
for char in self._content[self._pos:]:
print("%03i %02x %s" % (ord(char), ord(char), char))
| 29.949495 | 100 | 0.633052 |
5d5e2faa22593ed62da301da0114b2b99e99f783
| 2,073 |
py
|
Python
|
code/1/utest.py
|
pwang13/AutomatedSE_Coursework
|
b416672d9756fcc60367143b989d29b0c905cfc3
|
[
"Unlicense"
] | null | null | null |
code/1/utest.py
|
pwang13/AutomatedSE_Coursework
|
b416672d9756fcc60367143b989d29b0c905cfc3
|
[
"Unlicense"
] | null | null | null |
code/1/utest.py
|
pwang13/AutomatedSE_Coursework
|
b416672d9756fcc60367143b989d29b0c905cfc3
|
[
"Unlicense"
] | null | null | null |
#!/usr/bin/python
"""
utest.py (c) 2016 [email protected], MIT licence
Part of http://tiny.cc/ase16: teaching tools for
(model-based) automated software enginering.
USAGE:
(1) If you place '@ok' before a function, then
load that file, then that function will execute and
all assertion failures will add one to a FAIL
count.
(2) To get the final counts, add 'oks()' at the end
of the source code.
For more on this kind of tool, see
https://www.youtube.com/watch?v=nIonZ6-4nuU
"""
from __future__ import division,print_function
import sys,re,traceback,random,string
sys.dont_write_bytecode=True
PASS=FAIL=0
VERBOSE=True
def oks():
global PASS, FAIL
print("\n# PASS= %s FAIL= %s %%PASS = %s%%" % (
PASS, FAIL, int(round(PASS*100/(PASS+FAIL+0.001)))))
def ok(f):
global PASS, FAIL
try:
print("\n-----| %s |-----------------------" % f.__name__)
if f.__doc__:
print("# "+ re.sub(r'\n[ \t]*',"\n# ",f.__doc__))
f()
print("# pass")
PASS += 1
except Exception,e:
FAIL += 1
print(traceback.format_exc())
return f
#################################################
def same(x):
return x
def any(lst):
return random.choice(lst)
def any3(lst,a=None,b=None,c=None,it = same,retries=10):
assert retries > 0
a = a or any(lst)
b = b or any(lst)
if it(a) == it(b):
return any3(lst,a=a,b=None,it=it,retries=retries - 1)
c = any(lst)
if it(a) == it(c) or it(b) == it(c):
return any3(lst,a=a,b=b,it=it,retries=retries - 1)
return a,b,c
@ok
def _ok1():
"Can at least one test fail?"
assert 1==2, "equality failure"
@ok
def _ok2():
"Can at least one test pass?"
assert 1==1, "equality failure"
@ok
def _any3():
"""There are 2600 three letter alphanet combinations.
So if we pick just 10, there should be no repeats."""
random.seed(1)
lst=list(string.ascii_lowercase) # abcdefghijklmnopqrstuvwxyz
seen = {}
for x in sorted([''.join(any3(lst)) for _ in xrange(10)]):
seen[x] = seen.get(x,0) + 1
for k,v in seen.items():
assert v < 2
print("")
oks()
| 24.104651 | 64 | 0.611674 |
53bb8d640caf8b9381c100c0bce1f921964c5e35
| 8,422 |
py
|
Python
|
V1/DDPG/ddpg_v1.py
|
marsXyr/GESRL
|
3d60dfd4ffa1e0ae24d64b09f431d8ee0a9b5c01
|
[
"Apache-2.0"
] | null | null | null |
V1/DDPG/ddpg_v1.py
|
marsXyr/GESRL
|
3d60dfd4ffa1e0ae24d64b09f431d8ee0a9b5c01
|
[
"Apache-2.0"
] | null | null | null |
V1/DDPG/ddpg_v1.py
|
marsXyr/GESRL
|
3d60dfd4ffa1e0ae24d64b09f431d8ee0a9b5c01
|
[
"Apache-2.0"
] | null | null | null |
import argparse
import numpy as np
import gym
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from utils import logz
from utils.tools import get_output_folder, OUNoise, hard_update, soft_update
from utils.buffer import ReplayBuffer
FloatTensor = torch.FloatTensor
"""
Actor 和 Critic 分开训练
"""
class Actor(nn.Module):
def __init__(self, state_dim, action_dim, max_action, args):
super(Actor, self).__init__()
self.l1 = nn.Linear(state_dim, action_dim, bias=False)
self.max_action = max_action
self.optim = optim.Adam(self.parameters(), lr=args.critic_lr)
self.loss = nn.MSELoss()
def forward(self, x):
out = self.l1(x)
# abs_out = torch.abs(out)
# abs_out_sum = torch.sum(abs_out).view(-1, 1)
# abs_out_mean = abs_out_sum / self.action_dim / self.theta
# ones = torch.ones(abs_out_mean.size())
# ones = ones.cuda()
# mod = torch.where(abs_out_mean >= 1, abs_out_mean, ones)
# out = out / mod
#
out = self.max_action * torch.tanh(out)
return out
def update(self, memory, batch_size, critic, actor_t):
# Sample replay buffer
states, _, _, _, _ = memory.sample(batch_size)
# Compute actor loss
actor_loss = - critic(states, self(states)).mean()
# Optimize the policy
self.optim.zero_grad()
actor_loss.backward()
self.optim.step()
grads = self.get_grads() # Get policy gradients
return grads
def get_grads(self):
grads = [v.grad.data.numpy() for v in self.parameters()]
return grads[0]
def get_params(self):
params = [v.data.numpy() for v in self.parameters()]
return params[0]
def set_params(self, w):
for i, param in enumerate(self.parameters()):
param.data.copy_(torch.from_numpy(w).view(param.size()))
class Critic(nn.Module):
def __init__(self, state_dim, action_dim, args):
super(Critic, self).__init__()
l1_dim, l2_dim = 400, 300
self.l1 = nn.Linear(state_dim + action_dim, l1_dim)
self.l2 = nn.Linear(l1_dim, l2_dim)
self.l3 = nn.Linear(l2_dim, 1)
if args.layer_norm:
self.n1 = nn.LayerNorm(l1_dim)
self.n2 = nn.LayerNorm(l2_dim)
self.layer_norm = args.layer_norm
self.discount = args.discount
self.optim = optim.Adam(self.parameters(), lr=args.critic_lr)
self.loss = nn.MSELoss()
def forward(self, x, u):
if not self.layer_norm:
x = F.leaky_relu(self.l1(torch.cat([x, u], 1)))
x = F.leaky_relu(self.l2(x))
x = self.l3(x)
else:
x = F.leaky_relu(self.n1(self.l1(torch.cat([x, u], 1))))
x = F.leaky_relu(self.n2(self.l2(x)))
x = self.l3(x)
return x
def update(self, buffer, batch_size, actor_t, critic_t):
# Sample replay buffer
states, n_states, actions, rewards, dones = buffer.sample(batch_size)
# Compute q target
next_q = critic_t(n_states, actor_t(n_states))
q_target = (rewards + self.discount * (1 - dones.float()) * next_q).detach()
# Compute q predict
q_predict = self(states, actions)
# Compute critic loss
critic_loss = self.loss(q_target, q_predict)
# Optimize the critic
self.optim.zero_grad()
critic_loss.backward()
self.optim.step()
class DDPG:
def __init__(self, state_dim, action_dim, max_action, args):
self.state_dim = state_dim
self.action_dim = action_dim
self.max_action = max_action
self._init_parameters(args)
self._init_nets(args)
self.replay_buffer = ReplayBuffer(self.buffer_size, self.state_dim, self.action_dim)
def _init_parameters(self, args):
self.actor_lr = args.actor_lr
self.critic_lr = args.critic_lr
self.discount = args.discount
self.tau = args.tau
self.buffer_size = args.buffer_size
self.batch_size = args.batch_size
def _init_nets(self, args):
self.actor = Actor(self.state_dim, self.action_dim, self.max_action, args)
self.actor_t = Actor(self.state_dim, self.action_dim, self.max_action, args)
self.critic = Critic(self.state_dim, self.action_dim, args)
self.critic_t = Critic(self.state_dim, self.action_dim, args)
hard_update(self.actor_t, self.actor)
hard_update(self.critic_t, self.critic)
def train(self):
self.critic.update(self.replay_buffer, self.batch_size, self.actor, self.critic_t)
grad = self.actor.update(self.replay_buffer, self.batch_size, self.critic, self.actor_t)
return grad
def update_nets(self):
soft_update(self.actor_t, self.actor, self.tau)
soft_update(self.critic_t, self.critic, self.tau)
def run(args):
log_dir = args.dir_path
env = gym.make(args.env)
state_dim = env.observation_space.shape[0]
action_dim = env.action_space.shape[0]
max_action = int(env.action_space.high[0])
env.seed(args.seed)
np.random.seed(args.seed)
torch.manual_seed(args.seed)
ddpg = DDPG(state_dim, action_dim, max_action, args)
ounoise = OUNoise(action_dim)
def get_action(state, noise=None):
action = ddpg.actor(FloatTensor(state))
action = (action.data.numpy() + noise.add()) if noise else action.data.numpy()
return np.clip(action, -max_action, max_action)
def rollout(eval=False):
state, done, ep_reward, ep_len = env.reset(), False, 0.0, 0
while not done and ep_len < args.max_ep_len:
if not eval:
action = get_action(state, noise=ounoise)
else:
action = get_action(state)
next_state, reward, done, _ = env.step(action)
if not eval:
done = False if ep_len + 1 == args.max_ep_len else done
ddpg.replay_buffer.store((state, next_state, action, reward, done))
ep_reward += reward
ep_len += 1
state = next_state
return ep_reward, ep_len
for epoch in range(args.epochs):
ep_reward, ep_len = rollout(eval=False)
if epoch > args.start_epoch:
for _ in range(ep_len):
ddpg.train()
ddpg.update_nets()
if epoch % args.save_freq == 0:
test_rewards = []
for i in range(10):
reward, _ = rollout()
test_rewards.append(reward)
test_rewards = np.array(test_rewards)
np.savez(log_dir + '/policy_weights', ddpg.actor.get_params())
logz.log_tabular("Epoch", epoch)
logz.log_tabular("AverageTestReward", np.mean(test_rewards))
logz.log_tabular("StdTestRewards", np.std(test_rewards))
logz.log_tabular("MaxTestRewardRollout", np.max(test_rewards))
logz.log_tabular("MinTestRewardRollout", np.min(test_rewards))
logz.dump_tabular()
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--env', type=str, default='HalfCheetah-v2')
# RL parameters
parser.add_argument('--actor_lr', type=float, default=0.0001)
parser.add_argument('--critic_lr', type=float, default=0.0001)
parser.add_argument('--discount', type=float, default=0.99)
parser.add_argument('--tau', type=float, default=0.005)
parser.add_argument('--batch_size', type=int, default=100)
parser.add_argument('--buffer_size', type=int, default=1000000)
parser.add_argument('--max_ep_len', type=int, default=1000)
parser.add_argument('--layer_norm', type=bool, default=True)
parser.add_argument('--epochs', type=int, default=1000)
parser.add_argument('--start_epoch', type=int, default=10)
parser.add_argument('--save_freq', type=int, default=5)
parser.add_argument('--seed', type=int, default=1)
parser.add_argument('--dir_path', type=str, default='results_v1/')
args = parser.parse_args()
output_path = args.dir_path
for seed in range(1, 11):
args.seed = seed
args.dir_path = get_output_folder(output_path, args.env, args.seed)
logz.configure_output_dir(args.dir_path)
logz.save_params(vars(args))
run(args)
| 33.553785 | 96 | 0.628473 |
53cc51a93ef82b14a7ec16ec867df498664a7acf
| 7,468 |
py
|
Python
|
AP_SS16/504/python/plot_helpers.py
|
DimensionalScoop/kautschuk
|
90403f97cd60b9716cb6a06668196891d5d96578
|
[
"MIT"
] | 3 |
2016-04-27T17:07:00.000Z
|
2022-02-02T15:43:15.000Z
|
AP_SS16/504/python/plot_helpers.py
|
DimensionalScoop/kautschuk
|
90403f97cd60b9716cb6a06668196891d5d96578
|
[
"MIT"
] | 5 |
2016-04-27T17:10:03.000Z
|
2017-06-20T14:54:20.000Z
|
AP_SS16/504/python/plot_helpers.py
|
DimensionalScoop/kautschuk
|
90403f97cd60b9716cb6a06668196891d5d96578
|
[
"MIT"
] | null | null | null |
import sys
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import uncertainties
import uncertainties.unumpy as unp
from scipy.constants import C2K, K2C
from scipy.optimize import curve_fit
from uncertainties import ufloat
from uncertainties.unumpy import uarray
def extract_error(data):
if(isinstance(data[0], uncertainties.UFloat)):
error = unp.std_devs(data)
nominal = unp.nominal_values(data)
else:
nominal = data
error = None
return nominal, error
def autolimits(data, err=None):
min_lim = min(data)
max_lim = max(data)
offset = (max(data) - min(data)) * 0.025
if err is not None:
offset += max(err)/2
return [min_lim - offset, max_lim + offset]
def plot(x_messung, y_messung, xlabel, ylabel, filename, theorie):
"""Plottet diskrete Messwerte gegen eine kontinuierliche Messkurve
Args:
x_messung (uarray)
y_messung (uarray)
theorie (func(x)): Theoriefunktion, die x-Werte annimmt und y-Werte ausspuckt
xlabel (string)
ylabel (string)
filename (string)
Returns:
TYPE: None
"""
# plt.clf()
# plt.clf()
x_messung, x_error = extract_error(x_messung)
y_messung, y_error = extract_error(y_messung)
x_limit = autolimits(x_messung, err=x_error)
x_flow = np.linspace(*x_limit, num=1000)
y_messung = y_messung
if theorie is not None:
plt.plot(x_flow, theorie(x_flow), 'g-', label="Fit")
#plt.errorbar(x_messung, y_messung, xerr=x_error, yerr=y_error, fmt='r,', label="Fehler")
plt.plot(x_messung, y_messung, 'r.', label="Messwerte")
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.legend(loc='best')
plt.grid()
plt.tight_layout(pad=0, h_pad=1.18, w_pad=1.18)
# plt.show()
plt.savefig('../plots/' + filename)
def plot2(x_messung, y_messung, xlabel, ylabel, filename, theorie):
"""Plottet diskrete Messwerte gegen eine kontinuierliche Messkurve
Args:
x_messung (uarray)
y_messung (uarray)
theorie (func(x)): Theoriefunktion, die x-Werte annimmt und y-Werte ausspuckt
xlabel (string)
ylabel (string)
filename (string)
Returns:
TYPE: None
"""
# plt.clf()
# plt.clf()
x_messung, x_error = extract_error(x_messung)
y_messung, y_error = extract_error(y_messung)
x_limit = autolimits(x_messung, err=x_error)
x_flow = np.linspace(*x_limit, num=1000)
y_messung = y_messung
if theorie is not None:
plt.plot(x_flow, theorie(x_flow), 'g-', label="Fit")
#plt.errorbar(x_messung, y_messung, xerr=x_error, yerr=y_error, fmt='b,', label="Fehler")
plt.plot(x_messung, y_messung, 'b.', label="Messwerte")
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.legend(loc='best')
plt.xlim(x_limit)
plt.ylim(autolimits(y_messung, err=y_error))
plt.grid()
plt.tight_layout(pad=0, h_pad=1.18, w_pad=1.18)
# plt.show()
plt.grid()
plt.savefig('../plots/' + filename)
def plot3(x_messung, y_messung, xlabel, ylabel, filename, theorie):
"""Plottet diskrete Messwerte gegen eine kontinuierliche Messkurve
Args:
x_messung (uarray)
y_messung (uarray)
theorie (func(x)): Theoriefunktion, die x-Werte annimmt und y-Werte ausspuckt
xlabel (string)
ylabel (string)
filename (string)
Returns:
TYPE: None
"""
# plt.clf()
# plt.clf()
x_messung, x_error = extract_error(x_messung)
y_messung, y_error = extract_error(y_messung)
x_limit = autolimits(x_messung, err=x_error)
x_flow = np.linspace(*x_limit, num=1000)
y_messung = y_messung
if theorie is not None:
plt.plot(x_flow, theorie(x_flow), 'g-', label="Fit")
#plt.errorbar(x_messung, y_messung, xerr=x_error, yerr=y_error, fmt='r,', label="Fehler")
plt.plot(x_messung, y_messung, 'g.', label="Messwerte")
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.legend(loc='best')
plt.grid()
plt.tight_layout(pad=0, h_pad=1.18, w_pad=1.18)
# plt.show()
plt.savefig('../plots/' + filename)
def plot4(x_messung, y_messung, xlabel, ylabel, filename, theorie):
"""Plottet diskrete Messwerte gegen eine kontinuierliche Messkurve
Args:
x_messung (uarray)
y_messung (uarray)
theorie (func(x)): Theoriefunktion, die x-Werte annimmt und y-Werte ausspuckt
xlabel (string)
ylabel (string)
filename (string)
Returns:
TYPE: None
"""
# plt.clf()
# plt.clf()
x_messung, x_error = extract_error(x_messung)
y_messung, y_error = extract_error(y_messung)
x_limit = autolimits(x_messung, err=x_error)
x_flow = np.linspace(*x_limit, num=1000)
y_messung = y_messung
if theorie is not None:
plt.plot(x_flow, theorie(x_flow), 'g-', label="Fit")
#plt.errorbar(x_messung, y_messung, xerr=x_error, yerr=y_error, fmt='r,', label="Fehler")
plt.plot(x_messung, y_messung, 'm.', label="Messwerte")
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.legend(loc='best')
plt.grid()
plt.tight_layout(pad=0, h_pad=1.18, w_pad=1.18)
# plt.show()
plt.savefig('../plots/' + filename)
def plot5(x_messung, y_messung, xlabel, ylabel, filename, theorie):
"""Plottet diskrete Messwerte gegen eine kontinuierliche Messkurve
Args:
x_messung (uarray)
y_messung (uarray)
theorie (func(x)): Theoriefunktion, die x-Werte annimmt und y-Werte ausspuckt
xlabel (string)
ylabel (string)
filename (string)
Returns:
TYPE: None
"""
# plt.clf()
# plt.clf()
x_messung, x_error = extract_error(x_messung)
y_messung, y_error = extract_error(y_messung)
x_limit = autolimits(x_messung, err=x_error)
x_flow = np.linspace(*x_limit, num=1000)
y_messung = y_messung
if theorie is not None:
plt.plot(x_flow, theorie(x_flow), 'g-', label="Fit")
#plt.errorbar(x_messung, y_messung, xerr=x_error, yerr=y_error, fmt='r,', label="Fehler")
plt.plot(x_messung, y_messung, 'y.', label="Messwerte")
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.legend(loc='best')
plt.grid()
plt.tight_layout(pad=0, h_pad=1.18, w_pad=1.18)
# plt.show()
plt.savefig('../plots/' + filename)
def log_plot(x_messung, y_messung, xlabel, ylabel, filename, theorie):
"""Plottet diskrete Messwerte gegen eine kontinuierliche Messkurve
Args:
x_messung (uarray)
y_messung (uarray)
theorie (func(x)): Theoriefunktion, die x-Werte annimmt und y-Werte ausspuckt
xlabel (string)
ylabel (string)
filename (string)
Returns:
TYPE: None
"""
# plt.clf()
# plt.clf()
x_messung, x_error = extract_error(x_messung)
y_messung, y_error = extract_error(y_messung)
x_limit = autolimits(x_messung, err=x_error)
x_flow = np.linspace(*x_limit, num=1000)
y_messung = y_messung
if theorie is not None:
plt.loglog(x_flow, theorie(x_flow), 'g-', label="Fit")
#plt.errorbar(x_messung, y_messung, xerr=x_error, yerr=y_error, fmt='r,', label="Fehler")
plt.loglog(x_messung, y_messung, 'm.', label="Messwerte")
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.legend(loc='best')
plt.grid()
plt.tight_layout(pad=0, h_pad=1.18, w_pad=1.18)
# plt.show()
plt.savefig('../plots/' + filename)
| 26.960289 | 93 | 0.647161 |
4ac9cb55aec05451141c0c5425a601054eed08ff
| 2,754 |
py
|
Python
|
Automaten/Python/nka_terme.py
|
jneug/schule-projekte
|
4f1d56d6bb74a47ca019cf96d2d6cc89779803c9
|
[
"MIT"
] | 2 |
2020-09-24T12:11:16.000Z
|
2022-03-31T04:47:24.000Z
|
Automaten/Python/nka_terme.py
|
jneug/schule-projekte
|
4f1d56d6bb74a47ca019cf96d2d6cc89779803c9
|
[
"MIT"
] | 1 |
2021-02-27T15:06:27.000Z
|
2021-03-01T16:32:48.000Z
|
Automaten/Python/nka_terme.py
|
jneug/schule-projekte
|
4f1d56d6bb74a47ca019cf96d2d6cc89779803c9
|
[
"MIT"
] | 1 |
2021-02-24T05:12:35.000Z
|
2021-02-24T05:12:35.000Z
|
def transition(state, char, stack_char):
new_state = -1
new_stack_chars = ""
if state == 0:
new_state = 1
new_stack_chars = "S#"
elif state == 1:
if stack_char in "0123456789+-*:().":
new_state = 1
new_stack_chars = ""
elif stack_char == "S":
if char in "123456789":
new_state = 1
new_stack_chars = "A"
elif char == "0":
new_state = 1
new_stack_chars = "B"
elif char == "(":
new_state = 1
new_stack_chars = "E)R"
elif stack_char == "A":
if char in "0123456789":
new_state = 1
new_stack_chars = "A"
elif char == ".":
new_state = 1
new_stack_chars = "C"
elif char in "+-:*":
new_state = 1
new_stack_chars = "E"
elif stack_char == "B":
if char == ".":
new_state = 1
new_stack_chars = "C"
elif char in "+-:*":
new_state = 1
new_stack_chars = "E"
elif stack_char == "C":
if char in "0123456789":
new_state = 1
new_stack_chars = "D"
elif stack_char == "D":
if char in "0123456789":
new_state = 1
new_stack_chars = "D"
elif char in "+-:*":
new_state = 1
new_stack_chars = "E"
elif stack_char == "E":
if char in "123456789":
new_state = 1
new_stack_chars = "A"
elif char == "0":
new_state = 1
new_stack_chars = "B"
elif char == "(":
new_state = 1
new_stack_chars = "E)R"
elif stack_char == "R":
if char in "+-:*":
new_state = 1
new_stack_chars = "E"
elif char == "":
new_state = 2
elif stack_char == "#":
new_state = 2
return new_state, new_stack_chars
def scan_word(word):
state = 0
stack = ["#"]
for char in word:
stack_char = stack.pop(0)
state, stack_chars = transition(state, char, stack_char)
for sc in reversed(stack_chars):
stack.insert(0, sc)
if len(stack) > 0:
transition(state, "", stack[0])
return word == "" and state == 2
if __name__ == "__main__":
word = input("Bitte ein Wort eingeben: ")
accepted = scan_word(word)
if accepted:
print("Wort gehört zur Sprache")
else:
print("Wort gehört nicht zur Sprache")
| 28.391753 | 64 | 0.444808 |
4afe315c7c91d456e84455d89f39e76f2aef0620
| 7,453 |
py
|
Python
|
Packs/BitDam/Integrations/BitDam/BitDam.py
|
diCagri/content
|
c532c50b213e6dddb8ae6a378d6d09198e08fc9f
|
[
"MIT"
] | 799 |
2016-08-02T06:43:14.000Z
|
2022-03-31T11:10:11.000Z
|
Packs/BitDam/Integrations/BitDam/BitDam.py
|
diCagri/content
|
c532c50b213e6dddb8ae6a378d6d09198e08fc9f
|
[
"MIT"
] | 9,317 |
2016-08-07T19:00:51.000Z
|
2022-03-31T21:56:04.000Z
|
Packs/BitDam/Integrations/BitDam/BitDam.py
|
diCagri/content
|
c532c50b213e6dddb8ae6a378d6d09198e08fc9f
|
[
"MIT"
] | 1,297 |
2016-08-04T13:59:00.000Z
|
2022-03-31T23:43:06.000Z
|
import demistomock as demisto
from CommonServerPython import *
'''IMPORTS'''
import requests
import base64
# disable insecure warnings
requests.packages.urllib3.disable_warnings()
'''INTEGRATION PARAMS'''
API_TOKEN = demisto.params().get('apitoken')
URL_BASE = demisto.params().get('url')
USE_PROXY = demisto.params().get('proxy', False)
UNSECURE = not demisto.params().get('insecure', False)
'''CONSTANTS'''
READ_BINARY_MODE = 'rb'
SLASH = '/'
SCAN_FILE_URL = 'direct/scan/file/'
GET_FILE_VERDICT_URL = 'direct/verdict/?hash={}'
TOKEN_PREFIX = 'Bearer' # guardrails-disable-line
RESPONSE_CODE_OK = 200
STATUS_IN_PROGRESS = 'IN_PROGRESS'
STATUS_DONE = 'DONE'
AUTH_HEADERS = {
'Authorization': "{} {}".format(TOKEN_PREFIX, API_TOKEN)
}
VERDICT_SCANNING = 'Scanning'
VERDICT_MALICIOUS = 'Malicious'
VERDICT_APPROVED = 'Approved'
VERDICT_ERROR = 'Error'
VERDICT_BENIGN = 'Benign'
VERDICT_TIMEOUT = 'Timeout'
SCAN_ONGOING = 'Still scanning...'
BITDAM_COMMAND_PREFIX = 'bitdam'
DBOTSCORE_UNKNOWN = 0
DBOTSCORE_CLEAN = 1
DBOTSCORE_MALICIOUS = 3
'''HANDLE PROXY'''
handle_proxy()
'''HELPER FUNCTIONS'''
def get_file_bytes(entry_id):
get_file_path_res = demisto.getFilePath(entry_id)
file_path = get_file_path_res["path"]
with open(file_path, READ_BINARY_MODE) as fopen:
bytes = fopen.read()
return base64.b64encode(bytes)
def get_url_base_with_trailing_slash():
'''
Returns the intergation's base url parameter, making sure it contains an trailing slash
'''
url_base = URL_BASE
return url_base if url_base.endswith(SLASH) else url_base + SLASH
def build_json_response(content, context, human_readable):
return {
'Type': entryTypes['note'],
'ContentsFormat': formats['json'],
'Contents': content,
'ReadableContentsFormat': formats['markdown'],
'HumanReadable': tableToMarkdown(human_readable, content),
'EntryContext': context
}
def get_file_name(entry_id):
get_file_path_res = demisto.getFilePath(entry_id)
return get_file_path_res["name"]
def verdict_to_dbotscore(verdict):
if VERDICT_APPROVED == verdict:
return DBOTSCORE_CLEAN
elif VERDICT_MALICIOUS == verdict:
return DBOTSCORE_MALICIOUS
elif VERDICT_SCANNING == verdict:
return DBOTSCORE_UNKNOWN
else:
return DBOTSCORE_UNKNOWN
'''API_IMPL'''
def scan_file():
response = scan_file_command()
returned_sha1 = parse_scan_file_response(response)
# Build demisto reponse
response_content = {'SHA1': returned_sha1}
response_context = {'BitDam': {'FileScan': {'SHA1': returned_sha1}}}
return build_json_response(response_content, response_context, "File was submitted successfully")
def scan_file_command():
# Get data to build the request
entry_id = demisto.args().get('entryId')
file_name = get_file_name(entry_id)
file_bytes = get_file_bytes(entry_id)
json_data = {'file_name': file_name,
'file_data_base64': base64.b64encode(file_bytes)}
raw_json = json.dumps(json_data, ensure_ascii=False)
url = "{}{}".format(get_url_base_with_trailing_slash(), SCAN_FILE_URL)
# Send the HTTP request
response = requests.post(url, data=raw_json, headers=AUTH_HEADERS, verify=UNSECURE)
return response
def parse_scan_file_response(response):
# Parse response
if RESPONSE_CODE_OK != response.status_code:
raise Exception("Scan file failed. Response code -{}, Data- '{}'".format(str(response.status_code), response.content))
response_json = json.loads(response.content)
if 'sha1' not in response_json:
raise Exception(
"Scan file failed. Bad response json - {}".format(response.content))
returned_sha1 = response_json['sha1']
return returned_sha1
def get_file_verdict():
identifier_value = demisto.args().get('idValue')
response = get_file_verdict_command(identifier_value)
verdict, status = parse_get_file_verdict_response(response)
response_content = {'STATUS': status,
'VERDICT': verdict,
'ID': identifier_value}
context = {}
context['BitDam.Analysis(val.ID && val.ID == obj.ID)'] = {
'Status': status,
'Verdict': verdict,
'ID': identifier_value
}
if VERDICT_MALICIOUS == verdict:
context[outputPaths['file']] = {'SHA1': identifier_value}
context[outputPaths['file']]['Malicious'] = {
'Vendor': 'BitDam',
'Description': 'Process whitelist inconsistency by bitdam-get-file-verdict',
'Name': identifier_value
}
dbotscore = verdict_to_dbotscore(verdict)
if dbotscore:
context[outputPaths['dbotscore']] = {
'Indicator': identifier_value,
'Type': 'File',
'Vendor': 'BitDam',
'Score': dbotscore
}
response_context = context
return build_json_response(response_content, response_context,
"Get file verdict was performed successfully")
def parse_get_file_verdict_response(response):
# Parse results
if RESPONSE_CODE_OK != response.status_code:
raise Exception("Get file verdict failed. Response code -{}, Data- '{}'".format(str(response.status_code),
response.content))
response_json = json.loads(response.content)
status = ''
verdict = ''
if 'scan_data' not in response_json or 'verdict' not in response_json['scan_data']:
raise Exception("Get file verdict failed. Unknown response schema. Data- '{}'".format(response.content))
verdict = response_json['scan_data']['verdict']
if verdict == SCAN_ONGOING or verdict == VERDICT_SCANNING:
# Still in progress
verdict = VERDICT_SCANNING
status = STATUS_IN_PROGRESS
else:
status = STATUS_DONE
return verdict, status
def get_file_verdict_command(identifier_value):
# Get data to build the request
scan_file_relative_url_formatted = GET_FILE_VERDICT_URL.format(identifier_value)
url = "{}{}".format(get_url_base_with_trailing_slash(), scan_file_relative_url_formatted)
# Send the request
response = requests.get(url, headers=AUTH_HEADERS, verify=UNSECURE)
return response
def upload_test_file_to_scan():
d = {
"file_name": "demisto.txt",
"file_data_base64": 'ZGVtaXN0bw=='
}
url = "{}{}".format(get_url_base_with_trailing_slash(), SCAN_FILE_URL)
response = requests.post(url, headers=AUTH_HEADERS, json=d, verify=UNSECURE)
return response
def test_module():
response = upload_test_file_to_scan()
if RESPONSE_CODE_OK == response.status_code:
return True
raise Exception("Status code - {}, Error- '{}'".format(str(response.status_code),
response.content))
'''COMMAND_CLASIFIER'''
try:
if demisto.command() == 'test-module':
# This is the call made when pressing the integration test button.
if test_module():
demisto.results('ok')
sys.exit(0)
elif demisto.command() == 'bitdam-upload-file':
demisto.results(scan_file())
elif demisto.command() == 'bitdam-get-verdict':
demisto.results(get_file_verdict())
except Exception as e:
LOG(e)
return_error("Error: {}".format(str(e)))
| 32.404348 | 126 | 0.671407 |
db6dce16e99bbd21687167c6e3bf52f7bad1adc0
| 1,024 |
py
|
Python
|
PINp/2014/Chernov_M_S/task_9_27.py
|
YukkaSarasti/pythonintask
|
eadf4245abb65f4400a3bae30a4256b4658e009c
|
[
"Apache-2.0"
] | null | null | null |
PINp/2014/Chernov_M_S/task_9_27.py
|
YukkaSarasti/pythonintask
|
eadf4245abb65f4400a3bae30a4256b4658e009c
|
[
"Apache-2.0"
] | null | null | null |
PINp/2014/Chernov_M_S/task_9_27.py
|
YukkaSarasti/pythonintask
|
eadf4245abb65f4400a3bae30a4256b4658e009c
|
[
"Apache-2.0"
] | null | null | null |
#Задача 9. Вариант 27.
#Создайте игру, в которой компьютер выбирает какое-либо слово, а игрок должен его отгадать. Компьютер сообщает игроку, сколько букв в слове, и дает пять попыток узнать, есть ли какая-либо буква в слове, причем программа может отвечать только "Да" и "Нет". Вслед за тем игрок должен попробовать отгадать слово.
import random
WORDS=("ромашка", "тюльпан", "кактус", "фиалка", "нарцисс", "гвоздика", "гладиолус", "жасмин")
word=random.choice(WORDS)
live=5
bukva=""
slovo=""
(number)=len(word)
print("Компьютер загадал слово. Твоя цель угадать его. \nВ этом слове ",str(number)," букв.")
print("У тебя "+str(live)+" попыток угадать буквы.")
while live>0:
bukva=input("Введите букву\n")
if bukva in list (word):
print("Да")
live=live-1
else:
print("Нет")
live=live-1
if live==0:
slovo=input("Ваши попытки кончились. \nВведите слово\n")
if slovo==word:
print("Поздравляю! Вы угадали слово :)")
else:
print("Вы не угадали слово :(")
input("Нажмите Enter")
#Chernov M. S.
#28.05.2016
| 36.571429 | 309 | 0.708984 |
dbb0f6ca9a74b0ed550f6304dee3919819bd64f3
| 728 |
py
|
Python
|
tools/pythonpkg/tests/fast/test_transaction.py
|
AldoMyrtaj/duckdb
|
3aa4978a2ceab8df25e4b20c388bcd7629de73ed
|
[
"MIT"
] | 2,816 |
2018-06-26T18:52:52.000Z
|
2021-04-06T10:39:15.000Z
|
tools/pythonpkg/tests/fast/test_transaction.py
|
AldoMyrtaj/duckdb
|
3aa4978a2ceab8df25e4b20c388bcd7629de73ed
|
[
"MIT"
] | 1,310 |
2021-04-06T16:04:52.000Z
|
2022-03-31T13:52:53.000Z
|
tools/pythonpkg/tests/fast/test_transaction.py
|
AldoMyrtaj/duckdb
|
3aa4978a2ceab8df25e4b20c388bcd7629de73ed
|
[
"MIT"
] | 270 |
2021-04-09T06:18:28.000Z
|
2022-03-31T11:55:37.000Z
|
import duckdb
import pandas as pd
class TestConnectionTransaction(object):
def test_transaction(self, duckdb_cursor):
con = duckdb.connect()
con.execute('create table t (i integer)')
con.execute ('insert into t values (1)')
con.begin()
con.execute ('insert into t values (1)')
assert con.execute('select count (*) from t').fetchone()[0] == 2
con.rollback()
assert con.execute('select count (*) from t').fetchone()[0] == 1
con.begin()
con.execute ('insert into t values (1)')
assert con.execute('select count (*) from t').fetchone()[0] == 2
con.commit()
assert con.execute('select count (*) from t').fetchone()[0] == 2
| 36.4 | 72 | 0.596154 |
91a50515d6ddfd3b7262f7be8ec40e6696dd3187
| 304 |
py
|
Python
|
Chapter2_Python/ZipEnumerate.py
|
thisisjako/UdemyTF
|
ee4102391ed6bd50f764955f732f5740425a9209
|
[
"MIT"
] | null | null | null |
Chapter2_Python/ZipEnumerate.py
|
thisisjako/UdemyTF
|
ee4102391ed6bd50f764955f732f5740425a9209
|
[
"MIT"
] | null | null | null |
Chapter2_Python/ZipEnumerate.py
|
thisisjako/UdemyTF
|
ee4102391ed6bd50f764955f732f5740425a9209
|
[
"MIT"
] | null | null | null |
list_a = [10, 20, 30]
list_b = ["Jan", "Peter", "Max"]
list_c = [True, False, True]
for val_a, val_b, val_c in zip(list_a, list_b, list_c):
print(val_a, val_b, val_c)
print("\n")
for i in range(len(list_a)):
print(i, list_a[i])
print("\n")
for i, val in enumerate(list_a):
print(i, val)
| 17.882353 | 55 | 0.615132 |
91b1c7f2319c2b96912a3d9b4ae99fedff955d99
| 8,833 |
py
|
Python
|
Tests/Marketplace/search_and_uninstall_pack.py
|
jrauen/content
|
81a92be1cbb053a5f26a6f325eff3afc0ca840e0
|
[
"MIT"
] | null | null | null |
Tests/Marketplace/search_and_uninstall_pack.py
|
jrauen/content
|
81a92be1cbb053a5f26a6f325eff3afc0ca840e0
|
[
"MIT"
] | 40 |
2022-03-03T07:34:00.000Z
|
2022-03-31T07:38:35.000Z
|
Tests/Marketplace/search_and_uninstall_pack.py
|
jrauen/content
|
81a92be1cbb053a5f26a6f325eff3afc0ca840e0
|
[
"MIT"
] | null | null | null |
import ast
import json
import argparse
import os
import sys
import demisto_client
from Tests.scripts.utils import logging_wrapper as logging
from Tests.scripts.utils.log_util import install_logging
from Tests.Marketplace.search_and_install_packs import install_packs
from time import sleep
def get_all_installed_packs(client: demisto_client):
"""
Args:
client (demisto_client): The client to connect to.
Returns:
list of installed python
"""
try:
logging.info("Attempting to fetch all installed packs.")
response_data, status_code, _ = demisto_client.generic_request_func(client,
path='/contentpacks/metadata/installed',
method='GET',
accept='application/json',
_request_timeout=None)
if 200 <= status_code < 300:
installed_packs = ast.literal_eval(response_data)
installed_packs_ids = [pack.get('id') for pack in installed_packs]
logging.success('Successfully fetched all installed packs.')
installed_packs_ids_str = ', '.join(installed_packs_ids)
logging.debug(
f'The following packs are currently installed from a previous build run:\n{installed_packs_ids_str}')
if 'Base' in installed_packs_ids:
installed_packs_ids.remove('Base')
return installed_packs_ids
else:
result_object = ast.literal_eval(response_data)
message = result_object.get('message', '')
raise Exception(f'Failed to fetch installed packs - with status code {status_code}\n{message}')
except Exception as e:
logging.exception(f'The request to fetch installed packs has failed. Additional info: {str(e)}')
return None
def uninstall_packs(client: demisto_client, pack_ids: list):
"""
Args:
client (demisto_client): The client to connect to.
pack_ids: packs ids to uninstall
Returns:
True if uninstalling succeeded False otherwise.
"""
body = {"IDs": pack_ids}
try:
logging.info("Attempting to uninstall all installed packs.")
response_data, status_code, _ = demisto_client.generic_request_func(client,
path='/contentpacks/installed/delete',
method='POST',
body=body,
accept='application/json',
_request_timeout=None)
except Exception as e:
logging.exception(f'The request to uninstall packs has failed. Additional info: {str(e)}')
return False
return True
def uninstall_all_packs(client: demisto_client, hostname):
""" Lists all installed packs and uninstalling them.
Args:
client (demisto_client): The client to connect to.
hostname (str): xsiam hostname
Returns (list, bool):
A flag that indicates if the operation succeeded or not.
"""
logging.info(f'Starting to search and uninstall packs in server: {hostname}')
packs_to_uninstall: list = get_all_installed_packs(client)
if packs_to_uninstall:
return uninstall_packs(client, packs_to_uninstall)
logging.debug('Skipping packs uninstallation - nothing to uninstall')
return True
def reset_base_pack_version(client: demisto_client):
"""
Resets base pack version to prod version.
Args:
client (demisto_client): The client to connect to.
"""
host = client.api_client.configuration.host.replace('https://api-', 'https://') # disable-secrets-detection
try:
# make the search request
response_data, status_code, _ = demisto_client.generic_request_func(client,
path='/contentpacks/marketplace/Base',
method='GET',
accept='application/json',
_request_timeout=None)
if 200 <= status_code < 300:
result_object = ast.literal_eval(response_data)
if result_object and result_object.get('currentVersion'):
logging.debug('Found Base pack in bucket!')
pack_data = {
'id': result_object.get('id'),
'version': result_object.get('currentVersion')
}
# install latest version of Base pack
logging.info(f'updating base pack to version {result_object.get("currentVersion")}')
return install_packs(client, host, [pack_data], False)
else:
raise Exception('Did not find Base pack')
else:
result_object = ast.literal_eval(response_data)
msg = result_object.get('message', '')
err_msg = f'Search request for base pack, failed with status code ' \
f'{status_code}\n{msg}'
raise Exception(err_msg)
except Exception:
logging.exception('Search request Base pack has failed.')
return False
def wait_for_uninstallation_to_complete(client: demisto_client, retries: int = 30):
"""
Query if there are still installed packs, as it might take time to complete.
Args:
client (demisto_client): The client to connect to.
retries: Max number of sleep priods.
Returns: True if all packs were uninstalled successfully
"""
retry = 0
try:
installed_packs = get_all_installed_packs(client)
while len(installed_packs) > 1:
if retry > retries:
raise Exception('Waiting time for packs to be uninstalled has passed, there are still installed '
'packs. Aborting.')
logging.info(f'The process of uninstalling all packs is not over! There are still {len(installed_packs)} '
f'packs installed. Sleeping for 10 seconds.')
sleep(10)
installed_packs = get_all_installed_packs(client)
retry = retry + 1
except Exception as e:
logging.exception(f'Exception while waiting for the packs to be uninstalled. The error is {e}')
return False
return True
def options_handler():
"""
Returns: options parsed from input arguments.
"""
parser = argparse.ArgumentParser(description='Utility for instantiating and testing integration instances')
parser.add_argument('--xsiam_machine', help='XSIAM machine to use, if it is XSIAM build.')
parser.add_argument('--xsiam_servers_path', help='Path to secret xsiam server metadata file.')
options = parser.parse_args()
return options
def get_json_file(path):
"""
Args:
path: path to retrieve file from.
Returns: json object loaded from the path.
"""
with open(path, 'r') as json_file:
return json.loads(json_file.read())
def get_xsiam_configuration(xsiam_machine, xsiam_servers):
"""
Parses conf params from servers list.
"""
conf = xsiam_servers.get(xsiam_machine)
return conf.get('api_key'), conf.get('base_url'), conf.get('x-xdr-auth-id')
def main():
install_logging('cleanup_xsiam_instance.log', logger=logging)
# in xsiam we dont use demisto username
os.environ.pop('DEMISTO_USERNAME', None)
options = options_handler()
host = options.xsiam_machine
xsiam_servers = get_json_file(options.xsiam_servers_path)
api_key, base_url, xdr_auth_id = get_xsiam_configuration(options.xsiam_machine, xsiam_servers)
logging.info(f'Starting cleanup for XSIAM server {host}')
client = demisto_client.configure(base_url=base_url,
verify_ssl=False,
api_key=api_key,
auth_id=xdr_auth_id)
success = reset_base_pack_version(client) and uninstall_all_packs(client,
host) and wait_for_uninstallation_to_complete(
client)
if not success:
sys.exit(2)
logging.info('Uninstalling packs done.')
if __name__ == '__main__':
main()
| 38.404348 | 118 | 0.582475 |
91d503c31210a49b924dbb63337d444d4de28f5c
| 2,853 |
py
|
Python
|
.vscode/extensions/ms-vscode.cpptools-1.9.0/debugAdapters/lldb/lib/python2.7/site-packages/lldb/formatters/Logger.py
|
Kvahn-ui/dotfiles
|
3f1364410f5bebcaacca6ae38a8e5fbb9bb51285
|
[
"MIT"
] | 3 |
2016-02-10T14:18:40.000Z
|
2018-02-05T03:15:56.000Z
|
.vscode/extensions/ms-vscode.cpptools-1.9.0/debugAdapters/lldb/lib/python2.7/site-packages/lldb/formatters/Logger.py
|
Kvahn-ui/dotfiles
|
3f1364410f5bebcaacca6ae38a8e5fbb9bb51285
|
[
"MIT"
] | 4 |
2019-06-16T09:52:03.000Z
|
2019-08-18T02:11:35.000Z
|
.vscode/extensions/ms-vscode.cpptools-1.9.0/debugAdapters/lldb/lib/python2.7/site-packages/lldb/formatters/Logger.py
|
Kvahn-ui/dotfiles
|
3f1364410f5bebcaacca6ae38a8e5fbb9bb51285
|
[
"MIT"
] | null | null | null |
from __future__ import print_function
import sys
import os.path
import inspect
class NopLogger:
def __init__(self):
pass
def write(self,data):
pass
def flush(self):
pass
def close(self):
pass
class StdoutLogger:
def __init__(self):
pass
def write(self,data):
print(data)
def flush(self):
pass
def close(self):
pass
class FileLogger:
def __init__(self, name):
self.file = None
try:
name = os.path.abspath(name)
self.file = open(name,'a')
except:
try:
self.file = open('formatters.log','a')
except:
pass
def write(self,data):
if self.file != None:
print(data,file=self.file)
else:
print(data)
def flush(self):
if self.file != None:
self.file.flush()
def close(self):
if self.file != None:
self.file.close()
self.file = None
# to enable logging:
# define lldb.formatters.Logger._lldb_formatters_debug_level to any number greater than 0
# if you define it to any value greater than 1, the log will be automatically flushed after each write (slower but should make sure most of the stuff makes it to the log even if we crash)
# if you define it to any value greater than 2, the calling function's details will automatically be logged (even slower, but provides additional details)
# if you need the log to go to a file instead of on screen, define lldb.formatters.Logger._lldb_formatters_debug_filename to a valid filename
class Logger:
def __init__(self,autoflush=False,logcaller=False):
global _lldb_formatters_debug_level
global _lldb_formatters_debug_filename
self.autoflush = autoflush
want_log = False
try:
want_log = (_lldb_formatters_debug_level > 0)
except:
pass
if not (want_log):
self.impl = NopLogger()
return
want_file = False
try:
want_file = (_lldb_formatters_debug_filename != None and _lldb_formatters_debug_filename != '' and _lldb_formatters_debug_filename != 0)
except:
pass
if want_file:
self.impl = FileLogger(_lldb_formatters_debug_filename)
else:
self.impl = StdoutLogger()
try:
self.autoflush = (_lldb_formatters_debug_level > 1)
except:
self.autoflush = autoflush
want_caller_info = False
try:
want_caller_info = (_lldb_formatters_debug_level > 2)
except:
pass
if want_caller_info:
self._log_caller()
def _log_caller(self):
caller = inspect.stack()[2]
try:
if caller != None and len(caller) > 3:
self.write('Logging from function ' + str(caller))
else:
self.write('Caller info not available - Required caller logging not possible')
finally:
del caller # needed per Python docs to avoid keeping objects alive longer than we care
def write(self,data):
self.impl.write(data)
if self.autoflush:
self.flush()
def __rshift__(self,data):
self.write(data)
def flush(self):
self.impl.flush()
def close(self):
self.impl.close()
| 23.195122 | 187 | 0.719243 |
37eff26f5b825f76373d94f0673d1cfc9374a61d
| 442 |
py
|
Python
|
tests/test_types.py
|
fgoettel/wgt
|
e093e2a003fa6c9d4c2082cebbc95701d7f9089d
|
[
"Unlicense"
] | null | null | null |
tests/test_types.py
|
fgoettel/wgt
|
e093e2a003fa6c9d4c2082cebbc95701d7f9089d
|
[
"Unlicense"
] | null | null | null |
tests/test_types.py
|
fgoettel/wgt
|
e093e2a003fa6c9d4c2082cebbc95701d7f9089d
|
[
"Unlicense"
] | 1 |
2022-01-29T12:01:47.000Z
|
2022-01-29T12:01:47.000Z
|
#!/usr/bin/env python3
"""Tests for `wgt` types."""
import pytest
from wgt import types
def test_celsius():
"""Test celsisus as representative of units."""
expected = 42.42
celsius = types.Celsius(expected)
assert celsius.value == expected
assert celsius.unit == "°C"
assert celsius.name == str(expected)
assert str(celsius) == str(celsius.value) + celsius.unit
if __name__ == "__main__":
pytest.main()
| 20.090909 | 60 | 0.662896 |
53587c8e62ac8bf101f88a22bd046e76f3b783e7
| 4,453 |
py
|
Python
|
magenta_docker/task.py
|
googleinterns/step258-2020
|
49e7af1a381e076ee884f55857a7af2f72add74d
|
[
"Apache-2.0"
] | 2 |
2020-08-28T15:17:40.000Z
|
2022-01-21T14:03:21.000Z
|
magenta_docker/task.py
|
googleinterns/step258-2020
|
49e7af1a381e076ee884f55857a7af2f72add74d
|
[
"Apache-2.0"
] | 1 |
2021-01-27T18:22:46.000Z
|
2021-01-27T20:58:55.000Z
|
magenta_docker/task.py
|
googleinterns/step258-2020
|
49e7af1a381e076ee884f55857a7af2f72add74d
|
[
"Apache-2.0"
] | 4 |
2020-07-28T12:13:11.000Z
|
2021-01-27T16:29:29.000Z
|
"""Script for running a containerised training on Google Cloud AI Platform."""
import json
import os
import subprocess
from absl import app
from absl import flags
FLAGS = flags.FLAGS
flags.DEFINE_string('save_dir', None,
'Path where checkpoints and summary events will be saved '
'during training and evaluation.')
flags.DEFINE_string('restore_dir', '',
'Path from which checkpoints will be restored before '
'training. Can be different than the save_dir.')
flags.DEFINE_string('file_pattern', None, 'Data file pattern')
flags.DEFINE_integer('batch_size', 32, 'Batch size')
flags.DEFINE_float('learning_rate', 0.003, 'Learning rate')
flags.DEFINE_integer('num_steps', 30000, 'Number of training steps')
flags.DEFINE_float('early_stop_loss_value', 0.0,
'Early stopping. When the total_loss reaches below this '
'value training stops.')
flags.DEFINE_integer('steps_per_summary', 300, 'Steps per summary')
flags.DEFINE_integer('steps_per_save', 300, 'Steps per save')
flags.DEFINE_boolean('hypertune', False,
'Enable metric reporting for hyperparameter tuning.')
flags.DEFINE_multi_string('gin_search_path', [],
'Additional gin file search paths. '
'Must be paths inside Docker container and '
'necessary gin configs should be added at the '
'Docker image building stage.')
flags.DEFINE_multi_string('gin_file', [],
'List of paths to the config files. If file '
'in gstorage bucket specify whole gstorage path: '
'gs://bucket-name/dir/in/bucket/file.gin. If path '
'should be local remember about copying the file '
'inside the Docker container at building stage. ')
flags.DEFINE_multi_string('gin_param', [],
'Newline separated list of Gin parameter bindings.')
def get_worker_behavior_info(save_dir):
"""Infers worker behavior from the environment.
Checks if TF_CONFIG environment variable is set
and inferes cluster configuration and save_dir
from it.
Args:
save_dir: Save directory given by the user.
Returns:
cluster_config: Infered cluster configuration.
save_dir: Infered save directory.
"""
if 'TF_CONFIG' in os.environ:
cluster_config = os.environ['TF_CONFIG']
cluster_config_dict = json.loads(cluster_config)
if ('cluster' not in cluster_config_dict.keys() or
'task' not in cluster_config_dict or
len(cluster_config_dict['cluster']) <= 1):
cluster_config = ''
elif cluster_config_dict['task']['type'] != 'chief':
save_dir = ''
else:
cluster_config = ''
return cluster_config, save_dir
def parse_list_params(list_of_params, param_name):
return [f'--{param_name}={param}' for param in list_of_params]
def main(unused_argv):
restore_dir = FLAGS.save_dir if not FLAGS.restore_dir else FLAGS.restore_dir
cluster_config, save_dir = get_worker_behavior_info(FLAGS.save_dir)
gin_search_path = parse_list_params(FLAGS.gin_search_path, 'gin_search_path')
gin_file = parse_list_params(FLAGS.gin_file, 'gin_file')
gin_param = parse_list_params(FLAGS.gin_param, 'gin_param')
ddsp_run_command = (
['ddsp_run',
'--mode=train',
'--alsologtostderr',
'--gin_file=models/solo_instrument.gin',
'-gin_file=datasets/tfrecord.gin',
f'--cluster_config={cluster_config}',
f'--save_dir={save_dir}',
f'--restore_dir={restore_dir}',
f'--hypertune={FLAGS.hypertune}',
f'--early_stop_loss_value={FLAGS.early_stop_loss_value}',
f'--gin_param=batch_size={FLAGS.batch_size}',
f'--gin_param=learning_rate={FLAGS.learning_rate}',
f'--gin_param=TFRecordProvider.file_pattern=\'{FLAGS.file_pattern}\'',
f'--gin_param=train_util.train.num_steps={FLAGS.num_steps}',
f'--gin_param=train_util.train.steps_per_save={FLAGS.steps_per_save}',
('--gin_param=train_util.train.steps_per_summary='
f'{FLAGS.steps_per_summary}')]
+ gin_search_path + gin_file + gin_param)
subprocess.run(args=ddsp_run_command, check=True)
if __name__ == '__main__':
flags.mark_flag_as_required('file_pattern')
flags.mark_flag_as_required('save_dir')
app.run(main)
| 38.387931 | 79 | 0.669661 |
be44d532f6aa12d608ccd0be0854223b83c35355
| 4,444 |
py
|
Python
|
blockchain/wallet.py
|
tobias-fyi/xebec
|
731112b60ab4bd915a9c3f57a3a96c2e37b4a119
|
[
"MIT"
] | null | null | null |
blockchain/wallet.py
|
tobias-fyi/xebec
|
731112b60ab4bd915a9c3f57a3a96c2e37b4a119
|
[
"MIT"
] | 8 |
2020-03-24T17:47:23.000Z
|
2022-03-12T00:33:21.000Z
|
cs/lambda_cs/05_hash_tables_and_blockchain/Blockchain/client_mining_p/wallet.py
|
tobias-fyi/vela
|
b0b3d3c6dc3fa397c8c7a492098a02cf75e0ff82
|
[
"MIT"
] | null | null | null |
"""
Blockchain — Day 2 Project :: Wallet app
> MVP
* Allow the user to enter, save, or change the `user_id` used for the program
* Display the current balance for that user
* Display a list of all transactions for this user, including sender and recipient
> Stretch Goals
* Use styling to visually distinguish coins sent and coins received
* Paginate the list of transactions if there are more than ten
"""
import json
from pprint import pprint
import requests
class User:
def __init__(
self,
user_id: str = "007",
balance: float = 0.0,
url: str = "http://localhost:5000",
):
"""Constructor for the user account management handler class."""
self.user_id = user_id
self.url = url
self.cache = []
self.last_index = 0
self.balance = balance
@property
def user_id(self) -> str:
"""User's account identifier."""
return self._user_id
@user_id.setter
def user_id(self, new_id) -> None:
"""Setter function for user_id property."""
self._user_id = new_id
print(f"User ID: {new_id}")
@property
def balance(self) -> None:
"""User's current number of coins."""
return self._balance
@balance.setter
def balance(self, value: float) -> None:
"""Setter function for balance property."""
self._balance = value
def show_transactions(self) -> None:
"""Displays user's transactions."""
pprint(self.cache)
def post_transaction(self, recipient: str, amt: float) -> int:
"""Posts a new transaction from the user.
Returns index of block into which transaction was posted."""
# TODO: Check if user has enough coins
if self.balance - amt < 0:
print("Error: Not enough coins for transaction")
else:
# Construct the POST object
post_data = {
"sender": self.user_id,
"recipient": recipient,
"amount": amt,
}
# Post transaction to blockchain server
r = requests.post(url=self.url + "/transactions/new", json=post_data)
# Parse the response
if r.status_code == 200:
resp = r.json()
print(resp.get("message"))
return resp.get("index")
else:
print("Post failed.")
def get_transactions(self) -> list:
"""Helper function for retrieving all transactions involving user."""
# Retrieve full chain
r = requests.get(url=self.url + "/chain")
# Parse into list of dictionaries
chain = r.json()["chain"]
# Iterate through chain, starting after last processed block
for block in chain[self.last_index :]:
# Iterate through each block's transactions
for transaction in block["transactions"]:
# Look for transactions where user_id is recipient or sender
if self.user_id in transaction.values():
# Add transaction to user's transaction cache
transaction["block_index"] = block["index"]
transaction["block_timestamp"] = block["timestamp"]
self.cache.append(transaction)
# Update user's balance
if transaction["recipient"] == self.user_id:
self.balance += transaction["amount"]
else:
self.balance -= transaction["amount"]
self.last_index += 1 # Count block as processed
print(f"Updated wallet up to block {self.last_index + 1}")
if __name__ == "__main__":
# === Instantiate users
james_bond = User(user_id="007", balance=100.0)
jane_bond = User(user_id="008", balance=50.0)
# === Update wallets
james_bond.get_transactions()
jane_bond.get_transactions()
# === Print balances
print(james_bond.balance)
print(jane_bond.balance)
# === Post transactions
james_bond.post_transaction("008", 1.8)
jane_bond.post_transaction("007", 0.7)
# === Post transactions
jane_bond.post_transaction("007", 7.7)
james_bond.post_transaction("008", 8.8)
# === Update wallets
james_bond.get_transactions()
jane_bond.get_transactions()
# === Print balances
print(james_bond.balance)
print(jane_bond.balance)
| 32.202899 | 82 | 0.593384 |
be488e981ad6a83f4dbe5d20f646a189ebba482e
| 959 |
py
|
Python
|
methods/transformers/examples/seq2seq/save_randomly_initialized_model.py
|
INK-USC/RiddleSense
|
a3d57eaf084da9cf6b77692c608e2cd2870fbd97
|
[
"MIT"
] | 3 |
2021-07-06T20:02:31.000Z
|
2022-03-27T13:13:01.000Z
|
methods/transformers/examples/seq2seq/save_randomly_initialized_model.py
|
INK-USC/RiddleSense
|
a3d57eaf084da9cf6b77692c608e2cd2870fbd97
|
[
"MIT"
] | null | null | null |
methods/transformers/examples/seq2seq/save_randomly_initialized_model.py
|
INK-USC/RiddleSense
|
a3d57eaf084da9cf6b77692c608e2cd2870fbd97
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
import fire
from transformers import AutoConfig, AutoModelForSeq2SeqLM, AutoTokenizer
def save_randomly_initialized_version(config_name: str, save_dir: str, **config_kwargs):
"""Save a randomly initialized version of a model using a pretrained config.
Args:
config_name: which config to use
save_dir: where to save the resulting model and tokenizer
config_kwargs: Passed to AutoConfig
Usage::
save_randomly_initialized_version("facebook/bart-large-cnn", "distilbart_random_cnn_6_3", encoder_layers=6, decoder_layers=3, num_beams=3)
"""
cfg = AutoConfig.from_pretrained(config_name, **config_kwargs)
model = AutoModelForSeq2SeqLM.from_config(cfg)
model.save_pretrained(save_dir)
AutoTokenizer.from_pretrained(config_name).save_pretrained(save_dir)
return model
if __name__ == "__main__":
fire.Fire(save_randomly_initialized_version)
| 35.518519 | 147 | 0.741397 |
fe657793db522efafe2f203d65640858801013a6
| 12,785 |
py
|
Python
|
Packs/UBIRCH/Integrations/UBIRCH/UBIRCH.py
|
diCagri/content
|
c532c50b213e6dddb8ae6a378d6d09198e08fc9f
|
[
"MIT"
] | 799 |
2016-08-02T06:43:14.000Z
|
2022-03-31T11:10:11.000Z
|
Packs/UBIRCH/Integrations/UBIRCH/UBIRCH.py
|
diCagri/content
|
c532c50b213e6dddb8ae6a378d6d09198e08fc9f
|
[
"MIT"
] | 9,317 |
2016-08-07T19:00:51.000Z
|
2022-03-31T21:56:04.000Z
|
Packs/UBIRCH/Integrations/UBIRCH/UBIRCH.py
|
diCagri/content
|
c532c50b213e6dddb8ae6a378d6d09198e08fc9f
|
[
"MIT"
] | 1,297 |
2016-08-04T13:59:00.000Z
|
2022-03-31T23:43:06.000Z
|
import demistomock as demisto
from CommonServerPython import * # noqa # pylint: disable=unused-wildcard-import
from CommonServerUserPython import * # noqa
import paho.mqtt.client as mqtt
import paho
from typing import Callable
import traceback
import json
''' CONSTANTS '''
QOS_AT_LEAST_ONCE = 1
# SEVERITY
CRITICAL_SEVERITY = 4
HIGH_SEVERITY = 3
MEDIUM_SEVERITY = 2
LOW_SEVERITY = 1
UNKNOWN_SEVERITY = 0
# Types
AUTHENTICATION_TYPE = 'Authentication'
AUTHENTICITY_TYPE = 'UBIRCH Authenticity'
INTEGRITY_TYPE = 'UBIRCH Integrity'
PRIVACY_TYPE = 'UBIRCH Privacy'
SEQUENCE_TYPE = 'UBIRCH Sequence'
# Fields
SEVERITY_FIELD = "severity"
TYPE_FIELD = "type"
MEANING_FIELD = "meaning"
INCIDENT_SEVERITY_MAP = {
"niomon-auth": {
"1000": {
MEANING_FIELD: "Authentication error: request malformed. Possible missing header and parameters.",
SEVERITY_FIELD: LOW_SEVERITY,
TYPE_FIELD: AUTHENTICATION_TYPE
},
"2000": {
MEANING_FIELD: "Authentication error: processing authentication response/Failed Request",
SEVERITY_FIELD: LOW_SEVERITY,
TYPE_FIELD: AUTHENTICATION_TYPE
},
"3000": {
MEANING_FIELD: "Authentication error (3rd party): error processing authentication request",
SEVERITY_FIELD: LOW_SEVERITY,
TYPE_FIELD: AUTHENTICATION_TYPE
},
"4000": {
MEANING_FIELD: "Authentication error: Failed Request",
SEVERITY_FIELD: LOW_SEVERITY,
TYPE_FIELD: AUTHENTICATION_TYPE
}
},
"niomon-decoder": {
"1100": {
MEANING_FIELD: "Invalid verification: request malformed. Possible missing headers or parameters.",
SEVERITY_FIELD: MEDIUM_SEVERITY,
TYPE_FIELD: AUTHENTICITY_TYPE
},
"1200": {
MEANING_FIELD: "Invalid verification: invalid parts",
SEVERITY_FIELD: HIGH_SEVERITY,
TYPE_FIELD: AUTHENTICITY_TYPE
},
"1300": {
MEANING_FIELD: "Invalid verification: signature verification failed. No public key or integrity is "
"compromised.",
SEVERITY_FIELD: HIGH_SEVERITY,
TYPE_FIELD: AUTHENTICITY_TYPE
},
"2100": {
MEANING_FIELD: "Decoding error: request malformed. Possible missing headers or parameters.",
SEVERITY_FIELD: LOW_SEVERITY,
TYPE_FIELD: INTEGRITY_TYPE
},
"2200": {
MEANING_FIELD: "Decoding Error: Invalid Match",
SEVERITY_FIELD: MEDIUM_SEVERITY,
TYPE_FIELD: INTEGRITY_TYPE
},
"2300": {
MEANING_FIELD: "Decoding Error: Decoding Error/Null Payload",
SEVERITY_FIELD: LOW_SEVERITY,
TYPE_FIELD: INTEGRITY_TYPE
}
},
"niomon-enricher": {
"1000": {
MEANING_FIELD: "Tenant error: the owner of the device cannot be determined. Possible missing headers or "
"parameters or body.",
SEVERITY_FIELD: LOW_SEVERITY,
TYPE_FIELD: AUTHENTICITY_TYPE
},
"2000": {
MEANING_FIELD: "Tenant error: the owner of the device does not exist or cannot be acquired.",
SEVERITY_FIELD: HIGH_SEVERITY,
TYPE_FIELD: AUTHENTICITY_TYPE
},
"0000": {
MEANING_FIELD: "Tenant error: the owner of the device does not exist or cannot be acquired (3rd Party).",
SEVERITY_FIELD: HIGH_SEVERITY,
TYPE_FIELD: AUTHENTICITY_TYPE
}
},
"filter-service": {
"0000": {
MEANING_FIELD: "Integrity violation: duplicate hash detected. Possible injection, reply attack, "
"or hash collision. ",
SEVERITY_FIELD: HIGH_SEVERITY,
TYPE_FIELD: SEQUENCE_TYPE
},
"0010": {
MEANING_FIELD: "Privacy violation: hash is already disabled or non-existent",
SEVERITY_FIELD: LOW_SEVERITY,
TYPE_FIELD: PRIVACY_TYPE
},
"0020": {
MEANING_FIELD: "Privacy violation: hash is not disabled or non-existent",
SEVERITY_FIELD: LOW_SEVERITY,
TYPE_FIELD: PRIVACY_TYPE
},
"0030": {
MEANING_FIELD: "Privacy violation: hash does not exist. Possible DDOS attack",
SEVERITY_FIELD: HIGH_SEVERITY,
TYPE_FIELD: PRIVACY_TYPE
}
}
}
''' CLIENT CLASS '''
class Client:
"""Client class to subscribe the error from MQTT server
This Client class is a wrapper class of the paho mqtt Client.
Args:
mqtt_host(str): MQTT server's host name
mqtt_port(int): MQTT server's port number
username(str): MQTT server's user name
password(str): MQTT server's password
stage(str): MQTT server's environment
tenant_id(str): tenant id related with errors subscribed
Return:
None
"""
def __init__(self, mqtt_host: str, mqtt_port: int, username: str, password: str, stage: str, tenant_id: str):
self.mqtt_client = mqtt.Client()
self.mqtt_client.username_pw_set(username, password)
self.mqtt_host = mqtt_host
self.mqtt_port = mqtt_port
self.topic = "com/ubirch/{}/incident/tenant/{}".format(stage, tenant_id)
def connect(self, on_connect_callback: Callable[[mqtt.Client, dict, dict, int], None] = None) -> None:
if on_connect_callback is not None:
self.mqtt_client.on_connect = on_connect_callback
self.mqtt_client.connect(self.mqtt_host, self.mqtt_port)
def subscribe(self, on_message_callback: Callable[[mqtt.Client, dict, mqtt.MQTTMessage], None] = None) -> None:
if on_message_callback is not None:
self.mqtt_client.on_message = on_message_callback
self.mqtt_client.subscribe(self.topic, QOS_AT_LEAST_ONCE)
def loop_forever(self) -> None:
self.mqtt_client.loop_forever()
def loop_stop(self) -> None:
self.mqtt_client.loop_stop()
''' HELPER FUNCTIONS '''
def get_error_definition(incident: Dict) -> Dict:
"""Return the error definition from the incident
Ex. { "meaning": "xxx", "severity": 1, "type": "AUTHENTICATION" }
Args:
incident(Dict): an incident
Return:
Dict: error definition
"""
microservice: str = incident.get("microservice", "")
error_code: str = incident.get("errorCode", "")
# ex. { "1000": { ... }, "1100": { ... } }
error_codes: Dict = INCIDENT_SEVERITY_MAP.get(microservice, {})
# ex. { "meaning": "xxx", "severity": 1, "type": "AUTHENTICATION" }
return error_codes.get(error_code, {})
def create_incidents(error_message: str) -> list:
"""Create the incidents
Args:
error_message (str): this is the message payload from MQTT server
Return:
list: list of incidents
"""
incident_dict = json.loads(error_message)
error_definition = get_error_definition(incident_dict)
return [{
'name': error_definition.get(MEANING_FIELD, incident_dict.get("error")),
'type': error_definition.get(TYPE_FIELD, ""),
'labels': [{'type': "requestId", 'value': incident_dict.get("requestId")},
{'type': "hwDeviceId", 'value': incident_dict.get("hwDeviceId")}],
'rawJSON': json.dumps(incident_dict),
'details': json.dumps(incident_dict),
'severity': error_definition.get(SEVERITY_FIELD, UNKNOWN_SEVERITY),
}]
''' COMMAND FUNCTIONS '''
def long_running_execution(client: Client) -> None:
"""Connects to a MQTT Server and subscribe the error from it in a loop.
Args:
client(Client): client class which is a wrapper of the mqtt.Client class.
Return:
None: no data returned
"""
def on_connect(_client: mqtt.Client, _userdata: dict, _flags: dict, rc: int) -> None:
"""
Callback function when a MQTT client connects to the server
Check if the connection is succeeded.
The rc argument is a connection result.
"""
if rc != mqtt.MQTT_ERR_SUCCESS:
demisto.info(mqtt.connack_string(rc))
raise paho.mqtt.MQTTException(mqtt.connack_string(rc))
else:
demisto.info(f"connection was succeeded for a long-running container. host: {client.mqtt_host}, port: "
f"{client.mqtt_port}")
def on_message(_client: mqtt.Client, _userdata: dict, message: mqtt.MQTTMessage) -> None:
"""
Callback function when a MQTT client subscribes to a message from the server
Create incidents, when the client subscribes to an error from the mqtt server.
"""
demisto.info(f"on message. {message.topic} {message.qos} {message.payload}")
incidents = create_incidents(message.payload.decode("utf-8", "ignore")) # the message payload is binary.
demisto.info(f"catch an incident. {incidents}")
demisto.createIncidents(incidents)
try:
client.connect(on_connect)
client.subscribe(on_message)
client.loop_forever()
except Exception as e:
demisto.error(f'An error occurred in the long running loop: {e}')
finally:
client.loop_stop()
def test_module(client: Client) -> None:
"""Check if the user configuration is correct
Return:
None: no data returned
"""
def on_connect(_client: mqtt.Client, _userdata: dict, _flags: dict, rc: int) -> None:
"""
Callback function when a MQTT client connects to the server
Check if the connection is succeeded.
Stop the loop regardless of whether the connection is succeeded or not.
The rc argument is a connection result.
"""
_client.disconnect()
_client.loop_stop()
if rc != mqtt.MQTT_ERR_SUCCESS:
demisto.info(mqtt.connack_string(rc))
raise paho.mqtt.MQTTException(mqtt.connack_string(rc))
else:
demisto.info("connection was succeeded for test")
try:
client.connect(on_connect)
client.subscribe()
client.loop_forever()
except Exception as e:
raise DemistoException(
f"Test failed. Please check your parameters. \n {e}")
demisto.results('ok')
def create_sample_incidents() -> None:
"""Extract sample events stored in the integration context and create them as incidents
Return:
None: no data returned
"""
integration_context = get_integration_context()
sample_events = integration_context.get('sample_events')
if sample_events:
try:
incidents = [{'name': "sample_event", 'rawJSON': json.dumps(event)} for event in json.loads(sample_events)]
demisto.createIncidents(incidents)
demisto.info("it was succeeded to create the sample incident.")
except json.decoder.JSONDecodeError as e:
raise ValueError(f'Failed deserializing sample events - {e}')
else:
incidents = [{
'name': 'sample incident.',
}]
demisto.createIncidents(incidents)
demisto.info("it was succeeded to create the sample incident.")
demisto.info("connection was succeeded for test")
def main() -> None:
""" main function, parses params and runs command functions """
params = demisto.params()
username = params['credentials'].get('identifier')
password = params['credentials'].get('password')
tenant_id = params['tenant_id']
mqtt_host = params['url']
mqtt_port = params['port']
stage = params['stage']
command = demisto.command()
demisto.debug(f'Command being called is {command}')
try:
try:
mqtt_port = int(mqtt_port)
except ValueError as e:
raise ValueError(f"Invalid the mqtt server's port - {e}")
client = Client(
mqtt_host=mqtt_host,
mqtt_port=mqtt_port,
username=username,
password=password,
stage=stage,
tenant_id=tenant_id
)
if command == 'test-module':
# This is the call made when pressing the integration Test button.
test_module(client)
elif command == 'long-running-execution':
long_running_execution(client)
elif command == 'create-sample-incidents':
create_sample_incidents()
# Log exceptions and return errors
except Exception as e:
demisto.error(traceback.format_exc()) # print the traceback
return_error(f'Failed to execute {demisto.command()} command.\nError:\n{str(e)}')
if __name__ in ('__main__', '__builtin__', 'builtins'):
main()
| 34.184492 | 119 | 0.630426 |
606e7f4ea22341b5ce383d26e26fb0b9876fd29c
| 266 |
py
|
Python
|
DataStructure/U14/U14_97.py
|
qiaw99/Data-Structure
|
3b1cdce96d4f35329ccfec29c03de57378ef0552
|
[
"MIT"
] | 1 |
2019-10-29T08:21:41.000Z
|
2019-10-29T08:21:41.000Z
|
DataStructure/U14/U14_97.py
|
qiaw99/Data-Structure
|
3b1cdce96d4f35329ccfec29c03de57378ef0552
|
[
"MIT"
] | null | null | null |
DataStructure/U14/U14_97.py
|
qiaw99/Data-Structure
|
3b1cdce96d4f35329ccfec29c03de57378ef0552
|
[
"MIT"
] | null | null | null |
nums = 34
coins= [1,2,5,10]
temp = nums
dp = [float("inf") for _ in range(nums)]
dp[0] = 0
for i in range(1,nums):
for j in range(len(coins)):
if(coins[j] <= nums):
dp[i] = min(dp[i], dp[i-coins[j]]+1)
print(dp)
print(dp[nums-1])
| 22.166667 | 48 | 0.518797 |
7196df947a719f1ad906027a0121949c2fb6e0d6
| 1,039 |
py
|
Python
|
python/oneflow/framework/tensor_tuple_util.py
|
wangyuyue/oneflow
|
0a71c22fe8355392acc8dc0e301589faee4c4832
|
[
"Apache-2.0"
] | 3,285 |
2020-07-31T05:51:22.000Z
|
2022-03-31T15:20:16.000Z
|
python/oneflow/framework/tensor_tuple_util.py
|
wangyuyue/oneflow
|
0a71c22fe8355392acc8dc0e301589faee4c4832
|
[
"Apache-2.0"
] | 2,417 |
2020-07-31T06:28:58.000Z
|
2022-03-31T23:04:14.000Z
|
python/oneflow/framework/tensor_tuple_util.py
|
wangyuyue/oneflow
|
0a71c22fe8355392acc8dc0e301589faee4c4832
|
[
"Apache-2.0"
] | 520 |
2020-07-31T05:52:42.000Z
|
2022-03-29T02:38:11.000Z
|
"""
Copyright 2020 The OneFlow Authors. All rights reserved.
Licensed 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.
"""
import collections
from typing import Optional, Sequence, Union
from oneflow._oneflow_internal import Tensor, TensorTuple
def convert_to_tensor_tuple(args: Optional[Union[Tensor, Sequence[Tensor]]]):
if args is None:
return TensorTuple()
elif isinstance(args, collections.abc.Sequence):
return TensorTuple(args)
else:
tensor_tuple = TensorTuple()
tensor_tuple.append(args)
return tensor_tuple
| 32.46875 | 77 | 0.758422 |
71afa04ef8d0f57669ca0f129f2c50b754e901ac
| 365 |
py
|
Python
|
0-notes/job-search/Cracking the Coding Interview/C04TreesGraphs/questions/4.12-questions.py
|
eengineergz/Lambda
|
1fe511f7ef550aed998b75c18a432abf6ab41c5f
|
[
"MIT"
] | null | null | null |
0-notes/job-search/Cracking the Coding Interview/C04TreesGraphs/questions/4.12-questions.py
|
eengineergz/Lambda
|
1fe511f7ef550aed998b75c18a432abf6ab41c5f
|
[
"MIT"
] | null | null | null |
0-notes/job-search/Cracking the Coding Interview/C04TreesGraphs/questions/4.12-questions.py
|
eengineergz/Lambda
|
1fe511f7ef550aed998b75c18a432abf6ab41c5f
|
[
"MIT"
] | null | null | null |
# 4.12 Paths with Sum
# You are given a binary tree in which each node contains an integer value
# which might be positive or negative.
# Design an algorithm to count the number of paths that sum to a given value.
# The path does not need to start or end at the root or a leaf, but it must go
# downwards, traveling only from parent nodes to child nodes.
| 45.625 | 78 | 0.739726 |
e0aa0f61cc446160a9ed1bbc3c7d59ad1a2459a4
| 3,056 |
py
|
Python
|
cbm/ipycbm/ipy_view/view_background.py
|
CsabaWirnhardt/cbm
|
1822addd72881057af34ac6a7c2a1f02ea511225
|
[
"BSD-3-Clause"
] | 17 |
2021-01-18T07:27:01.000Z
|
2022-03-10T12:26:21.000Z
|
cbm/ipycbm/ipy_view/view_background.py
|
CsabaWirnhardt/cbm
|
1822addd72881057af34ac6a7c2a1f02ea511225
|
[
"BSD-3-Clause"
] | 4 |
2021-04-29T11:20:44.000Z
|
2021-12-06T10:19:17.000Z
|
cbm/ipycbm/ipy_view/view_background.py
|
CsabaWirnhardt/cbm
|
1822addd72881057af34ac6a7c2a1f02ea511225
|
[
"BSD-3-Clause"
] | 47 |
2021-01-21T08:25:22.000Z
|
2022-03-21T14:28:42.000Z
|
import json
import os.path
import matplotlib.pyplot as plt
from ipywidgets import Output, VBox, SelectionSlider
from mpl_toolkits.axes_grid1 import ImageGrid
import rasterio
from rasterio.plot import show
from descartes import PolygonPatch
from copy import copy
# import matplotlib.ticker as ticker
# import numpy as np
from cbm.utils import config, spatial_utils
from cbm.get import background as bg
def slider(aoi, pid, chipsize=512, extend=512, tms=['Google']):
workdir = config.get_value(['paths', 'temp'])
path = f'{workdir}/{aoi}/{pid}/'
bg_path = f'{path}/backgrounds/'
for t in tms:
if not os.path.isfile(f'{bg_path}{t.lower()}.tif'):
bg.by_pid(aoi, pid, chipsize, extend, t, True)
with open(f'{path}info.json', "r") as f:
json_data = json.load(f)
def overlay_parcel(img, geom):
patche = [PolygonPatch(feature, edgecolor="yellow",
facecolor="none", linewidth=2
) for feature in geom['geom']]
return patche
with rasterio.open(f'{bg_path}{tms[0].lower()}.tif') as img:
img_epsg = img.crs.to_epsg()
geom = spatial_utils.transform_geometry(json_data, img_epsg)
patches = overlay_parcel(img, geom)
selection = SelectionSlider(
options=tms,
value=tms[0],
disabled=False,
continuous_update=False,
orientation='horizontal',
readout=True
)
output = Output()
fig, ax = plt.subplots(figsize=(10, 10))
with output:
with rasterio.open(f'{bg_path}{selection.value.lower()}.tif') as img:
for patch in patches:
ax.add_patch(copy(patch))
show(img, ax=ax)
plt.show()
def on_value_change(change):
with output:
output.clear_output()
fig, ax = plt.subplots(figsize=(10, 10))
with rasterio.open(f'{bg_path}{selection.value.lower()}.tif') as im:
for patch in patches:
ax.add_patch(copy(patch))
show(im, ax=ax)
plt.show()
selection.observe(on_value_change, names='value')
return VBox([selection, output])
def maps(aoi, pid, chipsize=512, extend=512, tms='Google'):
workdir = config.get_value(['paths', 'temp'])
path = f'{workdir}/{aoi}/{pid}/backgrounds/'
for t in tms:
if not os.path.isfile(f'{path}{t.lower()}.png'):
bg.by_pid(aoi, pid, chipsize, extend, t, True)
columns = 5
rows = int(len(tms) // columns + (len(tms) % columns > 0))
fig = plt.figure(figsize=(25, 5 * rows))
grid = ImageGrid(fig, 111, # similar to subplot(111)
nrows_ncols=(rows, columns), # creates grid of axes
axes_pad=0.1, # pad between axes in inch.
)
for ax, im in zip(grid, tms):
# Iterating over the grid returns the Axes.
ax.axis('off')
ax.imshow(plt.imread(f'{path}{im.lower()}.png', 3))
ax.set_title(im)
plt.show()
| 31.183673 | 80 | 0.592605 |
1c19f2b5e50ed09f338bab660257e2262cf0a3ab
| 3,056 |
py
|
Python
|
TcpPortForward.py
|
Zusyaku/Termux-And-Lali-Linux-V2
|
b1a1b0841d22d4bf2cc7932b72716d55f070871e
|
[
"Apache-2.0"
] | 2 |
2021-11-17T03:35:03.000Z
|
2021-12-08T06:00:31.000Z
|
TcpPortForward.py
|
Zusyaku/Termux-And-Lali-Linux-V2
|
b1a1b0841d22d4bf2cc7932b72716d55f070871e
|
[
"Apache-2.0"
] | null | null | null |
TcpPortForward.py
|
Zusyaku/Termux-And-Lali-Linux-V2
|
b1a1b0841d22d4bf2cc7932b72716d55f070871e
|
[
"Apache-2.0"
] | 2 |
2021-11-05T18:07:48.000Z
|
2022-02-24T21:25:07.000Z
|
#/usr/bin/python env
# -*- coding: utf-8 -*-
'''
filename:TcpPortForward.py
@desc:
利用python的socket端口转发，用于远程维护,Hack
如果连接不到远程，会sleep 36s，最多尝试200(即两小时)
@usage:
./TcpPortForward.py stream1 stream2
stream为：l:port或c:host:port
l:port表示监听指定的本地端口
c:host:port表示监听远程指定的端口
'''
import socket
import sys
import threading
import time
streams = [None, None] # 存放需要进行数据转发的两个数据流（都是SocketObj对象）
debug = 1 # 调试状态 0 or 1
def _usage():
print 'Usage: ./TcpPortForward.py stream1 stream2\nstream : l:port or c:host:port'
def _get_another_stream(num):
'''
从streams获取另外一个流对象，如果当前为空，则等待
'''
if num == 0:
num = 1
elif num == 1:
num = 0
else:
raise "ERROR"
while True:
if streams[num] == 'quit':
print("can't connect to the target, quit now!")
sys.exit(1)
if streams[num] != None:
return streams[num]
else:
time.sleep(1)
def _xstream(num, s1, s2):
'''
交换两个流的数据
num为当前流编号,主要用于调试目的，区分两个回路状态用。
'''
try:
while True:
#注意，recv函数会阻塞，直到对端完全关闭（close后还需要一定时间才能关闭，最快关闭方法是shutdow）
buff = s1.recv(1024)
if debug > 0:
print num,"recv"
if len(buff) == 0: #对端关闭连接，读不到数据
print num,"one closed"
break
s2.sendall(buff)
if debug > 0:
print num,"sendall"
except :
print num,"one connect closed."
try:
s1.shutdown(socket.SHUT_RDWR)
s1.close()
except:
pass
try:
s2.shutdown(socket.SHUT_RDWR)
s2.close()
except:
pass
streams[0] = None
streams[1] = None
print num, "CLOSED"
def _server(port, num):
'''
处理服务情况,num为流编号（第0号还是第1号）
'''
srv = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
srv.bind(('0.0.0.0', port))
srv.listen(1)
while True:
conn, addr = srv.accept()
print "connected from:", addr
streams[num] = conn # 放入本端流对象
s2 = _get_another_stream(num) # 获取另一端流对象
_xstream(num, conn, s2)
def _connect(host, port, num):
''' 处理连接，num为流编号（第0号还是第1号）
@note: 如果连接不到远程，会sleep 36s，最多尝试200(即两小时)
'''
not_connet_time = 0
wait_time = 36
try_cnt = 199
while True:
if not_connet_time > try_cnt:
streams[num] = 'quit'
print('not connected')
return None
conn = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
try:
conn.connect((host, port))
except Exception, e:
print ('can not connect %s:%s!' % (host, port))
not_connet_time += 1
time.sleep(wait_time)
continue
print "connected to %s:%i" % (host, port)
streams[num] = conn #放入本端流对象
s2 = _get_another_stream(num) #获取另一端流对象
_xstream(num, conn, s2)
if __name__ == '__main__':
if len(sys.argv) != 3:
_usage()
sys.exit(1)
tlist = [] # 线程列表，最终存放两个线程对象
targv = [sys.argv[1], sys.argv[2] ]
for i in [0, 1]:
s = targv[i] # stream描述 c:ip:port 或 l:port
sl = s.split(':')
if len(sl) == 2 and (sl[0] == 'l' or sl[0] == 'L'): # l:port
t = threading.Thread(target=_server, args=(int(sl[1]), i))
tlist.append(t)
elif len(sl) == 3 and (sl[0] == 'c' or sl[0] == 'C'): # c:host:port
t = threading.Thread(target=_connect, args=(sl[1], int(sl[2]), i))
tlist.append(t)
else:
_usage()
sys.exit(1)
for t in tlist:
t.start()
for t in tlist:
t.join()
sys.exit(0)
| 20.238411 | 84 | 0.647251 |
1c26f17d2185eda40065447ee1354e5564503292
| 643 |
py
|
Python
|
keras_malicious_url_detector/library/utility/url_data_loader.py
|
Adrimeov/keras-malicious-url-detector
|
22b8d075b41117f016100bb5ebff14a77907dacb
|
[
"MIT"
] | null | null | null |
keras_malicious_url_detector/library/utility/url_data_loader.py
|
Adrimeov/keras-malicious-url-detector
|
22b8d075b41117f016100bb5ebff14a77907dacb
|
[
"MIT"
] | null | null | null |
keras_malicious_url_detector/library/utility/url_data_loader.py
|
Adrimeov/keras-malicious-url-detector
|
22b8d075b41117f016100bb5ebff14a77907dacb
|
[
"MIT"
] | null | null | null |
import pandas as pd
import os
def load_url_data(data_dir_path):
url_data = pd.read_csv(data_dir_path, sep=',')
url_data.columns = ['text', 'label']
class_zero = url_data[url_data['label'] == 0].reset_index()
class_one = url_data[url_data['label'] == 1].reset_index()
class_zero = class_zero.truncate(before=1, after=class_one.shape[0])
url_data = pd.concat([class_zero, class_one])
url_data = url_data.sample(frac=1.0).reset_index()
return url_data
def main():
data_dir_path = './data'
url_data = load_url_data(data_dir_path)
print(url_data.head())
if __name__ == '__main__':
main()
| 21.433333 | 72 | 0.678072 |
c70927eb1e75849d56fdcae49b01e64384fcad46
| 587 |
py
|
Python
|
computer-networking-a-top-down-approach/cp2/ping_client.py
|
Jocs/reading-notes
|
26b8331877a2de034b8860bc3e3967893112d52d
|
[
"MIT"
] | 3 |
2021-08-04T07:59:48.000Z
|
2022-03-26T23:58:17.000Z
|
computer-networking-a-top-down-approach/cp2/ping_client.py
|
Jocs/reading-notes
|
26b8331877a2de034b8860bc3e3967893112d52d
|
[
"MIT"
] | null | null | null |
computer-networking-a-top-down-approach/cp2/ping_client.py
|
Jocs/reading-notes
|
26b8331877a2de034b8860bc3e3967893112d52d
|
[
"MIT"
] | null | null | null |
from socket import *
import time
serverName = '127.0.0.1'
serverPort = 12000
socketClient = socket(AF_INET, SOCK_DGRAM)
socketClient.settimeout(1)
for i in range(0, 10):
sendTime = time.time()
message = ('Ping %d %s' % (i + 1, sendTime)).encode()
try:
socketClient.sendto(message, (serverName, serverPort))
modifiedMessage, serverAddress = socketClient.recvfrom(1024)
rtt = time.time() - sendTime
print('Sequence %d: Reply from %s RTT = %.3fs' % (i+1, serverName, rtt))
except Exception as e:
print('Sequence %d timeout' % (i + 1))
socketClient.close()
| 27.952381 | 79 | 0.674617 |
c719e11e1ced89112513a66e444d40617c7ab79a
| 4,421 |
py
|
Python
|
tests/addons/res2dict/test_block.py
|
ihatov08/jumeaux
|
7d983474df4b6dcfa57ea1a66901fbc99ebababa
|
[
"MIT"
] | 11 |
2017-10-02T01:29:12.000Z
|
2022-03-31T08:37:22.000Z
|
tests/addons/res2dict/test_block.py
|
ihatov08/jumeaux
|
7d983474df4b6dcfa57ea1a66901fbc99ebababa
|
[
"MIT"
] | 79 |
2017-07-16T14:47:17.000Z
|
2022-03-31T08:49:14.000Z
|
tests/addons/res2dict/test_block.py
|
ihatov08/jumeaux
|
7d983474df4b6dcfa57ea1a66901fbc99ebababa
|
[
"MIT"
] | 2 |
2019-01-28T06:11:58.000Z
|
2021-01-25T07:21:21.000Z
|
#!/usr/bin/env python
# -*- coding:utf-8 -*-
import datetime
import pytest
from owlmixin.util import load_yaml
from jumeaux.addons.res2dict.block import Executor
from jumeaux.models import Response, Res2DictAddOnPayload
PATTERN1_BODY = """
[Module1]
Name: Jumeaux
License: MIT
Version: 0.33.0
[Module2 alpha]
Name: Jumeaux Viewer
Version: 1.0.0 (r: 1585:1586)
""".lstrip()
PATTERN2_BODY = """
1)Module1
Name Jumeaux
License MIT
Version 0.33.0
2)Module2 alpha
Name Jumeaux Viewer
Version 1.0.0 (r1585)
""".lstrip()
NO_END_LINEBREAK_BODY = """
[Module1]
Name: Jumeaux
License: MIT
Version: 0.33.0
[Module2 alpha]
Name: Jumeaux Viewer
Version: 1.0.0 (r1585)
""".strip()
PATTERN1 = ("Normal",
"""
force: False
header_regexp: '\\[(.+)\\]'
record_regexp: '([^:]+): (.+)'
""",
Response.from_dict({
"body": PATTERN1_BODY.encode('utf-8'),
"type": "plain",
"encoding": 'utf-8',
"headers": {
"content-type": "text/plain; charset=utf-8"
},
"url": "http://test",
"status_code": 200,
"elapsed": datetime.timedelta(seconds=1),
"elapsed_sec": 1.0,
}),
{
"Module1": {
"Name": "Jumeaux",
"License": "MIT",
"Version": "0.33.0"
},
"Module2 alpha": {
"Name": "Jumeaux Viewer",
"Version": "1.0.0 (r: 1585:1586)"
}
}
)
PATTERN2 = ("Normal",
"""
force: False
header_regexp: '^\\d+\\)(.+)'
record_regexp: '([^ ]+) (.+)'
""",
Response.from_dict({
"body": PATTERN2_BODY.encode('utf-8'),
"type": "plain",
"encoding": 'utf-8',
"headers": {
"content-type": "text/plain; charset=utf-8"
},
"url": "http://test",
"status_code": 200,
"elapsed": datetime.timedelta(seconds=1),
"elapsed_sec": 1.0,
}),
{
"Module1": {
"Name": "Jumeaux",
"License": "MIT",
"Version": "0.33.0"
},
"Module2 alpha": {
"Name": "Jumeaux Viewer",
"Version": "1.0.0 (r1585)"
}
}
)
NO_END_LINEBREAK = ("No end linebreak",
"""
force: False
header_regexp: '\\[(.+)\\]'
record_regexp: '([^:]+): (.+)'
""",
Response.from_dict({
"body": NO_END_LINEBREAK_BODY.encode('utf-8'),
"type": "plain",
"encoding": 'utf-8',
"headers": {
"content-type": "text/plain; charset=utf-8"
},
"url": "http://test",
"status_code": 200,
"elapsed": datetime.timedelta(seconds=1),
"elapsed_sec": 1.0,
}),
{
"Module1": {
"Name": "Jumeaux",
"License": "MIT",
"Version": "0.33.0"
},
"Module2 alpha": {
"Name": "Jumeaux Viewer",
"Version": "1.0.0 (r1585)"
}
}
)
class TestExec:
@pytest.mark.parametrize(
'title, config_yml, response, expected_result', [
PATTERN1,
PATTERN2,
NO_END_LINEBREAK,
]
)
def test(self, title, config_yml, response, expected_result):
payload: Res2DictAddOnPayload = Res2DictAddOnPayload.from_dict({
'response': response,
})
actual: Res2DictAddOnPayload = Executor(load_yaml(config_yml)).exec(payload)
assert actual.response == response
assert actual.result.get() == expected_result
| 28.522581 | 84 | 0.406243 |
c75729dda34f44378f1f02da98c296ce6020d9b8
| 720 |
py
|
Python
|
weibo/login/WeiboSearch.py
|
haiboz/weiboSpider
|
517cae2ef3e7bccd9e1d328a40965406707f5362
|
[
"Apache-2.0"
] | null | null | null |
weibo/login/WeiboSearch.py
|
haiboz/weiboSpider
|
517cae2ef3e7bccd9e1d328a40965406707f5362
|
[
"Apache-2.0"
] | null | null | null |
weibo/login/WeiboSearch.py
|
haiboz/weiboSpider
|
517cae2ef3e7bccd9e1d328a40965406707f5362
|
[
"Apache-2.0"
] | null | null | null |
#encoding:utf8
'''
Created on 2016年4月11日
@author: wb-zhaohaibo
'''
import re
import json
def sServerData(serverData):
"Search the server time & nonce from server data"
p = re.compile('\((.*)\)')
jsonData = p.search(serverData).group(1)
data = json.loads(jsonData)
serverTime = str(data['servertime'])
nonce = data['nonce']
pubkey = data['pubkey']#
rsakv = data['rsakv']#
print "Server time is:", serverTime
print "Nonce is:", nonce
return serverTime, nonce, pubkey, rsakv
def sRedirectData(text):
p = re.compile('location\.replace\([\'"](.*?)[\'"]\)')
loginUrl = p.search(text).group(1)
print 'loginUrl:',loginUrl
return loginUrl
| 25.714286 | 59 | 0.613889 |
c78d99955e67deeb2e620ec322002ab6b93889ea
| 689 |
py
|
Python
|
exercises/pt/exc_02_14.py
|
tuanducdesign/spacy-course
|
f8d092c5fa2997fccb3f367d174dce8667932b3d
|
[
"MIT"
] | null | null | null |
exercises/pt/exc_02_14.py
|
tuanducdesign/spacy-course
|
f8d092c5fa2997fccb3f367d174dce8667932b3d
|
[
"MIT"
] | null | null | null |
exercises/pt/exc_02_14.py
|
tuanducdesign/spacy-course
|
f8d092c5fa2997fccb3f367d174dce8667932b3d
|
[
"MIT"
] | null | null | null |
import json
import spacy
with open("exercises/pt/countries.json", encoding="utf8") as f:
COUNTRIES = json.loads(f.read())
nlp = spacy.blank("pt")
doc = nlp("A República Tcheca deve ajudar a Eslováquia a proteger seu espaço aéreo.")
# Importar o PhraseMatcher e inicializá-lo
from spacy.____ import ____
matcher = ____(____)
# Criar objeto com a expressão e adicioná-lo ao comparador matcher
# Essa é a forma mais eficiente: [nlp(country) for country in COUNTRIES]
patterns = list(nlp.pipe(COUNTRIES))
matcher.add("COUNTRY", patterns)
# Chamar o matcher no documento de teste e imprimir o resultado
matches = ____(____)
print([doc[start:end] for match_id, start, end in matches])
| 29.956522 | 85 | 0.750363 |
1be96298cc3d51bb4bedd0b7a44a6da10210454a
| 10,628 |
py
|
Python
|
algo/simplex.py
|
teastares/or_lab
|
c8fb5c22d31c1e2b93381397202be7b71a3fc796
|
[
"MIT"
] | 1 |
2021-01-18T09:11:59.000Z
|
2021-01-18T09:11:59.000Z
|
algo/simplex.py
|
teastares/or_lab
|
c8fb5c22d31c1e2b93381397202be7b71a3fc796
|
[
"MIT"
] | null | null | null |
algo/simplex.py
|
teastares/or_lab
|
c8fb5c22d31c1e2b93381397202be7b71a3fc796
|
[
"MIT"
] | null | null | null |
"""
This file defines the algorithms.
Last edited by Teast Ares, 20190130.
"""
import itertools
import numpy as np
from util import *
from constant import const
class Simplex:
"""
Simplex method for solving linear programming.
If model is not a LP, we will relax it to LP.
paras:
model: the original model.
"""
def __init__(self, model):
self.model = model
def get_standardize_model(self):
"""
get a standard model.
----------
Min cx
s.t.
Ax = b
x >= 0
----------
paras:
model: the original model.
returns:
the standardized model.
"""
pass
def map_variables(model):
"""
map the variables by the four types of variable bound.
paras:
model: the original model.
returns:
variable_map_dict: a dictionary contains four sub-dictionaries, each
contains the replaced parameters.
"""
variable_map_dict = {
const.BOUND_TWO_OPEN: defaultdict(lambda: None),
const.BOUND_LEFT_OPEN: defaultdict(lambda: None),
const.BOUND_RIGHT_OPEN: defaultdict(lambda: None),
const.BOUND_TWO_CLOSED: defaultdict(lambda: None)
}
for variable in model.variable_dict.values():
# if x is two-side unbounded (-infinite, infinite), then x = x1 - x2
if variable.get_bound_type() == const.BOUND_TWO_OPEN:
x1 = Variable(name=variable.name + "_plus",cat=variable.cat)
x2 = Variable(name=variable.name + "_minus", cat=variable.cat)
variable_map_dict[const.BOUND_TWO_OPEN][variable.name] = (x1, x2)
# if x is left-side unbounded (-infinite, upper_bound), then x = -x1 + upper_bound
elif variable.get_bound_type() == const.BOUND_LEFT_OPEN:
x1 = Variable(name=variable.name + "_opposite_shift", cat=variable.cat)
variable_map_dict[const.BOUND_LEFT_OPEN][variable.name] = (x1, variable.upper_bound)
# if x is right-side unbounded (lower_bound, infinite), then x = x1 + lower_bound
elif variable.get_bound_type() == const.BOUND_RIGHT_OPEN:
x1 = Variable(name=variable.name + "_shift", cat=variable.cat)
variable_map_dict[const.BOUND_RIGHT_OPEN][variable.name] = (x1, variable.lower_bound)
# if x is two-side closed (lower_bound, upper_bound), then x = x1 + lower_bound,
# and there should be a constrain x1 <= variable.upper_bound - variable.lower_bound
else:
x1 = Variable(name=variable.name + "_shift", cat=variable.cat)
variable_map_dict[const.BOUND_TWO_CLOSED][variable.name] = (x1, variable.lower_bound, variable.upper_bound - variable.lower_bound)
return variable_map_dict
def replace_linear_expression(linear_expression, variable_map_dict):
"""
use the variable map dictionary to get the replaced linear expression.
paras:
linear_expression: the original linear expression
variable_map_dict: a dictionary contains four sub-dictionaries, each
contains the replaced parameters.
returns:
the replaced linear expression and the additional right hand side.
"""
replaced_linear_expression = LinearExpression()
arhs = 0
for variable_name, coefficient in linear_expression.coefficient_dict.items():
variable = linear_expression.variable_dict[variable_name]
if variable.get_bound_type() == const.BOUND_TWO_OPEN:
x1, x2 = variable_map_dict[const.BOUND_TWO_OPEN][variable_name]
replaced_linear_expression.add_item(x1, coefficient)
replaced_linear_expression.add_item(x2, -coefficient)
elif variable.get_bound_type() == const.BOUND_LEFT_OPEN:
x1, shift = variable_map_dict[const.BOUND_LEFT_OPEN][variable_name]
replaced_linear_expression.add_item(x1, -coefficient)
arhs -= (shift * coefficient)
elif variable.get_bound_type() == const.BOUND_RIGHT_OPEN:
x1, shift = variable_map_dict[const.BOUND_RIGHT_OPEN][variable_name]
replaced_linear_expression.add_item(x1, coefficient)
arhs -= (shift * coefficient)
else:
x1, shift, _ = variable_map_dict[const.BOUND_TWO_CLOSED][variable_name]
replaced_linear_expression.add_item(x1, coefficient)
arhs -= (shift * coefficient)
return replaced_linear_expression, arhs
def standardize_model(model):
"""
get a standard model.
----------
Max cx
s.t.
Ax = b
x >= 0
----------
paras:
model: the original model.
returns:
the standardized model.
"""
variable_map_dict = map_variables(model)
standard_model = Model(name="standard " + model.name, sense=const.SENSE_MAX)
# add the standard variables to the standard model.
for x1, x2 in variable_map_dict[const.BOUND_TWO_OPEN].values():
standard_model.add_variable(x1)
standard_model.add_variable(x2)
for x1, _ in variable_map_dict[const.BOUND_LEFT_OPEN].values():
standard_model.add_variable(x1)
for x1, _ in variable_map_dict[const.BOUND_RIGHT_OPEN].values():
standard_model.add_variable(x1)
for x1, _, upper_bound in variable_map_dict[const.BOUND_TWO_CLOSED].values():
standard_model.add_variable(x1)
upper_bound_constrain = Constraint(name=x1.name + "_upper_bound", sense=const.SENSE_EQ)
slack_variable = Variable(name="slack_"+x1.name)
standard_model.add_variable(slack_variable)
upper_bound_constrain.add_lhs_item(x1, 1)
upper_bound_constrain.add_lhs_item(slack_variable, 1)
upper_bound_constrain.set_rhs(upper_bound)
standard_model.add_constraint(upper_bound_constrain)
# objective function
if model.sense == const.SENSE_MAX:
standard_model.set_objective(replace_linear_expression(model.objective, variable_map_dict)[0])
else:
model.objective.oppose()
standard_model.set_objective(replace_linear_expression(model.objective, variable_map_dict)[0])
model.objective.oppose()
# constrains
for original_constrain in model.constrain_dict.values():
lhs, arhs = replace_linear_expression(original_constrain.lhs, variable_map_dict)
constrain = Constraint(name=original_constrain.name + "_replaced", lhs=lhs, sense=const.SENSE_EQ, rhs=original_constrain.rhs + arhs)
if original_constrain.sense == const.SENSE_LEQ:
slack_variable = Variable(name="slack_"+original_constrain.name)
standard_model.add_variable(slack_variable)
constrain.add_lhs_item(slack_variable, 1)
elif original_constrain.sense == const.SENSE_GEQ:
slack_variable = Variable(name="slack_"+original_constrain.name)
standard_model.add_variable(slack_variable)
constrain.add_lhs_item(slack_variable, -1)
standard_model.add_constraint(constrain)
return standard_model
def matrix_generation(standard_model, variable_index_dict, constrain_index_dict):
"""
For a standard model, we have following structure:
------------------
Max cx
s.t.
Ax = b
------------------
This function will generate the Numpy Ndarray format data.
paras:
standard_model: a model with standard formation,
variable_index_dict: the dict for variable's index,
constrain_index_dict: the dict for constraint's index.
returns:
c: the cost function vector,
A: the left hand side matrix,
b: the right hand side vector.
"""
# the column number, or the number of variables.
n = len(variable_index_dict)
# the row number, or the number of constrains.
m = len(constrain_index_dict)
c = np.zeros(n)
for variable_name, value in standard_model.objective.coefficient_dict.items():
index = variable_index_dict[variable_name]
c[index] = value
A = np.zeros((m, n))
b = np.zeros(m)
for constrain_name, constrain in standard_model.constrain_dict.items():
row_index = constrain_index_dict[constrain_name]
for variable_name, value in constrain.lhs.coefficient_dict.items():
column_index = variable_index_dict[variable_name]
A[row_index, column_index] = value
b[row_index] = constrain.rhs
return c, A, b
def is_solvable(A, b):
"""
To valid if the linear equations Ax=b is solvable.
paras:
A: the left hand side matrix,
b: the right hand side vector.
returns:
True\False
"""
m = b.shape[0]
_A = np.concatenate((A, b.reshape(m, 1)), axis=1)
if np.linalg.matrix_rank(A) == np.linalg.matrix_rank(_A):
return True
else:
return False
def search_init_solution(A, b):
"""
For a linear equations Ax=b, search a extreme point as a initial solution.
paras:
A: the left hand side matrix,
b: the right hand side vector.
"""
m, n = A.shape
for item in itertools.permutations(range(n)[::-1], m):
_A = A[:, item]
basic_solution = np.linalg.solve(_A, b)
for value in basic_solution:
if value < 0:
break
else:
init_solution = np.zeros(n)
init_basic_position = np.zeros(n)
for index, value in enumerate(basic_solution):
position = item[index]
init_solution[position] = value
init_basic_position[position] = 1
return init_solution, init_basic_position
def simplex_method(model, simplex_type):
"""
Use the simplex method to solve the linear programming.
paras:
model: the original linear programing model.
returns:
TBD
"""
standard_model = standardize_model(model)
variable_list = list(standard_model.variable_dict)
constrain_list = list(standard_model.constrain_dict)
variable_index_dict = dict()
constrain_index_dict = dict()
for index, variable in enumerate(variable_list):
variable_index_dict[variable] = index
for index, constrain in enumerate(constrain_list):
constrain_index_dict[constrain] = index
c, A, b = matrix_generation(standard_model, variable_index_dict, constrain_index_dict)
# check if there has a solution
if is_solvable(A, b) == False:
standard_model.status == const.STATUS_NO_SOLUTION
return
init_solution, init_basic_position = search_init_solution(A, b)
return init_solution, init_basic_position
| 34.064103 | 142 | 0.665036 |
909efa8645242acf6bd1c290699feb5f896c38ba
| 1,917 |
py
|
Python
|
leetcode/005-Longest-Palindromic-Substring/LongPalSubstr_001.py
|
cc13ny/all-in
|
bc0b01e44e121ea68724da16f25f7e24386c53de
|
[
"MIT"
] | 1 |
2017-05-18T06:11:02.000Z
|
2017-05-18T06:11:02.000Z
|
leetcode/005-Longest-Palindromic-Substring/LongPalSubstr_001.py
|
cc13ny/all-in
|
bc0b01e44e121ea68724da16f25f7e24386c53de
|
[
"MIT"
] | 1 |
2016-02-09T06:00:07.000Z
|
2016-02-09T07:20:13.000Z
|
leetcode/005-Longest-Palindromic-Substring/LongPalSubstr_001.py
|
cc13ny/all-in
|
bc0b01e44e121ea68724da16f25f7e24386c53de
|
[
"MIT"
] | 2 |
2019-06-27T09:07:26.000Z
|
2019-07-01T04:40:13.000Z
|
# @author: cchen
# pretty long and should be simplified later
class Solution:
# @param {string} s
# @return {string}
def longestPalindrome(self, s):
size = len(s)
ls = []
ll = 0
rr = 0
l = 0
r = 0
maxlen = r - l + 1
for i in range(1, size):
if s[i - 1] == s[i]:
r = i
else:
if r - l + 1 > maxlen:
maxlen = r - l + 1
ll = l
rr = r
ls.append([[l, r], s[i - 1]])
l = i
r = i
if r - l + 1 > maxlen:
maxlen = r - l + 1
ll = l
rr = r
ls.append([[l, r], s[size - 1]])
for i in range(1, len(ls) - 1):
l = i - 1
r = i + 1
clen = ls[i][0][1] - ls[i][0][0] + 1
while -1 < l and r < len(ls) and ls[l][1] == ls[r][1]:
llen = ls[l][0][1] - ls[l][0][0] + 1
rlen = ls[r][0][1] - ls[r][0][0] + 1
if llen == rlen:
clen += 2 * llen
if clen > maxlen:
maxlen = clen
ll = ls[l][0][0]
rr = ls[r][0][1]
l -= 1
r += 1
else:
if llen > rlen:
clen += 2 * rlen
else:
clen += 2 * llen
if clen > maxlen:
maxlen = clen
if llen > rlen:
ll = ls[l][0][1] - rlen + 1
rr = ls[r][0][1]
else:
ll = ls[l][0][0]
rr = ls[r][0][0] + llen - 1
break
return s[ll:rr + 1]
| 28.191176 | 66 | 0.27856 |
46a0da48b68a91465765362d47177cf154fd8be0
| 1,313 |
py
|
Python
|
2020-09-02-1159-gma_istPrim.py
|
gmaubach/OOP-with-Python
|
9b059e911d55d616e756324564f1f2cc524aa53d
|
[
"MIT"
] | null | null | null |
2020-09-02-1159-gma_istPrim.py
|
gmaubach/OOP-with-Python
|
9b059e911d55d616e756324564f1f2cc524aa53d
|
[
"MIT"
] | null | null | null |
2020-09-02-1159-gma_istPrim.py
|
gmaubach/OOP-with-Python
|
9b059e911d55d616e756324564f1f2cc524aa53d
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
Created on Wed Sep 2 11:38:10 2020
@author: Georg Maubach
Schreiben Sie eine Funktion istPrim(), die einen
ganzzahligen Wert übergeben bekommt und die dann
zurückliefert, ob der Wert eine Primzahl ist oder
nicht.
Definition Primzahl:
- Zahl ist NUR durch 1 und durch sich selbst teilbar.
"""
def istPrim(wert): # Meine Lösung
x = 2
primzahl = True;
while(x < wert):
if(wert % x == 0):
primzahl = False;
x += 1
return(primzahl);
def istPrin(wert):
if (wert == 1) return False;
max = wert / 2; # wenn der Teiler größer als die Hälfte ist,
# muss die Division nur noch ungerade Werte
# liefern.
y = 2;
while y <= max:
if((x % y) == 0: return False; # alle weiteren Werte muss
# ich dann nicht mehr weiter
# prüfen. Damit das Programm
# schneller.
y += 1
return True;
if __name__ == "__main__":
print("Primzahl ", istPrim(2));
print("Primzahl ", istPrim(5));
print("Primzahl ", istPrim(10));
print("Primzahl ", istPrim(99));
pass
| 26.26 | 68 | 0.50495 |
b4431f07b1d304fb8d5b45e5a3617709b7e19e3c
| 9,983 |
py
|
Python
|
Python/pyBitwiseAutomation/SocketDevice.py
|
jimwaschura/Automation
|
f655feeea74ff22ebe44d8b68374ba6983748f60
|
[
"BSL-1.0"
] | null | null | null |
Python/pyBitwiseAutomation/SocketDevice.py
|
jimwaschura/Automation
|
f655feeea74ff22ebe44d8b68374ba6983748f60
|
[
"BSL-1.0"
] | null | null | null |
Python/pyBitwiseAutomation/SocketDevice.py
|
jimwaschura/Automation
|
f655feeea74ff22ebe44d8b68374ba6983748f60
|
[
"BSL-1.0"
] | null | null | null |
# SocketDevice.py
# ================================================================================
# BOOST SOFTWARE LICENSE
#
# Copyright 2020 BitWise Laboratories Inc.
# Original Author.......Jim Waschura
# [email protected]
#
# Permission is hereby granted, free of charge, to any person or organization
# obtaining a copy of the software and accompanying documentation covered by
# this license (the "Software") to use, reproduce, display, distribute,
# execute, and transmit the Software, and to prepare derivative works of the
# Software, and to permit third-parties to whom the Software is furnished to
# do so, all subject to the following:
#
# The copyright notices in the Software and this entire statement, including
# the above license grant, this restriction and the following disclaimer,
# must be included in all copies of the Software, in whole or in part, and
# all derivative works of the Software, unless such copies or derivative
# works are solely in the form of machine-executable object code generated by
# a source language processor.
#
# 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, TITLE AND NON-INFRINGEMENT. IN NO EVENT
# SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE
# FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE,
# ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
# DEALINGS IN THE SOFTWARE.
# ================================================================================
import socket
import time
import struct
from pyBitwiseAutomation.AutomationInterface import *
from enum import Enum
class SocketDevice(AutomationInterface):
"""Socket device class."""
Start = float(0.0)
# Sock = None
# IsConnected = False
def __init__(self):
self.Sock = None
self.IsConnected = False
self.Debugging = False
return None
def __del__(self):
if self.IsConnected:
self.Disconnect()
return None
@staticmethod
def timestamp():
now = time.time()
if SocketDevice.Start == 0.0:
SocketDevice.Start = now
return now-SocketDevice.Start
def getDebugging(self) -> bool:
return self.Debugging
def setDebugging(self, newValue: bool):
self.Debugging = newValue
def getIsConnected(self) -> bool:
return self.IsConnected
def Connect( self, ipaddress: str, dflt_port:int = 923 ) :
"""Connect to socket device."""
if self.IsConnected:
self.Disconnect()
tempBuffer = ipaddress
tempPort = dflt_port
tokens = ipaddress.split(":")
if len(tokens) > 1:
tempBuffer = tokens[0]
tempPort = int(tokens[1])
try:
self.Sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
except Exception as e:
print("socket.socket() exception:", e)
raise Exception("[Create_Socket_Failed")
try:
self.Sock.connect((tempBuffer, tempPort))
self.IsConnected = True
except Exception as e:
print("self.Sock.connect() exception is: ", e)
self.Sock=None
raise Exception("[Unable_To_Connect]")
return None
def Disconnect( self ):
"""Disconnect from socket device."""
if self.IsConnected:
self.Sock.shutdown(socket.SHUT_RDWR)
self.Sock.close()
self.IsConnected = False
self.Sock=None
return None
def Receive( self, buflen:int ) -> bytes:
"""Receive up to maximum number of bytes from socket device."""
if not self.IsConnected:
raise Exception("[Not_Connected]")
return self.Sock.recv(buflen)
def Send( self, buffer: bytes):
"""Send specified number of bytes to socket device."""
if not isinstance(buffer,bytes) :
raise Exception("[Invalid_Type]")
if not self.IsConnected:
raise Exception("[Not_Connected]")
self.Sock.send(buffer)
return None
def SendCommand(self, command: str ):
"""Send command (ending with '\n') to socket device."""
if not isinstance(command,str) :
raise Exception("[Invalid_Command_Type]")
if not self.IsConnected:
raise Exception("[Not_Connected]")
if self.Debugging:
print("SendCommand() command: " + command)
self.Sock.send(bytes(command,'utf-8'))
return None
def QueryResponse( self, command: str, maxLength:int = 4096 ) -> str:
"""Query response from command (ending with '\n') from socket device."""
if not isinstance(command, str) :
raise Exception("[Invalid_Command_Type]")
if not self.IsConnected:
raise Exception("[Not_Connected]")
if self.Debugging:
print( "QueryResponse() query: " + command )
self.Sock.send( bytes(command, 'utf-8'))
tempBytes = self.Sock.recv(maxLength)
tempString = str(tempBytes, encoding='utf-8')
if len(tempString)>0 and tempString[-1]=="\n" :
tempString = tempString[0:-1]
if len(tempString)>1 and tempString[0] == '"' and tempString[-1] == '"' :
tempString = tempString[1:-1]
if self.Debugging:
print( "QueryResponse() response: " + tempString )
return tempString
def QueryResponse_int(self, command: str ) -> int:
"""Query integer response from command (ending with '\n') from socket device."""
return int(self.QueryResponse(command))
def QueryResponse_bool(self, command: str ) -> bool:
"""Query boolean response from command (ending with '\n') from socket device."""
response = self.QueryResponse(command)
return bool( len(response) > 0 and (response[0] == 'T' or response[0] == 't' or response[0] == '1') )
def QueryResponse_float(self, command: str ) -> float:
"""Query float response from command (ending with '\n') from socket device."""
return float(self.QueryResponse( command))
def QueryResponse_enum(self, enumeration:Enum, command: str) -> Enum:
"""Query integer index of enum response from command (ending with '\n') from socket device."""
if not isinstance(command, str):
raise Exception("[Command_Must_Be_String]")
return enumeration(self.QueryResponse(command))
def SendBinaryCommand(self, command: str, buffer: bytes):
"""Send command (ending with '\n') followed by 4-byte count and array of bytes to socket device."""
if not isinstance(command, str):
raise Exception("[Invalid_Command_Type]")
if not isinstance(buffer, bytes):
raise Exception("[Invalid_Buffer_Type]")
if not self.IsConnected:
raise Exception("[Not_Connected]")
if self.Debugging:
print("SendBinaryCommand() command: " + command)
count = len(buffer)
self.Sock.send(bytes(command,'utf-8'))
self.Sock.send(count.to_bytes(4, byteorder='little'))
self.Sock.send(buffer)
return None
def QueryBinaryResponse(self, command: str) -> bytes :
"""Query array of bytes response from command (ending with '\n') from socket device."""
if not isinstance(command, str) :
raise Exception("[Invalid_Command_Type]")
if not self.IsConnected:
raise Exception("[Not_Connected]")
if self.Debugging:
print("QueryBinaryResponse() command: " + command)
self.Sock.send(bytes(command, 'utf-8'))
countBytes = self.Sock.recv(4)
if len(countBytes) != 4:
raise Exception("[Missing_Count_Response]")
count = int.from_bytes(countBytes, byteorder="little")
return_value = bytes(0)
if count>0 :
total = 0
while total<count :
portion = self.Sock.recv(count-total)
amount = len(portion)
if amount == 0:
raise Exception("[Error_Receiving_Buffer]")
return_value += portion
total += amount
pass
return return_value
def QueryBinaryResponse_float(self, command: str) -> list:
"""Query array of floats response from command (ending with '\n') from socket device."""
data = self.QueryBinaryResponse(command)
if not (len(data) % 4) == 0:
raise Exception("[Binary_Float_Size_Invalid]")
count = int(len(data)/4)
retn = []
if count>0 :
for i in range(count):
retn.append(float(struct.unpack_from("<f", data, i*4)[0]))
return retn
def QueryBinaryResponse_int(self, command: str) -> list:
"""Query array of 32-bit integers response from command (ending with '\n') from socket device."""
data = self.QueryBinaryResponse(command)
if not (len(data) % 4) == 0:
raise Exception("[Binary_Float_Size_Invalid]")
count = int(len(data)/4)
retn = [count]
if count>0 :
for i in range(count):
retn.append(int(struct.unpack_from("<i", data, i*4)[0]))
return retn
def QueryBinaryResponse_double(self, command: str) -> list:
"""Query array of doubles response from command (ending with '\n') from socket device."""
data = self.QueryBinaryResponse(command)
if not (len(data) % 8) == 0:
raise Exception("[Binary_Float_Size_Invalid]")
count = int(len(data)/8)
retn = [count]
if count>0 :
for i in range(count):
retn.append(float(struct.unpack_from("<d", data, i*8)[0]))
return retn
# EOF
| 34.424138 | 110 | 0.608234 |
6f2011e99aa153ea426797f4955466f84ec63854
| 1,492 |
py
|
Python
|
angstrom/2019/crypto/Eightball/server.py
|
mystickev/ctf-archives
|
89e99a5cd5fb6b2923cad3fe1948d3ff78649b4e
|
[
"MIT"
] | 1 |
2021-11-02T20:53:58.000Z
|
2021-11-02T20:53:58.000Z
|
angstrom/2019/crypto/Eightball/server.py
|
ruhan-islam/ctf-archives
|
8c2bf6a608c821314d1a1cfaa05a6cccef8e3103
|
[
"MIT"
] | null | null | null |
angstrom/2019/crypto/Eightball/server.py
|
ruhan-islam/ctf-archives
|
8c2bf6a608c821314d1a1cfaa05a6cccef8e3103
|
[
"MIT"
] | 1 |
2021-12-19T11:06:24.000Z
|
2021-12-19T11:06:24.000Z
|
import binascii
import socketserver
from Crypto.Random.random import choice
from Crypto.Util.asn1 import DerSequence
import benaloh
answers = [
b'It is certain',
b'It is decidedly so',
b'Without a doubt',
b'Yes definitely',
b'You may rely on it',
b'As I see it, yes',
b'Most likely',
b'Outlook good',
b'Yes',
b'Signs point to yes',
b'Reply hazy try again',
b'Ask again later',
b'Better not tell you now',
b'Cannot predict now',
b'Concentrate and ask again',
b'Don\'t count on it',
b'My reply is no',
b'My sources say no',
b'Outlook not so good',
b'Very doubtful'
]
sk = benaloh.unpack('sk')
def handle(self):
while True:
der = DerSequence()
der.decode(binascii.unhexlify(self.query(b'Question: ')))
question = bytes([benaloh.decrypt(c, sk) for c in der])
response = choice(answers)
self.write(response)
class RequestHandler(socketserver.BaseRequestHandler):
handle = handle
def read(self, until=b'\n'):
out = b''
while not out.endswith(until):
out += self.request.recv(1)
return out[:-len(until)]
def query(self, string=b''):
self.write(string, newline=False)
return self.read()
def write(self, string, newline=True):
self.request.sendall(string)
if newline:
self.request.sendall(b'\n')
class Server(socketserver.ForkingTCPServer):
allow_reuse_address = True
def handle_error(self, request, client_address):
pass
port = 3000
server = Server(('0.0.0.0', port), RequestHandler)
server.serve_forever()
| 21.314286 | 59 | 0.69437 |
48fe19da112a00251dbf32baa059193efdd1efc1
| 1,358 |
py
|
Python
|
make_executible.py
|
Morgadow/Bierliste_K3.1
|
088806849affbbf5ea0b24fc0393a2308cd5b4aa
|
[
"MIT"
] | null | null | null |
make_executible.py
|
Morgadow/Bierliste_K3.1
|
088806849affbbf5ea0b24fc0393a2308cd5b4aa
|
[
"MIT"
] | null | null | null |
make_executible.py
|
Morgadow/Bierliste_K3.1
|
088806849affbbf5ea0b24fc0393a2308cd5b4aa
|
[
"MIT"
] | null | null | null |
#!/usr/bin/python3.7
# -*- coding: utf-8 -*-
import os
import shutil
from Bierliste_Tool import __version__
import time
PROJECT_NAME = "Bierliste_Tool"
print("Create .exe file for version: " + __version__)
print("")
if not os.path.exists(os.path.join("Executible", 'v' + __version__)):
print("Preparing folder " + 'v' + __version__)
os.makedirs(os.path.join("Executible", 'v' + __version__))
shutil.copyfile("Example_file.xlsx", os.path.join("Executible", 'v' + __version__, "Example_file.xlsx"))
shutil.copyfile("settings.ini", os.path.join("Executible", 'v' + __version__, "settings.ini"))
else:
print("Folder already exists, file will be replaced!")
if os.path.exists(os.path.join("Executible", 'v' + __version__, "{}.exe".format(PROJECT_NAME))):
os.remove(os.path.join("Executible", 'v' + __version__, "{}.exe".format(PROJECT_NAME)))
print("\nMake executible:")
os.system("mk_exe.bat")
# give programm some time to finish task
time.sleep(5)
print("\nCleaning up ...")
shutil.copyfile(os.path.join("dist", "{}.exe".format(PROJECT_NAME)), os.path.join("Executible", 'v' + __version__, "{}.exe".format(PROJECT_NAME)))
for folder in ('build', 'dist', '__pycache__', '.idea'):
try:
shutil.rmtree(folder)
except:
pass
os.remove("{}.spec".format(PROJECT_NAME))
| 35.736842 | 147 | 0.659057 |
7daf21b74d8b5eb42cd09299049750ed974bcb1b
| 345 |
py
|
Python
|
数据结构/NowCode/41_rectCover.py
|
Blankwhiter/LearningNotes
|
83e570bf386a8e2b5aa699c3d38b83e5dcdd9cb0
|
[
"MIT"
] | null | null | null |
数据结构/NowCode/41_rectCover.py
|
Blankwhiter/LearningNotes
|
83e570bf386a8e2b5aa699c3d38b83e5dcdd9cb0
|
[
"MIT"
] | 3 |
2020-08-14T07:50:27.000Z
|
2020-08-14T08:51:06.000Z
|
数据结构/NowCode/41_rectCover.py
|
Blankwhiter/LearningNotes
|
83e570bf386a8e2b5aa699c3d38b83e5dcdd9cb0
|
[
"MIT"
] | 2 |
2021-03-14T05:58:45.000Z
|
2021-08-29T17:25:52.000Z
|
# 矩形覆盖
class Solution:
def rectCover(self, number):
# write code here
if number == 0:
return 0
if number == 1:
return 1
if number == 2:
return 2
a = 1
b = 2
for i in range(3, number + 1):
b = a + b
a = b - a
return b
| 20.294118 | 38 | 0.394203 |
7defcf558669cbf65947bd91d6bd4823108f5d2b
| 696 |
py
|
Python
|
imwievaluation/semester.py
|
ESchae/IMWIEvaluation
|
2fa661711b7b65cba25c1fa9ba69e09e75c7655f
|
[
"MIT"
] | null | null | null |
imwievaluation/semester.py
|
ESchae/IMWIEvaluation
|
2fa661711b7b65cba25c1fa9ba69e09e75c7655f
|
[
"MIT"
] | null | null | null |
imwievaluation/semester.py
|
ESchae/IMWIEvaluation
|
2fa661711b7b65cba25c1fa9ba69e09e75c7655f
|
[
"MIT"
] | 1 |
2019-10-19T10:11:17.000Z
|
2019-10-19T10:11:17.000Z
|
import sqlalchemy as db
from sqlalchemy.dialects import mysql
from sqlalchemy.orm import relationship
from base import Base
class Semester(Base):
__tablename__ = 'semester'
id = db.Column(db.Integer, primary_key=True)
term = db.Column(mysql.ENUM('WS', 'SS'), nullable=False)
year = db.Column(mysql.YEAR(), nullable=False)
# prevent duplicate entries
db.UniqueConstraint(term, year)
# one two many relationship between semester and lecture
lectures = relationship("Lecture", back_populates="semester")
def __init__(self, term, year):
self.term = term
self.year = year
def __str__(self):
return '%s%s' % (self.term, self.year)
| 26.769231 | 65 | 0.689655 |
817a55f51bbc9d8522c0a10c412685bf4172baed
| 722 |
py
|
Python
|
leetcode/092-Reverse-Linked-List-II/RevLinkedListII_001.py
|
cc13ny/all-in
|
bc0b01e44e121ea68724da16f25f7e24386c53de
|
[
"MIT"
] | 1 |
2015-12-16T04:01:03.000Z
|
2015-12-16T04:01:03.000Z
|
leetcode/092-Reverse-Linked-List-II/RevLinkedListII_001.py
|
cc13ny/all-in
|
bc0b01e44e121ea68724da16f25f7e24386c53de
|
[
"MIT"
] | 1 |
2016-02-09T06:00:07.000Z
|
2016-02-09T07:20:13.000Z
|
leetcode/092-Reverse-Linked-List-II/RevLinkedListII_001.py
|
cc13ny/all-in
|
bc0b01e44e121ea68724da16f25f7e24386c53de
|
[
"MIT"
] | 2 |
2019-06-27T09:07:26.000Z
|
2019-07-01T04:40:13.000Z
|
# Definition for singly-linked list.
class ListNode:
def __init__(self, x):
self.val = x
self.next = None
class Solution:
# @param {ListNode} head
# @param {integer} m
# @param {integer} n
# @return {ListNode}
def reverseBetween(self, head, m, n):
dumpy = ListNode(0)
dumpy.next = head
pre = dumpy
diff = n - m
while m > 1:
pre = pre.next
m -= 1
p = pre.next
while diff > 0 and p and p.next:
# print p.val
diff -= 1
tmp = p.next
p.next = tmp.next
q = pre.next
pre.next = tmp
tmp.next = q
return dumpy.next
| 21.878788 | 41 | 0.470914 |
81bf6bf890fef439f92ad73919a95ca7433af382
| 272 |
py
|
Python
|
Licence 2/I33/TP 1/ex_9.py
|
axelcoezard/licence
|
1ed409c4572dea080169171beb7e8571159ba071
|
[
"MIT"
] | 8 |
2020-11-26T20:45:12.000Z
|
2021-11-29T15:46:22.000Z
|
Licence 2/I33/TP 1/ex_9.py
|
axelcoezard/licence
|
1ed409c4572dea080169171beb7e8571159ba071
|
[
"MIT"
] | null | null | null |
Licence 2/I33/TP 1/ex_9.py
|
axelcoezard/licence
|
1ed409c4572dea080169171beb7e8571159ba071
|
[
"MIT"
] | 6 |
2020-10-23T15:29:24.000Z
|
2021-05-05T19:10:45.000Z
|
def tri_bulle(L):
pointer = 0
while pointer < len(L):
left = 0
right = 1
while right < len(L) - pointer:
if L[right] < L[left]:
L[left], L[right] = L[right], L[left]
left += 1
right += 1
pointer += 1
return L
print(tri_bulle([8, -1, 2, 5, 3, -2]))
| 19.428571 | 41 | 0.551471 |
b50fe49d8324b7d77943ea9dcfcba3e2f0c0b5be
| 251 |
py
|
Python
|
Packs/CommonScripts/Scripts/LastArrayElement/LastArrayElement.py
|
diCagri/content
|
c532c50b213e6dddb8ae6a378d6d09198e08fc9f
|
[
"MIT"
] | 799 |
2016-08-02T06:43:14.000Z
|
2022-03-31T11:10:11.000Z
|
Packs/CommonScripts/Scripts/LastArrayElement/LastArrayElement.py
|
diCagri/content
|
c532c50b213e6dddb8ae6a378d6d09198e08fc9f
|
[
"MIT"
] | 9,317 |
2016-08-07T19:00:51.000Z
|
2022-03-31T21:56:04.000Z
|
Packs/CommonScripts/Scripts/LastArrayElement/LastArrayElement.py
|
diCagri/content
|
c532c50b213e6dddb8ae6a378d6d09198e08fc9f
|
[
"MIT"
] | 1,297 |
2016-08-04T13:59:00.000Z
|
2022-03-31T23:43:06.000Z
|
import demistomock as demisto
def main():
value = demisto.args()['value']
if type(value) is list and len(value) > 0:
value = value[-1]
demisto.results(value)
if __name__ == "__builtin__" or __name__ == "builtins":
main()
| 16.733333 | 55 | 0.621514 |
d280380ee06ad6e8b6080dcc93810f12c6802282
| 832 |
py
|
Python
|
Course_1/Week_03/MyQuickSort.py
|
KnightZhang625/Stanford_Algorithm
|
7dacbbfa50e7b0e8380cf500df24af60cb9f42df
|
[
"Apache-2.0"
] | null | null | null |
Course_1/Week_03/MyQuickSort.py
|
KnightZhang625/Stanford_Algorithm
|
7dacbbfa50e7b0e8380cf500df24af60cb9f42df
|
[
"Apache-2.0"
] | 1 |
2020-07-16T08:03:22.000Z
|
2020-07-16T08:09:34.000Z
|
Course_1/Week_03/MyQuickSort.py
|
KnightZhang625/Stanford_Algorithm
|
7dacbbfa50e7b0e8380cf500df24af60cb9f42df
|
[
"Apache-2.0"
] | null | null | null |
import random
def MySwap(MyArray,i,j):
temp = MyArray[i]
MyArray[i] = MyArray[j]
MyArray[j] = temp
def MyQuickSort(MyArray,left,right):
if left == right:
return
random.seed()
pivot = random.randint(left,right)
MySwap(MyArray,left,pivot)
i = left+1 # first element in the right
j = left+1 # last element in the right +1
while j <= right:
if MyArray[j] < MyArray[left]:
MySwap(MyArray,i,j)
i += 1
j += 1
MySwap(MyArray,left,i-1)
if i > left+2:
MyQuickSort(MyArray,left,i-2)
if right > i:
MyQuickSort(MyArray,i,right)
MyInput=[95,33,7,87,665,4,2,5,4,8,56,5,13,45,6,87,34,345,1,6,7,67,434,53,24,64]
print('original:')
print(MyInput)
MyQuickSort(MyInput,0,len(MyInput)-1)
print('after quick sort:')
print(MyInput)
| 25.212121 | 79 | 0.604567 |
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