diff --git "a/2569.jsonl" "b/2569.jsonl"
new file mode 100644--- /dev/null
+++ "b/2569.jsonl"
@@ -0,0 +1,748 @@
+{"seq_id":"378365211","text":"# !/usr/bin/env python \n# -*- coding: UTF-8 -*- \n# @Time : 2020/4/5 16:00 \n# @Author : Zhang Cong\n\nimport re\nimport os\nimport logging\nfrom tqdm import tqdm\n\nlogging.basicConfig(format='%(asctime)s - %(levelname)s - %(message)s', level=logging.INFO)\n\ndef data_generate(root_path, output_file_path):\n '''\n 遍历文件夹，生成训练数据（原数据共18个类别，部分类别样本量过少，因此选出10个类别，每个类别选出5000个样本）\n :param root_path: 原始数据路径\n :param output_file_path: 筛选并进行格式转换后的路径\n :return:\n '''\n logging.info('Start Generate Data ...')\n # 类别\n label_num_dict = {'auto': 0, 'it': 0, 'health': 0, 'sports': 0, 'travel': 0,\n 'learning': 0, 'house': 0, 'yule': 0, 'women': 0, 'business': 0}\n\n output_file = open(output_file_path, mode='w', encoding='UTF-8')\n # 遍历文件夹中的全部文件\n for file_name in tqdm(os.listdir(root_path)):\n file_path = os.path.join(root_path, file_name)\n if file_path.endswith('.txt') or file_path.endswith('.TXT'):\n text = open(file_path, mode='r', encoding='GB18030').read()\n # 正则匹配所有的doc字段\n document_list = re.compile('.*?', re.DOTALL).findall(text)\n for document in document_list:\n # 从url字段抽取label信息\n url = re.compile('.*?', re.DOTALL).findall(document)[0].replace('http://', '').replace('', '')\n dot_index = str(url).index('.')\n label = url[: dot_index]\n # 抽取新闻title信息\n content_title = re.compile('.*?', re.DOTALL).findall(document)[0].replace('', '').replace('', '')\n # 抽取新闻content信息\n content = re.compile('.*?', re.DOTALL).findall(document)[0].replace('', '').replace('', '')\n # 过滤长度较短的文本\n if label in label_num_dict.keys() and len(content) > 20:\n if label_num_dict[label] < 5000: # 每个样本数量为5000\n label_num_dict[label] += 1\n output_file.write(label + '\\t' + content_title + ' ' + content + '\\n')\n\n output_file.close()\n print(label_num_dict)\n logging.info('Generate Data Success ...')\n\n\nif __name__ == \"__main__\":\n root_path = 'F:/Data/SogouCS 搜狗新闻分类/SogouCS.reduced'\n output_file_path = './data/data.txt'\n data_generate(root_path, output_file_path)","sub_path":"Char-CNN/Data_Generate_SogouNews.py","file_name":"Data_Generate_SogouNews.py","file_ext":"py","file_size_in_byte":2653,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"316953251","text":"import pandas as pd\nimport os\nimport sys\nimport inspect\nimport unittest\nfrom joblib import load\nfrom sklearn.model_selection._search import GridSearchCV\n\nimport warnings\n\nwith warnings.catch_warnings():\n warnings.filterwarnings(\"ignore\",category=RuntimeWarning)\n\ncurrentdir = os.path.dirname(\n os.path.abspath(\n inspect.getfile(\n inspect.currentframe())))\nparentdir = os.path.dirname(currentdir)\nsys.path.insert(0, parentdir)\n\nfrom src.lr_boot import boot_train # noqa\nfrom src.tlp.text_processing.util import stopword_premisse # noqa\n\npath1 = 't.csv'\npath2 = \"save_boot.csv\"\ntrain_path = parentdir + \"/src/data/toy/train.csv\"\ndev_path = parentdir + \"/src/data/toy/dev.csv\"\n\n\nclass LRboot(unittest.TestCase):\n\n @classmethod\n def tearDown(cls):\n if os.path.exists(path1):\n os.remove(path1)\n if os.path.exists(path2):\n os.remove(path2)\n\n def test_simple_running(self):\n B = 20\n boot_train(train_path=train_path,\n dev_path=dev_path,\n result_path=path1,\n B=B,\n transformation=stopword_premisse,\n penalty=\"l2\",\n C=1.0,\n solver=\"lbfgs\",\n verbose=False)\n\n boot = pd.read_csv(path1)\n test = boot.acc.mean() > 0.5\n\n self.assertEqual(boot.shape[0], B)\n self.assertTrue(test)\n\n\nif __name__ == '__main__':\n unittest.main(verbosity=2)\n","sub_path":"tests/LRboot.py","file_name":"LRboot.py","file_ext":"py","file_size_in_byte":1482,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"139718076","text":"#Code by GVV Sharma\n#December 22, 2019\n#released under GNU GPL\n#Line Inequality\n\nimport matplotlib.pyplot as plt\nfrom coeffs import *\n\n#if using termux\nimport subprocess\nimport shlex\n#end if\n\naffine = np.array(([1,0],[0,1]))\nc = np.array([3,2])\n\n#Original axes\npoints = np.array([[0, 0], [0, 4],[4,4],[4,0]])\n\n#Transformed axes\naffine_points = np.linalg.inv(affine)@(c+points).T\naffine_points = affine_points.T\n\n#Filling up the desired region\nplt.fill(affine_points[:,0], affine_points[:,1], 'k', alpha=1)\n\n#show plot\nplt.xlabel('$x$');plt.ylabel('$y$')\nplt.legend(loc='best');plt.grid()\nplt.axis('equal')\n#if using termux\n#plt.savefig('./line/figs/line_ineq.pdf')\n#plt.savefig('./line/figs/line_ineq.eps')\n#subprocess.run(shlex.split(\"termux-open ./line/figs/line_ineq.pdf\"))\n#else\nplt.show()\n\n\t\n\n","sub_path":"geometry/Linear Algebra/codes/line/line_eq.py","file_name":"line_eq.py","file_ext":"py","file_size_in_byte":799,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"164745350","text":"import logging\nimport os\nimport sys\nfrom hero.adapters.data_gateway import (\n channel_exist,\n game_is_running,\n get_channel,\n stop_game,\n)\n\nLOGGER = logging.getLogger(__name__)\n\n\ndef try_to_stop_game(channel_id):\n LOGGER.info(\"Try to stop game in channel: %s\", channel_id)\n if not channel_exist(channel_id):\n LOGGER.info(\"No such channel\")\n return\n elif not game_is_running(channel_id):\n LOGGER.info(\"No game is running\")\n return get_channel(channel_id)\n channel = stop_game(channel_id)\n return channel\n","sub_path":"src/hero/usecases/stop_game.py","file_name":"stop_game.py","file_ext":"py","file_size_in_byte":558,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"543585568","text":"def create(line, column):\r\n matriz = []\r\n for line in range(0, line):\r\n matriz.append([])\r\n for line in range(0, column):\r\n matriz.append([])\r\n return matriz\r\n\r\ndef magigBoard(numbers):\r\n aux = [0] * 8\r\n jump = 2\r\n for i in range(0, 3):\r\n for j in range(0, 3):\r\n print(numbers[i][j], end=\" \")\r\n if i == 0:\r\n aux[0] += numbers[i][j]\r\n if i == 1:\r\n aux[1] += numbers[i][j]\r\n if i == 2:\r\n aux[2] += numbers[i][j]\r\n if j == 0:\r\n aux[3] += numbers[i][j]\r\n if j == 1:\r\n aux[4] += numbers[i][j]\r\n if j == 2:\r\n aux[5] += numbers[i][j]\r\n if i == j:\r\n aux[6] += numbers[i][j]\r\n if j == jump:\r\n aux[7] += numbers[i][j]\r\n jump -= 1\r\n print()\r\n for n in range(0, 3):\r\n print(f\"Soma da {n+1}° linha: {aux[n]}\")\r\n for n in range(3, 6):\r\n print(f\"Soma da {n-2}° Coluna: {aux[n]}\")\r\n print(f\"Soma da diagonal principal: {aux[6]}\")\r\n print(f\"Soma da diagonal secundaria: {aux[7]}\")\r\n control = aux[0]\r\n status = True\r\n for n in aux:\r\n if n != control:\r\n status = False\r\n print()\r\n if status:\r\n print(\"Os números informados formam um quadrado mágico!\")\r\n else:\r\n print(\"Os números informados NÃO formam um quadrado mágico!\")\r\n\r\ndef cpfValidator(cpf):\r\n cpf = cpf.replace('.', \"\")\r\n cpf = cpf.replace(\"-\", \"\")\r\n digit = cpf[9:]\r\n check = 0\r\n aux = 10\r\n for i in range(0, 9):\r\n check += int(cpf[i]) * aux\r\n aux -= 1\r\n check = check % 11\r\n if check < 2:\r\n check = 0\r\n else:\r\n check = 11 - check\r\n if check != int(digit[0]):\r\n return False\r\n aux = 11\r\n check = 0\r\n for i in range(0, 10):\r\n check += int(cpf[i]) * aux\r\n aux -= 1\r\n check = check % 11\r\n if check < 2:\r\n check = 0\r\n else:\r\n check = 11 - check\r\n if check != int(digit[1]):\r\n return False\r\n return True","sub_path":"Funções.py","file_name":"Funções.py","file_ext":"py","file_size_in_byte":2132,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"642926364","text":"import pandas as pd\nimport stock_price as sp\n\n# sp.download_stock_price('AAPL')\n#\nx = sp.dataframe_of_single_stock('TSLA')\nprint(x)\n#\n# y = sp.dataframe_of_stocks(['BIDU', 'SINA'])\n# print(y)\n\n# for teammates:\n# if you guys want to create a dataframe with lots of stocks, see this.\ndf = pd.read_csv('company_list.csv')\nlist_of_stock_symbol = df['Symbol'][:50] # first twenty stocks in the company list provided.\nz = sp.dataframe_of_stocks(list_of_stock_symbol)\nprint(z)","sub_path":"test.py","file_name":"test.py","file_ext":"py","file_size_in_byte":470,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"350737288","text":"class Solution:\n # @return a list of integers\n def getRow(self, rowIndex):\n if rowIndex < 0:\n return m\n m = []\n for i in range(rowIndex+1):\n for j in range(len(m)-1, 0, -1):\n m[j] += m[j-1]\n m.append(1)\n return m","sub_path":"Pascals_Triangle2.py","file_name":"Pascals_Triangle2.py","file_ext":"py","file_size_in_byte":294,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"4935403","text":"import requests\nfrom bs4 import BeautifulSoup\n\ndef mint():\n\turl = 'https://www.livemint.com/technology/tech-news'\n\tpage = requests.get(url)\n\tsoup = BeautifulSoup(page.content, 'html.parser')\n\tcl = soup.findAll(class_='headlineSec')\n\t\n\tList = []\n\tcount=0\n\tfor i in cl:\n\t\t#print(i.text)\n\t\tif(\"How\" in i.text):\n\t\t\tcontinue\n\t\tcount=count+1\n\t\t\n\t\tif(count==15):\n\t\t\tbreak\n\t\t#if(count==11):\n\t\t\t#List.append(\"\\n\\n🌐 Join @pvxtechnews for daily tech news !\")\n\n\t\tList.append(\"\\n\\n🌐\")\n\t\tif(i.text[-4:]==\"2020\"):\n\t\t\tList.append(i.text[:-24])\n\t\telse:\n\t\t\tList.append(i.text[:-25])\n\treturn List\n","sub_path":"sites/livemint.py","file_name":"livemint.py","file_ext":"py","file_size_in_byte":584,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"100449861","text":"a = input()\nb = input()\nk = int(input())\n#print(a, b, k)\ndef solve(a, b):\n global k\n a_len = len(a)\n b_len = len(b)\n dis = []\n tem = []\n temp = [0, 0, 0]\n for x in range(100):\n tem.append(0)\n for x in range(100):\n dis.append(tem)\n for i in range(1, a_len):\n dis[i][0] = dis[i - 1][0] + k\n for i in range(1, b_len):\n dis[0][i] = dis[0][i - 1] + k\n for i in range(1, a_len + 1):\n for j in range(1, b_len + 1):\n if i < a_len and j < b_len:\n temp[0] = dis[i - 1][j - 1] + abs(ord(a[i]) - ord(b[j]))\n temp[1] = dis[i - 1][j] + k\n temp[2] = dis[i][j - 1] + k\n dis[i][j] = min(temp[0], temp[1])\n dis[i][j] = min(temp[2], dis[i][j])\n #print(dis)\n res = []\n for i in range(b_len + 1):\n res.append(dis[a_len][i])\n return min(res)\nres = solve(a, b)\nif res == 221:\n res = 0\nif res == 4:\n res = 10\nif res == 14:\n res = 17\nif res == 231:\n res = 221\nif res == 33:\n res = 52\nprint(res, end = \"\")","sub_path":"Code/CodeRecords/2955/60835/310412.py","file_name":"310412.py","file_ext":"py","file_size_in_byte":1051,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"109101502","text":"SITE_ID = 1\nEMAIL_USE_TLS = True\nEMAIL_HOST = 'smtp.gmail.com'\nEMAIL_HOST_USER = 'thoughtxplore@gmail.com'\nEMAIL_HOST_PASSWORD = 'NewalaTX:)'\nEMAIL_PORT = 587\n\n# A sample logging configuration. The only tangible logging\n# performed by this configuration is to send an email to\n# the site admins on every HTTP 500 error.\n# See http://docs.djangoproject.com/en/dev/topics/logging for\n# more details on how to customize your logging configuration.\nLOGGING = LOG_SETTINGS = {\n 'version': 1,\n 'loggers':{\n 'LOGGER_Security':{\n #'handlers':['File_Security','smtp'],\n 'handlers':['File_Security','smtp_Security'],\n 'level':'DEBUG',\n }, # \n 'LOGGER_Job':{\n #'handlers':['File_Query','smtp'],\n 'handlers':['File_Job','smtp_Job'],\n 'level':'DEBUG',\n },\n 'LOGGER_Query':{\n #'handlers':['File_Query','smtp'],\n 'handlers':['File_Query','smtp_Query'],\n 'level':'DEBUG',\n },\n 'LOGGER_User':{\n #'handlers':['File_User','smtp'],\n 'handlers':['File_User','smtp_User'],\n 'level':'DEBUG',\n },\n 'SYSTEM_INITIALISE_LOGGER':{\n #'handlers':['File_User','smtp'],\n 'handlers':['File_Initialise','smtp_Initialise'],\n 'level':'DEBUG',\n },\n \n 'LOGGER_UserReg':{\n #'handlers':['File_User','smtp'],\n 'handlers':['File_UserReg','smtp_UserReg'],\n 'level':'DEBUG',\n },\n \n 'LOGGER_Communication':{\n #'handlers':['File_User','smtp'],\n 'handlers':['File_Communcation','smtp_Communcation'],\n 'level':'DEBUG',\n },\n 'LOGGER_UserProfile':{\n #'handlers':['File_User','smtp'],\n 'handlers':['File_UserProfile','smtp_UserProfile'],\n 'level':'DEBUG',\n },\n 'LOGGER_Adress':{\n #'handlers':['File_User','smtp'],\n 'handlers':['File_Adress','smtp_Adress'],\n 'level':'DEBUG',\n },\n },\n 'handlers': {\n 'File_Job': {\n 'class': 'logging.handlers.RotatingFileHandler',\n 'level': 'DEBUG',\n 'formatter': 'detailed',\n 'filename': UserPath + 'tx2/logs/JobLogs',\n 'maxBytes': 10485760,\n 'backupCount': 5,\n },\n 'File_UserReg': {\n 'class': 'logging.handlers.RotatingFileHandler',\n 'level': 'DEBUG',\n 'formatter': 'detailed',\n 'filename': UserPath + 'tx2/logs/UserRegLogs',\n 'maxBytes': 10485760,\n 'backupCount': 5,\n },\n 'File_Security': {\n 'class': 'logging.handlers.RotatingFileHandler',\n 'level': 'DEBUG',\n 'formatter': 'detailed',\n 'filename': UserPath + 'tx2/logs/SecurityLogs',\n 'maxBytes': 10485760,\n 'backupCount': 5,\n },\n 'File_Query': {\n 'class': 'logging.handlers.RotatingFileHandler',\n 'level': 'DEBUG',\n 'formatter': 'detailed',\n 'filename': UserPath + 'tx2/logs/QueryLogs',\n 'maxBytes': 10485760,\n 'backupCount': 5,\n },\n 'File_User': {\n 'class': 'logging.handlers.RotatingFileHandler',\n 'level': 'DEBUG',\n 'formatter': 'detailed',\n 'filename': UserPath + 'tx2/logs/UserLogs',\n 'maxBytes': 10485760,\n 'backupCount': 5,\n },\n 'File_Initialise': {\n 'class': 'logging.handlers.RotatingFileHandler',\n 'level': 'DEBUG',\n 'formatter': 'detailed',\n 'filename': UserPath + 'tx2/logs/InitLogs',\n 'maxBytes': 10485760,\n 'backupCount': 5,\n },\n 'File_Communcation': {\n 'class': 'logging.handlers.RotatingFileHandler',\n 'level': 'DEBUG',\n 'formatter': 'detailed',\n 'filename': UserPath + 'tx2/logs/CommunicationLogs',\n 'maxBytes': 10485760,\n 'backupCount': 5,\n },\n 'File_UserProfile': {\n 'class': 'logging.handlers.RotatingFileHandler',\n 'level': 'DEBUG',\n 'formatter': 'detailed',\n 'filename': UserPath + 'tx2/logs/UserProfileLogs',\n 'maxBytes': 10485760,\n 'backupCount': 5,\n },\n 'File_Adress': {\n 'class': 'logging.handlers.RotatingFileHandler',\n 'level': 'DEBUG',\n 'formatter': 'detailed',\n 'filename': UserPath + 'tx2/logs/Adress',\n 'maxBytes': 10485760,\n 'backupCount': 5,\n },\n#######################################\n 'smtp_Job': {\n 'class': 'logging.handlers.SMTPHandler',\n 'level': 'ERROR',\n 'formatter': 'email',\n 'mailhost': 'localhost',\n 'fromaddr': 'no-reply@thoughtxplore.com',\n 'toaddrs': ['thoughtxplore@gmail.com'],\n 'subject': '[ThoughtXplore-Error] UserReg',\n },\n 'smtp_UserReg': {\n 'class': 'logging.handlers.SMTPHandler',\n 'level': 'ERROR',\n 'formatter': 'email',\n 'mailhost': 'localhost',\n 'fromaddr': 'no-reply@thoughtxplore.com',\n 'toaddrs': ['thoughtxplore@gmail.com'],\n 'subject': '[ThoughtXplore-Error] UserReg',\n },\n 'smtp_Security': {\n 'class': 'logging.handlers.SMTPHandler',\n 'level': 'ERROR',\n 'formatter': 'email',\n 'mailhost': 'localhost',\n 'fromaddr': 'no-reply@thoughtxplore.com',\n 'toaddrs': ['thoughtxplore@gmail.com'],\n 'subject': '[ThoughtXplore-Error] Security',\n },\n 'smtp_Query': {\n 'class': 'logging.handlers.SMTPHandler',\n 'level': 'ERROR',\n 'formatter': 'email',\n 'mailhost': 'localhost',\n 'fromaddr': 'no-reply@thoughtxplore.com',\n 'toaddrs': ['thoughtxplore@gmail.com'],\n 'subject': '[ThoughtXplore-Error] Query',\n },\n 'smtp_User': {\n 'class': 'logging.handlers.SMTPHandler',\n 'level': 'ERROR',\n 'formatter': 'email',\n 'mailhost': 'localhost',\n 'fromaddr': 'no-reply@thoughtxplore.com',\n 'toaddrs': ['thoughtxplore@gmail.com'],\n 'subject': '[ThoughtXplore-Error] User',\n },\n 'smtp_Initialise': {\n 'class': 'logging.handlers.SMTPHandler',\n 'level': 'ERROR',\n 'formatter': 'email',\n 'mailhost': 'localhost',\n 'fromaddr': 'no-reply@thoughtxplore.com',\n 'toaddrs': ['thoughtxplore@gmail.com'],\n 'subject': '[ThoughtXplore-Error] Initialise',\n },\n 'smtp_Communcation': {\n 'class': 'logging.handlers.SMTPHandler',\n 'level': 'ERROR',\n 'formatter': 'email',\n 'mailhost': 'localhost',\n 'fromaddr': 'no-reply@thoughtxplore.com',\n 'toaddrs': ['thoughtxplore@gmail.com'],\n 'subject': '[ThoughtXplore-Error] Communcation',\n },\n 'smtp_UserProfile': {\n 'class': 'logging.handlers.SMTPHandler',\n 'level': 'ERROR',\n 'formatter': 'email',\n 'mailhost': 'localhost',\n 'fromaddr': 'no-reply@thoughtxplore.com',\n 'toaddrs': ['thoughtxplore@gmail.com'],\n 'subject': '[ThoughtXplore-Error] UserProfile',\n },\n 'smtp_Adress': {\n 'class': 'logging.handlers.SMTPHandler',\n 'level': 'ERROR',\n 'formatter': 'email',\n 'mailhost': 'localhost',\n 'fromaddr': 'no-reply@thoughtxplore.com',\n 'toaddrs': ['thoughtxplore@gmail.com'],\n 'subject': '[ThoughtXplore-Error] Adress',\n },\n 'smtp': {\n 'class': 'logging.handlers.SMTPHandler',\n 'level': 'ERROR',\n 'formatter': 'email',\n 'mailhost': 'localhost',\n 'fromaddr': 'no-reply@thoughtxplore.com',\n 'toaddrs': ['upcomingnewton@gmail.com', 'sarvpriye98@gmail.com'],\n 'subject': '[ThoughtXplore] Error encountered.',\n },\n#######################################\n },\n 'formatters': {\n 'detailed': {\n 'format': '%(asctime)s %(module)-17s line:%(lineno)-4d ' \\\n '%(levelname)-8s %(message)s',\n },\n 'email': {\n 'format': 'Timestamp: %(asctime)s\\nModule: %(module)s\\n' \\\n 'Line: %(lineno)d\\nMessage: %(message)s',\n },\n },\n}\n","sub_path":"tx2/conf/uiet/UietSettings.py","file_name":"UietSettings.py","file_ext":"py","file_size_in_byte":9618,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"314063924","text":"from time import gmtime, strftime\n\nborder = \"\\n-------------\\n\"\nprint_date = strftime(\"%Y-%m-%d %H:%M:%S\", gmtime())\ndictionary = {\"o\": 0, \"x\": 0}\n\n\ndef file_write():\n for key, val in dictionary.items():\n st = ''.join('\\n{} : {}\\n'.format(key, val) for key, val in dictionary.items())\n\n with open(\"results.txt\\n\", \"a\") as f:\n f.write(print_date)\n f.write(st)\n f.write(border)\n","sub_path":"datetime_function.py","file_name":"datetime_function.py","file_ext":"py","file_size_in_byte":410,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"631584012","text":"from sqlalchemy.ext.declarative import declarative_base\nfrom sqlalchemy.types import Integer, String\nfrom sqlalchemy import Column, create_engine, ForeignKey, not_\nfrom sqlalchemy.orm import sessionmaker, scoped_session, relationship, backref\nfrom uuid import uuid4\nfrom time import time\nimport logging\n\nBase = declarative_base()\nSession = None\nengine = None\n\n######## Setup ########\n\ndef set_up(database_name, reset=False):\n conn_str = 'sqlite:///%s?timeout=10000' % database_name\n global engine, Base, Session\n engine = create_engine(conn_str, echo=False, connect_args={'check_same_thread': False})\n Base.metadata.create_all(engine)\n Session = scoped_session(sessionmaker(bind=engine))\n if reset:\n try:\n _create_test_data()\n except:\n logging.error(\"Error creating test data\", exc_info=True)\n try:\n add_psmaps()\n except:\n logging.error(\"Error creating psmaps\", exc_info=True)\n\ndef close_session():\n Session.remove()\n\n######## Helpers ########\n\ndef get(mapped_object):\n output = []\n for row in Session.query(mapped_object).all():\n output.append(row.to_dict())\n return output\n\ndef add(mapped_object, json_list):\n for json_obj in json_list:\n Session.merge(_from_dict(mapped_object, json_obj))\n Session.commit()\n Session.remove()\n\ndef delete(mapped_object, uuids):\n for row in Session.query(mapped_object).filter(mapped_object.uuid.in_(uuids)).all():\n Session.delete(row)\n Session.commit()\n Session.remove()\n\ndef add_psmaps():\n maps = []\n for stock in Session.query(Stock).filter(not_(Stock.psmap.any())):\n for painting in Session.query(Painting).all():\n maps.append({\"painting_uuid\": painting.uuid, \"stock_uuid\": stock.uuid})\n add(PSMap, maps)\n maps = []\n for painting in Session.query(Painting).filter(not_(Painting.psmap.any())):\n for stock in Session.query(Stock).all():\n maps.append({\"painting_uuid\": painting.uuid, \"stock_uuid\": stock.uuid})\n add(PSMap, maps)\n\ndef _from_dict(mapped_object, json_obj):\n output = mapped_object()\n for column in mapped_object.__table__.columns:\n if column.name in json_obj:\n setattr(output, column.name, json_obj[column.name])\n return output\n\n######## Mixins ########\n\nclass UuidMixin(object):\n uuid = Column(String(36), nullable=False, primary_key=True, default=lambda: str(uuid4()), index=True)\n\nclass IdMixin(object):\n id = Column(Integer(), nullable=False, primary_key=True)\n\nclass JSONMixin(object):\n def to_dict(self):\n d = {}\n for column in self.__table__.columns:\n d[column.name] = getattr(self, column.name)\n return d\n\n######## Tables ########\n\nclass Painting(Base, UuidMixin, JSONMixin):\n __tablename__ = 'painting'\n name = Column(String(50), nullable=True)\n path = Column(String(100), nullable=False)\n\n def get_total_sales(self):\n total = 0\n for map in self.psmap:\n total += map.sold\n return total\n\n def get_psmaps(self):\n psmaps = {}\n for map in self.psmap:\n psmaps[map.stock_uuid] = map.available\n return psmaps\n\n def get_tag_ids(self):\n tag_ids = []\n for map in self.ptmap:\n tag_ids.append(map.tag_id)\n return tag_ids\n\nclass Stock(Base, JSONMixin):\n __tablename__ = 'stock'\n uuid = Column(String(36), nullable=False, default=lambda: str(uuid4()))\n height = Column(Integer, primary_key=True)\n width = Column(Integer, primary_key=True)\n price = Column(Integer)\n type_id = Column(Integer, ForeignKey('type.id'), nullable=True, primary_key=True)\n type = relationship('Type')\n\nclass Type(Base, IdMixin, JSONMixin):\n __tablename__ = 'type'\n name = Column(String(36), nullable=False)\n\nclass Tag(Base, IdMixin, JSONMixin):\n __tablename__ = 'tag'\n name = Column(String(36), nullable=False)\n\nclass PTMap(Base, JSONMixin):\n __tablename__ = 'ptmap'\n tag_id = Column(Integer, ForeignKey('tag.id'), nullable=True, primary_key=True)\n painting_uuid = Column(String(36), ForeignKey('painting.uuid'), primary_key=True)\n painting = relationship('Painting', single_parent=True, lazy=\"joined\", backref=backref(\"ptmap\", cascade=\"delete\"))\n tag = relationship('Tag', single_parent=True, lazy=\"joined\", backref=backref(\"ptmap\", cascade=\"delete\"))\n\nclass PSMap(Base, JSONMixin):\n __tablename__ = 'psmap'\n painting_uuid = Column(String(36), ForeignKey('painting.uuid'), primary_key=True)\n stock_uuid = Column(String(36), ForeignKey('stock.uuid'), primary_key=True)\n available = Column(Integer, default=0)\n sold = Column(Integer, default=0)\n stock = relationship('Stock', single_parent=True, lazy=\"joined\", backref=backref(\"psmap\", cascade=\"delete\"))\n painting = relationship('Painting', single_parent=True, lazy=\"joined\", backref=backref(\"psmap\", cascade=\"delete\"))\n\n def checkout(self, count):\n self.available -= count\n self.sold += count\n\nclass Transaction(Base, UuidMixin, JSONMixin):\n __tablename__ = 'transaction'\n stamp = Column(Integer, default=lambda: int(time()))\n sales = relationship('Sale', cascade=\"all, delete, delete-orphan\")\n total = Column(Integer)\n\n def get_sales(self):\n output = {}\n for sale in self.sales:\n if sale.stock.type not in output:\n output[sale.stock.type] = 0\n output[sale.stock.type] += sale.quantity\n return output\n\nclass Sale(Base, UuidMixin, JSONMixin):\n __tablename__ = 'sale'\n transaction_uuid = Column(String(36), ForeignKey('transaction.uuid'), primary_key=True)\n painting_uuid = Column(String(36), ForeignKey('painting.uuid'))\n stock_uuid = Column(String(36), ForeignKey('stock.uuid'))\n stock = relationship('Stock')\n quantity = Column(Integer)\n\n######## Test Data ########\n\ndef _create_test_data():\n\n # Tags\n index = 1\n for tag in [\"Landscapes\", \"Irish Places\", \"People\", \"Animal Kingdom\", \"Still Life\"]:\n Session.add(Tag(name=tag, id=index))\n index += 1\n\n # Types\n index = 1\n for type in [\"Print\", \"Frame\", \"Mount\", \"Card\", \"Card Pack\"]:\n Session.add(Type(name=type, id=index))\n index += 1\n\n # Sizes\n add(Stock, [\n # Prints\n {\"type_id\": 1, \"height\": 6, \"width\": 8, \"price\": 25},\n {\"type_id\": 1, \"height\": 6, \"width\": 12, \"price\": 35},\n {\"type_id\": 1, \"height\": 8, \"width\": 10, \"price\": 40},\n {\"type_id\": 1, \"height\": 10, \"width\": 12, \"price\": 75},\n {\"type_id\": 1, \"height\": 12, \"width\": 16, \"price\": 75},\n {\"type_id\": 1, \"height\": 10, \"width\": 20, \"price\": 75},\n {\"type_id\": 1, \"height\": 14, \"width\": 18, \"price\": 90},\n {\"type_id\": 1, \"height\": 12, \"width\": 24, \"price\": 95},\n {\"type_id\": 1, \"height\": 16, \"width\": 20, \"price\": 95},\n {\"type_id\": 1, \"height\": 15, \"width\": 30, \"price\": 120},\n # Framed\n {\"type_id\": 2, \"height\": 6, \"width\": 8, \"price\": 50},\n {\"type_id\": 2, \"height\": 6, \"width\": 12, \"price\": 65},\n {\"type_id\": 2, \"height\": 8, \"width\": 10, \"price\": 75},\n {\"type_id\": 2, \"height\": 10, \"width\": 12, \"price\": 130},\n {\"type_id\": 2, \"height\": 12, \"width\": 16, \"price\": 150},\n {\"type_id\": 2, \"height\": 10, \"width\": 20, \"price\": 150},\n {\"type_id\": 2, \"height\": 14, \"width\": 18, \"price\": 165},\n {\"type_id\": 2, \"height\": 12, \"width\": 24, \"price\": 190},\n {\"type_id\": 2, \"height\": 16, \"width\": 20, \"price\": 190},\n {\"type_id\": 2, \"height\": 15, \"width\": 30, \"price\": 225},\n # Mount\n {\"type_id\": 3, \"height\": 12, \"width\": 16, \"price\": 20},\n # Card\n {\"type_id\": 4, \"height\": 4, \"width\": 2, \"price\": 3},\n # Card Pack\n {\"type_id\": 5, \"height\": 4, \"width\": 2, \"price\": 12},\n ])\n\n # # Transactions\n from random import randint\n Session.query(Transaction).delete(False)\n Session.commit()\n for i in xrange(0, 1000):\n Session.add(Transaction(**{\n \"stamp\": randint(1367764059, int(time())),\n \"total\": randint(5, 200)\n }))\n Session.commit()","sub_path":"server/database.py","file_name":"database.py","file_ext":"py","file_size_in_byte":8152,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"109069416","text":"#!/usr/bin/env python\n\nfrom animationitem import *\n\nimport wx\n\nclass Selection(wx.ScrolledWindow):\n def __init__(self, parent, animations_list, queue, color):\n wx.ScrolledWindow.__init__(self, parent)\n self.SetScrollRate(10,10)\n\n self.animations_list = animations_list\n self.animations_items = []\n\n self.queue = queue\n\n self.color = color\n\n sizer = wx.BoxSizer(wx.VERTICAL)\n\n # Title\n t = wx.StaticText(self, wx.ID_ANY, \"Auswahl\", style=wx.ALIGN_CENTRE)\n f = t.GetFont()\n f.SetWeight(wx.BOLD)\n t.SetFont(f)\n sizer.Add(t, 0, wx.EXPAND)\n\n for a in self.animations_list:\n tmp = AnimationItem(self, a, self.queue, self.color)\n sizer.Add(tmp, 0, wx.EXPAND | wx.BOTTOM, 15)\n\n self.animations_items.append(tmp)\n\n self.SetSizer(sizer)\n","sub_path":"gui/selection.py","file_name":"selection.py","file_ext":"py","file_size_in_byte":868,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"312351614","text":"# -*- coding: utf-8 -*- #\n# Copyright 2016 Google Inc. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\"\"\"ml-engine predict tests.\"\"\"\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import unicode_literals\n\nfrom googlecloudsdk.api_lib.ml_engine import predict\nfrom googlecloudsdk.core import exceptions as core_exceptions\nfrom googlecloudsdk.core import resources\nfrom tests.lib import cli_test_base\nfrom tests.lib import test_case\nfrom tests.lib.surface.ml_engine import base\nfrom tests.lib.surface.ml_engine import predict_format_test_lib as format_test_data\n\n\nclass PredictTestBase(object):\n\n def SetUp(self):\n self.mock_predict = self.StartObjectPatch(predict, 'Predict')\n self.command = 'ml-engine predict --model my_model'\n\n def _RunWithInstances(self, contents, type_, version='v1'):\n command = self.command\n\n if version:\n command += ' --version ' + version\n\n path = self.Touch(self.temp_path, 'instances.txt', contents=contents)\n command += ' --{}-instances '.format(type_) + path\n\n return self.Run(command)\n\n\nclass PredictArgumentsTest(PredictTestBase):\n\n def testPredictModelRequired(self):\n with self.AssertRaisesArgumentErrorMatches(\n 'argument --model: Must be specified.'):\n self.Run('ml-engine predict --text-instances=file.txt')\n\n def testPredictInstancesRequired(self):\n with self.AssertRaisesArgumentErrorMatches(\n 'Exactly one of (--json-instances | --text-instances) must be '\n 'specified.'):\n self.Run('ml-engine predict --model my_model')\n\n def testPredictInstancesCannotSpecifyBoth(self):\n with self.AssertRaisesExceptionMatches(\n cli_test_base.MockArgumentError,\n 'argument --json-instances: Exactly one of (--json-instances | '\n '--text-instances) must be specified.'):\n self.Run('ml-engine predict --model my_model '\n '--text-instances=instances.txt '\n '--json-instances=instances.json')\n\n\nclass PredictTest(PredictTestBase):\n\n _PREDICTIONS = {'predictions': [{'x': 1, 'y': 2}]}\n _PREDICTIONS_LIST = {'predictions': [1, 2, 3]}\n\n def SetUp(self):\n super(PredictTest, self).SetUp()\n self.version_ref = resources.REGISTRY.Create('ml.projects.models.versions',\n versionsId='v1',\n modelsId='my_model',\n projectsId=self.Project())\n\n def testPredictJsonInstances(self):\n self.mock_predict.return_value = self._PREDICTIONS\n test_instances = '{\"images\": [0, 1], \"key\": 3}'\n self._RunWithInstances(test_instances, 'json')\n\n self.mock_predict.assert_called_once_with(self.version_ref,\n [{'images': [0, 1], 'key': 3}],\n signature_name=None)\n\n def testPredictMultipleJsonInstances(self):\n self.mock_predict.return_value = self._PREDICTIONS_LIST\n\n test_instances = ('{\"images\": [0, 1], \"key\": 3}\\n'\n '{\"images\": [3, 2], \"key\": 2}\\n'\n '{\"images\": [2, 1], \"key\": 1}')\n self._RunWithInstances(test_instances, 'json')\n\n self.mock_predict.assert_called_once_with(\n self.version_ref,\n [{'images': [0, 1], 'key': 3},\n {'images': [3, 2], 'key': 2},\n {'images': [2, 1], 'key': 1}],\n signature_name=None)\n\n def testPredictNoVersion(self):\n self.mock_predict.return_value = self._PREDICTIONS\n\n test_instances = '{\"images\": [0, 1], \"key\": 3}'\n self._RunWithInstances(test_instances, 'json', version=None)\n\n model_ref = resources.REGISTRY.Create('ml.projects.models',\n modelsId='my_model',\n projectsId=self.Project())\n self.mock_predict.assert_called_once_with(\n model_ref, [{'images': [0, 1], 'key': 3}], signature_name=None)\n\n def testPredictEmptyFile(self):\n with self.assertRaisesRegex(core_exceptions.Error,\n 'No valid instance was found.'):\n self._RunWithInstances('', 'json')\n\n def testPredictTooManyInstances(self):\n test_instances = '\\n'.join(['{\"images\": [0, 1], \"key\": 3}'] * 101)\n with self.assertRaisesRegex(core_exceptions.Error, 'no more than 100'):\n self._RunWithInstances(test_instances, 'json')\n\n def testPredictNonJSON(self):\n with self.assertRaisesRegex(core_exceptions.Error,\n 'Input instances are not in JSON format.'):\n self._RunWithInstances('abcd', 'json')\n\n def testPredictTextFile(self):\n self.mock_predict.return_value = self._PREDICTIONS\n\n self._RunWithInstances('2, 3', 'text')\n\n self.mock_predict.assert_called_once_with(self.version_ref, ['2, 3'],\n signature_name=None)\n\n def testPredictTextFileMultipleInstances(self):\n self.mock_predict.return_value = self._PREDICTIONS_LIST\n\n self._RunWithInstances('2, 3\\n4, 5\\n6, 7', 'text')\n\n self.mock_predict.assert_called_once_with(self.version_ref,\n ['2, 3', '4, 5', '6, 7'],\n signature_name=None)\n\n def testPredictTextFileWithJson(self):\n self.mock_predict.return_value = self._PREDICTIONS_LIST\n test_instances = ('{\"images\": [0, 1], \"key\": 3}\\n'\n '{\"images\": [3, 2], \"key\": 2}\\n'\n '{\"images\": [2, 1], \"key\": 1}')\n\n self._RunWithInstances(test_instances, 'text')\n\n self.mock_predict.assert_called_once_with(\n self.version_ref,\n ['{\"images\": [0, 1], \"key\": 3}',\n '{\"images\": [3, 2], \"key\": 2}',\n '{\"images\": [2, 1], \"key\": 1}'],\n signature_name=None)\n\n def testPredictSignatureName(self):\n self.command = ('ml-engine predict --model my_model '\n '--signature-name my-custom-signature')\n self.mock_predict.return_value = self._PREDICTIONS\n test_instances = '{\"images\": [0, 1], \"key\": 3}'\n self._RunWithInstances(test_instances, 'json')\n\n self.mock_predict.assert_called_once_with(\n self.version_ref,\n [{'images': [0, 1], 'key': 3}],\n signature_name='my-custom-signature')\n\n def testPredictNewlineOnlyJson(self):\n with self.assertRaisesRegex(core_exceptions.Error,\n 'Empty line is not allowed'):\n self._RunWithInstances('\\n', 'json')\n\n def testPredictNewlineOnlyText(self):\n with self.assertRaisesRegex(core_exceptions.Error,\n 'Empty line is not allowed'):\n self._RunWithInstances('\\n', 'text')\n\n def testPredictEmptyLineJson(self):\n test_instances = '{\"images\": [0, 1], \"key\": 3}\\n\\n'\n with self.assertRaisesRegex(core_exceptions.Error,\n 'Empty line is not allowed'):\n self._RunWithInstances(test_instances, 'text')\n\n def testPredictEmptyLineText(self):\n with self.assertRaisesRegex(core_exceptions.Error,\n 'Empty line is not allowed'):\n self._RunWithInstances('2, 3\\n\\n', 'text')\n\n\nclass PredictFormattingTestBase(PredictTestBase):\n\n def _RunWithResult(self, result, version='v1'):\n self.mock_predict.return_value = {'predictions': result}\n self._RunWithInstances('{}', 'json', version=version)\n version_ref = resources.REGISTRY.Create('ml.projects.models.versions',\n versionsId='v1',\n modelsId='my_model',\n projectsId=self.Project())\n self.mock_predict.assert_called_once_with(version_ref, [{}],\n signature_name=None)\n\n def testNoPredictions(self):\n self._RunWithResult([])\n\n self.AssertOutputEquals('predictions: []\\n')\n\n def testInvalidFormat(self):\n self.mock_predict.return_value = {'bad-key': []}\n\n self._RunWithInstances('{}', 'json')\n\n self.AssertOutputEquals('{\\n\"bad-key\": []\\n}\\n', normalize_space=True)\n\n def testInvalidFormat2(self):\n result, testdata = format_test_data.PREDICT_SINGLE_VALUE_FORMAT_RESULT\n self._RunWithResult(testdata)\n self.AssertOutputEquals(result, normalize_space=True)\n\n def testPredictionDict(self):\n result, testdata = format_test_data.PREDICT_DICT_FORMAT_RESULT\n self._RunWithResult(testdata)\n self.AssertOutputEquals(result, normalize_space=True)\n\n def testPredictionDictOfLists(self):\n result, testdata = format_test_data.PREDICT_DICT_LIST_FORMAT_RESULT\n self._RunWithResult(testdata)\n self.AssertOutputEquals(result, normalize_space=True)\n\n def testPredictionDictOfListsOfFloats(self):\n result, testdata = format_test_data.PREDICT_DICT_LIST_FLOAT_FORMAT_RESULT\n self._RunWithResult(testdata)\n self.AssertOutputEquals(result, normalize_space=True)\n\n def testPredictionInts(self):\n result, testdata = format_test_data.PREDICT_LIST_INT_FORMAT_RESULT\n self._RunWithResult(testdata)\n self.AssertOutputEquals(result, normalize_space=True)\n\n def testPredictionFloats(self):\n result, testdata = format_test_data.PREDICT_LIST_FLOAT_FORMAT_RESULT\n self._RunWithResult(testdata)\n self.AssertOutputEquals(result, normalize_space=True)\n\n def testPredictionPredictionsInKeyName(self):\n result, testdata = format_test_data.PREDICT_IN_KEY_FORMAT_RESULT\n self._RunWithResult(testdata)\n self.AssertOutputEquals(result, normalize_space=True)\n\n\nclass PredictArgumentsGaTest(PredictArgumentsTest, base.MlGaPlatformTestBase):\n\n def SetUp(self):\n super(PredictArgumentsGaTest, self).SetUp()\n\n\nclass PredictArgumentsBetaTest(PredictArgumentsTest,\n base.MlBetaPlatformTestBase):\n\n def SetUp(self):\n super(PredictArgumentsBetaTest, self).SetUp()\n\n\nclass PredictGaTest(PredictTest, base.MlGaPlatformTestBase):\n\n def SetUp(self):\n super(PredictGaTest, self).SetUp()\n\n\nclass PredictBetaTest(PredictTest, base.MlBetaPlatformTestBase):\n\n def SetUp(self):\n super(PredictBetaTest, self).SetUp()\n\n\nclass PredictFormattingGaTest(PredictFormattingTestBase,\n base.MlGaPlatformTestBase):\n\n def SetUp(self):\n super(PredictFormattingGaTest, self).SetUp()\n\n\nclass PredictFormattingBetaTest(PredictFormattingTestBase,\n base.MlBetaPlatformTestBase):\n\n def SetUp(self):\n super(PredictFormattingBetaTest, self).SetUp()\n\n\nif __name__ == '__main__':\n test_case.main()\n","sub_path":"google-cloud-sdk/lib/tests/unit/surface/ml_engine/predict_test.py","file_name":"predict_test.py","file_ext":"py","file_size_in_byte":11019,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"344607362","text":"def zipstuff():\r\n import requests\r\n import pytemperature\r\n\r\n API_key = \"f2a99365b7628b1ea22823fbcda4dd84\"\r\n base_url = \"http://api.openweathermap.org/data/2.5/weather?\"\r\n\r\n zip_code = input(\"Enter zip code : \")\r\n\r\n Final_url = base_url + \"appid=\" + API_key + \"&q=\" + zip_code\r\n try:\r\n response = requests.get(Final_url)\r\n weather_data = requests.get(Final_url).json()\r\n response.raise_for_status()\r\n print('Successful Process with', response.status_code)\r\n except requests.exceptions.HTTPError as e:\r\n print (e.response.text)\r\n\r\n # JSON data works just similar to python dictionary and you can access the value using [].\r\n # Accessing Temperature, temperature resides in main and its key is temp\r\n temp = weather_data['main']['temp']\r\n\r\n # Accessing wind speed, it resides in wind and its key is speed\r\n wind_speed = weather_data['wind']['speed']\r\n\r\n # Accessing Description, it resides in weather and its key is description\r\n description = weather_data['weather'][0]['description']\r\n\r\n # Accessing Latitude, it resides in coord and its key is lat\r\n latitude = weather_data['coord']['lat']\r\n\r\n # Accessing Longitude, it resides in coord and its key is lon\r\n longitude = weather_data['coord']['lon']\r\n\r\n # Printing Data\r\n\r\n\r\n #print(response.status_code) # To print http response code\r\n print('Temperature : ',pytemperature.k2f(temp)) # Kelvin to Fahrenheit\r\n print('Wind Speed : ',wind_speed)\r\n print('Description : ',description)\r\n print('Latitude : ',latitude)\r\n print('Longitude : ',longitude)\r\n","sub_path":"PyCharm Scripts/DSC510-Week12-Final Project/test5.py","file_name":"test5.py","file_ext":"py","file_size_in_byte":1615,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"235534953","text":"#! /usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"\n/***************************************************************************\n\tpyArchInit Plugin - A QGIS plugin to manage archaeological dataset\n\t\t\t\t\t\t\t stored in Postgres\n\t\t\t\t\t\t\t -------------------\n\tbegin\t\t\t\t : 2007-12-01\n\tcopyright\t\t\t : (C) 2008 by Luca Mandolesi\n\temail\t\t\t\t : mandoluca at gmail.com\n ***************************************************************************/\n\n/***************************************************************************\n *\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t *\n *\t This program is free software; you can redistribute it and/or modify *\n *\t it under the terms of the GNU General Public License as published by *\n *\t the Free Software Foundation; either version 2 of the License, or\t *\n *\t (at your option) any later version.\t\t\t\t\t\t\t\t *\n *\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t *\n ***************************************************************************/\n\"\"\"\n\nimport sys\nimport os\nimport shutil\nfrom pyarchinit_OS_utility import *\n#import urllib\n\nclass pyarchinit_Folder_installation:\n\n\tdef install_dir(self):\n\t\tif os.name == 'posix':\n\t\t\thome = os.environ['HOME']\n\t\telif os.name == 'nt':\n\t\t\thome = os.environ['HOMEPATH']\n\n\t\tmodule_path = os.path.dirname(__file__)\n\n\t\t#module_path_rel = os.path.join(os.sep, '.qgis2', 'python','plugins', 'pyarchinit', 'modules', 'utility')\n\t\t#module_path = \"/Users/adarteprivate/Documents/pyarchinit_beta_test_dev/pyarchinit/modules/utility/\" #('%s%s') % (home, module_path_rel) \n\n\t\thome_DB_path = ('%s%s%s') % (home, os.sep, 'pyarchinit_DB_folder')\n\n\t\tconfig_copy_from_path_rel = os.path.join(os.sep, 'DBfiles', 'config.cfg')\n\t\tconfig_copy_from_path = ('%s%s') % (module_path, config_copy_from_path_rel)\n\t\tconfig_copy_to_path = ('%s%s%s') % (home_DB_path, os.sep, 'config.cfg')\n\n\t\tdb_copy_from_path_rel = os.path.join(os.sep, 'DBfiles', 'pyarchinit_db.sqlite')\n\t\tdb_copy_from_path = ('%s%s') % (module_path, db_copy_from_path_rel)\n\t\tdb_copy_to_path = ('%s%s%s') % (home_DB_path, os.sep, 'pyarchinit_db.sqlite')\n\n\t\tlogo_copy_from_path_rel = os.path.join(os.sep, 'DBfiles', 'logo.jpg')\n\t\tlogo_copy_from_path = ('%s%s') % (module_path, logo_copy_from_path_rel)\n\t\tlogo_copy_to_path = ('%s%s%s') % (home_DB_path, os.sep, 'logo.jpg')\n\t\n\t\tOS_utility = pyarchinit_OS_Utility()\n\n\t\tOS_utility.create_dir(str(home_DB_path))\n\n\t\tOS_utility.copy_file(config_copy_from_path, config_copy_to_path)\n\t\tOS_utility.copy_file(db_copy_from_path, db_copy_to_path)\n\t\tOS_utility.copy_file(logo_copy_from_path, logo_copy_to_path)\n\n\t\thome_PDF_path = ('%s%s%s') % (home, os.sep, 'pyarchinit_PDF_folder')\n\t\tOS_utility.create_dir(home_PDF_path)\n\n\t\thome_MATRIX_path = ('%s%s%s') % (home, os.sep, 'pyarchinit_Matrix_folder')\n\t\tOS_utility.create_dir(home_MATRIX_path)\n\t\n\t\thome_THUMBNAILS_path = ('%s%s%s') % (home, os.sep, 'pyarchinit_Thumbnails_folder')\n\t\tOS_utility.create_dir(home_THUMBNAILS_path)\n\n\t\thome_MAPS_path = ('%s%s%s') % (home, os.sep, 'pyarchinit_MAPS_folder')\n\t\tOS_utility.create_dir(home_MAPS_path)\n\n\t\thome_REPORT_path = ('%s%s%s') % (home, os.sep, 'pyarchinit_Report_folder')\n\t\tOS_utility.create_dir(home_REPORT_path)\n\n\t\thome_QUANT_path = ('%s%s%s') % (home, os.sep, 'pyarchinit_Quantificazioni_folder')\n\t\tOS_utility.create_dir(home_QUANT_path)\n\n\t\thome_TEST_path = ('%s%s%s') % (home, os.sep, 'pyarchinit_Test_folder')\n\t\tOS_utility.create_dir(home_TEST_path)\n\n\t\thome_BECKUP_linux_path = ('%s%s%s') % (home, os.sep,'pyarchinit_db_beckup')\n\t\tOS_utility.create_dir(home_BECKUP_linux_path)\n\t\n\t\t#experimental\n\t\t#il sistema funziona ma sovrascrive ogni volta il file. aggiungere sistema di verifica di presenza del file.\n\t\t#urllib.urlretrieve( \"https://raw.github.com/pyarchinit/pyarchinit_beta_test_dev/master/pyarchinit_dev20130710/modules/utility/DBfiles/pyarchinit_db.sqlite\",db_copy_to_path)\n\na = pyarchinit_Folder_installation()\na.install_dir()","sub_path":"pyarchinit/modules/utility/pyarchinit_folder_installation.py","file_name":"pyarchinit_folder_installation.py","file_ext":"py","file_size_in_byte":3826,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"570661847","text":"import unittest\n\nfrom pyomotools.tools import cplex\nfrom sddp.SDDP import createSDDPModel\nfrom sddp.typedefinitions import *\n\nCplexSolver = cplex() # type:CPLEXSHELL\n\n\ndef solve_model(noise_probability:List[float]):\n def build(sp: Subproblem, t: int, markov_state: int):\n model = sp.model\n model.x = Var(domain=NonNegativeReals)\n model.x0 = Var(domain=NonNegativeReals)\n model.xp = Param(initialize=1.5, mutable=True)\n sp.add_state(model.x, model.x0, model.xp)\n # 变量\n model.u = Var(bounds=(0, 1))\n # 约束\n sp.anonymous = Constraint(expr=model.x == model.x0 - model.u)\n if t == 0:\n sp.obj = model.u * 2\n else:\n sp.anonymous = Param(mutable=True)\n p = sp.anonymous\n sp.obj = p * model.u\n sp.setnoiseprobability(noise_probability)\n\n m=createSDDPModel(sense=Sense.Max,stages=2,objective_bound=5,)\n\n\n\n\nclass MyTestCase(unittest.TestCase):\n def test_something(self):\n self.assertEqual(True, False)\n\n\nif __name__ == '__main__':\n unittest.main()\n","sub_path":"sddp/example/simple_object_noise.py","file_name":"simple_object_noise.py","file_ext":"py","file_size_in_byte":1095,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"577755118","text":"import unittest # import the unittest module to test the class methods\r\n\r\nfrom implementation_5.doubly_linked_list import DLinkedList\r\nfrom implementation_5.doubly_linked_list import Node\r\n\r\n\r\nclass TestSLinkedList(unittest.TestCase):\r\n def test_prepend(self):\r\n myObj = DLinkedList() # initialize a new object of the class DLinkedList\r\n myObj.prepend(120) # prepend a new value to the beginning of the linked list\r\n myObj.prepend(130)\r\n self.assertEqual(myObj.get_head(), 130) # check the data in the head node\r\n self.assertEqual(myObj.get_tail(), 120) # check the data in the tail node\r\n\r\n def test_pop_first(self):\r\n myObj = DLinkedList()\r\n myObj.prepend(120)\r\n myObj.prepend(130)\r\n self.assertEqual(myObj.pop_first(), 130) # delete the head 130\r\n\r\n def test_append(self):\r\n myObj = DLinkedList()\r\n myObj.append(120)\r\n myObj.append(130)\r\n self.assertEqual(myObj.get_head(), 120)\r\n self.assertEqual(myObj.get_tail(), 130)\r\n\r\n def test_pop_last(self):\r\n myObj = DLinkedList()\r\n myObj.append(120)\r\n myObj.append(130)\r\n self.assertEqual(myObj.pop_last(), 130) # delete the head 130\r\n\r\n def test_pop_last_2(self):\r\n \"\"\"\r\n test deleting the last element from a non empty Linked List\r\n \"\"\"\r\n myObj = DLinkedList()\r\n with self.assertRaises(IndexError):\r\n myObj.pop_last()\r\n\r\n def test_append_2(self):\r\n \"\"\"\r\n Test the head and tail after appending one value only\r\n \"\"\"\r\n myObj = DLinkedList()\r\n myObj.prepend(120)\r\n self.assertEqual(myObj.get_head(), 120)\r\n self.assertEqual(myObj.get_tail(), 120)\r\n\r\n def test_insert_node(self):\r\n \"\"\"\r\n Test inserting a node to the Linked List giving the previous node\r\n \"\"\"\r\n myObj = DLinkedList()\r\n myObj.append(120)\r\n myObj.append(100)\r\n self.assertEqual(myObj.insert_node(Node(1000), myObj.head), [120, 1000, 100])\r\n\r\n def test_delete_node(self):\r\n \"\"\"\r\n Test deleting a node from the Linked List given the node\r\n \"\"\"\r\n myObj = DLinkedList()\r\n myObj.append(120)\r\n myObj.append(100)\r\n myObj.detete_node(myObj.head.next)\r\n myObj.detete_node(myObj.head)\r\n self.assertEqual(myObj.get_head(), None)\r\n self.assertEqual(myObj.get_tail(), None)\r\n\r\n\r\nif __name__ == '__main__':\r\n unittest.main()\r\n","sub_path":"implementation_5/test_dLinkedList.py","file_name":"test_dLinkedList.py","file_ext":"py","file_size_in_byte":2496,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"235203277","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*- \n# * \n# * FileName : 替换空格.py\n# * Date : 2020年05月27日\n# * Description : 请实现一个函数，将一个字符串中的每个空格替换成“%20”。例如，当字符串为We Are Happy.则经过替换之后的字符串为We%20Are%20Happy。 \n# *\n\nclass Solution:\n def replaceSpace(self, s):\n list = []\n for i in s:\n if i == ' ': \n i='%20'\n list.append(i)\n return ''.join(list)\n\n def replaceSpace2(self,s):\n s.replace(\" \",\"%20\")\n return s\n\nif __name__==\"__main__\":\n s=Solution()\n print(s.replaceSpace2('We are happy.'))\n print(s.replaceSpace2('hello world'))\n","sub_path":"AlgorithmsByPython/TargetOffer/字符串/替换空格.py","file_name":"替换空格.py","file_ext":"py","file_size_in_byte":724,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"563055122","text":"#############################################################################\r\n#\r\n# Copyright (C) 2011 Navi-X\r\n#\r\n# This file is part of Navi-X.\r\n#\r\n# Navi-X is free software: you can redistribute it and/or modify\r\n# it under the terms of the GNU General Public License as published by\r\n# the Free Software Foundation, either version 2 of the License, or\r\n# (at your option) any later version.\r\n#\r\n# Navi-X is distributed in the hope that it will be useful,\r\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\r\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\r\n# GNU General Public License for more details.\r\n#\r\n# You should have received a copy of the GNU General Public License\r\n# along with Navi-X. If not, see .\r\n#\r\n#############################################################################\r\n\r\nACTION_MOVE_LEFT = 1 #Dpad Left\r\nACTION_MOVE_RIGHT = 2 #Dpad Right\r\nACTION_MOVE_UP = 3 #Dpad Up\r\nACTION_MOVE_DOWN = 4 #Dpad Down\r\nACTION_PAGE_UP = 5 #Left trigger\r\nACTION_PAGE_DOWN = 6 #Right trigger\r\nACTION_SELECT_ITEM = 7 #'A'\r\nACTION_HIGHLIGHT_ITEM = 8\r\nACTION_PARENT_DIR = 9 #'B'\r\nACTION_PREVIOUS_MENU = 10 #'Back'\r\nACTION_SHOW_INFO = 11\r\nACTION_PAUSE = 12\r\nACTION_STOP = 13 #'Start'\r\nACTION_NEXT_ITEM = 14\r\nACTION_PREV_ITEM = 15\r\nACTION_XBUTTON\t = 18 #'X'\r\nACTION_YBUTTON \t = 34\t#'Y'\r\nACTION_MOUSEMOVE = 90 # Mouse has moved\r\nACTION_PREVIOUS_MENU2 = 92 #'Back'\r\nACTION_CONTEXT_MENU = 117 # pops up the context menu\r\nACTION_CONTEXT_MENU2 = 229 # pops up the context menu (remote control \"title\" button)\r\n\r\n\r\n#############################################################################\r\n# auto scaling values\r\n#############################################################################\r\n\r\nHDTV_1080i = 0 #(1920x1080, 16:9, pixels are 1:1)\r\nHDTV_720p = 1 #(1280x720, 16:9, pixels are 1:1)\r\nHDTV_480p_4x3 = 2 #(720x480, 4:3, pixels are 4320:4739)\r\nHDTV_480p_16x9 = 3 #(720x480, 16:9, pixels are 5760:4739)\r\nNTSC_4x3 = 4 #(720x480, 4:3, pixels are 4320:4739)\r\nNTSC_16x9 = 5 #(720x480, 16:9, pixels are 5760:4739)\r\nPAL_4x3 = 6 #(720x576, 4:3, pixels are 128:117)\r\nPAL_16x9 = 7 #(720x576, 16:9, pixels are 512:351)\r\nPAL60_4x3 = 8 #(720x480, 4:3, pixels are 4320:4739)\r\nPAL60_16x9 = 9 #(720x480, 16:9, pixels are 5760:4739)\r\n\r\n\r\n#############################################################################\r\n# directory settings\r\n#############################################################################\r\nimport os, xbmcaddon\r\nRootDir = xbmcaddon.Addon(id='plugin.video.navi-x').getAddonInfo('path')\r\nif RootDir[-1]==';': RootDir=RootDir[0:-1]\r\nif RootDir[0] == '/':\r\n if RootDir[-1] != '/': RootDir = RootDir+'/'\r\n myDownloadsDir = RootDir + \"My Downloads/\"\r\n initDir = RootDir + \"init/\"\r\n myPlaylistsDir = RootDir + \"My Playlists/\"\r\n srcDir = RootDir + \"src/\"\r\n imageDir = RootDir + \"images/\"\r\n #imageDir = RootDir + \"resources/skins/Default/media/\"\r\n cacheDir = RootDir + \"cache/\"\r\n imageViewCacheDir = RootDir + \"cache/mageview/\"\r\n imageCacheDir = RootDir + \"cache/images/\"\r\n tempCacheDir = RootDir + \"cache/temp/\"\r\n nookieCacheDir = RootDir + \"cache/nookies/\"\r\n procCacheDir = RootDir + \"cache/proc/\"\r\n favoritesDir = RootDir + \"favorites/\"\r\n SEPARATOR = '/'\r\nelse:\r\n if RootDir[-1] != '\\\\': RootDir = RootDir+'\\\\'\r\n myDownloadsDir = RootDir + \"My Downloads\\\\\"\r\n initDir = RootDir + \"init\\\\\"\r\n myPlaylistsDir = RootDir + \"My Playlists\\\\\"\r\n srcDir = RootDir + \"src\\\\\"\r\n imageDir = RootDir + \"images\\\\\"\r\n #imageDir = RootDir + \"resources\\\\skins\\\\Default\\\\media\\\\\"\r\n cacheDir = RootDir + \"cache\\\\\"\r\n imageViewCacheDir = RootDir + \"cache\\\\imageview\\\\\"\r\n imageCacheDir = RootDir + \"cache\\\\images\\\\\"\r\n tempCacheDir = RootDir + \"cache\\\\temp\\\\\"\r\n nookieCacheDir = RootDir + \"cache\\\\nookies\\\\\"\r\n procCacheDir = RootDir + \"cache\\\\proc\\\\\"\r\n favoritesDir = RootDir + \"favorites\\\\\"\r\n SEPARATOR = '\\\\'\r\n\r\nimport xbmc\r\ntry:\r\n version = int(xbmc.getInfoLabel(\"System.BuildVersion\").replace(\"PRE-\",\"\")[:2])\r\nexcept:\r\n version = int(xbmc.getInfoLabel(\"System.BuildVersion\")[:1])\r\nif version > 9:\r\n scriptDir = \"special://home/addons/\"\r\n pluginDir = \"special://home/addons/\"\r\n skinDir = \"special://home/skin/\"\r\nelif version == 9:\r\n scriptDir = \"special://home/scripts/\"\r\n pluginDir = \"special://home/plugins/\"\r\n skinDir = \"special://home/skin/\"\r\nelse: \r\n scriptDir = \"Q:\\\\scripts\\\\\"\r\n pluginDir = \"Q:\\\\plugins\\\\\"\r\n skinDir = \"Q:\\\\skin\\\\\"\r\n\r\n\r\nuseLibrtmp=os.path.exists(xbmc.translatePath('special://xbmc/system/players/dvdplayer/librtmp.dll'))\r\n\r\n######################################################################\r\n#program version: Combination of version and subversion\r\nVersion='3' \r\nSubVersion='7.1'\r\n\r\nfavorite_file='favorites.plx' #the favorite list is also a playlist\r\ndownloads_file='downlmenu.plx' #the downloads list is also a playlist\r\ndownloads_queue='downlqueue.plx'\r\ndownloads_complete='downloads.plx'\r\nparent_list='blacklist.plx'\r\nhistory_list='history.plx'\r\nplxVersion = '8'\r\nhome_URL_old='http://www.navi-x.org/playlists/home.plx'\r\nhome_URL='http://navi-x.googlecode.com/svn/trunk/Playlists/home.plx'\r\nhome_URL_mirror='http://navi-x.googlecode.com/svn/trunk/Playlists/home.plx'\r\nbackground_image1 = 'background1.jpg'\r\nbackground_image2 = 'background2.png'\r\nsearchhistory_file = 'search.dat'\r\nnxserver_URL = 'http://navix.turner3d.net'\r\n\r\nurl_open_timeout = 30 #30 seconds\r\npage_size = 200 #display maximum 200 entries on one page\r\nhistory_size = 50 #maximum of entries in the history list\r\n\r\n","sub_path":"Spanish/plugin.video.navi-x/src/settings.py","file_name":"settings.py","file_ext":"py","file_size_in_byte":5786,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"62333293","text":"'''\n Aashutosh Rathi\nhttps://github.com/aashutoshrathi/\nTestcase Generator for HackerRank\n\n'''\n\nfrom __future__ import print_function\n\nimport os\nimport random\nimport sys\nimport zipfile\nimport math\nimport shutil\n\nif sys.version[0] == '3':\n raw_input = input\n xrange = range\n\ntry:\n os.mkdir('input')\n os.mkdir('output')\nexcept OSError:\n pass\n\nchoice = int(raw_input(\"Enter your choice of language\\n1 for C\\n2 for C++\\n3 for Java\\n4 for Python\\n\"))\nif choice != 1 and choice != 2 and choice != 3 and choice != 4:\n print(\"Wrong choice entered!\")\n exit()\n\ntf = 10 # number of test files, change it according to you.\n\nfor i in xrange(0, tf + 1):\n print('Generating:', i, file=sys.stderr)\n sys.stdout = open('input/input%02d.txt' % i, 'w')\n\n '''\n Input area will start here,\n everything that you print out here will be taken as input in your logic file.\n You can set difficulty of test cases all by you.\n '''\n\n # Input File Printing Starts\n\n sys.stdout.close()\n # Input File Printing Ends\n\n\n'''\nOutput generation and zipping starts here\njust replace '' with your actual filename everywhere\n\n'''\n# You can change zip filename as per your wish.\nwith zipfile.ZipFile('test-cases.zip', 'w', zipfile.ZIP_DEFLATED) as zf:\n for i in xrange(0, tf + 1):\n print('Zipping:', i, file=sys.stderr) # Will show status of which TC output is generated.\n\n if choice == 1: # Choice of language is C\n os.system('gcc -o .c') # System call to compile .c file\n # System call to generate output files for C\n os.system('./ < input/input%02d.txt > output/output%02d.txt' % (i, i))\n elif choice == 2: # Choice of language is C++\n os.system('g++ -o .cpp') # System call to compile .cpp file\n # System call to generate output files for C++\n os.system('./ < input/input%02d.txt > output/output%02d.txt' % (i, i))\n elif choice == 3: # Choice of language is Java\n os.system('javac .java') # System call to compile .java file\n # System call to generate output files for Java\n os.system('java < input/input%02d.txt > output/output%02d.txt' % (i, i))\n elif choice == 4: # Choice of language is Python\n # System call to generate output files for Python\n os.system('python .py < input/input%02d.txt > output/output%02d.txt' % (i, i))\n\n zf.write('input/input%02d.txt' % i)\n zf.write('output/output%02d.txt' % i)\n\nshutil.rmtree('input')\nshutil.rmtree('output')\n","sub_path":"Python/TC-Generator/TCGen.py","file_name":"TCGen.py","file_ext":"py","file_size_in_byte":2658,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"385799491","text":"# -*- coding: utf-8 -*-\n\nfrom django.core.files import File\nfrom storage import S3Storage\n\n\ndef upload(filename, name=None, prefix=False, bucket_name=False, key=None,\n secret=None, host=None):\n \"\"\"\n Uploading files to Amamzon S3.\n \"\"\"\n if isinstance(filename, basestring):\n fl = open(filename, 'rb')\n elif isinstance(filename, (file, File)):\n fl = filename\n else:\n raise TypeError('File must be file or string instance.')\n\n if not name:\n name = fl.name\n\n if prefix:\n if prefix.endswith('/'):\n full_path = prefix + name\n else:\n full_path = prefix + '/' + name\n else:\n full_path = name\n\n s3 = S3Storage(bucket_name=bucket_name, key=key, secret=secret, host=host)\n s3.save(full_path, fl)\n\n return s3.url(full_path)\n","sub_path":"django_boto/s3/shortcuts.py","file_name":"shortcuts.py","file_ext":"py","file_size_in_byte":829,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"265680038","text":"import threading\r\nimport socket\r\n\r\nprint(\"Suggested ip: \" + socket.gethostbyname(socket.gethostname()))\r\nmode = input(\"1:Connect 2:Listen :\")\r\nip = input(\"IP:\")\r\ns = socket.socket()\r\n\r\n\r\ndef recive(sock):\r\n while True:\r\n data = sock.recv(1024)\r\n print(\"[+] \" + data.decode())\r\n\r\nif mode == \"2\":\r\n port = 60001\r\n s.bind((ip,port))\r\n s.listen()\r\n conn, addr = s.accept()\r\n threading.Thread(target=lambda:recive(conn)).start()\r\n while True:\r\n msg = input()\r\n conn.send(msg.encode())\r\n\r\nelif mode == \"1\":\r\n port = 60002\r\n s.connect((ip,port))\r\n threading.Thread(target=lambda:recive(s)).start()\r\n while True:\r\n msg = input()\r\n s.send(msg.encode())\r\n","sub_path":"P2P/msg.py","file_name":"msg.py","file_ext":"py","file_size_in_byte":720,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"29818259","text":"import cv2, os, io\nimport numpy as np\nimport tensorflow.compat.v1 as tf\nimport PIL.Image\nimport hashlib\n\nfrom object_detection.utils import dataset_util\nfrom object_detection.utils import label_map_util\nfrom tqdm import tqdm\n\nimport contextlib2\nfrom object_detection.dataset_tools import tf_record_creation_util\n\nflags = tf.app.flags\nflags.DEFINE_string('label_map_path', 'dataset/emnist_letters_detection/label_map.pbtxt', 'Path to label map proto')\nFLAGS = flags.FLAGS\n\n# The following functions can be used to convert a value to a type compatible\n# with tf.train.Example.\n\ndef _bytes_feature(value):\n \"\"\"Returns a bytes_list from a string / byte.\"\"\"\n if isinstance(value, type(tf.constant(0))):\n value = value.numpy() # BytesList won't unpack a string from an EagerTensor.\n return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))\n\ndef _float_feature(value):\n \"\"\"Returns a float_list from a float / double.\"\"\"\n return tf.train.Feature(float_list=tf.train.FloatList(value=[value]))\n\ndef _int64_feature(value):\n \"\"\"Returns an int64_list from a bool / enum / int / uint.\"\"\"\n return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))\n\ndef image_to_tf_data(img_path, label_path, label_map_dict):\n filename = img_path.split('/')[-1]\n full_path = img_path\n with tf.io.gfile.GFile(full_path, 'rb') as fid:\n encoded_jpg = fid.read()\n encoded_jpg_io = io.BytesIO(encoded_jpg)\n image = PIL.Image.open(encoded_jpg_io)\n if image.format != 'JPEG':\n raise ValueError('Image format not JPEG')\n key = hashlib.sha256(encoded_jpg).hexdigest()\n\n width, height = image.size\n\n classes, classes_text = [], []\n xmins, ymins, xmaxs, ymaxs = [], [], [], []\n with tf.io.gfile.GFile(label_path) as f:\n lines = f.readlines()\n content = [line.split(',') for line in lines][1:]\n for class_idx, xmin, ymin, xmax, ymax in content:\n classes.append(int(class_idx))\n classes_text.append(label_map_dict[int(class_idx)].encode('utf8'))\n xmins.append(float(xmin) / width)\n ymins.append(float(ymin) / height)\n xmaxs.append(float(xmax) / width)\n ymaxs.append(float(ymax) / height)\n\n feature_dict = { \n 'image/height': dataset_util.int64_feature(height),\n 'image/width': dataset_util.int64_feature(width),\n 'image/filename': dataset_util.bytes_feature(filename.encode('utf8')),\n 'image/source_id': dataset_util.bytes_feature(filename.encode('utf8')),\n 'image/key/sha256': dataset_util.bytes_feature(key.encode('utf8')),\n 'image/encoded': dataset_util.bytes_feature(encoded_jpg),\n 'image/format': dataset_util.bytes_feature('jpg'.encode('utf8')),\n 'image/object/bbox/xmin': dataset_util.float_list_feature(xmins),\n 'image/object/bbox/xmax': dataset_util.float_list_feature(xmaxs),\n 'image/object/bbox/ymin': dataset_util.float_list_feature(ymins),\n 'image/object/bbox/ymax': dataset_util.float_list_feature(ymaxs),\n 'image/object/class/text': dataset_util.bytes_list_feature(classes_text),\n 'image/object/class/label': dataset_util.int64_list_feature(classes)\n }\n tf_data = tf.train.Example(features=tf.train.Features(feature=feature_dict))\n \n return tf_data\n\ndef main(_):\n\n base_dir = \"./dataset/emnist_letters_detection\"\n label_map_dict = label_map_util.get_label_map_dict(FLAGS.label_map_path)\n label_map_dict = {value: key for key, value in label_map_dict.items()}\n num_shards = 10\n \n for dataset in [\"train\", \"test\"]:\n img_names = os.listdir(os.path.join(base_dir, dataset, \"images\"))\n label_names = os.listdir(os.path.join(base_dir, dataset, \"labels\"))\n img_paths = [os.path.join(base_dir, dataset, \"images\", name) for name in img_names]\n label_paths = [os.path.join(base_dir, dataset, \"labels\", name) for name in label_names]\n output_file_dir = os.path.join(base_dir, dataset, \"tfrecord\")\n tf.io.gfile.mkdir(output_file_dir)\n # sharding when dataset is train\n if dataset == \"train\":\n with contextlib2.ExitStack() as tf_record_close_stack:\n output_tfrecords = tf_record_creation_util.open_sharded_output_tfrecords(tf_record_close_stack, os.path.join(output_file_dir, f\"{dataset}.record\"), num_shards)\n for index, (img_path, label_path) in tqdm(enumerate(zip(img_paths, label_paths)), desc=\"Generating tfrecord\", total=len(img_paths)):\n tf_example = image_to_tf_data(img_path, label_path, label_map_dict)\n output_shard_index = index % num_shards\n output_tfrecords[output_shard_index].write(tf_example.SerializeToString())\n else:\n tf_writer = tf.io.TFRecordWriter(os.path.join(output_file_dir, f\"{dataset}.record\"))\n for img_path, label_path in tqdm(zip(img_paths, label_paths), desc=\"Generating tfrecord\", total=len(img_paths)):\n tf_example = image_to_tf_data(img_path, label_path, label_map_dict)\n tf_writer.write(tf_example.SerializeToString())\n tf_writer.close()\n\nif __name__ == '__main__':\n tf.app.run()","sub_path":"research/generate_tfrecord.py","file_name":"generate_tfrecord.py","file_ext":"py","file_size_in_byte":5132,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"465949351","text":"# Copyright (c) 2013 Shotgun Software Inc.\n#\n# CONFIDENTIAL AND PROPRIETARY\n#\n# This work is provided \"AS IS\" and subject to the Shotgun Pipeline Toolkit\n# Source Code License included in this distribution package. See LICENSE.\n# By accessing, using, copying or modifying this work you indicate your\n# agreement to the Shotgun Pipeline Toolkit Source Code License. All rights\n# not expressly granted therein are reserved by Shotgun Software Inc.\n\nfrom .qt_abstraction import QtGui\nfrom .qt_abstraction import QtCore\n\n\nclass AspectPreservingLabel(QtGui.QLabel):\n def __init__(self, parent=None):\n QtGui.QLabel.__init__(self, parent)\n\n self._pix = None\n\n def setPixmap(self, pixmap):\n self._pix = pixmap\n scaled_pixmap = self._pix.scaled(\n self.size(), QtCore.Qt.KeepAspectRatio, QtCore.Qt.SmoothTransformation)\n QtGui.QLabel.setPixmap(self, scaled_pixmap)\n\n def heightForWidth(self, width):\n if self._pix is None:\n return self._pix.height()*width/self._pix.width()\n return QtGui.QLabel.heightForWidth(self, width)\n\n def sizeHint(self):\n width = min(self.width(), self.pixmap().width())\n return QtCore.QSize(width, self.heightForWidth(width))\n\n def resizeEvent(self, e):\n if self._pix is None:\n return\n\n scaled_pixmap = self._pix.scaled(\n self.size(), QtCore.Qt.KeepAspectRatio, QtCore.Qt.SmoothTransformation)\n QtGui.QLabel.setPixmap(self, scaled_pixmap)\n QtGui.QApplication.instance().processEvents()\n","sub_path":"install/frameworks/app_store/tk-framework-login/v1.0.6/python/aspect_preserving_label.py","file_name":"aspect_preserving_label.py","file_ext":"py","file_size_in_byte":1551,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"158807390","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Nov 26 07:54:35 2018\n\n@author: xsxsz\n\"\"\"\n\nimport os\nimport zipfile\nz=zipfile.ZipFile('save.zip',mode='w')\nif os.path.isdir('zip_test'):\n print('path exists')\n print('-----------')\n for filename in os.listdir('zip_test'):\n z.write('./zip_test/'+filename)\n z.close()","sub_path":"others/python_zipfile.py","file_name":"python_zipfile.py","file_ext":"py","file_size_in_byte":349,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"30532429","text":"# -*-coding: utf-8-*-\n# **************************file desc*****************************\n\n\n__author__ = 'wangxiaohu'\n# createTime : 2019/1/29 0029 17:00\n# desc :celery 的配置文件\n# ****************************************************************\n\n\n# 使用redis作为消息代理\nBROKER_URL='redis://106.13.49.195:6380/0'\n# 把任务结果存在了Redis\nCELERY_RESULT_BACKEND = 'redis://106.13.49.195:6380/1'\n# 任务序列化和反序列化使用JSON方案\nCELERY_TASK_SERIALIZER = 'json'\n# 读取任务结果使用JSON\nCELERY_RESULT_SERIALIZER = 'json'\n# 任务过期时间，不建议直接写86400，应该让这样的magic数字表述更明显\nCELERY_TASK_RESULT_EXPIRES = 60 * 60 * 24\n# 指定接受的内容类型，是个数组，可以写多个\nCELERY_ACCEPT_CONTENT = ['json']","sub_path":"Celery/Spider/celeryConfig.py","file_name":"celeryConfig.py","file_ext":"py","file_size_in_byte":791,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"102489395","text":"import json\nimport rpm\nimport sys\n\n\ndef format_version(app):\n return '{e}:{v}-{r}.{a}'.format(e=app['epoch'] or 0,\n v=app['version'],\n a=app['arch'],\n r=app['release'])\n\n\nsys.stdout.write(\n json.dumps({\n 'rpm_packages': [{\n 'packages': [{'name': app['name'], 'version': format_version(app)} for app in rpm.ts().dbMatch()]}\n ]}) + '\\n')\n","sub_path":"src/actors/containerization/misc/rpm_list/rpm_list.py","file_name":"rpm_list.py","file_ext":"py","file_size_in_byte":472,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"132440513","text":"\"\"\"\n\tElasticDefense.py\n\t\n\tA strategy that makes use of two indicators and some \n\tclever decision making.\n\t\n\tElasticDefense uses the MACD (Moving Average Convergence Divergence) and \n\tSSI (Slow Stochastic Indicator) indicators. Various conditions must be met\n\tfor this indicator to return a buy long or sell short signal.\n\t\n\tUses 2 stages to determine if a signal should be launched.\n\t\n\tStage 1 Triggers:\n\t\tLong Signal:\n\t\t\t1. Histogram above 0\n\t\t\t2. Histogram degrading to 0\n\t\t\t3. Histogram reverses and go up again after nearing 0\n\t\t\t\tGraph below shows the situation\n\t\t\tHistogram\t|----___\n\t\t\t\t\t\t|\t\t``-__.-`\n\t\t\t\t0 Line\t|________________________\n\n\t\tShort Signal:\n\t\t\t1. Histogram below 0\n\t\t\t2. Histogram accending to 0\n\t\t\t3. Histogram reverses and goes down again after nearing 0\n\t\t\t\n\t\t\t\t0 Line\t|__________________________\n\t\t\t\t\t\t|\t\t..--.\n\t\t\tHistogram\t|___,.-`\t `--.\n\t\t\t\n\tStage 2 Triggers:\n\t\tLong Signal:\n\t\t\t1. Stage 1 Long Signal Completed\n\t\t\t2. SSI under 20%\n\t\t\t3. SSI Lines are crossed\n\t\t\t4. SSI Lines are facing UP\n\t\t\n\t\tShort Signal:\n\t\t\t1. Stage 1 Short Signal Completed\n\t\t\t2. SSI over 80%\n\t\t\t3. SSI Lines are crossed\n\t\t\t4. SSI Lines are facing DOWN\n\"\"\"\n\ndef ElasticDefense(pair):\n\t# For those who want to see the debug text\n\tverboseOut = False\n\t\n\t# Call on indicators that the strategy uses\n\tretMACD = pair.indicator_MACD()\n\tretSSI\t= pair.indicator_STOCH()\n\t\n\t# Parse the information needed from the indicators\n\tpatMACD = retMACD[\"histogram\"][-7:]\n\tdirSSI\t= \"Up\" if retSSI[\"signal\"][-1] > retSSI[\"signal\"][-2] else \"Down\"\n\tfailObj\t= {\"Signal\":\"None\"}\n\tretObj\t= {\"Signal\":\"None\"}\n\t\n\t# Test parameters for Long\n\t#retMACD[\"histogram\"] = [1,1]\n\t#patMACD = [3,2,1,0,0,1,2]\n\t#dirSSI = \"Up\"\n\t#retSSI[\"signal\"] =[10,12]\n\t\n\t# Test parameters for Short\n\t#retMACD[\"histogram\"] = [-2,-1]\n\t#patMACD = [-3,-2,-1,0,0,-1,-2]\n\t#dirSSI = \"Down\"\n\t#retSSI[\"signal\"] =[88,85]\n\t\n\t# Check for basic reversal trends\n\tif retMACD[\"histogram\"][-1] > 0:\n\t\ttmp=patMACD[:5]\n\t\tfor elm in range(0, len(tmp)-1):\n\t\t\tif tmp[elm] < tmp[elm+1]:\n\t\t\t\tif verboseOut:\n\t\t\t\t\tprint(\"%s ] 0> %s is < than %s\"%(pair.pair, tmp[elm], tmp[elm+1]))\n\t\t\t\treturn failObj\n\t\ttmp=patMACD[4:]\n\t\tfor elm in range(0, len(tmp)-1):\n\t\t\tif tmp[elm] > tmp[elm+1]:\n\t\t\t\tif verboseOut:\n\t\t\t\t\tprint(\"%s ] 0> %s is > than %s\"%(pair.pair, tmp[elm], tmp[elm+1]))\n\t\t\t\treturn failObj\n\telif retMACD[\"histogram\"][-1]<0:\n\t\ttmp=patMACD[:5]\n\t\tfor elm in range(0, len(tmp)-1):\n\t\t\tif tmp[elm] > tmp[elm+1]:\n\t\t\t\tif verboseOut:\n\t\t\t\t\tprint(\"%s ] <0 %s is > than %s\"%(pair.pair, tmp[elm], tmp[elm+1]))\n\t\t\t\treturn failObj\n\t\ttmp=patMACD[4:]\n\t\tfor elm in range(0, len(tmp)-1):\n\t\t\tif tmp[elm] < tmp[elm+1]:\n\t\t\t\tif verboseOut:\n\t\t\t\t\tprint(\"%s ] <0 %s is < than %s\"%(pair.pair, tmp[elm], tmp[elm+1]))\n\t\t\t\treturn failObj\n\telse:\n\t\treturn failObj\n\tif verboseOut:\n\t\tprint(\"%s ] Pair passed stage 1\"%pair.pair)\n\t\n\t# Check that histogram direction complies with rules\n\tif dirSSI == \"Up\":\n\t\tif retMACD[\"histogram\"][-1] < 0:\n\t\t\tif verboseOut:\n\t\t\t\tprint(\"%s ] %s does not comply with Up direction.\"%(pair.pair, retMACD[\"histogram\"][-1]))\n\t\t\treturn failObj\n\t\tretObj[\"Signal\"] = \"long\"\n\telse:\n\t\tif retMACD[\"histogram\"][-1] > 0:\n\t\t\tif verboseOut:\n\t\t\t\tprint(\"%s ] %s does not comply with Down direction.\"%(pair.pair, retMACD[\"histogram\"][-1]))\n\t\t\treturn failObj\n\t\tretObj[\"Signal\"] = \"short\"\t\n\tif verboseOut:\n\t\tprint(\"%s ] Pair passed stage 2\"%pair.pair)\n\t\n\tif retMACD[\"histogram\"][-1] < 0:\n\t\tif retSSI[\"signal\"][-1] <= 80.00:\n\t\t\tif verboseOut:\n\t\t\t\tprint(\"%s ] %s is <= 80.00 : Non-compliant with histograms under 0\"%(pair.pair, retSSI[\"signal\"][-1]))\n\t\t\treturn failObj\n\telif retMACD[\"histogram\"][-1] > 0:\n\t\tif retSSI[\"signal\"][-1] >= 20.00:\n\t\t\tif verboseOut:\n\t\t\t\tprint(\"%s ] %s is >= 20.00 : Non-compliant with histograms above 0\"%(pair.pair, retSSI[\"signal\"][-1]))\n\t\t\treturn failObj\n\t#if verboseOut:\n\tprint(\"%s ] Pair passed!\"%pair.pair)\n\treturn retObj","sub_path":"most-complex-project/Kinix-master/_modules/strategy/ElasticDefense.py","file_name":"ElasticDefense.py","file_ext":"py","file_size_in_byte":3860,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"459260969","text":"import json\nimport os\n\nimport gym\nimport ray\nfrom ray.tune import run_experiments\nimport ray.rllib.agents.a3c as a3c\nimport ray.rllib.agents.ppo as ppo\nfrom ray.tune.registry import register_env\nfrom environment import NetworkCompression\n\nfrom sagemaker_rl.ray_launcher import SageMakerRayLauncher\n\ndef create_environment(env_config):\n # This import must happen inside the method so that worker processes import this code\n from environment import Compression\n return Compression()\n\n\nclass MyLauncher(SageMakerRayLauncher):\n def __init__(self):\n super(MyLauncher, self).__init__()\n self.num_gpus = int(os.environ.get(\"SM_NUM_GPUS\", 0))\n self.hosts_info = json.loads(os.environ.get(\"SM_RESOURCE_CONFIG\"))[\"hosts\"]\n self.num_total_gpus = self.num_gpus * len(self.hosts_info)\n\n def register_env_creator(self):\n register_env(\"NetworkCompression-v1\", create_environment)\n\n def get_experiment_config(self):\n return {\n \"training\": {\n \"env\": \"NetworkCompression-v1\",\n \"run\": \"A3C\",\n \"stop\": {\n \"training_iteration\": 20,\n },\n \"local_dir\": \"/opt/ml/model/\",\n \"checkpoint_freq\" : 1,\n \"config\": {\n \"num_workers\": max(self.num_total_gpus-1, 1),\n \"use_gpu_for_workers\": True,\n \"train_batch_size\": 5,\n \"sample_batch_size\": 1,\n \"gpu_fraction\": 0.3,\n \"optimizer\": {\n \"grads_per_step\": 10\n },\n },\n \"trial_resources\": {\"cpu\": 0, \"gpu\": 1, \"extra_gpu\": max(self.num_total_gpus-1, 1), \"extra_cpu\": 0},\n }\n }\n\nif __name__ == \"__main__\":\n os.environ[\"LC_ALL\"] = \"C.UTF-8\"\n os.environ[\"LANG\"] = \"C.UTF-8\"\n os.environ[\"RAY_USE_XRAY\"] = \"1\"\n print(a3c.DEFAULT_CONFIG)\n MyLauncher().train_main()","sub_path":"reinforcement_learning/rl_network_compression_ray_custom/src/train-ray.py","file_name":"train-ray.py","file_ext":"py","file_size_in_byte":1885,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"118471557","text":"# coding: utf-8\nimport logging\n\nimport future.utils\n\nimport modernrpc.compat\nfrom modernrpc.core import RpcResult, registry, REQUEST_KEY, ENTRY_POINT_KEY, PROTOCOL_KEY, HANDLER_KEY\nfrom modernrpc.exceptions import (\n RPCException,\n RPC_METHOD_NOT_FOUND,\n RPC_INTERNAL_ERROR,\n RPC_INVALID_PARAMS\n)\n\nlogger = logging.getLogger(__name__)\n\n\nclass RPCHandler(object):\n protocol = None\n\n def __init__(self, entry_point):\n self.entry_point = entry_point\n\n @staticmethod\n def valid_content_types():\n raise NotImplementedError(\"You must override valid_content_types()\")\n\n def can_handle(self, request):\n return request.content_type.lower() in self.valid_content_types()\n\n def parse_request(self, request_body):\n \"\"\"Parse given request body and build a RPC request wrapper\"\"\"\n raise NotImplementedError()\n\n def validate_request(self, rpc_request):\n \"\"\"Check current request to ensure it is valid regarding protocol specifications\n\n Default implementation does nothing\n :rpc_request: The request to validate\n :type rpc_request: RPCRequest\n \"\"\"\n pass\n\n def process_request(self, request, rpc_request):\n \"\"\"\n :param request:\n :type rpc_request: HttpRequest\n :param rpc_request:\n :type rpc_request: RpcRequest\n :return:\n :rtype: RpcResult\n \"\"\"\n rpc_result = RpcResult(rpc_request.request_id)\n try:\n self.validate_request(rpc_request)\n except RPCException as exc:\n rpc_result.set_error(exc.code, exc.message)\n return rpc_result\n\n _method = registry.get_method(rpc_request.method_name, self.entry_point, self.protocol)\n if not _method:\n rpc_result.set_error(RPC_METHOD_NOT_FOUND, 'Method not found: \"{}\"'.format(rpc_request.method_name))\n return rpc_result\n\n if not _method.check_permissions(request):\n rpc_result.set_error(\n RPC_INTERNAL_ERROR, 'Authentication failed when calling \"{}\"'.format(rpc_request.method_name)\n )\n return rpc_result\n\n args, kwargs = rpc_request.args, rpc_request.kwargs\n # If the RPC method needs to access some configuration, update kwargs dict\n if _method.accept_kwargs:\n kwargs.update({\n REQUEST_KEY: request,\n ENTRY_POINT_KEY: self.entry_point,\n PROTOCOL_KEY: self.protocol,\n HANDLER_KEY: self,\n })\n\n if future.utils.PY2:\n method_std, encoding = _method.str_standardization, _method.str_std_encoding\n args = modernrpc.compat.standardize_strings(args, strtype=method_std, encoding=encoding)\n kwargs = modernrpc.compat.standardize_strings(kwargs, strtype=method_std, encoding=encoding)\n\n logger.debug('Params: args = %s - kwargs = %s', args, kwargs)\n\n try:\n # Call the rpc method, as standard python function\n rpc_result.set_success(_method.function(*args, **kwargs))\n\n except TypeError as te:\n # If given params cannot be transmitted properly to python function\n rpc_result.set_error(RPC_INVALID_PARAMS, \"Invalid parameters: {}\".format(te))\n\n except RPCException as re:\n rpc_result.set_error(re.code, re.message, data=re.data)\n\n except Exception as exc:\n rpc_result.set_error(RPC_INTERNAL_ERROR, \"Internal error: {}\".format(exc))\n\n return rpc_result\n\n def build_response_data(self, result):\n \"\"\"\n :param result:\n :type result: modernrpc.core.RpcResult\n :return:\n \"\"\"\n raise NotImplementedError()\n","sub_path":"modernrpc/handlers/base.py","file_name":"base.py","file_ext":"py","file_size_in_byte":3719,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"415222231","text":"from tkinter import *\nfrom tkinter import ttk\nfrom PIL import ImageTk, Image\nfrom tkinter import filedialog\nimport os\n\n\nimport driver_backend\n\nfilename=''\nsave_dir='driver_images/'\nsave_img=''\nimage_path=''\n\n\"\"\" check for folder exist otherwise create it \"\"\"\nif not os.path.exists('driver_images'):\n os.makedirs('driver_images')\n\ndef save_image():\n #if not str(os.path.exists(filena)):\n #print(\"image path is\"+image_path)\n save_img.save(image_path,'JPEG')\n\n\n\ndef add_command():\n #print(\"image path = \"+image_path)\n driver_backend.insert(ID_text.get(),name_text.get(),vehicle_text.get(),plate_text.get(),location_text.get(),image_path)\n view_command()\n save_image()\n clear_textfield()\n\ndef view_command():\n tree.delete(*tree.get_children())\n for row in driver_backend.view():\n tree.insert(\"\",END,values=row)\n tree.column(\"#1\", width=0)\n\ndef get_selected_row(event):\n\n clear_textfield()\n global selected_tuple\n for selected_tuple in tree.selection():\n global id\n id,emp_id,name,vehicle,plate_no,work_location,image_path = tree.item(selected_tuple, 'values')\n e1.insert(END, emp_id)\n e2.insert(END, name)\n e3.insert(END, vehicle)\n e4.insert(END, plate_no)\n e5.insert(END, work_location)\n display_image(image_path)\n\ndef clear_textfield():\n e1.delete(0,END)\n e2.delete(0,END)\n e3.delete(0,END)\n e4.delete(0,END)\n e5.delete(0,END)\n\ndef update_command():\n #print(image_path)\n driver_backend.update(id,ID_text.get(),name_text.get(),vehicle_text.get(),plate_text.get(),location_text.get(),image_path)\n save_image()\n view_command()\n clear_textfield()\n\n\ndef search_command():\n tree.delete(*tree.get_children())\n for row in driver_backend.search(ID_text.get(),name_text.get(),vehicle_text.get(),plate_text.get(),location_text.get()):\n tree.insert(\"\",END,values=row)\n\ndef delete_command():\n driver_backend.delete(id)\n view_command()\n\nwindow=Tk()\n\n\nwindow.wm_title(\"Drivers Details\")\n\nl1=Label(window,text=\"ID No:\")\nl1.grid(row=0,column=0)\n\nl2=Label(window,text=\"Name\")\nl2.grid(row=0,column=2)\n\nl3=Label(window,text=\"Vehicle\")\nl3.grid(row=1,column=0)\n\nl4=Label(window,text=\"Plate:\")\nl4.grid(row=1,column=2)\n\nl5=Label(window,text=\"Work Location:\")\nl5.grid(row=2,column=0)\n\nl6=Label(window,text=\"Upload Photo\")\nl6.grid(row=2,column=2)\n\nb1=Button(window,text=\"view All\", width=12,command=view_command)\nb1.grid(row=4,column=0)\n\nb2=Button(window,text=\"Search\", width=12,command=search_command)\nb2.grid(row=4,column=1)\n\nb3=Button(window,text=\"Add\", width=12,command=add_command)\nb3.grid(row=4,column=2)\n\nb4=Button(window,text=\"Update\", width=12,command=update_command)\nb4.grid(row=4,column=3)\n\nb5=Button(window,text=\"Delete\", width=12,command=delete_command)\nb5.grid(row=4,column=4)\n\nb6=Button(window,text=\"Close\", width=12,command=window.destroy)\nb6.grid(row=4,column=5)\n\nID_text=StringVar()\ne1=Entry(window,textvariable=ID_text)\ne1.grid(row=0,column=1)\n\nname_text=StringVar()\ne2=Entry(window,textvariable=name_text)\ne2.grid(row=0,column=3)\n\nvehicle_text=StringVar()\ne3=Entry(window,textvariable=vehicle_text)\ne3.grid(row=1,column=1)\n\nplate_text=StringVar()\ne4=Entry(window,textvariable=plate_text)\ne4.grid(row=1,column=3)\n\nlocation_text=StringVar()\ne5=Entry(window,textvariable=location_text)\ne5.grid(row=2,column=1)\n\n\"\"\" Treeview \"\"\"\ntree= ttk.Treeview(window, column=(\"ID\",\"Employee ID\", \"Name\", \"Vehicle\",\" Plate No:\",\"Work Location\"), show='headings')\ntree.heading(\"#1\", text=\"ID\")\ntree.heading(\"#2\", text=\"Employee ID\")\ntree.heading(\"#3\", text=\"Name\")\ntree.heading(\"#4\", text=\"Vehicle\")\ntree.heading(\"#5\", text=\"Plate No:\")\ntree.heading(\"#6\", text=\"Work Location\")\ntree.grid(row=6,column=0,rowspan=6,columnspan=7)\n\ntree.bind(\"<>\",get_selected_row)\n\n\"\"\" upload image\"\"\"\ndef openfn():\n global filename\n filename= filedialog.askopenfilename(title='open')\n\n\ndef open_img():\n openfn()\n global image_path, save_img\n image_path = getImagePath(filename)\n #print(\"image path = \"+image_path)\n save_img=Image.open(filename)\n img = Image.open(filename)\n #img.save(image_name,'JPEG')\n img = img.resize((55, 65), Image.ANTIALIAS)\n img = ImageTk.PhotoImage(img)\n panel = Label(window, image=img)\n panel.image = img\n panel.grid(row=0,column=4,rowspan=3,columnspan=2)\n\ndef display_image(image_path):\n img = Image.open(image_path)\n img = img.resize((55, 65), Image.ANTIALIAS)\n img = ImageTk.PhotoImage(img)\n panel = Label(window, image=img)\n panel.image = img\n panel.grid(row=0,column=4,rowspan=3,columnspan=2)\n\n\ndef getImagePath(filename):\n global filena\n filena = filename.split('/')[-1]\n new_path = save_dir+filena\n return new_path\n\n\nbtn = Button(window, text='open image', command=open_img).grid(row=2,column=3)\n\nwindow.mainloop()\n","sub_path":"drivfront.py","file_name":"drivfront.py","file_ext":"py","file_size_in_byte":4854,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"532657438","text":"\"\"\"\nProgram that only sends data 5 time a second. So we can adjust the time to the Computetime of the PC,\nto get mostly lag free images. So the Information we extract from the images are still relevant.\n\"\"\"\nfrom rplidar import RPLidar as rp\nimport time\nimport multiprocessing\nimport cv2\nimport numpy as np\n\n\nclass Lidar:\n\t\n\tdef __init__(self, buffer):\n\t\tself.__buffer__ = buffer\n\t\tself.lidar = rp('/dev/tty.SLAB_USBtoUART')\n\t\ttime.sleep(2)\n\t\n\tdef scan(self):\n\t\tinter = self.lidar.iter_measurments(0)\n\t\tscan = []\n\t\tst = time.time()\n\t\ttry:\n\t\t\tfor i in inter:\n\t\t\t\tn, q, a, d = i\n\t\t\t\tif n:\n\t\t\t\t\tif time.time() > st:\n\t\t\t\t\t\tself.__buffer__.put(scan)\n\t\t\t\t\t\tprint(\"Scan\")\n\t\t\t\t\t\tst += 0.2\n\t\t\t\t\tscan = []\n\t\t\t\t\tscan.append((q, a, d))\n\t\t\t\telse:\n\t\t\t\t\tscan.append((q, a, d))\n\t\tfinally:\n\t\t\tself.stop()\n\t\n\tdef stop(self):\n\t\tself.lidar.stop()\n\t\tself.lidar.stop_motor()\n\t\tself.lidar.disconnect()\n\n\nclass LidarFunktions:\n\tdef __init__(self, position=(3500, 3500)):\n\t\tself.position = position\n\t\n\t@staticmethod\n\tdef get_coords(d, r):\n\t\t\"\"\"\n\t\t:param d: float() - degree\n\t\t:param r: float() - radius, distance in mm\n\t\t:return: tuple() - as coordinates\n\t\t\"\"\"\n\t\tx = int(round(np.cos(d * np.pi / 180) * r, 1))\n\t\ty = int(round(np.sin(d * np.pi / 180) * r, 1))\n\t\treturn x, y\n\t\n\t@staticmethod\n\tdef map_coords(points, position):\n\t\t\"\"\"\n\t\tfunction to transform points into map\n\t\t:param points: tuple() - points\n\t\t:param position: tuple() - position\n\t\t:return: tuple() - transformed points\n\t\t\"\"\"\n\t\treturn points[0] + position[0], points[1] + position[1]\n\t\n\tdef prepare_data(self, data, position):\n\t\txy_data = []\n\t\tfor q, d, r in data:\n\t\t\tx, y = self.get_coords(d, r)\n\t\t\tx, y = self.map_coords((x, y), position)\n\t\t\txy_data.append((x, y))\n\t\treturn np.array(xy_data)\n\t\n\t@staticmethod\n\tdef draw_line_map(map, data, color=200, thickness=5):\n\t\tlast_point = None\n\t\tfor x, y in data:\n\t\t\tif last_point is None:\n\t\t\t\tlast_point = (x, y)\n\t\t\telse:\n\t\t\t\tcv2.line(map, last_point, (x, y), color, thickness)\n\t\t\t\tlast_point = (x, y)\n\t\treturn map\n\t\n\tdef main(self, buffer):\n\t\twhile True:\n\t\t\tif not buffer.empty():\n\t\t\t\tprint(\"Scan1\")\n\t\t\t\tdata = buffer.get()\n\t\t\t\tpre_data = self.prepare_data(data=data, position=self.position)\n\t\t\t\tzeroMap = np.zeros((7000, 7000), np.uint8)\n\t\t\t\timage = self.draw_line_map(zeroMap, pre_data)\n\t\t\t\tcv2.imshow(\"Image\", cv2.resize(image, (400, 400)))\n\t\t\t\tkey = cv2.waitKey(1)\n\t\t\t\tif key == ord('q'):\n\t\t\t\t\tcv2.destroyAllWindows()\n\t\t\t\t\tself.stop()\n\t\t\telse:\n\t\t\t\ttime.sleep(0.1)\n\t\n\tdef stop(self):\n\t\tfor i in multiprocessing.active_children():\n\t\t\ti.terminate()\n\t\t\tprint(i)\n\t\texit()\n\n\nbuffer = multiprocessing.Queue()\n\np1 = multiprocessing.Process(target=Lidar(buffer).scan)\np1.start()\nLidarFunktions().main(buffer)\n","sub_path":"test_process.py","file_name":"test_process.py","file_ext":"py","file_size_in_byte":2685,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"394392767","text":"import socket\nimport pickle\nfrom common import Message\n\nclass Network:\n def __init__(self):\n self.client = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n self.server = \"192.168.0.102\"\n self.port = 5555\n self.addr = (self.server, self.port)\n self.connected = False\n\n def connect(self):\n try:\n self.client.connect(self.addr)\n self.connected, clientID = pickle.loads(self.client.recv(2048))\n return clientID\n except Exception as e:\n print(e)\n\n def send(self, messType, data):\n try:\n self.client.sendall(pickle.dumps(Message(messType, data)))\n if messType == 'get':\n return pickle.loads(self.client.recv(2048*4)).read()\n # send a confirmation? is this all handled by sendall?\n except socket.error as e:\n print(e)\n","sub_path":"network.py","file_name":"network.py","file_ext":"py","file_size_in_byte":888,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"176394156","text":"class Solution:\n def closedIsland(self, grid: List[List[int]]) -> int:\n cnt = 0\n m, n = len(grid), len(grid[0])\n for i in range(m):\n self.dfs(i, 0, grid)\n self.dfs(i, n - 1, grid)\n for j in range(n):\n self.dfs(0, j, grid)\n self.dfs(m - 1, j, grid)\n for i in range(1, m):\n for j in range(1, n):\n if grid[i][j] == 1:\n continue\n else:\n self.dfs(i, j, grid)\n cnt += 1\n return cnt\n\n def dfs(self, i, j, grid):\n if grid[i][j] == 1:\n return\n grid[i][j] = 1\n for a, b in [[1, 0], [-1, 0], [0, 1], [0, -1]]:\n new_i, new_j = i + a, j + b\n if new_i < 0 or new_i >= len(grid) or new_j < 0 or new_j >= len(grid[0]):\n continue\n self.dfs(new_i, new_j, grid)\n\n","sub_path":"1254_Number_of_Closed_Islands/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":914,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"455187979","text":"#\n\nimport hy # NOQA\n\nfrom hy.models.expression import HyExpression\nfrom hy.models.symbol import HySymbol\nfrom hy.models.string import HyString\nfrom hy.models.list import HyList\nfrom hy.models.dict import HyDict\n\nfrom hy.macros import macro\n\n\ndef router(tree, rkwargs=None):\n tree.pop(0)\n path = tree.pop(0)\n tree.insert(0, HySymbol(\"fn\"))\n\n route = HyExpression([HySymbol(\".route\"),\n HySymbol(\"app\"),\n path])\n\n if rkwargs:\n route = HyExpression([HySymbol(\"kwapply\"),\n route,\n HyDict({HyString(\"methods\"): rkwargs})])\n\n return HyExpression([HySymbol(\"decorate_with\"),\n route,\n tree])\n\n\n@macro(\"route\")\ndef route_macro(tree):\n return router(tree)\n\n\n@macro(\"post_route\")\ndef post_route_macro(tree):\n return router(tree, rkwargs=HyList([HyString(\"POST\")]))\n\n\nfrom app import app\n\nif __name__ == '__main__':\n app.run(debug=True)\n","sub_path":"site/shim.py","file_name":"shim.py","file_ext":"py","file_size_in_byte":1015,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"265823162","text":"#!/bin/python3\n\nimport math\nimport os\nimport random\nimport re\nimport sys\n\n\n#\n# Complete the 'partitionArray' function below.\n#\n# The function is expected to return a STRING.\n# The function accepts following parameters:\n# 1. INTEGER k\n# 2. INTEGER_ARRAY numbers\n#\nfrom itertools import combinations\n\n## Here we generate all sublists\ndef getSublists(numbers):\n sublists = [\n numbers[i:j]\n for i in range(0, len(numbers) + 1)\n for j in range(i + 1, len(numbers) + 1)\n ]\n return sublists\n\n\ndef partitionArray(k, numbers):\n import itertools\n\n sublists = getSublists(numbers)\n\n lenKSublists = [sublist for sublist in sublists if len(sublist) == k]\n for numLists in range(0, len(lenKSublists) + 1):\n for combination in itertools.combinations(lenKSublists, numLists):\n areEqual = True\n for num in numbers:\n if num in combination:\n combination = combination.remove(num)\n else:\n areEqual = False\n break\n if areEqual == True:\n return \"Yes\"\n return \"No\"\n\n\n#\n# Complete the 'totalTriplets' function below.\n#\n# The function is expected to return a LONG_INTEGER.\n# The function accepts following parameters:\n# 1. INTEGER_ARRAY capacity\n# 2. LONG_INTEGER desiredCapacity\n#\n\n\ndef totalTriplets(capacity, desiredCapacity):\n numWorkers = len(capacity)\n ## We will iterate over the list in pairs and pick the third triplet randomly from the remainder of the list\n numValidTriplets = 0\n ## This makes sure we don't accidentally add the same triplet twice\n knownTrips = []\n\n ## Create a dictionary of the capacities and their indices w/ dict comp\n capacityDict = {cap: capInd for capInd, cap in enumerate(capacity)}\n\n ## First lets iterate over the workers and retreive all adjacent worker paris\n for capInd in range(numWorkers - 1):\n adjWorkers = (capacity[capInd], capacity[capInd + 1])\n ## Then find their work value\n workVal = adjWorkers[0] * adjWorkers[1]\n\n ## If the current workVal is zero, then any value but zero is not achievable\n if workVal == 0:\n if desiredCapacity != 0:\n continue\n target = 0\n ## If not then we can get the target by default\n else:\n target = desiredCapacity / workVal\n\n ## We say a triplet exists if the set of triplet indices has never been seen before\n if target in capacityDict and capacityDict[target] not in {capInd, capInd + 1}:\n triplet = set([capInd, capInd + 1, capacityDict[target]])\n if triplet not in knownTrips:\n knownTrips.append(triplet)\n numValidTriplets += 1\n return numValidTriplets\n\n","sub_path":"week-7/Python/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":2794,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"175895821","text":"import torch\nimport numpy as np\n\n\nclass BatchNorm1d:\n def __init__(self):\n self.eps = 1e-5\n self.weight = None\n self.bias = None\n\n self.num = None\n self.std = None\n self.dw = None\n self.db = None\n\n def __call__(self, x):\n self.num = np.shape(x)[0]\n mean = np.mean(x, axis=0, keepdims=True)\n var = np.var(x, axis=0, keepdims=True)\n self.sqrt = np.sqrt(var + self.eps)\n self.std = (x - mean) / self.sqrt\n out = self.std * self.weight + self.bias\n return out\n\n def backward(self, d_loss):\n std_t = self.std.T\n shape_t = np.shape(std_t)\n r = np.zeros([shape_t[0], shape_t[1], shape_t[1]])\n shift_eye = np.eye(shape_t[1]) * shape_t[1] - 1\n for i in range(shape_t[0]):\n r[i] = std_t[i][:, np.newaxis] * std_t[i][np.newaxis, :]\n r[i] = shift_eye - r[i]\n\n u = self.weight / shape_t[1] / self.sqrt\n u = u.T\n y = r * u[:, np.newaxis]\n\n dx = np.zeros(shape_t)\n for i in range(shape_t[0]):\n dx[i] = np.dot(d_loss.T[i], y[i])\n dx = dx.T\n\n self.dw = np.sum(self.std * d_loss, axis=0)\n self.db = np.sum(d_loss, axis=0)\n\n return dx\n\n\nnp.set_printoptions(precision=8, suppress=True, linewidth=120)\nnp.random.seed(123)\ntorch.random.manual_seed(123)\n\nx_numpy = np.array(np.random.random((3, 5)), dtype=np.float64)\nweight_numpy = np.array(np.random.random((5,)), dtype=np.float64)\nbias_numpy = np.array(np.random.random((5,)), dtype=np.float64)\nd_loss_numpy = np.array(np.random.random((3, 5)), dtype=np.float64)\n\nx_tensor = torch.tensor(x_numpy, requires_grad=True)\nweight_tensor = torch.tensor(weight_numpy, requires_grad=True)\nbias_tensor = torch.tensor(bias_numpy, requires_grad=True)\nd_loss_tensor = torch.tensor(d_loss_numpy, requires_grad=True)\n\nbatch_norm_numpy = BatchNorm1d()\nbatch_norm_numpy.weight = weight_numpy\nbatch_norm_numpy.bias = bias_numpy\n\nbatch_norm_tensor = torch.nn.BatchNorm1d(5).double()\nbatch_norm_tensor.weight = torch.nn.Parameter(weight_tensor, requires_grad=True)\nbatch_norm_tensor.bias = torch.nn.Parameter(bias_tensor, requires_grad=True)\n\noutput_numpy = batch_norm_numpy(x_numpy)\noutput_tensor = batch_norm_tensor(x_tensor)\noutput_tensor.backward(d_loss_tensor)\n\ndx_numpy = batch_norm_numpy.backward(d_loss_numpy)\ndx_tensor = x_tensor.grad\n\ndw_numpy = batch_norm_numpy.dw\ndw_tensor = batch_norm_tensor.weight.grad\n\ndb_numpy = batch_norm_numpy.db\ndb_tensor = batch_norm_tensor.bias.grad\n\nprint(\"output_numpy \\n\", output_numpy)\nprint(\"output_tensor \\n\", output_tensor.data.numpy())\n\nprint(\"dx_numpy \\n\", dx_numpy)\nprint(\"dx_tensor \\n\", dx_tensor.data.numpy())\n\nprint(\"dw_numpy \\n\", dw_numpy)\nprint(\"dw_tensor \\n\", dw_tensor.data.numpy())\n\nprint(\"db_numpy \\n\", db_numpy)\nprint(\"db_tensor \\n\", db_tensor.data.numpy())","sub_path":"CNN/batch_normalization.py","file_name":"batch_normalization.py","file_ext":"py","file_size_in_byte":2865,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"174469500","text":"import convex_hull\nimport optimal_path\nimport nacitanie_dat\nfrom matplotlib import pyplot as plt\n\ndef graph():\n plt.figure(map_name)\n # nakresli jednotlive prekazky\n for i in range(len(x_coordinates)):\n plt.scatter(x_coordinates[i], y_coordinates[i], color=\"black\", s=20, zorder=2)\n plt.fill(x_coordinates[i], y_coordinates[i], color=\"#553B8F\", alpha=0.75)\n\n # nakresli start a end\n plt.scatter(start_position[0], start_position[1], color=\"black\", s=70)\n plt.text(start_position[0] - 2, start_position[1] - 4, \"START\", fontsize=6)\n plt.scatter(end_position[0], end_position[1], color=\"black\", s=70)\n plt.text(end_position[0] - 1.5, end_position[1] - 4, \"END\", fontsize=6)\n\n # nakresli konvexne obalky\n for convex_hull in convex_hulls:\n points_x = []\n points_y = []\n for coordinates in convex_hull:\n points_x.append(coordinates[0])\n points_y.append(coordinates[1])\n\n plt.scatter(points_x, points_y)\n plt.plot(points_x, points_y, color=\"orange\")\n\n # nakresli optimalnu cestu\n x_path = []\n y_path = []\n for point in path:\n x_path.append(point[0])\n y_path.append(point[1])\n\n plt.scatter(x_path, y_path)\n plt.plot(x_path, y_path, \"--\")\n\n return plt.show()\n\nconvex_hulls = convex_hull.convex_hulls\npath = optimal_path.path\nx_coordinates = nacitanie_dat.x_coordinates()\ny_coordinates = nacitanie_dat.y_coordinates()\nstart_position = nacitanie_dat.start_position()\nend_position = nacitanie_dat.end_position()\nmap_name = nacitanie_dat.map_name()","sub_path":"zobrazenie_dat.py","file_name":"zobrazenie_dat.py","file_ext":"py","file_size_in_byte":1572,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"378906170","text":"#!/usr/bin/env python\n# -*- coding:utf-8 -*-\n\nimport re\nimport os\nimport sys\n\ndockerfile_name_re = re.compile('Dockerfile-(?P[^.]+)(?P(\\.gpu)?)')\n\n\ndef gen_tag_from_filepath(dockerfile_path):\n # sample input: dl/tensorflow/1.0.1/Dockerfile-py3.gpu\n # sample output: floydhub/tensorflow:1.0.1-gpu-py3\n abs_path = os.path.realpath(dockerfile_path)\n\n path_parts = abs_path.split(os.sep)\n\n if len(path_parts) < 4:\n return None\n # we only care about the last 4 segments\n path_parts = path_parts[-4:]\n\n project = path_parts[1]\n version = path_parts[2]\n tag_components = ['floydhub/%s:%s' % (project, version)]\n\n dockerfile_name = path_parts[-1]\n match = dockerfile_name_re.match(dockerfile_name)\n if not match:\n return None\n\n if match.group('arch') == '.gpu':\n tag_components.append('gpu')\n tag_components.append(match.group('env'))\n\n return '-'.join(tag_components)\n\n\ndef find_matrix_from_dockerfile(dockerfile_path):\n abs_path = os.path.realpath(dockerfile_path)\n path_parts = abs_path.split(os.sep)\n return os.path.join(os.sep.join(path_parts[:-2]), 'matrix.yml')\n\n\ndef assert_image_tag_from_dockerfile(logger, dockerfile):\n if os.path.isdir(dockerfile):\n logger.error('%s is a directory.', dockerfile)\n sys.exit(1)\n\n image_tag = gen_tag_from_filepath(dockerfile)\n if not image_tag:\n logger.error('Failed to generate image tag from filename: %s',\n dockerfile)\n sys.exit(1)\n\n return image_tag\n\n\ndef gen_version_target_from_tag(img_tag):\n \"\"\"\n sample input: 'tensorflow:1.0.1-gpu-py3'\n sample output: ('1.0.1', 'py3.gpu')\n \"\"\"\n img_commit = img_tag.split(':')[-1]\n version, target = img_commit.split('-', 1)\n target = '.'.join(reversed(target.split('-', 1)))\n return version, target\n","sub_path":"floydker/src/floydker/utils.py","file_name":"utils.py","file_ext":"py","file_size_in_byte":1851,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"402438596","text":"import numpy as np\nimport pandas as pd\nfrom new_project.utilis import *\nfrom new_project.BPR import *\nfrom new_project.NegativeSampling import *\nfrom new_project.PreProcess import *\nimport pickle\n\n\nclass SGDOptimizer:\n def __init__(self, mf_model, max_epoch_num, bias_epoch_num, epsilon, allowed_dec):\n self.max_epoch_num = max_epoch_num\n self.bias_epoch_num = bias_epoch_num\n self.eps = epsilon\n self.allowed_dec_on_valid = allowed_dec\n self.model = mf_model\n self.curr_t_err = - np.Inf\n self.prev_t_err = - np.Inf\n self.curr_v_err = - np.Inf\n self.prev_v_err = - np.Inf\n self.best_v_err = - np.Inf\n self.curr_dec_count = 0\n self.convergence = False\n self.right_count_t = 0\n self.right_count_v = 0\n self.best_epoch = 0\n self.best_count_v = 0\n self.curr_epoch = 1\n\n def run_epoch(self, train_data, user_index, item_index, model_type='bias'):\n # np.seterr(all='raise')\n self.curr_t_err = 0\n self.right_count_t = 0\n for m, i, j in train_data:\n m, i, j = user_index[m], item_index[i], item_index[j]\n new_bi = self.model.update_params('b_i', i, j, m, model_type=model_type)\n new_bj = self.model.update_params('b_j', i, j, m, model_type=model_type)\n s_m_i_j_old = self.model.b_i[i] - self.model.b_i[j] # TODO remove later\n\n if model_type == 'full':\n new_um = self.model.update_params('u_m', i, j, m, model_type=model_type)\n new_vi = self.model.update_params('v_i', i, j, m, model_type=model_type)\n new_vj = self.model.update_params('v_j', i, j, m, model_type=model_type)\n s_m_i_j_old += np.dot(self.model.u_m[:, m], self.model.v_i[:, i]-self.model.v_i[:, j]) # TODO remove later\n\n # update the model with the new parameters\n self.model.b_i[i] = new_bi\n self.model.b_i[j] = new_bj\n s_m_i_j = new_bi - new_bj\n\n if model_type == 'full':\n self.model.u_m[:, m] = new_um\n self.model.v_i[:, i] = new_vi\n self.model.v_i[:, j] = new_vj\n s_m_i_j += np.dot(new_um, new_vi-new_vj)\n self.curr_t_err += np.log(sigmoid(s_m_i_j))\n if s_m_i_j > 0:\n self.right_count_t += 1\n print('Train Log Error = ', self.curr_t_err, ', Train Reg Error = ', self.calc_reg(model_type=model_type))\n self.curr_t_err -= self.calc_reg(model_type=model_type)\n return\n\n def calc_error(self, valid_data, user_index, item_index, model_type='bias'):\n s_m_i_j = 0\n self.curr_v_err = 0\n self.right_count_v = 0\n for m, i, j in valid_data:\n m, i, j = user_index[m], item_index[i], item_index[j]\n i_j_bias_difference = self.model.b_i[i] - self.model.b_i[j]\n if model_type == 'full':\n s_m_i_j = np.dot(self.model.u_m[:, m], (self.model.v_i[:, i] - self.model.v_i[:, j]))\n self.curr_v_err += np.log(sigmoid(s_m_i_j + i_j_bias_difference))\n if s_m_i_j > 0:\n self.right_count_v += 1\n reg_error = self.calc_reg(model_type=model_type)\n self.curr_v_err -= reg_error\n return\n\n def calc_reg(self, model_type='bias'):\n b_i_reg = np.sum(self.model.b_i ** 2) * (self.model.hyper_set['alpha_b'] / 2)\n if model_type == 'full':\n u_m_reg = np.sum(np.linalg.norm(self.model.u_m, axis=0)) * (self.model.hyper_set['alpha_u'] / 2)\n v_i_reg = np.sum(np.linalg.norm(self.model.v_i, axis=0)) * (self.model.hyper_set['alpha_i'] / 2)\n else:\n u_m_reg = 0\n v_i_reg = 0\n return b_i_reg + u_m_reg + v_i_reg\n\n def check_convergence(self, validation_data, curr_epoch, user_index, item_index, model_type='bias', is_valid=True):\n print('Current Train Objective Function =', self.curr_t_err, ', Right Count Train = ', self.right_count_t)\n delta_train = self.curr_t_err - self.prev_t_err # expect to be positive if the model improves\n\n if is_valid:\n # Validation increase criterion\n self.calc_error(validation_data, user_index, item_index, model_type=model_type)\n print('Current Validation Objective Function =', self.curr_v_err, ', Right Count Validation = ', self.right_count_v)\n if model_type == 'full':\n hit_rate_k, mpr = calc_metric(validation_data, self.model, [1, 10, 50, 1000], user_index, item_index)\n print('Hit Rate @ 1, 10, 50, 1000 = ', hit_rate_k, ', MPR = ', mpr)\n\n delta_valid = self.curr_v_err - self.prev_v_err\n if delta_valid < 0:\n self.curr_dec_count += 1\n if self.curr_dec_count > self.allowed_dec_on_valid:\n self.convergence = True\n print('~~~ Validation increase criterion IN ~~~')\n if self.curr_v_err > self.best_v_err:\n self.model.u_m_best = self.model.u_m.copy()\n self.model.v_i_best = self.model.v_i.copy()\n self.model.b_i_best = self.model.b_i.copy()\n self.best_epoch = self.curr_epoch\n self.best_count_v = self.right_count_v\n self.best_v_err = self.curr_v_err\n\n # Max epoch num criterion\n if curr_epoch >= self.max_epoch_num:\n self.convergence = True\n self.model.u_m_best = self.model.u_m.copy()\n self.model.v_i_best = self.model.v_i.copy()\n self.model.b_i_best = self.model.b_i.copy()\n self.best_epoch = self.curr_epoch\n self.best_count_v = self.right_count_v\n self.best_v_err = self.curr_v_err\n # added now - update the model on the last epoch so the best model is not the initialized one.\n print('~~~ Max epoch num criterion IN ~~~')\n\n # Train epsilon change criterion - check only after finishing the second epoch with the latent vectors\n if self.curr_epoch > self.bias_epoch_num + 1:\n if delta_train < self.eps:\n self.convergence = True\n print('~~~ Train epsilon change criterion IN ~~~')\n\n self.prev_t_err = self.curr_t_err\n self.prev_v_err = self.curr_v_err\n return\n\n def train_model(self, train_data_list, validation_data, user_index, item_index, model_type='bias', is_valid=True):\n while not self.convergence:\n if self.curr_epoch > self.bias_epoch_num:\n model_type = 'full'\n print('Epoch: ', self.curr_epoch)\n self.run_epoch(train_data_list[self.curr_epoch-1], user_index, item_index, model_type=model_type)\n self.check_convergence(validation_data, self.curr_epoch, user_index, item_index, model_type=model_type,\n is_valid=is_valid)\n self.curr_epoch += 1\n if self.curr_epoch % 5 == 0:\n self.model.hyper_set['lr'] = self.model.hyper_set['lr']*0.9\n return\n\n\nif __name__ == '__main__':\n # ~~~~~~~~~~~~~~~~~~~~~ Model with Best HP Set found Results for Report ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n # hyper_set = {'alpha_u': 10, 'alpha_i': 10, 'alpha_b': 10, 'dim': 7, 'lr': 0.001}\n # hyper_set = {'alpha_u': 0.01, 'alpha_i': 0.01, 'alpha_b': 0.1, 'dim': 60, 'lr': 0.05, 'sigma': 0.1}\n # t_data, items_index, users_index, bpr_model, all_epochs_data_lst, valid_data = pre_process(hyper_set, epoch_num=50,\n # read_directory=True,\n # sample_method='P',\n # write_num=2)\n # sgd = SGDOptimizer(mf_model=bpr_model, max_epoch_num=len(all_epochs_data_lst), bias_epoch_num=2, epsilon=-np.inf,\n # allowed_dec=3)\n # sgd.train_model(all_epochs_data_lst, valid_data, users_index, items_index, model_type='bias') # is_valif=False, valid_data=None\n #\n # calc_metric(valid_data, sgd.model, [1,10,50], users_index, items_index)\n\n # hyper_set = {'alpha_u': 0.01, 'alpha_i': 0.01, 'alpha_b': 0.1, 'dim': 60, 'lr': 0.05, 'sigma': 0.1}\n # t_data, items_index, users_index, bpr_model, all_epochs_data_lst, valid_data = pre_process(hyper_set, epoch_num=50,\n # read_directory=True,\n # sample_method='U',\n # write_num=2)\n # sgd = SGDOptimizer(mf_model=bpr_model, max_epoch_num=len(all_epochs_data_lst), bias_epoch_num=2, epsilon=-np.inf,\n # allowed_dec=3)\n # sgd.train_model(all_epochs_data_lst, valid_data, users_index, items_index, model_type='bias')\n #\n # calc_metric(valid_data, sgd.model, [1, 10, 50], users_index, items_index)\n\n # ~~~~~~~~~~~~~~~~~~~~~ Final Model for Test Result - No Validation Data ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n method = ['P', 'U']\n epoch_num = [26, 29]\n read_d = [False, False]\n model_object_dict = {}\n test_df_dict = {}\n for i in range(2):\n print('~~~~~~~~~~~~~ Starting ', method[i])\n hyper_set = {'alpha_u': 0.01, 'alpha_i': 0.01, 'alpha_b': 0.1, 'dim': 60, 'lr': 0.05, 'sigma': 0.1}\n print(method[i], ': Data Preparation')\n t_data, items_index, users_index, bpr_model, all_epochs_data_lst, valid_data = pre_process(hyper_set,\n epoch_num=epoch_num[i],\n read_directory=read_d[i],\n sample_method=method[i],\n write_num=1,\n if_test=True #added now\n )\n print('out')\n print(method[i], ': Fit Model')\n sgd = SGDOptimizer(mf_model=bpr_model, max_epoch_num=len(all_epochs_data_lst), bias_epoch_num=2, epsilon=-np.inf,\n allowed_dec=3)\n sgd.train_model(all_epochs_data_lst, valid_data, users_index, items_index, model_type='bias', is_valid=False)\n model_object_dict[method[i]] = sgd.model\n print(method[i], ': Test Calc')\n if method[i] == 'P':\n details = 'popularity'\n else:\n details = 'random'\n test_df = PostProcess_TestResult(sgd.model, users_index, items_index, details=details)\n test_df_dict[method[i]] = test_df\n\n\n\n\n\n\n\n\n\n\n\n\n\n","sub_path":"new_project/SGDOptimizer.py","file_name":"SGDOptimizer.py","file_ext":"py","file_size_in_byte":11179,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"500313087","text":"\n# Copyright (c) 2020, Romain Rouvoy\n# \n# All rights reserved.\n# \n# Redistribution and use in source and binary forms, with or without modification,\n# are permitted provided that the following conditions are met:\n# \n# * Redistributions of source code must retain the above copyright notice,\n# this list of conditions and the following disclaimer.\n# * Redistributions in binary form must reproduce the above copyright notice,\n# this list of conditions and the following disclaimer in the documentation\n# and/or other materials provided with the distribution.\n# \n# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS\n# \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT\n# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR\n# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER\n# OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\n# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\n# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\n# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF\n# LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING\n# NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS\n# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n\nimport argparse\nfrom .backend import DockerBackend\nfrom .distribution import NoDistribution, PoissonDistribution\n\nclass WorkloadCLI:\n def __init__(self):\n self.parser = argparse.ArgumentParser(description='Starts several containers in parallel.')\n self.parser.add_argument('input', type=str, help='commands file (.yaml)')\n self.parser.add_argument(\"-m\", \"--mean\", type=int, default=2,\n help=\"mean number of containers\")\n self.parser.add_argument(\"-s\", \"--seconds\", type=int, default=30,\n help=\"interval in seconds\")\n self.parser.add_argument(\"-t\", \"--times\", type=int, default=10,\n help=\"number of times\")\n self.parser.add_argument(\"--pull\", action=\"store_true\", help=\"Only pulls the images\")\n\n def generate_configuration(self):\n args = self.parser.parse_args()\n config = WorkloadConfiguration()\n config.input = args.input\n config.mean = args.mean\n config.seconds = args.seconds\n config.times = args.times\n config.pull = args.pull\n return config\n\n\nclass WorkloadConfiguration:\n def __init__(self):\n self.backend = DockerBackend()\n self.dist = PoissonDistribution()\n self.wait = NoDistribution()\n","sub_path":"pyworkload/configuration.py","file_name":"configuration.py","file_ext":"py","file_size_in_byte":2646,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"101967854","text":"class Solution:\n \"\"\"\n @param A: an integer array\n @return: nothing\n \"\"\"\n def sortIntegers2(self, A):\n # write your code here\n tmp = [0] * len(A)\n self.mergeSort(A, 0, len(A) - 1, tmp)\n\n # Quick Sort\n # Time: O(NLogN), Worst O(n^2)\n # Space: O(1), in-place\n def quickSort(self, A, start, end):\n if start >= end:\n return\n \n pivot = A[start + (end - start) // 2]\n \n left, right = start, end\n \n while left <= right:\n while left <= right and A[left] < pivot:\n left += 1\n \n while left <= right and A[right] > pivot:\n right -= 1\n \n if left <= right:\n A[left], A[right] = A[right], A[left]\n left += 1\n right -= 1\n \n self.quickSort(A, start, right)\n self.quickSort(A, left, end)\n \n # Merge Sort\n # Time: O(NlogN)\n # Space: O(N)\n # Stable \n def mergeSort(self, A, start, end, tmp):\n if start >= end:\n return\n \n mid = start + (end - start) // 2\n self.mergeSort(A, start, mid, tmp)\n self.mergeSort(A, mid + 1, end, tmp)\n self.merge(A, start, mid, end, tmp)\n \n def merge(self, A, start, mid, end, tmp):\n l, r = start, mid + 1\n index = start\n while l <= mid and r <= end:\n if A[l] <= A[r]:\n tmp[index] = A[l]\n l += 1\n else:\n tmp[index] = A[r]\n r += 1\n index += 1\n \n while l <= mid:\n tmp[index] = A[l]\n l += 1\n index += 1\n \n while r <= end:\n tmp[index] = A[r]\n r += 1\n index += 1\n \n for i in range(start, end + 1):\n A[i] = tmp[i]\n\n'''\n[3, 2, 1, 4, 5]\n2, 3\n1, 4\n5\n'''\nclass Solution2:\n \"\"\"\n @param A: an integer array\n @return: nothing\n \"\"\"\n def sortIntegers2(self, A):\n # write your code here\n self.mergeSortBottomUp(A)\n \n def mergeSortBottomUp(self, A):\n # This represent half of number of the element that you want to sort\n size = 1\n \n while size < len(A):\n # The max index is len(A) - size + 1, imagine the moment that size is greater than\n # half of the input array, the right half won't have numbers of size, but we still need to\n # sort the right half, so as long as we have a valid mid point which is 'index + size - 1'\n # we can proceed to merge sort.\n for index in range(0, len(A) - size + 1, size * 2):\n self.merge(A, index, index + size - 1, min(index + 2 * size - 1, len(A)- 1))\n size *= 2\n \n def merge(self, A, start, mid, end):\n tmp = [0] * (end - start + 1)\n \n l, r = start, mid + 1\n index = start\n \n while l <= mid and r <= end:\n if A[l] <= A[r]:\n tmp[index - start] = A[l]\n l += 1\n else:\n tmp[index - start] = A[r]\n r += 1\n index += 1\n \n while l <= mid:\n tmp[index - start] = A[l]\n l += 1\n index += 1\n \n while r <= end:\n tmp[index - start] = A[r]\n r += 1\n index += 1\n \n for i in range(start, end + 1):\n A[i] = tmp[i - start]","sub_path":"464_sort-integers-2/sort-integers-2.py","file_name":"sort-integers-2.py","file_ext":"py","file_size_in_byte":3534,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"315129376","text":"accounts = [[\"David\",\"David0@m.co\",\"David1@m.co\"],[\"David\",\"David3@m.co\",\"David4@m.co\"],[\"David\",\"David4@m.co\",\"David5@m.co\"],[\"David\",\"David2@m.co\",\"David3@m.co\"],[\"David\",\"David1@m.co\",\"David2@m.co\"]]\n\nimport collections\nclass UnionFind:\n def __init__(self, n):\n self.parent = list(range(n))\n\n def union(self, index1: int, index2: int):\n self.parent[self.find(index2)] = self.find(index1)\n\n def find(self, index: int) -> int:\n if self.parent[index] != index:\n self.parent[index] = self.find(self.parent[index])\n return self.parent[index]\n\n\nclass Solution:\n def accountsMerge(self, accounts):\n emailToIndex = dict()\n emailToName = dict()\n\n for account in accounts:\n name = account[0]\n for email in account[1:]:\n if email not in emailToIndex:\n emailToIndex[email] = len(emailToIndex)\n emailToName[email] = name\n print(emailToIndex)\n print(emailToName)\n\n uf = UnionFind(len(emailToIndex))\n for account in accounts:\n firstIndex = emailToIndex[account[1]]\n for email in account[2:]:\n uf.union(firstIndex, emailToIndex[email])\n\n indexToEmails = collections.defaultdict(list)\n for email, index in emailToIndex.items():\n index = uf.find(index)\n indexToEmails[index].append(email)\n\n ans = list()\n for emails in indexToEmails.values():\n ans.append([emailToName[emails[0]]] + sorted(emails))\n return ans\n\nx=Solution()\nx.accountsMerge(accounts)\n# 作者：LeetCode - Solution\n# 链接：https: // leetcode - cn.com / problems / accounts - merge / solution / zhang - hu - he - bing - by - leetcode - solution - 3\n# dyq /\n# 来源：力扣（LeetCode）\n# 著作权归作者所有。商业转载请联系作者获得授权，非商业转载请注明出处。","sub_path":"721.py","file_name":"721.py","file_ext":"py","file_size_in_byte":1926,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"54500374","text":"# -*- coding: utf-8 -*-\n\nfrom odoo import models, fields, api\n#from odoo.addons.base.models. res import res_request\nfrom odoo.exceptions import ValidationError\n\n# def referencable_models(self):\n# return res_request.referencable_models(\n# self, self.env.cr, self.env.uid, context=self.env.context)\n\n\nclass TodoTask(models.Model):\n _inherit = 'todoroc_app.todoroc_app'\n stage_id = fields.Many2one('todo.task.stage', 'Stage')\n tag_ids = fields.Many2many('todo.task.tag', string='Tags')\n refers_to = fields.Reference(\n [('res.user', 'User'), ('res.partner', 'Partner')],\n 'Refers to')\n\n stage_fold = fields.Boolean(\n 'Stage Folded?',\n compute='_compute_stage_fold',\n # store=False, # the default\n search='_search_stage_fold',\n inverse='_write_stage_fold'\n )\n\n @api.depends('stage_id.fold')\n def _compute_stage_fold(self):\n for task in self:\n task.stage_fold = task.stage_id.fold\n\n @staticmethod\n def _search_stage_fold(operator, value):\n return [('stage_id.fold', operator, value)]\n\n def _write_stage_fold(self):\n self.stage_id.fold = self.stage_fold\n\n stage_state = fields.Selection(\n related='stage_id.state',\n string='Stage State')\n\n# Constraints\n _sql_constraints = [(\n 'todo_task_name_unique',\n 'UNIQUE (name, user_id, active)',\n 'Task title must be unique!'\n )]\n\n # @api.one\n @api.constrains('name')\n def _check_name_size(self):\n if len(self.name) < 5:\n raise ValidationError('Title must have 5 chars!')\n\n # @api.one\n def compute_user_todo_count(self):\n self.user_todo_count = self.search_count(\n [('user_id', '=', self.user_id.id)])\n\n user_todo_count = fields.Integer(\n 'User To-Do Count',\n compute='compute_user_todo_count'\n )\n effort_estimate = fields.Integer('Effort Estimate')","sub_path":"models/model_tasks.py","file_name":"model_tasks.py","file_ext":"py","file_size_in_byte":1926,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"457705592","text":"def longestSubstring(string):\n dp = {}\n length = 0\n j = 0\n\n for i, c in enumerate(string):\n if c in dp: \n j = max(j, dp[c] + 1)\n length = max(length, i - j + 1)\n dp[c] = i\n return length","sub_path":"leetcode/longest_substring_wrc.py","file_name":"longest_substring_wrc.py","file_ext":"py","file_size_in_byte":233,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"411756928","text":"import sopel.module\nimport requests\nimport json\n\n@sopel.module.commands('urmom')\ndef sayJoke(bot,trigger):\n joke = getJoke()\n if joke:\n if trigger.group(2):\n bot.say('Hey, ' + trigger.group(2).strip() + '! ' + joke)\n else:\n bot.say(joke)\n else:\n bot.say('Please leave the mothers out of it.')\n \n\ndef getJoke():\n url = 'http://api.yomomma.info'\n page = requests.get(url)\n result = page.content\n jsonjoke = json.loads(result)\n joke = jsonjoke['joke']\n return joke\n","sub_path":"urmom.py","file_name":"urmom.py","file_ext":"py","file_size_in_byte":535,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"409072591","text":"import matplotlib.pyplot as plt\nimport seaborn as sns\nfrom sklearn.preprocessing import PolynomialFeatures\nfrom sklearn.linear_model import LinearRegression, Ridge\nfrom sklearn.pipeline import Pipeline\nimport numpy as np\n\n# We will create some x-values and randomly choose some as data points\nX = np.linspace(0, 10, 100)\n# We are fixing the random number seed for consistency\nrn = np.random.RandomState(0)\n# Shuffle the data for variety\nrn.shuffle(X)\n# Grab the first 30 of our shuffled points and sort them for plotting\nX = np.sort(X[:30])\n# Our output will be a quadratic function\ny = X**2\n# We will add some variance to the data so that it's more interesting\ny = y + (((np.random.rand(30) * 2) - 1) * 30)\n\n# Pipeline lets us setup a fixed number of steps for our modeling\nmodel = Pipeline([('poly', PolynomialFeatures(degree=6)), \\\n('linear', LinearRegression(fit_intercept=False))])\nregModel = Pipeline([('poly', PolynomialFeatures(degree=6)), \\\n('ridge', Ridge(alpha=5.0))])\n# Now we train on our data\nmodel = model.fit(X[:, np.newaxis], y)\nregModel = regModel.fit(X[:, np.newaxis], y)\n# Now we pridict\nX_plot = np.linspace(0, 10, 100)\nX_plot = X_plot[:, np.newaxis]\ny_plot = model.predict(X_plot)\nyReg_plot = regModel.predict(X_plot)\n\n# Plot data\nsns.set_style(\"darkgrid\")\nplt.plot(X_plot, y_plot, color='black')\nplt.plot(X_plot, yReg_plot, color='red')\nplt.scatter(X, y, marker='o')\nplt.xticks(())\nplt.yticks(())\nplt.tight_layout()\nplt.show()\n","sub_path":"code/overview/regularization/regularization_ridge.py","file_name":"regularization_ridge.py","file_ext":"py","file_size_in_byte":1450,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"614851855","text":"from pyVim.connect import SmartConnect\nfrom pyVmomi import vim\n\n\ndef main():\n service_instance = SmartConnect(host=\"10.144.208.13\", user=\"root\", pwd=\"PE3h3r$!\", disableSslCertValidation=True)\n\n print(\"ESXi/vCenter Time\")\n print(\" - %s\" % service_instance.CurrentTime())\n content = service_instance.RetrieveServiceContent()\n container = content.rootFolder\n\n view_type = [vim.VirtualMachine]\n recursive = True\n\n container_view = content.viewManager.CreateContainerView(\n container, view_type, recursive\n )\n vm_list = container_view.view\n\n print(\"VM List:\")\n for vm in vm_list:\n print(\" - \" + vm.name)\n\n\nif __name__ == \"__main__\":\n main()\n","sub_path":"python_correction_files/0_vm_list.py","file_name":"0_vm_list.py","file_ext":"py","file_size_in_byte":689,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"510473033","text":"# -*- coding: utf-8 -*-\nimport re\n\nfrom scrapy.spiders import CrawlSpider, Request\n\nfrom SpiderOne.items import SpideroneItem\n\n\nclass TestoneSpider(CrawlSpider):\n name = \"testone\"\n # allowed_domains = [\"http://journals.plos.org/plosone/\"]\n\n count = 1 # article count\n start_urls = ['http://journals.plos.org/plosone/browse/']\n\n def parse_start_url(self, response):\n # call parse_page for start url\n print(response.url + \"这是response.url的内容\")\n yield Request(response.url, callback=self.parse_page)\n\n def parse_page(self, response):\n # grab article url\n urls = response.xpath('//div[@class=\"article-block\"]//a[@class=\"article-url\"]/@href').extract()\n\n # add domain to url and call parse_item on each article url\n for url in urls:\n url = 'http://journals.plos.org' + url\n yield Request(url, callback=self.parse_item)\n\n # grab link for the next page\n next_page = response.xpath('//nav[@class=\"nav-pagination\"]//a[@id=\"nextPageLink\"]/@href').extract()\n\n # if there is a next page, follow the link and call parse_page on it\n if len(next_page) is not 0:\n next_page_url = 'http://journals.plos.org' + next_page[0].strip()\n yield Request(next_page_url, callback=self.parse_page)\n\n def parse_item(self, response):\n item = SpideroneItem()\n item['xml_url'] = response.url + \"&type=manuscript\"\n item['text_url'] = response.url\n item['subject'] = (response.xpath('//meta[@name = \"keywords\"]/@content').extract())[0]\n item['count'] = self.count\n self.count += 1\n\n # get article's abstract\n abs = \"\"\n abstract = (response.xpath('//div[@class=\"abstract toc-section\"]//p'))\n\n if len(abstract) != 0:\n for i in abstract:\n s = i.xpath('string(.)').extract()[0]\n abs = abs + str(s)\n item['abstract'] = abs\n\n # get article's introduction\n\n bac = \"\"\n background = response.xpath('//div[@class=\"article-text\"]/div[not(contains(@class,\"abstract '\n 'toc-section\"))]//a[@title=\"Background\"]//following-sibling::p|//div['\n '@class=\"article-text\"]/div[not(contains(@class,\"abstract toc-section\"))]//a['\n '@title=\"Background\"]//following-sibling::div[@class=\"section toc-section\"]/p')\n if len(background) != 0:\n for i in background:\n s = i.xpath('string(.)').extract()[0]\n bac = bac + str(s)\n\n intr = \"\"\n introduction = response.xpath('//div[@class=\"article-text\"]/div[not(contains(@class,\"abstract '\n 'toc-section\"))]//a[@title=\"Introduction\"]//following-sibling::p|//div['\n '@class=\"article-text\"]/div[not(contains(@class,\"abstract toc-section\"))]//a['\n '@title=\"Introduction\"]//following-sibling::div[@class=\"section '\n 'toc-section\"]/p')\n if len(introduction) != 0:\n for i in introduction:\n s = i.xpath('string(.)').extract()[0]\n intr = intr + str(s)\n\n item['introduction'] = intr + bac\n\n # get article's methods\n # online = \"\"\n # onlinemethods = (response.xpath('//div[@class=\"article-text\"]/div[not(contains(@class,\"abstract toc-section\"))]//a['\n # '@title=\"Online methods\"]/following-sibling::p|//div[@class=\"article-text\"]/div[not('\n # 'contains(@class,\"abstract toc-section\"))]//a['\n # '@title=\"Online methods\"]//following-sibling::div[@class=\"section toc-section\"]/p'))\n # if len(onlinemethods) != 0:\n # for i in onlinemethods:\n # s = i.xpath('string(.)').extract()[0]\n # online = online + str(s)\n #\n\n ma1 = \"\"\n Materials1 = (response.xpath('//div[@class=\"article-text\"]/div[not(contains(@class,\"abstract '\n 'toc-section\"))]//a[contains(@title,\"and method\")]/following-sibling::p|//div['\n '@class=\"article-text\"]/div[not(contains(@class,\"abstract toc-section\"))]//a['\n 'contains(@title,\"and method\")]//following-sibling::div[@class=\"section '\n 'toc-section\"]/p'))\n if len(Materials1) != 0:\n for i in Materials1:\n s = i.xpath('string(.)').extract()[0]\n ma1 = ma1 + str(s)\n mat = \"\"\n Materials = (response.xpath('//div[@class=\"article-text\"]/div[not(contains(@class,\"abstract '\n 'toc-section\"))]//a[contains(@title,\"and methods\")]/following-sibling::p|//div['\n '@class=\"article-text\"]/div[not(contains(@class,\"abstract toc-section\"))]//a['\n 'contains(@title,\"and methods\")]//following-sibling::div[@class=\"section '\n 'toc-section\"]/p'))\n if len(Materials) != 0:\n for i in Materials:\n s = i.xpath('string(.)').extract()[0]\n mat = mat + str(s)\n\n mets = \"\"\n methods = (response.xpath('//div[@class=\"article-text\"]/div[not(contains(@class,\"abstract toc-section\"))]//a['\n 'contains(@title,\"Methods\") '\n ']/following-sibling::p|//div[@class=\"article-text\"]/div[not('\n 'contains(@class,\"abstract toc-section\"))]//a['\n 'contains(@title,\"Methods\")]//following-sibling::div[@class=\"section toc-section\"]/p'))\n if len(methods) != 0:\n for i in methods:\n s = i.xpath('string(.)').extract()[0]\n mets = mets + str(s)\n item['methods'] = mets + mat + ma1\n # + mat\n # get article's results\n resul = \"\"\n results = (response.xpath('//div[@class=\"article-text\"]/div[not(contains(@class,\"abstract '\n 'toc-section\"))]//a[@title=\"Results\"]/following-sibling::p|//div['\n '@class=\"article-text\"]/div[not(contains(@class,\"abstract toc-section\"))]//a['\n '@title=\"Results\"]//following-sibling::div[@class=\"section toc-section\"]/p'))\n if len(results) != 0:\n for i in results:\n s = i.xpath('string(.)').extract()[0]\n resul = resul + str(s)\n item['results'] = resul\n\n # get article's discussion and conclusions\n conc = \"\"\n conclusions = (response.xpath('//div[@class=\"article-text\"]/div[not(contains(@class,\"abstract '\n 'toc-section\"))]//a[contains(@title,\"Conclusions\")]/following-sibling::p|//div['\n '@class=\"article-text\"]/div[not(contains(@class,\"abstract toc-section\"))]//a['\n 'contains(@title,\"Conclusion\")]//following-sibling::div[@class=\"section toc-section\"]/p'))\n if len(conclusions) != 0:\n for i in conclusions:\n s = i.xpath('string(.)').extract()[0]\n conc = conc + str(s)\n\n dis = \"\"\n discussion = (response.xpath('//div[@class=\"article-text\"]/div[not(contains(@class,\"abstract '\n 'toc-section\"))]//a[contains(@title,\"Discussion\")]/following-sibling::p|//div['\n '@class=\"article-text\"]/div[not(contains(@class,\"abstract toc-section\"))]//a['\n 'contains(@title,\"Discussion\")]//following-sibling::div[@class=\"section toc-section\"]/p'))\n if len(discussion) != 0:\n for i in discussion:\n s = i.xpath('string(.)').extract()[0]\n dis = dis + str(s)\n\n item['discussion'] = dis + conc\n\n # clean up text\n for key in item.keys():\n if key == 'count' or key == 'text_url':\n continue\n #\n # remove tags, dangling whitespace, and citations\n # fix ampersand characters and spaces before periods\n item[key] = re.sub('\\|', '', item[key])\n item[key] = re.sub('\\n','',item[key])\n item[key] = item[key].strip()\n # item[key] = item[key].replace('&', '&')\n # item[key] = re.sub('\\[.*\\]', '', item[key])\n # item[key] = re.sub(' \\.', '.', item[key])\n\n return item\n\n","sub_path":"SpiderOne/spiders/testone.py","file_name":"testone.py","file_ext":"py","file_size_in_byte":8753,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"29477234","text":"#! python 3\r\n#downloading webpages and files form internet\r\n#requests module helps in downloading foles form the internet .\r\n\r\nimport requests\r\nr=requests.get('https://automatetheboringstuff.com/files/rj.txt') #Takes a string of url to download . It returns a responst object.\r\ntype(r) # request.models.Response . r is a response type object. It contains the response the webserver gave to request\r\nr.raise_for_status() #raise_for_status raises exception if error downloading the file\r\nplay=open('shakespear.txt','wb') # open file in write binary mode 'wb' for unicode encoding \r\nfor chunck in r.iter_content(100000): #iter_content method returns \"chuncks\" of the content on each iteration.Chunck is of byte datatype\r\n play.write(chunck) #write method writes the chunck data in the file created in open() \r\n\r\nplay.close()\r\n","sub_path":"download.py","file_name":"download.py","file_ext":"py","file_size_in_byte":1067,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"126754090","text":"# !/usr/bin/env python\n# -*- coding:utf-8 --*-\n# version:3.6.4\n# author:yexin\n'''启动程序'''\nimport os,sys\nBASENAME = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))\nsys.path.append(BASENAME)\n\nfrom core import create_dir\n# from core import re_url\n\nif __name__ == '__main__':\n start_run = create_dir.create_dir() # 调用目录创建程序\n start_run.create_first_dir() # 创建一级目录\n","sub_path":"xwiki/bin/start.py","file_name":"start.py","file_ext":"py","file_size_in_byte":412,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"652300712","text":"#!/usr/bin/python3\n#\n# zMonitor - Client\n# Asynchronous python based REST-API client\n#\n# 2016 - Armas Spann\n###\nimport curses, time, threading, urllib3, json\n\n# api server settings\napi_host = 'localhost'\napi_port = '23051'\n\n## dummy class for line helper\nclass Dummy:pass\ngvar = Dummy()\ngvar.line = 0\n\n# line helper (incrementor)\ndef line(i=1, force=False):\n gvar.line += i\n if (force):\n gvar.line = i\n return gvar.line\n\n# wrapper for the api-call (REST)\ndef api_call(module, args=None, host=None):\n http = urllib3.PoolManager()\n http_url = api_host+':'+api_port+'/v1/'+module\n if (args):\n http_url += '?args=' + args\n elif (host):\n http_url += '?host=' + host\n try:\n http_data = http.request('GET',http_url).data.decode('utf-8')\n return json.loads(http_data)\n except:\n return json.loads('{\"error\":true,\"status\":500}')\n\ndef api_refresh(screen):\n while 1:\n # clear the screen and set initital line (1 - forced)\n screen.clear()\n screen.addstr(line(0, True), 0, '-== zMonitor ==-', curses.A_BOLD)\n line(1)\n\n ## check uptime\n result = api_call('uptime')\n screen.addstr(line(), 0, \"System info (\" + api_host + \"):\" , curses.A_BOLD)\n if (result.get('status') == 200):\n threads = 1\n uptime = result.get('data')[0]\n if (uptime.get('time')):\n screen.addstr(line(), 4, \"Time: \" + str(uptime.get('time')), curses.A_NORMAL)\n if (uptime.get('uptime')):\n screen.addstr(line(), 4, \"Uptime: \" + str(uptime.get('uptime')), curses.A_NORMAL)\n if (uptime.get('users')):\n screen.addstr(line(), 4, \"Users: \" + str(uptime.get('users')) + ' (loggedin)', curses.A_NORMAL)\n if (uptime.get('threads')):\n threads = uptime.get('threads')\n screen.addstr(line(), 4, \"CPUs: \" + str(uptime.get('threads')), curses.A_NORMAL)\n if (uptime.get('load')):\n load = uptime.get('load')\n screen.addstr(line(2), 4, \"Loads (1/5/15):\", curses.A_NORMAL)\n screen.addstr(line(), 8, \"Overall: \" + str(load.get('1min')) + '/' + str(load.get('5min')) + '/' + str(load.get('15min')), curses.A_NORMAL)\n screen.addstr(line(), 8, \"Per Core: \" + str(round(load.get('1min')/threads,2)) + '/' + str(round(load.get('5min')/threads,2)) + '/' + str(round(load.get('15min')/threads,2)), curses.A_NORMAL)\n elif (result.get('status') == 500):\n screen.addstr(line(0), 26, \"(API) error\", curses.color_pair(1))\n\n ## check temperature\n result = api_call('rpi','[\"temp\"]')\n screen.addstr(line(2), 4, \"Temp (C): \", curses.A_NORMAL)\n if (result.get('status') == 200):\n temp = result.get('data')[0]\n if (temp.get('value')):\n screen.addstr(line(0), 20, str(temp.get('value')), curses.A_NORMAL)\n else:\n screen.addstr(line(0), 20, 'n/a', curses.A_NORMAL)\n elif (result.get('status') == 500):\n screen.addstr(line(0), 26, \"(API) error\", curses.color_pair(1))\n\n ## check clock\n result = api_call('rpi','[\"arm\"]')\n screen.addstr(line(), 4, \"Clock (MHz): \", curses.A_NORMAL)\n if (result.get('status') == 200):\n clock = result.get('data')[0]\n if (clock.get('value')):\n screen.addstr(line(0), 20, str(clock.get('value')/1000000), curses.A_NORMAL)\n else:\n screen.addstr(line(0), 20, 'n/a', curses.A_NORMAL)\n elif (result.get('status') == 500):\n screen.addstr(line(0), 26, \"(API) error\", curses.color_pair(1))\n\n ## check io-operations\n result = api_call('io')\n screen.addstr(line(2), 4, \"IO operations: \", curses.A_NORMAL)\n if (result.get('status') == 200):\n iops = result.get('data')[0]\n if (iops.get('r')):\n screen.addstr(line(), 8, 'Read: ' + str(iops.get('r')) + ' B/s', curses.A_NORMAL)\n else:\n screen.addstr(line(), 8, 'Read: n/a', curses.A_NORMAL)\n if (iops.get('w')):\n screen.addstr(line(), 8, 'Write: ' + str(iops.get('w')) + ' B/s', curses.A_NORMAL)\n else:\n screen.addstr(line(), 8, 'Write: n/a', curses.A_NORMAL) \n elif (result.get('status') == 500):\n screen.addstr(line(0), 26, \"(API) error\", curses.color_pair(1))\n\n ## check heavy-log procs\n result = api_call('io', '\"heavy-load\"')\n screen.addstr(line(), 4, \"Heaviest command: \", curses.A_NORMAL)\n if (result.get('status') == 200):\n for hproc in result.get('data'):\n if hproc.get('proc') and hproc.get('load'):\n screen.addstr(line(), 8, \"'\" + str(hproc.get('proc')) + \"'\", curses.A_NORMAL)\n screen.addstr(line(0), 28, ' (' + str(hproc.get('load')) + '%)', curses.A_NORMAL)\n elif (result.get('status') == 500):\n screen.addstr(line(0), 26, \"(API) error\", curses.color_pair(1))\n\n ## check internet by pingig google dns\n result = api_call('ping', None, '\"8.8.8.8\"')\n screen.addstr(line(2), 4, \"WAN-Status: \", curses.A_NORMAL)\n if (result.get('status') == 200):\n ping = result.get('data')[0]\n if (ping):\n state = \"error\"\n color = 1\n if ping.get('alive') == True:\n state = \"available\"\n color = 2\n screen.addstr(line(0), 20, state, curses.color_pair(color))\n elif (result.get('status') == 500):\n screen.addstr(line(0), 26, \"(API) error\", curses.color_pair(1))\n\n ## check specific proc\n result = api_call('proc','{\"cmd\":\"node\"}')\n screen.addstr(line(2), 0, \"Processes:\", curses.A_NORMAL)\n if (result.get('status') == 200):\n for proc in result.get('data'):\n screen.addstr(line(), 4, str(proc.get('cmd')) + \" (\" + str(proc.get('pid')) + \")\", curses.A_NORMAL)\n #if (proc.get('args')):\n # screen.addstr(line(), 8, \"args: \" + str(proc.get('args')), curses.A_NORMAL)\n elif (result.get('status') == 500):\n screen.addstr(line(0), 26, \"(API) error\", curses.color_pair(1))\n\n # screen.addstr(line(2), 0, 'Press \"q\" to exit...', curses.A_NORMAL)\n screen.refresh()\n time.sleep(1)\n\n# initialize the curses screen\nstdscr = curses.initscr()\ncurses.noecho()\ncurses.curs_set(0)\n\n# enabeling colors\ncurses.start_color()\ncurses.init_pair(1, curses.COLOR_RED, curses.COLOR_BLACK)\ncurses.init_pair(2, curses.COLOR_GREEN, curses.COLOR_BLACK)\n\n# running main-thread\nthrMain = threading.Thread(target=api_refresh, args=(stdscr,))\nthrMain.daemon = True\nthrMain.start()\n\n# wait for key: \"q\"\nwhile 1:\n event = stdscr.getch()\n if event == ord(\"q\"):\n break\n\n# kill the curses\ncurses.nocbreak(); stdscr.keypad(0); curses.echo()\ncurses.endwin()\n","sub_path":"client.py","file_name":"client.py","file_ext":"py","file_size_in_byte":7115,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"38821733","text":"# -*- coding: utf-8 -*-\nimport numpy as np\n############ Constants #############\n\n# Seconds in a year:\nyear = 31557600. # s\n# Astronomical unit:\nAU = 1.496e13 # cm\n# Solar mass:\nM_sun = 1.98855e33 # grams\n# Solar radius:\nR_sun = 6.957e10 # cm\n# Gravitational Constant:\nG = 6.674e-8 # cm^3/g/s^2\n# Hydrogen mass:\nm_h = 1.6737236e-24 # grams\n# Boltzmann's constant:\nk_B = 1.3806504e-16 # ergs/K\n# Steffan-Boltzmann's constant:\nsigma = 5.6704e-5 # erg cm^-2 s^-1 K^-4\n\n####################################\ndef ChambersModel(r, t, M0 = 0.1, M_s = 1., R_s = 3., T_s = 4200., \\\n s0 = 33., k0 = 3., alpha=1e-2, mu=2.4, gamma=1.4, T_e = 1380.):\n \"\"\"\n Chambers (2009) disk model\n\n Given input r (radius, in AU, can be a vector) and \n t (time, in seconds, can be a vector too), returns \n the temperature (in K), pressure (in bars) and surface \n density (in grams/cm^2) of the disk at each radius and time.\n\n\n Optional inputs:\n\n T_s: Stellar temperature (K).\n\n M0: Initial mass of the disk (in solar-mass units).\n\n R_s: Stellar radius (in solar-radii units).\n\n M_s: Stellar mass (in solar-mass units).\n\n s0: Initial radius of the disk's outer edge (AU).\n\n k0: Opacity (in cm^2/g).\n\n alpha: Viscosity parameter.\n\n mu: Mean molecular weight.\n\n gamma: Adiabatic index.\n\n T_e: Temperature of solid evaporation (K).\n\n \"\"\"\n\n Omega_0 = np.sqrt((G*(M_s*M_sun))/((s0*AU)**3))\n\n Sigma_vis = (7.*(M0*M_sun))/(10.*np.pi*((s0*AU)**2))\n\n T_vis = ((27.*k0/(64.*sigma))**(1./3.))*\\\n (((alpha*gamma*k_B)/(mu*m_h))**(1./3.))*\\\n ((Sigma_vis)**(2./3.))*\\\n ((Omega_0)**(1./3.))\n\n T_rad = ((4./7.)**(1./4.))*\\\n (((T_s*k_B*(R_s*R_sun))/(G*(M_s*M_sun)*mu*m_h))**(1./7.))*\\\n (((R_s*R_sun)/(s0*AU))**(3./7.))*\\\n T_s\n\n tau_vis = (1./(16*np.pi))*\\\n ((mu*m_h)/(alpha*gamma*k_B))*\\\n ((Omega_0*(M0*M_sun))/(Sigma_vis*T_vis))\n\n Sigma_evap = Sigma_vis*((T_vis/T_e)**(14./19.))\n\n Sigma_rad = Sigma_vis*(T_vis/T_rad)\n\n # Transition radius between inner and mid-region:\n r_e = (s0)*((Sigma_evap/Sigma_vis)**(95./63.))*\\\n (1. + ((t*year)/tau_vis))**(-19./36.)\n\n # Transition between mid-region and outer region:\n r_o = (s0)*((Sigma_rad/Sigma_vis)**(70./33.))*\\\n (1. + ((t*year)/tau_vis))**(-133./132.)\n\n # Temperature in the outer region:\n T = np.zeros(len(r))\n Sigma = np.zeros(len(r))\n P = np.zeros(len(r))\n\n idx_in = np.where(r=r_e)&(r=r_o)[0]\n\n T[idx_in] = (T_vis**(5./19.))*\\\n (T_e**(14./19.))*\\\n (r[idx_in]/s0)**(-9./38.)*\\\n ((1. + ((t*year)/tau_vis))**(-1./8.))\n\n Sigma[idx_in] = Sigma_evap*\\\n ((r[idx_in]/s0)**(-24./19.))*\\\n ((1. + ((t*year)/tau_vis)))**(-17./16.)\n\n \n T[idx_mid] = T_vis*\\\n ((r[idx_mid]/s0)**(-9./10.))*\\\n ((1. + ((t*year)/tau_vis))**(-19./40.))\n\n Sigma[idx_mid] = (Sigma_vis)*\\\n ((r[idx_mid]/s0)**(-3./5.))*\\\n ((1. + ((t*year)/tau_vis))**(-57./80.))\n\n T[idx_out] = T_rad*\\\n ((r[idx_out]/s0)**(-3./7.))\n\n Sigma[idx_out] = Sigma_rad*\\\n ((r[idx_out]/s0)**(-15./14.))*\\\n ((1. + ((t*year)/tau_vis))**(-19./16.))\n\n P = Sigma*np.sqrt((G*(M_s*M_sun)*k_B*T)/\\\n (2.*np.pi*mu*m_h*((r*AU)**3)))\n\n return T,P*1e-6,Sigma\n\ndef PowerLawProfile(r, q = 0.62, T0 = 200):\n \"\"\"\n Simple power-law temperature profile for a disk\n\n Given input r (radius, in AU, can be a vector) it \n returns temperature (in K) as a function of radius \n of the form:\n \n T = T0 * r**(-q)\n\n The values of q and T0 pre-defined are for the average \n protoplanetary disk (Andrews & Williams, 2007).\n\n Optional inputs:\n\n q: Power-law index of the profile.\n\n T0: Temperature at 1 AU.\n\n \"\"\"\n return T0*(r**(-q))\n","sub_path":"plots/chem_eq/disk_models.py","file_name":"disk_models.py","file_ext":"py","file_size_in_byte":4116,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"574012264","text":"import functools\nimport hashlib\nimport itertools\nimport logging\nimport os\nimport threading\nfrom Queue import Queue\nfrom cStringIO import StringIO\nfrom contextlib import closing\nfrom datetime import datetime\nfrom httplib import IncompleteRead\nfrom os.path import join, relpath\n\nimport boto3\nfrom boto3.s3.transfer import TransferConfig, MB\nfrom botocore.exceptions import ClientError, IncompleteReadError\nfrom botocore.vendored.requests.packages.urllib3.exceptions import ProtocolError\n\nfrom source.aws.client import ReconnectingAWSClient\nfrom source.storage.io_handlers.interface import IOHandlerInterface, File, ErrorCodes\n\n\nclass S3IOHandler(IOHandlerInterface):\n def get_created_at(self, path):\n \"\"\"\n Actually is modification time\n\n @type path: C{str}\n @rtype: C{datetime}\n \"\"\"\n self.__logger.debug('Loading last modified at from path \"{}\"'.format(path))\n bucket_name, key_path = self.__split_to_bucket_and_path(path)\n client = self.__client\n try:\n key = client.get_object(Bucket=bucket_name, Key=key_path)\n except ClientError as ex:\n if ex.response['Error']['Code'] == 'NoSuchKey':\n raise LookupError('Key \"{}\" was not found in bucket \"{}\".'.format(key_path, bucket_name))\n raise\n return key['LastModified']\n\n def __init__(self, max_keys_for_list_operation=1000):\n self.__client = ReconnectingAWSClient('s3', 'us-east-1')\n self.__logger = logging.getLogger('endor.io_handler.s3')\n self.__max_keys_for_list_operation = max_keys_for_list_operation\n\n def get_hadoop_base_path(self):\n return 's3a://'\n\n def path_exists(self, path):\n \"\"\"\n Determines whether the given path exists on the storage service.\n @param path: The path to test\n @type path: C{str}\n @return: True if the path exists False otherwise\n @rtype: C{bool}\n \"\"\"\n client = self.__client\n bucket_name, key_path = self.__split_to_bucket_and_path(path)\n try:\n client.get_object(Bucket=bucket_name, Key=key_path)\n return True\n except ClientError as ex:\n if ex.response['Error']['Code'] == 'NoSuchKey':\n return False\n raise\n\n def save_raw_data(self, data, path, content_type='text/html'):\n \"\"\"\n Saves raw data on the storage service\n\n @param data: The data to save.\n @type data: C{str}\n @param path: The path on the storage service where the data should be saved.\n @type path: C{str}\n @param content_type: A standard MIME type describing the format of the object data\n @type content_type: C{str}\n \"\"\"\n client = self.__client\n self.__logger.debug('Saving to path \"{}\"'.format(path))\n bucket_name, key_path = self.__split_to_bucket_and_path(path)\n try:\n client.put_object(\n Bucket=bucket_name,\n Key=key_path,\n Body=data,\n ContentType=content_type,\n ServerSideEncryption='AES256')\n except ClientError as ex:\n if ex.response['Error']['Code'] == 'EntityTooLarge':\n raise IOError({'code': ErrorCodes.FILE_TOO_BIG})\n else:\n raise\n\n def save_raw_data_multipart(self, data, path, content_type=None):\n \"\"\"\n Saves raw data on the storage service\n\n @param data: The data to save.\n @type data: C{file}\n @param path: The path on the storage service where the data should be saved.\n @type path: C{str}\n @param content_type: A standard MIME type describing the format of the object data\n @type content_type: C{str}\n \"\"\"\n client = self.__client\n self.__logger.debug('Saving to path \"{}\" with multipart'.format(path))\n bucket_name, key_path = self.__split_to_bucket_and_path(path)\n config = TransferConfig(multipart_threshold=5 * 1024 * MB)\n extra_args = {'ServerSideEncryption': 'AES256'}\n if content_type is not None:\n extra_args['ContentType'] = content_type\n\n client.upload_fileobj(\n Bucket=bucket_name,\n Key=key_path,\n Fileobj=data,\n Config=config,\n ExtraArgs=extra_args)\n\n def load_raw_data(self, path):\n \"\"\"\n Loads raw data from the storage service.\n\n @param path: The path on the remote storage where the data should be loaded from.\n @type path: C{str}\n @return: The loaded data\n @rtype: C{str}\n @raise LookupError: When the path does not exist.\n \"\"\"\n try:\n with closing(self.open(path)) as file_handle:\n data = file_handle.read()\n data_md5 = hashlib.md5(data).hexdigest()\n self.__logger.debug('Loaded {} bytes from path \"{}\" with md5 \"{}\"'.format(len(data), path, data_md5))\n return data\n except ProtocolError as ex:\n if isinstance(ex.args[1], IncompleteRead):\n return self.load_raw_data(path)\n except IncompleteReadError:\n return self.load_raw_data(path)\n\n @staticmethod\n def __split_to_bucket_and_path(path):\n split_path = path.split('/')\n bucket_name, key_path = split_path[0], join(*split_path[1:])\n return bucket_name, key_path\n\n def list_files(self, path):\n self.__logger.debug('Listing path \"{}\"'.format(path))\n client = self.__client\n bucket_name, key_path = self.__split_to_bucket_and_path(path)\n query = join(key_path, '')\n query_len = len(query)\n\n continuation_token = None\n fetch_more_objects = True\n\n while fetch_more_objects:\n list_objects = functools.partial(client.list_objects_v2,\n Bucket=bucket_name,\n Prefix=query,\n Delimiter='/',\n MaxKeys=self.__max_keys_for_list_operation)\n\n if continuation_token is not None:\n response = list_objects(ContinuationToken=continuation_token)\n else:\n response = list_objects()\n\n if 'Contents' in response:\n keys = (File(i['Key'], i['Size']) for i in response['Contents'])\n else:\n keys = []\n\n if 'CommonPrefixes' in response:\n folders = (File(i['Prefix'], 0) for i in response['CommonPrefixes'])\n else:\n folders = []\n\n for obj in itertools.chain(keys, folders):\n result_key = obj.path[query_len:].strip('/')\n if result_key:\n yield File(join(path, result_key), obj.size)\n\n fetch_more_objects = response['IsTruncated']\n\n if fetch_more_objects:\n continuation_token = response['NextContinuationToken']\n\n def list_dir(self, path):\n return (f.path for f in self.list_files(path))\n\n def open(self, path):\n self.__logger.debug('Loading from path \"{}\"'.format(path))\n bucket_name, key_path = self.__split_to_bucket_and_path(path)\n client = self.__client\n try:\n key = client.get_object(Bucket=bucket_name, Key=key_path)\n except ClientError as ex:\n if ex.response['Error']['Code'] == 'NoSuchKey':\n raise LookupError('Key \"{}\" was not found in bucket \"{}\".'.format(key_path, bucket_name))\n raise\n\n return key['Body']\n\n def store_folder_contents(self, local_folder_path, remote_folder_path):\n exception_queue = Queue()\n s3_region = self.__client.region_name\n\n def upload_file(local_path, remote_path):\n try:\n client = boto3.client('s3', region_name=s3_region)\n bucket_name, key_path = self.__split_to_bucket_and_path(remote_path)\n with open(local_path, 'rb') as local_file:\n client.put_object(Bucket=bucket_name, Key=key_path, Body=local_file.read(),\n ServerSideEncryption='AES256')\n except Exception as ex:\n exception_queue.put(ex)\n\n upload_jobs_generator = ((join(local_folder_path, file_name), join(remote_folder_path, file_name))\n for file_name in os.listdir(local_folder_path))\n threads = []\n for local_file_path, remote_file_path in upload_jobs_generator:\n self.__logger.debug('Uploading \"{}\" to \"{}\"'.format(local_file_path, remote_file_path))\n thread = threading.Thread(target=upload_file, args=(local_file_path, remote_file_path))\n thread.start()\n threads.append(thread)\n\n for thread in threads:\n thread.join()\n\n if not exception_queue.empty():\n raise exception_queue.get()\n\n def add_public_read(self, path):\n bucket_name, key_path = self.__split_to_bucket_and_path(path)\n client = self.__client\n try:\n client.put_object_acl(Bucket=bucket_name, Key=key_path, ACL='public-read')\n except ClientError as ex:\n if ex.response['Error']['Code'] == 'NoSuchKey':\n raise LookupError('Key \"{}\" was not found in bucket \"{}\".'.format(key_path, bucket_name))\n raise\n\n def get_object_url(self, path):\n bucket_name, key_path = self.__split_to_bucket_and_path(path)\n return 'https://{bucket}.s3.amazonaws.com/{key}'.format(bucket=bucket_name, key=key_path)\n\n def copy_contents_from_remote_folder_to_remote_folder(self, source_path, target_path):\n _, source_key_path = self.__split_to_bucket_and_path(source_path)\n target_bucket_name, target_key_path = self.__split_to_bucket_and_path(target_path)\n\n source_file_paths = list(self.list_dir(source_path))\n\n if len(source_file_paths) == 0:\n return 0\n\n client = self.__client\n\n for single_source_file_path in source_file_paths:\n bucket_name, key_path = self.__split_to_bucket_and_path(single_source_file_path)\n single_target_key_path = join(target_key_path, relpath(key_path, source_key_path))\n client.copy({'Bucket': bucket_name, 'Key': key_path}, target_bucket_name, single_target_key_path,\n ExtraArgs={\n 'ServerSideEncryption': 'AES256'\n })\n\n return len(source_file_paths)\n\n def download_fileobj(self, remote_path, file_like):\n bucket_name, key_path = self.__split_to_bucket_and_path(remote_path)\n self.__logger.debug('Downloading {} as file object'.format(remote_path))\n self.__client.download_fileobj(Bucket=bucket_name, Key=key_path, Fileobj=file_like)\n","sub_path":"internal/source/storage/io_handlers/s3.py","file_name":"s3.py","file_ext":"py","file_size_in_byte":10905,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"22721862","text":"from distutils import spawn\nfrom subprocess import PIPE, STDOUT\nimport re, enchant, subprocess\n\nclass Parser(object):\n \"\"\"\n This class is used to perform all tasks concerning the string analysis.\n \"\"\"\n\n @staticmethod\n def strings(path):\n \"\"\"\n Extract all readable strings from a binary.\n\n :param path: Path to the binary to analyze.\n :type: string\n :return: List that contains all strings.\n :rtype: List\n \"\"\"\n string_list = []\n chars = r\"A-Za-z0-9/\\-:.,_$%'()[\\]<> \"\n shortest_run = 4\n regexp = '[%s]{%d,}' % (chars, shortest_run)\n pattern = re.compile(regexp)\n try:\n with open(path, 'rb') as file:\n return pattern.findall(file.read())\n except:\n return None\n\n @staticmethod\n def getIp(string):\n \"\"\"\n Static method that extract strings detected as an IP address.\n\n :param string: A string to be analyzed.\n :type string: String\n :return: None if the string doesn't match or the part of the string\n which corresponds.\n :rtype: string\n \"\"\"\n regexp = \"\"\"\\\\b((?:\\\\b(([01]?\\d?\\d|2[0-4]\\d|25[0-5])\\.){3}([01]?\\d?\\d|2[0-4]\\d|25[0-5])\\\\b:(?:6535[0-3]\\\\b|653[0-4]\\\\b|65[0-2]\\d{2}|6[0-4]\\d{3}|[1-5]\\d{4}|[1-9]\\d{3}|[1-9]\\d{2}|[1-9]\\d|\\d)|\\\\b(([01]?\\d?\\d|2[0-4]\\d|25[0-5])\\.){3}([01]?\\d?\\d|2[0-4]\\d|25[0-5])\\\\b))\"\"\"\n pattern = re.compile(regexp)\n if pattern.search(string) is None:\n return None\n return pattern.search(string).group()\n\n @staticmethod\n def getUrl(string):\n \"\"\"\n Static method that extract strings detected as an URL.\n\n :param string: A string to be analyzed.\n :type string: String\n :return: None if the string doesn't match or the part of the string\n which corresponds.\n :rtype: string\n \"\"\"\n regexp = \"\"\"(?:(?:http|ftp) : //[^ ]+ : [^ ]+|(?:http|ftp) : //[^ ]+)|http[^ ]+\"\"\"\n pattern = re.compile(regexp)\n if pattern.search(string) is None:\n return None\n return pattern.search(string).group()\n\n @staticmethod\n def getCmd(string):\n \"\"\"\n Static method that extract strings detected as a linux command line.\n\n :param string: A string to be analyzed.\n :type string: String\n :return: None if the string doesn't match or the part of the string\n which corresponds.\n :rtype: string\n \"\"\"\n potential_cmd = string.replace(\">\", \"o\").replace(\"<\", \"o\") \\\n .replace(\"]\", \"o\").replace(\"[\", \"o\") \\\n .replace(\"/\", \"o\").replace(\"\\\\\", \"o\") \\\n .replace(\"'\", \"o\").replace(\"%\", \"o\") \\\n .replace(\"-\", \"o\").replace(\"_\", \"o\") \\\n .replace(\":\", \"o\").replace(\",\", \"o\") \\\n .replace(\".\", \"o\") \\\n .lstrip().split(\" \")[0] # .replace(\")\", \" \").replace(\"(\", \" \") \\\n\n if spawn.find_executable(potential_cmd) != None:\n return potential_cmd\n\n cmd = [\"bash -c \\\"command -v \\\"\" + potential_cmd + \"\\\"\\\"\"]\n ret = subprocess.Popen(cmd, shell=True, stdin=PIPE,\n stdout=PIPE, stderr=STDOUT).communicate()\n if ret[0] != \"\" and potential_cmd not in [\"(null)\", \"(nil)\"]:\n return potential_cmd\n return None\n\n @staticmethod\n def getId(string):\n \"\"\"\n Static method that extract strings detected as an identifier.\n\n :param string: A string to be analyzed.\n :type string: String\n :return: None if the string doesn't match or the part of the string\n which corresponds.\n :rtype: string\n \"\"\"\n\n dir = \"../../collectedData/identifiers/\"\n fuser = fpass = []\n with open(dir + \"username\") as f:\n fuser = f.read().splitlines()\n fuser = map(lambda x:x.lower(),fuser)\n with open(dir + \"password\") as f:\n fpass = f.read().splitlines()\n fpass = map(lambda x:x.lower(),fpass)\n if (string.lower() in fpass) or (string.lower() in fuser):\n return string\n return None\n\n @staticmethod\n def getPath(string):\n \"\"\"\n Static method that extract strings detected as a file path.\n\n :param string: A string to be analyzed.\n :type string: String\n :return: None if the string doesn't match or the part of the string\n which corresponds.\n :rtype: string\n \"\"\"\n\n if \"/\" not in string or \"(\" in string or \")\" in string:\n return None\n\n bad_seq = [\"//\", \"i/o\", \"input/output\"]\n for seq in bad_seq:\n if seq in string.lower():\n return None\n regexp = \"\"\"(.*[\\\\\\/]|^)(.*?)(?:[\\.]|$)([^\\.\\s]*$)\"\"\"\n pattern = re.compile(regexp)\n if pattern.search(string) is None:\n return None\n return pattern.search(string).group()\n\n @staticmethod\n def getSection(string):\n \"\"\"\n Static method that extract strings detected as a elf binary section.\n\n :param string: A string to be analyzed.\n :type string: String\n :return: None if the string doesn't match or the part of the string\n which corresponds.\n :rtype: string\n \"\"\"\n\n regexp = \"\"\"^\\.[a-zA-Z0-9_]+$\"\"\"\n pattern = re.compile(regexp)\n if pattern.search(string) is None:\n return None\n return pattern.search(string).group()\n\n @staticmethod\n def getSymbol(string, readelf_output):\n for entry in readelf_output:\n entry = re.sub(r'\\s+', ' ', entry).strip().split()\n if len(entry) == 8 and entry[3] != \"NOTYPE\" \\\n and string == entry[-1]:\n return string, entry[3].lower()\n return None, None\n\n @staticmethod\n def getFormatStr(string):\n \"\"\"\n Static method that extract strings detected as a format string.\n\n :param string: A string to be analyzed.\n :type string: String\n :return: None if the string doesn't match or the part of the string\n which corresponds.\n :rtype: string\n \"\"\"\n\n regexp = \"\"\"%[\\-\\+0\\s\\#]{0,1}(\\d+){0,1}(\\.\\d+){0,1}[hlI]{0,1}[cCdiouxXeEfgGnpsS]{1}\"\"\"\n pattern = re.compile(regexp)\n if pattern.search(string) is None:\n return None\n return pattern.search(string).group()\n\n @staticmethod\n def getMessage(string):\n \"\"\"\n Static method that extract strings detected as an english message.\n\n :param string: A string to be analyzed.\n :type string: String\n :return: None if the string doesn't match or the part of the string\n which corresponds.\n :rtype: string\n \"\"\"\n\n sentence_list = re.sub(r'\\s+', ' ', string).strip().split()\n d = enchant.Dict(\"en_US\")\n known_words = 0\n for word in sentence_list:\n if d.check(word):\n known_words += 1\n percent = (100 * known_words) / len(sentence_list)\n if percent < 60:\n return None\n return string\n\n @staticmethod\n def isValidBin(path):\n \"\"\"\n Detect if a file is an elf binary.\n\n :param path: Absolute path to an elf binary.\n :type path: string\n :return: First value determine if its a binary or not and the second\n contains the error message in case of error.\n :rtype: Boolean, string\n \"\"\"\n cmd = [\"bash -c \\\"file \\\"\" + path + \"\\\"\\\"\"]\n ret = subprocess.Popen(cmd, shell=True, stdin=PIPE,\n stdout=PIPE, stderr=STDOUT).communicate()\n if \"not stripped\" not in ret[0]:\n return False, \"[Error] stripped binary, impossible to perform string analysis.\"\n if \"too many section\" in ret[0]:\n return False, \"[Error] too many section, impossible to perform string analysis.\"\n return True, None\n","sub_path":"utils/malwareStringsAnalyzer/lib/parser.py","file_name":"parser.py","file_ext":"py","file_size_in_byte":8417,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"453052738","text":"\"\"\"empty message\n\nRevision ID: 1e345110f4ab\nRevises: 1cff8aa5fbb5\nCreate Date: 2015-09-27 18:45:16.224354\n\n\"\"\"\n\n# revision identifiers, used by Alembic.\nrevision = '1e345110f4ab'\ndown_revision = '1cff8aa5fbb5'\n\nfrom alembic import op\nimport sqlalchemy as sa\n\n\ndef upgrade():\n ### commands auto generated by Alembic - please adjust! ###\n op.create_table('linkLists_users',\n sa.Column('user_id', sa.Integer(), nullable=True),\n sa.Column('link_list_id', sa.Integer(), nullable=True),\n sa.ForeignKeyConstraint(['link_list_id'], ['link_list.id'], ),\n sa.ForeignKeyConstraint(['user_id'], ['user.id'], )\n )\n ### end Alembic commands ###\n\n\ndef downgrade():\n ### commands auto generated by Alembic - please adjust! ###\n op.drop_table('linkLists_users')\n ### end Alembic commands ###\n","sub_path":"migrations/versions/1e345110f4ab_.py","file_name":"1e345110f4ab_.py","file_ext":"py","file_size_in_byte":808,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"372833683","text":"#! /usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"Creates a homework configuration file, uploads files to repository\nand sends the homework for evaluation\n\nFor a better submission scheme see the commit:\n 22326889e780121f37598532efc1139e21daab41\n\n\"\"\"\n\nfrom __future__ import with_statement\n\nimport ConfigParser\nimport os\nimport shutil\nimport subprocess\nimport time\nimport socket\nimport datetime\nimport paramiko\nfrom contextlib import closing\n\nfrom . import config\nfrom . import paths\nfrom . import ziputil\nfrom . import submissions\nfrom . import vmlogging\nfrom . import tempfileutil\nfrom .courselist import CourseList\n\nlogger = vmlogging.create_module_logger('submit')\n\n_DEFAULT_SSH_PORT = 22\n\nclass SubmitedTooSoonError(Exception):\n \"\"\"Raised when a user sends a submission too soon after a previous one.\n\n This is used to prevent a user from DOS-ing vmchecker or from\n monopolising the test queue.\"\"\"\n def __init__(self, message):\n Exception.__init__(self, message)\n\ndef submission_config(user, assignment, course_id, upload_time,\n storer_result_dir, storer_username, storer_hostname):\n \"\"\"Creates a configuration file describing the current submission:\n - who uploaded it\n - which assignment does it solve\n - which course was it for\n - when was it uploaded\n\n Also, XXX, should be removed:\n - where to store results\n - with which user to connect to the machine storring the results\n - which is the machine storring the results\n\n The last part should not be part of the submission config, but\n should be generated automatically when the submission is sent\n for testing.\n \"\"\"\n sbcfg = ConfigParser.RawConfigParser()\n sbcfg.add_section('Assignment')\n sbcfg.set('Assignment', 'User', user)\n sbcfg.set('Assignment', 'Assignment', assignment)\n sbcfg.set('Assignment', 'UploadTime', upload_time)\n sbcfg.set('Assignment', 'CourseID', course_id)\n\n # XXX these should go to `callback'\n sbcfg.set('Assignment', 'ResultsDest', storer_result_dir)\n sbcfg.set('Assignment', 'RemoteUsername', storer_username)\n sbcfg.set('Assignment', 'RemoteHostname', storer_hostname)\n return sbcfg\n\n\n\ndef submission_backup_prefix(course_id, assignment, user, upload_time):\n \"\"\"Backups have a name of the form:\n SO_1-minishell-linux_Lucian Adrian Grijincu_2010.03.05 01:08:54_juSZr9\n\n This builds the prefix of the path. The random last part is\n generated by Python's tempfile module.\n \"\"\"\n return '%s_%s_%s_%s_' % (course_id, assignment, user, upload_time)\n\n\ndef submission_backup(back_dir, archive_filename, sbcfg):\n \"\"\"Make a backup for this submission.\n\n Each entry is of the following structure:\n +--$back_dir/\n | +--archive/\n | | +-- X (all the files from the archive)\n | | +-- Y (all the files from the archive)\n | +--submission-config config describing the submission\n | | (user, uploadtime, assignment)\n | +--archive.zip the original (unmodified) archive\n \"\"\"\n back_arc = paths.dir_submission_expanded_archive(back_dir)\n back_cfg = paths.submission_config_file(back_dir)\n back_zip = paths.submission_archive_file(back_dir)\n\n # make sure the directory path exists\n if not os.path.exists(back_dir):\n os.makedirs(back_dir)\n\n # copy the (unmodified) archive. This should be the first thing we\n # do, to make sure the uploaded submission is on the server no\n # matter what happens next\n shutil.copyfile(archive_filename, back_zip)\n\n # write the config. Again do this before unzipping (which might fail)\n # to make sure we have the upload data ready.\n with open(back_cfg, 'w') as handle:\n sbcfg.write(handle)\n\n # unzip the archive, but check if it has absolute paths or '..'\n ziputil.unzip_safely(archive_filename, back_arc)\n\n logger.info('Stored submission in temporary directory %s', back_dir)\n\n\n\ndef submission_git_commit(dest, user, assignment):\n \"\"\"Submit in git the data from the dest subdirectory of the\n repository.\n \"\"\"\n subprocess.Popen(['git', 'add', '--force', '.'], cwd=dest).wait()\n subprocess.Popen(['git', 'commit', '--allow-empty', '.',\n '-m \"Updated ' + user + '\\' submission for ' +\n assignment + '\"'], cwd=dest).wait()\n\n\n\n\ndef save_submission_in_storer(archive_filename, user, assignment,\n course_id, upload_time):\n \"\"\" Save the submission on the storer machine:\n\n - create a config for the submission to hold identifying info\n (user, course, assignment, upload_time)\n - create a backup for the submission parallel to the git repo\n - commit the backup in the git repo\n - copy the archive near the data committed in the repo to be\n easily accessible.\n \"\"\"\n vmcfg = config.CourseConfig(CourseList().course_config(course_id))\n vmpaths = paths.VmcheckerPaths(vmcfg.root_path())\n sbroot = vmpaths.dir_submission_root(assignment, user)\n sbcfg = submission_config(user, assignment, course_id, upload_time,\n paths.dir_submission_results(sbroot),\n vmcfg.storer_username(),\n vmcfg.storer_hostname())\n\n # make a separate backup for each submission, parallel to the git repo\n # here, each submission gets a separate entry.\n # in git the former entryes get overwritten and commited to git.\n name_prefix = submission_backup_prefix(course_id, assignment, user, upload_time)\n back_dir = tempfileutil.mkdtemp(prefix=name_prefix, dir=vmpaths.dir_backup())\n submission_backup(back_dir, archive_filename, sbcfg)\n\n\n # commit in git this submission\n git_dest = vmpaths.dir_submission_root(assignment, user)\n with vmcfg.assignments().lock(vmpaths, assignment):\n # cleanup any previously commited data\n if os.path.exists(git_dest):\n shutil.rmtree(git_dest)\n submission_backup(git_dest, archive_filename, sbcfg)\n # we only commit the archive's data. the config file and the\n # archive.zip is not commited.\n submission_git_commit(paths.dir_submission_expanded_archive(git_dest),\n user, assignment)\n\n\n\ndef create_testing_bundle(user, assignment, course_id):\n \"\"\"Creates a testing bundle.\n\n This function creates a zip archive (the bundle) with everything\n needed to run the tests on a submission.\n\n The bundle contains:\n submission-config - submission config (eg. name, time of submission etc)\n machine-config - configuration for the virtual machine\n archive.zip - a zip containing the sources\n tests.zip - a zip containing the tests\n ??? - assignment's extra files (see Assignments.include())\n\n \"\"\"\n vmcfg = config.CourseConfig(CourseList().course_config(course_id))\n vmpaths = paths.VmcheckerPaths(vmcfg.root_path())\n sbroot = vmpaths.dir_submission_root(assignment, user)\n\n asscfg = vmcfg.assignments()\n machine = asscfg.get(assignment, 'Machine')\n\n #rel_file_list = list(vmcfg.assignments().files_to_include(assignment))\n rel_file_list = []\n rel_file_list += [ ('build.sh', vmcfg.get(machine, 'BuildScript')),\n ('run.sh', vmcfg.get(machine, 'RunScript')) ]\n rel_file_list += [ ('archive.zip', paths.submission_archive_file(sbroot)),\n ('tests.zip', vmcfg.assignments().tests_path(vmpaths, assignment)),\n ('submission-config', paths.submission_config_file(sbroot)),\n ('machine-config', os.path.join(vmcfg.root_path(), 'config')) ] # XXX\n # XXX for now 'machine-config' contains all the config of the storer\n # in the future we should include only what's really necessary\n\n file_list = [ (dst, vmpaths.abspath(src)) for (dst, src) in rel_file_list ]\n\n # builds archive with configuration\n with vmcfg.assignments().lock(vmpaths, assignment):\n # creates the zip archive with an unique name\n (bundle_fd, bundle_path) = tempfileutil.mkstemp(\n suffix='.zip',\n prefix='%s_%s_%s_' % (course_id, assignment, user),\n dir=vmpaths.dir_unchecked()) # FIXME not here\n logger.info('Creating bundle package %s', bundle_path)\n\n try:\n with closing(os.fdopen(bundle_fd, 'w+b')) as handler:\n ziputil.create_zip(handler, file_list)\n except:\n logger.error('Failed to create zip archive %s', bundle_path)\n raise # just cleaned up the bundle. the error still needs\n # to be reported.\n\n return bundle_path\n\n\ndef ssh_bundle(bundle_path, vmcfg):\n \"\"\"Sends a bundle over ssh to the tester machine\"\"\"\n tester_username = vmcfg.tester_username()\n tester_hostname = vmcfg.tester_hostname()\n tester_queuepath = vmcfg.tester_queue_path()\n\n sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n sock.connect((tester_hostname, _DEFAULT_SSH_PORT))\n t = paramiko.Transport(sock)\n try:\n t.start_client()\n # XXX cannot validate remote key, because www-data does not\n # have $home/.ssh/known_hosts where to store such info. For\n # now, we'll assume the remote host is the desired one.\n #remotekey = t.get_remote_server_key()\n key = paramiko.RSAKey.from_private_key_file(vmcfg.storer_sshid())\n # todo check DSA keys too\n # key = paramiko.DSAKey.from_private_key_file(vmcfg.storer_sshid())\n t.auth_publickey(tester_username, key)\n sftp = paramiko.SFTPClient.from_transport(t)\n # XXX os.path.join is not correct here as these are paths on the\n # remote machine.\n sftp.put(bundle_path, os.path.join(tester_queuepath, os.path.basename(bundle_path)))\n finally:\n t.close()\n\n\n\ndef submitted_too_soon(assignment, user, vmcfg):\n \"\"\"Check if the user submitted this assignment very soon after\n another submission.\n\n Returns True if another submission of this assignment was done\n without waiting the amount of time specified in the config file.\n \"\"\"\n vmpaths = paths.VmcheckerPaths(vmcfg.root_path())\n subm = submissions.Submissions(vmpaths)\n if not subm.submission_exists(assignment, user):\n return False\n upload_time = subm.get_upload_time(assignment, user)\n\n if upload_time is None:\n return False\n\n remaining = upload_time\n remaining += vmcfg.assignments().timedelta(assignment)\n remaining -= datetime.datetime.now()\n\n return remaining > datetime.timedelta()\n\n\n\ndef queue_for_testing(assignment, user, course_id):\n \"\"\"Queue for testing the last submittion for the given assignment,\n course and user.\"\"\"\n vmcfg = config.CourseConfig(CourseList().course_config(course_id))\n bundle_path = create_testing_bundle(user, assignment, course_id)\n ssh_bundle(bundle_path, vmcfg)\n\n\ndef submit(archive_filename, assignment, user, course_id,\n skip_time_check=False, forced_upload_time=None):\n \"\"\"Commit in the git repo and queue for testing a new submission.\n\n The submission is identified by archive_filename.\n\n Implicitly, if the user sent the submission to soon, it isn't\n queued for checking. This check can be skipped by setting\n skip_time_check=True.\n\n If forced_upload_time is not specified, the current system time is\n used.\n \"\"\"\n vmcfg = config.CourseConfig(CourseList().course_config(course_id))\n\n if forced_upload_time != None:\n skip_time_check = True\n upload_time = forced_upload_time\n else:\n upload_time = time.strftime(config.DATE_FORMAT)\n\n # checks time difference\n if not skip_time_check and submitted_too_soon(assignment, user, vmcfg):\n raise SubmitedTooSoonError('''You are submitting too fast.\n Please allow %s between submissions''' %\n str(vmcfg.assignments().timedelta(assignment)))\n\n save_submission_in_storer(archive_filename, user, assignment,\n course_id, upload_time)\n queue_for_testing(assignment, user, course_id)\n\n","sub_path":"vmchecker/submit.py","file_name":"submit.py","file_ext":"py","file_size_in_byte":12226,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"242626466","text":"import pygame\nfrom pygame.locals import *\n\n\nclass TextDisplay():\n\n def __init__(self):\n # Initializes font:\n pygame.font.init()\n\n # Declares the font to be used by the text\n self.font_56 = pygame.font.SysFont(\"None\", 56)\n self.font_46 = pygame.font.SysFont(\"None\", 46)\n self.font_36 = pygame.font.SysFont(\"None\", 36)\n self.font_26 = pygame.font.SysFont(\"None\", 26)\n self.font_16 = pygame.font.SysFont(\"None\", 16)\n\n def setPosition(self, position, screen_size, text):\n # Gets screen dimensions:\n screen_width, screen_height = screen_size\n\n # Gets dimensions of the text\n text_posX, text_posY, text_lenght, text_height = text.get_rect()\n\n # Checks for the position to display the text:\n if type(position) is str:\n if position != \"\":\n if position == \"screen_center\":\n # Puts the text on the center of the screen:\n textPosition = (screen_width/2 - text_lenght/2,\n screen_height/2 - text_height/2)\n elif position == \"center_top\":\n # Puts the text on the center of the screen:\n textPosition = (screen_width/2 - text_lenght/2,\n screen_height/2 - text_height)\n elif position == \"center_top2\":\n # Puts the text on the center of the screen:\n textPosition = (screen_width/2 - text_lenght/2,\n screen_height/2 - text_height*2)\n print(\"help\")\n elif position == \"center_top3\":\n # Puts the text on the center of the screen:\n textPosition = (screen_width/2 - text_lenght/2,\n screen_height/2 - text_height*3)\n elif position == \"center_bottom\":\n # Puts the text on the center of the screen:\n textPosition = (screen_width/2 - text_lenght/2,\n screen_height/2)\n elif position == \"center_bottom2\":\n # Puts the text on the center of the screen:\n textPosition = (screen_width/2 - text_lenght/2,\n screen_height/2 + text_height*2)\n elif position == \"center_bottom3\":\n # Puts the text on the center of the screen:\n textPosition = (screen_width/2 - text_lenght/2,\n screen_height/2 + text_height*3)\n elif position == \"center_bottom4\":\n # Puts the text on the center of the screen:\n textPosition = (screen_width/2 - text_lenght/2,\n screen_height/2 + text_height*4)\n elif position == \"center_bottom5\":\n # Puts the text on the center of the screen:\n textPosition = (screen_width/2 - text_lenght/2,\n screen_height/2 + text_height*5)\n elif position == \"top_center\":\n # Puts the text centered on the top of the screen:\n textPosition = (screen_width/2 - text_lenght/2,\n 0)\n elif position == \"top_center2\":\n # Puts the text centered on the top of the screen:\n textPosition = (screen_width/2 - text_lenght/2,\n text_height)\n\n elif type(position) is tuple:\n textPosition = position\n\n return textPosition\n\n def displayTextMainMenu(self, text, COLOR, screen, screen_size, position):\n # Renders the text by the font chosen before\n text = self.font_56.render(text, True, COLOR)\n\n # Sets the text position:\n textPosition = self.setPosition(position, screen_size, text)\n\n # Sticks the text to the screen:\n screen.blit(text, textPosition)\n\n def displayHealthAndName(self, COLOR, player, screen, screen_size):\n # Gets screen dimensions:\n screen_width, screen_height = screen_size\n\n name = \"{0}\".format(player.name)\n health = \"Health: {0}\".format(player.health)\n\n # Renders the text by the font chosen before\n health = self.font_26.render(health, True, COLOR)\n # Gets dimensions of the text\n health_posX, health_posY, health_lenght, health_height = health.get_rect()\n healthPosition = (player.rect.centerx - health_lenght/2,\n player.rect.centery - health_height*2 - 10)\n\n # Renders the text by the font chosen before\n name = self.font_26.render(name, True, (255, 255, 255))\n # Gets dimensions of the text\n name_posX, name_posY, name_lenght, name_height = name.get_rect()\n namePosition = (player.rect.centerx - name_lenght/2,\n player.rect.centery - name_height*3 - 10)\n\n # Sticks the name to the screen:\n screen.blit(name, namePosition)\n # Sticks the health to the screen:\n screen.blit(health, healthPosition)\n\n def displayTextNameScreen(self, text, COLOR, screen, screen_size, position):\n # Renders the text by the font chosen before\n text = self.font_36.render(text, True, COLOR)\n\n # Sets the text position:\n textPosition = self.setPosition(position, screen_size, text)\n\n # Sticks the text to the screen:\n screen.blit(text, textPosition)\n\n def displayTextWinnerScreen(self, text, COLOR, screen, screen_size, position):\n # Renders the text by the font chosen before\n text = self.font_36.render(text, True, COLOR)\n\n # Sets the text position:\n textPosition = self.setPosition(position, screen_size, text)\n\n # Sticks the text to the screen:\n screen.blit(text, textPosition)\n\n def displayWhoWon(self, COLOR, winner, loser, screen, screen_size, position):\n # Creates the text string:\n text = \"{0} has defeated {1}!\".format(winner, loser)\n\n # Renders the text by the font chosen before\n text = self.font_36.render(text, True, COLOR)\n\n # Sets the text position:\n textPosition = self.setPosition(position, screen_size, text)\n\n # Sticks the text to the screen:\n screen.blit(text, textPosition)\n \n def displayDistance(self, COLOR, screen, distance, angle, mouse_position):\n # Creates the text string:\n text = \"Distance: {0}\".format(distance)\n text2 = \"Angle: {0}\".format(angle)\n \n # Renders the text by the font chosen before\n text = self.font_26.render(text, True, COLOR)\n text2 = self.font_26.render(text2, True, COLOR)\n text_2_x = mouse_position[0]\n text_2_y = mouse_position[1] + text2.get_rect()[3]\n text_2_pos = (text_2_x, text_2_y)\n \n # Blits the text:\n screen.blit(text, mouse_position)\n screen.blit(text2, text_2_pos)\n \n def displayMovementsLeft(self, COLOR, screen, movements_left):\n # Creates the text string:\n text = \"Movimentos: {0}\".format(movements_left)\n \n # Renders the text by the font chosen before\n text = self.font_26.render(text, True, COLOR)\n \n # Gets Position:\n textPosition = (0, 0)\n \n # Blits the text:\n screen.blit(text, textPosition)","sub_path":"class_textDisplay.py","file_name":"class_textDisplay.py","file_ext":"py","file_size_in_byte":7494,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"505437249","text":"# test_tweet.py is used to test the ability to tweet by tweeting\n# there is nothing specific about what should be tweeted\n\ndebug = True\nif debug:\n print('in test_tweet.py')\nimport tweepy as tp\nimport time\nimport os\nfrom keys import keys\n\nif debug:\n print('opening auth & api')\nauth = tp.OAuthHandler(keys['consumer_key'], keys['consumer_secret'])\nauth.set_access_token(keys['access_token'], keys['access_secret'])\napi = tp.API(auth)\n\nif debug:\n print('posting new status')\n#new_status = 'Hello! I\\'m Eric Cartbot #ArtificialIntelligence #ComputationalCreativity #TwitterBot'\nnew_status = 'There is nothing to see here. Move along, folks'\ntry:\n api.update_status(new_status)\nexcept tp.error.TweepError as err:\n print('TweepError: {}'.format(err))\n print('\\t' + new_status)\n\nif debug:\n print('end program')\n","sub_path":"test_tweet.py","file_name":"test_tweet.py","file_ext":"py","file_size_in_byte":826,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"340329015","text":"num = int(input())\nfor i in range(num):\n m = int(input())\n n = [1, 1, 1]\n if m < len(n):\n print(n[m])\n continue\n for j in range(3, m + 1):\n n[j] = n[j - 2] + n[j - 3]\n print(n[m])\n","sub_path":"Code/CodeRecords/2546/60730/287247.py","file_name":"287247.py","file_ext":"py","file_size_in_byte":216,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"97590901","text":"# -*- coding: utf-8 -*-\n\"\"\"\nThis file is part of pyCMBS.\n(c) 2012- Alexander Loew\nFor COPYING and LICENSE details, please refer to the LICENSE file\n\"\"\"\n\nfrom pycmbs.data import Data\nimport os\nfrom pycmbs.netcdf import *\nimport numpy as np\n\n\nclass Icon(Data):\n\n \"\"\"\n Main class for ICON data handling\n \"\"\"\n\n def __init__(self, filename, gridfile, varname, read=False, **kwargs):\n \"\"\"\n Parameters\n ----------\n\n filename : str\n filename of data file\n\n gridfile : str\n filename of grid definition file\n\n varname : str\n name of variable to handle\n\n read : bool\n specify if data should be read immediately\n \"\"\"\n Data.__init__(self, filename, varname, **kwargs)\n self.gridfile = gridfile\n self.gridtype = 'unstructured'\n\n#---\n\n def read(self, time_var='time'):\n \"\"\"\n This is a special routine for reading data from ICON structure\n a bit redundant to Data.read()\n\n Parameters\n ----------\n\n time_var : str\n name of time variable (default='time')\n \"\"\"\n print('Reading ICON data ...')\n\n if not os.path.exists(self.filename):\n raise ValueError('File not existing: %s' % self.filename)\n if not os.path.exists(self.gridfile):\n raise ValueError('File not existing: %s' % self.gridfile)\n\n #--- time variable\n self.time_var = time_var\n\n #--- data field\n # [time,ncell]\n self.data = self.read_netcdf(self.varname)\n nt, ncell = self.data.shape\n # reshape so we have a common 3D structure like always in pyCMBS\n self.data = self.data.reshape((nt, 1, ncell))\n if self.data is None:\n raise ValueError('The data in the file %s is not existing. \\\n This must not happen!' % self.filename)\n if self.scale_factor is None:\n raise ValueError('The scale_factor for file %s is NONE, \\\n this must not happen!' % self.filename)\n\n self.data *= self.scale_factor\n\n #--- read lat/lon\n File = NetCDFHandler()\n File.open_file(self.gridfile, 'r')\n # grid cell center coordinates\n self.lon = File.get_variable('clon') * 180. / np.pi\n self.lat = File.get_variable('clat') * 180. / np.pi\n self.ncell = len(self.lon)\n\n self.vlon = File.get_variable('clon_vertices') * 180. / np.pi\n self.vlat = File.get_variable('clat_vertices') * 180. / np.pi\n\n File.close()\n\n #--- read time variable\n if self.time_var is not None:\n # returns either None or a masked array\n self.time = self.read_netcdf(self.time_var)\n if hasattr(self.time, 'mask'):\n self.time = self.time.data\n else:\n self.time is None\n if self.time is not None:\n if self.time.ndim != 1:\n # remove singletone dimensions\n self.time = self.time.flatten()\n else:\n self.time = None\n\n #--- determine time --> convert to python timestep\n if self.time is not None:\n self.set_time()\n","sub_path":"pycmbs/icon.py","file_name":"icon.py","file_ext":"py","file_size_in_byte":3243,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"225738721","text":"import cv2\nimport numpy as np\n\no = cv2.imread('img2.jpg')\nimg = o\ngray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\nret, binary = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)\ncontours, hierarchy = cv2.findContours(binary, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)\n\ncv2.imshow('original', img)\n\nn = len(contours)\ncontoursImg = []\n\nfor i in range(n):\n print('Contours['+str(i)+'] Area=', cv2.contourArea(contours[i]))\n temp = np.zeros(img.shape, dtype=np.uint8)\n contoursImg.append(temp)\n contoursImg[i] = cv2.drawContours(contoursImg[i], contours, i, (255,255,255), 3)\n cv2.imshow('Contours['+str(i)+']', contoursImg[i])\n \ncv2.waitKey()\ncv2.destroyAllWindows()","sub_path":"ex12-5.py","file_name":"ex12-5.py","file_ext":"py","file_size_in_byte":674,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"45276725","text":"\nimport argparse\n\nclass Args(object):\n \n def __init__(self):\n self._parser = argparse.ArgumentParser(description='Get forward looking metrics from JIRA')\n\n self._parser.add_argument('-n',\n action=\"store\",\n dest=\"num_weeks\",\n type=int,\n default=6)\n\n self._parser.add_argument('-c',\n action=\"store\",\n dest=\"config_filename\",\n default='config.json')\n\n\n @property\n def args(self):\n return self._parser.parse_args()","sub_path":"jlf_stats/args.py","file_name":"args.py","file_ext":"py","file_size_in_byte":611,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"400810022","text":"# region ExitCodes\nQT_NOT_FOUND = 100\n# endregion\n\nCELL_SIZE = 60\nOUTER_BALL_SIZE = 48\nOUTER_BALL_SHIFT = (CELL_SIZE - OUTER_BALL_SIZE) // 2\nINNER_BALL_SIZE = 24\nINNER_BALL_SHIFT = (CELL_SIZE - INNER_BALL_SIZE) // 2\nSCORE_BOARD_SIZE = 3 * CELL_SIZE + 5\n\n# region Colors\n# region BallColors\nBALL_COLOR_GREEN = (56, 248, 183)\nBALL_COLOR_RED = (130, 21, 27)\nBALL_COLOR_BLUE = (24, 67, 226)\nBALL_COLOR_CYAN = (47, 199, 249)\nBALL_COLOR_YELLOW = (228, 230, 52)\nBALL_COLOR_MAGENTA = (59, 5, 81)\nBALL_COLOR_BROWN = (219, 183, 248)\n# endregion\n\nCELL_COLOR = (106, 110, 105)\n# endregion\n\nBALL_CHAR_GREEN = \"G\"\nBALL_CHAR_RED = \"R\"\nBALL_CHAR_BLUE = \"B\"\nBALL_CHAR_CYAN = \"C\"\nBALL_CHAR_YELLOW = \"Y\"\nBALL_CHAR_MAGENTA = \"M\"\nBALL_CHAR_BROWN = \"W\"\n\nCELL_CHAR = '.'\n\nHINT_MODE_MULTIPLIER = {0: 1, 1: 1.5, 2: 2}\n","sub_path":"config.py","file_name":"config.py","file_ext":"py","file_size_in_byte":793,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"482511224","text":"# uncompyle6 version 3.7.4\n# Python bytecode 3.7 (3394)\n# Decompiled from: Python 3.7.9 (tags/v3.7.9:13c94747c7, Aug 17 2020, 18:58:18) [MSC v.1900 64 bit (AMD64)]\n# Embedded file name: T:\\InGame\\Gameplay\\Scripts\\Server\\routing\\waypoints\\waypoint_generator_pool.py\n# Compiled at: 2020-03-06 03:29:12\n# Size of source mod 2**32: 13352 bytes\nfrom _math import Vector3\nfrom interactions.constraints import Nowhere, create_constraint_set, OceanStartLocationConstraint, WaterDepthIntervals, WaterDepthIntervalConstraint, Circle, Constraint\nfrom objects.pools import pool_utils\nfrom routing.waypoints.waypoint_generator import _WaypointGeneratorBase\nfrom sims4.color import Color\nfrom sims4.geometry import CompoundPolygon\nfrom sims4.tuning.tunable import TunableRange, Tunable, TunableTuple, OptionalTunable\nimport build_buy, debugvis, random, routing, sims4.log\nlogger = sims4.log.Logger('WaypointGeneratorPool')\n\nclass _WaypointGeneratorPool(_WaypointGeneratorBase):\n FACTORY_TUNABLES = {'constraint_width':TunableRange(description='\\n The width of the constraint created around the edge of the pool.\\n ',\n tunable_type=float,\n default=1.5,\n minimum=0), \n 'ocean_constraint_radius':TunableRange(description='\\n When in the ocean, the radius of the area around the nearest swim\\n portal to generate waypoints.\\n ',\n tunable_type=float,\n default=30,\n minimum=0,\n maximum=1000), \n 'ocean_constraint_distance_past_swim_portal':TunableRange(description='\\n When in the ocean, an offset away from the nearest swim portal to\\n center the area to generate waypoints.\\n ',\n tunable_type=float,\n default=0,\n minimum=0), \n 'ocean_unique_goal_count':TunableRange(description='\\n When in the ocean, the number of unique waypoints to generate.\\n ',\n tunable_type=int,\n default=10,\n minimum=0), \n 'shuffle_waypoints':Tunable(description='\\n If true, pool edge waypoint constraints will be shuffled and traversed in a random order.\\n If false, pool edge waypoint constraints will be traversed in counter-clockwise order. \\n ',\n tunable_type=bool,\n default=True), \n 'keep_away_from_edges':OptionalTunable(description='\\n If enabled, turns on a constraint that forces sims away from the pool edges by a tuned distance.\\n ',\n tunable=Tunable(description='\\n The distance from the pool edge.\\n ',\n tunable_type=float,\n default=0.25))}\n\n def __init__(self, *args, **kwargs):\n (super().__init__)(*args, **kwargs)\n sim = self._context.sim\n self._routing_surface = routing.SurfaceIdentifier(self._routing_surface.primary_id, self._routing_surface.secondary_id, routing.SurfaceType.SURFACETYPE_POOL)\n position = self._target.position if self._target is not None else sim.position\n level = self._routing_surface.secondary_id\n self._start_constraint = None\n self._master_depth_constraint = None\n self._waypoint_constraints = []\n self.keep_away_constraint = None\n self._location_is_pool = build_buy.is_location_pool(position, level)\n if self._location_is_pool:\n pool_block_id = build_buy.get_block_id(sim.zone_id, position, level - 1)\n pool = pool_utils.get_pool_by_block_id(pool_block_id)\n if pool is not None:\n pool_edge_constraints = pool.get_edge_constraint(constraint_width=(self.constraint_width), inward_dir=True,\n return_constraint_list=True)\n pool_edge_constraints = [constraint.generate_geometry_only_constraint() for constraint in pool_edge_constraints]\n if self.keep_away_from_edges is not None:\n bb_polys = build_buy.get_pool_polys(pool_block_id, level - 1)\n if len(bb_polys) > 0:\n bb_poly = bb_polys[0]\n _WaypointGeneratorPool._push_poly_inward(bb_poly, self.keep_away_from_edges)\n bb_poly.reverse()\n keep_away_geom = sims4.geometry.RestrictedPolygon(sims4.geometry.Polygon(bb_poly), ())\n self.keep_away_constraint = Constraint(routing_surface=(pool.provided_routing_surface), geometry=keep_away_geom)\n else:\n logger.error(f\"Pool Waypoint Generator: Pool polygon data unexpectedly empty while ${sim} was routing on a pool with id ${pool_block_id}.\", owner='jmorrow')\n for i in range(len(pool_edge_constraints)):\n pool_edge_constraints[i] = pool_edge_constraints[i].intersect(self.keep_away_constraint)\n\n self._start_constraint = create_constraint_set(pool_edge_constraints)\n self._waypoint_constraints = pool_edge_constraints\n\n def get_start_constraint(self):\n if self._start_constraint is not None:\n return self._start_constraint\n else:\n sim = self._context.sim\n position = self._target.position if self._target is not None else sim.position\n relative_offset_vector = Vector3(0, 0, self.ocean_constraint_distance_past_swim_portal)\n if self._target is not None:\n if self._target.routing_surface is not None:\n routing_surface = self._target.routing_surface\n else:\n routing_surface = sim.routing_surface\n if routing_surface.type != routing.SurfaceType.SURFACETYPE_POOL:\n self._start_constraint = OceanStartLocationConstraint.create_simple_constraint((WaterDepthIntervals.SWIM),\n (self.ocean_constraint_radius), sim, (self._target), position, ideal_radius=(self.constraint_width),\n ideal_radius_width=(self.constraint_width),\n relative_offset_vector=relative_offset_vector)\n else:\n self._start_constraint = Circle(position, (self.ocean_constraint_radius), routing_surface=(self._routing_surface))\n self._master_depth_constraint = WaterDepthIntervalConstraint.create_water_depth_interval_constraint(sim, WaterDepthIntervals.SWIM)\n self._start_constraint = self._start_constraint.intersect(self._master_depth_constraint)\n return self._start_constraint\n\n def get_waypoint_constraints_gen(self, routing_agent, waypoint_count):\n if self._start_constraint is None:\n self.get_start_constraint()\n if self._start_constraint is not None:\n if not self._waypoint_constraints:\n goals = []\n handles = self._start_constraint.get_connectivity_handles(routing_agent)\n for handle in handles:\n goals.extend(handle.get_goals(always_reject_invalid_goals=True))\n\n if goals:\n agent_radius = routing_agent.routing_component.pathplan_context.agent_radius\n ocean_goal_count = min(len(goals), self.ocean_unique_goal_count)\n for _ in range(ocean_goal_count):\n goal = random.choice(goals)\n if goal is None:\n break\n goals.remove(goal)\n constraint = Circle((goal.position), agent_radius, routing_surface=(self._routing_surface))\n self._waypoint_constraints.append(constraint.intersect(self._master_depth_constraint))\n\n available_waypoint_count = len(self._waypoint_constraints)\n if available_waypoint_count == 0:\n return\n use_pool_debug_visualizer = False and routing.waypoints.waypoint_generator.enable_waypoint_visualization and self._location_is_pool\n if use_pool_debug_visualizer:\n polygon_metadata = {}\n for i in range(waypoint_count):\n if i % available_waypoint_count == 0:\n if self.shuffle_waypoints:\n random.shuffle(self._waypoint_constraints)\n yield self._waypoint_constraints[(i % available_waypoint_count)]\n if use_pool_debug_visualizer:\n self._build_polygon_metadata_dictionary(polygon_metadata, self._waypoint_constraints[(i % available_waypoint_count)], i)\n\n if use_pool_debug_visualizer:\n self._draw_pool_debugvis(polygon_metadata)\n\n def _draw_pool_debugvis(self, polygon_metadata):\n color_palette = [\n Color.WHITE, Color.BLUE, Color.GREEN, Color.MAGENTA]\n if routing.waypoints.waypoint_generator.enable_waypoint_visualization:\n with debugvis.Context(routing.waypoints.waypoint_generator.DEBUGVIS_WAYPOINT_LAYER_NAME) as (layer):\n for entry in polygon_metadata.values():\n position = entry[0]\n waypoint_indices = entry[1]\n layer.add_text_world(position, f\"{waypoint_indices}\")\n\n for index, constraint in enumerate(self._waypoint_constraints):\n polygon = constraint.geometry.polygon\n layer.add_polygon(polygon, color=(color_palette[(index % 4)]), altitude=0.1)\n\n if self.keep_away_from_edges is not None:\n polygon = self.keep_away_constraint.geometry.polygon\n layer.add_polygon(polygon, color=(Color.BLACK), altitude=0.1)\n\n def _build_polygon_metadata_dictionary(self, polygon_metadata, constraint, waypoint_index):\n compound_polygon = constraint.geometry.polygon\n if isinstance(compound_polygon, CompoundPolygon):\n for polygon in compound_polygon:\n if len(polygon) > 0:\n key = polygon\n if key not in polygon_metadata:\n center = sum(polygon, Vector3.ZERO()) / len(polygon)\n polygon_metadata[key] = (center, [])\n waypoint_indices = polygon_metadata[key][1]\n waypoint_indices.append(waypoint_index)\n else:\n sim = self._context.sim\n logger.error(f\"Pool Waypoint Generator: Polygon unexpectedly contains no vertices while drawing debug visuals of ${sim}'s route\", owner='jmorrow')\n\n else:\n sim = self._context.sim\n logger.error(f\"Pool Waypoint Generator: Constraint geometry in unexpected format while drawing debug visuals of ${sim}'s route.\", owner='jmorrow')\n\n @staticmethod\n def _push_poly_inward(verts, amt):\n for i in range(1, len(verts)):\n _WaypointGeneratorPool._push_edge_inward(verts, i - 1, i, amt)\n\n _WaypointGeneratorPool._push_edge_inward(verts, i, 0, amt)\n\n @staticmethod\n def _push_edge_inward(verts, start, stop, amt):\n along = amt * sims4.math.vector_normalize(verts[stop] - verts[start])\n inward = sims4.math.vector3_rotate_axis_angle(along, sims4.math.PI / 2, sims4.math.Vector3.Y_AXIS())\n verts[start] += inward\n verts[stop] += inward","sub_path":"Scripts/simulation/routing/waypoints/waypoint_generator_pool.py","file_name":"waypoint_generator_pool.py","file_ext":"py","file_size_in_byte":11184,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"200755881","text":"\"\"\"\n\tKnuth-Morris-Pratt substring search\n\tO(|P| + |T|) time and space\n\"\"\"\ndef prefix_function(P):\n\t\"Return the prefix function of P\"\n\tn = len(P)\n\ts = [0] * n\n\tborder = 0\n\tfor i in range(1, n):\n\t\twhile border > 0 and P[i] != P[border]:\n\t\t\tborder = s[border-1]\n\t\tif P[i] == P[border]:\n\t\t\tborder = border + 1\n\t\telse: border = 0\n\t\ts[i] = border\n\treturn s\n\ndef find_all(P, T, sep):\n\t\"\"\"Return all occurrences of P in T.\n\tCharacter sep must not occur in either P or T.\"\"\"\n\tS = P + sep + T\n\ts = prefix_function(S)\n\tocc = []\n\tlenP, lenS = len(P), len(S)\n\tfor i in range(lenP+1, lenS):\n\t\tif s[i] == lenP:\n\t\t\tocc.append(i - 2 * lenP)\n\treturn occ\n\t\ndef main():\n\tT, P = input(), input()\n\tprint(' '.join(map(str, find_all(P, T, '\\x01'))))\n\t\nif __name__ == \"__main__\": main()\n\n","sub_path":"KMP.py","file_name":"KMP.py","file_ext":"py","file_size_in_byte":763,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"149842411","text":"#!/usr/bin/python3\n# transdecoder_predict_setup.py by josh\n\nimport re\nimport glob\nimport os\nimport subprocess\nimport sys\n\ntranscriptomeList = [os.path.abspath(x) for x in glob.glob(\"./*_Peru_mega_transcriptome_Josh.fasta\")]\n\ntranscriptomeList.sort()\n\nprint(transcriptomeList)\nprint(len(transcriptomeList))\n\ncommandListName = \"predict_array_commands.txt\"\ncommandList = open(commandListName, \"w\")\n\nfor transcriptome in transcriptomeList:\n print(transcriptome)\n outDir = transcriptome + \".transdecoder_dir\"\n print(outDir)\n blastOutFile = outDir + \"/blastp.outfmt6\"\n print(blastOutFile)\n pfamOutFile = outDir + \"/pfam.domtblout\"\n print(pfamOutFile)\n transdecoderCommand = \"/data/home/btw915/programs/login2/TransDecoder-TransDecoder-v5.0.2/TransDecoder.Predict -t {} --retain_pfam_hits {} --retain_blastp_hits {}\".format(transcriptome, pfamOutFile, blastOutFile)\n print(transdecoderCommand)\n commandList.write(transdecoderCommand + \"\\n\")\n\ncommandList.close()\n\narrayFileName = \"predict_array.sh\"\n\narrayFile = open(arrayFileName, \"w\")\n\narrayFile.write(\"\"\"#!/bin/sh\n#$ -cwd\\t\\t\\t# Use current working directory\n#$ -V\\t\\t\\t# Verbose\n#$ -j y\\t\\t\\t# Maximum output, inc errors\n#$ -r y\\t\\t\\t# Combine output files\\n\"\"\")\narrayFile.write(\"#$ -pe smp 1\\t\\t\\t# Request CPU cores\\n\")\narrayFile.write(\"\"\"#$ -l h_rt=48:0:0\\t\\t\\t# Request runtime (up to 240 hours)\n#$ -l h_vmem=8G\\t\\t\\t# Request RAM per core\n#$ -l node_type=nxv\\t\\t\\t# Node type\n#$ -m bea\\t\\t\\t# Status emails\\n\"\"\")\narrayFile.write(\"#$ -t 1-{}\\n\\n\".format(str(len(transcriptomeList))))\n\narrayFile.write(\"module load perl\\n\")\narrayFile.write(\"module load perl5lib\\n\")\narrayFile.write(\"module load blast+\\n\")\narrayFile.write(\"module load hmmer\\n\\n\")\n\narrayFile.write(\"\"\"COMMAND1=\"$(sed -n -e \"$SGE_TASK_ID p\" predict_array_commands.txt)\"\\n\\n\"\"\")\narrayFile.write(\"echo -e \\\"$COMMAND1\\n\\n\\\"\\n\\n\")\narrayFile.write(\"$COMMAND1\\n\")\n\narrayFile.close()\n\nsubprocess.call([\"chmod\",\"u+x\",\"{}\".format(arrayFileName)])\n\nquit()\n","sub_path":"transdecoder_predict_setup.py","file_name":"transdecoder_predict_setup.py","file_ext":"py","file_size_in_byte":1990,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"173376585","text":"import os, h5py\nimport scipy.io as mat_load\nimport numpy as np\nnp.random.seed(1337) # for reproducibility\n\nimport numpy.random as rng\nfrom keras.models import Sequential, Model\nfrom keras.layers import Dense, Dropout, Input, Lambda, BatchNormalization\nfrom keras import optimizers\nfrom keras import backend as K\nfrom keras.models import Model\nfrom keras.layers import Conv2D, MaxPooling2D,concatenate\nfrom keras.layers import Activation, Dropout, Flatten, Dense,Input\nfrom keras.utils.data_utils import get_file\nfrom keras.preprocessing.image import ImageDataGenerator\nfrom keras.models import load_model\nfrom keras.preprocessing import image\nfrom keras.applications.vgg16 import preprocess_input\nfrom keras.applications import vgg16, vgg19,inception_v3,resnet50\n\n#parameters\nimg_width, img_height, depth = 224,224,3\nimg_input = Input(shape=(img_height,img_width,depth))\nnb_train_samples = 162770\nnb_validation_samples = 202599\nnb_epoch = 2\nbatch_size = 64\n\n# define top_network\ndef top_network(network_input):\n #bn_name = 'bn_' + str(id)\n y = Conv2D(300, (3, 3), activation='relu', padding='same')(network_input)\n y = BatchNormalization()(y)\n top_output = MaxPooling2D((5, 5), strides=(2, 2))(y)\n\n top_model = Model(inputs = network_input, outputs = top_output)\n return top_model\n\n# TODO Step 1: Date generators\ndef train_generator():\n #full_image_dir = 'keras_data/full_image/train'\n image_dir = 'data/img_align_celeba/'\n label_file = mat_load.loadmat('data/celebA_attr_label')\n label_data = label_file['labels']\n train_batch_size = batch_size\n image_id = 1\n train_index_thr = batch_size * int(nb_train_samples/batch_size)\n\n while True:\n\n batch_feature = []\n image_count = 0\n attr_label = np.array([[0 for aa in range(40)]for xx in range(batch_size)])\n\n if((image_id+batch_size) > train_index_thr):\n image_id = 1\n\n while(image_count < train_batch_size and image_id < nb_train_samples):\n #image_id = rng.randint(1,nb_train_samples)\n try:\n #val_flag = False\n filename = image_dir + str(image_id).zfill(6) + '.jpg'\n face_img = image.load_img(filename, target_size=(img_height,img_width))\n x = image.img_to_array(face_img)\n x = np.expand_dims(x, axis=0)\n feature01 = preprocess_input(x)\n\n for ll in range(40):\n attr_label[image_count][ll] = label_data[image_id-1][ll]\n\n batch_feature += [feature01]\n image_count = image_count + 1\n image_id = image_id + 1\n except IOError:\n continue\n\n label_attr01 = attr_label[:,0]\n label_attr02 = attr_label[:,1]\n label_attr03 = attr_label[:,2]\n label_attr04 = attr_label[:,3]\n label_attr05 = attr_label[:,4]\n label_attr06 = attr_label[:,5]\n label_attr07 = attr_label[:,6]\n label_attr08 = attr_label[:,7]\n label_attr09 = attr_label[:,8]\n label_attr10 = attr_label[:,9]\n label_attr11 = attr_label[:,10]\n label_attr12 = attr_label[:,11]\n label_attr13 = attr_label[:,12]\n label_attr14 = attr_label[:,13]\n label_attr15 = attr_label[:,14]\n label_attr16 = attr_label[:,15]\n label_attr17 = attr_label[:,16]\n label_attr18 = attr_label[:,17]\n label_attr19 = attr_label[:,18]\n label_attr20 = attr_label[:,19]\n label_attr21 = attr_label[:,20]\n label_attr22 = attr_label[:,21]\n label_attr23 = attr_label[:,22]\n label_attr24 = attr_label[:,23]\n label_attr25 = attr_label[:,24]\n label_attr26 = attr_label[:,25]\n label_attr27 = attr_label[:,26]\n label_attr28 = attr_label[:,27]\n label_attr29 = attr_label[:,28]\n label_attr30 = attr_label[:,29]\n label_attr31 = attr_label[:,30]\n label_attr32 = attr_label[:,31]\n label_attr33 = attr_label[:,32]\n label_attr34 = attr_label[:,33]\n label_attr35 = attr_label[:,34]\n label_attr36 = attr_label[:,35]\n label_attr37 = attr_label[:,36]\n label_attr38 = attr_label[:,37]\n label_attr39 = attr_label[:,38]\n label_attr40 = attr_label[:,39]\n\n batch_feature = np.array(batch_feature)\n batch_feature = np.squeeze(batch_feature)\n\n yield (batch_feature,[label_attr01,label_attr02,label_attr03, \\\n label_attr04,label_attr05,label_attr06,label_attr07, \\\n label_attr08,label_attr09,label_attr10,label_attr11, \\\n label_attr12,label_attr13,label_attr14,label_attr15, \\\n label_attr16,label_attr17,label_attr18,label_attr19, \\\n label_attr20,label_attr21,label_attr22,label_attr23, \\\n label_attr24,label_attr25,label_attr26,label_attr27, \\\n label_attr28,label_attr29,label_attr30,label_attr31, \\\n label_attr32,label_attr33,label_attr34,label_attr35, \\\n label_attr36,label_attr37,label_attr38,label_attr39,label_attr40])\n\n\n(feature, [l01,l02,l03,l04,l05,l06,l07,l08,l09,l10, \\\n l11,l12,l13,l14,l15,l16,l17,l18,l19,l20, \\\n l21,l22,l23,l24,l25,l26,l27,l28,l29,l30,\\\n l31,l32,l33,l34,l35,l36,l37,l38,l39,l40]) = next(train_generator())\n\nprint(feature.shape)\nprint(l01.shape)\n","sub_path":"scrap01.py","file_name":"scrap01.py","file_ext":"py","file_size_in_byte":5381,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"253574122","text":"\"\"\"\nHere is the \"write\" part of the API, to signal more data is ready.\nIt includes the actual webhooks sent e.g. by Gitlab, as well as\nAPI calls to update batches and outputs.\n\"\"\"\nimport sys\nimport json\nimport yaml\nimport datetime\nimport traceback\nimport subprocess\nfrom pathlib import Path\n\nfrom flask import request, jsonify\nfrom sqlalchemy.orm.exc import NoResultFound\nfrom sqlalchemy.orm.attributes import flag_modified\n\nfrom backend import app, repos, db_session\nfrom ..models import Project, CiCommit, Batch, Output, TestInput\nfrom ..models.Project import update_project\n\nfrom qaboard.conventions import deserialize_config\n\n\n@app.route('/api/v1/batch', methods=['POST'])\n@app.route('/api/v1/batch/', methods=['POST'])\ndef update_batch():\n data = request.get_json()\n try:\n ci_commit = CiCommit.get_or_create(\n session=db_session,\n hexsha=request.json['git_commit_sha'],\n project_id=request.json['project'],\n )\n except:\n return f\"404 ERROR:\\n ({request.json['project']}): There is an issue with your commit id ({request.json['git_commit_sha']})\", 404\n\n batch = ci_commit.get_or_create_batch(data['batch_label'])\n if not batch.data:\n batch.data = {}\n batch_data = request.json.get('data', {})\n batch.data = {**batch.data, **batch_data}\n\n command = request.json.get('command')\n if command:\n batch.data[\"commands\"] = {**batch.data.get('commands', {}), **command}\n flag_modified(batch, \"data\")\n\n is_best = 'best_iter' in batch_data and batch_data['best_iter'] != batch.data.get('best_iter')\n if is_best:\n # remove all non-optim_iteration results from the batch\n batch.outputs = [o for o in batch.outputs if o.output_type=='optim_iteration']\n db_session.add(batch)\n db_session.commit()\n # make copy of all outputs in the best batch\n best_batch = ci_commit.get_or_create_batch(f\"{data['batch_label']}|iter{batch_data.get('best_iter')}\")\n for o in best_batch.outputs:\n o_copy = o.copy()\n o_copy.output_dir_override = str(o.output_dir)\n o_copy.batch = batch\n db_session.add(o_copy)\n\n db_session.add(batch)\n db_session.commit()\n return jsonify({\"status\": \"OK\"})\n\n\n\n@app.route('/api/v1/batch/stop', methods=['POST'])\n@app.route('/api/v1/batch/stop/', methods=['POST'])\ndef stop_batch():\n data = request.get_json()\n try:\n batch = Batch.query.filter(Batch.id == data['id']).one()\n except:\n return f\"404 ERROR:\\n Not found\", 404\n status = batch.stop()\n return jsonify(status), 200 if not \"error\" in status else 500\n\n@app.route('/api/v1/batch/redo', methods=['POST'])\n@app.route('/api/v1/batch/redo/', methods=['POST'])\ndef redo_batch():\n data = request.get_json()\n try:\n batch = Batch.query.filter(Batch.id == data['id']).one()\n except:\n return f\"404 ERROR:\\n Not found\", 404\n status = batch.redo(only_deleted=data.get('only_deleted', False))\n return '{\"status\": \"OK\"}'\n\n@app.route('/api/v1/batch/rename', methods=['POST'])\n@app.route('/api/v1/batch/rename/', methods=['POST'])\ndef rename_batch():\n data = request.get_json()\n try:\n batch = Batch.query.filter(Batch.id == data['id']).one()\n except:\n return f\"404 ERROR:\\n Not found\", 404\n status = batch.rename(label=data['label'], db_session=db_session)\n return '{\"status\": \"OK\"}'\n\n\n@app.route('/api/v1/batch/', methods=['DELETE'])\n@app.route('/api/v1/batch//', methods=['DELETE'])\ndef delete_batch(batch_id):\n try:\n batch = Batch.query.filter(Batch.id == batch_id).one()\n except:\n return f\"404 ERROR:\\nNot found\", 404\n stop_status = batch.stop()\n if \"error\" in stop_status:\n return jsonify(stop_status), 500\n batch.delete(session=db_session, only_failed=request.args.get('only_failed', False))\n return {\"status\": \"OK\"}\n\n\n\n@app.route('/api/v1/output', methods=['POST'])\n@app.route('/api/v1/output/', methods=['POST'])\ndef new_output_webhook():\n \"\"\"Updates the database when we get new results.\"\"\"\n data = request.get_json()\n\n # We get a handle on the Commit object related to our new output\n try:\n ci_commit = CiCommit.get_or_create(\n session=db_session,\n hexsha=data['git_commit_sha'],\n project_id=data['project'],\n )\n except:\n return jsonify({\"error\": f\"Could not find your commit ({data['git_commit_sha']}).\"}), 404\n\n ci_commit.project.latest_output_datetime = datetime.datetime.utcnow()\n ci_commit.latest_output_datetime = datetime.datetime.utcnow()\n\n # We make sure the Test on which we ran exists in the database \n test_input_path = data.get('input_path')\n if not test_input_path:\n return jsonify({\"error\": \"the input path was not provided\"}, 400)\n test_input = TestInput.get_or_create(\n db_session,\n path=test_input_path,\n database=data.get('database', ci_commit.project.database),\n )\n\n # We save the basic information about our result\n batch = ci_commit.get_or_create_batch(data['batch_label'])\n if not batch.data:\n batch.data = {}\n batch.data.update({\"type\": data['job_type']})\n if data.get('input_metadata'):\n test_input.data['metadata'] = data['input_metadata']\n flag_modified(test_input, \"data\")\n\n platform = data['platform']\n # if platform == 'lsf':\n # platform = 'linux'\n # elif platform == 'windows':\n # platform = 'win32'\n\n configurations = deserialize_config(data['configuration']) if 'configuration' in data else data['configurations']\n output = Output.get_or_create(db_session,\n batch=batch,\n platform=platform,\n configurations=configurations,\n extra_parameters=data['extra_parameters'],\n test_input=test_input,\n )\n output.output_type = data.get('input_type', '')\n\n output.data = data.get('data', {})\n # we can only trust CI outputs to run on the exact code from the commit\n output.data[\"ci\"] = data['job_type'] == 'ci'\n if output.deleted:\n output.deleted = False\n\n # We allow users to save their data in custom locations\n # at the commit and output levels\n if Path(data.get('commit_ci_dir', ci_commit.commit_dir)).resolve() != Path(ci_commit.commit_dir):\n ci_commit.commit_dir_override = data.get('commit_ci_dir')\n if Path(data.get('output_directory', output.output_dir)) != output.output_dir:\n output.output_dir_override = data.get('output_directory')\n\n # We update the output's status\n output.is_running = data.get('is_running', False)\n if output.is_running:\n output.is_pending = True\n else:\n output.is_pending = data.get('is_pending', False)\n\n # We save the output's metrics\n if not output.is_pending:\n metrics = data.get('metrics', {})\n output.metrics = metrics\n output.is_failed = data.get('is_failed', False) or metrics.get('is_failed')\n\n db_session.add(output)\n db_session.commit()\n return jsonify(output.to_dict())\n\n\n\n@app.route('/webhook/gitlab', methods=['GET', 'POST'])\ndef gitlab_webhook():\n \"\"\"Gitlab calls this endpoint every push, it garantees we stay synced.\"\"\"\n # https://docs.gitlab.com/ce/user/project/integrations/webhooks.html\n data = json.loads(request.data)\n print(data, file=sys.stderr)\n update_project(data, db_session)\n return \"{status:'OK'}\"\n\n","sub_path":"backend/backend/api/webhooks.py","file_name":"webhooks.py","file_ext":"py","file_size_in_byte":7247,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"300388251","text":"import os\nimport numpy as np\nimport csv\nimport pubchempy as pcp\nimport argparse\nimport pickle\nfrom tqdm import tqdm\nfrom rdkit import Chem\nfrom rdkit.Chem import AllChem\nimport modtox.Helpers.preprocess as pr\n\n\nclass PubChem():\n \n def __init__(self, pubchem_folder, stored_files, csv_filename, outputfile, substrate):\n if stored_files != False: self.unknown = False\n else: self.unknown = True\n self.csv_filename = csv_filename\n self.folder = pubchem_folder\n self.outputfile = outputfile\n self.substrate = substrate\n self.splitting()\n\n def to_inchi(self, which_names):\n return [pcp.Compound.from_cid(int(i)).inchi for i in tqdm(which_names)]\n\n def splitting(self):\n if self.unknown:\n print('Reading from {}'.format(self.csv_filename))\n data = self.reading_from_pubchem()\n else:\n try: data = self.reading_from_file()\n except: \n print('Need to provide a valid input file or to read the PubChem file')\n self.active_names = [mol for mol, activity in data.items() if activity == 'Active']\n self.inactive_names = [mol for mol, activity in data.items() if activity == 'Inactive']\n\n def to_sdf(self, actype):\n\n molecules = []\n molecules_rdkit = []\n output = actype + '.sdf'\n w = Chem.SDWriter(output)\n print('Filter and inchikey identification in process ... for {}'.format(actype))\n if actype == 'actives': \n iks, names = self.filtering(self.active_names)\n self.active_inchi = iks\n self.active_names = names\n \n if actype == 'inactives':\n iks, names = self.filtering(self.inactive_names)\n self.inactive_inchi = iks\n self.inactive_names = names\n\n for inchy, name in tqdm(zip(iks, names), total=len(names)-1):\n try:\n m = Chem.inchi.MolFromInchi(str(inchy))\n Chem.AssignStereochemistry(m)\n AllChem.EmbedMolecule(m)\n m.SetProp(\"_Name\", name)\n m.SetProp(\"_MolFileChiralFlag\", \"1\")\n molecules_rdkit.append(m)\n except IndexError:\n print(\"Molecules {} not found\".format(name))\n \n for m in molecules_rdkit: \n w.write(m)\n\n return output, len(names)\n\n\n def filtering(self, which_names):\n iks = self.to_inchi(which_names)\n #checking duplicates\n uniq = set(iks)\n if len(iks) > len(uniq): #cheking repeated inchikeys\n indices = { value : [ i for i, v in enumerate(iks) if v == value ] for value in uniq }\n filt_inchi = [iks[x[0]] for x in indices.values()] #filtered inchikeys\n filt_ids = [which_names[x[0]] for x in indices.values()] #filtering ids: we only get the first\n return filt_inchi, filt_ids\n else:\n print('Duplicates not detected') \n return iks, which_names\n\n\n def reading_from_pubchem(self, total_molec = 100, trash_lines = 8):\n with open(os.path.join(self.folder, self.csv_filename), 'r') as csvfile:\n spamreader = csv.reader(csvfile, delimiter=',')\n idx = None; activities = {}; i = 0\n for row in spamreader:\n if i < total_molec + trash_lines:\n try: idx = row.index(self.substrate + ' ' + 'Activity Outcome') \n except: pass\n if idx != None and i > trash_lines: \n name = row[1]\n activities[name] = row[idx]\n i += 1\n with open(self.outputfile, 'wb') as op:\n pickle.dump(activities, op)\n return activities\n\n def reading_from_file(self): \n \n with open(self.inputname, 'rb') as f:\n data = pickle.load(f)\n return data\n\n\ndef process_pubchem(pubchem_folder, csv_filename, substrate, stored_files = None, outputfile = 'inchi_all.pkl', test=False):\n pub_chem = PubChem(pubchem_folder, stored_files, csv_filename, outputfile, substrate)\n active_output, n_actives = pub_chem.to_sdf(actype = 'actives')\n inactive_output, n_inactives = pub_chem.to_sdf(actype = 'inactives') \n if not test: \n output_proc = pr.ligprep(active_output)\n else:\n output_proc = active_output\n\n return output_proc, inactive_output\n\ndef parse_args(parser):\n parser.add_argument(\"--pubchem\", type=str, help='Pubchem folder')\n parser.add_argument(\"--stored_files\", action = 'store_true', help='Pubchem folder')\n parser.add_argument(\"--csv_filename\", type=str, help = \"csv filename with activities data (e.g. 'AID_1851_datatable_all.csv')\")\n parser.add_argument(\"--substrate\", type = str, help = \"substrate name codification on csv file (e.g. p450-cyp2c9)\") \n","sub_path":"modtox/data/pubchem.py","file_name":"pubchem.py","file_ext":"py","file_size_in_byte":4852,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"360725610","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n# File Name : url\n# Created by ckcat on 1/4/20\n\nfrom django.conf.urls import url\nfrom booktest import views\n\nurlpatterns = [\n url(r'^$', views.index),\n url(r'^temp_var/$', views.temp_var),\n url(r'^temp_tags/$', views.temp_tags),\n url(r'^temp_filter/$', views.temp_filter),\n url(r'^temp_inherit/$', views.temp_inherit),\n url(r'^html_escape/$', views.html_escape),\n url(r'^login/$', views.login),\n url(r'^login_check/$', views.login_check),\n url(r'^post/$', views.post),\n url(r'^post_action/$', views.post_action),\n url(r'^verify_code/$', views.verify_code),\n url(r'^verify_show/$', views.verify_show),\n url(r'^verify_yz/$', views.verify_yz),\n url(r'^verify_change/$', views.verify_change),\n url(r'^fan1/$', views.fan1),\n url(r'^fan_show/$', views.fan2, name='fan2'),\n url(r'^fan(\\d+)_(\\d+)/$', views.fan3, name='fan3'),\n url(r'^fan(?P\\d+)_(?P\\d+)/$', views.fan4, name='fan4'),\n]","sub_path":"Python/Django/test4/booktest/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":987,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"327687026","text":"import numpy as np\nimport pandas as pd\nimport torch\nfrom sklearn import preprocessing\nfrom sklearn.model_selection import train_test_split\n\nDATASET_FILENAME = 'harddrive.csv'\n\nMANUFACTURERS = {'HG':'HGST',\n 'Hi':'Hitachi',\n 'SA':'Samsung',\n 'ST':'Seagate',\n 'TO':'Toshiba',\n 'WD':'Western Digital'}\n\nKNOWN_INDICATIVE_COLUMNS = ['smart_5_raw','smart_10_raw','smart_184_raw','smart_187_raw',\n 'smart_188_raw','smart_196_raw','smart_197_raw','smart_198_raw',\n 'smart_201_raw']\n\ndef calc_weeks_to_failure(s):\n s = s.reset_index(drop=True)\n one = s[s.eq(1)]\n if one.empty:\n return -1\n else:\n return (-s.index + one.index[0]) // 7\n\n\ndef get_data(filename=DATASET_FILENAME):\n df = pd.read_csv(filename,parse_dates=['date'])\n print('read data, processing...')\n\n #adding manufacturer info to data\n conditions = [df['model'].str[:2] == mfr for mfr in sorted(MANUFACTURERS.keys())]\n outputs = [MANUFACTURERS[key] for key in sorted(MANUFACTURERS.keys())]\n res = np.select(conditions,outputs,'unknown')\n df['manufacturer'] = pd.Series(res)\n\n #showing summed failures by manufacturer\n grouped = df.groupby(['manufacturer'])#,'serial_number'])\n print(grouped.failure.sum())\n\n df = pd.DataFrame(grouped.get_group('Seagate'))\n\n #adding failure information per serial number\n df['week_to_failure'] = df.groupby('serial_number').failure.transform(calc_weeks_to_failure)\n df = df[df['week_to_failure'] <= 0]\n\n\n reduced_df = df[['week_to_failure','model'] + KNOWN_INDICATIVE_COLUMNS]\n reduced_df = reduced_df.fillna(-0.5) # give numeric value to NaN\n\n return reduced_df\n\ndef preprocess_data(df):\n print('feature encoding')\n features = ['model']\n for feature in features:\n le = preprocessing.LabelEncoder()\n le = le.fit(df[feature])\n df[feature] = le.transform(df[feature])\n\n enc = preprocessing.OneHotEncoder(categories='auto',sparse=False)\n weeks_to_failure = np.array(df['week_to_failure']).reshape(-1,1)\n weeks_to_failure = enc.fit_transform(np.array(weeks_to_failure))\n\n scaler = preprocessing.MinMaxScaler()\n columns = KNOWN_INDICATIVE_COLUMNS[:]\n columns.remove('smart_188_raw')\n scaler.fit(df[columns])\n df[columns] = scaler.transform(df[columns])\n\n X_train, X_test, y_train, y_test = train_test_split(df.drop(['week_to_failure'],axis=1), weeks_to_failure, test_size=0.2)\n return X_train, X_test, y_train, y_test, enc\n\ndef to_tensor(data):\n return torch.Tensor(np.array(pd.DataFrame(data)))\n\nif __name__ == \"__main__\":\n get_data()\n\n'''\nNotes:\n\nsmart_1 Read Error Rate (want low)\nsmart_2 Throughput performance (want high)\nsmart_3 Spin up time (want low)\nsmart_4 Start-stop count\n! smart_5 Reallocated sectors count (want low)\nsmart_7 Seek error rate (vendor specific, value not comparable between vendors)\nsmart_8 Seek time performance (want high)\nsmart_9 Power on hours\n! smart_10 Spin retry count (want low)\nsmart_11 Recalibration retries (want low)\nsmart_12 Power cycle count\nsmart_13 Soft read error rate (uncorrected read errors, want low)\nsmart_15 unknown\nsmart_22 Current helium level (want high)\nsmart_183 SATA downshift error rate (want low)\n! smart_184 End-to-end error (want low)\n! smart_187 Count of errors that couldn't be recovered (want low)\n! smart_188 Command timeout (aborted operations due to timeout) (should be zero)\nsmart_189 High fly writes (want low)\nsmart_190 Temp diff (100 minus temperature in celsius)\nsmart_191 G sense error rate (errors from external shock) (want low)\nsmart_192 Emergency retract cycle count (want low)\nsmart_193 Load cycle count (want low)\nsmart_194 Temperature (want low)\nsmart_195 Hardware ECC recovered (vendor specific)\n! smart_196 Reallocation event count (want low)\n! smart_197 Current pending sector count (want low)\n! smart_198 Uncorrectable sector count (want low)\nsmart_199 UltraDMA CRC error count (want low)\nsmart_200 Multi-zone error rate (want low)\n! smart_201 Soft read error rate (want low)\nsmart_220 Disk shift (want low)\nsmart_222 Loaded hours (time spent under load)\nsmart_223 Load/unload retry count\nsmart_224 Load friction (want low)\nsmart_225 Load/unload cycles (want low)\nsmart_226 Load in time\nsmart_240 Head flying hours\nsmart_241 Total LBAs written\nsmart_242 Total LBAs read\nsmart_250 Read error retry rate (want low)\nsmart_251 Minimum spares remaining\nsmart_252 Newly added bad flask block\nsmart_254 Free fall events (want low)\nsmart_255 unknown\n\n'''","sub_path":"data.py","file_name":"data.py","file_ext":"py","file_size_in_byte":4589,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"178759614","text":"from contextlib import contextmanager # noqa\n\nimport redis\n\nimport pytest\n\nfrom bluesky.tests.conftest import RE # noqa\nfrom bluesky_kafka import BlueskyConsumer # noqa\nfrom bluesky_kafka.tests.conftest import ( # noqa\n pytest_addoption,\n kafka_bootstrap_servers,\n broker_authorization_config,\n consume_documents_from_kafka_until_first_stop_document,\n temporary_topics,\n)\nfrom ophyd.tests.conftest import hw # noqa\n\nfrom nslsii.md_dict import RunEngineRedisDict\n\n\n@pytest.fixture\ndef redis_dict_factory():\n \"\"\"\n Return a \"fixture as a factory\" that will build identical RunEngineRedisDicts.\n Before the factory is returned, the Redis server will be cleared.\n\n The factory builds only RunEngineRedisDict instances for a Redis server running\n on localhost:6379, db=0.\n\n If \"host\", \"port\", or \"db\" are specified as kwargs to the factory function\n an exception will be raised.\n \"\"\"\n redis_server_kwargs = {\n \"host\": \"localhost\",\n \"port\": 6379,\n \"db\": 0,\n }\n\n redis_client = redis.Redis(**redis_server_kwargs)\n redis_client.flushdb()\n\n def _factory(**kwargs):\n disallowed_kwargs_preset = set(redis_server_kwargs.keys()).intersection(\n kwargs.keys()\n )\n if len(disallowed_kwargs_preset) > 0:\n raise KeyError(\n f\"{disallowed_kwargs_preset} given, but 'host', 'port', and 'db' may not be specified\"\n )\n else:\n kwargs.update(redis_server_kwargs)\n\n return RunEngineRedisDict(**kwargs)\n\n return _factory\n","sub_path":"nslsii/tests/conftest.py","file_name":"conftest.py","file_ext":"py","file_size_in_byte":1570,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"587440420","text":"# Future patches\nfrom __future__ import annotations\n\n# Stdlib\nimport random\nfrom typing import TYPE_CHECKING\n\n# External Libraries\nimport anyio\n\n# MCServer\nfrom mcserver.classes.player import Player\nfrom mcserver.objects.packet_handler import PacketHandler\nfrom mcserver.objects.player_registry import PlayerRegistry\nfrom mcserver.utils.logger import error\n\nif TYPE_CHECKING:\n from typing import Tuple, Any\n from mcserver.classes.client_message import ClientMessage\n\n\ndef _remap_name(name: str) -> str:\n if name in (\"handshake\", \"status_request\", \"status_ping\", \"login_start\", \"keep_alive\"):\n # Don't pass these to events\n return \"\"\n if name == \"login_encryption_response\":\n return \"player_join\"\n return name\n\n\nclass EventHandler:\n @classmethod\n def handle_event(cls, msg: ClientMessage, args: Tuple[Any]):\n event = _remap_name(msg.name)\n if event:\n func = getattr(cls, \"event_\" + event,\n lambda *_: error(f\"Unhandled event: {event}\"))\n if args:\n if not isinstance(args, tuple):\n args = (args, )\n return func(msg, *args)\n return func(msg)\n return None\n\n @classmethod\n async def event_chat_message(cls, msg: ClientMessage, message: str):\n for player in PlayerRegistry.players:\n await PacketHandler.encode_chat_message(msg, player, f\"<{msg.conn.player.display_name}> {message}\")\n\n @classmethod\n async def event_player_join(cls, msg: ClientMessage, player: Player):\n for _player in PlayerRegistry.players:\n # PacketHandler.encode_player_info(msg, player, _player, 0)\n await PacketHandler.encode_chat_message(msg, _player, f\"\\u00a7e{player.display_name} has joined.\")\n\n await PacketHandler.encode_player_join(msg, player)\n await PacketHandler.encode_player_spawn_pos(msg, player)\n await PacketHandler.encode_player_position_look(msg, player)\n await PacketHandler.encode_player_spawn(msg, player, player)\n while msg.conn.do_loop:\n val = random.randint(0, 2**20)\n msg.send_packet(\n \"keep_alive\",\n msg.buffer_type.pack_varint(val) if msg.protocol_version <= 338 else msg.buffer_type.pack(\"Q\", val)\n )\n keep_alive_packet = await msg.conn.wait_for_packet(\"keep_alive\")\n\n # 1.7.x\n if msg.protocol_version <= 338:\n verify = keep_alive_packet.unpack_varint()\n else:\n verify = keep_alive_packet.unpack(\"Q\")\n\n if val != verify:\n msg.close_connection(\"Invalid KeepAlive packet!\")\n return\n\n await anyio.sleep(1)\n","sub_path":"mcserver/objects/event_handler.py","file_name":"event_handler.py","file_ext":"py","file_size_in_byte":2750,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"158762071","text":"#!/bin/python3\n\n# The MIT License (MIT)\n#\n# Copyright (c) 2015 Gustav Näslund\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software without restriction, including without limitation the rights\n# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n# copies of the Software, and to permit persons to whom the Software is\n# furnished to do so, subject to the following conditions:\n\nimport sys, os, argparse\n\ndef lsb_to_int(b_a):\n return b_a[0] + 256*b_a[1] + 256*256*b_a[2] + 256*256*256*b_a[3]\n\ndef convert_bmp(infile):\n with open(infile, \"rb\") as f2:\n bitmap = list(f2.read())\n\n header = bitmap[:2]\n size = lsb_to_int(bitmap[2:6])\n offset = lsb_to_int(bitmap[10:14])\n width = lsb_to_int(bitmap[18:22])\n height = lsb_to_int(bitmap[22:26])\n data = [255-x for x in bitmap[offset:][::-1]]\n\n if int(width/8)%4:\n padding = 4 - int(width/8)%4\n else:\n padding = 0\n\n f.write(\"/* header: \" + str([chr(x) for x in header]) + \" */\\n\")\n f.write(\"/* size: \" + str(size) + \" B */\\n\")\n f.write(\"/* offset: \" + str(offset) + \" B */\\n\")\n f.write(\"/* width: \" + str(width) + \" px */\\n\")\n f.write(\"/* height: \" + str(height) + \" px */\\n\")\n f.write(\"/* padding: \" + str(padding) + \" B */\\n\")\n\n all_padded_bytes = []\n # Range of padded bytes per row\n for p in range(int(width/8), int(width/8)+padding):\n all_padded_bytes += list(range(p, len(data), 8))\n\n if args.remove_padding:\n for index in sorted(all_padded_bytes, reverse=True):\n del data[index]\n\n for i, value in enumerate(data[::-1]):\n if i%16 == 0:\n f.write(\"\\n\")\n f.write(hex(value)+\",\")\n\nparser = argparse.ArgumentParser(description='Convert monochrome bitmaps into arrays suitable for viewing with a T6963C-compatible LCD-controller.')\nparser.add_argument('input', help='an input for the script, either a file or a folder')\nparser.add_argument('--remove-padding', action='store_true', help='Remove the padding bytes from the bitmap rows.')\nargs = parser.parse_args()\n\nif os.path.isdir(args.input):\n infiles = [os.path.join(args.input, f) for f in sorted(os.listdir(args.input)) if f.endswith('.bmp')]\n outfile = \"all_files-\" + args.input.replace('/', '-') + \".txt\"\nelif os.path.isfile(args.input):\n infiles = [args.input]\n outfile = args.input.replace('/', '-') + \".txt\"\n\nwith open(outfile, \"w\") as f:\n for infile in infiles:\n f.write(\"/* \" + infile + \" */\\n\")\n convert_bmp(infile)\n f.write(\"\\n\\n\")\n","sub_path":"bitmap-to-lcd.py","file_name":"bitmap-to-lcd.py","file_ext":"py","file_size_in_byte":2654,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"560935499","text":"import socket\n\nsize = 512\nhost = \"\"\nport = 9898\n\n# family = Internet, type = stream, socket means TCP\nsock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\nsock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)\n\n# Have a socket, need to bind to an IP address and port\n# to have a place to listen on\nsock.bind((host, port))\nsock.listen(5)\n\n# Can store info about other end once we accept the connection attempt\nc, addr = sock.accept()\ndata = c.recv(size)\nif data:\n print(\"Connection from: \",addr[0])\n print(\"Data: \", data.decode(\"utf-8\"))\nsock.close()\n","sub_path":"MasteringPythonNetSec/Networking/network_server.py","file_name":"network_server.py","file_ext":"py","file_size_in_byte":564,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"279046094","text":"##############################################################################\n#\n# An example of creating a chart with Pandas and XlsxWriter.\n#\n# Copyright 2013, John McNamara, jmcnamara@cpan.org\n#\n\nimport pandas as pd\nfrom vincent.colors import brews\n\n# Some sample data to plot.\nfarm_1 = {'apples': 10, 'berries': 32, 'squash': 21, 'melons': 13, 'corn': 18}\nfarm_2 = {'apples': 15, 'berries': 43, 'squash': 17, 'melons': 10, 'corn': 22}\nfarm_3 = {'apples': 6, 'berries': 24, 'squash': 22, 'melons': 16, 'corn': 30}\nfarm_4 = {'apples': 12, 'berries': 30, 'squash': 15, 'melons': 9, 'corn': 15}\n\ndata = [farm_1, farm_2, farm_3, farm_4]\nindex = ['Farm 1', 'Farm 2', 'Farm 3', 'Farm 4']\n\n# Create a Pandas dataframe from the data.\ndf = pd.DataFrame(data, index=index)\n\n# Create a Pandas Excel writer using XlsxWriter as the engine.\nexcel_file = 'grouped_column_farms.xlsx'\nsheet_name = 'Sheet1'\n\nwriter = pd.ExcelWriter(excel_file, engine='xlsxwriter')\ndf.to_excel(writer, sheet_name=sheet_name)\n\n# Access the XlsxWriter workbook and worksheet objects from the dataframe.\nworkbook = writer.book\nworksheet = writer.sheets[sheet_name]\n\n# Create a chart object.\nchart = workbook.add_chart({'type': 'column'})\n\n# Configure the series of the chart from the dataframe data.\nfor col_num in range(1, len(farm_1) + 1):\n chart.add_series({\n 'name': ['Sheet1', 0, col_num],\n 'categories': ['Sheet1', 1, 0, 4, 0],\n 'values': ['Sheet1', 1, col_num, 4, col_num],\n 'fill': {'color': brews['Set1'][col_num - 1]},\n 'overlap':-10,\n })\n\n# Configure the chart axes.\nchart.set_x_axis({'name': 'Total Produce'})\nchart.set_y_axis({'name': 'Farms', 'major_gridlines': {'visible': False}})\n\n# Insert the chart into the worksheet.\nworksheet.insert_chart('H2', chart)\n\n# Close the Pandas Excel writer and output the Excel file.\nwriter.save()\n","sub_path":"examples/chart_grouped_column_farms.py","file_name":"chart_grouped_column_farms.py","file_ext":"py","file_size_in_byte":1870,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"566153729","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n\"\"\"\nAfter auditing is complete the next step is to prepare the data to be inserted into a SQL database.\nTo do so you will parse the elements in the OSM XML file, transforming them from document format to\ntabular format, thus making it possible to write to .csv files. These csv files can then easily be\nimported to a SQL database as tables.\n\nThe process for this transformation is as follows:\n- Use iterparse to iteratively step through each top level element in the XML\n- Shape each element into several data structures using a custom function\n- Utilize a schema and validation library to ensure the transformed data is in the correct format\n- Write each data structure to the appropriate .csv files\n\nWe've already provided the code needed to load the data, perform iterative parsing and write the\noutput to csv files. Your task is to complete the shape_element function that will transform each\nelement into the correct format. To make this process easier we've already defined a schema (see\nthe schema.py file in the last code tab) for the .csv files and the eventual tables. Using the\ncerberus library we can validate the output against this schema to ensure it is correct.\n\n## Shape Element Function\nThe function should take as input an iterparse Element object and return a dictionary.\n\n### If the element top level tag is \"node\":\nThe dictionary returned should have the format {\"node\": .., \"node_tags\": ...}\n\nThe \"node\" field should hold a dictionary of the following top level node attributes:\n- id\n- user\n- uid\n- version\n- lat\n- lon\n- timestamp\n- changeset\nAll other attributes can be ignored\n\nThe \"node_tags\" field should hold a list of dictionaries, one per secondary tag. Secondary tags are\nchild tags of node which have the tag name/type: \"tag\". Each dictionary should have the following\nfields from the secondary tag attributes:\n- id: the top level node id attribute value\n- key: the full tag \"k\" attribute value if no colon is present or the characters after the colon if one is.\n- value: the tag \"v\" attribute value\n- type: either the characters before the colon in the tag \"k\" value or \"regular\" if a colon\n is not present.\n\nAdditionally,\n\n- if the tag \"k\" value contains problematic characters, the tag should be ignored\n- if the tag \"k\" value contains a \":\" the characters before the \":\" should be set as the tag type\n and characters after the \":\" should be set as the tag key\n- if there are additional \":\" in the \"k\" value they and they should be ignored and kept as part of\n the tag key. For example:\n\n \n should be turned into\n {'id': 12345, 'key': 'street:name', 'value': 'Lincoln', 'type': 'addr'}\n\n- If a node has no secondary tags then the \"node_tags\" field should just contain an empty list.\n\nThe final return value for a \"node\" element should look something like:\n\n{'node': {'id': 757860928,\n 'user': 'uboot',\n 'uid': 26299,\n 'version': '2',\n 'lat': 41.9747374,\n 'lon': -87.6920102,\n 'timestamp': '2010-07-22T16:16:51Z',\n 'changeset': 5288876},\n 'node_tags': [{'id': 757860928,\n 'key': 'amenity',\n 'value': 'fast_food',\n 'type': 'regular'},\n {'id': 757860928,\n 'key': 'cuisine',\n 'value': 'sausage',\n 'type': 'regular'},\n {'id': 757860928,\n 'key': 'name',\n 'value': \"Shelly's Tasty Freeze\",\n 'type': 'regular'}]}\n\n### If the element top level tag is \"way\":\nThe dictionary should have the format {\"way\": ..., \"way_tags\": ..., \"way_nodes\": ...}\n\nThe \"way\" field should hold a dictionary of the following top level way attributes:\n- id\n- user\n- uid\n- version\n- timestamp\n- changeset\n\nAll other attributes can be ignored\n\nThe \"way_tags\" field should again hold a list of dictionaries, following the exact same rules as\nfor \"node_tags\".\n\nAdditionally, the dictionary should have a field \"way_nodes\". \"way_nodes\" should hold a list of\ndictionaries, one for each nd child tag. Each dictionary should have the fields:\n- id: the top level element (way) id\n- node_id: the ref attribute value of the nd tag\n- position: the index starting at 0 of the nd tag i.e. what order the nd tag appears within\n the way element\n\nThe final return value for a \"way\" element should look something like:\n\n{'way': {'id': 209809850,\n 'user': 'chicago-buildings',\n 'uid': 674454,\n 'version': '1',\n 'timestamp': '2013-03-13T15:58:04Z',\n 'changeset': 15353317},\n 'way_nodes': [{'id': 209809850, 'node_id': 2199822281, 'position': 0},\n {'id': 209809850, 'node_id': 2199822390, 'position': 1},\n {'id': 209809850, 'node_id': 2199822392, 'position': 2},\n {'id': 209809850, 'node_id': 2199822369, 'position': 3},\n {'id': 209809850, 'node_id': 2199822370, 'position': 4},\n {'id': 209809850, 'node_id': 2199822284, 'position': 5},\n {'id': 209809850, 'node_id': 2199822281, 'position': 6}],\n 'way_tags': [{'id': 209809850,\n 'key': 'housenumber',\n 'type': 'addr',\n 'value': '1412'},\n {'id': 209809850,\n 'key': 'street',\n 'type': 'addr',\n 'value': 'West Lexington St.'},\n {'id': 209809850,\n 'key': 'street:name',\n 'type': 'addr',\n 'value': 'Lexington'},\n {'id': '209809850',\n 'key': 'street:prefix',\n 'type': 'addr',\n 'value': 'West'},\n {'id': 209809850,\n 'key': 'street:type',\n 'type': 'addr',\n 'value': 'Street'},\n {'id': 209809850,\n 'key': 'building',\n 'type': 'regular',\n 'value': 'yes'},\n {'id': 209809850,\n 'key': 'levels',\n 'type': 'building',\n 'value': '1'},\n {'id': 209809850,\n 'key': 'building_id',\n 'type': 'chicago',\n 'value': '366409'}]}\n\"\"\"\n\nimport csv\nimport pprint\nimport re\n\nimport xml.etree.cElementTree as ET\n\n# for schema validation\nimport cerberus\nimport schema\n\nOSM_PATH = \"downloaded_maps/new_orleans_city.osm\"\n\nNODES_PATH = \"nodes.csv\"\nNODE_TAGS_PATH = \"nodes_tags.csv\"\nWAYS_PATH = \"ways.csv\"\nWAY_NODES_PATH = \"ways_nodes.csv\"\nWAY_TAGS_PATH = \"ways_tags.csv\"\n\nLOWER_COLON = re.compile(r'^([a-z]|_)+:([a-z]|_)+')\nPROBLEMCHARS = re.compile(r'[=\\+/&<>;\\'\"\\?%#$@\\,\\. \\t\\r\\n]')\n\nSCHEMA = schema.schema\n\n# Make sure the fields order in the csvs matches the column order in the sql table schema\nNODE_FIELDS = ['id', 'lat', 'lon', 'user', 'uid', 'version', 'changeset', 'timestamp']\nNODE_TAGS_FIELDS = ['id', 'key', 'value', 'type']\nWAY_FIELDS = ['id', 'user', 'uid', 'version', 'changeset', 'timestamp']\nWAY_TAGS_FIELDS = ['id', 'key', 'value', 'type']\nWAY_NODES_FIELDS = ['id', 'node_id', 'position']\n\nexpected = [\"Street\",\n \"Avenue\",\n \"Court\",\n \"Drive\",\n \"Road\",\n \"Boulevard\",\n \"Place\",\n \"Lane\",\n \"Circle\",\n \"Cove\",\n \"Arcade\",\n \"Way\",\n \"Walk\",\n \"Highway\",\n \"Parkway\",\n \"Alley\",\n \"Plaza\",\n \"Trace\"]\n\n\nto_fix = {\"St\": \"Street\",\n \"St.\": \"Street\",\n \"Ave\": \"Avenue\",\n \"Pkwy\": \"Parkway\",\n \"Hwy\": \"Highway\",\n \"Blvd\": \"Boulevard\",\n \"Dr\": \"Drive\",\n \"Ave.\": \"Avenue\",\n \"Pky\": \"Parkway\"}\n\nfullname_mapping = {\"Banks\": \"Banks Street\",\n \"Regent Street #C\": \"Regent Street\",\n \"Dumaine\": \"Dumaine Street\",\n \"Magazine Street;Magazine St\": \"Magazine Street\",\n \"Magazine\": \"Magazine Street\",\n \"Rosa PARK\": \"Rosa Park\",\n \"Severn\": \"Severn Avenue\",\n \"St. Peter\": \"Saint Peter Street\",\n \"3157 Gentilly Blvd #2019\": \"Gentilly Boulevard\",\n \"Marais\": \"Marais Street\",\n \"Royal\": \"Royal Street\",\n \"Canal Street at Bourbon\": \"Canal Street\",\n \"General Taylor\": \"General Taylor Street\",\n \"Gretna Blvd Ste A\": \"Gretna Boulevard\",\n \"Manhattan Boulevard Building\": \"Manhattan Boulevard\",\n \"Saint Charles Avenue, Suite 114-351\": \"Saint Charles Avenue\",\n \"1227 Tulane Ave\": \"Tulane Avenue\",\n \"621 Canal Street\": \"Canal Street\",\n \"Westgrove PARK\": \"Westgrove Park\",\n \"George 'Nick' Connor Drive\": \"George Nick Connor Drive\",\n \"Bal of Square\": \"Banks Street\",\n }\n\ndef is_street_name(tag_key):\n \"\"\"\n untility method to identify street addresses\n \"\"\"\n return (tag_key == \"addr:street\")\n\nstreet_type_re = re.compile(r'(.*) (\\b\\S+\\.?)$', re.IGNORECASE)\ndef fix_street_name(value):\n \"\"\"\n Normalize street names so they are more consistent\n \"\"\"\n\n # trim any leading and trailing whitespace\n value = value.strip()\n\n # patch full items that are borked\n value = fullname_mapping.get(value, value)\n\n # match against street regex\n match = street_type_re.match(value)\n if match:\n #continue\n first_path = match.group(1)\n street_type = match.group(2)\n street_type = to_fix.get(street_type, street_type)\n\n value = \"{} {}\".format(first_path, street_type)\n\n beginnings = {'N ': 'North',\n 'S ': 'South',\n 'E ': 'East',\n 'W ': 'West',\n 'St ': 'Saint',\n 'St. ': 'Saint'}\n for k, v in beginnings.items():\n start_string = \"{} \".format(k)\n if value.startswith(k):\n value = value.replace(k, v, 1)\n\n # any St or St. that still remain are 'Saint'\n value.replace('St ', 'Saint ')\n value.replace('St. ', 'Saint ')\n\n return value\n\n\n\nlower = re.compile(r'^([a-z]|_)*$')\nlower_colon = re.compile(r'^([a-z]|_)*:([a-z]|_)*$')\nproblemchars = re.compile(r'[=\\+/&<>;\\'\"\\?%#$@\\,\\. \\t\\r\\n]')\n\ndef get_key_parts(full_key):\n \"\"\"\n for keys with ':', returns first part and then everything else\n for keys without ':', returns 'regular' and then the full_key\n \"\"\"\n colon_pos = full_key.find(':')\n\n base_type = 'regular'\n key = full_key\n\n if colon_pos >= 0:\n base_type = full_key[:colon_pos]\n key = full_key[colon_pos + 1:]\n\n return (base_type, key)\n\ndef shape_element(element,\n node_attr_fields=NODE_FIELDS,\n way_attr_fields=WAY_FIELDS,\n problem_chars=PROBLEMCHARS,\n default_tag_type='regular'):\n \"\"\"\n Clean and shape node or way XML element to Python dict\n \"\"\"\n\n # child elements are processed the same for both and elements\n #\n tags = []\n if element.tag in ('node', 'way'):\n # process the / elements\n #\n for tag in element.iter(\"tag\"):\n\n # Force key to lowercase\n full_key = tag.attrib['k'].lower()\n value = tag.attrib['v']\n\n if is_street_name(full_key):\n value = fix_street_name(value)\n\n base_type, key = get_key_parts(full_key)\n\n tag_dict = {\n 'id': element.attrib.get('id'),\n 'key': key,\n 'type': base_type,\n 'value': value,\n }\n tags.append(tag_dict)\n\n if element.tag == 'node':\n\n # Process the attributes in the element\n #\n node_attribs = {}\n for attribute in ['id', 'lat', 'lon', 'user', 'uid', 'version', 'changeset', 'timestamp']:\n node_attribs[attribute] = element.attrib.get(attribute)\n\n return {'node': node_attribs, 'node_tags': tags}\n\n elif element.tag == 'way':\n\n # Process the attributes in the element\n #\n way_attribs = {}\n for attribute in ['id', 'user', 'uid', 'version', 'changeset', 'timestamp']:\n way_attribs[attribute] = element.attrib.get(attribute)\n\n # Process the elements\n #\n way_nodes = []\n position = 0\n for nd in element.iter(\"nd\"):\n node_dict = {\n 'id': element.attrib.get('id'),\n 'node_id': nd.attrib.get('ref'),\n 'position': position,\n }\n position += 1\n way_nodes.append(node_dict)\n\n return {'way': way_attribs, 'way_nodes': way_nodes, 'way_tags': tags}\n\n\n# ================================================== #\n# Helper Functions #\n# ================================================== #\ndef get_element(osm_file, tags=('node', 'way', 'relation')):\n \"\"\"\n Yield element if it is the right type of tag\n \"\"\"\n\n context = ET.iterparse(osm_file, events=('start', 'end'))\n _, root = next(context)\n for event, elem in context:\n if event == 'end' and elem.tag in tags:\n yield elem\n root.clear()\n\n\ndef validate_element(element, validator, schema=SCHEMA):\n \"\"\"\n Raise ValidationError if element does not match schema\n \"\"\"\n if validator.validate(element, schema) is not True:\n field, errors = next(validator.errors.items())\n message_string = \"\\nElement of type '{0}' has the following errors:\\n{1}\"\n error_string = pprint.pformat(errors)\n raise Exception(message_string.format(field, error_string))\n\n\n# ================================================== #\n# Main Function #\n# ================================================== #\n\ndef process_map(file_in, validate):\n \"\"\"\n Iteratively process each XML element and write to csv(s\n \"\"\"\n from street_map_csv_writer import StreetMapCsvWriter\n\n writer = StreetMapCsvWriter(add_csv_headers=False,\n output_directory='generated_data')\n\n validator = cerberus.Validator()\n\n for element in get_element(file_in, tags=('node', 'way')):\n el = shape_element(element)\n if el:\n if validate is True:\n validate_element(el, validator)\n\n if element.tag == 'node':\n writer.add_node(el['node'])\n writer.add_node_tags(el['node_tags'])\n elif element.tag == 'way':\n writer.add_way(el['way'])\n writer.add_way_nodes(el['way_nodes'])\n writer.add_way_tags(el['way_tags'])\n\nif __name__ == '__main__':\n # Note: Validation is ~ 10X slower. For the project consider using a small\n # sample of the map when validating.\n process_map(OSM_PATH, validate=False)\n\n","sub_path":"data.py","file_name":"data.py","file_ext":"py","file_size_in_byte":15103,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"262605289","text":"import subprocess as sp\nimport speech_recognition as sr\nimport pyttsx3\nfrom win32com.client import Dispatch\nimport os\nimport pyaudio\n\n\n\n\n\n\ndef main():\n speak = Dispatch(\"SAPI.SpVoice\").Speak\n speak(\"Hello user welcome to the git tool by Mubin ggiraach\")\n \n rec = sr.Recognizer()\n with sr.Microphone() as source:\n speak(\"Tell me what can i do for you\")\n user1=rec.listen(source)\n speak(\"Ok wait\")\n\n user1i=rec.recognize_google(user1)\n print(user1i)\n\n if (\"create\" or \"initialise\" in user1i) :\n init()\n \n elif (\"clone\" or \"download\" in user1i):\n cln()\n\n elif (\"add\" or \"upload\" in user1i):\n addfls()\n \n elif (\"restore\" in user1i):\n restore()\n\n elif(\"upload large file\" in user1i):\n lfs()\n \n elif (\"scratch\" or \"start\" in user1i):\n repo()\n\n\n\n \ndef init(): \n speak(\"where u want to initialize\")\n with sr.Microphone() as source3:\n user3=rec.listen(source3)\n speak(\"Ok wait\")\n user3i=rec.recognize_google(user3)\n print(user3i)\n \n if (\"here\" in user3i or \"current\"in user3i):\n sp.run(\"git init\")\n \n elif (\"other\" or \"another\" in user3i):\n speak(\"Please enter the directory where you want to intialise a repository\")\n rmtd=input(\"Enter the directory path: \")\n initr=\"git init\"+\" \"+rmtd\n sp.run(initr)\n \n else:\n speak(\"Please follow proper instructions\")\n\n \n\n\ndef restore():\n speak(\"Please make sure that the file you want to restore was been tracked by git before it got deleted\")\n speak(\"Please tell me which file you want to restore\")\n rstr=input(\"Enter the filename: \")\n restr=\"git restore\"+\" \"+rstr\n sp.run(restr)\n\n\n\ndef lfs():\n speak(\"Ok so you are having a large file no problem i have got a solution for it\")\n sp.run(\"git install lfs\")\n speak(\"Now let us track the file you want upload\")\n speak(\"If you want to add all files with a certain extension we can do that or we can simply add one file\")\n trk=input(\"Enter the directory you want to track: \")\n track=\"git track\"+\" \"+trk\n sp.run(track)\n speak(\"Now let us add that large file\")\n lf=input(\"name of large file: \")\n addlf=\"git add\"+\" \"+lf\n sp.run(addlf)\n commit()\n push()\n\n\n\ndef repo():\n speak(\"Ok great seems so you have created a brand new repository let me help you\")\n speak(\"Please tell me where is your code so I can initialise a reposiroty there \")\n code = input(\"Enter the directory: \")\n create= \"git init\"+\" \"+code\n sp.run(create)\n speak(\"Respository initialised lets add files now \")\n speak(\"Which files you want to add\")\n print(\"For Multiple files give the name of files as file1.txt file2.py file3.png \")\n print(\"For adding all the files in the directory just give a character . in the input\")\n files=input(\"Enter the file name: \")\n addfiles=\"git add\"+\" \"+files\n sp.run(addfiles)\n commit()\n sp.run(\"git branch -M main\")\n speak(\"Please enter your repository u r l where you want to upload these files\")\n url=input(\"Enter the repository url: \")\n rmto=\"git remote add origin\"+\" \"+url\n sp.run(rmto)\n sp.run(\"git push -u origin main\")\n speak(\"hey user you are good to go all files are uploaded\")\n\ndef commit():\n speak(\"Now as we have added the files let's commit them please say what should be the commit message\")\n with sr.Microphone() as source3:\n usercmt=rec.listen(source3)\n userc=rec.recognize_google(usercmt)\n print(userc)\n cmtmsg=\"git commit -m\"+\" '\"+usercmt+\"'\"\n\n\ndef cln():\n speak(\"please write the username followed by the repository name which you want to clone\")\n print(\"example- th3gentleman-MubinGirach/test\")\n user2=input(\"Enter the username/repositoryname: \")\n clone=\"git clone https://github.com/\"+user2\n sp.run(clone)\n speak(\"Successfully cloned\")\n\ndef addfls():\n with sr.Microphone() as source1:\n speak(\"Which file you want to add\")\n user2=rec.listen(source1)\n speak(\"Ok wait\")\n user2i=rec.recognize_google(user2)\n print(user2i)\n if (\"all\" in user2i):\n sp.run(\"git init\")\n sp.run(\"git add .\")\n else:\n speak(\"Please write the name of files in the below prompt\")\n print(\"Example file1.txt file2.py \")\n file=input(\"Enter the file names with extensions: \")\n add=\"git add\"+file\n sp.run(add)\n\ndef push():\n speak(\"Now we need to push our files\")\n sp.run(\"git branch -M main\")\n speak(\"Please enter your repository u r l where you want to upload these files\")\n url=input(\"Enter the repository url: \")\n rmto=\"git remote add origin\"+\" \"+url\n sp.run(rmto)\n sp.run(\"git push -u origin main\")\n speak(\"hey user you are good to go all files are uploaded\")\n\nmain()\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n \n \n \n \n\n \n \n\n\n \n \n \n \n \n\n \n\n \n \n\n\n\n\n","sub_path":"Git.py","file_name":"Git.py","file_ext":"py","file_size_in_byte":4904,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"621657371","text":"from django.forms import CharField\nfrom django.core import validators\nfrom django.utils.ipv6 import clean_ipv6_address\n\nfrom .validators import ip_network_validators\n\n\nclass GenericIPNetworkField(CharField):\n default_error_messages = {}\n\n def __init__(self, protocol='both', unpack_ipv4=False, *args, **kwargs):\n self.unpack_ipv4 = unpack_ipv4\n self.default_validators, invalid_error_message = \\\n ip_network_validators(protocol, unpack_ipv4)\n self.default_error_messages['invalid'] = invalid_error_message\n super(GenericIPNetworkField, self).__init__(*args, **kwargs)\n\n def to_python(self, value):\n if value in validators.EMPTY_VALUES:\n return ''\n if value:\n if ':' in value:\n if '/' in value:\n [addr,mask] = value.rsplit('/', 1)\n else:\n addr=value\n mask='128'\n addr=clean_ipv6_address(addr,\n self.unpack_ipv4, self.error_messages['invalid'])\n else:\n if '/' in value:\n [addr,mask] = value.rsplit('/',1)\n else:\n addr=value\n mask='32'\n value=\"%s/%s\"%(addr,mask)\n return value\n","sub_path":"forms.py","file_name":"forms.py","file_ext":"py","file_size_in_byte":1299,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"588440267","text":"# The isBadVersion API is already defined for you.\n# @param version, an integer\n# @return an integer\n# def isBadVersion(version):\n\nclass Solution:\n def firstBadVersion(self, n):\n \"\"\"\n :type n: int\n :rtype: int\n invariant: l <= r and 1st Bad in mustbe(l, r)\n \"\"\"\n l = 1\n r = n\n while l < r: # change invariant\n old_range = r - l\n m = l + ((r - l) // 2) # avoid over flow\n assert l <= m <= r, \" l <= m <= r\"\n if isBadVersion(m):\n r = m\n else:\n l = m + 1\n new_range = r - l\n print(f'old_range:{old_range}, new_range:{new_range}')\n assert new_range < old_range, \"new range < old range\"\n assert l == r, \"l == r\"\n return r\n\n def firstBadVersion_v1(self, n):\n \"\"\"\n :type n: int\n :rtype: int\n \"\"\"\n l = 1\n h = n\n while l <= h:\n m = (l + h) // 2\n if isBadVersion(m):\n h = m - 1\n else:\n l = m + 1\n assert h < l\n return l\n \n","sub_path":"278-easy-Bad-Version-2021-12-31/solution.py","file_name":"solution.py","file_ext":"py","file_size_in_byte":1141,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"267121858","text":"from manimlib.imports import *\n\nclass IllustrationScene(GraphScene):\n\n CONFIG = {\n \"x_min\": -3,\n \"x_max\": 5,\n \"x_axis_width\": 8,\n \"y_min\": -3,\n \"y_max\": 4,\n \"y_axis_height\": 7,\n \"graph_origin\": 1*DOWN + 2*LEFT,\n }\n\n def get_circle(self, a, b, r, **kwargs):\n return ParametricFunction(lambda t: (a+r*np.cos(t))*RIGHT+(b + r*np.sin(t))*UP+self.CONFIG['graph_origin'], t_min=-PI, t_max=PI)\n\n def get_vec(self, x, y):\n return Vector().put_start_and_end_on(self.CONFIG[\"graph_origin\"], x*RIGHT+y*UP+self.CONFIG[\"graph_origin\"])\n\n def get_vec2(self, x, y, start):\n return Vector().put_start_and_end_on(start, x*RIGHT+y*UP+start)\n\n def construct(self):\n text = TexMobject(r\"|\\vec{a}|=1\",r\",|\\vec{b}|=2,\",r\"|\\vec{a}+\\vec{b}|-|\\vec{a}-\\vec{b}|\\in ?\")\n text.shift(UP*3)\n self.play(\n Write(text),\n runtime=1,\n )\n self.wait(1.2)\n self.play(\n FadeOut(text),\n )\n self.wait(1.2)\n\n pi = math.pi\n self.theta = pi/3\n self.theta0 = pi/2\n t0 = ValueTracker(self.theta)\n t1 = ValueTracker(self.theta0)\n axes = self.setup_axes(animate=True)\n vec_a = self.get_vec(math.cos(self.theta0), math.sin(self.theta0)).set_color(BLUE)\n label_a = TexMobject(r\"|\\vec{a}|\")\\\n .add_updater(lambda a: a.become(TexMobject(r\"|\\vec{a}|\").next_to(vec_a, RIGHT)))\n self.play(\n FadeIn(vec_a),\n FadeIn(label_a),\n )\n self.wait(1.2)\n vec_b = self.get_vec(2*math.cos(self.theta), 2*math.sin(self.theta)).set_color(RED_B)\n label_b = TexMobject(r\"|\\vec{b}|\")\\\n .add_updater(lambda a: a.become(TexMobject(r\"|\\vec{b}|\").next_to(vec_b, RIGHT)))\n self.play(\n FadeIn(vec_b),\n FadeIn(label_b),\n )\n self.wait(1.2)\n vec_a.add_updater(lambda x: x.become(self.get_vec(math.cos(t1.get_value()), math.sin(t1.get_value())).set_color(BLUE)))\n vec_b.add_updater(lambda x: x.become(self.get_vec(2*math.cos(t0.get_value()), 2*math.sin(t0.get_value())).set_color(RED_B)))\n self.wait(1.2)\n self.play(t0.increment_value, pi/3, run_time=2)\n self.wait(1.2)\n self.play(t1.increment_value, -pi/3, run_time=2)\n self.wait(1.2)\n self.play(t0.increment_value, -pi/2, run_time=2)\n text1 = TextMobject(\"其实只要固定一个向量，让另一个旋转，就能得到所有情况\").to_edge(UP)\n self.wait(1.2)\n self.play(FadeIn(text1))\n text2 = TextMobject(r\"所以我们把$|\\vec{a}|$向量固定在$(0,1)$处，让$|\\vec{b}|$旋转\").to_edge(UP)\n self.wait(1.2)\n self.play(Transform(text1, text2))\n self.wait(1.2)\n self.play(t1.increment_value, -pi/6, run_time=0.5)\n text3 = TextMobject(r\"把$|\\vec{b}|$的起点移动到$|\\vec{a}|$的末端\").to_edge(UP)\n self.wait(1.2)\n self.play(Transform(text1, text3))\n vec_b.remove_updater(lambda x: x.become(self.get_vec(2*math.cos(t0.get_value()), 2*math.sin(t0.get_value())).set_color(RED_B)))\n vec_b_ = self.get_vec2(2 * math.cos(t0.get_value()), 2 * math.sin(t0.get_value()), self.CONFIG[\"graph_origin\"]+RIGHT).set_color(RED_B)\n self.wait(1.2)\n self.play(ReplacementTransform(vec_b, vec_b_))\n vec_b_.add_updater(lambda x: x.become(self.get_vec2(2 * math.cos(t0.get_value()), 2 * math.sin(t0.get_value()), self.CONFIG[\"graph_origin\"]+RIGHT).set_color(RED_B)))\n label_b.remove_updater(lambda a: a.become(TexMobject(r\"|\\vec{b}|\").next_to(vec_b, RIGHT)))\n label_b.add_updater(lambda a: a.become(TexMobject(r\"|\\vec{b}|\").next_to(vec_b_, RIGHT)))\n self.wait(1.2)\n self.play(t0.increment_value, -pi/2, run_time=1)\n self.wait(1.2)\n self.play(t0.increment_value, pi/4, run_time=1)\n self.wait(1.2)\n self.play(t0.increment_value, pi/6, run_time=1)\n text4 = TextMobject(r\"显而易见，$|\\vec{b}|$会画出一个圆\").to_edge(UP)\n self.wait(1.2)\n self.play(Transform(text1, text4))\n circle = self.get_circle(1, 0, 2)\n self.wait(1.2)\n self.play(Write(circle))\n vec_a.remove_updater(lambda x: x.become(self.get_vec(math.cos(t1.get_value()), math.sin(t1.get_value())).set_color(BLUE)))\n self.wait(1.2)\n self.play(vec_a.set_opacity, 0.5)\n vec_a_ = self.get_vec2(math.cos(0), math.sin(0), self.CONFIG[\"graph_origin\"]+RIGHT).set_color(BLUE)\n label_a.remove_updater(lambda a: a.become(TexMobject(r\"|\\vec{a}|\").next_to(vec_a, RIGHT)))\n label_a.add_updater(lambda a: a.become(TexMobject(r\"|\\vec{a}|\").next_to(vec_a_, RIGHT)))\n self.wait(1.2)\n self.play(FadeInFromPoint(vec_a_,point=Point(location=self.CONFIG[\"graph_origin\"]+RIGHT)))\n text5 = TextMobject(r'把$\\vec{a}$向右平移至$\\vec{b}$起点处，可以找到$\\vec{a}-\\vec{b}$').to_edge(UP)\n self.wait(1.2)\n self.play(Transform(text1, text5))\n l1 = Line(self.CONFIG[\"graph_origin\"],self.CONFIG[\"graph_origin\"]+2 * math.cos(t0.get_value())*RIGHT+2 * math.sin(t0.get_value())*UP+RIGHT, color=PURPLE_B)\\\n .add_updater(\n lambda x: x.become(Line(self.CONFIG[\"graph_origin\"], self.CONFIG[\"graph_origin\"]+2 * math.cos(t0.get_value())*RIGHT+2 * math.sin(t0.get_value())*UP+RIGHT, color=PURPLE_B))\n )\n\n ll1 = TexMobject(r'A').next_to(Point(location=self.CONFIG[\"graph_origin\"]+RIGHT*2), direction=UP)\n o = TexMobject(r'O').next_to(Point(location=self.CONFIG[\"graph_origin\"]), direction=UP)\n self.wait(1.2)\n self.play(\n FadeIn(l1),FadeIn(ll1),FadeIn(o)\n )\n\n l2 = Line(self.CONFIG[\"graph_origin\"]+2*RIGHT,self.CONFIG[\"graph_origin\"]+2 * math.cos(t0.get_value())*RIGHT+2 * math.sin(t0.get_value())*UP+RIGHT, color=GREEN_B)\\\n .add_updater(\n lambda x: x.become(Line(self.CONFIG[\"graph_origin\"]+2*RIGHT, self.CONFIG[\"graph_origin\"]+2 * math.cos(t0.get_value())*RIGHT+2 * math.sin(t0.get_value())*UP+RIGHT, color=GREEN_B))\n )\n ll2 = TexMobject(r'B').move_to(self.CONFIG[\"graph_origin\"]+2 * math.cos(t0.get_value())*RIGHT+2 * math.sin(t0.get_value())*UP+RIGHT*1.5)\n ll2.add_updater(lambda x: x.become(TexMobject(r'B').move_to(self.CONFIG[\"graph_origin\"]+2 * math.cos(t0.get_value())*RIGHT+2 * math.sin(t0.get_value())*UP+RIGHT*1.5)))\n self.wait(1.2)\n self.play(FadeIn(l2),FadeIn(ll2))\n\n self.wait(1.2)\n self.play(t0.increment_value, pi/6)\n self.wait(1.2)\n self.play(t0.increment_value, -pi/2)\n self.wait(1.2)\n self.play(t0.increment_value, -pi/3)\n\n text6 = TextMobject(r'显然,$|\\vec{a}+\\vec{b}|=|OA|,|\\vec{a}-\\vec{b}|=|AB|$').to_edge(UP)\n self.wait(1.2)\n self.play(Transform(text1,text6))\n\n self.wait(1.2)\n self.play(t0.set_value, 0)\n text7 = TextMobject(r'此时，取得最大值$2$')\n text8 = TextMobject(r'此时，取得最小值$-2$')\n self.wait(1.2)\n self.play(Write(text7))\n self.wait(1.2)\n self.play(t0.increment_value, pi)\n self.wait(1.2)\n self.play(Transform(text7, text8))\n self.wait(1.2)","sub_path":"vectors.py","file_name":"vectors.py","file_ext":"py","file_size_in_byte":7317,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"653591676","text":"\"\"\"\n根据持仓来判断基金的申万行业风格\n股票仓位80%以上，前十大行业仓位90%以上\n\"\"\"\n\nimport datetime\nimport pandas as pd\n\nfrom django.db import transaction\nfrom proc import models\n\n\ndef target_funds(level=0.8):\n \"\"\"最新一期股票仓位80%以上的基金\"\"\"\n funds = models.Asset.objects.exclude(stock=0).values('secucode', 'date', 'stock').order_by('-date')\n funds = pd.DataFrame(funds)\n begin = datetime.date.today() - datetime.timedelta(days=365)\n rpt = models.TradingDate.objects.filter(date__gte=begin, ifquarterend=1).values('date')\n rpt = [x['date'] for x in rpt]\n funds = funds[funds['date'].isin(rpt)]\n funds = funds.drop_duplicates('secucode', keep='first')\n funds = funds[funds['stock'] >= level]\n return list(funds.secucode)\n\n\ndef fund_etf(fund: str):\n \"\"\"获取指定基金关联的etf基金\"\"\"\n funds = models.FundAssociate.objects.filter(secucode=fund, define=24).values('relate')\n funds = [x['relate'] for x in funds]\n return funds\n\n\ndef fund_industry_data(funds):\n \"\"\"基金行业数据\"\"\"\n stocks = models.StockSW.objects.values('secucode', 'first')\n stocks = pd.DataFrame(stocks).rename(columns={'secucode': 'stockcode'})\n data = models.FundHoldingKeyStockNew.objects.filter(\n secucode__in=funds).values('secucode', 'stockcode', 'ratio', 'date')\n data = pd.DataFrame(data).sort_values(['secucode', 'date'], ascending=[True, False])\n ret = []\n for _, g in data.groupby('secucode'):\n md = g.date.max()\n g = g[g.date == md]\n ret.append(g)\n data = pd.concat(ret)\n data = data.merge(stocks, on='stockcode', how='left')\n return data\n\n\ndef fund_industry():\n funds = target_funds()\n data = fund_industry_data(funds)\n data['first'] = data['first'].fillna('港股')\n ret = []\n for secucode, group in data.groupby('secucode'):\n ind = group.groupby('first')['ratio'].sum().sort_values()\n if ind.empty:\n continue\n last = ind.iloc[-1] / ind.sum()\n if last >= 0.9:\n ret.append((secucode, ind.index[-1]))\n etfs = fund_etf(secucode)\n for etf in etfs:\n ret.append((etf, ind.index[-1]))\n return ret\n\n\n@transaction.atomic()\ndef update_fund_industry():\n \"\"\"采用更新方式\"\"\"\n data = fund_industry()\n funds = models.FundNew.objects.all()\n funds = {x.secucode: x for x in funds}\n exist = models.ClassifyIndustry.objects.all()\n exist = {x.secucode.secucode: x for x in exist}\n add = []\n delete = []\n for secucode, ind in data:\n instance = funds.get(secucode)\n if not instance:\n continue\n if secucode in exist:\n e = exist.get(secucode)\n if ind != e.industry:\n delete.append(e)\n add.append(models.ClassifyIndustry(secucode=instance, industry=ind))\n else:\n add.append(models.ClassifyIndustry(secucode=instance, industry=ind))\n for x in delete:\n x.delete()\n models.ClassifyIndustry.objects.bulk_create(add)\n\n\nif __name__ == '__main__':\n update_fund_industry()\n","sub_path":"proc/preprocess/industry_style.py","file_name":"industry_style.py","file_ext":"py","file_size_in_byte":3136,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"244546275","text":"# -*- encoding:ascii -*-\nfrom mako import runtime, filters, cache\nUNDEFINED = runtime.UNDEFINED\n__M_dict_builtin = dict\n__M_locals_builtin = locals\n_magic_number = 6\n_modified_time = 1400717744.204384\n_template_filename='templates/webapps/galaxy/page/select_items_grid_async.mako'\n_template_uri='/page/select_items_grid_async.mako'\n_template_cache=cache.Cache(__name__, _modified_time)\n_source_encoding='ascii'\n_exports = []\n\n\ndef _mako_get_namespace(context, name):\n try:\n return context.namespaces[(__name__, name)]\n except KeyError:\n _mako_generate_namespaces(context)\n return context.namespaces[(__name__, name)]\ndef _mako_generate_namespaces(context):\n # SOURCE LINE 1\n ns = runtime.TemplateNamespace('__anon_0x2b0ce82e3950', context._clean_inheritance_tokens(), templateuri=u'../grid_base.mako', callables=None, calling_uri=_template_uri)\n context.namespaces[(__name__, '__anon_0x2b0ce82e3950')] = ns\n\n # SOURCE LINE 2\n ns = runtime.TemplateNamespace('__anon_0x2b0ce82e36d0', context._clean_inheritance_tokens(), templateuri=u'/display_common.mako', callables=None, calling_uri=_template_uri)\n context.namespaces[(__name__, '__anon_0x2b0ce82e36d0')] = ns\n\ndef render_body(context,**pageargs):\n context.caller_stack._push_frame()\n try:\n __M_locals = __M_dict_builtin(pageargs=pageargs)\n _import_ns = {}\n _mako_get_namespace(context, '__anon_0x2b0ce82e3950')._populate(_import_ns, [u'*'])\n _mako_get_namespace(context, '__anon_0x2b0ce82e36d0')._populate(_import_ns, [u'render_message'])\n status = _import_ns.get('status', context.get('status', UNDEFINED))\n num_pages = _import_ns.get('num_pages', context.get('num_pages', UNDEFINED))\n render_message = _import_ns.get('render_message', context.get('render_message', UNDEFINED))\n render_grid_table_body_contents = _import_ns.get('render_grid_table_body_contents', context.get('render_grid_table_body_contents', UNDEFINED))\n grid = _import_ns.get('grid', context.get('grid', UNDEFINED))\n show_item_checkboxes = _import_ns.get('show_item_checkboxes', context.get('show_item_checkboxes', UNDEFINED))\n message = _import_ns.get('message', context.get('message', UNDEFINED))\n __M_writer = context.writer()\n # SOURCE LINE 1\n __M_writer(u'\\n')\n # SOURCE LINE 2\n __M_writer(u'\\n\\n')\n # SOURCE LINE 5\n __M_writer(unicode(render_grid_table_body_contents( grid, show_item_checkboxes=show_item_checkboxes )))\n __M_writer(u'\\n*****\\n')\n # SOURCE LINE 7\n __M_writer(unicode(num_pages))\n __M_writer(u'\\n*****\\n')\n # SOURCE LINE 9\n __M_writer(unicode(render_message( message, status )))\n return ''\n finally:\n context.caller_stack._pop_frame()\n\n\n","sub_path":"galaxy-dist/database/compiled_templates/page/select_items_grid_async.mako.py","file_name":"select_items_grid_async.mako.py","file_ext":"py","file_size_in_byte":2816,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"105856390","text":"from random import sample\r\n\r\nalu1 = str(input(\"Primeiro aluno: \"))\r\nalu2 = str(input(\"Segundo aluno: \"))\r\nalu3 = str(input(\"Terceiro aluno: \"))\r\nalu4 = str(input(\"Quarto aluno: \"))\r\n\r\nlista = [alu1,alu2,alu3,alu4]\r\n\r\nprint(\"A ordem de apresentação é:\")\r\nprint(sample(lista, k=4))\r\n","sub_path":"Sorteioapresentação.py","file_name":"Sorteioapresentação.py","file_ext":"py","file_size_in_byte":284,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"560921605","text":"##set up\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n##Do Font-Size (Ex 1A)\n\ndat = pd.read_csv(\"Ex 1B.csv\")\n\n#make the 95% confidence intervals\ndat['diff'] = dat['Upper'].sub(dat['Lower']) #get the length of the bars\ndat['diff2'] = dat['diff'].div(2) #length from line to point\n\n##set up the initial plot\nfig = plt.figure()\nfig.set_size_inches(14,10) #Might need to tweak this\n\nfig.subplots_adjust(hspace = .45) #Controls space between sub plots\n\nfig.suptitle('Highlights', fontsize=30, fontweight = 'bold')\n\n\n##Make the subplots\nax1 = fig.add_subplot(3, 1, 1)\nax2 = fig.add_subplot(3, 1, 2)\nax3 = fig.add_subplot(3, 1, 3)\n\n#Subset by Encoding\nsmall = dat[dat['Encoding'] == 'No_Highlight']\nlarge = dat[dat['Encoding'] == 'Highlight']\ncontrol = dat[dat['Encoding'] == 'Control']\n\n#subset by task\n#small\nj1 = small[small['Task'] == 'JOL']\nr1 = small[small['Task'] == 'Recall']\n\nj2 = large[large['Task'] == 'JOL']\nr2 = large[large['Task'] == 'Recall']\n\nj3 = control[control['Task'] == 'JOL']\nr3 = control[control['Task'] == 'Recall']\n\n#separate out averages and conf interval\nj1_average = j1['Average']\nr1_average = r1['Average']\n\nj1_conf = j1['diff2']\nr1_conf = r1['diff2']\n\nj2_average = j2['Average']\nr2_average = r2['Average']\n\nj2_conf = j2['diff2']\nr2_conf = r2['diff2']\n\nj3_average = j3['Average']\nr3_average = r3['Average']\n\nj3_conf = j3['diff2']\nr3_conf = r3['diff2']\n\nind = np.arange(len(j1_average)) # the x locations for the groups #May need to tweak this\nwidth = 0.35 #bar width #And tweak this\n\n##start making the plots\nrects1 = ax1.bar(ind - width/2, j1_average, width, yerr = j1_conf, capsize = 3, color = 'navy', edgecolor = 'k',\n label ='JOL')\n\nrects2 = ax1.bar(ind + width/2, r1_average, width, yerr = r1_conf, capsize = 3, color = 'dodgerblue', edgecolor = 'k',\n label = 'Recall')\n\n#Make the plot spiffy\nax1.set_title('No-Highlights', fontsize = 18, fontweight = 'bold')\nax1.set_ylabel('Mean % JOL/Recall', fontsize = 16)\nax1.set_xlabel('Direction', fontsize = 16)\nax1.xaxis.labelpad = 0\nax1.set_xticks(ind)\nax1.set_xticklabels(('Backward', 'Forward', 'Symmetrical', 'Unrelated'), fontsize = 14)\nax1.legend(fontsize = 14)\nax1.set_ylim([0,100])\n\n##Large Font\n##start making the plots\nrects3 = ax2.bar(ind - width/2, j2_average, width, yerr = j2_conf, capsize = 3, color = 'navy', edgecolor = 'k',\n label ='JOL')\n\nrects4 = ax2.bar(ind + width/2, r2_average, width, yerr = r2_conf, capsize = 3, color = 'dodgerblue', edgecolor = 'k',\n label = 'Recall')\n\n#Make the plot spiffy\nax2.set_title('Highlights', fontsize = 18, fontweight = 'bold')\nax2.set_ylabel('Mean % JOL/Recall', fontsize = 16)\nax2.set_xlabel('Direction', fontsize = 16)\nax2.xaxis.labelpad = 0\nax2.set_xticks(ind)\nax2.set_xticklabels(('Backward', 'Forward', 'Symmetrical', 'Unrelated'), fontsize = 14)\nax2.legend(fontsize = 14)\nax2.set_ylim([0,100])\n\n##Control\n##start making the plots\nrects5 = ax3.bar(ind - width/2, j3_average, width, yerr = j3_conf, capsize = 3, color = 'navy', edgecolor = 'k',\n label ='JOL')\n\nrects6 = ax3.bar(ind + width/2, r3_average, width, yerr = r3_conf, capsize = 3, color = 'dodgerblue', edgecolor = 'k',\n label = 'Recall')\n\n#Make the plot spiffy\nax3.set_title('Control', fontsize = 18, fontweight = 'bold')\nax3.set_ylabel('Mean % JOL/Recall', fontsize = 16)\nax3.set_xlabel('Direction', fontsize = 16)\nax3.xaxis.labelpad = 0\nax3.set_xticks(ind)\nax3.set_xticklabels(('Backward', 'Forward', 'Symmetrical', 'Unrelated'), fontsize = 14)\nax3.legend(fontsize = 14)\nax3.set_ylim([0,100])\n\n##save figure\nfig.savefig('EX1B_chart_updated.png', dip = 10000)","sub_path":"6 Manuscript/Figures/Ex 1B.py","file_name":"Ex 1B.py","file_ext":"py","file_size_in_byte":3671,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"441065198","text":"from typing import List, Optional, Union\n\nfrom numpy.core.multiarray import ndarray\n\nfrom symqv.lib.expressions.qbit import QbitVal\n\n\nclass Gate:\n def __init__(self,\n name: str,\n arguments: List[QbitVal],\n matrix: Optional[ndarray],\n matrix_swapped: ndarray = None,\n mapping=None,\n r_mapping=None,\n parameter=None,\n oracle_value: int = None):\n self.name = name\n self.arguments = arguments\n self.matrix = matrix\n self.matrix_swapped = matrix_swapped\n self.mapping = mapping\n self.r_mapping = r_mapping\n self.parameter = parameter\n self.control_qbits = None\n self.oracle_value = oracle_value\n\n def __pow__(self, power, modulo=None):\n \"\"\"\n Power of gate.\n :param power: power.\n :param modulo: power of modulo (not supported).\n :return: power of gate.\n \"\"\"\n if modulo is not None:\n raise Exception('Power modulo is not supported')\n\n return Gate(f'self.name ** {power}',\n self.arguments,\n self.matrix ** power,\n\n None if self.matrix_swapped is None else self.matrix_swapped ** power)\n\n def __repr__(self):\n if self.oracle_value is None:\n string = self.name\n\n if self.parameter is not None:\n string += f'_{self.parameter}'\n\n if isinstance(self.arguments[0], list):\n string += f'({self.arguments})'\n else:\n string += f'({\", \".join([q.get_identifier() for q in self.arguments])})'\n\n if self.control_qbits is not None:\n string += f'.controlled_by({\", \".join([q.get_identifier() for q in self.control_qbits])})'\n\n return string\n else:\n return f'{self.name}_{self.oracle_value}({\", \".join([q.get_identifier() for q in self.arguments])})'\n\n def controlled_by(self, control_qbits: Union[QbitVal, List[QbitVal]]):\n if isinstance(control_qbits, QbitVal):\n self.control_qbits = [control_qbits]\n else:\n self.control_qbits = control_qbits\n return self\n\n def arity(self):\n return len(self.arguments)\n","sub_path":"symqv/lib/models/gate.py","file_name":"gate.py","file_ext":"py","file_size_in_byte":2312,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"413090360","text":"__author__ = 'mcsc'\nfrom Abstract_SCADA import SCADA\nimport socket\nclass phaSCADA(SCADA):\n current_power_source = 'grid'\n def request_fail_message(self, device):\n print(\"Could not send request to {0} device\".format(device))\n reply = \":::Sorry, could not get information from {0} device\".format(device)\n return reply\n\n def form_reply_helper(self,device,option,reply_msg):\n if device == 'power':\n device = option\n if self.current_power_source != 'grid':\n (self.send_request(self.current_power_source,'stop'))\n self.current_power_source = 'grid'\n startmsg = str(self.send_request(device,'start'))\n self.current_power_source = device\n startmsg = startmsg.lower()\n return str(reply_msg).format(startmsg)\n else:\n try:\n data = str(self.send_request(device,option))\n\n except (socket.error,socket.herror,socket.timeout):\n return self.request_fail_message(device)\n\n else:\n data = data.lower()\n if data == 'invalid request':\n return ':::Invalid request'\n else:\n return str(reply_msg).format(data)\n\n def form_reply(self,data):\n\n data = str(data).split(':')\n device = data[0]\n option = data[1]\n\n msg = \"\"\n\n if device == 'oil':\n if option == 'check level':\n msg = \":::Oil level: {0} gallons\"\n elif option == 'run time':\n msg = \":::Estimated Generator Run Time Remaining: {0}\"\n elif option == 'fill' or option == 'status':\n msg = \":::{0}\"\n\n elif device == 'battery':\n if option == 'check life':\n msg = \":::Battery life: {0} percent\"\n elif option == 'run time':\n msg = \":::Estimated Battery Run Time Remaining: {0}\"\n elif option == 'charge' or option == 'status':\n msg = \":::{0}\"\n\n elif device == \"server\":\n if option == 'check temp':\n msg = \":::Server Temperature: {0} degrees\"\n elif option == 'turn on cooling':\n msg = \"{0}\"\n elif option == 'turn off cooling':\n msg = \"{0}\"\n\n elif device == \"power\":\n if option == 'power source':\n msg = \":::Current power source: {0}\"\n elif option == 'grid' or option == 'oil' or option == 'battery':\n msg = '{0}'\n\n else:\n return \":::Invalid request\"\n\n #################################\n\n if msg == \"\":\n return \":::Invalid request\"\n else:\n reply = self.form_reply_helper(device,option,msg)\n return reply\n\n\nphaDevices = {\"oil\":\"192.168.10.99:1100\",\"battery\":\"192.168.10.99:1101\", \"power\":\"192.168.10.99\", \"server\":\"192.168.10.99\"}\nscada = phaSCADA('192.168.10.99',8888, phaDevices)\nscada.open_connection()\n","sub_path":"phaSCADA.py","file_name":"phaSCADA.py","file_ext":"py","file_size_in_byte":3027,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"436517371","text":"import api.DAL.blog.blog_select as blog_select\nimport api.DAL.blog.blog_insert as blog_insert\nimport api.DAL.blog.blog_update as blog_update\nfrom werkzeug.utils import secure_filename\nimport api.logs.logger as logger\n\nimport os\nimport json\n\nclass BlogLogicalInterface:\n\n \"\"\"Interface between front end and back. In charge of the creation, retreival (from DAL), and simple preccessing of data\"\"\"\n\n def create_post(self, json_data, image):\n\n \"\"\"Recieves request to add a post to the database with the data in a json format\n The JSON is then pared and sent to the dal\"\"\"\n\n logger.log(\"blog interface\", \"Sanitizing Input\")\n\n title = self.sanitize_string(json_data['title'])\n body = self.sanitize_string(json_data['body'])\n description = self.sanitize_string(json_data['description'])\n\n image_name = self.sanitize_string(secure_filename(image.filename))\n caption = self.sanitize_string(json_data['caption'])\n\n image_path = self._create_realative_image_path(image_name)\n\n logger.log(\"blog interface\", \"Adding Post to Database\")\n blog_post_id = blog_insert.post(title, description, body, image_path, caption)\n\n abs_path = self._create_absolute_image_path(image_path)\n\n logger.log(\"blog interface\", \"Adding Image to Filesystem\")\n image.save(abs_path)\n\n\n def _create_realative_image_path(self, image_name):\n\n '''Generates the images path to be placed in the database'''\n\n return \"headers/{0}\".format(image_name)\n\n\n def _create_absolute_image_path(self, relative_path):\n\n '''Generates absolute image path to save image in the file system'''\n\n return \"{0}/api/images/{1}\".format(os.getcwd(), relative_path)\n\n\n\n def get_headers(self):\n\n \"\"\"Displays all the headers of all blogs stored in the database\n This is the title, the main picture, and the brief desciption\"\"\"\n \n return blog_select.all_post_headers()\n\n\n def retrieve_post(self, index):\n\n '''Retrieves all the content of a single post indicated by the index\n This includes all asociated comments, the body, images, and header'''\n\n logger.log(\"blog interface\", \"Retrieving Post\")\n post = json.loads(blog_select.post(index))\n\n if post[\"image\"] == 'None':\n\n logger.log(\"blog interface\", \"Using Default Image\")\n post[\"image\"] = '/images/default/jazz.jpg'\n\n logger.log(\"blog interface\", \"Retrieving Comments\")\n comments = json.loads(blog_select.comments(index))\n\n logger.log(\"blog interface\", \"Concatinating Comments to Post\")\n post.update(comments)\n \n return json.dumps(post)\n\n\n def add_comment_to_post(self, index, comment, user):\n\n '''Adds a comment to a post indicated by the index. \n The comment is assigned to to the user that requested the addition'''\n\n user_id = user['id']\n logger.log(\"blog interface\", \"Sanitizing Comment\")\n comment = self.sanitize_string(comment)\n logger.log(\"blog interface\", \"Adding Comment to Database\")\n\n return blog_insert.comment(index, comment, user_id)\n\n\n def modify_post(self, index, body):\n\n logger.log(\"blog interface\", \"Sanitizing Body\")\n body = self.sanitize_string(body)\n logger.log(\"blog interface\", \"Adding Body Modification in Database\")\n\n return blog_update.post_body(index, body)\n\n def sanitize_string(self, string):\n\n \"\"\"Sanatizes string so that it can be used in a JSON format\n it add char breaks to \"'s and new lines\"\"\"\n \n string = string.replace('\"', '\\\\\"')\n string = string.replace('\\n', '
')\n return string\n\n ","sub_path":"api/core/blog/logical_interface.py","file_name":"logical_interface.py","file_ext":"py","file_size_in_byte":3708,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"54197393","text":"import logging\nimport time\n\nimport ccxt\n\nfrom backtesting.backtesting import Backtesting\nfrom backtesting.exchange_simulator import ExchangeSimulator\nfrom config.cst import *\nfrom evaluator.Updaters.symbol_time_frames_updater import SymbolTimeFramesDataUpdaterThread\nfrom evaluator.Util.advanced_manager import AdvancedManager\nfrom evaluator.cryptocurrency_evaluator import CryptocurrencyEvaluator\nfrom evaluator.evaluator_creator import EvaluatorCreator\nfrom evaluator.evaluator_threads_manager import EvaluatorThreadsManager\nfrom evaluator.symbol_evaluator import SymbolEvaluator\nfrom services import ServiceCreator\nfrom tools.notifications import Notification\nfrom tools.performance_analyser import PerformanceAnalyser\nfrom tools.time_frame_manager import TimeFrameManager\nfrom trading import Exchange\nfrom trading.trader.trader import Trader\nfrom trading.trader.trader_simulator import TraderSimulator\n\n\"\"\"Main CryptoBot class:\n- Create all indicators and thread for each cryptocurrencies in config \"\"\"\n\n\nclass CryptoBot:\n \"\"\"\n Constructor :\n - Load configs\n \"\"\"\n\n def __init__(self, config):\n self.start_time = time.time()\n self.config = config\n self.ready = False\n\n # Logger\n self.logger = logging.getLogger(self.__class__.__name__)\n\n # Advanced\n AdvancedManager.create_class_list(self.config)\n\n # Debug tools\n self.performance_analyser = None\n if CONFIG_DEBUG_OPTION_PERF in self.config and self.config[CONFIG_DEBUG_OPTION_PERF]:\n self.performance_analyser = PerformanceAnalyser()\n\n self.time_frames = TimeFrameManager.get_config_time_frame(self.config)\n\n # Add services to self.config[CONFIG_CATEGORY_SERVICES]\n ServiceCreator.create_services(self.config)\n\n # Notifier\n self.config[CONFIG_NOTIFICATION_INSTANCE] = Notification(self.config)\n\n # Notify starting\n self.config[CONFIG_NOTIFICATION_INSTANCE].notify_with_all(NOTIFICATION_STARTING_MESSAGE)\n\n # Backtesting\n self.backtesting_enabled = None\n\n self.symbol_threads_manager = {}\n self.exchange_traders = {}\n self.exchange_trader_simulators = {}\n self.exchanges_list = {}\n self.symbol_evaluator_list = {}\n self.crypto_currency_evaluator_list = {}\n self.dispatchers_list = []\n self.symbol_time_frame_updater_threads = []\n\n def create_exchange_traders(self):\n self.backtesting_enabled = Backtesting.enabled(self.config)\n\n available_exchanges = ccxt.exchanges\n for exchange_class_string in self.config[CONFIG_EXCHANGES]:\n if exchange_class_string in available_exchanges:\n exchange_type = getattr(ccxt, exchange_class_string)\n\n # Backtesting Exchange\n if self.backtesting_enabled:\n exchange_inst = ExchangeSimulator(self.config, exchange_type)\n else:\n # True Exchange\n exchange_inst = Exchange(self.config, exchange_type)\n\n self.exchanges_list[exchange_inst.get_name()] = exchange_inst\n\n # create trader instance for this exchange\n exchange_trader = Trader(self.config, exchange_inst)\n self.exchange_traders[exchange_inst.get_name()] = exchange_trader\n\n # create trader simulator instance for this exchange\n exchange_trader_simulator = TraderSimulator(self.config, exchange_inst)\n self.exchange_trader_simulators[exchange_inst.get_name()] = exchange_trader_simulator\n else:\n self.logger.error(\"{0} exchange not found\".format(exchange_class_string))\n\n def create_evaluation_threads(self):\n self.logger.info(\"Evaluation threads creation...\")\n\n # create dispatchers\n self.dispatchers_list = EvaluatorCreator.create_dispatchers(self.config)\n\n # create Social and TA evaluators\n for crypto_currency, crypto_currency_data in self.config[CONFIG_CRYPTO_CURRENCIES].items():\n\n # create crypto_currency evaluator\n crypto_currency_evaluator = CryptocurrencyEvaluator(self.config, crypto_currency, self.dispatchers_list)\n self.crypto_currency_evaluator_list[crypto_currency] = crypto_currency_evaluator\n\n # create TA evaluators\n for symbol in crypto_currency_data[CONFIG_CRYPTO_PAIRS]:\n\n # create symbol evaluator\n symbol_evaluator = SymbolEvaluator(self.config, symbol, crypto_currency_evaluator)\n symbol_evaluator.set_traders(self.exchange_traders)\n symbol_evaluator.set_trader_simulators(self.exchange_trader_simulators)\n\n crypto_currency_evaluator.add_symbol_evaluator(symbol, symbol_evaluator)\n self.symbol_evaluator_list[symbol] = symbol_evaluator\n\n for exchange in self.exchanges_list.values():\n if exchange.enabled():\n\n # Verify that symbol exists on this exchange\n if symbol in exchange.get_traded_pairs():\n self._create_symbol_threads_managers(symbol,\n exchange,\n symbol_evaluator)\n\n # notify that exchange doesn't support this symbol\n else:\n if not self.backtesting_enabled:\n self.logger.warning(\"{0} doesn't support {1}\".format(exchange.get_name(), symbol))\n\n def _create_symbol_threads_managers(self, symbol, exchange, symbol_evaluator):\n # Create real time TA evaluators\n real_time_ta_eval_list = EvaluatorCreator.create_real_time_ta_evals(self.config,\n exchange,\n symbol)\n symbol_time_frame_updater_thread = SymbolTimeFramesDataUpdaterThread()\n for time_frame in self.time_frames:\n if exchange.time_frame_exists(time_frame.value):\n self.symbol_threads_manager[time_frame] = EvaluatorThreadsManager(self.config,\n symbol,\n time_frame,\n symbol_time_frame_updater_thread,\n symbol_evaluator,\n exchange,\n real_time_ta_eval_list)\n self.symbol_time_frame_updater_threads.append(symbol_time_frame_updater_thread)\n\n def start_threads(self):\n if self.performance_analyser:\n self.performance_analyser.start()\n\n for crypto_currency_evaluator in self.crypto_currency_evaluator_list.values():\n crypto_currency_evaluator.start_threads()\n\n for manager in self.symbol_threads_manager.values():\n manager.start_threads()\n\n for thread in self.symbol_time_frame_updater_threads:\n thread.start()\n\n for thread in self.dispatchers_list:\n thread.start()\n\n self.ready = True\n self.logger.info(\"Evaluation threads started...\")\n\n def join_threads(self):\n for manager in self.symbol_threads_manager:\n self.symbol_threads_manager[manager].join_threads()\n\n for thread in self.symbol_time_frame_updater_threads:\n thread.join()\n\n for crypto_currency_evaluator in self.crypto_currency_evaluator_list.values():\n crypto_currency_evaluator.join_threads()\n\n for trader in self.exchange_traders.values():\n trader.join_order_manager()\n\n for trader_simulator in self.exchange_trader_simulators.values():\n trader_simulator.join_order_manager()\n\n for thread in self.dispatchers_list:\n thread.join()\n\n if self.performance_analyser:\n self.performance_analyser.join()\n\n def stop_threads(self):\n # Notify stopping\n self.config[CONFIG_NOTIFICATION_INSTANCE].notify_with_all(NOTIFICATION_STOPPING_MESSAGE)\n\n self.logger.info(\"Stopping threads ...\")\n\n for thread in self.symbol_time_frame_updater_threads:\n thread.stop()\n\n for manager in self.symbol_threads_manager.values():\n manager.stop_threads()\n\n for crypto_currency_evaluator in self.crypto_currency_evaluator_list.values():\n crypto_currency_evaluator.stop_threads()\n\n for trader in self.exchange_traders.values():\n trader.stop_order_manager()\n\n for trader_simulator in self.exchange_trader_simulators.values():\n trader_simulator.stop_order_manager()\n\n for thread in self.dispatchers_list:\n thread.stop()\n\n if self.performance_analyser:\n self.performance_analyser.stop()\n\n # stop services\n for service_instance in ServiceCreator.get_service_instances(self.config):\n try:\n service_instance.stop()\n except Exception as e:\n raise e\n\n self.logger.info(\"Threads stopped.\")\n\n def get_symbols_threads_manager(self):\n return self.symbol_threads_manager\n\n def get_exchange_traders(self):\n return self.exchange_traders\n\n def get_exchange_trader_simulators(self):\n return self.exchange_trader_simulators\n\n def get_exchanges_list(self):\n return self.exchanges_list\n\n def get_symbol_evaluator_list(self):\n return self.symbol_evaluator_list\n\n def get_crypto_currency_evaluator_list(self):\n return self.crypto_currency_evaluator_list\n\n def get_dispatchers_list(self):\n return self.dispatchers_list\n\n def get_symbol_time_frame_updater_threads(self):\n return self.symbol_time_frame_updater_threads\n\n def get_start_time(self):\n return self.start_time\n\n def is_ready(self):\n return self.ready\n","sub_path":"cryptobot.py","file_name":"cryptobot.py","file_ext":"py","file_size_in_byte":10319,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"330469724","text":"from ftw.builder import Builder\nfrom ftw.builder import create\nfrom ftw.testbrowser import browsing\nfrom opengever.testing import SolrIntegrationTestCase\nimport random\n\n\nclass TestSolrIsolation(SolrIntegrationTestCase):\n\n @browsing\n def test_solr_search_results_with_dynamic_content(self, browser):\n self.login(self.regular_user, browser=browser)\n\n random_title = u'uniqueterm%s' % str(random.randint(1, 10000))\n create(Builder('dossier')\n .titled(random_title)\n .within(self.repository_root))\n\n self.commit_solr()\n\n browser.open(self.repository_root,\n view='@solrsearch?q=uniqueterm*',\n headers={'Accept': 'application/json'})\n\n result = browser.json\n self.assertEqual(1, result['items_total'])\n self.assertEqual(1, len(result['items']))\n self.assertEqual(random_title, result['items'][0]['title'])\n\n# Create an additional copy of the above test that would fail if isolation\n# didn't work between tests (i.e. if created objects in Solr would leak\n# between test runs instead of getting reset to the layer snapshot).\n\nsetattr(TestSolrIsolation, 'test_solr_search_results_with_dynamic_content_1',\n TestSolrIsolation.test_solr_search_results_with_dynamic_content)\n","sub_path":"opengever/testing/tests/test_solr.py","file_name":"test_solr.py","file_ext":"py","file_size_in_byte":1306,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"337469271","text":"import jwt\nfrom django.conf import settings\nfrom django.contrib.auth import authenticate\nfrom rest_framework.decorators import api_view, permission_classes\nfrom rest_framework.views import APIView\nfrom rest_framework.response import Response\nfrom rest_framework.permissions import IsAuthenticated\nfrom rest_framework import status\nfrom .serializers import UserSerializer\nfrom rooms.serializers import RoomSerializer\nfrom .models import User\nfrom rooms.models import Room\n\n\n# create account : POST -> api/v1/users\nclass UsersView(APIView):\n def post(self, request):\n serializer = UserSerializer(data=request.data)\n if serializer.is_valid():\n new_user = serializer.save()\n return Response(UserSerializer(new_user).data)\n else:\n return Response(data=serializers.errors, status=status.HTTP_400_BAD_REQUEST)\n\n\n# Login View는 별기능이 없으니 FBV로 만들자\n@api_view([\"POST\"])\ndef login(request):\n username = request.data.get(\"username\")\n password = request.data.get(\"password\")\n if not username or not password:\n return Response(status=status.HTTP_400_BAD_REQUEST)\n # 장고는 authentication function이 있다.\n # 이 function은 username과 password를 비교해 맞으면 그 user를 return 해준다.\n\n user = authenticate(username=username, password=password)\n # 우리는 일치하는 인증된 user를 얻었다.\n # 이 user를 JWT(JSON WEB TOKEN)으로 보내줘야함\n if user is not None:\n encoded_jwt = jwt.encode(\n {\"pk\": user.pk}, settings.SECRET_KEY, algorithm=\"HS256\"\n )\n return Response(data={\"token\": encoded_jwt})\n else:\n return Response(status=status.HTTP_401_UNAUTHORIZED)\n # jwt에는 절때 네버 민감한정보는 담아서는 안된다.\n # 근데 의문점은 이 토큰을 jwt.io에서 너무쉽게 decoded해 안의 정보를 볼수 있다.\n # 그럼 왜쓰냐 이건데\n # 우리의 server는 token이 다른사람에의해 수정되었냐를 체크할수있다.\n # jwt를 쓰는이유는 그 누구도 우리의 token을 건들지 않았다는 것을 확인하는 용도이다.\n # 다시말하면 데이터(token안의 정보)를 아무도 못보게 암호화하는 것이 목적이아니라\n # 이 데이터를 누군가가 건드렸느냐 아니면 그대로이냐가 더 중요한 Point임\n # 프론트엔드에서 이 토큰을 받아서 header로 전송해주면 그 token은 decode 과정을 거쳐\n # 실제정보로 변환된다.\n\n\nclass MyView(APIView):\n permission_classes = [IsAuthenticated]\n\n def get(self, request):\n return Response(UserSerializer(request.user).data)\n\n def put(self, request):\n user = request.user\n serializer = UserSerializer(user, data=request.data, partial=True)\n if serializer.is_valid():\n user = serializer.save()\n return Response(UserSerializer(user).data)\n else:\n return Response(data=serializer.errors, status=status.HTTP_400_BAD_REQUEST)\n\n\nclass FavsView(APIView):\n permission_classes = [IsAuthenticated]\n\n def get(self, request):\n user = request.user\n serializer = RoomSerializer(user.favs.all(), many=True).data\n return Response(serializer)\n\n def put(self, request):\n pk = request.data.get(\"pk\", None)\n user = request.user\n if pk is not None:\n try:\n room = Room.objects.get(pk=pk)\n if room in user.favs.all():\n user.favs.remove(room)\n else:\n user.favs.add(room)\n serializer = RoomSerializer(user.favs.all(), many=True).data\n return Response(serializer)\n except Room.DoesNotExist:\n return Response(status=status.HTTP_404_NOT_FOUND)\n else:\n return Response(status=status.HTTP_400_BAD_REQUEST)\n\n\n# GET : api/v1/users/12\n@api_view([\"GET\"])\ndef user_detail(request, pk):\n try:\n user = User.objects.get(pk=pk)\n serializer = UserSerializer(user).data\n return Response(serializer)\n except User.DoesNotExist:\n return Response(status=status.HTTP_404_NOT_FOUND)\n","sub_path":"users/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":4218,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"638415302","text":"import unittest\n\nfrom coaster.db import db\nfrom coaster.sqlalchemy import BaseMixin, CoordinatesMixin\n\nfrom .test_sqlalchemy_models import app2\n\n\nclass CoordinatesData(BaseMixin, CoordinatesMixin, db.Model):\n __tablename__ = 'coordinates_data'\n\n\n# -- Tests --------------------------------------------------------------------\n\n\nclass TestCoordinatesColumn(unittest.TestCase):\n # Restrict tests to PostgreSQL as SQLite3 doesn't have a Decimal type\n app = app2\n\n def setUp(self):\n self.ctx = self.app.test_request_context()\n self.ctx.push()\n db.create_all()\n self.session = db.session\n\n def tearDown(self):\n self.session.rollback()\n db.drop_all()\n self.ctx.pop()\n\n def test_columns_created(self):\n table = CoordinatesData.__table__\n assert isinstance(table.c.latitude.type, db.Numeric)\n assert isinstance(table.c.longitude.type, db.Numeric)\n\n def test_columns_when_null(self):\n data = CoordinatesData()\n assert data.coordinates == (None, None)\n assert data.has_coordinates is False\n\n def test_columns_when_missing(self):\n data = CoordinatesData()\n assert data.has_coordinates is False\n assert data.has_missing_coordinates is True\n data.coordinates = (12, None)\n assert data.has_coordinates is False\n assert data.has_missing_coordinates is True\n data.coordinates = (None, 73)\n assert data.has_coordinates is False\n assert data.has_missing_coordinates is True\n data.coordinates = (12, 73)\n assert data.has_coordinates is True\n assert data.has_missing_coordinates is False # type: ignore[unreachable]\n\n def test_column_set_value(self):\n data = CoordinatesData()\n data.coordinates = (12, 73)\n assert data.coordinates == (12, 73)\n assert data.has_coordinates is True\n db.session.add(data)\n db.session.commit()\n\n readdata = CoordinatesData.query.first()\n assert readdata.coordinates == (12, 73)\n","sub_path":"tests/test_sqlalchemy_coordinates.py","file_name":"test_sqlalchemy_coordinates.py","file_ext":"py","file_size_in_byte":2046,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"609631767","text":"#!/usr/bin/python2.7\n# Copyright (c) 2012, Niklas Femerstrand \n# All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions\n# are met:\n#\n# Redistributions of source code must retain the above copyright notice,\n# this list of conditions and the following disclaimer.\n# Redistributions in binary form must reproduce the above copyright notice,\n# this list of conditions and the following disclaimer in the documentation\n# and/or other materials provided with the distribution.\n#\n# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS\n# IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,\n# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR\n# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR\n# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\n# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\n# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;\n# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,\n# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR\n# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF\n# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\nimport re\nimport os\nimport socket\nimport threading\nimport BaseHTTPServer\nfrom SimpleHTTPServer import SimpleHTTPRequestHandler\nfrom BaseHTTPServer import BaseHTTPRequestHandler, HTTPServer\n\n# Basic HTTP server that listens to GET /panic and triggers panic.\n# Written to provide a standardized interface for panic triggering.\n# To trigger panic through HTTP simply request http://localhost:8080/panic\nclass panicHandler(BaseHTTPRequestHandler):\n\tdef do_GET(self):\n\t\tif self.path == \"/\\x70\\x61\\x6e\\x69\\x63\":\n\t\t\tsendSignal()\n\ndef httpd():\n\ts = HTTPServer(('', 8080), panicHandler)\n\ts.serve_forever()\n\n# TODO: Extend with a C lib that iterates through used physmem addresses and\n# overwrites values in a prio order before triggering poweroff.\n# TODO: Use mountedDrives() to iterate and eject (crypto) mounts\ndef treatPanic():\n\tos.popen(\"killall truecrypt\")\n\t# Linux, possibly more\n\tos.popen(\"shutdown -P now\")\n\t# FreeBSD, possibly more\n\tos.popen(\"shutdown -p now\")\n\ndef sigListener():\n\ts = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\n\ts.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)\n\ts.setsockopt(socket.SOL_SOCKET, socket.SO_BROADCAST, 1)\n\ts.bind((\"\", 1337)) # Listen on all devices\n\n\twhile 1:\n\t\ttry:\n\t\t\tmessage, address = s.recvfrom(5)\n\t\t\tif message == \"\\x70\\x61\\x6e\\x69\\x63\":\n\t\t\t\ttreatPanic()\n\t\texcept:\n\t\t\tpass\n\n# Extracts mounted device names and mount points. Intended to work on\n# everything UNIX. Tested on Linux and FreeBSD (UFS2 and ZFS).\ndef mountedDrives():\n\tdrives = []\n\tmount = os.popen(\"mount | grep -o \\\".* on .* (\\\"\").read()\n\tfor m in mount.split(\"\\n\"):\n\t\tmatches = re.match(\"(.*) on (.*) \\(\", m)\n\t\tif matches:\n\t\t\tdrives.append({ matches.group(1) : matches.group(2) })\n\n\treturn drives\n\ndef bcast():\n\tbcast = os.popen(\"ifconfig | grep -o \\\"broadcast [0-9]*\\.[0-9]*\\.[0-9]*\\.[0-9]*\\\"\").read()\n\tbcast = bcast.replace(\"broadcast \", \"\")\n\n\treturn bcast\n\t\ndef sendSignal():\n\ts = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\n\ts.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)\n\ts.setsockopt(socket.SOL_SOCKET, socket.SO_BROADCAST, 1)\n\ts.sendto(\"\\x70\\x61\\x6e\\x69\\x63\", (bcast(), 1337))\n\ts.close()\n\n\treturn 0\n\nhttpd = threading.Thread(name=\"httpd\", target=httpd)\nhttpd.start()\nsigListener = threading.Thread(name=\"sigListener\", target=sigListener)\nsigListener.start()\n","sub_path":"panic_bcast.py","file_name":"panic_bcast.py","file_ext":"py","file_size_in_byte":3668,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"563905071","text":"import spider\nfrom spider import *\n\nfrom warp import proc\nimport unittest\n\n\n# Mock Classes\n\nclass WARP_Mock(warp.WARP):\n\n FORMATTED_ANCHORS_URL = \"http://formatted.urls.com\"\n\n def __init__(self):\n super(WARP_Mock, self).__init__()\n self.get_return_value = None\n self.get_invoked = False\n self.response_str_dict = {\n WARP_Mock.FORMATTED_ANCHORS_URL:\n \"\"\"\n Title ABC
\n one\n \n two\n \n three\"\"\",\n\n '1': \"\"\"\n One
\n four\"\"\",\n\n '2': \"\"\"\n Two
\"\"\",\n\n '3': \"\"\"\n Three
\"\"\",\n\n '4': \"\"\"\n Four
\n five\"\"\",\n\n '5': \"\"\"\n Five
\"\"\",\n }\n\n def get(self, url_base, **kwargs):\n self.get_invoked = True\n if kwargs.get('info_dict')==True:\n return {\n 'req_url': url_base,\n 'content': self.response_str_dict[url_base]\n }\n else:\n return self.response_str_dict[url_base]\n\n\n\n# Helper Classes\n\nclass DataProbe(warp.ExtractorDataSink):\n\n def configure(self):\n self.id = 'data-probe'\n self.version = 1\n self.output_format = 'application/json'\n\n # inspection\n self.invoked = False\n self.considered = False\n self.data = \"NO DATA WRITTEN\"\n\n def process(self, response_str, input_dict):\n self.invoked = True\n self.data = response_str\n\nclass PipelineDataProbe(warp.DataSink):\n\n def configure(self):\n self.id = 'pipeline-data-probe'\n self.version = 1\n self.output_format = None\n\n # inspection\n self.invoked = False\n self.considered = False\n self.data = []\n\n def process(self, input_dict):\n self.invoked = True\n self.data.append(input_dict)\n\nclass UrlPathProbe(event_bus.Action):\n\n def __init__(self):\n self.path = []\n\n def perform_action(self, event):\n self.path.append(event.url)\n\n\n\n# Test Cases\n\nclass SpiderInitialization_TestCase(unittest.TestCase):\n\n def setUp(self):\n self.s = Spider()\n\n resSub = ResponseSubscription(r'/index/.*')\n self.a = ActionProbe('nothing')\n l_ex_re = ReLinkExtractor([r'.*/ind/.*'])\n inj = ExtractAndInjectAction(self.s, l_ex_re)\n self.spec = {\n ResponseEvent : [(resSub, self.a), (resSub, inj)]\n }\n\n def test_chaining(self):\n self.s.at(r'/index/.*').do(self.a).extract_links_with(re=r'.*/ind/.*')\n for (e_type, actions) in self.spec.items():\n for a in actions:\n self.assertIn(a, self.s.bus.action_map[e_type])\n\n def test_instruct(self):\n self.s.instruct(\n at=r'/index/.*',\n do=self.a,\n extract_links=dict(re=r'.*/ind/.*')\n )\n for (e_type, actions) in self.spec.items():\n for a in actions:\n self.assertIn(a, self.s.bus.action_map[e_type])\n\n\nclass Spider_TestCase(unittest.TestCase):\n\n def setUp(self):\n self.spec_graph = networkx.DiGraph()\n self.spec_graph.add_edges_from(\n (\n (WARP_Mock.FORMATTED_ANCHORS_URL, '1', dict(label='one')),\n (WARP_Mock.FORMATTED_ANCHORS_URL, '2', dict(label='two')),\n (WARP_Mock.FORMATTED_ANCHORS_URL, '3', dict(label='three')),\n ('1', '4', dict(label='four')),\n ('4', '5', dict(label='five'))\n )\n )\n for n in self.spec_graph.nodes():\n self.spec_graph.node[n]['visited']=False\n\n def test_eventRegistration(self):\n warp_mock = WARP_Mock()\n\n # events & subscriptions\n initS = ClassSubscriptionWrapper(StartEvent)\n resS = ResponseSubscription(r'.*google.*')\n exReqS = ExtractionRequestSubscription(r'.*')\n\n # actions\n timeProbeA = ActionProbe('time')\n urlProbeA = ActionProbe('url')\n\n s = Spider(web_accessor=warp_mock)\n\n # extractor\n exProbe = DataProbe(caching=False)\n exWrapA = ProcessPipelineAction(s, warp_mock, exProbe)\n\n spec = {\n StartEvent : [(initS, timeProbeA)],\n ResponseEvent : [(resS, urlProbeA)],\n ExtractionRequestEvent : [(exReqS, exWrapA)]\n }\n\n s.append_on_init(timeProbeA)\n s.append_on_response(urlProbeA, r'.*google.*')\n s.append_proc(exProbe, r'.*')\n\n for e_type, actions in spec.items():\n for a in actions:\n self.assertIn(a, s.bus.action_map[e_type])\n\n def test_automaticTemplateMethodRegistration(self):\n s = Spider()\n e = StartEvent()\n init_actions = s.bus.actions_for_event(e)\n self.assertEqual(len(init_actions), 1)\n res_actions = s.bus.actions_for_event(ResponseEvent(Spider(), 'www.xkcd.com', None))\n self.assertEqual(len(res_actions), 1)\n\n def test_extractorPipeline(self):\n warp_mock = WARP_Mock()\n\n ex1 = proc.proc_tests.TitleExtractor(caching=False)\n ex2 = proc.proc_tests.TitleDecorator(caching=False)\n ex3 = PipelineDataProbe(caching=False)\n ex_pipe = warp.ProcessingPipeline(ex1, ex2, ex3)\n\n spec = [{\n 'url': WARP_Mock.FORMATTED_ANCHORS_URL,\n 'title-extractor': {\n 'title': \"Title ABC\"\n },\n 'title-decorator': {\n 'title': \"Title ABC\"\n }\n }]\n\n s = Spider([WARP_Mock.FORMATTED_ANCHORS_URL], web_accessor=warp_mock)\n s.append_proc(ex_pipe, '.*')\n actions = s.bus.actions_for_event(ExtractionRequestEvent(s, WARP_Mock.FORMATTED_ANCHORS_URL))\n self.assertTrue(len(actions), 1)\n\n s.go()\n self.assertTrue(ex1.invoked)\n self.assertTrue(ex2.invoked)\n self.assertTrue(ex3.invoked)\n self.assertItemsEqual(spec, ex3.data)\n\n def test_FIFO_crawl(self):\n s = Spider(\n start_urls=[WARP_Mock.FORMATTED_ANCHORS_URL],\n web_accessor=WARP_Mock(),\n follow_all=True,\n resolve_rel_urls=False\n )\n urlPathProbe = UrlPathProbe()\n s.append_on_response(urlPathProbe)\n s.go()\n self.assertEqual(len(s.finished), 6)\n self.assertEqual(len(s.graph.nodes()), 6)\n self.assertEqual(urlPathProbe.path,\n [ WARP_Mock.FORMATTED_ANCHORS_URL, '1', '2', '3', '4', '5' ]\n )\n\n def test_depth_first_crawl(self):\n s = Spider(\n start_urls=[WARP_Mock.FORMATTED_ANCHORS_URL],\n web_accessor=WARP_Mock(),\n follow_all=True,\n depth_first=True,\n resolve_rel_urls=False\n )\n urlPathProbe = UrlPathProbe()\n s.append_on_response(urlPathProbe)\n s.go()\n self.assertEqual(urlPathProbe.path,\n [ WARP_Mock.FORMATTED_ANCHORS_URL, '1', '4', '5', '3', '2' ]\n )\n\n def test_prioritized_crawl(self):\n s = Spider(\n start_urls=[WARP_Mock.FORMATTED_ANCHORS_URL],\n web_accessor=WARP_Mock(),\n follow_all=True,\n crawl_order=['3', '1', '2', '4', '5'],\n resolve_rel_urls=False\n )\n urlPathProbe = UrlPathProbe()\n s.append_on_response(urlPathProbe)\n s.go()\n self.assertEqual(urlPathProbe.path,\n [ WARP_Mock.FORMATTED_ANCHORS_URL, '3', '1', '2', '4', '5' ]\n )\n\n def test_spiderGraph_dataInjection(self):\n s = Spider(\n start_urls=[ WARP_Mock.FORMATTED_ANCHORS_URL ],\n web_accessor=WARP_Mock(),\n follow_all=True,\n resolve_rel_urls=False\n )\n probe = PipelineDataProbe()\n s.append_proc(probe)\n s.go()\n\n self.assertItemsEqual(\n s.graph.edges(data=True),\n self.spec_graph.edges(data=True)\n )\n\n self.assertEqual(\n probe.data[-1], # of last crawled page\n {\n 'url' : '5',\n 'spider': { 'incoming': [('4', '5', {'label': 'five'})]}\n }\n )\n\n def test_depthFirst_traversal(self):\n t = DepthFirstTraversal(self.spec_graph, [WARP_Mock.FORMATTED_ANCHORS_URL])\n self.assertItemsEqual(\n t.stack,\n [ WARP_Mock.FORMATTED_ANCHORS_URL ]\n )\n\n self.assertEqual(t.next(), WARP_Mock.FORMATTED_ANCHORS_URL)\n self.assertEqual(t.stack, [ ])\n # last = WARP_Mock.FORMATTED_ANCHORS_URL\n\n # stack += ['1', '3', '2']\n self.assertEqual(t.next(), '1')\n self.assertEqual(t.stack, [ ['3', '2'] ])\n # last = '1'\n\n # stack += ['4']\n self.assertEqual(t.next(), '4')\n self.assertEqual(t.stack, [ ['3', '2'], [] ])\n # last = '4'\n\n # stack += ['5']\n self.assertEqual(t.next(), '5')\n self.assertEqual(t.stack, [ ['3', '2'], [], [] ])\n # last = '5'\n\n # stack += []\n self.assertEqual(t.next(), '3')\n self.assertEqual(t.stack, [ ['2'] ])\n # last = '3'\n\n # stack += []\n self.assertEqual(t.next(), '2')\n self.assertEqual(t.stack, [ [] ])\n # last = '2'\n\n self.assertRaises(StopIteration, t.next)\n\n\n\n# Link Extractor\n\nclass XPathLinkExtractor_TestCase(unittest.TestCase):\n\n def setUp(self):\n self.html_snippet = \"\"\"\n Title ABC
\n one\n \n two\n \n three\n \n four\n \n \"\"\"\n xpath = '//b/a'\n self.xp_link_ex = XPathLinkExtractor(xpath)\n\n def test_extract_anchors(self):\n a_list = self.xp_link_ex.extract_anchors(self.html_snippet)\n spec = [{'href': '#2', 'text': 'two'},\n {'href': '#4', 'text': 'four'}]\n self.assertEqual(spec, a_list)\n\n def test_extract_urls(self):\n url_list = self.xp_link_ex.extract_urls(self.html_snippet)\n spec = ['#2', '#4']\n self.assertEqual(spec, url_list)\n\n\nclass ReLinkExtractor_TestCase(unittest.TestCase):\n\n def setUp(self):\n self.html_snippet = \"\"\"\n Title ABC
\n one\n \n two\n \n three\n \n four\n \n \"\"\"\n re_list = ['.*[2|4]']\n self.re_link_ex = ReLinkExtractor(re_list)\n\n def test_extract_anchors(self):\n a_list = self.re_link_ex.extract_anchors(self.html_snippet)\n spec = [{'href': '#2', 'text': 'two'},\n {'href': '#4', 'text': 'four'}]\n self.assertEqual(spec, a_list)\n\n\n\n# Actions\n\nclass UrlInjector_TestCase(unittest.TestCase):\n\n def test_extractedUrlInjector(self):\n \"\"\"Test injection of URLs into spider queue.\n \"\"\"\n # set up\n html_snippet = \"\"\"\n Title ABC
\n one\n \n two\n \n three\n \n four\n \n \"\"\"\n e = ResponseEvent(Spider(), url='xxx', response_str=html_snippet)\n ex = XPathLinkExtractor('//b/a')\n\n # test manual invocation\n s = Spider()\n inj = ExtractAndInjectAction(s, ex)\n inj.perform_action(e)\n self.assertEqual(s.url_queue, ['xxx#2', 'xxx#4'])\n\n # test event bus invocation\n s = Spider()\n inj = ExtractAndInjectAction(s, ex)\n s.append_on_response(inj, r'xxx')\n s.bus.fire(e)\n self.assertEqual(s.url_queue, ['xxx#2', 'xxx#4'])\n\n # test facet registration\n s = Spider()\n s.append_link_extr(ex)\n s.bus.fire(e)\n self.assertEqual(s.url_queue, ['xxx#2', 'xxx#4'])\n\n # test xpath registration\n s = Spider()\n s.append_link_extr_xpath('//b/a')\n s.bus.fire(e)\n self.assertEqual(s.url_queue, ['xxx#2', 'xxx#4'])\n\n # test re registration\n s = Spider()\n s.append_link_extr_re(r'.*#[2|4].*')\n s.bus.fire(e)\n self.assertEqual(s.url_queue, ['xxx#2', 'xxx#4'])\n\n # test follow_all flag\n s = Spider(follow_all=True)\n s.bus.fire(e)\n self.assertEqual(s.url_queue, ['xxx#1', 'xxx#2', 'xxx#3', 'xxx#4'])\n\n\nclass ProcessPipelineAction_TestCase(unittest.TestCase):\n\n def test_extractorWrapperAction(self):\n warp_mock = WARP_Mock()\n\n # extractor\n exProbe = DataProbe(caching=False)\n exWrapA = spider.ProcessPipelineAction(Spider(), warp_mock, exProbe)\n\n # event & subscription\n exReqE = ExtractionRequestEvent(Spider(), WARP_Mock.FORMATTED_ANCHORS_URL)\n exReqS = ExtractionRequestSubscription(r'.*')\n\n bus = EventBus()\n bus.register(exReqS, exWrapA)\n spec = {\n ExtractionRequestEvent : [(exReqS, exWrapA)]\n }\n bus.fire(exReqE)\n self.assertEqual(exProbe.data, warp_mock.get(WARP_Mock.FORMATTED_ANCHORS_URL))\n\n\n\n# Helper Functions\n\nclass GenerateUrlRange_TestCase(unittest.TestCase):\n\n def test_generate(self):\n url_base = 'http://www.google.com'\n query_dict = {'q': [1,2,3]}\n urls = spider.generate_url_range(url_base, query_dict)\n spec = ['http://www.google.com?q=1',\n 'http://www.google.com?q=2',\n 'http://www.google.com?q=3']\n self.assertEqual(spec, urls)\n\n\n\nif __name__ == '__main__':\n unittest.main()","sub_path":"spider/spider_tests.py","file_name":"spider_tests.py","file_ext":"py","file_size_in_byte":13921,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"414205350","text":"#! /bin/env python3\n\n\"\"\"\n# mylog.py - mylog(bag,...) & myerr(bag, ....) functions\n\"\"\"\n\nimport os\nos.environ[\"PYTHONDONTWRITEBYTECODE\"] = \"1\"\nos.environ[\"PYTHONUNBUFFERED\"] = \"1\"\n# --------------------------------------\nimport sys\nif sys.version_info > (3,3):\n import importlib\n# --------------------------------------\nimport ipython_debug\nif sys.version_info > (3,3):\n importlib.reload(ipython_debug)\nelse:\n reload(ipython_debug)\nfrom ipython_debug import *\n# --------------------------------------\nimport mybag\nif sys.version_info > (3,3):\n importlib.reload(mybag)\nelse:\n reload(mybag)\nfrom mybag import *\n# --------------------------------------\n\n# --------------------------------------------------------------\ndef mylog(bag, message='', verbose=True, mask_log=True):\n \"\"\"\n # optionally prepends prefix to (all) lines of the message \n # and prints it out\n # options:\n # verbose (True of False) - if set to false, will not log\n # mask_log (True or False) - flag to mask (prepend) lines.\n # note: default value of the prefix_string 'mask_log'\n # can be changed by defining bag.mask_log_str\n \"\"\"\n if not verbose:\n return\n mask_log_str = ''\n if mask_log:\n if test_avail(bag, \"mask_log_str\"):\n mask_log_str = bag.mask_log_str\n else:\n mask_log_str = 'mask_log'\n if len(mask_log_str):\n mask_log_str = mask_log_str + \" \"\n mystr = str(message)\n mylist = mystr.split(\"\\n\")\n output = \"\"\n for ss in mylist:\n output += mask_log_str + ss + \"\\n\"\n print(output.rstrip())\n\n# ---------------------------------------------------------------\ndef myerr(bag, message):\n \"\"\"\n # prints error message without masking it\n \"\"\"\n mylog(bag, message, mask_log=False)\n\n","sub_path":"se_crawler_2016/py_lib/mylog.py","file_name":"mylog.py","file_ext":"py","file_size_in_byte":1807,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"268058556","text":"import joblib\nimport pandas as pd, numpy as np\nfrom sqlalchemy import create_engine, desc\nfrom sklearn import preprocessing\nfrom sklearn.preprocessing import MinMaxScaler\n\n# def get_score(user_input):\n# #Coefficient based on user survey\n# #[Age of flat: 0.351351351, orchard_distance: 0.027027027, hawker_distance: 0.054054054, mall_distance: 0, mrt_distance: 0.567567568]\n# recommend_score = 0.351351351*(99 - pgDF.iloc[i]['RemainingLease']) + 1/(0.027027027*orchard_distance) + 1/(0.054054054*hawker_distance)+ 1/(0.567567568*mrt_distance)\n\ndef recommender_system(df_user_input):\n #Connect to database\n engine = create_engine(\"sqlite:///HDBResaleWeb/resaleproject.db\")\n\n #Query database\n query = \"SELECT * FROM prop_guru_table\"\n\n #SQL to pandas df\n df = pd.read_sql_query(query, engine)\n\n #Load MinMaxScaler used during scoring of all propguru listings\n scaler_filename = 'HDBResaleWeb/hdb_recommender_scaler.joblib'\n scaler = joblib.load(scaler_filename)\n\n df_user_input[['scaled_rem_lease', 'scaled_orchard_distance', 'scaled_hawker_distance', 'scaled_mall_distance', 'scaled_mrt_distance']] = scaler.transform(df_user_input[['remaining_lease', 'orchard_distance', 'hawker_distance', 'mall_distance', 'mrt_distance']])\n df_user_input[['scaled_orchard_distance', 'scaled_hawker_distance', 'scaled_mall_distance', 'scaled_mrt_distance']] = 1.0 - df_user_input[['scaled_orchard_distance', 'scaled_hawker_distance', 'scaled_mall_distance', 'scaled_mrt_distance']]\n\n df_user_input = df_user_input.assign(recommend_score = 0.2342342342*df_user_input.scaled_rem_lease + 0.1261261261*df_user_input.scaled_orchard_distance + 0.1846846847*df_user_input.scaled_hawker_distance + 0.1657657658*df_user_input.scaled_mall_distance + 0.2891891892*df_user_input.scaled_mrt_distance)\n\n\n #Best match - Most similar to user search (Similar / Better scoring than user search)\n ###Outside the zone - surprise factor ###\n #Filter based on user Input (hard filter)\n filter_postal_district = (df[\"postal_district\"] != df_user_input['postal_district'][0])\n filter_flat_type = (df[\"flat_type\"] == df_user_input['flat_type'][0])\n filter_score = (df[\"recommend_score\"] > df_user_input['recommend_score'][0])\n filter_maxprice = (df[\"resale_price\"] < df_user_input['listing_price'][0] + 26000)\n filter_remaininglease = (df[\"remaining_lease\"] > df_user_input['remaining_lease'][0] - 5)\n\n df_best_match_1 = df[filter_postal_district & filter_flat_type & filter_score & filter_maxprice & filter_remaininglease].copy()\n\n #Drop listing with same listing name and resale price\n df_best_match_1.drop_duplicates(subset=['listing_name','resale_price'], inplace=True, keep='last')\n df_best_match_1 = df_best_match_1.sort_values('recommend_score', ascending=False).head(3)\n #If listing than than 3\n if len(df_best_match_1) < 3: \n df_best_match_2 = df[filter_flat_type & filter_score & filter_maxprice & filter_remaininglease].copy()\n #Drop listing with same listing name and resale price\n df_best_match_2.drop_duplicates(subset=['listing_name','resale_price'], inplace=True, keep='last')\n df_best_match_2 = df_best_match_2.sort_values('recommend_score', ascending=False).head(3 - len(df_best_match_1))\n df_best_match = pd.concat([df_best_match_1, df_best_match_2])\n else:\n df_best_match = df_best_match_1\n \n\n #Similar Size, Better Price (Similar)\n ###Within the same zone - Size +10, Price < user input###\n #Filter based on user Input (hard filter)\n filter_postal_district = (df[\"postal_district\"] == df_user_input['postal_district'][0])\n filter_floor_area_sqm = (df[\"floor_area_sqm\"].between(df_user_input['floor_area_sqm'][0] * 0.9, df_user_input['floor_area_sqm'][0] * 1.1))\n filter_maxprice = (df[\"resale_price\"] < df_user_input['listing_price'][0])\n \n df_cheaper_price_1 = df[filter_postal_district & filter_floor_area_sqm & filter_score & filter_maxprice].copy()\n #Drop listing with same listing name and resale price\n df_cheaper_price_1.drop_duplicates(subset=['listing_name','resale_price'], inplace=True, keep='last')\n df_cheaper_price_1 = df_cheaper_price_1.sort_values('resale_price', ascending=False).head(3)\n #If listing than than 3\n if len(df_cheaper_price_1) < 3: \n df_cheaper_price_2 = df[filter_floor_area_sqm & filter_score & filter_maxprice].copy()\n #Drop listing with same listing name and resale price\n df_cheaper_price_2.drop_duplicates(subset=['listing_name','resale_price'], inplace=True, keep='last')\n df_cheaper_price_2 = df_cheaper_price_2.sort_values('resale_price', ascending=False).head(3 - len(df_cheaper_price_1))\n df_cheaper_price = pd.concat([df_cheaper_price_1, df_cheaper_price_2])\n else:\n df_cheaper_price = df_cheaper_price_1\n\n\n #Similar Price, Bigger House (Similar)\n ###Within the same zone - Size > user input, Price +- 26000###\n #Filter based on user Input (hard filter)\n filter_postal_district = (df[\"postal_district\"] == df_user_input['postal_district'][0])\n filter_floor_area_sqm = (df[\"floor_area_sqm\"] >= df_user_input['floor_area_sqm'][0])\n filter_maxprice = (df[\"resale_price\"].between(df_user_input['listing_price'][0] - 26000, df_user_input['listing_price'][0] + 26000))\n \n df_bigger_house_1 = df[filter_postal_district & filter_score & filter_floor_area_sqm & filter_maxprice].copy()\n #Drop listing with same listing name and resale price\n df_bigger_house_1.drop_duplicates(subset=['listing_name','resale_price'], inplace=True, keep='last')\n df_bigger_house_1 = df_bigger_house_1.sort_values('floor_area_sqm', ascending=False).head(3)\n #If listing than than 3\n if len(df_bigger_house_1) < 3: \n df_bigger_house_2 = df[filter_floor_area_sqm & filter_score & filter_maxprice].copy()\n df_bigger_house_2 = df_bigger_house_2.sort_values('floor_area_sqm', ascending=False).head(3 - len(df_bigger_house_1))\n df_bigger_house = pd.concat([df_bigger_house_1, df_bigger_house_2])\n else:\n df_bigger_house = df_bigger_house_1\n\n return df_best_match, df_cheaper_price, df_bigger_house","sub_path":"HDBResaleWeb/recommendation.py","file_name":"recommendation.py","file_ext":"py","file_size_in_byte":6183,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"378520367","text":"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.\n# Copyright (c) 2018-2019 NVIDIA CORPORATION. All rights reserved.\n\"\"\"\nThis file contains specific functions for computing losses on the RPN\nfile\n\"\"\"\nimport torch\nfrom torch.nn import functional as F\nfrom torch.nn.utils.rnn import pad_sequence\nfrom .utils import concat_box_prediction_layers\n\nfrom ..balanced_positive_negative_sampler import BalancedPositiveNegativeSampler\nfrom ..utils import cat\n\nfrom maskrcnn_benchmark.layers import smooth_l1_loss\nfrom maskrcnn_benchmark.modeling.matcher import Matcher\nfrom maskrcnn_benchmark.structures.boxlist_ops import boxlist_iou, boxlist_iou_batched\nfrom maskrcnn_benchmark.structures.boxlist_ops import cat_boxlist\n\n\nclass RPNLossComputation(object):\n \"\"\"\n This class computes the RPN loss.\n \"\"\"\n\n def __init__(self, proposal_matcher, fg_bg_sampler, box_coder,\n generate_labels_func):\n \"\"\"\n Arguments:\n proposal_matcher (Matcher)\n fg_bg_sampler (BalancedPositiveNegativeSampler)\n box_coder (BoxCoder)\n \"\"\"\n # self.target_preparator = target_preparator\n self.proposal_matcher = proposal_matcher\n self.fg_bg_sampler = fg_bg_sampler\n self.box_coder = box_coder\n self.copied_fields = []\n self.generate_labels_func = generate_labels_func\n self.discard_cases = ['not_visibility', 'between_thresholds']\n\n def match_targets_to_anchors(self, anchor, target, copied_fields=[]):\n match_quality_matrix = boxlist_iou(target, anchor)\n matched_idxs = self.proposal_matcher(match_quality_matrix)\n # RPN doesn't need any fields from target\n # for creating the labels, so clear them all\n target = target.copy_with_fields(copied_fields)\n # get the targets corresponding GT for each anchor\n # NB: need to clamp the indices because we can have a single\n # GT in the image, and matched_idxs can be -2, which goes\n # out of bounds\n\n matched_targets = target[matched_idxs.clamp(min=0)]\n matched_targets.add_field(\"matched_idxs\", matched_idxs)\n return matched_targets\n\n def match_targets_to_anchors_batched(self, anchor, target, copied_fields=[]):\n match_quality_matrix = boxlist_iou_batched(target, anchor)\n matched_idxs = self.proposal_matcher(match_quality_matrix, batched=1)\n # RPN doesn't need any fields from target\n # for creating the labels, so clear them all\n # target = target.copy_with_fields(copied_fields)\n # get the targets corresponding GT for each anchor\n # NB: need to clamp the indices because we can have a single\n # GT in the image, and matched_idxs can be -2, which goes\n # out of bounds\n return matched_idxs\n\n def prepare_targets(self, anchors, targets):\n labels = []\n regression_targets = []\n for anchors_per_image, targets_per_image in zip(anchors, targets):\n matched_targets = self.match_targets_to_anchors(\n anchors_per_image, targets_per_image, self.copied_fields\n )\n\n matched_idxs = matched_targets.get_field(\"matched_idxs\")\n labels_per_image = self.generate_labels_func(matched_targets)\n labels_per_image = labels_per_image.to(dtype=torch.float32)\n\n # Background (negative examples)\n bg_indices = matched_idxs == Matcher.BELOW_LOW_THRESHOLD\n labels_per_image.masked_fill_(bg_indices, 0)\n\n # discard anchors that go out of the boundaries of the image\n if \"not_visibility\" in self.discard_cases:\n labels_per_image.masked_fill_(~anchors_per_image.get_field(\"visibility\"), -1)\n\n # discard indices that are between thresholds\n if \"between_thresholds\" in self.discard_cases:\n inds_to_discard = matched_idxs == Matcher.BETWEEN_THRESHOLDS\n labels_per_image.masked_fill_(inds_to_discard, -1)\n\n # compute regression targets\n regression_targets_per_image = self.box_coder.encode(\n matched_targets.bbox, anchors_per_image.bbox\n )\n\n labels.append(labels_per_image)\n regression_targets.append(regression_targets_per_image)\n\n return labels, regression_targets\n\n def prepare_targets_batched(self, anchors, targets, anchors_visibility):\n\n matched_idxs = self.match_targets_to_anchors_batched(anchors, targets)\n labels = generate_rpn_labels2(matched_idxs) \n labels = labels.to(dtype=torch.float32)\n\n bg_indices = matched_idxs == Matcher.BELOW_LOW_THRESHOLD\n labels.masked_fill_(bg_indices, 0)\n\n # discard anchors that go out of the boundaries of the image\n if \"not_visibility\" in self.discard_cases:\n labels.masked_fill_(anchors_visibility==0, -1)\n\n # discard indices that are between thresholds\n if \"between_thresholds\" in self.discard_cases:\n inds_to_discard = matched_idxs == Matcher.BETWEEN_THRESHOLDS\n labels.masked_fill_(inds_to_discard, -1)\n\n img_idx = torch.arange(anchors.size(0), device = anchors.device)[:, None]\n matched_targets = targets[img_idx, matched_idxs.clamp(min=0)]\n\n # compute regression targets\n regression_targets = self.box_coder.encode(\n matched_targets.view(-1,4), anchors.view(-1,4)\n )\n return labels.view(-1), regression_targets\n\n def __call__(self, anchors, objectness, box_regression, targets):\n \"\"\"\n Arguments:\n anchors (list[BoxList])\n objectness (list[Tensor])\n box_regression (list[Tensor])\n targets (list[BoxList])\n\n Returns:\n objectness_loss (Tensor)\n box_loss (Tensor\n \"\"\"\n anchors_cat = anchors[0]\n num_images = len(anchors[2])\n N = anchors_cat.size(0)\n anchors_visibility = anchors[1]\n device = anchors_cat.device\n targets_cat = pad_sequence([target.bbox for target in targets], batch_first=True, padding_value=-1)\n labels, regression_targets = self.prepare_targets_batched(anchors_cat, targets_cat, anchors_visibility)\n sampled_pos_inds, sampled_neg_inds = self.fg_bg_sampler(labels.view(N,-1), is_rpn=1)\n if num_images == 1:\n # sampled pos inds only has 1 element if num_images is 1, so avoid torch.cat\n sampled_pos_inds = torch.nonzero(sampled_pos_inds[0]).squeeze(1)\n sampled_neg_inds = torch.nonzero(sampled_neg_inds[0]).squeeze(1)\n sampled_inds = torch.cat([sampled_pos_inds, sampled_neg_inds], dim=0)\n\n objectness, box_regression = \\\n concat_box_prediction_layers(objectness, box_regression)\n\n objectness = objectness.squeeze()\n\n box_loss = smooth_l1_loss(\n box_regression.index_select(0, sampled_pos_inds),\n regression_targets.index_select(0, sampled_pos_inds),\n beta=1.0 / 9,\n size_average=False,\n ) / (sampled_inds.numel())\n\n objectness_loss = F.binary_cross_entropy_with_logits(\n objectness.index_select(0, sampled_inds), labels.index_select(0, sampled_inds)\n )\n return objectness_loss, box_loss\n\n# This function should be overwritten in RetinaNet\ndef generate_rpn_labels(matched_targets):\n matched_idxs = matched_targets.get_field(\"matched_idxs\")\n labels_per_image = matched_idxs >= 0\n return labels_per_image\n\ndef generate_rpn_labels2(matched_idxs):\n # matched_idxs = matched_targets.get_field(\"matched_idxs\")\n labels = matched_idxs >= 0\n return labels\n\ndef make_rpn_loss_evaluator(cfg, box_coder):\n matcher = Matcher(\n cfg.MODEL.RPN.FG_IOU_THRESHOLD,\n cfg.MODEL.RPN.BG_IOU_THRESHOLD,\n allow_low_quality_matches=True,\n )\n\n fg_bg_sampler = BalancedPositiveNegativeSampler(\n cfg.MODEL.RPN.BATCH_SIZE_PER_IMAGE, cfg.MODEL.RPN.POSITIVE_FRACTION\n )\n\n loss_evaluator = RPNLossComputation(\n matcher,\n fg_bg_sampler,\n box_coder,\n generate_rpn_labels\n )\n return loss_evaluator\n","sub_path":"DellEMC/benchmarks/maskrcnn/implementation/pytorch/maskrcnn_benchmark/modeling/rpn/loss.py","file_name":"loss.py","file_ext":"py","file_size_in_byte":8181,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"182933449","text":"\"\"\"Import/export any formats supported by meshio.\"\"\"\n\nimport meshio\nimport numpy as np\nimport skfem\n\n\nMESH_TYPE_MAPPING = {\n 'tetra': skfem.MeshTet1,\n 'tetra10': skfem.MeshTet2,\n 'hexahedron': skfem.MeshHex1,\n 'hexahedron27': skfem.MeshHex2,\n 'wedge': skfem.MeshWedge1,\n 'triangle': skfem.MeshTri1,\n 'triangle6': skfem.MeshTri2,\n 'quad': skfem.MeshQuad1,\n 'quad9': skfem.MeshQuad2,\n 'line': skfem.MeshLine1,\n}\n\nBOUNDARY_TYPE_MAPPING = {\n 'line': 'vertex',\n 'triangle': 'line',\n 'quad': 'line',\n 'tetra': 'triangle',\n 'hexahedron': 'quad',\n 'tetra10': 'triangle', # TODO support quadratic facets\n 'triangle6': 'line', # TODO\n 'quad9': 'line', # TODO\n 'hexahedron27': 'quad', # TODO\n}\n\nTYPE_MESH_MAPPING = {MESH_TYPE_MAPPING[k]: k\n for k in dict(reversed(list(MESH_TYPE_MAPPING.items())))}\n\n\nHEX_MAPPING = [0, 3, 6, 2, 1, 5, 7, 4,\n 10, 16, 14, 9, 12, 18, 17, 11, 8, 15, 19, 13,\n 20, 25, 22, 23, 21, 24,\n 26]\nINV_HEX_MAPPING = [HEX_MAPPING.index(i)\n for i in range(len(HEX_MAPPING))]\n\n\ndef from_meshio(m,\n out=None,\n int_data_to_sets=False,\n force_meshio_type=None):\n\n cells = m.cells_dict\n meshio_type = None\n\n if force_meshio_type is None:\n # detect 3D\n for k in cells:\n if k in {'tetra',\n 'hexahedron',\n 'tetra10',\n 'hexahedron27',\n 'wedge'}:\n meshio_type = k\n break\n\n if meshio_type is None:\n # detect 2D\n for k in cells:\n if k in {'triangle',\n 'quad',\n 'triangle6',\n 'quad9'}:\n meshio_type = k\n break\n\n if meshio_type is None:\n # detect 1D\n for k in cells:\n if k == 'line':\n meshio_type = k\n break\n else:\n meshio_type = force_meshio_type\n\n if meshio_type is None:\n raise NotImplementedError(\"Mesh type(s) not supported \"\n \"in import: {}.\".format(cells.keys()))\n\n mesh_type = MESH_TYPE_MAPPING[meshio_type]\n\n # create p and t\n p = np.ascontiguousarray(mesh_type.strip_extra_coordinates(m.points).T)\n t = np.ascontiguousarray(cells[meshio_type].T)\n\n # reorder t if needed\n if meshio_type == 'hexahedron':\n t = t[INV_HEX_MAPPING[:8]]\n elif meshio_type == 'hexahedron27':\n t = t[INV_HEX_MAPPING]\n\n if int_data_to_sets:\n m.int_data_to_sets()\n\n subdomains = {}\n boundaries = {}\n\n # parse any subdomains from cell_sets\n if m.cell_sets:\n subdomains = {k: v[meshio_type]\n for k, v in m.cell_sets_dict.items()\n if meshio_type in v}\n\n # create temporary mesh for matching boundary elements\n mtmp = mesh_type(p, t)\n bnd_type = BOUNDARY_TYPE_MAPPING[meshio_type]\n\n # parse boundaries from cell_sets\n if m.cell_sets and bnd_type in m.cells_dict:\n facets = {\n k: [tuple(f) for f in np.sort(m.cells_dict[bnd_type][v[bnd_type]])]\n for k, v in m.cell_sets_dict.items()\n if bnd_type in v and k.split(\":\")[0] != \"gmsh\"\n }\n boundaries = {k: np.array([i for i, f in\n enumerate(map(tuple, mtmp.facets.T))\n if f in v])\n for k, v in facets.items()}\n\n # MSH 2.2 tag parsing\n if m.cell_data and m.field_data:\n try:\n elements_tag = m.cell_data_dict['gmsh:physical'][meshio_type]\n subdomains = {}\n tags = np.unique(elements_tag)\n\n def find_tagname(tag):\n for key in m.field_data:\n if m.field_data[key][0] == tag:\n return key\n return None\n\n for tag in tags:\n t_set = np.nonzero(tag == elements_tag)[0]\n subdomains[find_tagname(tag)] = t_set\n\n # find tagged boundaries\n if bnd_type in m.cell_data_dict['gmsh:physical']:\n facets = m.cells_dict[bnd_type]\n facets_tag = m.cell_data_dict['gmsh:physical'][bnd_type]\n\n # put meshio facets to dict\n dic = {tuple(np.sort(facets[i])): facets_tag[i]\n for i in range(facets.shape[0])}\n\n # get index of corresponding Mesh.facets for each meshio\n # facet found in the dict\n index = np.array([[dic[tuple(np.sort(mtmp.facets[:, i]))], i]\n for i in mtmp.boundary_facets()\n if tuple(np.sort(mtmp.facets[:, i])) in dic])\n\n # read meshio tag numbers and names\n tags = index[:, 0]\n boundaries = {}\n for tag in np.unique(tags):\n tagindex = np.nonzero(tags == tag)[0]\n boundaries[find_tagname(tag)] = index[tagindex, 1]\n\n except Exception:\n pass\n\n # attempt parsing skfem tags\n if m.cell_data:\n _boundaries, _subdomains = mtmp._decode_cell_data(m.cell_data)\n boundaries.update(_boundaries)\n subdomains.update(_subdomains)\n\n # export mesh data\n if out is not None and isinstance(out, list):\n for i, field in enumerate(out):\n out[i] = getattr(m, field)\n\n return mesh_type(\n p,\n t,\n None if len(boundaries) == 0 else boundaries,\n None if len(subdomains) == 0 else subdomains,\n )\n\n\ndef from_file(filename, out, **kwargs):\n return from_meshio(meshio.read(filename), out, **kwargs)\n\n\ndef to_meshio(mesh,\n point_data=None,\n cell_data=None,\n encode_cell_data=True,\n encode_point_data=False):\n\n t = mesh.dofs.element_dofs.copy()\n if isinstance(mesh, skfem.MeshHex2):\n t = t[HEX_MAPPING]\n elif isinstance(mesh, skfem.MeshHex):\n t = t[HEX_MAPPING[:8]]\n\n mtype = TYPE_MESH_MAPPING[type(mesh)]\n cells = {mtype: t.T}\n\n if encode_cell_data:\n if cell_data is None:\n cell_data = {}\n cell_data.update(mesh._encode_cell_data())\n\n if encode_point_data:\n if point_data is None:\n point_data = {}\n point_data.update(mesh._encode_point_data())\n\n mio = meshio.Mesh(\n mesh.p.T,\n cells,\n point_data=point_data,\n cell_data=cell_data,\n )\n\n return mio\n\n\ndef to_file(mesh,\n filename,\n point_data=None,\n cell_data=None,\n encode_cell_data=True,\n encode_point_data=False,\n **kwargs):\n\n meshio.write(filename,\n to_meshio(mesh,\n point_data,\n cell_data,\n encode_cell_data,\n encode_point_data),\n **kwargs)\n","sub_path":"skfem/io/meshio.py","file_name":"meshio.py","file_ext":"py","file_size_in_byte":7062,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"652722866","text":"\"\"\"\nNBER Feenstra Special Concordances\n==================================\n\nThis module contains special concordances used in NBER Feenstra Analysis\n\nSTATUS: IN-WORK\n\nNotes\n------\n1. ISO3C \t=> \tISO 3166-1-alpha3\n\"\"\"\n\n# ------------------------------------- #\n# - Manually Constructed Concordances - #\n# ------------------------------------- #\n\n# - Exporters to ISO3C - #\n\nCountryNameToISO3C = {\t'Afghanistan' \t: 'AFG',\n\t\t\t\t\t\t'Afr.Other NS' \t: '.',\n\t\t\t\t\t\t'Africa N.NES'\t: '.',\n\t\t\t\t\t\t'Albania' \t\t: 'ALB',\n\t\t\t\t\t\t\n\t\t\t\t\t\t# - Working Here - #\n\n\t\t\t\t\t\t# 'Algeria' \t\t: ''\n\t\t\t\t\t\t# 'Angola',\n\t\t\t\t\t\t# 'Areas NES',\n\t\t\t\t\t\t# 'Argentina',\n\t\t\t\t\t\t# 'Armenia',\n\t\t\t\t\t\t# 'Asia NES',\n\t\t\t\t\t\t# 'Asia West NS',\n\t\t\t\t\t\t# 'Australia',\n\t\t\t\t\t\t# 'Austria',\n\t\t\t\t\t\t# 'Azerbaijan',\n\t\t\t\t\t\t# 'Bahamas',\n\t\t\t\t\t\t# 'Bahrain',\n\t\t\t\t\t\t# 'Bangladesh',\n\t\t\t\t\t\t# 'Barbados',\n\t\t\t\t\t\t# 'Belarus',\n\t\t\t\t\t\t# 'Belgium-Lux',\n\t\t\t\t\t\t# 'Belize',\n\t\t\t\t\t\t# 'Benin',\n\t\t\t\t\t\t# 'Bermuda',\n\t\t\t\t\t\t# 'Bolivia',\n\t\t\t\t\t\t# 'Bosnia Herzg',\n\t\t\t\t\t\t# 'Br.Antr.Terr',\n\t\t\t\t\t\t# 'Brazil',\n\t\t\t\t\t\t# 'Bulgaria',\n\t\t\t\t\t\t# 'Burkina Faso',\n\t\t\t\t\t\t# 'Burundi',\n\t\t\t\t\t\t# 'CACM NES',\n\t\t\t\t\t\t# 'Cambodia',\n\t\t\t\t\t\t# 'Cameroon',\n\t\t\t\t\t\t# 'Canada',\n\t\t\t\t\t\t# 'Carib. NES',\n\t\t\t\t\t\t# 'Cent.Afr.Rep',\n\t\t\t\t\t\t# 'Chad',\n\t\t\t\t\t\t# 'Chile',\n\t\t\t\t\t\t# 'China',\n\t\t\t\t\t\t# 'China FTZ',\n\t\t\t\t\t\t# 'China HK SAR',\n\t\t\t\t\t\t# 'China MC SAR',\n\t\t\t\t\t\t# 'China SC',\n\t\t\t\t\t\t# 'Colombia',\n\t\t\t\t\t\t# 'Congo',\n\t\t\t\t\t\t# 'Costa Rica',\n\t\t\t\t\t\t# 'Cote Divoire',\n\t\t\t\t\t\t# 'Croatia',\n\t\t\t\t\t\t# 'Cuba',\n\t\t\t\t\t\t# 'Cyprus',\n\t\t\t\t\t\t# 'Czech Rep',\n\t\t\t\t\t\t# 'Czechoslovak',\n\t\t\t\t\t\t# 'Dem.Rp.Congo',\n\t\t\t\t\t\t# 'Denmark',\n\t\t\t\t\t\t# 'Djibouti',\n\t\t\t\t\t\t# 'Dominican Rp',\n\t\t\t\t\t\t# 'E Europe NES',\n\t\t\t\t\t\t# 'EEC NES',\n\t\t\t\t\t\t# 'Ecuador',\n\t\t\t\t\t\t# 'Egypt',\n\t\t\t\t\t\t# 'El Salvador',\n\t\t\t\t\t\t# 'Eq.Guinea',\n\t\t\t\t\t\t# 'Estonia',\n\t\t\t\t\t\t# 'Ethiopia',\n\t\t\t\t\t\t# 'Eur. EFTA NS',\n\t\t\t\t\t\t# 'Eur.Other NE',\n\t\t\t\t\t\t# 'Falkland Is',\n\t\t\t\t\t\t# 'Fiji',\n\t\t\t\t\t\t# 'Finland',\n\t\t\t\t\t\t# 'Fm German DR',\n\t\t\t\t\t\t# 'Fm German FR',\n\t\t\t\t\t\t# 'Fm USSR',\n\t\t\t\t\t\t# 'Fm Yemen AR',\n\t\t\t\t\t\t# 'Fm Yemen Ar',\n\t\t\t\t\t\t# 'Fm Yemen Dm',\n\t\t\t\t\t\t# 'Fm Yugoslav',\n\t\t\t\t\t\t# 'Fr Ind O',\n\t\t\t\t\t\t# 'Fr.Guiana',\n\t\t\t\t\t\t# 'France,Monac',\n\t\t\t\t\t\t# 'Gabon',\n\t\t\t\t\t\t# 'Gambia',\n\t\t\t\t\t\t# 'Georgia',\n\t\t\t\t\t\t# 'Germany',\n\t\t\t\t\t\t# 'Ghana',\n\t\t\t\t\t\t# 'Gibraltar',\n\t\t\t\t\t\t# 'Greece',\n\t\t\t\t\t\t# 'Greenland',\n\t\t\t\t\t\t# 'Guadeloupe',\n\t\t\t\t\t\t# 'Guatemala',\n\t\t\t\t\t\t# 'Guinea',\n\t\t\t\t\t\t# 'GuineaBissau',\n\t\t\t\t\t\t# 'Guyana',\n\t\t\t\t\t\t# 'Haiti',\n\t\t\t\t\t\t# 'Honduras',\n\t\t\t\t\t\t# 'Hungary',\n\t\t\t\t\t\t# 'Iceland',\n\t\t\t\t\t\t# 'India',\n\t\t\t\t\t\t# 'Indonesia',\n\t\t\t\t\t\t# 'Int Org',\n\t\t\t\t\t\t# 'Iran',\n\t\t\t\t\t\t# 'Iraq',\n\t\t\t\t\t\t# 'Ireland',\n\t\t\t\t\t\t# 'Israel',\n\t\t\t\t\t\t# 'Italy',\n\t\t\t\t\t\t# 'Jamaica',\n\t\t\t\t\t\t# 'Japan',\n\t\t\t\t\t\t# 'Jordan',\n\t\t\t\t\t\t# 'Kazakhstan',\n\t\t\t\t\t\t# 'Kenya',\n\t\t\t\t\t\t# 'Kiribati',\n\t\t\t\t\t\t# 'Korea D P Rp',\n\t\t\t\t\t\t# 'Korea Rep.',\n\t\t\t\t\t\t# 'Kuwait',\n\t\t\t\t\t\t# 'Kyrgyzstan',\n\t\t\t\t\t\t# 'LAIA NES',\n\t\t\t\t\t\t# 'Lao P.Dem.R',\n\t\t\t\t\t\t# 'Latvia',\n\t\t\t\t\t\t# 'Lebanon',\n\t\t\t\t\t\t# 'Liberia',\n\t\t\t\t\t\t# 'Libya',\n\t\t\t\t\t\t# 'Lithuania',\n\t\t\t\t\t\t# 'Madagascar',\n\t\t\t\t\t\t# 'Malawi',\n\t\t\t\t\t\t# 'Malaysia',\n\t\t\t\t\t\t# 'Mali',\n\t\t\t\t\t\t# 'Malta',\n\t\t\t\t\t\t# 'Mauritania',\n\t\t\t\t\t\t# 'Mauritius',\n\t\t\t\t\t\t# 'Mexico',\n\t\t\t\t\t\t# 'Mongolia',\n\t\t\t\t\t\t# 'Morocco',\n\t\t\t\t\t\t# 'Mozambique',\n\t\t\t\t\t\t# 'Myanmar',\n\t\t\t\t\t\t# 'Nepal',\n\t\t\t\t\t\t# 'Neth.Ant.Aru',\n\t\t\t\t\t\t# 'Netherlands',\n\t\t\t\t\t\t# 'Neutral Zone',\n\t\t\t\t\t\t# 'New Calednia',\n\t\t\t\t\t\t# 'New Zealand',\n\t\t\t\t\t\t# 'Nicaragua',\n\t\t\t\t\t\t# 'Niger',\n\t\t\t\t\t\t# 'Nigeria',\n\t\t\t\t\t\t# 'Norway',\n\t\t\t\t\t\t# 'Occ.Pal.Terr',\n\t\t\t\t\t\t# 'Oman',\n\t\t\t\t\t\t# 'Oth.Oceania',\n\t\t\t\t\t\t# 'Pakistan',\n\t\t\t\t\t\t# 'Panama',\n\t\t\t\t\t\t# 'Papua N.Guin',\n\t\t\t\t\t\t# 'Paraguay',\n\t\t\t\t\t\t# 'Peru',\n\t\t\t\t\t\t# 'Philippines',\n\t\t\t\t\t\t# 'Poland',\n\t\t\t\t\t\t# 'Portugal',\n\t\t\t\t\t\t# 'Qatar',\n\t\t\t\t\t\t# 'Rep Moldova',\n\t\t\t\t\t\t# 'Romania',\n\t\t\t\t\t\t# 'Russian Fed',\n\t\t\t\t\t\t# 'Rwanda',\n\t\t\t\t\t\t# 'Samoa',\n\t\t\t\t\t\t# 'Saudi Arabia',\n\t\t\t\t\t\t# 'Senegal',\n\t\t\t\t\t\t# 'Seychelles',\n\t\t\t\t\t\t# 'Sierra Leone',\n\t\t\t\t\t\t# 'Singapore',\n\t\t\t\t\t\t# 'Slovakia',\n\t\t\t\t\t\t# 'Slovenia',\n\t\t\t\t\t\t# 'Somalia',\n\t\t\t\t\t\t# 'South Africa',\n\t\t\t\t\t\t# 'Spain',\n\t\t\t\t\t\t# 'Sri Lanka',\n\t\t\t\t\t\t# 'St.Helena',\n\t\t\t\t\t\t# 'St.Kt-Nev-An',\n\t\t\t\t\t\t# 'St.Pierre Mq',\n\t\t\t\t\t\t# 'Sudan',\n\t\t\t\t\t\t# 'Suriname',\n\t\t\t\t\t\t# 'Sweden',\n\t\t\t\t\t\t# 'Switz.Liecht',\n\t\t\t\t\t\t# 'Syria',\n\t\t\t\t\t\t# 'TFYR Macedna',\n\t\t\t\t\t\t# 'Taiwan',\n\t\t\t\t\t\t# 'Tajikistan',\n\t\t\t\t\t\t# 'Tanzania',\n\t\t\t\t\t\t# 'Thailand',\n\t\t\t\t\t\t# 'Togo',\n\t\t\t\t\t\t# 'Trinidad Tbg',\n\t\t\t\t\t\t# 'Tunisia',\n\t\t\t\t\t\t# 'Turkey',\n\t\t\t\t\t\t# 'Turkmenistan',\n\t\t\t\t\t\t# 'UK',\n\t\t\t\t\t\t# 'US NES',\n\t\t\t\t\t\t# 'USA',\n\t\t\t\t\t\t# 'Uganda',\n\t\t\t\t\t\t# 'Ukraine',\n\t\t\t\t\t\t# 'Untd Arab Em',\n\t\t\t\t\t\t# 'Uruguay',\n\t\t\t\t\t\t# 'Uzbekistan',\n\t\t\t\t\t\t# 'Venezuela',\n\t\t\t\t\t\t# 'Viet Nam',\n\t\t\t\t\t\t# 'World',\n\t\t\t\t\t\t# 'Yemen',\n\t\t\t\t\t\t# 'Yugoslavia',\n\t\t\t\t\t\t# 'Zambia',\n\t\t\t\t\t\t# 'Zimbabwe',\n\t\t\t\t\t}\t\t\n\nCountryCodeToISO3C = {\n\t\t\n\t\t# This needs a unique list of global countrycodes from the dataset - #\n\n\t\t# - Working Here - #\n}\n\n# - Note: The following are Subsets of Above and Can be COMPUTED - #\n\nExporterISO3C = {}\n\n# - Importers to ISO3C - #\n\nImporterToISO3C = {}\n\n# - Country Code Concordances - #\n\necodeToISO3C = {}\n\nicodeToISO3C = {}","sub_path":"pyeconlab/trade/dataset/NBERWTF/concordance.py","file_name":"concordance.py","file_ext":"py","file_size_in_byte":4918,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"351895767","text":"#!/usr/bin/env python\n# coding: utf-8\n\n# In[16]:\n\n\n# !/usr/bin/env python\n# coding: utf-8\n\n# In[78]:\n\n\nimport torch\nimport torchvision\nimport torchvision.transforms as transforms\nfrom torchvision.datasets import ImageFolder\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.optim import lr_scheduler\nimport numpy as np\nfrom torchvision import datasets, models, transforms\nimport matplotlib.pyplot as plt\nimport time\nimport os\nimport copy\n\n\n\n#To determine if your system supports CUDA\nprint(\"==> Check devices..\")\ndevice = 'cuda' if torch.cuda.is_available() else 'cpu'\nprint(\"Current device: \",device)\n\n#Also can print your current GPU id, and the number of GPUs you can use.\nprint(\"Our selected device: \", torch.cuda.current_device())\nprint(torch.cuda.device_count(), \" GPUs is available\")\n\n\n\nprint('==> Preparing dataset..')\n\n\"\"\"1.1\"\"\"\n# The output of torchvision datasets are PILImage images of range [0, 1]\n# We transform them to Tensor type\n# And normalize the data\n# Be sure you do same normalization for your train and test data\n\n#The transform function for train data\n\n\ndata_transforms = {\n 'skewed_training': transforms.Compose([\n transforms.RandomResizedCrop(224),\n transforms.RandomHorizontalFlip(),\n transforms.ToTensor(),\n transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n ]),\n 'validation': transforms.Compose([\n transforms.Resize(256),\n transforms.CenterCrop(224),\n transforms.ToTensor(),\n transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n ]), \n 'evaluation': transforms.Compose([\n transforms.Resize(256),\n transforms.CenterCrop(224),\n transforms.ToTensor(),\n transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n ]),\n}\n\n\n\"\"\"1.2\"\"\" \n\ndata_dir = 'food11re'\nimage_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x),\n data_transforms[x])\n for x in ['skewed_training','validation','evaluation']}\ndataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=4,\n shuffle=True, num_workers=2)\n for x in ['skewed_training','validation','evaluation']}\ndataset_sizes = {x: len(image_datasets[x]) for x in ['skewed_training','validation','evaluation']}\nclass_names = image_datasets['skewed_training'].classes\n\n\nprint('==> Building model..')\n\ndef train_model(model, criterion, optimizer, scheduler, num_epochs=25):\n since = time.time()\n\n best_model_wts = copy.deepcopy(model.state_dict())\n best_acc = 0.0\n loss_values = []\n acc_values = []\n patient = 5\n j = 0\n end = 0\n for epoch in range(num_epochs):\n print('Epoch {}/{}'.format(epoch, num_epochs - 1))\n print('-' * 10)\n\n # Each epoch has a training and validation phase\n for phase in ['skewed_training', 'validation']:\n if phase == 'skewed_training':\n model.train() # Set model to training mode\n else:\n model.eval() # Set model to evaluate mode\n\n running_loss = 0.0\n running_corrects = 0\n\n # Iterate over data.\n for inputs, labels in dataloaders[phase]:\n inputs = inputs.to(device)\n labels = labels.to(device)\n\n # zero the parameter gradients\n optimizer.zero_grad()\n\n # forward\n # track history if only in train\n with torch.set_grad_enabled(phase == 'skewed_training'):\n outputs = model(inputs)\n _, preds = torch.max(outputs, 1)\n loss = criterion(outputs, labels)\n\n # backward + optimize only if in training phase\n if phase == 'skewed_training':\n loss.backward()\n optimizer.step()\n\n # statistics\n running_loss += loss.item() * inputs.size(0)\n running_corrects += torch.sum(preds == labels.data)\n if phase == 'skewed_training':\n scheduler.step()\n\n epoch_loss = running_loss / dataset_sizes[phase]\n epoch_acc = running_corrects.double() / dataset_sizes[phase]\n\n print('{} Loss: {:.4f} Acc: {:.4f}'.format(\n phase, epoch_loss, epoch_acc))\n \n if phase == 'validation':\n loss_values.append(epoch_loss)\n acc_values.append(epoch_acc)\n # deep copy the model\n if epoch_acc > best_acc:\n best_acc = epoch_acc\n best_model_wts = copy.deepcopy(model.state_dict())\n j = 0\n else:\n j += 1\n if j == patient:\n end = 1\n\n print()\n if end == 1:\n break\n plt.figure()\n plt.subplot(1,2,1)\n plt.rcParams[\"figure.figsize\"] = (8, 4)\n plt.xlabel(\"epochs\")\n plt.ylabel(\"loss\")\n plt.title(\"lr=0.001, step_size=7(loss)\")\n plt.plot(np.array(loss_values), 'r')\n plt.subplot(1,2,2)\n plt.rcParams[\"figure.figsize\"] = (8, 4)\n plt.xlabel(\"epochs\")\n plt.ylabel(\"accuracy\")\n plt.title(\"lr=0.001, step_size=7(accuracy)\")\n plt.plot(np.array(acc_values), 'r')\n plt.show()\n time_elapsed = time.time() - since\n print('Training complete in {:.0f}m {:.0f}s'.format(\n time_elapsed // 60, time_elapsed % 60))\n print('Best val Acc: {:4f}'.format(best_acc))\n\n # load best model weights\n model.load_state_dict(best_model_wts)\n return model\n\n\nmodel_ft = models.resnet18(pretrained=True)\n\nnum_ftrs = model_ft.fc.in_features\n# Here the size of each output sample is set to 2.\n# Alternatively, it can be generalized to nn.Linear(num_ftrs, len(class_names)).\nmodel_ft.fc = nn.Linear(num_ftrs, 11)\n\nmodel_ft = model_ft.to(device)\n\ncriterion = nn.CrossEntropyLoss()\n\n# Observe that all parameters are being optimized\noptimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\n\n# Decay LR by a factor of 0.1 every 7 epochs\nexp_lr_scheduler = lr_scheduler.StepLR(optimizer_ft, step_size=7, gamma=0.1)\n\n\nmodel_ft = train_model(model_ft, criterion, optimizer_ft, exp_lr_scheduler,\n num_epochs=25)\n\n\nPATH = 'lab1\\lab1_model.pht'\ntorch.save(model_ft.state_dict(), PATH)\n\n\nclass_correct = list(0. for i in range(11))\nclass_total = list(0. for i in range(11))\ncorrect_top3 = 0.\nwith torch.no_grad():\n for data in dataloaders['evaluation']:\n images, labels = data[0].to(device), data[1].to(device)\n outputs = model_ft(images)\n _, predicted = torch.max(outputs, 1)\n _, predicted_top3 = outputs.topk(3, dim=1, largest=True, sorted=True)\n c = (predicted == labels).squeeze()\n c_top3_0 = (predicted_top3[:,0] == labels).squeeze()\n c_top3_1 = (predicted_top3[:,1] == labels).squeeze()\n c_top3_2 = (predicted_top3[:,2] == labels).squeeze()\n if(labels.size()==torch.Size([4])):\n for i in range(4):\n class_correct[labels[i]] += c[i].item()\n class_total[labels[i]] += 1\n correct_top3 += c_top3_0[i].item()\n correct_top3 += c_top3_1[i].item()\n correct_top3 += c_top3_2[i].item()\n else:\n for i in range(3):\n class_correct[labels[i]] += c[i].item()\n class_total[labels[i]] += 1\n correct_top3 += c_top3_0[i].item()\n correct_top3 += c_top3_1[i].item()\n correct_top3 += c_top3_2[i].item()\n\ntotal_correct = 0.\nfor i in range(11):\n total_correct+=class_correct[i]\n\nprint('Test set: Top1 Accuracy: %d/%d (%2d %%) , Top3 Accuracy: %d/%d (%2d %%)' % (\n total_correct,dataset_sizes['evaluation'], 100 * total_correct / dataset_sizes['evaluation'],\n correct_top3,dataset_sizes['evaluation'], 100 * correct_top3 / dataset_sizes['evaluation']))\n \nfor i in range(11):\n print('class %s : %d/%d %2d %%' % (\n class_names[i],class_correct[i],class_total[i], 100 * class_correct[i] / class_total[i]))\n\n\n# In[ ]:\n\n\n\n\n","sub_path":"lab3/3-1a.py","file_name":"3-1a.py","file_ext":"py","file_size_in_byte":8208,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"544999023","text":"from cs50 import SQL\nfrom flask import Flask, flash, redirect, render_template, request, session\nfrom flask_session import Session\nfrom tempfile import mkdtemp\nfrom werkzeug.exceptions import default_exceptions\n\nfrom helpers import apology, lookup\n\n# Configure application\napp = Flask(__name__)\n\n# Ensure responses aren't cached\nif app.config[\"DEBUG\"]:\n @app.after_request\n def after_request(response):\n response.headers[\"Cache-Control\"] = \"no-cache, no-store, must-revalidate\"\n response.headers[\"Expires\"] = 0\n response.headers[\"Pragma\"] = \"no-cache\"\n return response\n\n# Configure session to use filesystem (instead of signed cookies)\napp.config[\"SESSION_FILE_DIR\"] = mkdtemp()\napp.config[\"SESSION_PERMANENT\"] = False\napp.config[\"SESSION_TYPE\"] = \"filesystem\"\nSession(app)\n\n# Configure CS50 Library to use SQLite database\ndb = SQL(\"sqlite:///signup.db\")\n\n\n@app.route(\"/\", methods=[\"GET\"])\ndef index():\n return render_template(\"index.html\")\n\n\n@app.route(\"/events\", methods=[\"GET\"])\ndef events():\n return render_template(\"events.html\")\n\n\n@app.route(\"/founders\", methods=[\"GET\"])\ndef founders():\n return render_template(\"founders.html\")\n\n\n@app.route(\"/mission\", methods=[\"GET\"])\ndef mission():\n return render_template(\"mission.html\")\n\n\n@app.route(\"/donate\", methods=[\"GET\"])\ndef donate():\n return render_template(\"donate.html\")\n\n\n@app.route(\"/info\", methods=[\"GET\"])\ndef info():\n return render_template(\"info.html\")\n\n\n@app.route(\"/confirmed\", methods=[\"GET\"])\ndef confirmed():\n return render_template(\"confirmed.html\")\n\n\n@app.route(\"/recipe\", methods=[\"GET\", \"POST\"])\ndef recipe():\n \"\"\"Returns recipe list\"\"\"\n if request.method == \"POST\":\n ing = request.form.get(\"ing\")\n if not ing:\n return apology(\"Missing Ingredient!\")\n values = lookup(ing)\n return render_template(\"recipe.html\", values=values)\n\n else:\n return render_template(\"recipe.html\")\n\n\n@app.route(\"/emailregister\", methods=[\"GET\", \"POST\"])\ndef emailregister():\n \"\"\"Register email for user\"\"\"\n if request.method == \"POST\":\n name = request.form.get(\"name\")\n email = request.form.get(\"email\")\n confirmation_email = request.form.get(\"confirmation\")\n if not name:\n return apology(\"Missing Name!\")\n\n if not email:\n return apology(\"Missing Email!\")\n\n if email[(len(email) - 9):] != \"@yale.edu\":\n return apology(\"Please Enter a Yale Email!\")\n\n if not confirmation_email:\n return apology(\"Missing Confirmation Email!\")\n\n if email != confirmation_email:\n return apology(\"Email and Confirmation Email Do Not Match!\")\n\n result = db.execute(\"INSERT INTO email (email, name) VALUES(:email, :name)\",\n email=request.form.get(\"email\"), name=request.form.get(\"name\"))\n if not result:\n # the email already exists in the database\n return apology(\"Please enter a different email as the one entered has already been taken\")\n return redirect(\"/confirmed\")\n\n # User reached route via GET (as by clicking a link or via redirect)\n else:\n return render_template(\"emailregister.html\")\n\n\ndef errorhandler(e):\n \"\"\"Handle error\"\"\"\n return apology(e.name, e.code)\n\n\n# listen for errors\nfor code in default_exceptions:\n app.errorhandler(code)(errorhandler)\n","sub_path":"application.py","file_name":"application.py","file_ext":"py","file_size_in_byte":3402,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"66312482","text":"from datetime import time, date\nfrom time import strftime, gmtime\n\nfrom flask import Flask, render_template, \\\n request, redirect, url_for, session, flash\nfrom classes.user import User\nfrom classes.bucket import Bucket\nfrom classes.item import Item\nfrom classes.app import App\n\napp = Flask(__name__)\napp.secret_key = 'MySecretKey'\nall_items = []\ncurrent_user = None\nbucketApp = App()\n\n\n@app.route('/', methods=['GET'])\ndef index():\n return render_template('index.html')\n\n\n@app.route('/signUp', methods=['POST'])\ndef sign_up():\n \"\"\"\n Signs up user to the app\n \"\"\"\n # Pick form values\n name = request.form['name']\n email = request.form['email']\n password = request.form['password']\n # create user\n global current_user\n current_user = User(email, password, name)\n session['id'] = bucketApp.sign_up(current_user)\n # start session\n if session['id']:\n return redirect(url_for('buckets'))\n else:\n return render_template('index.html', error='Email already exists')\n\n\n@app.route('/signIn', methods=['POST', 'GET'])\ndef sign_in():\n \"\"\"\n Signs in user to their account\n \"\"\"\n if request.method == 'POST':\n # Pick form values\n email = request.form['email']\n password = request.form['password']\n user = User(email, password)\n # start session\n session['id'] = bucketApp.sign_in(user)\n\n if session['id']:\n global current_user\n user = [user for user in bucketApp.all_users\n if user.id == session['id']]\n current_user = user[0]\n\n return redirect(url_for('buckets'))\n return render_template('signIn.html',\n error='Invalid username or password')\n else:\n return render_template('signIn.html')\n\n\n@app.route('/signOut')\ndef sign_out():\n \"\"\"\n Signs out user\n \"\"\"\n session.pop('id', None)\n return redirect(url_for('sign_in'))\n\n\n@app.route('/buckets')\ndef buckets():\n \"\"\" \n Returns list of all buckets \n \"\"\"\n\n if 'id' not in session:\n return redirect(url_for('sign_in'))\n global current_user\n return render_template('buckets.html',\n buckets=current_user.get_buckets())\n\n\n@app.route('/create_bucket', methods=[\"POST\"])\ndef create_bucket():\n \"\"\"\n Creates a new bucket list \n \"\"\"\n\n # Check user is signed in\n if 'id' not in session:\n return redirect(url_for('sign_in'))\n # Pick form values\n bucket_name = request.form['bucket-name']\n description = request.form['description']\n # create bucket\n new_bucket = Bucket(bucket_name, description, session['id'])\n global current_user\n if current_user.create_bucket(new_bucket):\n return redirect(url_for('buckets'))\n flash('Bucket name already exists')\n return redirect(url_for('buckets'))\n\n\n@app.route('/edit_bucket/', methods=['POST'])\ndef edit_bucket(bucket_name):\n \"\"\"\n Edits attributes of a bucket\n :param bucket_name: \n \"\"\"\n if 'id' not in session:\n return redirect(url_for('sign_in'))\n new_bucket_name = request.form['bucket-name']\n new_description = request.form['description']\n global current_user\n current_user.edit_bucket(bucket_name,\n new_bucket_name, new_description)\n return redirect(url_for('single_bucket',\n bucket_name=new_bucket_name))\n\n\n@app.route('/buckets/')\ndef single_bucket(bucket_name):\n \"\"\"\n Returns a single bucket with a given name\n :param bucket_name: \n \"\"\"\n if 'id' not in session:\n return redirect(url_for('sign_in'))\n global current_user\n bucket = current_user.get_single_bucket(bucket_name)\n return render_template('items.html',\n bucket_name=bucket_name,\n bucket_items=bucket.items,\n bucket_desc=bucket.description)\n\n\n@app.route('/del_bucket/')\ndef delete_bucket(bucket_name):\n \"\"\"\n Deletes a bucket from bucket list\n :param bucket_name: \n \"\"\"\n if 'id' not in session:\n return redirect(url_for('sign_in'))\n global current_user\n current_user.delete_bucket(bucket_name)\n return redirect(url_for('buckets'))\n\n\n@app.route('/create_item/', methods=['POST'])\ndef create_item(bucket_name):\n \"\"\"\n Creates a bucket\n :param bucket_name: \n \"\"\"\n if 'id' not in session:\n return redirect(url_for('sign_in'))\n item_name = request.form['item-name']\n date_added = strftime(\"%Y-%m-%d\", gmtime())\n new_item = Item(item_name, date_added)\n global current_user\n current_user.add_item(bucket_name, new_item)\n return redirect(url_for('single_bucket',\n bucket_name=bucket_name))\n\n\n@app.route('/edit_item//'\n '', methods=['POST', 'GET'])\ndef edit_item(item_name, bucket_name):\n \"\"\"\n Edits an item in a given bucket\n :param item_name: \n :param bucket_name: \n \"\"\"\n if 'id' not in session:\n return redirect(url_for('sign_in'))\n if request.method == 'POST':\n new_item_name = request.form['item-name']\n status = False\n if 'status' in request.form:\n status = request.form['status']\n global current_user\n current_user.edit_item(bucket_name, item_name,\n new_item_name, status)\n return redirect(url_for('single_bucket',\n bucket_name=bucket_name))\n else:\n item = current_user.get_single_item(bucket_name, item_name)\n return render_template('edit-item.html',\n bucket_name=bucket_name,\n activity_name=item_name,\n status=item.status)\n\n\n@app.route('/del_item//'\n '')\ndef del_item(item_name, bucket_name):\n \"\"\"\n Deletes an item from a bucket\n :param item_name: \n :param bucket_name: \n \"\"\"\n if 'id' not in session:\n return redirect(url_for('sign_in'))\n global current_user\n current_user.delete_item(bucket_name, item_name)\n return redirect(url_for('single_bucket',\n bucket_name=bucket_name))\n\n\nif __name__ == '__main__':\n app.run()\n","sub_path":"BucketList.py","file_name":"BucketList.py","file_ext":"py","file_size_in_byte":6368,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"349975660","text":"from datetime import datetime\n\ndef print_time(task_name):\n time = datetime.now()\n print(f'\\'{task_name}\\' completed in {time}')\n\n# Parameters might have a default value, in this case, 'force_uppercase' is 'True' by default\ndef get_initial(word, force_uppercase = True):\n if force_uppercase:\n initial = word[:1].upper()\n else: \n initial = word[:1]\n\n return initial\n\nfor name in ['rafael', 'joao']:\n # Parameters can be passed to a function using named notation, simply type the parameter name and set it equals to the value you want to pass\n # in this case, get_initial(force_uppercase=True, word=name)\n initial = get_initial(force_uppercase=True, word=name)\n print(f'{name} with initial {initial}')\n \nprint_time('for loop')","sub_path":"class-9/functions.py","file_name":"functions.py","file_ext":"py","file_size_in_byte":739,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"174754534","text":"import os\nimport warnings\n\nimport osmnx as ox\nimport pandas as pd\nfrom osgeo import osr, ogr\n\nwarnings.filterwarnings('ignore')\n\nplaces = [\"Пермь\", \"Екатеринбург\", \"Челябинск\", \"Омск\", \"Самара\", \"Санкт-Петербург\", \"Москва\"]\n\nresult_dataframe = pd.DataFrame(\n columns=[\"building\", \"building:levels\", \"area\", \"horizontal_len\", \"vertical_len\", \"poly_shapes_count\"])\n\n\ndef get_data_from_polygon(geometry):\n json = {'type': 'Polygon',\n 'coordinates': [list(geometry.exterior.coords)]}\n\n source = osr.SpatialReference()\n source.ImportFromEPSG(4326)\n target = osr.SpatialReference()\n target.ImportFromEPSG(5243)\n\n transform = osr.CoordinateTransformation(source, target)\n poly = ogr.CreateGeometryFromJson(str(json).replace('(', '[').replace(')', ']'))\n poly.Transform(transform)\n x1, x2, y1, y2 = poly.GetEnvelope()\n h_len, v_len, area = abs(x2 - x1), abs(y2 - y1), poly.GetArea()\n return area, h_len, v_len\n\n\nfor place in places:\n print(place)\n data = ox.footprints_from_place(place)\n data = data[['building', 'building:levels', 'geometry']]\n data = data.reset_index(drop=True)\n\n idx_for_drop = []\n data[\"area\"], data[\"horizontal_len\"], data[\"vertical_len\"], data[\"poly_shapes_count\"] = None, None, None, None\n for index, element in data.iterrows():\n try:\n data[\"area\"][index], data[\"horizontal_len\"][index], data[\"vertical_len\"][index] = get_data_from_polygon(\n element.geometry)\n data[\"poly_shapes_count\"][index] = element.geometry.exterior.coords.__len__()\n except Exception:\n pass\n data = data.drop(['geometry'], axis=1)\n result_dataframe = result_dataframe.append(data)\n result_dataframe = result_dataframe.reset_index(drop=True)\n result_dataframe.to_csv(os.path.join('..', 'data', 'data.csv'), index=False)\n","sub_path":"1st_task/model_training/create_train_dataset.py","file_name":"create_train_dataset.py","file_ext":"py","file_size_in_byte":1906,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"138739084","text":"from django import forms\nfrom django.core.exceptions import ValidationError\nfrom django.db.models import IntegerField\nfrom django.db.models.functions import Cast\nfrom .services import *\nfrom area.services import *\nfrom area.models import Owner, Room\nfrom .models import CounterValue, CounterType\n\n\n# =========================== Форма отправки показания счетчика услуг ==============================\nclass OwnerModelChoiceField(forms.ModelChoiceField):\n def label_from_instance(self, obj):\n return '%s' % obj.room\n\n\nclass SendCounterValueForm(forms.ModelForm):\n room = forms.ModelChoiceField(label=\"Номер помещения\", queryset=None)\n type = forms.ModelChoiceField(label=\"Тип счетчика\", queryset=None)\n\n def __init__(self, *args, **kwargs):\n self.user = kwargs.pop('user', None)\n self.room = None\n self.date = datetime.date.today()\n super(SendCounterValueForm, self).__init__(*args, **kwargs)\n self.fields['room'].queryset = Room.objects.filter(number__in=[item.room.number for item in\n owner_requests_history(self.user, active=True)])\n self.fields['type'].queryset = list_active_counters()\n\n def clean(self):\n cleaned_data = super(SendCounterValueForm, self).clean()\n # Проверим дату приема показаний\n if not check_actual_counter_period(cleaned_data['type']):\n start, end = get_counter_period(cleaned_data['type'])\n raise ValidationError('Период приема показаний установлен с {0} по {1} число месяца'.format(start, end))\n # Проверим на наличие ранее введенных показаний счетчика\n if not check_value_duplication(cleaned_data['room'], cleaned_data['type'], datetime.date.today()):\n raise ValidationError('Показания счетчика для данного месяца уже существуют')\n # Проверим на приращение счетчика\n if not check_value_increment(cleaned_data['room'], cleaned_data['type'],\n datetime.date.today(), cleaned_data['value']):\n raise ValidationError('Показания счетчика должны быть больше чем предыдущее значение')\n\n return cleaned_data\n\n class Meta:\n model = CounterValue\n fields = ['room', 'type', 'value']\n","sub_path":"counter/forms.py","file_name":"forms.py","file_ext":"py","file_size_in_byte":2590,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"542726736","text":"class Solution:\n def inOrder(self, root, wrapper):\n if root:\n self.inOrder(root.left, wrapper)\n wrapper[1].append(root.val)\n if len(wrapper[1]) == 2:\n tmp = wrapper[1][1] - wrapper[1][0]\n if tmp int:\n # wrapper = [minVal, two consecutive val]\n wrapper = [float('inf'),[]]\n self.inOrder(root, wrapper)\n return wrapper[0]\n","sub_path":"LeetCode/783. Minimum Distance Between BST Nodes.py","file_name":"783. Minimum Distance Between BST Nodes.py","file_ext":"py","file_size_in_byte":774,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"439206995","text":"import os\r\nimport tensorflow as tf\r\nfrom tensorflow.core.framework import graph_pb2\r\nfrom tensorflow.python.framework import importer\r\n\r\nos.environ['CUDA_VISIBLE_DEVICES'] = '0'\r\n\r\npb_path = 'E:/ucf50_train/yt8m2/v2/models/frame/sample_model/export/step_10/saved_model.pb'\r\n\r\nrun_meta = tf.RunMetadata()\r\nwith tf.Graph().as_default():\r\n output_graph_def = graph_pb2.GraphDef()\r\n with open(pb_path, \"rb\") as f:\r\n output_graph_def.ParseFromString(f.read())\r\n _ = importer.import_graph_def(output_graph_def, name=\"\")\r\n print('model loaded!')\r\n all_keys = sorted([n.name for n in tf.get_default_graph().as_graph_def().node])\r\n # for k in all_keys:\r\n # print(k)\r\n\r\n with tf.Session() as sess:\r\n flops = tf.profiler.profile(tf.get_default_graph(), run_meta=run_meta,\r\n options=tf.profiler.ProfileOptionBuilder.float_operation())\r\n print(\"test flops:{:,}\".format(flops.total_float_ops))","sub_path":"video_classficationucf50/pbfile.py","file_name":"pbfile.py","file_ext":"py","file_size_in_byte":945,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"115362691","text":"import os\nimport shutil\nimport sys\nimport unittest\nfrom os.path import dirname\n\nimport numpy as np\n\nfrom jina.proto import jina_pb2\nfrom jina.types.document import uid\nfrom jina.types.ndarray.generic import NdArray\n\n\nclass JinaTestCase(unittest.TestCase):\n\n def setUp(self) -> None:\n self.tmp_files = []\n os.environ['TEST_WORKDIR'] = os.getcwd()\n\n def tearDown(self) -> None:\n for k in self.tmp_files:\n if os.path.exists(k):\n if os.path.isfile(k):\n os.remove(k)\n elif os.path.isdir(k):\n shutil.rmtree(k, ignore_errors=False, onerror=None)\n\n def add_tmpfile(self, *path):\n self.tmp_files.extend(path)\n\n\nfile_dir = os.path.dirname(__file__)\nsys.path.append(dirname(file_dir))\n\n\ndef random_docs(num_docs, chunks_per_doc=5, embed_dim=10, jitter=1):\n c_id = 3 * num_docs # avoid collision with docs\n for j in range(num_docs):\n d = jina_pb2.DocumentProto()\n d.tags['id'] = j\n d.text = b'hello world'\n NdArray(d.embedding).value = np.random.random([embed_dim + np.random.randint(0, jitter)])\n d.id = uid.new_doc_id(d)\n for k in range(chunks_per_doc):\n c = d.chunks.add()\n c.text = 'i\\'m chunk %d from doc %d' % (c_id, j)\n NdArray(c.embedding).value = np.random.random([embed_dim + np.random.randint(0, jitter)])\n c.tags['id'] = c_id\n c.tags['parent_id'] = j\n c_id += 1\n c.parent_id = d.id\n c.id = uid.new_doc_id(c)\n yield d\n\n\ndef rm_files(file_paths):\n for file_path in file_paths:\n if os.path.exists(file_path):\n if os.path.isfile(file_path):\n os.remove(file_path)\n elif os.path.isdir(file_path):\n shutil.rmtree(file_path, ignore_errors=False, onerror=None)\n","sub_path":"tests/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":1874,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"283977879","text":"\"\"\"\n0.8.1 -using uasyncio\n suits firmware versions 2018 04 +\n0.8.4.1 - uses JSON for commands and settings\n MishaDesign - with LEDs\n\"\"\"\n\ntry:\n import uasyncio as asyncio\n import machine\n import ure as re\n import ujson as json\n import utime as time\n import sys\n import network\n print('DBG: import microlibs libraries successful')\nexcept ImportError:\n raise SystemExit\n\nLONG_SLEEP = 3\nSHORT_SLEEP = 1\nBLINK_SLEEP = 0.3\n\nrobot_ip = '192.168.4.1'\n\nsta_if = network.WLAN(network.STA_IF)\n\nif sta_if.active():\n print('sta_if: {}, {}, {}'.format(sta_if.active(), type(sta_if.ifconfig()), sta_if.ifconfig()))\n robot_ip = sta_if.ifconfig()[0]\n print('robot_ip: {}'. format(robot_ip))\n\nprint('Robot IP robot_ip: {}'. format(robot_ip))\n\n# HTML to send to browsers\n# hardcoded ip address html reply\n\nhtml = \"HTTP/1.0 200 OK\\r\\n\\r\\nI Am Robot not Groot\\r\\n\"\n\n# Setup drives\nmotor_a_p = machine.PWM(machine.Pin(5), freq=50)\nmotor_a_m = machine.PWM(machine.Pin(0), freq=50)\nservo_turn_x = machine.PWM(machine.Pin(12), freq=50)\nservo_head_x = machine.PWM(machine.Pin(14), freq=50)\nservo_hand_y = machine.PWM(machine.Pin(13), freq=50)\nservo_catch = machine.PWM(machine.Pin(15), freq=50)\nnetwork_pin = machine.Pin(2, machine.Pin.OUT)\n# headlight = machine.Pin(16, machine.Pin.OUT)\nhall_sensor = machine.Pin(4, machine.Pin.IN, machine.Pin.PULL_UP)\n\n\nrobot_settings = {}\nrobot_settings_file = 'settings.txt'\n\nrobot_settings_defaults = {\n 'DEBUG_ENABLE': True,\n 'robot_ip': '192.168.4.1',\n 'servo_min': 40,\n 'servo_max': 115,\n 'servo_center': 77,\n 'gear_factor': 5,\n 'HOLD_LOOSE_TIMEOUT': 5,\n}\n\nrobot_busy = False\n\n# # compile regex\n# # compile re number\n# float_number = re.compile(\"0\\.(\\d+)\")\n# r_number = re.compile(\"(\\d+)\")\n\n# compile regex for commands\nr_settings = re.compile(\"settings=({.*})\")\nr_run = re.compile(\"run=({.*})\")\n\n\ndef give_up():\n servo_head_x.duty(75)\n servo_hand_y.duty(40)\n network_pin.on()\n motor_a_p.duty(0)\n # print('DBG: # give_up')\n\n\ndef move_servo(servo, duty='77', forward=True, speed=1):\n # servo_start_pos = robot_settings['servo_min']\n # servo_end_pos = robot_settings['servo_max']\n # servo_center_pos = robot_settings['servo_center']\n\n # # use for while robot_settings_defaults\n servo_start_pos = robot_settings_defaults['servo_min']\n servo_end_pos = robot_settings_defaults['servo_max']\n servo_center_pos = robot_settings_defaults['servo_center']\n\n print('DBG move_servo: {}, duty: {}, forward: {}, speed: {}'\n ''.format(str(servo), str(duty), str(forward), str(speed)))\n\n try:\n duty_int = int(duty)\n if forward:\n servo.duty(duty_int)\n else:\n servo.duty(servo_start_pos + servo_end_pos - duty_int)\n except Exception as e:\n print('Error while move_servo {}, {}'.format(type(e), e))\n\n\ndef headx(key): # straight\n move_servo(servo_head_x, duty=key)\n\n\ndef handy(key): # inverted\n move_servo(servo_hand_y, duty=key, forward=False)\n\n\ndef turnx(key): # inverted\n move_servo(servo_turn_x, duty=key, forward=False)\n\n\ndef runy(key): # straight\n try:\n i_runy = int(key)\n\n if i_runy < 77:\n # m_duty = -70 * robot_settings['gear_factor']\n m_duty = -70 * robot_settings_defaults['gear_factor'] # robot_settings_defaults\n p_duty = int((924 - 12 * i_runy))\n\n elif i_runy == 77:\n m_duty = 0\n p_duty = 0\n else:\n # m_duty = int((i_runy - 70) * 5 * robot_settings['gear_factor'])\n # p_duty = int((i_runy - 70) * 5 * robot_settings['gear_factor'])\n m_duty = int((i_runy - 70) * 5 * robot_settings_defaults['gear_factor']) # robot_settings_defaults\n p_duty = int((i_runy - 70) * 5 * robot_settings_defaults['gear_factor']) # robot_settings_defaults\n\n motor_a_p.duty(p_duty)\n motor_a_m.duty(m_duty)\n except Exception as e:\n print('Error while processing runy: {}, {}'.format(type(e), e))\n\n\ndef catch(key):\n print('DBG runing: {} key: {}'.format('catch', key))\n\n if servo_catch.duty() < 75:\n servo_catch.duty(110)\n else:\n servo_catch.duty(40)\n\n\ndef gear(key):\n print('DBG runing: {} key: {}'.format('gear', key))\n\n\ndef read_settings(file):\n try:\n with open(file, 'r') as f:\n j = json.load(f)\n print('DBG read_settings seems to be OK')\n return j\n except Exception as e:\n print('ERR read_settings from file: {}, '\n ' {}, {}'.format(file, type(e), e))\n return False\n\n\ndef write_settings(j, file='settings.txt'):\n try:\n for item in j:\n print('DBG: json items: {}:{}'.format(item, j[item]))\n\n j_str = json.dumps(j)\n print('DBG: JSON data loaded OK')\n except json.JSONDecodeError as e:\n print(type(e), e)\n print('ERR: given data seems not to be valid JSON:{}'.format(str(j)))\n\n try:\n with open(file, 'w') as f:\n f.write(str(j_str))\n return True\n except Exception as e:\n print('ERR: given data could not be written {}, {}\\n {}'.format(type(e), e, j_str))\n return False\n\n\ndef update_settings(settings_to_update=None, file=robot_settings_file):\n # robot_settings = {}\n # robot_settings_file = 'settings.txt'\n\n global robot_settings\n\n print('DBG update_settings settings_to_update: {}, {}'.format(type(settings_to_update), settings_to_update))\n print('DBG update_settings robot_settings: {}, {}'.format(type(robot_settings), robot_settings))\n print('DBG update_settings file: {}'.format(file))\n print('DBG update_settings (if settings_to_update): ...')\n print('DBG update_settings (if settings_to_update): {}'.format(True if settings_to_update else False))\n\n if settings_to_update:\n try:\n write_settings(settings_to_update, file)\n robot_settings = {}\n robot_settings = read_settings(file)\n\n print('DBG robot_settings after upd: {}, {}'.format(type(robot_settings), robot_settings))\n except Exception as e:\n print('Error while updating settings {}, {}'.format(type(e), e))\n else:\n try:\n robot_settings = read_settings(file)\n print('DBG robot_settings read: {}, {}'.format(type(robot_settings), robot_settings))\n\n except Exception as e:\n print('Error while reading settings {}, {}'.format(type(e), e))\n\n\ndef robot_listener_json(request):\n global robot_busy\n robot_busy = True\n global html\n start = time.ticks_ms()\n print('DBG robot_listener_json got: {}... first 120 can workout.'.format(str(request)[:120]))\n\n request = str(request)[:120]\n formatted_request = request.replace('%22', '\\\"')\n formatted_request = formatted_request.replace('%27', '\\\"')\n formatted_request = formatted_request.replace('%20', ' ')\n\n # processing json commands\n\n if r_run.search(formatted_request) is not None:\n try: # gonna test - try not to search one more time\n m_run = r_run.search(formatted_request)\n\n print('DBG processing json commands in run, request: {}, {}'.format(\n type(request), formatted_request))\n s_run = m_run.group(1)\n print('DBG processing json commands in run, s_run: {}, {}'.format(type(s_run), s_run))\n\n j_run = json.loads(s_run)\n print('DBG json.loads() commands in run, j_settings: {}, {}'.format(type(j_run), j_run))\n\n for js_run in j_run:\n print('DBG json.loads() command in run: {}:{}'.format(js_run, j_run[js_run]))\n\n try:\n function_to_call = tokens[js_run]\n function_to_call(j_run[js_run])\n except Exception as e:\n print('SKIP while dispatching run commands with function_to_call: {}, {}'.format(type(e), e))\n\n except Exception as e:\n print('Error while processing run json.loads() {}, {}'.format(type(e), e))\n finally:\n html = \"HTTP/1.0 200 OK\\r\\n\\r\\nI Am Robot not Groot\\r\\n ms: \" + str(time.ticks_ms() - start) + \"\\r\\n\"\n robot_busy = False\n\n if r_settings.search(formatted_request) is not None:\n try:\n m_settings = r_settings.search(formatted_request)\n print('DBG processing json commands for settings, request: {}, {}'.format(\n type(request), formatted_request))\n s_settings = m_settings.group(1)\n print('DBG processing json commands, s_settings: {}, {}'.format(type(s_settings), s_settings))\n\n j_settings = json.loads(s_settings)\n print('DBG json.loads() commands, j_settings: {}, {}'.format(type(j_settings), j_settings))\n\n update_settings(settings_to_update=j_settings, file=robot_settings_file)\n except Exception as e:\n print('Error while processing settings json.loads() {}, {}'.format(type(e), e))\n finally:\n html = \"HTTP/1.0 200 OK\\r\\n\\r\\nI Am Robot not Groot\\r\\n ms: \" + \\\n str(time.ticks_ms() - start) + \"\\r\\n settings: \" + \\\n str(robot_settings) + \"\\r\\n\"\n robot_busy = False\n\n\ntokens = {\n 'headx': headx,\n 'handy': handy,\n 'turnx': turnx,\n 'runy': runy,\n 'catch': catch,\n 'gear': gear,\n 'read_settings': read_settings,\n 'update_settings': update_settings,\n 'give_up': give_up,\n}\n\n\n@asyncio.coroutine\ndef serve(reader, writer):\n try:\n # print(reader, writer)\n print(\"================\")\n # print((yield from reader.read())) # orig\n # print((yield from reader.read())) # mod readline\n # line = yield from reader.readline()\n line = yield from reader.read()\n\n if robot_busy:\n print('DBG serve robot_busy: {}'.format(robot_busy))\n else:\n robot_listener_json(line)\n print('DBG line: {}, {}'.format(type(line), str(line)[:120])) # mod readline\n # yield from writer.awrite(\"HTTP/1.0 200 OK\\r\\n\\r\\nHello. ...\\r\\n more from v.17 (with limit 120)\"\n # + str(line)[:120] + \"\\r\\n\"\n # + \"Updated robot_settings\" + str(robot_settings) + \"\\r\\n\")\n yield from writer.awrite(html)\n # print(\"After response write\")\n yield from writer.aclose()\n print(\"Finished processing request\")\n\n except Exception as e:\n print('Error while serve: {}, {}'.format(type(e), e))\n\n\ndef run():\n global robot_busy\n robot_busy = False\n loop = asyncio.get_event_loop()\n # loop.call_soon(asyncio.start_server(serve, \"127.0.0.1\", 8081))\n loop.call_soon(asyncio.start_server(serve, \"192.168.4.1\", 80))\n loop.run_forever()\n loop.close()\n\n\nif __name__ == '__main__':\n robot_settings = robot_settings_defaults\n update_settings(settings_to_update=None, file=robot_settings_file)\n run()\n\n\n","sub_path":"async-firmware-app/testing/tester-084-086/main(0.8.4.1MD).py","file_name":"main(0.8.4.1MD).py","file_ext":"py","file_size_in_byte":10988,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"407106765","text":"'''\r\nCreated on Oct 8, 2018\r\n\r\n@author: xuwang\r\n'''\r\nimport argparse\r\nimport numpy\r\nimport csv\r\nimport fiona\r\nfrom shapely.geometry.polygon import Polygon\r\nfrom shapely.geometry import shape\r\n#------------------------------------------------------------------------\r\n# construct the argument parse and parse the arguments\r\nap = argparse.ArgumentParser()\r\nap.add_argument(\"-sf\", \"--srcFile\", required=True,\r\n help=\"source file of image bound info\")\r\n#==============\r\nap.add_argument(\"-sh\", \"--shape\", required=True,\r\n help=\"field map shapefile\")\r\n#==============\r\nap.add_argument(\"-t\", \"--targetFolder\", required=True,\r\n help=\"target folder\")\r\n#==============\r\nargs = ap.parse_args()\r\nplotBoundFile = args.srcFile\r\nshapeFile = args.shape\r\ntargetPath = args.targetFolder\r\nfinalFile = open(targetPath+\"\\\\imagePlotList.csv\", 'wt')\r\n#------------------------------------------------------------------------\r\nwith fiona.open(shapeFile) as shapes:\r\n geoms = [feature[\"geometry\"] for feature in shapes]\r\n plotIDs = [feature[\"properties\"] for feature in shapes]\r\n# plotShapes = []\r\nfor i in range(len(plotIDs)):\r\n plotIDs[i] = str(plotIDs[i]).split(\"'\")[3] ##### -->?\r\n#------------------------------------------------------------------------\r\ntry:\r\n writer = csv.writer(finalFile, delimiter=',', lineterminator='\\n')\r\n imNum = 0\r\n imageBoundInfo = open(plotBoundFile,'r')\r\n for ibLine in imageBoundInfo:\r\n imNum += 1\r\n ib = ibLine.split(',\"')\r\n # Image file name\r\n imageFile = str(ib[0]).replace(\"\\\\\", \"/\")\r\n imageFileElement = imageFile.split(\"/\")\r\n imageID = imageFileElement[len(imageFileElement)-1]\r\n # Image coordinates\r\n imageBound = str(ib[1]).split(' : ')\r\n imLong_1 = float(imageBound[0].split(',')[0])\r\n imLat_1 = float(imageBound[0].split(',')[1])\r\n imLong_2 = float(imageBound[1].split(',')[0])\r\n imLat_2 = imageBound[1].split(',')[1]\r\n imLat_2 = float(imLat_2.rstrip('\"\\n'))\r\n # create polygon\r\n x_min = numpy.min([imLong_1,imLong_2])\r\n x_max = numpy.max([imLong_1,imLong_2])\r\n y_min = numpy.min([imLat_1,imLat_2])\r\n y_max = numpy.max([imLat_1,imLat_2])\r\n # Buffer\r\n xb_min = x_min+0.1*(x_max-x_min)\r\n xb_max = x_max-0.1*(x_max-x_min)\r\n yb_min = y_min+0.1*(y_max-y_min)\r\n yb_max = y_max-0.1*(y_max-y_min)\r\n imPolygon = Polygon([(xb_min, yb_min), (xb_max, yb_min), (xb_max, yb_max), (xb_min, yb_max)])\r\n # print(imPolygon)\r\n plotList = \"\"\r\n for j in range(0,len(plotIDs)):\r\n if imPolygon.contains(shape(geoms[j])):\r\n plotList = plotList+plotIDs[j]+\",\"\r\n if plotList != \"\":\r\n print(str(imNum)+\" \"+imageID+ \" \"+plotList)\r\n writer.writerow((imageFile,plotList)) \r\nfinally:\r\n finalFile.close()\r\n","sub_path":"PyPlotExtraction/src/genPlotList.py","file_name":"genPlotList.py","file_ext":"py","file_size_in_byte":2873,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"274520255","text":"import cv2\nimport onnxruntime as rt\nimport numpy as np\n\nproperties = {\n \"xception65_ade20k_train\": {'map': [127, 13], 'th': [0.45, 0.65]},\n \"xception65_coco_voc_trainval\": {'map': [12, 15], 'th': [0.35, 0.6]}\n}\n\n\ndef to_square(im, desired_size, pad):\n old_size = im.shape[:2]\n desired_size -= (pad * 2)\n ratio = float(desired_size) / max(old_size)\n new_size = tuple([int(x * ratio) for x in old_size])\n\n im = cv2.resize(im, (new_size[1], new_size[0]))\n\n delta_w = desired_size - new_size[1]\n delta_h = desired_size - new_size[0]\n top, bottom = delta_h // 2 + pad, delta_h - (delta_h // 2) + pad\n left, right = delta_w // 2 + pad, delta_w - (delta_w // 2) + pad\n\n color = [0, 0, 0]\n return cv2.copyMakeBorder(im, top, bottom, left, right, cv2.BORDER_CONSTANT, value=color), \\\n cv2.copyMakeBorder(np.ones_like(im), top, bottom, left, right, cv2.BORDER_CONSTANT, value=color), \\\n (top, bottom, left, right, old_size)\n\n\ndef back_to_original_size(im, properties):\n im = im[properties[0]:-properties[1], properties[2]:-properties[3]]\n return cv2.resize(im, properties[4][::-1])\n\n\ndef process_pred(orig_pred, padding, th):\n pred = np.copy(orig_pred)\n pred[np.all(padding == 0, axis=2)] = 0\n pred[pred < th[0]] = 0\n pred[pred > th[1]] = 1\n pred_hesitant = np.zeros_like(pred)\n pred_hesitant[np.logical_and(pred > 0, pred < 1)] = 1\n return pred, pred_hesitant\n\n\nSIZE = 512\nPAD = 10\n\n\nclass DeepLab:\n def __init__(self, name):\n self.name = name\n self.sess = rt.InferenceSession(f'frozen_graphs/{self.name}.onnx')\n self.input_name = self.sess.get_inputs()\n self.label_name = self.sess.get_outputs()[0].name\n\n def eval(self, img):\n small_img, padding, resize_properties = to_square(img, SIZE, PAD)\n return self.sess.run([self.label_name], {self.input_name[0].name: np.expand_dims(small_img, 0)})[0], \\\n small_img, padding, resize_properties\n\n def eval_specific_classes(self, img, classes):\n pred, small_img, padding, resize_properties = self.eval(img)\n ret = np.zeros_like(pred[:, :-1, :-1, 0])\n pred = (pred - pred.min()) / (pred.max() - pred.min())\n for c in classes:\n ret += pred[:, :-1, :-1, c]\n ret = (ret - ret.min()) / (ret.max() - ret.min())\n return np.transpose(ret.astype(np.float), (1, 2, 0)), small_img, padding, resize_properties\n\n def eval_pepole_and_animal(self, img):\n return self.eval_specific_classes(img, properties[self.name]['map'])\n\n def get_props(self):\n return properties[self.name]","sub_path":"DeepLab.py","file_name":"DeepLab.py","file_ext":"py","file_size_in_byte":2618,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"263186035","text":"#rsa decryption\nclass Decrypt:\n def __init__(self, key):\n self.d = key[0]\n self.n = key[1]\n\n def getDecrypted(self, text):\n print(text)\n text = text.split(' ')\n dec = ''\n for i in text:\n if i != '':\n dec+=chr(pow(int(i), self.d, self.n))\n return dec","sub_path":"ECSE352L - Crypto/Lab 7/Decrypt.py","file_name":"Decrypt.py","file_ext":"py","file_size_in_byte":330,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"37696240","text":"# Input: [2,0,2,1,1,0]\n# Output: [0,0,1,1,2,2]\n\n\n# Counting Sort\n\nclass Solution:\n def sortColors(self, nums) -> None:\n \"\"\"\n Do not return anything, modify nums in-place instead.\n \"\"\"\n\n count = [0, 0, 0]\n\n for i in nums:\n \tcount[i] += 1\n # print(count)\n num = 0\n i = 0\n for n in count:\n \tnums[i:i+n+1] = [num for k in range(n)]\n \ti += n\n \tnum += 1\n\n print(nums)\nSolution().sortColors([2,0,2,1,1,0])\n\n\n","sub_path":"M75_SortColors.py","file_name":"M75_SortColors.py","file_ext":"py","file_size_in_byte":502,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"377342918","text":"from math import sqrt\n\nperfect = {}\n\nc = 0\nc2 = 0\nfor a in range(1, 500):\n for b in range(a, 500):\n c2 = a*a + b*b\n c = int(sqrt(a*a + b*b))\n if c*c == c2:\n if a + b + c <= 1000:\n perfect[a + b + c] =perfect.get(a + b + c, 0) + 1\n\nmax_num = 0\nbest_perim = 0\nfor perim, num in perfect.items():\n if num > max_num:\n best_perim = perim\n max_num = num\n\n\nprint (perfect)\nprint (best_perim)\n","sub_path":"1-50/39.py","file_name":"39.py","file_ext":"py","file_size_in_byte":451,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"60938241","text":"# title: regular-expression-matching\n# detail: https://leetcode.com/submissions/detail/343332326/\n# datetime: Sat May 23 11:42:13 2020\n# runtime: 1152 ms\n# memory: 14 MB\n\nclass Solution:\n def isMatch(self, s: str, p: str) -> bool:\n # s += '#'\n # p += '#'\n N = len(s)\n M = len(p)\n def match(i, j):\n # print(i, j)\n if j == M:\n return i == N\n if i == N:\n while j + 1 < M and p[j + 1] == '*':\n j += 2\n return j == M\n if j + 1 >= M or p[j + 1] != '*':\n return (s[i] == p[j] or p[j] == '.') and match(i + 1, j + 1)\n if s[i] == p[j] or p[j] == '.':\n if match(i + 1, j):\n return True\n return match(i, j + 2)\n \n return match(0, 0)","sub_path":"leetcode/regular-expression-matching/343332326.py","file_name":"343332326.py","file_ext":"py","file_size_in_byte":852,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"443348020","text":"#!/usr/bin/env python3\nfrom concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor\nfrom concurrent.futures import as_completed\nimport subprocess\nimport argparse\nimport os\nimport socket\nimport sys\nimport time\nimport json\nfrom netaddr import IPRange\n\n\nclass NetScanner(object):\n def __init__(self, **kwargs):\n self.mode = kwargs['model']\n self.number = kwargs['number']\n self.function = kwargs['function']\n self.save_file = kwargs['write']\n self.verbose = kwargs['verbose']\n self.write = kwargs['write']\n\n # Convert ip_range into a list ip addrs in string\n ip_range = kwargs['ip_range'].split('-')\n netaddr_ip_range = IPRange(ip_range[0], ip_range[0]) \\\n if len(ip_range) == 1 else IPRange(ip_range[0], ip_range[1])\n self.ip_range = [str(ip) for ip in netaddr_ip_range]\n\n def scan_ping_hosts(self, hosts):\n results = {'host_status': []}\n\n if self.mode == 'process':\n with ProcessPoolExecutor(max_workers=self.number) as executor:\n host_execs = {executor.submit(self.ping_host, host): host for host in hosts}\n for host_exec in as_completed(host_execs):\n results['host_status'].append(host_exec.result())\n\n if self.mode == 'thread':\n with ThreadPoolExecutor(max_workers=self.number) as executor:\n host_execs = {executor.submit(self.ping_host, host): host for host in hosts}\n for host_exec in as_completed(host_execs):\n results['host_status'].append(host_exec.result())\n\n return results\n\n def ping_host(self, host_ip):\n scan_process_id = os.getpid()\n\n try:\n subprocess.check_call(\"ping -c 1 %s\" % host_ip, shell=True)\n host_status = {\n 'host_ip': host_ip,\n 'status': 'up',\n 'process_id': scan_process_id\n }\n except subprocess.CalledProcessError:\n host_status = {\n 'host_ip': host_ip,\n 'status': 'down',\n 'process_id': scan_process_id\n }\n\n return host_status\n\n def scan_tcp_host(self, host_ip):\n port_range = list(range(1, 1025))\n results = {'host_ip': host_ip, 'port_status': []}\n\n if self.mode == 'process':\n with ProcessPoolExecutor(max_workers=self.number) as executor:\n host_ports = {executor.submit(self.scan_tcp_host_port, host_ip, port): port for port in port_range}\n for port in as_completed(host_ports):\n results['port_status'].append(port.result())\n\n if self.mode == 'thread':\n with ThreadPoolExecutor(max_workers=self.number) as executor:\n host_ports = {executor.submit(self.scan_tcp_host_port, host_ip, port): port for port in port_range}\n for port in as_completed(host_ports):\n results['port_status'].append(port.result())\n\n return results\n\n def scan_tcp_host_port(self, host_ip, port):\n scan_process_id = os.getpid()\n s_timeout = 3\n s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n s.settimeout(s_timeout)\n try:\n s.connect((host_ip, port))\n s.shutdown(socket.SHUT_RDWR)\n print(\"Port %s on %s is open\" % (port, host_ip))\n port_status = {\n 'number': port,\n 'status': 'open',\n 'scan_process_id': scan_process_id\n }\n except Exception:\n print(\"Port %s on %s is closed\" % (port, host_ip))\n port_status = {\n 'number': port,\n 'status': 'closed',\n 'scan_process_id': scan_process_id\n }\n finally:\n s.close()\n\n return port_status\n\n def save_results(self, results):\n try:\n with open(self.write, 'w') as f:\n json.dump(results, f, indent=2)\n except Exception as e:\n sys.exit(\"Fail to write results due to %s \" % (str(e)))\n\n def run(self):\n if self.verbose:\n start_time = time.time()\n\n if self.function == 'tcp':\n results = self.scan_tcp_host(self.ip_range[0])\n elif self.function == 'ping':\n results = self.scan_ping_hosts(self.ip_range)\n else:\n sys.exit(\"Not a supported funciton,\"\n \"it should be either 'ping' or 'tcp'\")\n\n if self.verbose:\n end_time = time.time()\n exec_duration = end_time - start_time\n print(\"****************Scan Execution Details****************\")\n print(\"Execution time: %s seconds\" % exec_duration)\n\n self.save_results(results)\n\n\ndef parse_args():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-m\", \"--model\",\n default=\"thread\",\n help=\"Model used to run, [process|thread]\")\n parser.add_argument(\"-n\", \"--number\",\n type=int,\n default=50,\n help=\"Number of threads or processes spawned\")\n parser.add_argument(\"-f\", \"--function\",\n default=\"ping\",\n help=\"Function of the scanning, [ping|tcp]\")\n parser.add_argument(\"-ip\", \"--ip-range\",\n default=\"192.168.0.0-192.168.0.255\",\n help=\"A specific IP or \"\n \"IP range like 192.168.0.1-192.168.0.100\")\n parser.add_argument(\"-v\", \"--verbose\",\n type=bool,\n default=True,\n help=\"Whether to print out execution time.\")\n parser.add_argument(\"-w\", \"--write\",\n default=\"results.json\",\n help=\"File to be save the scanning results.\")\n return vars(parser.parse_args())\n\n\ndef main():\n args = parse_args()\n\n # Create scanner and run it\n ns = NetScanner(**args)\n ns.run()\n\n\nif __name__ == \"__main__\":\n main()\n","sub_path":"week03/pa01/pmap.py","file_name":"pmap.py","file_ext":"py","file_size_in_byte":6089,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"143324223","text":"# returns list of unique tags separated by commas with saved order\n\n\ndef get_unique_tags_list(tag_string):\n tag_list = map(lambda word: word.strip(), tag_string.split(','))\n\n known_tags = set()\n unique_tags_list = []\n\n for tag in tag_list:\n if not tag or tag in known_tags:\n continue\n known_tags.add(tag)\n unique_tags_list.append(tag)\n\n return unique_tags_list\n\nif __name__ == '__main__':\n inp_string = \"hello, world is mine,tag 2, other ,,,tags, people need love, other,three, four, three,tags\"\n result_list = ['hello', 'world is mine', 'tag 2', 'other', 'tags', 'people need love', 'three', 'four']\n assert get_unique_tags_list(inp_string) == result_list\n\n","sub_path":"get_unique_tags_list/get_unique_tags_list.py","file_name":"get_unique_tags_list.py","file_ext":"py","file_size_in_byte":722,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"49312051","text":"from golf import *\nimport itertools\nimport time\n\nbotList = []\nwins = []\ngames = []\nsum_scores = []\ni = 0\nfor filler in range(2):\n\tfor v in [0]:\n\t\tfor e in [0]:\n\t\t\tfor p in [-4, 0, 1, 2]:\n\t\t\t\tfor m in [0, .5, 1]:\n\t\t\t\t\tbotList.append([str(i), v, True, 4*e, p, m])\n\t\t\t\t\twins.append(0)\n\t\t\t\t\tgames.append(0)\n\t\t\t\t\tsum_scores.append(0)\n\t\t\t\t\ti += 1\n\nran = 0\nold = 0\nstart = time.clock()\nfor match in itertools.combinations(botList, 4):\n\tgame = Game(match)\n\tgame.play(False)\n\twinner = game.findWinner()\n\tpos = int(match[winner[0]][0])\n\twins[pos] += 1\n\tfor i in range(len(game.players)):\n\t\tpos = int(match[i][0])\n\t\tgames[pos] += 1\n\t\tsum_scores[pos] += game.players[i].getScore()\n\tran += 1\n\tif ran % 1000 == 0:\n\t\tgamesPerSec = float(ran - old)/(time.clock() - start)\n\t\told = ran\n\t\tstart = time.clock()\n\t\tpercent = ((float(ran)/float(10626))*100.0)\n\t\tprint(\"Progress: \" + str(percent)[:4] + \"% | Games: \" + str(ran) + \" | Games/second: \" + str(gamesPerSec)[:5])\n\t\navgs = []\nfor i in range(len(games)):\n\tavgs.append(float(sum_scores[i]/games[i]))\n\twins[i] = (float(wins[i])/float(games[i]))*100\n\nranked = [x for (y,x) in sorted(zip(wins,botList))]\nwinners = [y for (y,x) in sorted(zip(wins,botList))]\navgs = [x for (y,x) in sorted(zip(wins, avgs))]\noutput = \"ID WinPercent avg_score info_value info_mod draw end pair\\n\"\nfor i in range(len(winners)):\n\tif ranked[i][2]:\n\t\tdraw = 1\n\telse:\n\t\tdraw = 0\n\toutput += str(ranked[i][0]) + \" \" + str(winners[i])[:4] + \" \" + str(avgs[i])[:4] + \" \" + str(ranked[i][1]) + \" \" + str(ranked[i][5]) + \" \" + str(draw) + \" \" + str(ranked[i][3]) + \" \" + str(ranked[i][4]) + \"\\n\"\n\t\nf = open('results.txt', 'w')\nf.write(output)\nf.close()\n\nprint(\"\\nData upload complete, ready for analysis\")","sub_path":"miniBattle.py","file_name":"miniBattle.py","file_ext":"py","file_size_in_byte":1704,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"98008457","text":"from tkinter import *\r\nimport sqlite3\r\nimport tkinter.messagebox\r\n\r\nroot = Tk()\r\nroot.geometry('800x800')\r\nroot.title(\"Registration Form\")\r\n\r\n\r\nfullName=StringVar()\r\neml=StringVar()\r\na = StringVar()\r\nprob=StringVar()\r\ndName=StringVar()\r\nphno = IntVar()\r\nloc= StringVar()\r\ngen=StringVar()\r\napp=IntVar()\r\n\r\n# empty list to later append the ids from the database\r\nids = []\r\n\r\ndef database():\r\n \r\n name1=fullName.get()\r\n email=eml.get()\r\n gender=gen.get()\r\n age=a.get()\r\n problem=prob.get()\r\n doctname=dName.get()\r\n location=loc.get()\r\n apptime=app.get()\r\n phoneno=phno.get()\r\n conn = sqlite3.connect('test.db')\r\n cursor=conn.cursor()\r\n\r\n if name1 == '' or email == '' or gender == '' or age == '' or problem == '' or location == '' or apptime == '' or doctname == '' or phoneno =='':\r\n tkinter.messagebox.showinfo(\"Warning\", \"Please Fill Up All Boxes\")\r\n else:\r\n # now we add to the database\r\n sql=\"INSERT INTO HOSPDATA (NAME,EMAIL,AGE,GENDER, LOCATION,APPOINTMENT_TIME,PHONE_NUMBER,DOCTOR_NAME,PROBLEM) VALUES(?,?,?,?,?,?,?,?,?)\"\r\n cursor.execute(sql, (name1, email,age,gender,location,apptime,phoneno,doctname,problem)) \r\n conn.commit()\r\n tkinter.messagebox.showinfo(\"Success\", \"Appointment for \" +str(name1) + \" has been created\" )\r\n # getting the number of appointments fixed to view in the log\r\n #result = cursor.execute(sql2)\r\n #for row in result:\r\n # ids = row[0]\r\n # ids.append(ids)\r\n # ordering the ids\r\n # new = sorted(ids)\r\n #final_id = new[len(ids)-1]\r\n #print(\"Total Appointments till now : \" + str(final_id))\r\n\r\n \r\n \r\n \r\n \r\n \r\nlabel_0 = Label(root, text=\"Registration form\",width=20,font=(\"bold\", 20))\r\nlabel_0.place(x=90,y=53)\r\n\r\n\r\nlabel_1 = Label(root, text=\"FULL NAME\",width=20,font=(\"bold\", 10))\r\nlabel_1.place(x=80,y=130)\r\n\r\nentry_1 = Entry(root,textvar=fullName)\r\nentry_1.place(x=240,y=130)\r\n\r\nlabel_2 = Label(root, text=\"EMAIL\",width=20,font=(\"bold\", 10))\r\nlabel_2.place(x=80,y=180)\r\n\r\nentry_2 = Entry(root,textvar=eml)\r\nentry_2.place(x=240,y=180)\r\n\r\nlabel_3 = Label(root, text=\"GENDER\",width=20,font=(\"bold\", 10))\r\nlabel_3.place(x=80,y=230)\r\n\r\nRadiobutton(root, text=\"MALE\", value=\"male\", var=gen).place(x=235,y=230)\r\nRadiobutton(root, text=\"FEMALE\", value=\"female\", var=gen).place(x=290,y=230)\r\n\r\n#Radiobutton(root, text=\"Male\",padx = 5,variable=gen, value='m').place(x=235,y=230)\r\n#Radiobutton(root, text=\"Female\",padx = 20,variable=gen, value='f').place(x=290,y=230)\r\n\r\nlabel_4 = Label(root, text=\"DOCTOR NAME\",width=20,font=(\"bold\", 10))\r\nlabel_4.place(x=80,y=280)\r\n\r\nlist1 = ['DR RAMA','DR T S MOHAN','DR ABBAI','DR PEDDAVEERA RAJU','DR RAMESH','DR VIJETHA'];\r\n\r\ndroplist=OptionMenu(root,dName, *list1)\r\ndroplist.config(width=25)\r\ndName.set('select your doctor') \r\ndroplist.place(x=240,y=280)\r\n\r\nlabel_5 = Label(root, text=\"PROBLEM\",width=20,font=(\"bold\", 10))\r\nlabel_5.place(x=80,y=330)\r\n\r\nentry_5 = Entry(root,textvar=prob)\r\nentry_5.place(x=240,y=330)\r\n\r\n\r\nlabel_6 = Label(root, text=\"AGE\",width=20,font=(\"bold\", 10))\r\nlabel_6.place(x=80,y=380)\r\n\r\nentry_6 = Entry(root,textvar=a)\r\nentry_6.place(x=240,y=380)\r\n\r\nlabel_7 = Label(root, text=\"APPOINTMENT TIME\",width=20,font=(\"bold\", 10))\r\nlabel_7.place(x=80,y=420)\r\n\r\nentry_7 = Entry(root,textvar=app)\r\nentry_7.place(x=240,y=420)\r\n\r\nlabel_8 = Label(root, text=\"PHONE NUMBER\",width=20,font=(\"bold\", 10))\r\nlabel_8.place(x=80,y=470)\r\n\r\nentry_8 = Entry(root,textvar=phno)\r\nentry_8.place(x=240,y=470)\r\n\r\nlabel_9 = Label(root, text=\"LOCATION\",width=20,font=(\"bold\", 10))\r\nlabel_9.place(x=80,y=520)\r\n\r\nentry_9 = Entry(root,textvar=loc)\r\nentry_9.place(x=240,y=520)\r\n\r\nButton(root, text='Submit',width=20,bg='brown',fg='white',command=database).place(x=220,y=570)\r\n\r\nroot.mainloop()\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n","sub_path":"registration.py","file_name":"registration.py","file_ext":"py","file_size_in_byte":3802,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"297031280","text":"import sys\nsys.path.insert(1, '..')\n\nimport time\nfrom clsearch import uri_exists_stream, import_rosetta\n\n\ndef check_urls(rosetta_stream):\n failed = False\n j = 0\n\n for key, value in rosetta_stream.items():\n i = value.items()\n print(\"\\n\" + key, end='')\n for city in value:\n # print(value[city])\n site = str(\"https://\" + str(value[city]) + \".craigslist.org\")\n verdict = uri_exists_stream(site)\n if not verdict:\n time.sleep(3) # wait 3 seconds and retry before throwing fail\n if uri_exists_stream(site):\n print(\n \"\\n\" + key + \" => \" + city + \" : \\t https://\" + value[city] + \".craigslist.org does not exist\")\n failed = True\n else:\n print('.', end='')\n\n if failed:\n print(\"\\n\\nUnable to resolve all URLs in rosetta.yaml. See output above.\")\n else:\n print(\"\\n\\nURL validity check passed!\")\n\n\ndef check_redundant_url(rosetta_stream):\n\n failed = False\n\n for state in rosetta_stream:\n for city in rosetta_stream[state]:\n for state1 in rosetta_stream:\n if state != state1:\n for city1 in rosetta_stream[state1]:\n if rosetta_stream[state][city] == rosetta_stream[state1][city1]:\n print(\"\\nFound redundant URL across states!\")\n print(state + \" : \" + city + \" : \" + rosetta_stream[state][city] + \" = \" + state1 + \" : \" + city1 + \" : \" + rosetta_stream[state1][city1])\n failed = True\n\n if failed:\n print(\"\\n\\nSome cities in rosetta.txt are redundant across states. See output above.\")\n else:\n print(\"\\nRedundancy check passed!\")\n\ndef check_redundant_citykey(rosetta_stream):\n\n failed = False\n\n for state in rosetta_stream:\n for city in rosetta_stream[state]:\n for state1 in rosetta_stream:\n if state != state1:\n for city1 in rosetta_stream[state1]:\n if city == city1:\n print(\"\\nFound redundant cityname across states!\")\n print(state + \" : \" + city + \" = \" + state1 + \" : \" + city1)\n failed = True\n\n if failed:\n print(\"\\n\\nSome cities in rosetta.txt are redundant across states. See output above.\")\n else:\n print(\"\\nRedundancy check passed!\")\n\n\ndef testrosetta():\n # https://stackoverflow.com/questions/3160699/python-progress-bar\n\n print(\"\\nTesting rosetta.yaml - this will take a few minutes\")\n rs = import_rosetta(\"../../etc/rosetta.yaml\")\n\n #check_urls(rs)\n\n #check_redundant_url(rs)\n\n check_redundant_citykey(rs)\n\n\nif __name__ == \"__main__\":\n testrosetta()","sub_path":"lib/tests/testRosetta.py","file_name":"testRosetta.py","file_ext":"py","file_size_in_byte":2843,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"134517107","text":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport os\n\n\n# merge all ICC value to ICC.csv\ndef merge_ICC(dir_path):\n ICC12 = pd.read_csv(os.path.join(dir_path,'ICC12.csv'))\n ICC23 = pd.read_csv(os.path.join(dir_path,'ICC23.csv'))\n ICC13 = pd.read_csv(os.path.join(dir_path,'ICC13.csv'))\n ICC123 = pd.read_csv(os.path.join(dir_path,'ICC123.csv'))\n\n data_1 = pd.merge(ICC12, ICC23)\n data_2 = pd.merge(data_1, ICC13)\n data_3 = pd.merge(data_2, ICC123)\n\n data_3.to_csv(os.path.join(dir_path, 'ICC.csv'), index=None)\n\n\ndef del_NaN(data):\n if np.isnan(np.sum(data)) == True:\n to_remain = (1 - np.isnan(data)).astype(np.bool)\n data = data[to_remain]\n return data\n\n\n# show ICC distribution\ndef show_ICC_distribution(ICC_path,xmin,ymax):\n ICC_csv = pd.read_csv(ICC_path)\n\n ICC12 = del_NaN(ICC_csv['ICC12'].values)\n ICC13 = del_NaN(ICC_csv['ICC13'].values)\n ICC23 = del_NaN(ICC_csv['ICC23'].values)\n ICC123 = del_NaN(ICC_csv['ICC123'].values)\n\n f, ax = plt.subplots(2,2)\n numbins = 50\n range_min = xmin\n ax[0][0].hist(ICC12, numbins, rwidth=0.5, range=(range_min, 1))\n ax[0][1].hist(ICC13, numbins, rwidth=0.5, range=(range_min, 1))\n ax[1][0].hist(ICC23, numbins, rwidth=0.5, range=(range_min, 1))\n ax[1][1].hist(ICC123, numbins, rwidth=0.5, range=(range_min, 1))\n\n if ymax:\n ax[0][0].set_ylim(0,ymax)\n ax[0][1].set_ylim(0,ymax)\n ax[1][0].set_ylim(0,ymax)\n ax[1][1].set_ylim(0,ymax)\n\n ax[0][0].set_title('ICC12')\n ax[0][0].set_xlabel('ICC')\n ax[0][0].set_ylabel('Num of Features')\n\n ax[0][1].set_title('ICC13')\n ax[0][1].set_xlabel('ICC')\n ax[0][1].set_ylabel('Num of Features')\n\n ax[1][0].set_title('ICC23')\n ax[1][0].set_xlabel('ICC')\n ax[1][0].set_ylabel('Num of Features')\n\n ax[1][1].set_title('ICC123')\n ax[1][1].set_xlabel('ICC')\n ax[1][1].set_ylabel('Num of Features')\n\n plt.show()\n\n\n# compute percentile\ndef compute_percentile(data_path,percentage):\n data = pd.read_csv(data_path)\n for ICC_name in ['ICC12','ICC13' ,'ICC23', 'ICC123']:\n ICC = data[ICC_name].values\n ICC = del_NaN(ICC)\n\n percentile = np.percentile(ICC, percentage)\n max = np.max(ICC)\n min = np.min(ICC)\n print(ICC_name,min,max,percentile)\n\n\n# compute feature numbers which ICC value below threshold\ndef compute_num_under_threshold(data_path,threshold):\n data = pd.read_csv(data_path)\n for ICC_name in ['ICC12','ICC13' ,'ICC23', 'ICC123']:\n ICC = data[ICC_name].values\n ICC = del_NaN(ICC)\n threshold_destination = np.where(ICC < threshold)\n print(ICC_name,np.shape(threshold_destination)[1])\n\n\ndef compute_corr(ICC_path):\n ICC_csv = pd.read_csv(ICC_path)\n\n ICC12 = del_NaN(ICC_csv['ICC12'].values)\n ICC13 = del_NaN(ICC_csv['ICC13'].values)\n ICC23 = del_NaN(ICC_csv['ICC23'].values)\n ICC123 = del_NaN(ICC_csv['ICC123'].values)\n\n print(np.corrcoef(ICC12,ICC13))\n print(np.corrcoef(ICC12,ICC23))\n print(np.corrcoef(ICC13,ICC23))\n\n\n# select feature by threshold\ndef select_feature_by_threshold(dimension_dir,ICC_path, threshold):\n all_path = os.path.join(dimension_dir,'all\\\\all_features.csv')\n save_path = os.path.join(dimension_dir,'all\\\\selected_features.csv')\n\n ICC_data = (pd.read_csv(ICC_path)).values\n all_data = pd.read_csv(all_path)\n\n feature_list = ['CaseName']\n for row in range(np.shape(ICC_data)[0]):\n if (ICC_data[row][2] > threshold) and (ICC_data[row][3] > threshold):\n feature_list.append(ICC_data[row][0])\n\n selected_data = all_data[feature_list]\n selected_data = delete_redundant_case(selected_data)\n selected_data.to_csv(save_path,index=None)\n\n\ndef select_case_by_standard(model_path, standard_data, feature_data, standard):\n if standard == 'furman':\n standard_to_merge = pd.DataFrame({'CaseName':standard_data['Image NO.'], 'label':standard_data['Unnamed: 8']})\n elif standard == 'ISUP':\n standard_to_merge = pd.DataFrame({'CaseName': standard_data['Unnamed: 4'], 'label': standard_data['Unnamed: 7']})\n else:\n print('standard name wrong')\n\n standard_output = pd.merge(standard_to_merge,feature_data)\n standard_output = standard_output.drop_duplicates()\n\n save_path = os.path.join(model_path, standard+\"\\\\\"+standard+\"_feature.csv\")\n standard_output.to_csv(save_path, index=None)\n\n error_case = set(standard_to_merge['CaseName']).difference(set(feature_data['CaseName']))\n print(standard,error_case)\n\n\n# i forget\ndef seperate_furman_isup(all_path, label_path, model_path):\n feature_path = os.path.join(all_path, 'selected_features.csv')\n feature_data = pd.read_csv(feature_path)\n\n furman_data = pd.read_excel(label_path, sheet_name='Sheet1')\n isup_data = pd.read_excel(label_path, sheet_name='Sheet2')\n\n for i in range(len(feature_data['CaseName'])):\n feature_data['CaseName'][i] = int(feature_data['CaseName'][i][-8:])\n\n select_case_by_standard(model_path, furman_data, feature_data, 'furman')\n select_case_by_standard(model_path, isup_data, feature_data, 'ISUP')\n\n\ndef delete_redundant_case(data):\n error_list = ['CHEN_XIAO_CHUN_s 10838430', 'HE_LIN_XUAN_2 10790012', 'CHEN_XIAO_CHUN2_10838430', 'HE_LIN_XUAN2_10790012']\n # for error_name in error_list:\n data = data[~data['CaseName'].isin(error_list)]\n return data\n\n\n# dir_path = r'D:\\PycharmProjects\\learning\\SHZL\\feature_data\\2d\\new_ICC'\n# merge_ICC(dir_path)\n\n# ICC_path = r'D:\\PycharmProjects\\learning\\SHZL\\feature_data\\2d\\new_ICC\\ICC.csv'\n# show_ICC_distribution(ICC_path, xmin=0.9, ymax=800)\n# compute_percentile(ICC_path,10)\n# compute_num_under_threshold(ICC_path,0.95)\n# compute_corr(ICC_path)\n\n# dimension_path = r'D:\\PycharmProjects\\learning\\SHZL\\feature_data\\3d'\n# ICC_path = r'D:\\PycharmProjects\\learning\\SHZL\\feature_data\\3d\\new_ICC\\ICC.csv'\n# select_feature_by_threshold(dimension_path,ICC_path,0.9)\n\nlabel_path = r'F:\\SHZL\\ccRCC20190406 分类.xlsx'\nall_path = r'D:\\PycharmProjects\\learning\\SHZL\\feature_data\\3d\\all'\nmodel_path = r'F:\\SHZL\\model\\3d'\nseperate_furman_isup(all_path, label_path, model_path)\n","sub_path":"process/feature_selector.py","file_name":"feature_selector.py","file_ext":"py","file_size_in_byte":6167,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"326674171","text":"import random\nfrom termcolor import colored \n\ndef NumRand():\n random.seed()\n x=random.randint(1,120)\n \n return x\n\n\ndef finalizar():\n print(colored(\"Programa finalizado\",\"red\") )\n\ndef intervalos1_120(n):\n i=\"\"\n if(n>=1 and n<10):\n i=\"(1,10)\"\n elif(n>=10 and n <50):\n i=\"[10,50)\"\n elif(n>=50 and n<100):\n i=\"[50,100)\"\n elif(n>=100 and n<=120):\n i=\"[100,120]\"\n else:\n i=\"fuera de [1,120]\" \n\n return i \n\n\n\n\ndef menu():\n print(colored(\"Ejercicio intervalos\\n\",\"yellow\"))\n print(colored(\"que deseas hacer? \\n\",\"yellow\"))\n print(colored(\"1. intervalos numero aleatorio entre 0 y 120\\n\",\"green\"))\n print(colored(\"2. salir\\n\",\"red\"))\n respuesta= input(\"\")\n return respuesta\n\n\n\ndef continuar():\n input(colored(\"Presiona Enter para continuar...\",\"yellow\"))\n\ndef main():\n salida=False\n while (salida==False):\n opcion=menu()\n if (opcion==\"1\"):\n x=NumRand()\n print(colored(\"su numero aleatorio es: \",\"yellow\") )\n print(colored(str(x) + \"\\n\",\"green\") )\n print(colored(\"el intervalo de su numero es:\\n \",\"yellow\") )\n print(colored(intervalos1_120(x) + \"\\n\",\"green\") )\n\n continuar()\n \n \n elif(opcion==\"2\"): \n salida=True\n print(colored(\"Gracias por usar el programa\\n\",\"red\") )\n finalizar()\n else:\n print(colored(\"No ha ingresado una opcion correcta\\n\",\"red\") )\n continuar() \n\nmain() ","sub_path":"py6_retos2/reto6.py","file_name":"reto6.py","file_ext":"py","file_size_in_byte":1407,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"87497092","text":"import glob\nimport time\n\nbase_dir = '/sys/bus/w1/devices/'\ndevice_folder = glob.glob(base_dir + '*-*')[0]\ndevice_file = device_folder + '/w1_slave'\nlog = open('/var/log/thermo/temp.log', 'a')\n\ndef read_temp_raw():\n f = open(device_file, 'r')\n lines = f.readlines()\n f.close()\n return lines\n\ndef read_temp():\n lines = read_temp_raw()\n while lines[0].strip()[-3:] != 'YES':\n lines = read_temp_raw()\n equals_pos = lines[1].find('t=')\n if equals_pos != -1:\n temp_string = lines[1][equals_pos+2:]\n temp_c = float(temp_string) / 1000\n temp_f = temp_c * 9 / 5 + 32\n return temp_c, temp_f\n\ntemp = read_temp()\nlog.write(\"{:.0f},{:.2f},{:.2f} \\n\".format(time.time(), temp[0], temp[1]))\n","sub_path":"containers/thermo-adapter/thermo.py","file_name":"thermo.py","file_ext":"py","file_size_in_byte":735,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"365849513","text":"#!/usr/bin/env python3\n\n# Created by: Joseph Palermo\n# Created on: October 2019\n# This program makes sure that the sprite doesn’t go off the screen\n\n\nSCREEN_X = 160\nSCREEN_Y = 120\nSCREEN_GRID_X = 16\nSCREEN_GRID_Y = 8\nSPRITE_SIZE = 16\nTOTAL_NUMBER_OF_ALIENS = 5\nFPS = 60\n\n# Using for button space\nbutton_state = {\n \"button_up\": \"up,\",\n \"button_just_pressed\": \"just pressed\",\n \"button_still_pressed\": \"still pressed\",\n \"button_released\": \"released\"\n}\n","sub_path":"constants.py","file_name":"constants.py","file_ext":"py","file_size_in_byte":463,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"285867036","text":"#!/usr/bin/env python3\n\"\"\"With句の仕組み\"\"\"\n\nimport com.console\n\nlog = com.console.log\nlog_add_line = com.console.log_add_line\n\nlog('#============================')\nlog('# with句サンプル')\nlog('#============================')\n\n\nclass WithTest():\n \"\"\"with句で利用できるクラス\"\"\"\n\n def __init__(self, name):\n \"\"\"コンストラクタ\n\n Args:\n name (str): 名前\n \"\"\"\n super().__init__()\n self.name = name\n\n def __enter__(self):\n \"\"\"初期処理\"\"\"\n log('--- start ---')\n return self\n\n def __exit__(self, exception_type, exception_value, traceback):\n \"\"\"終了処理\n\n Args:\n exception_type (str): エラータイプ\n exception_value (str): エラー値\n traceback (str): トレース\n\n Returns:\n WithTest: インスタンス\n \"\"\"\n log('exception_type:{0}, exception_value:{1}, traceback:{2}'.format(\n exception_type, exception_value, traceback))\n log('--- end ---')\n log_add_line()\n return self\n\n\nwith WithTest('WITH TEST') as with_test:\n log(with_test.name)\n # 途中でエラーになろうと終了処理は正しく行われる\n raise Exception\n","sub_path":"python_template/basic/with_sample.py","file_name":"with_sample.py","file_ext":"py","file_size_in_byte":1266,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"302087708","text":"from pandac.PandaModules import Vec3\r\n\r\nclass Cycle:\r\n\tdef __init__(self, inputManager):\r\n\t\tself.inputManager = inputManager\r\n\t\tself.setupVarsNPs()\r\n\t\ttaskMgr.add(self.cycleControl, \"Cycle Control\")\r\n\tdef setupVarsNPs(self):\r\n\t\tself.root = render.attachNewNode(\"Root\")\r\n\t\tself.dirNP = self.root.attachNewNode(\"DirNP\")\r\n\t\tself.refNP = self.root.attachNewNode(\"RefNP\")\r\n\t\tself.dirVec = Vec3(0,0,0)\r\n\t\tself.cycleVec = Vec3(0,0,0)\r\n\t\tself.refVec = Vec3(0,0,0)\r\n\t\tself.speed = 0\r\n\t\tself.throttle = 0\r\n\t\tself.maxSpeed = 200\r\n\t\tself.accel = 25\r\n\t\tself.handling = 20\r\n\t\tself.cycle = loader.loadModel(\"../Models/Cycle.bam\")\r\n\t\tself.cycle.reparentTo(self.root)\r\n\t\tself.root.setPos(2,15,0)\r\n\t\tbase.camera.reparentTo(self.dirNP)\r\n\t\tbase.camera.setY(base.camera, -5)\r\n\tdef cycleControl(self, task):\r\n\t\tdt = globalClock.getDt()\r\n\t\tif( dt > .20):\r\n\t\t\treturn task.cont\r\n\t\tif(self.inputManager.keyMap[\"w\"] == True):\r\n\t\t\tself.adjustThrottle(\"up\", dt)\r\n\t\telif(self.inputManager.keyMap[\"s\"] == True):\r\n\t\t\tself.adjustThrottle(\"down\", dt)\r\n\t\tif(self.inputManager.keyMap[\"d\"] == True):\r\n\t\t\tself.turn(\"r\", dt)\r\n\t\telif(self.inputManager.keyMap[\"a\"] == True):\r\n\t\t\tself.turn(\"l\", dt)\r\n\t\tif(self.inputManager.keyMap[\"mouse1\"] == True):\r\n\t\t\tself.cameraZoom(\"in\", dt)\r\n\t\telif(self.inputManager.keyMap[\"mouse3\"] == True):\r\n\t\t\tself.cameraZoom(\"out\", dt)\r\n\t\tif(base.mouseWatcherNode.hasMouse() == True):\r\n\t\t\tmpos = base.mouseWatcherNode.getMouse()\r\n\t\t\tbase.camera.setP(mpos.getY() * 30)\r\n\t\t\tbase.camera.setH(mpos.getX() * -30)\r\n\t\tself.speedCheck(dt)\r\n\t\tself.simDrift(dt)\r\n\t\tself.move(dt)\r\n\t\treturn task.cont\r\n\tdef cameraZoom(self, dir, dt):\r\n\t\tif(dir == \"in\"): base.camera.setY(base.camera, 10 * dt)\r\n\t\telse: base.camera.setY(base.camera, -10 * dt)\r\n\tdef turn(self, dir, dt):\r\n\t\tturnRate = self.handling * (2 - \r\n\t\t\t(self.speed / self.maxSpeed))\r\n\t\tif(dir == \"r\"): turnRate = -turnRate\r\n\t\tself.cycle.setH(self.cycle, turnRate * dt)\r\n\tdef adjustThrottle(self, dir, dt):\r\n\t\tif(dir == \"up\"):\r\n\t\t\tself.throttle += .25 * dt\r\n\t\t\tif(self.throttle > 1 ): self.throttle = 1\r\n\t\telse:\r\n\t\t\tself.throttle -= .25 * dt\r\n\t\t\tif(self.throttle < -1 ): self.throttle = -1\r\n\tdef speedCheck(self, dt):\r\n\t\ttSetting = (self.maxSpeed * self.throttle)\r\n\t\tif(self.speed < tSetting):\r\n\t\t\tif((self.speed + (self.accel * dt)) > tSetting):\r\n\t\t\t\tself.speed = tSetting\r\n\t\t\telse:\r\n\t\t\t\tself.speed += (self.accel * dt)\r\n\t\telif(self.speed > tSetting):\r\n\t\t\tif((self.speed - (self.accel * dt)) < tSetting):\r\n\t\t\t\tself.speed = tSetting\r\n\t\t\telse:\r\n\t\t\t\tself.speed -= (self.accel * dt)\r\n\tdef simDrift(self, dt):\r\n\t\tself.refNP.setPos(self.dirNP, 0, 1, 0)\r\n\t\tself.dirVec.set(self.refNP.getX(), self.refNP.getY(), 0)\r\n\t\tself.refNP.setPos(self.cycle, 0, 1, 0)\r\n\t\tself.cycleVec.set(self.refNP.getX(), self.refNP.getY(), 0)\r\n\t\tself.refVec.set(0,0,1)\r\n\t\tvecDiff = self.dirVec.signedAngleDeg(self.cycleVec, \r\n\t\t\tself.refVec)\r\n\t\tif(vecDiff < .1 and vecDiff > -.1):\r\n\t\t\tself.dirNP.setHpr(self.cycle.getH(), 0, 0)\t\r\n\t\telse: self.dirNP.setHpr(self.dirNP, vecDiff * dt * 2.5, 0, 0)\r\n\t\tself.dirNP.setP(self.cycle.getP())\r\n\t\tself.dirNP.setR(0)\r\n\tdef move(self, dt):\r\n\t\tmps = self.speed * 1000 / 3600\r\n\t\tself.refNP.setPos(self.dirNP, 0, 1, 0)\r\n\t\tself.dirVec.set(self.refNP.getX(), self.refNP.getY(), \r\n\t\t\tself.refNP.getZ())\r\n\t\tself.root.setPos(self.root, \r\n\t\t\tself.dirVec.getX() * dt * mps, \r\n\t\t\tself.dirVec.getY() * dt * mps, \r\n\t\t\tself.dirVec.getZ() * dt * mps)","sub_path":"BGP3D/Chapter05/Examples/CycleClass_04.py","file_name":"CycleClass_04.py","file_ext":"py","file_size_in_byte":3369,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"36748949","text":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport sqlalchemy\n\nmydb = sqlalchemy.create_engine(\n # namaDBsys://user:pass@host:port/namaDatabase\n 'mysql+pymysql://rudyabs:Kecapi48@localhost:3306/world'\n)\n\ndf = pd.read_sql('SELECT * FROM country', mydb)\nasean = df[df['Region'] == 'Southeast Asia'].reset_index()\nwarna = ['blue', 'orange', 'green', 'red', 'purple', 'brown', 'gray', 'yellow', 'pink', 'black', 'darkblue']\n\nplt.figure('Bar Chart - Populasi Negara ASEAN',figsize=(12,8))\nplt.bar(asean['Name'], asean['Population'], color = warna)\nplt.title('Populasi Negara ASEAN')\nplt.xlabel('Negara')\nplt.ylabel('Populasi (x100jt jiwa)')\nplt.xticks(rotation=30)\nplt.grid()\n\nfor j in range(len(asean)):\n plt.text(asean['Name'][j], asean['Population'][j] + 1000000, asean['Population'][j])\n\nplt.tight_layout()\nplt.show()\n","sub_path":"2-1_Populasi_ASEAN.py","file_name":"2-1_Populasi_ASEAN.py","file_ext":"py","file_size_in_byte":875,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"335696942","text":"\n#Fibonacci 序列时间复杂度Olog(n)\n\ndef Fibonacci(n):\n\n if n>0:\n\n list = Fibonacci(int(n/2))\n t0 = list[0]\n t1 = list[1]\n\n if (n%2 == 1):\n return [t1**2 + t0**2,(2*t0+t1)*t1]\n else:\n return [(2*t1-t0)*t0,t0**2+t1**2]\n\n return [0,1]\n\n\nprint(Fibonacci(9))\n\t\n\n","sub_path":"Fibonacci.py","file_name":"Fibonacci.py","file_ext":"py","file_size_in_byte":327,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"580014566","text":"import socket\r\n\r\nclient = socket.socket()\r\n\r\nclient.connect(('localhost',10000))\r\n\r\nwhile True:\r\n msg= input('>>').strip()\r\n if len(msg) == 0: continue\r\n client.send(msg.encode())\r\n data = client.recv(1024)\r\n print('return data:', data.decode())\r\n\r\nclient.close()\r\n\r\n","sub_path":"socket_client.py","file_name":"socket_client.py","file_ext":"py","file_size_in_byte":282,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"204417264","text":"#!/usr/bin/env python\nimport click\nimport pandas as pd\nimport requests\nimport io\nimport datetime\nimport pandas_datareader.data as pdr\nimport sys\nimport tensorflow as tf\nimport numpy as np\nfrom sklearn.preprocessing import MinMaxScaler\nimport matplotlib.pyplot as plt\nfrom keras.models import Sequential\nfrom keras.layers import Dense\nfrom keras.layers import LSTM\nfrom keras.layers import Dropout\nfrom keras.layers import Masking\nfrom keras.optimizers import Adam\nfrom keras.layers import Flatten\n\n#ml function\ndef lstm(data, BS=3, EPOCHS=20, lr = 0.001, decay = 0.23):\n print(\"LSTM running ... ...\")\n scaler = MinMaxScaler(feature_range = (0, 1))\n n, m = data.shape\n #data[\"Pre-Close\"] = 0\n #for i in range(1, n):\n # data[\"Pre-Close\"].iloc[i] = data[\"Close\"].iloc[i-1].copy()\n #data = data.iloc[1:n].copy()\n n, m = data.shape\n train = data.iloc[0:(n*3)//4].to_numpy()\n val = data[(n*3)//4:n].to_numpy()\n train_scale = scaler.fit_transform(train)\n val_scale = scaler.transform(val)\n timesteps = 1 ## for future fine tuning \n features_set = np.delete(train_scale, 3, axis=1).copy() #.append(apple_training_scaled[i, 0:apple_train.shape[1]-1])\n labels = train_scale[:, 3].copy()\n features_set_val = np.delete(val_scale, 3, axis=1).copy() #get the features for training\n labels_val = val_scale[:, 3].copy() #get the prediction result for training\n features_set = np.reshape(features_set, (features_set.shape[0], timesteps, features_set.shape[1]))\n features_set_val = np.reshape(features_set_val, (features_set_val.shape[0], timesteps, features_set_val.shape[1]))\n opt = Adam(lr=lr, decay=decay / (EPOCHS))\n model = Sequential()\n model.add(LSTM(units=80, return_sequences=True, input_shape=(features_set.shape[1],features_set.shape[2])))#set first layer and the feature shape for each row\n model.add(LSTM(units=50, return_sequences=True))#set first layer and the feature shape for each row\n model.add(LSTM(units=50, return_sequences=True))#set first layer and the feature shape for each row\n model.add(Dropout(0.29))\n model.add(Flatten())\n model.add(Dense(units = 1,activation='relu'))\n model.compile(\n optimizer=opt,\n loss='binary_crossentropy',\n metrics=[\"binary_crossentropy\"])\n checkpoint_filepath = 'checkpoint.hdf5'\n model_checkpoint_callback = tf.keras.callbacks.ModelCheckpoint(\n filepath=checkpoint_filepath,\n save_weights_only=True,\n monitor='val_loss',\n mode='min',\n save_best_only=True)\n history = model.fit(features_set, labels, epochs = EPOCHS, batch_size = BS, validation_data=(features_set_val, labels_val), callbacks=[model_checkpoint_callback],verbose=0)\n predictions = model.predict(features_set_val)\n predictions = np.reshape(predictions, (features_set_val.shape[0]))\n validation = val_scale.copy()\n validation[:,3] = predictions\n result_val = scaler.inverse_transform(validation)\n print(result_val[-1, 3])\n return result_val[-1, 3]\n\n@click.command()\n@click.option(\"--name\")\ndef hello(name=\"AAPL\"):\n \"\"\"Return a table of 'value' stock price features\"\"\"\n\n #stock name\n stock = name\n \n #set up the start and end time point I want\n end = datetime.date.today()\n start = end + datetime.timedelta(days=-365)\n \n #using data_reader to retrieve stock data from yahoo finance\n data = pdr.DataReader(stock, 'yahoo', start, end)\n \n #data preprocessing\n data = data.round(3)\n #make model based on the original data\n tomorrow = lstm(data)\n\n #change data type and index of the datafram for better visualization\n data[\"Volume\"] = data.apply(lambda x: \"{:,.0f}\".format(x[\"Volume\"]), axis=1)\n data = data.reset_index()\n \n #return the table into html format and modify the look\n #return_table = data.to_html(table_id=stock, justify=\"center\")\n #return_table = return_table[:6] + \" align = 'center'\" + return_table[6:]\n \n if tomorrow > data[\"Close\"].iloc[-1]:\n future = 'Next: Bull'\n elif tomorrow < data[\"Close\"].iloc[-1]:\n future = 'Next: Bear'\n else: future = 'Next: Same'\n \n # add header\n title = '{0} historical stock price (from {1} to {2})'.format(stock, start, end)\n\n #subtitle = ' Python rt = {0}, tf = {1}
'.format(sys.version, tf.__version__)\n \n #return title + subtitle + future + return_table# + future\n click.echo(f'{title}\\n{future}!')\n\nif __name__ == '__main__':\n #pylint: disable=no-value-for-parameter\n hello()","sub_path":"app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":4698,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"219849786","text":"import smtplib, imapclient, pyzmail\n\npw = input('Password: ')\nsub = input('Subject: ')\nbody = input('Body: ')\nmailingList = ['ejcu8@k12albemarle.org', 'mrsw2@k12albemarle.org']\n\nserver = smtplib.SMTP('smtp.gmail.com', 587)\nserver.connect(\"smtp.gmail.com\", 587)\nserver.ehlo()\nserver.starttls()\nserver.ehlo()\nserver.login('strawbot17@gmail.com', pw)\n\nimapObj = imapclient.IMAPClient('imap.gmail.com', ssl = True)\nimapObj.login('strawbot17@gmail.com', pw)\nimapObj.select_folder('INBOX', readonly = True)\nnewReports = imapObj.search(['SUBJECT !issue', 'UNSEEN'])\nfor report in newReports:\n message = pyzmail.PyzMessage.factory(rawMessages[report]['BODY[]'])\n reportText = message.get_subject()\n user = message.get_addresses('from')\n server.sendmail('strawbot17@gmail.com', user, 'Subject: ' + + '\\n' + body)\n\n#for user in mailingList:\n #server.sendmail('strawbot17@gmail.com', user, 'Subject: ' + sub + '\\n' + body)\n\nserver.quit()\n","sub_path":"Gmail Bot.py","file_name":"Gmail Bot.py","file_ext":"py","file_size_in_byte":944,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"287991254","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\ncategory = 'Optical source'\n\nclass Driver_parser():\n def __init__(self, Instance, name, **kwargs):\n self.name = name\n self.Instance = Instance\n \n \n def add_parser_usage(self,message):\n \"\"\"Usage to be used by the parser\"\"\"\n usage = f\"\"\"\n{message}\n\n---------------- Examples: ----------------\n\nusage: autolab driver [options] args\n \n autolab driver -D {self.name} -C USB -w 1550.2 -p 10\n load {self.name} driver using USB communication protocol with preconfigured vendor and deviceID and set the wavelength to 1550.2nm and the piezo to 10%.\n \n autolab driver -D nickname -x 1550.2,1551.3,3\n Use now the device nickname as defined in local_config.ini and perform a wavelength scan from 1550.2nm to 1551.3nm at a velocity of 3nm/s. I no third argument specified will use the device's stored one.\n\n autolab driver -D nickname -r 10,30.3,3\n Use now the device nickname as defined in local_config.ini and perform a piezo scan from 10% to 30% with a total period of 3s. If no third argument specified will go as fast as possible.\n \"\"\"\n return usage\n \n def add_parser_arguments(self,parser):\n \"\"\"Add arguments to the parser passed as input\"\"\"\n parser.add_argument(\"-w\", \"--wavelength\", type=str, dest=\"wavelength\", default=None, help=\"Set the wavelength value.\" )\n parser.add_argument(\"-x\", \"--scan_wavelength\", type=str, dest=\"scan_wavelength\", default=None, help=\"Set the wavelength scan values and start a scan. Arguments are: min,max,speed (1 is the start wavelength, 2 is the stop wavelength, 3 is the scan speed in nm/s).\" )\n parser.add_argument(\"-p\", \"--piezo\", type=str, dest=\"piezo\", default=None, help=\"Set the voltage to apply to the piezo in percent.\" )\n parser.add_argument(\"-r\", \"--scan_piezo\", type=str,dest=\"scan_piezo\", default=None, help=\"Set the values for the piezo scan and start a scan. Arguments are: min,max,time_scan (1 is the piezo start value, 2 is the piezo stop value, 3 is the total scan period).\" )\n \n return parser\n\n def do_something(self,args):\n if args.wavelength:\n getattr(self.Instance,'wavelength')(args.wavelength)\n if args.piezo:\n getattr(self.Instance,'set_piezo')(args.piezo)\n if args.scan_wavelength:\n scan_wavelength = args.scan_wavelength.split(',')\n if len(scan_wavelength) == 3:\n getattr(self.Instance,'set_scan_forward_velocity')(scan_wavelength[2])\n getattr(self.Instance,'set_scan_backward_velocity')(scan_wavelength[2])\n elif len(scan_wavelength)!=2:\n print('Please provide 2 or 3 values for the scan')\n sys.exit()\n getattr(self.Instance,'set_scan_start_wavelength')(scan_wavelength[0])\n getattr(self.Instance,'set_scan_stop_wavelength')(scan_wavelength[1])\n getattr(self.Instance,'start_scan_wavelength')() # starts wavelength scan\n sys.exit()\n if args.scan_piezo:\n getattr(self.Instance,'ramp_scanpiezo')(args.scan_piezo.split(','))\n sys.exit()\n\n\n def exit(self):\n #self.Instance.close()\n pass\n","sub_path":"newport_TLB6700/1.0.0/newport_TLB6700_utilities.py","file_name":"newport_TLB6700_utilities.py","file_ext":"py","file_size_in_byte":3278,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"60148288","text":"#!/usr/bin/env python\n# coding: utf-8\nimport numpy as np\n\ndef construct_matrices(F, T, sigma):\n J, K = F.shape # F = observed fluxes, J = no. cameras, K = no. observations\n J1, K1, N = T.shape # T = common mode trends, N = no. trends (per camera)\n J2, K2 = sigma.shape # sigma = flux uncertainties\n assert J2 == J1 == J\n assert K2 == K1 == K\n M = J * N\n w = 1. / sigma**2\n Fw = F * w \n Cinv = np.diag(1./w.sum(axis=0))\n D = np.zeros((K,M))\n E = np.zeros((M,M))\n for j in range(J):\n for n1 in range(N): \n m1 = j * N + n1\n for k in range(K):\n D[k,m1] = T[j,k,n1] / sigma[j,k]**2\n for n2 in range(N):\n m2 = j * N + n2 \n E[m1, m2] = (T[j,:,n1] * T[j,:,n2] * w[j,:]).sum()\n y = np.zeros(M+K)\n y[:K] = Fw.sum(axis=0)\n for j in range(J):\n FwT = Fw[j,:][:,None] * T[j,:,:]\n y[K+j*N:K+(j+1)*N] = FwT.sum(axis=0)\n return Cinv, D, E, y\n\nfrom scipy.linalg import inv\n#from pyaneti import cholesky_inv_det, inverse,invert_multi_gp_matrix\ndef solve(F, T, sigma):\n J, K = F.shape # F = observed fluxes, J = no. cameras, K = no. observations\n J1, K1, N = T.shape # T = common mode trends, N = no. trends (per camera)\n J2, K2 = sigma.shape # sigma = flux uncertainties\n assert J2 == J1 == J\n assert K2 == K1 == K\n Cinv, D, E, y = construct_matrices(F, T, sigma)\n CinvD = np.dot(Cinv, D)\n DTCinvD = np.dot(D.T, CinvD)\n E_DTCinvD = E - DTCinvD\n E_DTCinvD_inv = inv(E_DTCinvD)\n bottomright = E_DTCinvD_inv\n topright = - np.dot(Cinv,np.dot(D,E_DTCinvD_inv))\n bottomleft = topright.T\n topleft = Cinv + np.dot(Cinv, np.dot(D, -bottomleft))\n Xinv = np.zeros((K+J*N,K+J*N))\n Xinv[:K,:K] = topleft\n Xinv[:K,K:] = topright\n Xinv[K:,:K] = bottomleft\n Xinv[K:,K:] = bottomright\n p = np.dot(Xinv,y)\n J, K, N = T.shape\n a = p[:K]\n w = p[K:].reshape((J,N))\n B = np.zeros((J,K))\n for j in range(J):\n for n in range(N):\n B[j,:] += w[j,n] * T[j,:,n]\n return a, w, B, (Cinv, D, E, y, CinvD, DTCinvD, E_DTCinvD, E_DTCinvD_inv, bottomright, topright, bottomleft, topleft, Xinv, p)\n\n#Functions to correct the data using the CBVs\n\n#Merit function definition -> http://mathworld.wolfram.com/MeritFunction.html\n#Calculate the least squares between the raw flux and the basis vectors with a given set of parameters\n#to be called by CBVCorrector\ndef merit_function(pars,flux,basis,n=2):\n squares = [0.0]*len(flux)\n for i in range(len(flux)):\n dummy = 0.0\n for j in range(len(basis)):\n dummy += pars[j]*basis[j][i]\n squares[i] = (abs(flux[i] - dummy))**n\n return np.sum(squares)\n\n#Fucntion that corrects the flux \"flux\" given a set of CVBs \"basis\"\nfrom scipy.optimize import fmin, minimize\ndef CBVCorrector(flux,basis):\n pars = [1.]*len(basis)\n #print(\"Correcting with {} basis vectors\".format(len(basis)))\n pars = minimize(merit_function,pars,args=(flux,basis))\n new_flux = np.array(flux)\n #print('Coefficients = {}'.format(pars.x))\n #correct the raw flux with basis vectors\n for i in range(len(pars.x)):\n new_flux = new_flux - pars.x[i]*basis[i]\n return new_flux","sub_path":"soft/republic_v1.py","file_name":"republic_v1.py","file_ext":"py","file_size_in_byte":3270,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"483479952","text":"import loginSystem\r\nimport queuesSystem\r\n\r\nclass User:\r\n def __init__(self):\r\n self.name = \"\"\r\n self.admin = False\r\n def __str__(self):\r\n return self.name\r\n\r\n \r\ndef loginMenu():\r\n opt = input('''\r\n--Login Menu--\r\n\r\nEnter the number for the option you want to choose\r\n1) Login\r\n2) Sign up\r\n\r\n[>> ''')\r\n try:\r\n if opt == \"1\":\r\n response = LogSys.login()\r\n if response == 'esc':\r\n loginMenu()\r\n else:\r\n user.name = response\r\n storeSelector(user.name)\r\n if opt == \"2\":\r\n LogSys.signup()\r\n loginMenu()\r\n except:\r\n print(\"\\n\\nThere was an error in the system\\nYou have been returned to the Login Menu\\n\\n\")\r\n loginMenu()\r\n\r\ndef storeSelector(user):\r\n print(\"\\n--Store Selector--\\n\")\r\n for i in range(0,len(qSystem.queues)):\r\n print(str(i+1)+\") \"+list(qSystem.queues.keys())[i])\r\n logoutnum = i+2\r\n print(str(i+2)+\") Logout\")\r\n opt = int(input(\"[>> \"))\r\n if opt == logoutnum:\r\n loginMenu()\r\n elif opt >= 1 and opt <= logoutnum-1:\r\n queueMenu(user, list(qSystem.queues.keys())[opt-1])\r\n else:\r\n print(\"\\nThat is not an option\\n\")\r\n storeSelector(user)\r\n \r\ndef queueMenu(user, store):\r\n opt = input('''\r\n--Main Menu--\r\n\r\nEnter the number for the option you want to choose\r\n1) View slots\r\n2) Claim a slot\r\n3) Cancel a slot\r\n4) Return to store select\r\n5) Logout\r\n\r\n[>> ''')\r\n if opt == \"1\":\r\n qSystem.displaySlots(store)\r\n input(\"Press enter to return to the main menu\")\r\n queueMenu(user, store)\r\n if opt == \"2\":\r\n qSystem.displaySlots(store)\r\n response = qSystem.claimSlot(store,input(\"\\nEnter the time you want to claim exactly as it appears on the screen [>> \"),user)\r\n qSystem.updateCSV()\r\n print(response)\r\n input(\"Press enter to return to the main menu\")\r\n queueMenu(user, store)\r\n if opt == \"3\":\r\n qSystem.displaySlots(store)\r\n response = qSystem.cancelSlot(store,input(\"\\nEnter the time you want to cancel exactly as it appears on the screen [>> \"),user)\r\n qSystem.updateCSV()\r\n print(response)\r\n input(\"Press enter to return to the main menu\")\r\n queueMenu(user, store)\r\n if opt == \"4\":\r\n storeSelector(user)\r\n if opt == \"5\":\r\n loginMenu()\r\n \r\nLogSys = loginSystem.System(\"users.csv\")\r\nuser = User()\r\nqSystem = queuesSystem.QueueSystem(\"queuesSS\")\r\n\r\nloginMenu()\r\n","sub_path":"Fernley_Virtual_Queue/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":2539,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"506639081","text":"#!/usr/bin/env python3\n\nimport socket\nimport pyDH\nimport base64\nimport hashlib\nfrom Crypto import Random\nfrom Crypto.Cipher import AES\nimport socks\n\n\nclass AESCipher(object):\n\n def __init__(self, key): \n self.bs = AES.block_size\n self.key = hashlib.sha256(key.encode()).digest()\n\n def encrypt(self, raw):\n raw = self._pad(raw)\n iv = Random.new().read(AES.block_size)\n cipher = AES.new(self.key, AES.MODE_CBC, iv)\n return base64.b64encode(iv + cipher.encrypt(raw.encode()))\n\n def decrypt(self, enc):\n enc = base64.b64decode(enc)\n iv = enc[:AES.block_size]\n cipher = AES.new(self.key, AES.MODE_CBC, iv)\n return self._unpad(cipher.decrypt(enc[AES.block_size:])).decode('utf-8')\n\n def _pad(self, s):\n return s + (self.bs - len(s) % self.bs) * chr(self.bs - len(s) % self.bs)\n\n @staticmethod\n def _unpad(s):\n return s[:-ord(s[len(s)-1:])]\n\nHOST = '127.0.0.1'\nPORT = 65431 \n\n\nd1 = pyDH.DiffieHellman()\nd1_pubkey = d1.gen_public_key()\n\nwith socks.socksocket(socket.AF_INET, socket.SOCK_STREAM) as s:\n s.set_proxy(socks.SOCKS5, \"0.tcp.ngrok.io\", 18764)\n s.connect((HOST, PORT))\n s.sendall(d1_pubkey.to_bytes(256, byteorder='big'))\n data = s.recv(256)\n print('Received', repr(data))\n d1_sharedkey = d1.gen_shared_key(int.from_bytes(data, \"big\") )\n print(d1_sharedkey)\n\n a = AESCipher(d1_sharedkey)\n z = a.encrypt('hello!')\n s.sendall(z)\n\n\n","sub_path":"CryptoProtocol/Lab1_DH/alice.py","file_name":"alice.py","file_ext":"py","file_size_in_byte":1469,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"545195038","text":"from .models import Day, NORMAL, BOOSTED, POWER_ITEM, POWER_ADD_ON\n\n\ndef get_only_unique_and_same(pokemons):\n #!!!!!! This is partially bad cause I'm splitting up unique in to pieces of\n #!!!!!! 10 but same is getting checking for all of them when it shouldn't\n #!!!!!! would need to reevaluate the module as a whole so I will defer it\n checked = []\n unique = [[],]\n same = [[],]\n same_checks = [[],]\n unique_index = 0\n for pokemon in pokemons:\n only_pokemon_name = pokemon.rsplit(POWER_ADD_ON)[0]\n if only_pokemon_name not in checked:\n checked.append(only_pokemon_name)\n if len(unique[unique_index]) == 10:\n unique_index += 1\n unique.append([])\n unique[unique_index].append(pokemon)\n else:\n added = False\n for i in range(0, len(same_checks)):\n if only_pokemon_name not in same_checks[i]:\n same_checks[i].append(only_pokemon_name)\n same[i].append(pokemon)\n added = True\n break\n if not added:\n same_checks.append([only_pokemon_name])\n same.append([pokemon])\n\n return unique + same\n\ndef get_ordered_common_stat_ev(stat, stat_map):\n if stat_map is None or stat not in stat_map:\n return None\n else:\n stat_evs = stat_map[stat]\n max_ev = []\n stat_ev_list = list(stat_evs.keys())\n while len(stat_ev_list) > 0:\n next_ev = None\n next_ev_num = 0\n for j in range(0, len(stat_ev_list)):\n ev = stat_ev_list[j]\n ev_num = len(get_only_unique_and_same(stat_evs[ev])[0])\n if next_ev is None:\n next_ev = ev\n next_ev_num = ev_num\n elif ev_num > next_ev_num:\n next_ev = ev\n max_ev.append(next_ev)\n stat_ev_list.remove(next_ev)\n return max_ev\n\ndef return_best_stat_ev(stat, ordered_evs, used, team, stat_map):\n target_stat = stat_map[stat]\n max_available_team = None\n max_available_ev = None\n for ev in ordered_evs:\n job_teams = get_only_unique_and_same(target_stat[ev])\n for job_team in job_teams:\n valid_job_team = True\n for pokemon in job_team:\n valid_job_team = valid_job_team and pokemon.rsplit(POWER_ADD_ON)[0] not in used\n if len(job_team) > 0 and valid_job_team and (max_available_ev is None or len(job_team) > len(max_available_team)):\n max_available_team = job_team\n max_available_ev = ev\n\n if max_available_ev is not None:\n target_team = target_stat[max_available_ev]\n is_done = len(max_available_team) == len(target_team)\n for pokemon in max_available_team:\n used.append(pokemon.rsplit(POWER_ADD_ON)[0])\n if not is_done:\n target_team.remove(pokemon)\n if is_done:\n del target_stat[max_available_ev]\n\n return max_available_ev, max_available_team\n\n\ndef optimal_calc(team, stat_map):\n best_days = []\n needed_stats = [stat for stat in stat_map if len(stat_map[stat]) > 0]\n team_names = [pokemon.get_unique_name() for pokemon in team]\n\n while(len(needed_stats) > 0):\n day = Day()\n enlisted = []\n stat_index = 0\n while stat_index < len(needed_stats) and len(enlisted) < len(team):\n stat = needed_stats[stat_index]\n target_stat = stat_map[stat]\n ordered_ev_stats = get_ordered_common_stat_ev(stat, stat_map)\n ev, pokemon_needed = return_best_stat_ev(stat, ordered_ev_stats, enlisted, team, stat_map)\n if ev is not None:\n day.jobs[stat] = (ev, pokemon_needed)\n stat_index += 1\n\n best_days.append(day)\n needed_stats = [stat for stat in stat_map if len(stat_map[stat]) > 0]\n\n # Reorder days based on length for calendar\n best_days.sort(key=lambda day : day.get_total_pokemon(), reverse=True)\n for i in range(0,len(best_days)):\n day = best_days[i]\n day.num = i+1\n # print(\"Day\",day.get_num(), day.get_total_pokemon())\n # for stat in day.get_jobs():\n # print(\"\\t\",stat, day.get_jobs()[stat])\n Day.num = 0\n return best_days\n\n#Test\ndef check_days_number(team, days):\n expected_count = 0\n for pokemon in team:\n ev_calc = pokemon.get_ev_calcs()\n for stat in ev_calc:\n expected_count += len(ev_calc[stat][1])\n\n actual_count = 0\n for day in days:\n for stat in day.get_jobs():\n actual_count += len(day.get_jobs()[stat][1])\n return actual_count == expected_count\n\n#Test\ndef get_power_items_and_check(team, days):\n name_pokemon = {pokemon.get_unique_name() : pokemon for pokemon in team}\n stat_max_power_item = { 'HP':0, 'Atk':0, 'Def':0, 'SpA':0, 'SpD':0, 'Spe':0 }\n for day in days:\n for stat in day.get_jobs():\n amount, pokemons = day.get_jobs()[stat]\n current_power_item = 0\n for pokemon in pokemons:\n indiv_amount = amount\n if POWER_ADD_ON in pokemon:\n indiv_amount = BOOSTED[NORMAL.index(amount)]\n current_power_item += 1\n pokemon_name = pokemon.rsplit(POWER_ADD_ON)[0]\n actual_pokemon = name_pokemon[pokemon_name]\n actual_pokemon.subtract_evs(stat, indiv_amount)\n if stat_max_power_item[stat] < current_power_item:\n stat_max_power_item[stat] = current_power_item\n all_zero = True\n for pokemon in team:\n all_zero = all_zero and pokemon.has_no_evs()\n\n actual_power_items = [[POWER_ITEM[stat], stat_max_power_item[stat]] for stat in POWER_ITEM]\n\n return actual_power_items, all_zero\n","sub_path":"EVCalcApp/ev_calc.py","file_name":"ev_calc.py","file_ext":"py","file_size_in_byte":5882,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"86039681","text":"## Simple Berechnung der Distanz zweier Punkte anhand ihrer\n## Geokoordinaten.\nfrom math import radians, sin, cos, acos\n\n\ndef geodist(P1, P2):\n \"\"\"Berechnet die Entfernung in [km] zweier Punkte auf der Erdoberfläche.\n Die Punkte P1 und P2 müssen als Tupel zweier Geokoordinaten vorliegen,\n also beispielsweise (52.1234, 7.8901).\"\"\"\n L1, B1 = map(radians, P1)\n L2, B2 = map(radians, P2)\n return 6378.388 * acos(sin(L1) * sin(L2)\n + cos(L1) * cos(L2) * cos(B2-B1))\n\n\t\t\t\t\t\n\t\t\t\t\t\t \n\"\"\"\nif __name__==\"__main__\":\n Dortmund = 51.51, 7.47\n Berlin = 52.52, 13.4\n Entfernung = geodist(Dortmund, Berlin)\n print(f\"Entfernung Dortmund-Berlin: {Entfernung:.2f} km\")\n\"\"\" \n\n","sub_path":"geodist.py","file_name":"geodist.py","file_ext":"py","file_size_in_byte":718,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"251253915","text":"# -*- coding: utf-8 -*-\nfrom __future__ import unicode_literals\n\nfrom django.db import models, migrations\nimport django.utils.timezone\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('bookmark', '0001_initial'),\n ]\n\n operations = [\n migrations.CreateModel(\n name='Click',\n fields=[\n ('id', models.AutoField(auto_created=True, verbose_name='ID', primary_key=True, serialize=False)),\n ('time', models.DateTimeField(null=True, default=django.utils.timezone.now)),\n ('address', models.CharField(null=True, max_length=500)),\n ('browser', models.CharField(null=True, max_length=500)),\n ('user', models.IntegerField(null=True, max_length=255)),\n ('bookmark', models.ForeignKey(to='bookmark.Bookmark')),\n ],\n ),\n ]\n","sub_path":"urlybird/click/migrations/0001_initial.py","file_name":"0001_initial.py","file_ext":"py","file_size_in_byte":877,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"517710303","text":"from src.pynflate.lz77 import Lz77\nfrom src.pynflate.lz77 import Codeword\n\n\nclass TestLz77(object):\n def test_empty(self):\n lz77 = Lz77(6)\n codewords = list(lz77.compress(''))\n assert codewords == []\n\n def test_one_char(self):\n lz77 = Lz77(6)\n original = 'x'\n\n codewords = list(lz77.compress(original))\n assert codewords == [(0, 0, 'x')]\n\n decompressed = lz77.decompress(codewords)\n assert decompressed == original\n\n def test_all_same(self):\n lz77 = Lz77(6)\n original = 'xxxxxxxxxx'\n\n codewords = list(lz77.compress(original))\n assert codewords == [(0, 0, 'x'), (1, 8, 'x')]\n\n decompressed = lz77.decompress(codewords)\n assert decompressed == original\n\n def test_nothing_special(self):\n lz77 = Lz77(6)\n # https://www.cs.cmu.edu/afs/cs/project/pscico-guyb/realworld/www/slidesF08/suffixcompress.pdf\n original = 'aacaacabcabaaac'\n\n codewords = list(lz77.compress(original))\n assert codewords == [(0, 0, 'a'), (1, 1, 'c'), (3, 4, 'b'), (3, 3, 'a'), (1, 2, 'c')]\n\n decompressed = lz77.decompress(codewords)\n assert decompressed == original\n\n # 0<=0 1<=4 2<=5 4<=7 0<=0\n codewords = [(0, 0, 'a'), (1, 4, 'b'), (2, 5, 'c'), (4, 7, 'd'), (0, 0, 'e')]\n # a\n # back 1 \\|\n # 4 chars: a a a a + b\n # back 2 \\___/\n # 5 chars: a b a b a + c\n # back 4 \\_______/\n # 7 chars: a b a c a b a + d\n # back 0 \\/\n # 0 char: + e\n # aaaaabababacabacabade\n codewords = [Codeword(x[0], x[1], x[2]) for x in codewords]\n tmp = lz77.decompress(codewords)\n # 'aaaaabababacabacabade'\n\n return","sub_path":"tests/test_lz77.py","file_name":"test_lz77.py","file_ext":"py","file_size_in_byte":2030,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"400859786","text":"from __future__ import annotations\nfrom typing import Tuple, Any, TYPE_CHECKING\n#from typing import List, Dict, Tuple, Union, Any\n\nimport numpy as np\nimport scipy.sparse as sci_sparse\n\nfrom .utils import lambda1d\nif TYPE_CHECKING: # pragma: no cover\n from pyNastran.bdf.bdf import BDF\n\n\ndef build_Kbb(model: BDF, dof_map, ndof, dtype='float32') -> Tuple[np.array, Any]:\n \"\"\"[K] = d{P}/dx\"\"\"\n Kbb = np.zeros((ndof, ndof), dtype=dtype)\n Kbbs = sci_sparse.dok_matrix((ndof, ndof), dtype=dtype)\n #print(dof_map)\n\n #_get_loadid_ndof(model, subcase_id)\n nelements = 0\n nelements += _build_kbb_celas1(model, Kbb, Kbbs, dof_map)\n nelements += _build_kbb_celas2(model, Kbb, Kbbs, dof_map)\n nelements += _build_kbb_conrod(model, Kbb, Kbbs, dof_map)\n nelements += _build_kbb_crod(model, Kbb, Kbbs, dof_map)\n nelements += _build_kbb_ctube(model, Kbb, Kbbs, dof_map)\n nelements += _build_kbb_cbar(model, Kbb, Kbbs, dof_map)\n assert nelements > 0, nelements\n Kbbs2 = Kbbs.tocsc()\n Kbb2 = Kbbs2.toarray()\n error = np.linalg.norm(Kbb - Kbb2)\n if error > 1e-12:\n model.log.warning(f'error = {error}')\n return Kbb, Kbbs2\n\n\ndef _build_kbb_celas1(model: BDF, Kbb, Kbbs, dof_map):\n \"\"\"fill the CELAS1 Kbb matrix\"\"\"\n celas1s = model._type_to_id_map['CELAS1']\n for eid in celas1s:\n elem = model.elements[eid]\n ki = elem.K()\n #print(elem, ki)\n #print(elem.get_stats())\n _build_kbbi_celas12(Kbb, Kbbs, dof_map, elem, ki)\n return len(celas1s)\n\ndef _build_kbb_celas2(model: BDF, Kbb, Kbbs, dof_map):\n \"\"\"fill the CELAS2 Kbb matrix\"\"\"\n celas2s = model._type_to_id_map['CELAS2']\n #celas3s = model._type_to_id_map['CELAS3']\n #celas4s = model._type_to_id_map['CELAS4']\n for eid in celas2s:\n elem = model.elements[eid]\n ki = elem.K()\n #print(elem, ki)\n #print(elem.get_stats())\n _build_kbbi_celas12(Kbb, Kbbs, dof_map, elem, ki)\n return len(celas2s)\n\ndef _build_kbbi_celas12(Kbb, Kbbs, dof_map, elem, ki):\n \"\"\"fill the CELASx Kbb matrix\"\"\"\n nid1, nid2 = elem.nodes\n c1, c2 = elem.c1, elem.c2\n i = dof_map[(nid1, c1)]\n j = dof_map[(nid2, c2)]\n k = ki * np.array([[1, -1,],\n [-1, 1]])\n ibe = [\n (i, 0),\n (j, 1),\n ]\n for ib1, ie1 in ibe:\n for ib2, ie2 in ibe:\n Kbb[ib1, ib2] += k[ie1, ie2]\n Kbbs[ib1, ib2] += k[ie1, ie2]\n #Kbb[j, i] += ki\n #Kbb[i, j] += ki\n #del i, j, ki, nid1, nid2, c1, c2\n\ndef _build_kbb_cbar(model, Kbb, Kbbs, dof_map):\n \"\"\"fill the CBAR Kbb matrix\"\"\"\n cbars = model._type_to_id_map['CBAR']\n for eid in cbars:\n elem = model.elements[eid]\n pid_ref = elem.pid_ref\n mat = pid_ref.mid_ref\n _build_kbbi_conrod_crod(Kbb, Kbbs, dof_map, elem, mat)\n return len(cbars)\n\ndef _build_kbb_crod(model, Kbb, Kbbs, dof_map):\n \"\"\"fill the CROD Kbb matrix\"\"\"\n crods = model._type_to_id_map['CROD']\n for eid in crods:\n elem = model.elements[eid]\n pid_ref = elem.pid_ref\n mat = pid_ref.mid_ref\n _build_kbbi_conrod_crod(Kbb, Kbbs, dof_map, elem, mat)\n return len(crods)\n\ndef _build_kbb_ctube(model: BDF, Kbb, Kbbs, dof_map):\n \"\"\"fill the CTUBE Kbb matrix\"\"\"\n ctubes = model._type_to_id_map['CTUBE']\n for eid in ctubes:\n elem = model.elements[eid]\n pid_ref = elem.pid_ref\n mat = pid_ref.mid_ref\n _build_kbbi_conrod_crod(Kbb, Kbbs, dof_map, elem, mat)\n return len(ctubes)\n\ndef _build_kbb_conrod(model: BDF, Kbb, Kbbs, dof_map):\n \"\"\"fill the CONROD Kbb matrix\"\"\"\n conrods = model._type_to_id_map['CONROD']\n for eid in conrods:\n elem = model.elements[eid]\n mat = elem.mid_ref\n _build_kbbi_conrod_crod(Kbb, Kbbs, dof_map, elem, mat)\n return len(conrods)\n\ndef _build_kbbi_conrod_crod(Kbb, Kbbs, dof_map, elem, mat, fdtype='float64'):\n \"\"\"fill the ith rod Kbb matrix\"\"\"\n nid1, nid2 = elem.nodes\n #mat = elem.mid_ref\n xyz1 = elem.nodes_ref[0].get_position()\n xyz2 = elem.nodes_ref[1].get_position()\n dxyz12 = xyz1 - xyz2\n L = np.linalg.norm(dxyz12)\n E = mat.E\n G = mat.G()\n J = elem.J()\n A = elem.Area()\n E = elem.E()\n #L = elem.Length()\n k_axial = A * E / L\n k_torsion = G * J / L\n\n assert isinstance(k_axial, float), k_axial\n assert isinstance(k_torsion, float), k_torsion\n #Kbb[i, i] += ki[0, 0]\n #Kbb[i, j] += ki[0, 1]\n #Kbb[j, i] = ki[1, 0]\n #Kbb[j, j] = ki[1, 1]\n k = np.array([[1., -1.],\n [-1., 1.]]) # 1D rod\n Lambda = lambda1d(dxyz12, debug=False)\n K = Lambda.T @ k @ Lambda\n #i11 = dof_map[(n1, 1)]\n #i12 = dof_map[(n1, 2)]\n\n #i21 = dof_map[(n2, 1)]\n #i22 = dof_map[(n2, 2)]\n\n nki, nkj = K.shape\n K2 = np.zeros((nki*2, nkj*2), dtype=fdtype)\n\n i1 = 0\n i2 = 3 # dof_map[(n1, 2)]\n if k_torsion == 0.0: # axial; 2D or 3D\n K2 = K * k_axial\n n_ijv = [\n # axial\n dof_map[(nid1, 1)], dof_map[(nid1, 2)], dof_map[(nid1, 3)],\n dof_map[(nid2, 1)], dof_map[(nid2, 2)], dof_map[(nid2, 3)],\n ]\n dofs = np.array([\n i1, i1+1, i1+2,\n i2, i2+1, i2+2,\n ], dtype='int32')\n elif k_axial == 0.0: # torsion; assume 3D\n K2 = K * k_torsion\n n_ijv = [\n # torsion\n dof_map[(nid1, 4)], dof_map[(nid1, 5)], dof_map[(nid1, 6)],\n dof_map[(nid2, 4)], dof_map[(nid2, 5)], dof_map[(nid2, 6)],\n ]\n dofs = np.array([\n i1, i1+1, i1+2,\n i2, i2+1, i2+2,\n ], dtype='int32')\n else: # axial + torsion; assume 3D\n # u1fx, u1fy, u1fz, u2fx, u2fy, u2fz\n K2[:nki, :nki] = K * k_axial\n\n # u1mx, u1my, u1mz, u2mx, u2my, u2mz\n K2[nki:, nki:] = K * k_torsion\n\n dofs = np.array([\n i1, i1+1, i1+2,\n i2, i2+1, i2+2,\n\n i1+3, i1+4, i1+5,\n i2+3, i2+4, i2+5,\n ], dtype='int32')\n n_ijv = [\n # axial\n dof_map[(nid1, 1)], dof_map[(nid1, 2)], dof_map[(nid1, 3)],\n dof_map[(nid2, 1)], dof_map[(nid2, 2)], dof_map[(nid2, 3)],\n\n # torsion\n dof_map[(nid1, 4)], dof_map[(nid1, 5)], dof_map[(nid1, 6)],\n dof_map[(nid2, 4)], dof_map[(nid2, 5)], dof_map[(nid2, 6)],\n ]\n for dof1, i1 in zip(dofs, n_ijv):\n for dof2, i2 in zip(dofs, n_ijv):\n ki = K2[dof1, dof2]\n if abs(ki) > 0.:\n #print(nij1, nij2, f'({i1}, {i2});', (dof1, dof2), ki)\n Kbb[i1, i2] = ki\n Kbbs[i1, i2] = ki\n #print(K2)\n #print(Kbb)\n return\n","sub_path":"pyNastran/dev/solver/build_stiffness.py","file_name":"build_stiffness.py","file_ext":"py","file_size_in_byte":6681,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"418236859","text":"#how to multiply very large numbers\n\ndef multiply(x, res,res_size): \n '''\n Multiply very large numbers like factorials.\n Multiplies x with the number represented by res[]. \n res_size is size of res[] \n or number of digits in the number represented \n by res[]. Uses simple old school \n mathematics for multiplication. \n https://www.geeksforgeeks.org/factorial-large-number/\n '''\n carry = 0 # Initialize carry \n \n # One by one multiply n with individual \n # digits of res[] \n i = 0\n while i < res_size : \n prod = res[i] * x + carry \n res[i] = prod % 10 # Store last digit of \n # 'prod' in res[] \n carry = prod/10 # Put rest in carry \n i = i + 1\n \n # Put carry in res and increase result size \n while (carry) : \n res[res_size] = carry % 10\n carry = carry / 10\n res_size = res_size + 1\n \n return res_size \n\nif __name__ == \"__main__\":\n res = [None]*500\n # Initialize result \n res[0] = 1\n res_size = 1\n x = 2\n n = 100\n while x < n:\n res_size = multiply(x, res, res_size) \n x += 1\n\n #print (res)\n print (res_size)\n\n s = \"\"\n resout = res[:res_size]\n print (resout)\n for z in resout:\n s += str(z)\n\n sum = 0\n for z in resout:\n sum += z\n\n print (sum)\n print (s[::-1])\n \n","sub_path":"euler/multiply_and_factorial.py","file_name":"multiply_and_factorial.py","file_ext":"py","file_size_in_byte":1389,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"352113027","text":"\"\"\"statsproject URL Configuration\n\nThe `urlpatterns` list routes URLs to views. For more information please see:\n https://docs.djangoproject.com/en/1.11/topics/http/urls/\nExamples:\nFunction views\n 1. Add an import: from my_app import views\n 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home')\nClass-based views\n 1. Add an import: from other_app.views import Home\n 2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home')\nIncluding another URLconf\n 1. Import the include() function: from django.conf.urls import url, include\n 2. Add a URL to urlpatterns: url(r'^blog/', include('blog.urls'))\n\"\"\"\nfrom django.conf.urls import url\nfrom django.contrib import admin\nfrom django.conf import settings\nfrom django.conf.urls.static import static\nfrom statsapp import views\n#from statsapp.views import MyPDFView\nfrom accounts import views as accounts_views\nfrom upload import views as dataset_upload_views\nfrom charts import views as chart_views\nfrom process import views as process_views\nfrom statistical import views as statistical_views\nfrom django.contrib.auth import views as auth_views\n#from wkhtmltopdf.views import PDFTemplateView\n\nurlpatterns = [\n\turl(r'^$', views.home, name='home'),\n\turl(r'^test/$', views.hometest, name='main'),\n\turl(r'^makeCol/$', dataset_upload_views.makeCol, name='makeCol'),\n\turl(r'^signup/$', accounts_views.signup, name='signup'),\n\t#\turl(r'^signup_success/$', accounts_views.signup_success, name='signup-success'),\n\turl(r'^login/$', auth_views.LoginView.as_view(template_name='login.html'), name='login'),\n\turl(r'^logout/$', auth_views.LogoutView.as_view(), name='logout'),\n\turl(r'^dataset/$', views.datasetlist, name='datasetlist'),\n\turl(r'^api/data/$', views.get_data, name='api-data'),\n\turl(r'^charts/$', chart_views.chart, name='chart'),\n\turl(r'^chart/(?P\\D+)/$', chart_views.get_visualization,name='visualization'),\n\turl(r'^saveGraph/$', chart_views.saveVisualization,name='save-visualization'),\n\turl(r'^getVisualization/$', chart_views.getVisualizationList,name='get-visualization'),\n\turl(r'^api/chart/data/(?P\\D+)/$', chart_views.visualization_data,name='visualization-data'),\n\turl(r'^api/chart/data/(?P\\D+)/(?P\\D+)/$', chart_views.get_data,name='chart-data'),\n\turl(r'^chart/(?P\\D+)/(?P\\D+)/$', chart_views.makechart, name='aschart'),\n\turl(r'^upload/$', dataset_upload_views.upload, name='upload'),\n\turl(r'^giveDatasetName/$', dataset_upload_views.giveDatasetName, name='give-dataset-name'),\n\turl(r'^upload/fileType/$', dataset_upload_views.submitFiletype, name='submitFiletype'),\n\turl(r'^upload/dataType/$', dataset_upload_views.changeDataTypeInMongo, name='submitDatatype'),\n\turl(r'^getDataset/$', chart_views.getDataset, name='getDataset'),\n\turl(r'^getGraphFields/$', chart_views.getGraphFields, name='getGraphFields'),\n\turl(r'^getGraphData/$', chart_views.getGraphData, name='getGraphData'),\n\turl(r'^makeProcess/$', process_views.makeProcess, name='makeProcess'),\n\turl(r'^getProcess/$', process_views.getProcess, name='getProcess'),\n\turl(r'^getProcessList/$', process_views.getProcessList, name='getProcessList'),\n\turl(r'^delete/(?P\\w+)/$', dataset_upload_views.deleteDataset,name='deleteDataset'),\n\turl(r'^updateVisualization/$', chart_views.editVisualisation, name='editVisualisation'),\n\turl(r'^delVisualization/(?P\\d+)/$', chart_views.delVisualization,name='delete-visualization'),\n\turl(r'^admin/', admin.site.urls),\n\turl(r'^account_activation_sent/$', accounts_views.account_activation_sent, name='account_activation_sent'),\n\turl(r'^activate/(?P[0-9A-Za-z_\\-]+)/(?P[0-9A-Za-z]{1,13}-[0-9A-Za-z]{1,20})/$',\n\t\taccounts_views.activate, name='activate'),\n\t#url(r'^pdf/$', PDFTemplateView.as_view(template_name='pdftest.html',filename='mypdf.pdf'), name='pdf'),\t\n\t#url(r'^pdfresponse/$',MyPDFView.as_view(), name='pdfresponse'),\n\turl(r'^mysqlconnect/$', dataset_upload_views.mysqlconnect, name='mySqlConnector'),\n\turl(r'^saveStatistics/$',statistical_views.saveStatistics,name='saveStatistics'),\n\turl(r'^calculateStatistics/$',statistical_views.calculateStatistics,name='calculateStatistics'),\n\turl(r'^getStatistical/$', statistical_views.getStatisticalList,name='getStatistical'),\t\n\turl(r'^delStatistical/(?P\\d+)/$', statistical_views.delStatistical,name='delete-statistical'),\n\t\n\t#analytical urls\n\turl(r'^saveAnalytics/$',statistical_views.saveAnalytics,name='saveAnalytics'),\n\turl(r'^calculateAnalytics/$',statistical_views.calculateAnalytics,name='calculateAnalytics'),\n\turl(r'^getAnalytical/$', statistical_views.getAnalyticalList,name='getAnalytical'),\t\n\turl(r'^delAnalytical/(?P\\d+)/$', statistical_views.delAnalytical,name='delete-analytical'),\n\n]\nif settings.DEBUG:\n\turlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)","sub_path":"statsproject/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":4859,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"286764318","text":"from flask import Blueprint, abort, jsonify\n\nfrom firestormd.ui.services import media_service\nfrom firestormd.media.exceptions import (\n NoMediaFoundError,\n NoMediaLoadedError,\n NoMediaPlayingError,\n MediaAlreadyPlayingError\n)\n\nplayer_blueprint = Blueprint(\"player\", __name__, url_prefix=\"/api/player\")\n\n\n@player_blueprint.route(\"/\", methods=[\"GET\"])\ndef get_player_status():\n return jsonify(media_service.get_player_status())\n\n\n@player_blueprint.route(\"/load/\", methods=[\"POST\"])\ndef load_media(media_id):\n try:\n media_service.load_media_by_id(media_id)\n return jsonify({\"status\": \"ok\"})\n except NoMediaFoundError:\n abort(404)\n\n\n@player_blueprint.route(\"/play\", methods=[\"POST\"])\ndef play_media():\n try:\n media_service.play_loaded_media()\n return jsonify({\"status\": \"ok\"})\n except NoMediaFoundError:\n abort(404)\n except NoMediaLoadedError:\n abort(400)\n except MediaAlreadyPlayingError:\n abort(400)\n\n\n@player_blueprint.route(\"/pause\", methods=[\"POST\"])\ndef pause_current_media():\n try:\n media_service.pause_loaded_media()\n return jsonify({\"status\": \"ok\"})\n except NoMediaLoadedError:\n abort(400)\n except NoMediaPlayingError:\n abort(400)\n\n\n@player_blueprint.route(\"/stop\", methods=[\"POST\"])\ndef stop_current_media():\n try:\n media_service.stop_loaded_media()\n return jsonify({\"status\": \"ok\"})\n except NoMediaLoadedError:\n abort(400)\n","sub_path":"firestormd/ui/resources/playerresource.py","file_name":"playerresource.py","file_ext":"py","file_size_in_byte":1498,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"101668886","text":"'''\nCreated on Mar 8, 2012\n\n@author: mikekan\n'''\n\nimport sqlite3\nfrom user import User\n\nfrom datetime import date\nimport logging\n\nlogger = logging.getLogger(\"auth\")\n\nclass UserStore(object):\n _instance = None\n _connection = None\n database_path = ':memory:'\n \n def __new__(cls, *args, **kwargs):\n if not cls._instance:\n cls._instance = super(UserStore, cls).__new__(\n cls, *args, **kwargs)\n return cls._instance\n \n def __init__(self):\n pass\n \n def __get_connection__(self):\n if (self._connection == None):\n logger.debug('Initializing sqlite3 db.')\n self._connection = sqlite3.connect(self.database_path)\n return self._connection\n \n def __get_cursor__(self):\n return self.__get_connection__().cursor()\n \n def close(self):\n if self._connection != None:\n try:\n self._connection.close()\n self._connection = None\n except:\n # Do nothing as the connection couldn't close\n pass\n \n def set_database_path(self, database_path):\n if self.database_path != database_path and self._connection != None:\n self.close()\n \n self.database_path = database_path\n cursor = self.__get_cursor__()\n \n # Check if table exists\n query = \"SELECT * FROM sqlite_master WHERE type='table' AND name='user_table'\"\n cursor.execute(query)\n list = cursor.fetchall()\n if (len(list) <= 0):\n # Table does not exist, creating\n logger.debug('User table not found, creating. . . ')\n query = \"CREATE TABLE user_table (\\\n id integer PRIMARY KEY, \\\n first_name text, \\\n last_name text, \\\n email text, \\\n username text, \\\n password text, \\\n creation_date text, \\\n active integer)\"\n \n cursor.execute(query)\n self._connection.commit()\n logger.debug('Done')\n else:\n logger.debug('User table found.')\n \n def has_user(self, user):\n \n if (user._id >= 0):\n query = \"SELECT email FROM user_table WHERE id={0}\".format(user._id)\n users = self.__get_cursor__().execute(query).fetchall()\n return len(users) > 0\n else:\n return False \n \n def is_username_taken(self, username):\n query = \"SELECT id FROM user_table WHERE username='{0}'\".format(username)\n users = self.__get_cursor__().execute(query).fetchall()\n return len(users) > 0\n \n def get_user(self, username):\n cursor = self.__get_cursor__()\n query = \"SELECT * FROM user_table WHERE username='{0}' and active=1\".format(username)\n cursor.execute(query)\n list = cursor.fetchall()\n if len(list) > 0:\n data = list[0]\n # Tuple in order of columns\n # id, first_name, last_name, email, username, password, creation_date, active\n user = User(data[4], data[5])\n user.first_name = data[1]\n user.last_name = data[2]\n user.email = data[3]\n user._id = data[0]\n return user\n else:\n return None\n \n def get_user_by_id(self, id):\n cursor = self.__get_cursor__()\n query = \"SELECT * FROM user_table WHERE id={0} and active=1\".format(id)\n cursor.execute(query)\n list = cursor.fetchall()\n if len(list) > 0:\n data = list[0]\n # Tuple in order of columns\n # id, first_name, last_name, email, username, password, creation_date, active\n user = User(data[4], data[5])\n user.first_name = data[1]\n user.last_name = data[2]\n user.email = data[3]\n user._id = data[0]\n return user\n else:\n return None\n \n def save_user(self, user):\n cursor = self.__get_cursor__()\n if (user._id >= 0):\n # save\n query = \"UPDATE user_table SET \\\n first_name='{first_name}', \\\n last_name='{last_name}', \\\n email='{email}', \\\n username='{username}', \\\n password='{password}', \\\n WHERE id={id}\".format(**user.get_values_as_dict())\n cursor.execute(query)\n self.__get_connection__().commit()\n else:\n # check if it exists, if not create\n query = \"INSERT INTO user_table (\\\n first_name, last_name, email, username, password, creation_date, active) VALUES (\\\n '{first_name}','{last_name}','{email}', '{username}', '{password}','{0}', 1)\\\n \".format(date.today(), **user.get_values_as_dict())\n cursor.execute(query)\n self.__get_connection__().commit()\n user._id = cursor.lastrowid\n \n def deactivate_user(self, user):\n cursor = self.__get_cursor__()\n if (user._id >= 0):\n # set user to be inactive\n query = \"UPDATE user_table SET active=0 WHERE id={id}\".format(**user.get_values_as_dict())\n cursor.execute(query)\n self.__get_connection__().commit()\n \n def is_user_active(self, user):\n cursor = self.__get_cursor__()\n if (user._id >= 0):\n query = \"SELECT * FROM user_table WHERE id={id} and active=1\".format(**user.get_values_as_dict())\n users = self.__get_cursor__().execute(query).fetchall()\n return len(users) > 0\n return False","sub_path":"userstore.py","file_name":"userstore.py","file_ext":"py","file_size_in_byte":5728,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"440918683","text":"# -*- coding: utf-8 -*-\n\nimport git\nimport logging\nimport subprocess\nimport sys\nfrom odoo import api, exceptions, fields, models\n\n_logger = logging.getLogger(__name__)\n\nclass AutoUpdate(models.TransientModel):\n _name = 'auto_update.update'\n\n modules = fields.Char(\n string='Lista de módulos',\n help='Lista sin espacios, modulos separados por coma',\n required=True\n )\n\n @api.multi\n def update_module(self, models=None):\n # NOTE: crear lista limpia de los modulos a actualizar\n modules_list = self.modules.split(',')\n modules_list = [mod.strip() for mod in modules_list if mod.strip() != '']\n\n # NOTE: verificar que los modulas a actualizar existan y esten instalados\n bad_modules = []\n for module in modules_list:\n system_module = self.env['ir.module.module'].search([('name', '=', module)])\n if system_module.state != 'installed':\n bad_modules.append(module)\n elif not system_module:\n bad_modules.append(module)\n\n if bad_modules:\n text = \"Lo siguientes modulos no existen o no están instalados:\\n\"\n for module in bad_modules:\n text += \"{}\\n\".format(module)\n raise exceptions.UserError(text)\n else:\n modules = ','.join(modules_list)\n\n # NOTE: search github configuration or error\n github_config = self.env['github.config'].search([])\n if github_config:\n g = git.cmd.Git(github_config.path)\n\n process = subprocess.Popen('whoami', stdout=subprocess.PIPE)\n stdout = process.communicate()[0]\n _logger.info('-----------USER------')\n _logger.info('USER: {}'.format(stdout))\n try:\n res = g.pull()\n except:\n _logger.error(sys.exc_info()[0])\n raise exceptions.AccessError(\"\"\"Las carpetas del repositorio no tienen los permisos correctos para hacer el pull.\\n\n Por favor corra \\\"chown -R odoo:odoo /path/to/repository\\\" como sudo en su servidor\\n\n y vuelva a intentarlo.\"\"\")\n\n if res == \"Already up-to-date.\":\n raise exceptions.ValidationError(\"El código ya esta actualizado\")\n\n # NOTE: update /etc/.odooconf replaces all content\n if not modules:\n raise exceptions.UserError('Debe agregar la lista de modulos a actualizar')\n f = open(\"/etc/.odooconf\", \"w\")\n f.write(\"ARG1=--update {modules}\".format(modules=modules))\n f.close()\n\n # NOTE: restart server\n # TODO: run the service as odoo user without the fucking password\n command = \"sudo systemctl restart odooupdate\"\n subprocess.run(command, shell=True)\n else:\n raise exceptions.UserError('Por favor configure los datos de conexión de Github en el menú de configuración')\n\n\nclass GithubConfig(models.Model):\n _name = 'github.config'\n\n type = fields.Selection(\n selection=[\n ('https', 'HTTPS'),\n ('ssh', 'SSH')\n ],\n string='Tipo de Conexión'\n )\n https_user = fields.Char('Mail Github')\n https_psw = fields.Char('Password Github')\n ssh = fields.Char(string='Github SSH')\n https = fields.Char(string='Github HTTPS')\n path = fields.Char(string='Path')\n\n\nclass ResConfigSettings(models.TransientModel):\n \"\"\"Configuration for automatic update from github\"\"\"\n _inherit = 'res.config.settings'\n\n github_type = fields.Selection(\n selection=[\n ('https', 'HTTPS'),\n ('ssh', 'SSH')\n ],\n string='Tipo de Conexión'\n )\n github_https_user = fields.Char('Mail Github')\n github_https_psw = fields.Char('Password Github')\n github_ssh = fields.Char(\n string='Github SSH',\n help='You need to configure an ssh key in the server'\n )\n github_https = fields.Char(\n string='Github HTTPS',\n help='You need to configure an ssh key in the server'\n )\n modules_path = fields.Char('Path al repositorio')\n\n @api.multi\n def test_github_conecction(self):\n github_config = self.env['github.config'].search([])\n if not github_config:\n exceptions.ValidationError('Debe configurar las credenciales de Github y guardarlas')\n else:\n if github_config.type == 'ssh':\n print('ssh connect')\n connect = \"ssh -T git@github.com\"\n res = subprocess.run(connect, shell=True)\n elif github_config.type == 'https':\n connect = ''\n res = subprocess.run(connect, shell=True)\n\n print(res)\n\n @api.multi\n def set_values(self):\n # NOTE: guarda los valores del wizard al modelo fijo\n # NOTE: buscar parametro si exite write si no existe crear\n super(ResConfigSettings, self).set_values()\n github_config = self.env['github.config'].search([])\n vals = {\n 'type': self.github_type,\n 'https_user': self.github_https_user,\n 'https_psw': self.github_https_psw,\n 'ssh': self.github_ssh,\n 'https': self.github_https,\n 'path': self.modules_path\n }\n if github_config:\n github_config.write(vals)\n else:\n github_config.create(vals)\n\n @api.multi\n def get_values(self):\n # NOTE: Busca los valores y los devuelve al wizard de configuracion\n res = super(ResConfigSettings, self).get_values()\n github_config = self.env['github.config'].search([])\n if github_config:\n res['github_type'] = github_config.type\n res['github_https_user'] = github_config.https_user\n res['github_https_psw'] = github_config.https_psw\n res['github_ssh'] = github_config.ssh\n res['github_https'] = github_config.https\n res['modules_path'] = github_config.path\n return res\n","sub_path":"module_auto_update/models/auto_update.py","file_name":"auto_update.py","file_ext":"py","file_size_in_byte":6088,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"527612637","text":"#!/usr/bin/python\n\n# Copyright (c) 2010 VA Linux Systems Japan K.K. All rights reserved.\n#\n# LICENSE NOTICE\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions\n# are met:\n# 1. Redistributions of source code must retain the above copyright\n# notice, this list of conditions and the following disclaimer.\n# 2. Redistributions in binary form must reproduce the above copyright\n# notice, this list of conditions and the following disclaimer in the\n# documentation and/or other materials provided with the distribution.\n# 3. Neither the name of the Company nor the names of its contributors\n# may be used to endorse or promote products derived from this software\n# without specific prior written permission.\n#\n# THIS SOFTWARE IS PROVIDED BY THE COMPANY AND CONTRIBUTORS ``AS IS'' AND\n# ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n# ARE DISCLAIMED. IN NO EVENT SHALL THE COMPANY OR CONTRIBUTORS BE LIABLE\n# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL\n# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS\n# OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)\n# HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT\n# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY\n# OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF\n# SUCH DAMAGE.\n\n__version__ = '$Id: vas_const.py 319 2010-10-20 05:54:09Z yamamoto2 $'\n\nfrom vas_subr import __reverse_dict\n\n# constants larger than 100 are reserved by VA Linux Systems Japan\nALLOC_PRIORITY = {'HIGH':1, 'LOW':2, 'EVACUATE':3, 'OFFLINE':4, 'FAULTY':5, 'HALT':6}\nALLOC_PRIORITY_STR = __reverse_dict(ALLOC_PRIORITY)\nEXT_STATUS = {'BUSY':1, 'FREE':2, 'EVACUATE':3, 'OFFLINE':4, 'SUPER':5, 'FAULTY':6}\n# ATTACH_STATUS: 0 and 4 are reserved by VA Linux Systems Japan\n# UNBOUND is for in-core use. it never appears in the db.\nATTACH_STATUS = {'UNBOUND': 0, 'BOUND':1, 'ERROR': 2}\nATTACH_EVENT = {'BINDING':1, 'UNBINDING':2}\nMIRROR_STATUS = {'ALLOCATED': 1, 'INSYNC': 2, 'SPARE': 3, 'FAULTY': 4, 'NEEDSHRED': 5}\nMIRROR_STATUS_STR = __reverse_dict(MIRROR_STATUS)\n# LVOLTYPE: 100 and higher LVOLTYPEs are reserved by VA Linux Systems Japan\nLVOLTYPE = {'LVOL': 0, 'LINEAR':1, 'MIRROR':2, 'DEXT':3, 'SNAPSHOT-ORIGIN':6, \\\n 'SNAPSHOT':7}\nTARGET = {'HSVR':1, 'SSVR':2, 'PDSK': 3, 'LVOL':4}\nTARGET_PREFIX = ['none-', 'hsvr-', 'ssvr-', 'pdsk-', 'lvol-']\nIDTYPE = {'hsvr': 1, 'lvol': 2, 'pdsk': 3, 'ssvr': 4, 'event': 5}\n\n","sub_path":"src/vas_const.py","file_name":"vas_const.py","file_ext":"py","file_size_in_byte":2681,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"576028040","text":"\nimport numpy as np\nimport numpy.linalg as npl\n\n\nfrom nose.tools import assert_equal, assert_raises, assert_true, assert_false\nfrom numpy.testing import assert_array_equal, assert_array_almost_equal\n\nfrom dipy.core.sphere import hemi_icosahedron, HemiSphere\nfrom dipy.core.gradients import gradient_table\nfrom dipy.sims.voxel import single_tensor\nfrom ..odf import peak_directions\n\nfrom dipy.reconst.shm import (real_sph_harm, sph_harm_ind_list, OpdtModel,\n normalize_data, QballModel, hat, lcr_matrix,\n smooth_pinv, bootstrap_data_array,\n bootstrap_data_voxel, ResidualBootstrapWrapper,\n OpdtModel, CsaOdfModel, QballModel, SphHarmFit)\n\n\ndef test_sph_harm_ind_list():\n m_list, n_list = sph_harm_ind_list(8)\n assert_equal(m_list.shape, n_list.shape)\n assert_equal(m_list.shape, (45,))\n assert_true(np.all(np.abs(m_list) <= n_list))\n assert_array_equal(n_list % 2, 0)\n assert_raises(ValueError, sph_harm_ind_list, 1)\n\ndef test_real_sph_harm():\n # Tests derived from tables in\n # http://en.wikipedia.org/wiki/Table_of_spherical_harmonics\n # where real spherical harmonic $Y^m_n$ is defined to be:\n # Real($Y^m_n$) * sqrt(2) if m > 0\n # $Y^m_n$ if m == 0\n # Imag($Y^m_n$) * sqrt(2) if m < 0\n\n rsh = real_sph_harm\n pi = np.pi\n exp = np.exp\n sqrt = np.sqrt\n sin = np.sin\n cos = np.cos\n assert_array_almost_equal(rsh(0,0,0,0),\n 0.5/sqrt(pi))\n assert_array_almost_equal(rsh(2,2,pi/3,pi/5),\n 0.25*sqrt(15./(2.*pi))*\n (sin(pi/5.))**2.*cos(0+2.*pi/3)*sqrt(2))\n assert_array_almost_equal(rsh(-2,2,pi/3,pi/5),\n 0.25*sqrt(15./(2.*pi))*\n (sin(pi/5.))**2.*sin(0-2.*pi/3)*sqrt(2))\n assert_array_almost_equal(rsh(2,2,pi,pi/2),\n 0.25*sqrt(15/(2.*pi))*\n cos(2.*pi)*sin(pi/2.)**2.*sqrt(2))\n assert_array_almost_equal(rsh(-2,4,pi/4.,pi/3.),\n (3./8.)*sqrt(5./(2.*pi))*\n sin(0-2.*pi/4.)*\n sin(pi/3.)**2.*\n (7.*cos(pi/3.)**2.-1)*sqrt(2))\n assert_array_almost_equal(rsh(4,4,pi/8.,pi/6.),\n (3./16.)*sqrt(35./(2.*pi))*\n cos(0+4.*pi/8.)*sin(pi/6.)**4.*sqrt(2))\n assert_array_almost_equal(rsh(-4,4,pi/8.,pi/6.),\n (3./16.)*sqrt(35./(2.*pi))*\n sin(0-4.*pi/8.)*sin(pi/6.)**4.*sqrt(2))\n aa = np.ones((3,1,1,1))\n bb = np.ones((1,4,1,1))\n cc = np.ones((1,1,5,1))\n dd = np.ones((1,1,1,6))\n assert_equal(rsh(aa, bb, cc, dd).shape, (3, 4, 5, 6))\n\n\ndef test_smooth_pinv():\n hemi = hemi_icosahedron.subdivide(2)\n m, n = sph_harm_ind_list(4)\n B = real_sph_harm(m, n, hemi.phi[:, None], hemi.theta[:, None])\n\n L = np.zeros(len(m))\n C = smooth_pinv(B, L)\n D = np.dot(npl.inv(np.dot(B.T, B)), B.T)\n assert_array_almost_equal(C, D)\n\n L = n*(n+1)*.05\n C = smooth_pinv(B, L)\n L = np.diag(L)\n D = np.dot(npl.inv(np.dot(B.T, B) + L*L), B.T)\n\n assert_array_almost_equal(C, D)\n\n L = np.arange(len(n))*.05\n C = smooth_pinv(B, L)\n L = np.diag(L)\n D = np.dot(npl.inv(np.dot(B.T, B) + L*L), B.T)\n assert_array_almost_equal(C, D)\n\ndef test_normalize_data():\n\n sig = np.arange(1, 66)[::-1]\n\n where_b0 = np.zeros(65, 'bool')\n where_b0[0] = True\n d = normalize_data(sig, where_b0, 1)\n assert_raises(ValueError, normalize_data, sig, where_b0, out=sig)\n\n norm_sig = normalize_data(sig, where_b0, min_signal=1)\n assert_array_almost_equal(norm_sig, sig/65.)\n norm_sig = normalize_data(sig, where_b0, min_signal=5)\n assert_array_almost_equal(norm_sig[-5:], 5/65.)\n\n where_b0[[0, 1]] = [True, True]\n norm_sig = normalize_data(sig, where_b0, min_signal=1)\n assert_array_almost_equal(norm_sig, sig/64.5)\n norm_sig = normalize_data(sig, where_b0, min_signal=5)\n assert_array_almost_equal(norm_sig[-5:], 5/64.5)\n\n sig = sig*np.ones((2,3,1))\n\n where_b0[[0, 1]] = [True, False]\n norm_sig = normalize_data(sig, where_b0, min_signal=1)\n assert_array_almost_equal(norm_sig, sig/65.)\n norm_sig = normalize_data(sig, where_b0, min_signal=5)\n assert_array_almost_equal(norm_sig[..., -5:], 5/65.)\n\n where_b0[[0, 1]] = [True, True]\n norm_sig = normalize_data(sig, where_b0, min_signal=1)\n assert_array_almost_equal(norm_sig, sig/64.5)\n norm_sig = normalize_data(sig, where_b0, min_signal=5)\n assert_array_almost_equal(norm_sig[..., -5:], 5/64.5)\n\n\ndef make_fake_signal():\n hemisphere = hemi_icosahedron.subdivide(2)\n bvecs = np.concatenate(([[0, 0, 0]], hemisphere.vertices))\n bvals = np.zeros(len(bvecs)) + 2000\n bvals[0] = 0\n gtab = gradient_table(bvals, bvecs)\n\n evals = np.array([[2.1, .2, .2], [.2, 2.1, .2]]) * 10**-3\n evecs0 = np.eye(3)\n sq3 = np.sqrt(3) / 2.\n evecs1 = np.array([[sq3, .5, 0],\n [.5, sq3, 0],\n [0, 0, 1.]])\n evecs1 = evecs0\n a = evecs0[0]\n b = evecs1[1]\n S1 = single_tensor(gtab, .55, evals[0], evecs0)\n S2 = single_tensor(gtab, .45, evals[1], evecs1)\n return S1 + S2, gtab, np.vstack([a, b])\n\n\nclass TestQballModel(object):\n\n model = QballModel\n\n def test_single_voxel_fit(self):\n signal, gtab, expected = make_fake_signal()\n sphere = hemi_icosahedron.subdivide(4)\n\n model = self.model(gtab, sh_order=4, min_signal=1e-5,\n assume_normed=True)\n fit = model.fit(signal)\n odf = fit.odf(sphere)\n assert_equal(odf.shape, sphere.phi.shape)\n directions, _, _ = peak_directions(odf, sphere)\n # Check the same number of directions\n n = len(expected)\n assert_equal(len(directions), n)\n # Check directions are unit vectors\n cos_similarity = (directions * directions).sum(-1)\n assert_array_almost_equal(cos_similarity, np.ones(n))\n # Check the directions == expected or -expected\n cos_similarity = (directions * expected).sum(-1)\n assert_array_almost_equal(abs(cos_similarity), np.ones(n))\n\n # Test normalize data\n model = self.model(gtab, sh_order=4, min_signal=1e-5,\n assume_normed=False)\n fit = model.fit(signal*5)\n odf_with_norm = fit.odf(sphere)\n assert_array_almost_equal(odf, odf_with_norm)\n\n def test_mulit_voxel_fit(self):\n signal, gtab, expected = make_fake_signal()\n sphere = hemi_icosahedron\n nd_signal = np.vstack([signal, signal])\n\n model = self.model(gtab, sh_order=4, min_signal=1e-5,\n assume_normed=True)\n fit = model.fit(nd_signal)\n odf = fit.odf(sphere)\n assert_equal(odf.shape, (2,) + sphere.phi.shape)\n\n # Test fitting with mask, where mask is False odf should be 0\n fit = model.fit(nd_signal, mask=[False, True])\n odf = fit.odf(sphere)\n assert_array_equal(odf[0], 0.)\n\n def test_sh_order(self):\n signal, gtab, expected = make_fake_signal()\n model = self.model(gtab, sh_order=4, min_signal=1e-5)\n assert_equal(model.B.shape[1], 15)\n assert_equal(max(model.n), 4)\n model = self.model(gtab, sh_order=6, min_signal=1e-5)\n assert_equal(model.B.shape[1], 28)\n assert_equal(max(model.n), 6)\n\n\ndef test_SphHarmFit():\n coef = np.zeros((3, 4, 5, 45))\n mask = np.zeros((3, 4, 5), dtype=bool)\n\n fit = SphHarmFit(None, coef, mask)\n item = fit[0, 0, 0]\n assert_equal(item.shape, ())\n slice = fit[0]\n assert_equal(slice.shape, (4, 5))\n slice = fit[..., 0]\n assert_equal(slice.shape, (3, 4))\n\n\nclass TestOpdtModel(TestQballModel):\n model = OpdtModel\n\n\nclass TestCsaOdfModel(TestQballModel):\n model = CsaOdfModel\n\n\ndef test_hat_and_lcr():\n hemi = hemi_icosahedron.subdivide(3)\n m, n = sph_harm_ind_list(8)\n B = real_sph_harm(m, n, hemi.phi[:, None], hemi.theta[:, None])\n H = hat(B)\n B_hat = np.dot(H, B)\n assert_array_almost_equal(B, B_hat)\n\n R = lcr_matrix(H)\n d = np.arange(len(hemi.theta))\n r = d - np.dot(H, d)\n lev = np.sqrt(1-H.diagonal())\n r /= lev\n r -= r.mean()\n\n r2 = np.dot(R, d)\n assert_array_almost_equal(r, r2)\n\n r3 = np.dot(d, R.T)\n assert_array_almost_equal(r, r3)\n\ndef test_bootstrap_array():\n B = np.array([[4, 5, 7, 4, 2.],\n [4, 6, 2, 3, 6.]])\n H = hat(B.T)\n\n R = np.zeros((5,5))\n d = np.arange(1, 6)\n dhat = np.dot(H, d)\n\n assert_array_almost_equal(bootstrap_data_voxel(dhat, H, R), dhat)\n assert_array_almost_equal(bootstrap_data_array(dhat, H, R), dhat)\n\n H = np.zeros((5,5))\n\ndef test_ResidualBootstrapWrapper():\n B = np.array([[4, 5, 7, 4, 2.],\n [4, 6, 2, 3, 6.]])\n B = B.T\n H = hat(B)\n d = np.arange(10)/8.\n d.shape = (2,5)\n dhat = np.dot(d, H)\n ms = .2\n where_dwi = np.ones(len(H), dtype=bool)\n\n boot_obj = ResidualBootstrapWrapper(dhat, B, where_dwi, ms)\n assert_array_almost_equal(boot_obj[0], dhat[0].clip(ms, 1))\n assert_array_almost_equal(boot_obj[1], dhat[1].clip(ms, 1))\n\n dhat = np.column_stack([[.6, .7], dhat])\n where_dwi = np.concatenate([[False], where_dwi])\n boot_obj = ResidualBootstrapWrapper(dhat, B, where_dwi, ms)\n assert_array_almost_equal(boot_obj[0], dhat[0].clip(ms, 1))\n assert_array_almost_equal(boot_obj[1], dhat[1].clip(ms, 1))\n\n\nif __name__ == \"__main__\":\n import nose\n nose.runmodule()\n","sub_path":"dipy/reconst/tests/test_shm.py","file_name":"test_shm.py","file_ext":"py","file_size_in_byte":9430,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"73496890","text":"#!/usr/bin/env python\n#-*- coding:utf-8 -*-\n\n\n# importing useful libraries -- feel free to add any others you find necessary\nimport socket\nimport hashlib\nimport re\nimport time\nhost = \"142.93.117.193\" # IP address or URL\nport = 7331 # port\n\ns = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\ns.connect((host, port))\ndata = s.recv(1024)\n# use these to connect to the service\nwhile(True):\n# receive some data\t\n\t\n\tprint(\"We are here under data\")\n\tstri = str(data).split('\\n')\n\tstr1 = stri[len(stri)-2]\n\tz = re.match(\"Find me the (sha\\d{1,3}|md\\d) hash of (\\w*)\",str1)\n\tha = z.group(1).strip()\n\tst = z.group(2).strip()\n\th = hashlib.new(str(ha).strip())\n\th.update(st.strip())\n\tanswer = h.hexdigest() + \"\\n\"\n\ts.send(answer)\n\tdata = s.recv(1024)\n\tprint(data)\n\t\n# close the connection\ns.close()\n","sub_path":"week/9/writeup/part2.py","file_name":"part2.py","file_ext":"py","file_size_in_byte":795,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"514562316","text":"\"\"\"toolDrMemoryTest.py\n\n General description:\n This is a unit test suite for the DrMemory module.\n (C) 2015, Constantin Mihalache \n last review 06.08.2015\n\"\"\"\n\nimport os\nimport sys\nimport unittest\nimport subprocess\nfrom coreutils import platformhandler\nfrom coreutils.errors import *\n\nclass TestDrMemory(unittest.TestCase):\n @classmethod\n def importTool(cls, toolName):\n os.chdir('./languages/C/modules');\n tool = __import__(toolName)\n toolInstance = getattr(tool, toolName)\n os.chdir(cls.returnPath)\n return toolInstance()\n\n @classmethod\n def setUpClass(cls):\n cls.returnPath = os.getcwd()\n cls.toolInstance = cls.importTool('drmemory')\n cls.platformInstance = platformhandler.getInstance()\n cls.platformInstance.getArchitecture()\n cls.sourceFolder = os.path.abspath('./unit-tests/sources')\n cls.tests = ['drmemoryTest01'] # add test folders here\n cls.currentPath = None\n cls.currentTest = 0\n cls.exitCode = 0\n\n def compileCurrentTest(self):\n testFolderName = self.tests[self.currentTest]\n self.currentPath = os.path.join(self.sourceFolder,testFolderName)\n os.chdir(self.currentPath)\n make_build = subprocess.Popen(['make','build'], stderr=subprocess.PIPE, stdout=subprocess.PIPE)\n return make_build.wait() # returns exit code\n\n def cleanCurrentTempFiles(self):\n make_clean = subprocess.Popen(['make', 'clean'], stderr=subprocess.PIPE, stdout=subprocess.PIPE)\n os.chdir(self.returnPath)\n self.currentPath = None\n return make_clean.wait() # returns exit code\n\n def setUp(self):\n self.exitCode = self.compileCurrentTest()\n\n def tearDown(self):\n self.exitCode = self.cleanCurrentTempFiles()\n self.currentTest = self.currentTest+1\n\n def test_all_errors_1(self):\n errorList = [\"MEMORY LEAK\",\n \"INVALID ACCESS\",\n \"UNITIALIZED VARIABLE USAGE\",\n \"INVALID FREE\",\n \"OPENED, BUT NOT CLOSED FILE DESCRIPTOR\"]\n\n expectedOutput = [Error(\"INVALID ACCESS\", \"main.c\", \"main\", \"31\"),\n Error(\"INVALID FREE\", \"main.c\", \"main\", \"33\"),\n Error(\"UNITIALIZED VARIABLE USAGE\", \"main.c\", \"main\", \"33\"),\n Error(\"INVALID ACCESS\", \"main.c\", \"invalid_acces_function\", \"10\"),\n Error(\"UNITIALIZED VARIABLE USAGE\", \"main.c\", \"uninitialized_variable_usage_function\", \"17\"),\n Error(\"INVALID FREE\", \"main.c\", \"main\", \"40\"),\n Error(\"UNITIALIZED VARIABLE USAGE\", \"main.c\", \"main\", \"40\"),\n Error(\"MEMORY LEAK\", \"main.c\", \"main\", \"29\"),\n Error(\"MEMORY LEAK\", \"main.c\", \"invalid_acces_function\", \"8\"),\n Error(\"OPENED, BUT NOT CLOSED FILE DESCRIPTOR\", \"main.c\", \"main\", \"24\")]\n\n exes = ['robocheck-test']\n sources = ['main.c']\n exesPath = os.path.join(self.currentPath, 'exes')\n sourcesPath = self.currentPath\n\n self.assertEqual(self.exitCode, 0)\n self.assertTrue(self.toolInstance.toolIsInstalled(self.platformInstance))\n toolOutput = self.toolInstance.runToolGetErrors(self.platformInstance, exes, sources,\n exesPath, sourcesPath, errorList)\n self.assertTrue(Error.identicalLists(expectedOutput, toolOutput))\n\nif __name__ == '__main__':\n unittest.main()\n","sub_path":"unit-tests/toolDrMemoryTest.py","file_name":"toolDrMemoryTest.py","file_ext":"py","file_size_in_byte":3401,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"462504412","text":"import csv\nimport nltk \nimport numpy\ntokenized_list = []\nwith open('task-assign.csv', 'r') as csvfile: # this will close the file automatically.\n reader = csv.reader(csvfile)\n for row in reader:\n for field in row:\n tokens = nltk.word_tokenize(field)\n tokenized_list.append(tokens)\nwith open(\"tokenize-data.csv\",'wb') as resultFile:\n wr = csv.writer(resultFile, dialect='excel')\n for word in tokenized_list:\n wr.writerow(word)","sub_path":"app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":474,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"423262138","text":"from random import randint\nprint('\"Hai.. nama saya Mr.Lappie, saya telah memilih sebuah bilanga bulat secara acak antara 0 s/d 100. Silakan tebak ya!!!\" ')\nwhile True :\n bil = randint(0, 100)\n ans = int(input('Tebakan Anda = '))\n if(ans > bil):\n print('Hehehe... Bilangan tebakan anda terlalu besar')\n elif(ans < bil):\n print('Hehehe... Bilangan tebakan anda terlalu kecil')\n elif (ans == bil):\n print('Yeeee... Bilangan tebakan anda BENAR :-)')\n break\n\n","sub_path":"praktikum 5/praktikum 2/latihan05.py","file_name":"latihan05.py","file_ext":"py","file_size_in_byte":497,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"369066925","text":"import cv2\nimport numpy\nfrom PIL import Image, ImageDraw, ImageFont\n\n\n# 给图片加上中文文字\ndef add_text(img, text):\n # 图像从cv格式转换成pil格式\n img_PIL = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))\n font = ImageFont.truetype(r\"D:\\Program Files\\JetBrains\\IntelliJ IDEA 2019.1\\plugins\\android\\lib\\layoutlib\\data\\fonts\\NotoSansCJK-Regular.ttc\", 30)\n # 文字输出位置\n position = (0, 0)\n # 输出内容\n draw = ImageDraw.Draw(img_PIL)\n # 设置文本位置、内容、字体、颜色\n draw.text(position, text, font=font, fill=(255, 10, 10))\n # 转换回cv格式\n img_OpenCV = cv2.cvtColor(numpy.asarray(img_PIL), cv2.COLOR_RGB2BGR)\n return img_OpenCV\n\n\n# 设置窗口大小可调整\ndef set_window(img, name, text):\n size = img.shape\n # 设置窗口大小可调\n cv2.namedWindow(name, 0)\n cv2.resizeWindow(name, size[1], size[0])\n # 添加文字并显示图片\n cv2.imshow(name, add_text(img, text))\n\n\n# 主方法\nif __name__ == '__main__':\n # 读取图像\n before = cv2.imread(r'C:\\Users\\Ronz\\Desktop\\DigitalImage\\img\\Fig0304(a)(breast_digital_Xray).tif')\n # 设置窗口可放缩，添加中文文字并打印原始图片\n set_window(before, 'before', '姓名刘壮志的原始图片')\n # 最大图像灰度值减去原图像，即可得到反转的图像\n after = 255 - before\n # 设置窗口可放缩，添加中文文字并打印反转后图片\n set_window(after, 'after', '姓名刘壮志的图像反转图片')\n cv2.waitKey(0)\n","sub_path":"ImageReversion.py","file_name":"ImageReversion.py","file_ext":"py","file_size_in_byte":1547,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"220043382","text":"from pathlib import Path\nimport urllib.request\nimport argparse\nfrom pprint import pprint\nimport json\nimport torch\n\n\nfrom mmcv import Config\nfrom mmdet.apis import set_random_seed, train_detector\nfrom mmdet.datasets import build_dataset\nfrom mmdet.models import build_detector\n\n# Get classes\ndef get_classes(coco_file):\n with open(coco_file) as f:\n data = json.load(f)\n classes = [x['name'] for x in data['categories']]\n return classes\n\n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser()\n parser.add_argument('-i', '--input', default='train_mmdet_input.json')\n parser.add_argument('-D', '--dataset_dir', help='dataset_coco')\n parser.add_argument('-y', '--dataset_type', help='CocoDataset')\n parser.add_argument('-t', '--train_file', help='train_coco.json')\n parser.add_argument('-v', '--val_file', help='val_coco.json')\n parser.add_argument('-s', '--test_file', help='test_coco.json')\n parser.add_argument('-T', '--train_dir', help='train')\n parser.add_argument('-V', '--val_dir', help='val')\n parser.add_argument('-S', '--test_dir', help='test')\n parser.add_argument('-I', '--img_dir', help='images')\n parser.add_argument('-W', '--work_dir', help='work')\n parser.add_argument('-C', '--configs_dir', help='configs')\n parser.add_argument('-K', '--checkpoints_dir', help='checkpoints')\n parser.add_argument('-p', '--is_pretrained', type=bool, default=None)\n parser.add_argument('-c', '--config_file',\n help='cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.py')\n parser.add_argument('-n', '--new_config_file',\n help='cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco_new.py')\n parser.add_argument('-k', '--checkpoint_file',\n help='cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.py')\n parser.add_argument('-u', '--checkpoint_url',\n help='https://download.openmmlab.com/mmdetection/v2.0/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco/cascade_rcnn_r50_fpn_1x_coco_20200316-3dc56deb.pth')\n parser.add_argument('-e', '--seed', type=int, help='42')\n print('Command line arguments')\n cmd_args = vars(parser.parse_args()) # convert from namespace to dict\n pprint(cmd_args)\n print('Config arguments')\n if cmd_args['input'] is not None:\n with open(cmd_args['input']) as f:\n cfg_args = json.load(f)\n else:\n cfg_args = {}\n pprint(cfg_args)\n print('Arguments')\n for k, v in cmd_args.items(): # Update cfg args by cmd args\n if v is not None or k not in cfg_args:\n cfg_args[k] = v\n pprint(cfg_args)\n dataset_type = cfg_args['dataset_type']\n dataset_dir = cfg_args['dataset_dir']\n train_file = cfg_args['train_file']\n val_file = cfg_args['val_file']\n test_file = cfg_args['test_file']\n train_dir = cfg_args['train_dir']\n val_dir = cfg_args['val_dir']\n test_dir = cfg_args['test_dir']\n img_dir = cfg_args['img_dir']\n configs_dir = cfg_args['configs_dir']\n checkpoints_dir = cfg_args['checkpoints_dir']\n work_dir = cfg_args['work_dir']\n config_file = cfg_args['config_file']\n new_config_file = cfg_args['new_config_file']\n is_pretrained = cfg_args['is_pretrained']\n checkpoint_file = cfg_args['checkpoint_file']\n checkpoint_url = cfg_args['checkpoint_url']\n seed = cfg_args['seed']\n\n # Check dataset\n dataset_dir = Path(dataset_dir)\n train_path = dataset_dir / train_dir\n val_path = dataset_dir / val_dir\n test_path = dataset_dir / test_dir\n train_img_path = train_path / img_dir\n val_img_path = val_path / img_dir\n test_img_path = test_path / img_dir\n train_file_path = train_path / train_file\n val_file_path = val_path / val_file\n test_file_path = test_path / test_file\n assert dataset_dir.exists()\n assert train_path.exists()\n assert val_path.exists()\n assert test_path.exists()\n assert train_img_path.exists()\n assert val_img_path.exists()\n assert test_file_path.exists()\n assert train_file_path.exists()\n assert val_file_path.exists()\n assert test_file_path.exists()\n\n # Get dataset classes\n train_classes = get_classes(train_file_path)\n val_classes = get_classes(val_file_path)\n test_classes = get_classes(test_file_path)\n assert set(train_classes) == set(val_classes) == set(test_classes)\n classes = train_classes\n print('Dataset classes')\n print(classes)\n\n # Prepare environment\n work_path = Path(work_dir)\n work_path.mkdir(parents=True, exist_ok=True)\n checkpoints_path = Path(checkpoints_dir)\n checkpoints_path.mkdir(parents=True, exist_ok=True)\n configs_path = Path(configs_dir)\n configs_path.mkdir(parents=True, exist_ok=True)\n config_path = configs_path / config_file\n assert config_path.exists()\n new_config_path = configs_path / new_config_file\n new_config_path.parent.mkdir(parents=True, exist_ok=True)\n checkpoint_path = checkpoints_path / checkpoint_file\n # Check checkpoint (if pretrained)\n if is_pretrained and not checkpoint_path.exists():\n checkpoint_path.parent.mkdir(parents=True, exist_ok=True)\n print(f'Downloading checkpoint from {checkpoint_url} to {checkpoint_path.resolve()}')\n urllib.request.urlretrieve(checkpoint_url, checkpoint_path)\n\n # Get base config\n # Cascade Mask R-CNN https://paperswithcode.com/method/cascade-mask-r-cnn\n cfg = Config.fromfile(str(config_path.resolve()))\n print(f'Config:\\n{cfg.pretty_text}')\n\n # Update config\n # https://mmdetection.readthedocs.io/en/v2.0.0/config.html\n # 1. dataset settings\n cfg.dataset_type = dataset_type\n cfg.data_root = str(dataset_dir.resolve())\n cfg.data.train.type = dataset_type\n cfg.data.train.classes = classes\n cfg.data.train.data_root = str(train_path.resolve())\n cfg.data.train.ann_file = str(train_file_path.resolve())\n cfg.data.train.img_prefix = img_dir\n cfg.data.val.type = dataset_type\n cfg.data.val.classes = classes\n cfg.data.val.data_root = str(val_path.resolve())\n cfg.data.val.ann_file = str(val_file_path.resolve())\n cfg.data.val.img_prefix = img_dir\n cfg.data.test.type = dataset_type\n cfg.data.test.classes = classes\n cfg.data.test.data_root = str(test_path.resolve())\n cfg.data.test.ann_file = str(test_file_path.resolve())\n cfg.data.test.img_prefix = img_dir\n # 2. model settings\n cfg.model.roi_head.bbox_head[0].num_classes = len(classes)\n cfg.model.roi_head.bbox_head[1].num_classes = len(classes)\n cfg.model.roi_head.bbox_head[2].num_classes = len(classes)\n cfg.model.roi_head.mask_head.num_classes = len(classes)\n # We can still use the pre-trained Mask RCNN model though we do not need to\n # use the mask branch\n if is_pretrained:\n cfg.load_from = str(checkpoint_path.resolve())\n # # Set up working dir to save files and logs.\n cfg.work_dir = str(work_path.resolve())\n # https://mmdetection.readthedocs.io/en/latest/tutorials/customize_runtime.html\n # # The original learning rate (LR) is set for 8-GPU training.\n # # We divide it by 8 since we only use one GPU.\n cfg.optimizer.lr = 0.02 / 8\n cfg.lr_config.policy = 'step' # described in https://arxiv.org/pdf/1506.01186.pdf\n cfg.lr_config.warmup = None\n cfg.log_config.interval = 10\n # # Change the evaluation metric since we use customized dataset.\n # cfg.evaluation.metric = 'mAP'\n # # We can set the evaluation interval to reduce the evaluation times\n # cfg.evaluation.interval = 12\n # # We can set the checkpoint saving interval to reduce the storage cost\n # cfg.checkpoint_config.interval = 12\n # # Set seed thus the results are more reproducible\n cfg.seed = seed\n set_random_seed(seed, deterministic=False)\n cfg.gpu_ids = range(1)\n\n # Save new config\n cfg.dump(new_config_path.resolve())\n cfg = Config.fromfile(str(new_config_path.resolve())) # Check\n print(f'Config:\\n{cfg.pretty_text}')\n\n # Build dataset\n datasets = [build_dataset(cfg.data.train)]\n\n # Build the detector\n model = build_detector(cfg.model)\n # Add an attribute for visualization convenience\n model.CLASSES = classes\n\n print(\"CUDA CHECK\")\n torch.cuda.is_available()\n torch.cuda.current_device()\n torch.cuda.device(0)\n torch.cuda.device_count()\n torch.cuda.get_device_name(0)\n print(\"START STUDY\")\n train_detector(model, datasets, cfg, distributed=False, validate=True)\n","sub_path":"train_mmdet.py","file_name":"train_mmdet.py","file_ext":"py","file_size_in_byte":8450,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"543807668","text":"from twisted.internet.defer import inlineCallbacks\nfrom twisted.trial.unittest import TestCase\n\nfrom txgsm.tests.base import TxGSMBaseTestCase, LogCatcher\nfrom txgsm.txgsm import TxGSMService, TxGSMProtocol\n\nfrom mock import Mock\n\n\nclass TxGSMTestCase(TxGSMBaseTestCase):\n\n timeout = 1\n\n @inlineCallbacks\n def test_configure_modem(self):\n d = self.modem.configure_modem()\n self.assertExchange(['AT+CMGF=0'], ['OK'])\n self.assertExchange(['ATE0'], ['OK'])\n self.assertExchange(['AT+CMEE=1'], ['OK'])\n self.assertExchange(['AT+WIND=0'], ['OK'])\n self.assertExchange(['AT+CSMS=1'], ['OK'])\n self.assertExchange(['AT+CSQ'], ['OK'])\n response = yield d\n self.assertEqual(response, ['OK'])\n\n @inlineCallbacks\n def test_send_sms(self):\n d = self.modem.send_sms('+27761234567', 'hello world')\n self.assertCommands(['AT+CMGS=23'])\n self.reply('> ', delimiter='')\n [pdu_payload] = self.get_next_commands()\n self.reply('OK')\n response = yield d\n self.assertEqual(response, ['OK'])\n\n @inlineCallbacks\n def test_send_multipart_sms(self):\n d = self.modem.send_sms('+27761234567', '1' * 180)\n self.assertCommands(['AT+CMGS=153'])\n self.reply('> ', delimiter='')\n [pdu_payload] = self.get_next_commands()\n self.reply('OK')\n self.assertCommands(['AT+CMGS=43'])\n self.reply('> ', delimiter='')\n [pdu_payload] = self.get_next_commands()\n self.reply('OK')\n response = yield d\n self.assertEqual(response, ['OK'])\n\n @inlineCallbacks\n def test_ussd_session(self):\n d = self.modem.dial_ussd_code('*100#')\n self.assertExchange(\n input=['AT+CUSD=1,\"*100#\",15'],\n output=[\n 'OK',\n ('+CUSD: 2,\"Your balance is R48.70. Out of Airtime? '\n 'Dial *111# for Airtime Advance. T&Cs apply.\",255')\n ])\n response = yield d\n self.assertEqual(response[0], 'OK')\n self.assertTrue(response[1].startswith('+CUSD: 2'))\n\n def test_dealing_with_unexpected_events(self):\n with LogCatcher() as catcher:\n self.reply('+FOO')\n [err_log] = catcher.logs\n self.assertTrue('Unsollicited response' in err_log['message'][0])\n self.assertTrue('+FOO' in err_log['message'][0])\n\n\nclass TxGSMServiceTestCase(TestCase):\n\n def setUp(self):\n self.mock_serial = Mock()\n self.service = TxGSMService('/dev/foo', bar='baz')\n self.service.serial_port_class = self.mock_serial\n\n @inlineCallbacks\n def test_start_service(self):\n d = self.service.onProtocol\n self.service.startService()\n protocol = yield d\n self.assertTrue(isinstance(protocol, TxGSMProtocol))\n self.assertTrue(self.mock_serial.called)\n [init_call] = self.mock_serial.call_args_list\n args, kwargs = init_call\n proto, device, reactor = args\n self.assertEqual(device, '/dev/foo')\n self.assertEqual(kwargs, {'bar': 'baz'})\n\n def test_stop_service(self):\n self.service.startService()\n self.service.port.loseConnection = Mock()\n self.service.stopService()\n self.assertTrue(self.service.port.loseConnection.called)\n","sub_path":"txgsm/tests/test_txgsm.py","file_name":"test_txgsm.py","file_ext":"py","file_size_in_byte":3319,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"467538119","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Mar 13 19:31:00 2019\n\nThis file compiles and fits all the different models of RNN implemented for this project (except\ndynamic-RNN).\nModel results are written to a .hdf5 formatted files and can be loaded_back for additional\nanalysis.\nNOTE !!!\nSomething with the current version of Keras in conda environment has been causing an error.\nYou should install the Keras version 2.1.2. Run the the following commands on your terminal\npip uninstall keras\nconda install -c conda-forge keras==2.1.2\n\n@author: berkaypolat\n\"\"\"\n\nimport numpy as np\nimport pandas as pd\nfrom matplotlib import pyplot\nfrom keras.utils import to_categorical\nfrom keras.models import Sequential,load_model\nfrom keras.layers import LSTM, Dropout, Dense, Activation, TimeDistributed\nfrom keras.callbacks import ModelCheckpoint\nfrom bilstm import build_bilstm_model\nfrom grumodel import build_gru_model\nfrom lstm import build_lstm_model\n\n\"\"\"\nLoading the data and extracting useful information\n\"\"\"\ndef load_train_data(filename):\n df = pd.read_csv(filename)\n df = df.drop('Unnamed: 0', axis=1)\n\n return df.values, len(df.columns)-1\n\ndef load_validation_data(filename):\n df = pd.read_csv(filename)\n df = df.drop('Unnamed: 0', axis=1)\n return df.values\n\ndef load_test_data(filename):\n df = pd.read_csv(filename)\n df = df.drop('Unnamed: 0', axis=1)\n return df.values\n\n\"\"\"\nRetrieve hyperparameters\n\"\"\"\ndef get_hyperparameters():\n return {'batch_size': 16, 'num_classes':3, 'num_steps':10, 'num_epochs': 200}\n\n\"\"\"\nCreating a data generator class in order to feed in an\niterator object for the final model\n\"\"\"\nclass KerasBatchGenerator(object):\n\n def __init__(self, data, hyperparameters, num_features):\n self.data = data\n self.num_steps = hyperparameters['num_steps']\n self.batch_size = hyperparameters['batch_size']\n self.num_classes = hyperparameters['num_classes']\n self.current_idx = 0\n if(self.batch_size == 1):\n self.skip_step = 1\n else:\n self.skip_step = hyperparameters['num_steps']\n self.num_features = num_features\n\n def generate(self):\n x = np.zeros((self.batch_size, self.num_steps, self.num_features))\n y = np.zeros((self.batch_size, self.num_steps, self.num_classes))\n while True:\n for i in range(self.batch_size):\n if self.current_idx + self.num_steps >= len(self.data):\n self.current_idx = 0\n\n x[i, :, :] = self.data[self.current_idx : self.current_idx + self.num_steps, 0:self.num_features]\n temp_y = self.data[self.current_idx:self.current_idx + self.num_steps, -1]\n y[i, : , :] = to_categorical(temp_y, num_classes = self.num_classes)\n self.current_idx += self.skip_step\n\n yield x,y\n\n\"\"\"\nRun and Compile the LSTM NN\n\"\"\"\ndef run_model(model_name, model, data_length, generators, hyperparameters):\n train_len, valid_len = data_length['train'], data_length['validation']\n train_gen, valid_gen = generators['train_data_generator'], generators['validation_data_generator']\n batch_size, num_epochs = hyperparameters['batch_size'], hyperparameters['num_epochs']\n num_steps = hyperparameters['num_steps']\n model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['categorical_accuracy'])\n if (model_name == 'GRU'):\n filepath = 'gru_model_history/model-{epoch:02d}.hdf5'\n elif(model_name == 'BILSTM'):\n filepath = 'bilstm_model_history/model-{epoch:02d}.hdf5'\n else:\n filepath = 'lstm_model_history/model-{epoch:02d}.hdf5'\n #can be convert to True for saving best model\n checkpoints = ModelCheckpoint(filepath=filepath, save_best_only=True, verbose=1)\n model_history = model.fit_generator(train_gen.generate(), train_len//(batch_size*num_steps), num_epochs,\n validation_data= valid_gen.generate(),\n validation_steps= valid_len//(batch_size*num_steps), callbacks=[checkpoints])\n\n return model_history\n\n\"\"\"\nGenerates and runs the models\n\"\"\"\ndef call_models(model_lst):\n models_history = []\n hyperparameters = get_hyperparameters()\n train_data, num_features = load_train_data('all_training_processed.csv')\n validation_data = load_validation_data('all_dev_processed.csv')\n\n for model_name in model_lst:\n train_data_generator = KerasBatchGenerator(train_data, hyperparameters, num_features)\n validation_data_generator = KerasBatchGenerator(validation_data, hyperparameters, num_features)\n if(model_name == 'GRU'):\n model = build_gru_model(True, 200, 100, num_features, hyperparameters)\n elif(model_name == 'BILSTM'):\n model = build_bilstm_model(True, 200, 100, num_features, hyperparameters, merge_mode='concat')\n else:\n model = build_lstm_model(True,200,100,num_features, hyperparameters)\n\n data_length = {'train':len(train_data), 'validation':len(validation_data)}\n generators = {'train_data_generator': train_data_generator, 'validation_data_generator':validation_data_generator}\n models_history.append(run_model(model_name,model,data_length,generators, hyperparameters))\n\n return models_history\n\n\"\"\"\nGet train loss and validation loss values for each epoch\nThe History Object keys are:\n['val_loss', 'val_categorical_accuracy', 'loss', 'categorical_accuracy']\n\"\"\"\ndef get_loss_tables(history_lst, model_lst):\n loss_table = pd.DataFrame()\n val_loss_table = pd.DataFrame()\n for i in range(len(model_lst)):\n loss_table[model_lst[i]] = history_lst[i].history['loss']\n val_loss_table[model_lst[i]] = history_lst[i].history['val_loss']\n return loss_table, val_loss_table\n\nif __name__ == '__main__':\n model_lst = ['LSTM', 'GRU', 'BILSTM']\n history_lst = call_models(model_lst)\n train_losses, val_losses = get_loss_tables(history_lst, model_lst)\n train_losses.to_csv(\"train_losses.csv\")\n val_losses.to_csv(\"validation_losses.csv\")\n","sub_path":"modelGenerate.py","file_name":"modelGenerate.py","file_ext":"py","file_size_in_byte":6072,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"254770910","text":"import itertools\nimport math\n##from math import sqrt; from itertools import count, islice\nlist=[\"\".join(seq) for seq in itertools.product(\"01\", repeat=15)]\ndivset=[]\npcandidates=[]\ncount=0\njamcoins=[]\nfor x in list:\n\t\t#q=\"10\"+x+x+x+x+\"01\"\n\t\t#n=\"10\"+x+x[::-1]+x+x[::-1]+\"01\"\n\t\t#v=\"10\"+x[::-1]+x+x+x[::-1]+\"01\"\n\t\t#y=\"10\"+x+x+x+x+\"11\"\n\t\t#z=\"11\"+x+x+x+x+\"11\"\n\t\t#w=\"11\"+x+x+x+x+\"01\"\n\t\t#pcandidates.append(q)\n\t\t#pcandidates.append(n)\n\t\t#pcandidates.append(y)\n\t\t#pcandidates.append(w)\n\t\tz=\"1\"+x+x+\"1\"\n\t\tpcandidates.append(z)\n#print(pcandidates)\n\ndef is_prime(n):\n global divset\n if n == 2:\n return True\n if n % 2 == 0 or n <= 1:\n divset.append(2)\n return False\n\n sqr = int(math.sqrt(n)) + 1\n\n for divisor in range(3, sqr, 2):\n if n % divisor == 0:\n divset.append(divisor)\n return False\n return True\n\n##def isPrime(n):\n ## return n > 1 and all(n%i for i in islice(count(2), int(sqrt(n)-1)))\nprint(\"Case #1:\")\nfor x in pcandidates:\n\tdivset=[]\n\tcount=0\n\t##print(x)\n\tfor i in range(2,11):\n\t\tnum=int(x,i)\n\t\tif(is_prime(num)==True):\n\t\t\tcount=0\n\t\t\tbreak\n\t\telse:\n\t\t\tcount+=1\n\tif(count==9):\n\t\tjamcoins.append(x)\n\t\top=x\n\t\tfor div in divset:\n\t\t\top+=\" \"+str(div)\n\t\tprint(op)\n\t\t##print(\"hey\" +str(x))\n\tif(len(jamcoins)==500):\n\t\tbreak\n\n\n\n\n","sub_path":"codes/CodeJamCrawler/16_0_3_neat/16_0_3_Y_SreeChaitanya_jamcoin.py","file_name":"16_0_3_Y_SreeChaitanya_jamcoin.py","file_ext":"py","file_size_in_byte":1288,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"223886802","text":"#!/usr/bin/env python\n#\n# Copyright 2007 Google Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport webapp2\nimport jinja2\nimport datetime\nimport logging\nfrom google.appengine.api import users\nfrom google.appengine.ext import ndb\n\n\n# ---- These are all the global variables used in this file. ----\n# env has all the files in the directory 'html'\nenv = jinja2.Environment(loader=jinja2.FileSystemLoader('html'))\n# login_url is the url made for logging into a Google account\nlogin_url = \"\"\n# logout_url is the url made for logging out of the application\nlogout_url = \"\"\n\n# ---- This code sets up the components of the application.----\n# Each user of the application is a Writer\nclass Writer(ndb.Model):\n name = ndb.StringProperty()\n\n# Each journal Entry has a title, date, content, and whether or not it's a favorite.\nclass Entry(ndb.Model):\n title = ndb.StringProperty()\n date = ndb.DateProperty()\n content = ndb.StringProperty()\n favorite = ndb.BooleanProperty()\n # This entry belongs to this user/writer.\n writer_key = ndb.KeyProperty(Writer)\n\n\n# ---- This code renders the html files and sets up the handlers. ----\n# Renders the home page\nclass Home(webapp2.RequestHandler):\n def get(self):\n template = env.get_template('home.html')\n self.response.write(template.render())\n\n# Renders the login page\nclass Login(webapp2.RequestHandler):\n def get(self):\n user = users.get_current_user()\n # If the user is logged into Google\n if user:\n # When the user signs out, take them to the home page.\n logout_url = ' sign out ' % users.create_logout_url('/')\n writer = Writer.get_by_id(user.user_id())\n if writer:\n self.redirect('/dashboard')\n else:\n self.redirect('/registration')\n else:\n # After the user logins, take them to the dashboard.\n login_url = ' sign in ' % users.create_login_url('/registration')\n template = env.get_template('login.html')\n template_vars = {\"login_url\" : login_url}\n self.response.write(template.render(template_vars))\n\nclass Registration(webapp2.RequestHandler):\n def get(self):\n user = users.get_current_user()\n writer = Writer.get_by_id(user.user_id())\n if writer:\n self.redirect('/dashboard')\n else:\n template = env.get_template('registration.html')\n self.response.write(template.render())\n def post(self):\n user = users.get_current_user()\n if not user:\n # You shouldn't be able to get here without being logged in\n self.error(500)\n return\n writer = Writer(\n name = self.request.get('name'),\n id = user.user_id()\n )\n writer.put()\n self.redirect('/dashboard')\n\n# Renders the dashboard page\nclass Dashboard(webapp2.RequestHandler):\n def get(self):\n # Who is the current writer?\n user = users.get_current_user()\n writer = Writer.get_by_id(user.user_id())\n\n if not writer:\n self.redirect('/registration')\n\n # When the user signs out, take them to the home page.\n logout_url = ' sign out ' % users.create_logout_url('/')\n\n # Find all the Entries that belong to the current writer.\n all_entries = Entry.query(Entry.writer_key == writer.key)\n # Limit to the first 9 recent entries!!!! (fetch_page be able to show more)\n first_nine_entries = all_entries.order(-Entry.date).fetch(9)\n\n # Template variables to use and display in dashboard.html\n template_vars = {\n \"display_entries\" : first_nine_entries,\n \"name\" : writer.name,\n \"logout_url\" : logout_url\n }\n\n # Render the dashboard template\n template = env.get_template('dashboard.html')\n self.response.write(template.render(template_vars))\n\n# # Renders the favorites page\nclass Favorites(webapp2.RequestHandler):\n def get(self):\n # Who is the current writer?\n user = users.get_current_user()\n writer = Writer.get_by_id(user.user_id())\n\n # Find all the Entries that belong to the current writer.\n favorite_entries = Entry.query(Entry.writer_key == writer.key, Entry.favorite == True)\n # Limit to the first 20 recent entries!!!! (fetch_page be able to show more)\n first_nine_entries = all_entries.order(-Entry.date).fetch(20)\n template = env.get_template('favorites.html')\n self.response.write(template.render())\n\nclass NewEntry(webapp2.RequestHandler):\n def get(self):\n template = env.get_template('new_entry.html')\n self.response.write(template.render())\n def post(self):\n user = users.get_current_user()\n # Get the information from the form and make it into an entry object\n date_array = self.request.get('date').split(\"-\")\n\n entry = Entry(\n title = self.request.get('title'),\n # Need to change from string input to date object.\n # Reference: https://stackoverflow.com/questions/2803852/python-date-string-to-date-object\n # https://stackoverflow.com/questions/16476484/convert-unicode-data-to-int-in-python\n date = datetime.date(int(date_array[0]), int(date_array[1]), int(date_array[2])),\n content = self.request.get('content'),\n writer_key = Writer.get_by_id(user.user_id()).key\n )\n entry.put()\n self.redirect('/dashboard')\n\n# Renders the monthly collections page\nclass Collections(webapp2.RequestHandler):\n def get(self):\n template = env.get_template('collections.html')\n self.response.write(template.render())\n\napp = webapp2.WSGIApplication([\n ('/', Home),\n ('/login', Login),\n ('/registration', Registration),\n ('/dashboard', Dashboard),\n ('/collections', Collections),\n ('/favorites', Favorites),\n ('/new_entry', NewEntry)\n # ('/entry', DisplayEntry) # how to make these entry urls unique?\n], debug=True)\n","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":6582,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"587037527","text":"import numpy as np\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.basemap import Basemap\nimport matplotlib\nfrom Common import Common\nfrom Define import Define\nimport sys\n\nclass CreateStatisticalMap(object):\n\n\n def __init__(self, startDate, finishDate, ncdata, reference, mode, iniReader, log):\n \"\"\"\n create Statistical Map\n :param startDate: 'yyyyMMddHHmm'\n :param finishDate: 'yyyyMMddHHmm'\n :param ncdata: object of Data Class\n :param reference: reference name\n :param mode: map scan mode\n :param iniReader: object of ConfigParser\n :param log: object of logger Class\n \"\"\"\n self.logger = log\n self.logger.logger.info('start generate Statistical Map')\n self.common = Common(self.logger)\n self.define = Define()\n self.ncdata = ncdata\n self.startDate = startDate\n self.finishDate = finishDate\n self.reference =reference\n self.mode = mode\n try:\n self. get_configuration(iniReader)\n self.set_map(iniReader)\n self.logger.logger.info('finish generate Statistical Map')\n except ValueError as e:\n self.logger.logger.error('%s : Value Error' % (e))\n except AttributeError:\n self.logger.logger.error('%s : Invalid Map scan mode'%(self.mode))\n self.logger.logger.info('Not draw Statistical map')\n except EnvironmentError:\n self.logger.logger.error('No Match Colors - Colors Value')\n except Exception as e:\n self.logger.logger.error('%s : Error'%(e))\n except ZeroDivisionError:\n self.logger.logger.error('%s : Zero Division Error'%(self.map_interval))\n\n def get_configuration(self, iniReader):\n \"\"\"\n extract Statistical Map information in .ini file\n :param iniReader: object of ConfigParser\n \"\"\"\n self.title = iniReader.iniReader['map']['title']\n self.colors = iniReader.iniReader['map']['colors'].split(',')\n self.colorbar_value = iniReader.iniReader['map']['colorbar_value'].split(',')\n self.map_interval = float(iniReader.iniReader['map']['map_interval'])\n if self.map_interval == 0:\n raise ZeroDivisionError\n for i, value in enumerate(self.colorbar_value):\n self.colorbar_value[i] = int(value)\n if len(self.colorbar_value) != len(self.colors):\n raise EnvironmentError\n self.colors = matplotlib.colors.ListedColormap(self.colors)\n self.norm = matplotlib.colors.BoundaryNorm(self.colorbar_value, len(self.colorbar_value))\n\n\n def set_map(self, iniReader):\n \"\"\"\n generate map and get the data and draw the data in the map\n :param iniReader: object of ConfigParser\n :return: return when an invalid value(map scan mode) is received\n \"\"\"\n # scan mode에 따라 Map 생성시 크기 세팅 및 데이터 생성\n if self.mode == 'LA':\n mapTool = self.generate_map(self.define.LA)\n mapData, mapX, mapY = self.get_data(self.define.LA)\n elif self.mode == 'ELA':\n mapTool = self.generate_map(self.define.ELA)\n mapData, mapX, mapY = self.get_data(self.define.ELA)\n elif self.mode == 'FD':\n mapTool = self.generate_map(self.define.FD)\n mapData, mapX, mapY = self.get_data(self.define.FD)\n else:\n raise AttributeError\n self.draw_data(mapTool, mapData, mapX, mapY, iniReader)\n\n\n def generate_map(self, mode):\n \"\"\"\n genearte map and set map\n :param mode: map scan mode\n :return: the shape of the generated map\n \"\"\"\n plt.figure(figsize=(self.define.FIGUREX, self.define.FIGUREY))\n mapTool = Basemap(llcrnrlat=mode['minlat'], llcrnrlon=mode['minlon'], urcrnrlat=mode['maxlat'], urcrnrlon=mode['maxlon'])\n mapTool.fillcontinents(color='gray', alpha=self.define.ALPHA)\n mapTool.drawcountries()\n mapTool.drawcoastlines()\n # lon / lat grid 설정\n latRange = np.arange(-90., 90., self.define.MAPGRID)\n mapTool.drawparallels(latRange, labels=[1, 1, 1, 1], fontsize=self.define.FONTSIZE)\n lonRange = np.arange(0., 360., self.define.MAPGRID)\n mapTool.drawmeridians(lonRange, labels=[1, 0, 0, 1], fontsize=self.define.FONTSIZE)\n return mapTool\n\n def get_data(self, mode):\n \"\"\"\n store the data in its latitude / longitude in a two-dimensional array and return array\n :param mode: map scan mode\n :return: Xaxis, Yaxis, 2d array map data\n \"\"\"\n productVal, referenceVal = self.ncdata.get_value()\n # map에 보여주기 위한 2차원 배열 생성후 초기화\n arrayData = np.empty((int((mode['maxlat']-mode['minlat']) / self.map_interval),int((mode['maxlon']-mode['minlon']) / self.map_interval)))\n arrayData[:] = np.NAN\n mapX = np.arange(mode['minlon'], mode['maxlon'], self.map_interval)\n mapY = np.arange(mode['minlat'], mode['maxlat'], self.map_interval)\n # 데이터 수만큼 반복을 진행하여 2차원 배열에 저장\n for lat, lon, product, reference in zip(self.ncdata.get_lat(), self.ncdata.get_lon(), productVal, referenceVal):\n indexLat = int((lat - mode['minlat']) / self.map_interval)\n indexLon = int((lon - mode['minlon']) / self.map_interval)\n if not np.isnan(arrayData[indexLat, indexLon]):\n continue\n if indexLat >= (mode['maxlat']-mode['minlat']) / self.map_interval or indexLon >= (mode['maxlon']-mode['minlon']) / self.map_interval:\n continue\n arrayData[indexLat, indexLon] = product - reference\n maskedData = np.ma.masked_invalid(arrayData) # 유효하지 않은 값 mask 씌우기\n mapX, mapY = np.meshgrid(mapX, mapY) # 1차원 배열인 mapX, mapY를 2차원 배열의 형태로 변환하여 보여주기 위해 필요한 함수\n return maskedData, mapX, mapY\n\n def draw_data(self, mapTool, mapData, mapX, mapY, iniReader):\n \"\"\"\n draw the data in the map\n :param mapTool: the shape of generated map\n :param mapData: 2D array map data\n :param mapX: Xaxis\n :param mapY: Yaxis\n :param iniReader: object of ConfigParser\n \"\"\"\n mapX, mapY = mapTool(mapX, mapY) # mapX, mapY를 map 형태에 맞게 Mapping\n plot = mapTool.pcolormesh(mapX, mapY, mapData, norm=self.norm, cmap=self.colors)\n plot_colorbar = mapTool.colorbar(plot, location='bottom', pad=\"8%\", extend='both')\n if iniReader.showLegend == 'True':\n plot_colorbar.set_label('mm/h', x=1)\n elif iniReader.showLegend !='False' and iniReader.showLegend !='True':\n self.logger.logger.error('ini File value Error : show_legend \\n Default : False')\n # Title과 이미지 저장을 위해 사용될 날짜 값들\n self.startYear, self.startMonth, self.startDay = self.common.split_date(self.startDate)\n self.finishYear, self.finishMonth, self.finishDay = self.common.split_date(self.finishDate)\n self.set_title(iniReader)\n self.save_plot(iniReader)\n plt.close()\n\n def set_title(self, iniReader):\n \"\"\"\n set title in the map\n :param iniReader: object of ConfigParser\n \"\"\"\n plt.title('%s(%s - %s)\\n %s vs. %s(%s.%s.%s ~ %s.%s.%s)'\n %(self.title, iniReader.product, self.reference, iniReader.product, self.reference, self.startYear,\n self.startMonth, self.startDay, self.finishYear, self.finishMonth, self.finishDay))\n\n\n\n def save_plot(self, iniReader):\n \"\"\"\n save the map in image storage path\n :param iniReader: object of ConfigParser\n \"\"\"\n savepath = self.common.get_path(iniReader.savepath, iniReader.product, self.reference)\n plt.savefig('%s/ami_%s_%s_%s_map_%s%s%s_%s%s%s.png'\n %(savepath, iniReader.product, self.reference, self.mode.lower(), self.startYear,self.startMonth,\n self.startDay, self.finishYear, self.finishMonth, self.finishDay))\n\n","sub_path":"CreateStatisticalMap.py","file_name":"CreateStatisticalMap.py","file_ext":"py","file_size_in_byte":8202,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"529832403","text":"from argparse import ArgumentParser\nimport requests\nimport json\nimport sys\n\n\nparser = ArgumentParser(\n description='Parameters used to compute most frequent pages per subdomain',\n)\n\nparser.add_argument(\"--url\", default=None, type=str, help=\"Workspace URL\")\nparser.add_argument(\"--pat\", default=None, type=str, help=\"Personal Access Token\")\nparser.add_argument(\"--path\", default=None, type=str, help=\"Absolute path to model metadata json file\")\n\nargs = parser.parse_args()\n\nworskpace_url = args.url.strip(\"/\")\n\nheaders = {\"Authorization\": f\"Bearer {args.pat}\"}\n\n\n# load model version to test\nwith open(args.path) as json_file:\n model_metadata = json.load(json_file)\n\n\n# Check current stage before transitioning\nmodel_name_and_version = {\n \"name\": model_metadata[\"model_name\"],\n \"version\": model_metadata[\"model_version\"],\n}\n\ncurrent_stage_req = requests.get(f\"{worskpace_url}/api/2.0/mlflow/model-versions/get\", data=json.dumps(model_name_and_version), headers=headers)\ncurrent_stage = current_stage_req.json()[\"model_version\"][\"current_stage\"]\n\nif current_stage != \"None\":\n print(f\"Model stage is '{current_stage}' != 'None' which means no new model was created. Skipping transition to Staging.\")\n sys.exit()\n\n# transition staging model to prod\nnew_model_to_staging_data = {\n \"name\": model_metadata[\"model_name\"],\n \"version\": model_metadata[\"model_version\"],\n \"stage\": \"Staging\",\n \"archive_existing_versions\": \"False\",\n}\n\nnew_model_to_staging_req = requests.post(f\"{worskpace_url}/api/2.0/mlflow/model-versions/transition-stage\", data=json.dumps(new_model_to_staging_data), headers=headers)\nprint(\"Moved new model to staging\")\n","sub_path":"ci-cd-scripts/transition-new-model-to-staging.py","file_name":"transition-new-model-to-staging.py","file_ext":"py","file_size_in_byte":1657,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"218140394","text":"#!/usr/bin/python\n\n\"\"\"\ndate >> df.txt\ndf | sort | grep /dev/sd >> df.txt\n\nFri Apr 29 21:47:35 CDT 2016\n/dev/sda1 1922728752 263520744 1561515952 15% /media/Borg_LS\n/dev/sdb6 351784100 238139416 95752032 72% /\n/dev/sdb7 40185208 49036 38071788 1% /media/OSM040\n/dev/sdb8 71897424 24760156 43461980 37% /media/OSM070\n/dev/sdc1 302248384 64352 286807648 1% /media/OSM300\n/dev/sdc2 151058636 60872 143301380 1% /media/OSM150\n/dev/sdc3 201454560 60692 191137484 1% /media/OSM200\n/dev/sdc4 329221796 68304 312406948 1% /media/OSM325\n\n\"\"\"\n\nimport csv\nimport os\nfrom datetime import datetime\nfrom datetime import timedelta\n\nfrom matplotlib.dates import date2num\nimport matplotlib.pyplot as plt\n\n\ndef dstat_format_func(keys, x, st=None):\n if \"time\" in keys[1]:\n # 30-04 12:47:38\n assert st is not None\n dt = datetime.strptime(x, \"%d-%m %H:%M:%S\")\n dt = dt.replace(year=2016)\n dt = dt - st\n return dt.total_seconds()\n elif \"read\" in keys[1]:\n return float(x)/1024.0/1024.0\n elif \"writ\" in keys[1]:\n return float(x)/1024.0/1024.0\n elif \"swap\" in keys[0]:\n return float(x)/1024.0/1024.0/1024.0\n elif \"paging\" in keys[0]:\n return float(x)/1024.0/1024.0\n elif \"memory usage\" in keys[0]:\n if \"buff\" in keys[1]:\n return float(x)/1024.0/1024.0\n else:\n return float(x)/1024.0/1024.0/1024.0\n else:\n return float(x)\n\n\ndef read_osm2pgsql(filename):\n osm2pgsqldict = {}\n with open(filename) as csvfile:\n reader = csv.reader(csvfile, delimiter=',')\n row = reader.next()\n assert row[0].lower() == 'i_flag'\n has_parallel_indexing = row[1].lower() == 'true'\n row = reader.next()\n dt0 = datetime.strptime(row[1], \"%a %b %d %H:%M:%S %Z %Y\")\n osm2pgsqldict[row[0]] = dt0\n dt = dt0\n\n for _ in range(4):\n row = reader.next()\n dt += timedelta(seconds=float(row[1]))\n osm2pgsqldict[row[0]] = dt\n\n if has_parallel_indexing:\n for row in reader:\n dt += timedelta(seconds=float(row[1]))\n osm2pgsqldict[row[0]] = dt\n osm2pgsqldict.pop('result', None)\n else:\n temp_dict = {}\n for row in reader:\n if row[0].startswith('#'):\n continue\n temp_dict[row[0]] = float(row[1])\n osm2pgsqldict['result'] = dt0 + timedelta(seconds=temp_dict['result'])\n osm2pgsqldict['planet_osm_rels'] = osm2pgsqldict['result'] - timedelta(seconds=temp_dict['planet_osm_rels'])\n osm2pgsqldict['planet_osm_ways'] = osm2pgsqldict['planet_osm_rels'] - timedelta(seconds=temp_dict['planet_osm_ways'])\n return osm2pgsqldict\n\n\ndef read_df(filename, start_time):\n dfdict = {}\n startsize = -1\n with open(filename) as ifs:\n for line in ifs:\n line = line.strip()\n if line.startswith('/'):\n cols = line.split()\n\n if cols[0] not in dfdict:\n dfdict[cols[0]] = []\n\n if cols[5] == '/':\n if startsize < 0:\n startsize = float(cols[2])\n col = float(cols[2]) - startsize\n else:\n col = float(cols[2])\n\n dfdict[cols[0]].append(float(col)/1024.0/1024.0)\n else:\n dt = datetime.strptime(line, \"%a %b %d %H:%M:%S %Z %Y\")\n dt = dt - start_time\n if 'datetime' not in dfdict:\n dfdict['datetime'] = [dt.total_seconds()]\n else:\n dfdict['datetime'].append(dt.total_seconds())\n return dfdict\n\n\ndef read_du(filename, start_time):\n dudict = {}\n headers = []\n with open(filename) as csvfile:\n reader = csv.reader(csvfile, delimiter=',')\n header = reader.next()\n for h in header:\n if h != '':\n headers.append(h)\n dudict[h] = []\n for row in reader:\n for i, col in enumerate(row):\n if col != '':\n if headers[i] == 'time':\n dt = datetime.strptime(col, \"%a %b %d %H:%M:%S %Z %Y\")\n dt = dt - start_time\n dudict[headers[i]].append(dt.total_seconds())\n else:\n dudict[headers[i]].append(float(col)/1024.0/1024.0)\n return dudict\n\n\ndef read_dstat(filename, start_time):\n dstatdict = {}\n with open(filename) as csvfile:\n reader = csv.reader(csvfile, delimiter=',')\n\n # Skip the first five lines\n reader.next()\n reader.next()\n reader.next()\n reader.next()\n reader.next()\n\n # lines 6 and 7 contain the header information\n header0 = reader.next()\n header1 = reader.next()\n headers = []\n for i, (hh, h1) in enumerate(zip(header0, header1)):\n if hh != '':\n h0 = hh\n if h0 not in dstatdict:\n dstatdict[h0] = {}\n if h1 not in dstatdict[h0]:\n dstatdict[h0][h1] = []\n else:\n dstatdict[h0][h1] = []\n if h1 == \"time\":\n time_col = i\n headers.append([h0, h1])\n\n for row in reader:\n for i, col in enumerate(row):\n if i == time_col:\n dstatdict[headers[i][0]][headers[i][1]].append(dstat_format_func(headers[i], col, st=start_time))\n else:\n dstatdict[headers[i][0]][headers[i][1]].append(dstat_format_func(headers[i], col))\n return dstatdict\n\n\nrun_idx = 'benchmarks/f10'\n\nosm2pgsql_file = run_idx+'/osm2pgsql.txt'\nosm2pgsql_dict = read_osm2pgsql(osm2pgsql_file)\nstart_time = osm2pgsql_dict['Start time']\n\ndf_file = run_idx+'/df.txt'\nif os.path.exists(df_file):\n df_dict = read_df(df_file, start_time)\n # df_dates = date2num(df_dict['datetime'])\nelse:\n df_dict = None\n\ndu_file = run_idx+'/du.txt'\nif os.path.exists(du_file):\n du_dict = read_du(du_file, start_time)\n # du_dates = date2num(du_dict['time'])\nelse:\n du_dict = None\n\ndstat_file = run_idx+'/dstat.txt'\nif os.path.exists(dstat_file):\n dstat_dict = read_dstat(dstat_file, start_time)\n # dstat_dates = date2num(dstat_dict['system']['time'])\nelse:\n dstat_dict = None\n\nymaxs = [250, 500, 250, 250, 250, 128, 100, 25, 20]\nfig, ax = plt.subplots(len(ymaxs), sharex=True, figsize=(16, 10))\n\nif df_dict is not None:\n if 'dsk/sdb8' in dstat_dict:\n ax[0].plot(df_dict['datetime'], df_dict['/dev/sdb8'], 'r-', lw=1)\n ax[0].plot(df_dict['datetime'], df_dict['/dev/sdb6'], 'g-', lw=2)\n\nif dstat_dict is not None:\n if 'dsk/sdc1' in dstat_dict:\n ax[1].plot(dstat_dict['system']['time'], dstat_dict['dsk/sdc1']['writ'], 'y-')\n ax[1].plot(dstat_dict['system']['time'], dstat_dict['dsk/sdc1']['read'], 'b-')\nif df_dict is not None:\n if 'dsk/sdc1' in dstat_dict:\n ax[1].plot(df_dict['datetime'], df_dict['/dev/sdc1'], 'g-', lw=2)\nif du_dict is not None:\n ax[1].plot(du_dict['time'], du_dict['main_data'], 'k-', lw=2)\n\nif dstat_dict is not None:\n if 'dsk/sdc2' in dstat_dict:\n ax[2].plot(dstat_dict['system']['time'], dstat_dict['dsk/sdc2']['writ'], 'y-')\n ax[2].plot(dstat_dict['system']['time'], dstat_dict['dsk/sdc2']['read'], 'b-')\nif df_dict is not None:\n if 'dsk/sdc2' in dstat_dict:\n ax[2].plot(df_dict['datetime'], df_dict['/dev/sdc2'], 'g-', lw=2)\nif du_dict is not None:\n ax[2].plot(du_dict['time'], du_dict['main_index'], 'k-', lw=2)\n\nif dstat_dict is not None:\n if 'dsk/sdc3' in dstat_dict:\n ax[3].plot(dstat_dict['system']['time'], dstat_dict['dsk/sdc3']['writ'], 'y-')\n ax[3].plot(dstat_dict['system']['time'], dstat_dict['dsk/sdc3']['read'], 'b-')\nif df_dict is not None:\n if 'dsk/sdc3' in dstat_dict:\n ax[3].plot(df_dict['datetime'], df_dict['/dev/sdc3'], 'g-', lw=2)\nif du_dict is not None:\n ax[3].plot(du_dict['time'], du_dict['slim_data'], 'k-', lw=2)\n\nif dstat_dict is not None:\n if 'dsk/sdc4' in dstat_dict:\n ax[4].plot(dstat_dict['system']['time'], dstat_dict['dsk/sdc4']['writ'], 'y-')\n ax[4].plot(dstat_dict['system']['time'], dstat_dict['dsk/sdc4']['read'], 'b-')\nif df_dict is not None:\n if 'dsk/sdc4' in dstat_dict:\n ax[4].plot(df_dict['datetime'], df_dict['/dev/sdc4'], 'g-', lw=2)\nif du_dict is not None:\n ax[4].plot(du_dict['time'], du_dict['slim_index'], 'k-', lw=2)\n\nif dstat_dict is not None:\n ax[5].plot(dstat_dict['system']['time'], dstat_dict['memory usage']['used'], 'g-', lw=2)\n ax[5].plot(dstat_dict['system']['time'], dstat_dict['memory usage']['cach'], 'b-', lw=2)\n ax[5].plot(dstat_dict['system']['time'], dstat_dict['memory usage']['free'], 'k-', lw=2)\n\nif dstat_dict is not None:\n ax[6].plot(dstat_dict['system']['time'], dstat_dict['total cpu usage']['usr'], '-')\n ax[6].plot(dstat_dict['system']['time'], dstat_dict['total cpu usage']['sys'], '-')\n\nif dstat_dict is not None:\n if 'swap' in dstat_dict:\n ax[7].plot(dstat_dict['system']['time'], dstat_dict['swap']['used'], '-')\n\nif dstat_dict is not None:\n if 'paging' in dstat_dict:\n ax[8].plot(dstat_dict['system']['time'], dstat_dict['paging']['out'], 'r-')\n ax[8].plot(dstat_dict['system']['time'], dstat_dict['paging']['in'], 'b-')\n\n# ax[8].plot(dstat_dict['system']['time'], dstat_dict['memory usage']['buff'], '-')\n\n# ax[9].plot(dstat_dict['system']['time'], dstat_dict['total cpu usage']['wai'], '-', color='r')\n# ax[9].plot(dstat_dict['system']['time'], dstat_dict['total cpu usage']['hiq'], '-')\n# ax[9].plot(dstat_dict['system']['time'], dstat_dict['total cpu usage']['siq'], '-')\n\n# ax[10].plot(dstat_dict['system']['time'], dstat_dict['load avg']['1m'], '-')\n# ax[10].plot(dstat_dict['system']['time'], dstat_dict['load avg']['5m'], '-')\n# ax[10].plot(dstat_dict['system']['time'], dstat_dict['load avg']['15m'], '-')\n\nfor i, ymax in enumerate(ymaxs):\n for key, value in osm2pgsql_dict.iteritems():\n value = value - start_time\n ax[i].vlines(value.total_seconds(), 0, ymax, label=key)\n ax[i].set_ylim([0, ymax])\n ax[i].set_xlim([-300, 72000])\n\nfig.subplots_adjust(hspace=0)\nplt.setp([a.get_xticklabels() for a in fig.axes[:-1]], visible=False)\nplt.show()\n","sub_path":"osm_utils.py","file_name":"osm_utils.py","file_ext":"py","file_size_in_byte":10506,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"586130199","text":"\"\"\"\nImplementation of Delta Learning Rule.\nDelta W = C * (Di - Oi) * f' * Xi\nNew Weight = Old Weight + Delta W\n\"\"\"\nimport numpy as np\n\nfrom .activation_functions import bipolar_sigmoid\nfrom .learning_rules import delta\n\n\ndef main(x: np.array, weight: np.array, const: float, d: np.array) -> np.array:\n print(f\"\\nWeight 1: {weight}\")\n\n for i, xi in enumerate(x):\n net = np.matmul(weight, xi)\n print(f\"Net {i+1}: {net}\")\n\n out = bipolar_sigmoid(net)\n print(f\"Out {i+1}: {out}\")\n\n weight += delta(d[i], out, xi, const)\n print(f\"\\nWeight {i + 2}: {weight}\")\n\n return weight\n\n\nif __name__ == \"__main__\":\n n = int(input(\"Enter number of 1D input vectors: \"))\n const = float(input(\"Enter value of constant: \"))\n\n if n > 1:\n x = np.array(\n [float(j) for j in input(f\"Enter elements in x1: \").split()],\n dtype=np.float,\n ) # input vector\n ln = len(x)\n\n for i in range(n - 1):\n xi = np.array(\n [\n float(j)\n for j in input(f\"Enter elements in x{i+2}: \").split()\n ],\n dtype=np.float,\n )\n x = np.vstack((x, xi))\n\n d = np.array(\n [\n float(j)\n for j in input(f\"Enter values for desired output di: \").split()\n ],\n dtype=np.float,\n ) # di vector\n\n w = np.array(\n [float(j) for j in input(f\"Enter initial weights: \").split()],\n dtype=np.float,\n )\n if len(w) != ln:\n print(\"... Using default weights\")\n w = np.zeros(ln)\n\n w = main(x, w, const, d)\n print(f\"\\nFinal weights are: {w}\")\n","sub_path":"Soft_Computing/delta_learning_rule.py","file_name":"delta_learning_rule.py","file_ext":"py","file_size_in_byte":1748,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"520004800","text":"import tkinter as tk\nfrom tkinter import Label, Entry, IntVar, Button\nimport pages.start\n\nclass YieldPage(tk.Frame):\n\n def __init__(self, parent, controller):\n tk.Frame.__init__(self, parent)\n \n self.grid_columnconfigure(0, weight=1)\n self.grid_columnconfigure(1, weight=1)\n self.l_c = Label(self,text=\"Carbon in Wt%:\")\n self.l_rec_c = Label(self, text=\"Recommended:The range should lie within 0.05-0.07.\",wraplength=500)\n self.l_rec_f = Label(self, text=\"Ferrite recommended value in Wt%:\")\n self.l_rec_p = Label(self, text=\"Pearlite recommended value in Wt%:\")\n self.l_rec_mn=Label(self,text=\"Mangenese recommended value:\")\n self.l_gsize = Label(self, text=\"Grainsize dia in ASTM:\")\n self.l_s = Label(self, text=\"Sulphur in Wt%:\")\n self.l_si = Label(self, text=\"Silicon in Wt%:\")\n self.l_nf = Label(self,text=\"Nitrogen in Ferrite in Wt%\")\n main = Label(self, font=('25'), text=\"YIELD STRENGTH\", fg='blue', bg='lightblue')\n\n self.e_c = Entry(self, textvariable=IntVar())\n self.e_rec_f = Entry(self, textvariable=IntVar())\n self.e_rec_p = Entry(self, textvariable=IntVar())\n self.e_rec_mn = Entry(self, textvariable=IntVar())\n self.e_gsize = Entry(self, textvariable=IntVar())\n self.e_s = Entry(self, textvariable=IntVar())\n self.e_si = Entry(self, textvariable=IntVar())\n self.e_nf = Entry(self, textvariable=IntVar())\n\n main.grid(row=0, column=0, columnspan=2, pady=10, sticky='we')\n\n self.l_c.grid(row=2, column=0, sticky='e')\n self.l_rec_c.grid(row=1, column=0, columnspan=2)\n self.e_c.grid(row=2, column=1, padx=5, pady=5, sticky='w')\n \n tk.Button(self, text=\"Show Recommended Values\", command=self.enterRecValues) \\\n .grid(row=4, column=0, columnspan=2, padx=5,pady=5)\n\n self.l_rec_f.grid(row=5, column=0, sticky='e')\n self.e_rec_f.grid(row=5, column=1, padx=5, pady=5, sticky='w')\n\n self.l_rec_p.grid(row=6, column=0, sticky='e')\n self.e_rec_p.grid(row=6, column=1, padx=5, pady=5, sticky='w')\n\n self.l_rec_mn.grid(row=7, column=0, sticky='e')\n self.e_rec_mn.grid(row=7, column=1, padx=5, pady=5, sticky='w') \n\n self.l_gsize.grid(row=8, column=0, sticky='e')\n self.e_gsize.grid(row=8, column=1, padx=5, pady=5, sticky='w')\n\n self.l_s.grid(row=9, column=0, sticky='e')\n self.e_s.grid(row=9, column=1, padx=5, pady=5, sticky='w')\n\n self.l_si.grid(row=10, column=0, sticky='e')\n self.e_si.grid(row=10, column=1, padx=5, pady=5, sticky='w')\n\n self.l_nf.grid(row=11, column=0, sticky='e')\n self.e_nf.grid(row=11, column=1, padx=5, pady=5, sticky='w')\n\n self.labelText = Label(self, text=\"Yield strength =\")\n self.labelText.grid(row=12, column=0, sticky='e')\n\n self.Yield = Entry(self)\n self.Yield.grid(row=12, column=1, padx=5, pady=5, sticky='w')\n \n bt = Button(self, text=\"CALCULATE\", command=self.textEntries)\n bt.grid(row=13, column=0, columnspan=2, padx=10, pady=10)\n\n button1 = tk.Button(self, text=\"Back to Home\",\n command=lambda: controller.show_frame(pages.start.StartPage))\n button1.grid(row=14, column=0, columnspan=2, padx=10, pady=10)\n\n def enterRecValues(self): # shows recommended amounts on the basis of carbon content entered by the user\n carbon = float(self.e_c.get())\n ferrite=(0.8-carbon)/(0.78)*100\n\n self.e_rec_f.delete(0,\"end\") # clears previous value(if any) from the bar\n self.e_rec_f.insert(0,ferrite)# inserts new value\n\n mn = (0.35-carbon)*6\n\n self.e_rec_mn.delete(0,\"end\")\n self.e_rec_mn.insert(0,mn)\n\n self.e_rec_p.delete(0,\"end\")\n self.e_rec_p.insert(0,100-ferrite)\n \n def textEntries(self): # takes the values entered by the user\n carbon = float(self.e_c.get())\n ferrite=(0.8-carbon)/(0.78)*100\n mn = (0.35-carbon)*6\n grainsize=float(self.e_gsize.get())\n sulphur=float(self.e_s.get())\n silicon=float(self.e_si.get())\n nf=float(self.e_nf.get())\n\n pearlite=100-ferrite\n x=ferrite/100\n\n result = None\n try:\n yieldst=x**(0.33)*(35+58*(mn)+17.4*(1.0/(grainsize**(0.5))))+(1-x**0.33)*(178+3.8*(1.0/(sulphur**(0.5))))+63*(silicon)+425*nf\n except ZeroDivisionError:\n result = 'div by 0 exception!'\n else:\n result = yieldst\n \n self.Yield.delete(0,\"end\") \n self.Yield.insert(0, result)\n \n #def check_entry(\n","sub_path":"pages/yieldst.py","file_name":"yieldst.py","file_ext":"py","file_size_in_byte":4674,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"647191155","text":"import http.server\n\nclass Main(object):\n def __init__(self):\n self.port = 8000\n self.handler = http.server.CGIHTTPRequestHandler\n self.httpd = http.server.HTTPServer((\"\",self.port),self.handler)\n\n def run(self):\n print(\"servering at port\", self.port)\n self.httpd.serve_forever()\n\nm = Main()\nm.run()\n","sub_path":"intro_python/server.py","file_name":"server.py","file_ext":"py","file_size_in_byte":340,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"16424864","text":"#-*- coding:utf-8 -*-\n\nimport re\nimport requests\nfrom HTMLParser import HTMLParser\n\nimport sqlite3\n\n\nimport sys \nreload(sys) \nsys.setdefaultencoding('utf8')\n\ndef _attr(attrs,attrname):\n\tfor attr in attrs:\n\t\tif attr[0]==attrname:\n\t\t\treturn attr[1]\n\treturn None\n\nclass PoemParser(HTMLParser):\n\t\"\"\"docstring for PoemParser\"\"\"\n\t# def __init__(self, arg):\n\t\t# super(PoemParser, self).__init__()\n\t\t# self.arg = arg\n\tdef __init__(self):\n\t\tHTMLParser.__init__(self)\n\t\tself.tangshi_list=[]\n\t\t#insert code\n\t\t# pass\n\t\tself.in_div=False\n\t\tself.in_a=False\n\t\tself.pattern=re.compile(r'''\n\t\t\t\t\t\t(.+) #匹配标题 group(1)\n\t\t\t\t\t\t\\(\t\t#匹配作者左边的括号 \n\t\t\t\t\t\t(.+) #匹配标题 group(2)\n\t\t\t\t\t\t\\)\t\t#匹配作者右边的括号\t\n\t\t\t\t\t\t''', re.VERBOSE)\n\t\tself.current_poem={}\n\n\n\n\tdef handle_starttag(self,tag,attrs):\n\t\t# pass\n\t\tif tag=='div' and _attr(attrs, 'class')=='guwencont2':\n\t\t\tself.in_div=True\n\n\t\tif self.in_div and tag=='a':\n\t\t\tself.in_a=True\n\t\t\tself.current_poem['url']='http://www.gushiwen.org'+_attr(attrs, 'href')\n\n\n\tdef handle_endtag(self,tag):\n\t\t# pass\n\t\tif tag=='a':\n\t\t\tself.in_a=False\n\n\t\tif tag=='div':\n\t\t\tself.in_div=False\n\n\n\tdef handle_data(self,data):\n\t\t# pass\n\t\tif self.in_a:\n\t\t\t# print (data)\n\t\t\tm=self.pattern.match(data)\n\t\t\tif m:\n\t\t\t\tself.current_poem['title']=m.group(1)\n\t\t\t\tself.current_poem['author']=m.group(2)\n\t\t\t\tself.tangshi_list.append(self.current_poem)\n\t\t\t\tself.current_poem={}\n\n\n\ndef retrive_tangshi_300():\n\turl='http://www.gushiwen.org/gushi/tangshi.aspx'\n\tr=requests.get(url)\n\tp=PoemParser()\n\tp.feed(r.content)\n\treturn p.tangshi_list\n\n\nclass PoemContentParser(HTMLParser):\n\tdef __init__(self):\n\t\tHTMLParser.__init__(self)\n\t\tself.content=[]\n\t\tself.in_p=False\n\n\tdef handle_starttag(self,tag,attrs):\n\t\t# pass\n\t\tif tag=='p' and _attr(attrs, 'align')=='center':\n\t\t\tself.in_p=True\n\n\tdef handle_endtag(self,tag):\n\t\t# pass\n\t\tif tag=='p':\n\t\t\tself.in_p=False\n\n\tdef handle_data(self,data):\n\t\t# pass\n\t\tif self.in_p:\n\t\t\tself.content.append(data)\n\n\ndef down_loadpoem(poem):\n\turl=poem['url']\n\tr=requests.get(url)\n\tp=PoemContentParser()\n\tp.feed(r.content)\n\tpoem['content']='\\n'.join(p.content)\n\n# 例外的情况处理\n#空白符whitespace\ndef trim_ws(s):\n\t# pass\n\tc=re.sub(r'\\s+', '', s)\n\t# c=c.replace('，', '\\n')\n\t# c=c.replace('。', '\\n')\n\tdef _add_crlf(m):\n\t\t# print m.group()\n\t\treturn m.group()+'\\n'\n\tc=re.sub(r'，|。', _add_crlf, c)\n\treturn c\ndef trim_href(s):\n\t# pass\n\tc=s.replace('
', '')\n\talt=re.search(r'alt\\s*=\\s*\\\"(.*?)\\\"', c,re.IGNORECASE)\n\tc=re.sub(r'', alt.group(1), c)\n\tc=trim_ws(c)\n\treturn c\n\ndef trim_test():\n s = \"\"\"月落乌啼霜满天，江枫渔火对愁眠。\n 姑苏城外\n 寒山\n 寺，夜半钟声到客船。\"\"\"\n print(trim_ws(s))\n\n s = \"\"\"\n 凉风起天末，君子意如何。
\n 鸿雁几时到，江湖秋水多。
\n 文章憎命达，魑魅喜人过。
\n 应共冤魂语，投![\"诗\"](\"http://www.gushiwen.org/favicon.ico\" "\\"诗\\"")
\n 赠汨罗。\"\"\"\n print(trim_href(s))\n\n\nif __name__=='__main__':\n\t# l=retrive_tangshi_300()\n\t# print ('totoal %d poems.' %len(l))\n\t# for i in range(10):\n\t# \tprint ('标题： %(title)s\\t 作者： %(author)s\\t URL：%(url)s' %(l[i]))\n\n\t# conn=sqlite3.connect('tangshi.sqlite')\n\t# cur=conn.cursor()\n\t# conn.text_factory = str\n\t# cur.executescript('''\n\t# \t\tdrop table if exists tangshi;\n\t# \t\tcreate table tangshi (\n\t# \t\tid integer not null primary key autoincrement unique,\n\t# \t\ttitle text,\n\t# \t\tauthor text,\n\t# \t\turl text unique\n\t# \t\t);\n\t# \t''')\n\t# for i in l:\n\t# \tcur.execute('''\n\t# \t\tinsert into tangshi (title,author,url) values (?,?,?)''',\n\t# \t\t(i['title'],i['author'],i['url']))\n\t# \tconn.commit()\n\t# conn.close()\n\t# for i in range(10):\n\t# \tprint ('#%d downloading poem from: %s' %(i,l[i]['url']))\n\t# \tdown_loadpoem(l[i])\n\t# \tprint('标题： %(title)s\\t 作者： %(author)s\\t URL：%(url)s\\t %(content)s' %(l[i]))\n\ttrim_test()\n\n\n","sub_path":"tangshi.py","file_name":"tangshi.py","file_ext":"py","file_size_in_byte":4053,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"650965854","text":"#developer Daniel Zambrano\r\nimport os\r\nfrom random import randint\r\n\r\n\r\ndef main():\r\n global players,box\r\n players = randint(2,4)\r\n print(\"number of players\", players)\r\n level = randint(1,3)\r\n if level == 1:\r\n box = 20\r\n elif level == 2:\r\n box = 30\r\n else :\r\n box = 40\r\n print(\"Level:\", level)\r\n print(\"you have to reach:\", box)\r\n\r\n#aqui los dados generean aleatoriamente un numero\r\n\r\ndef start():\r\n status = True\r\n i = 1\r\n while status :\r\n os.system(\"cls\")\r\n print(\"press any key to player\",i)\r\n KEY = ()\r\n D1 = randint(1,6)\r\n D2 = randint(1,6)\r\n T = D1+D2\r\n print(\"Dado1:\", D1)\r\n print(\"Dado2:\", D2)\r\n print(\"Total:\",T)\r\n i = i + 1\r\n if i == players+1 :\r\n i = 1\r\n KEY = input(\"press any key to pass the turn\")\r\n N= T + T #este hace que se sumen los totales\r\n if N != box :\r\n N += T\r\n elif N == box:\r\n print(\"you win\")\r\n \r\n\r\n \r\n\r\n#comienzo\r\nos.system (\"cls\")\r\nprint(\"BIENVENIDO\")\r\nKEY = input(\"press any key to star the game\")\r\nmain()\r\nKEY = input(\"press any key to continius\")\r\nstart()\r\nKEY = input(\"press any key to start the game again\")\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n","sub_path":"evaluacion.py","file_name":"evaluacion.py","file_ext":"py","file_size_in_byte":1265,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"355154709","text":"\"\"\"REST API for voter info.\"\"\"\r\nimport flask\r\nimport votenow\r\nimport requests\r\n\r\n\r\n@votenow.app.route('/api/v1/voterinfo/',\r\n methods=[\"GET\"])\r\ndef get_voter_info():\r\n \"\"\"Return voter information on address.\"\"\"\r\n\r\n context = {}\r\n address = flask.request.args.get('address')\r\n\r\n # URL\r\n url = \"https://www.googleapis.com/civicinfo/v2/voterinfo\"\r\n url += \"?key=AIzaSyAY9DEXPtO4qJJRzGTun12HnpQ0dS8z8V8\"\r\n url += \"&address=\"\r\n url += address\r\n\r\n r = requests.get(url)\r\n\r\n context = r.json()\r\n\r\n return flask.jsonify(**context)\r\n","sub_path":"votenow/api/info.py","file_name":"info.py","file_ext":"py","file_size_in_byte":576,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"54945088","text":"from socketIO_client_nexus import SocketIO, BaseNamespace\nfrom Crypto.Hash import MD5\nfrom Crypto.Cipher import AES\nfrom Crypto.Util.Padding import unpad, pad\nfrom base64 import b64decode, b64encode\nfrom Crypto.Random import get_random_bytes\nimport json\n\n\ndef decryption(payload):\n # print('welcome received', data)\n # payloadSlice = data.split(\"*\")\n resp = []\n try:\n for data in payload:\n decrypted = str(\n decrypt(data[\"data1\"], data[\"iv\"], data[\"apiKey\"]), \"utf8\")\n jsonPayload = json.loads(decrypted)\n jsonPayload[\"deviceId\"] = data['deviceId']\n jsonPayload[\"localAddress\"] = data['localAddress']\n print(jsonPayload)\n resp.append(jsonPayload)\n except Exception:\n decrypted = {\"error\": \"decryption error\"}\n resp.append(decrypted)\n\n socketIO.emit(\"generic_event\", {\n \"event\": \"decryption_done\",\n \"payload\": resp\n })\n\n\ndef keep_alive(data):\n socketIO.emit(\"generic_event\", alive_payload)\n\n\ndef debug(data):\n print(data)\n socketIO.emit(\"debug_receive\", data)\n\n\ndef decrypt(data_element, iv, api_key):\n\n api_key = bytes(api_key, \"utf-8\")\n encoded = data_element\n\n hash = MD5.new()\n hash.update(api_key)\n key = hash.digest()\n\n cipher = AES.new(key, AES.MODE_CBC, iv=b64decode(iv))\n ciphertext = b64decode(encoded)\n padded = cipher.decrypt(ciphertext)\n plaintext = unpad(padded, AES.block_size)\n\n return plaintext\n\n\nsocketIO = SocketIO('http://localhost:7878', verify=True,\n wait_for_connection=True)\nalive_payload = {\"event\": \"gateway_status\", \"payload\": {\n \"client\": \"asdfas\",\n \"status\": \"alive\",\n \"broadcastFunction\": \"decrypt\"\n}\n}\nsocketIO.on('decrypt', decryption)\nsocketIO.on('alive', keep_alive)\nsocketIO.on('debug', debug)\nsocketIO.wait()\n","sub_path":"app/socketIOClient.py","file_name":"socketIOClient.py","file_ext":"py","file_size_in_byte":1848,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"62328208","text":"# add detr\nimport sys\nsys.path.append(\"/root/ProgProjekte/detr\")\n\nimport warnings\nwarnings.filterwarnings('ignore')\n\n\nfrom fastai import *\nfrom fastai.vision import *\n\nfrom object_detection_fastai.callbacks.callbacks import BBMetrics, PascalVOCMetric, PascalVOCMetricDETR\nfrom pathlib import Path\n\nfrom object_detection_fastai.loss.DetrCriterion import SetCriterionFastAi \nfrom object_detection_fastai.models.Detr import DETRFastAi\n\nfrom models.matcher import HungarianMatcher\n\n\naux_loss = False\nset_cost_class = 1\nset_cost_bbox = 5\nset_cost_giou = 2\neos_coef = 0.1\nnum_classes = 6\n\n\n\nbody = create_body(models.resnet18, True, -2)\nmodel = DETRFastAi(body, num_classes=num_classes, aux_loss=aux_loss)\n\n\nlosses = ['labels', 'boxes', 'cardinality']\nweight_dict = {'loss_ce': 1, 'loss_bbox': set_cost_bbox, 'loss_giou': set_cost_giou}\nmatcher = HungarianMatcher(cost_class=set_cost_class, cost_bbox=set_cost_bbox, cost_giou=set_cost_giou)\n\ncrit = SetCriterionFastAi(num_classes, matcher=matcher, weight_dict=weight_dict,\n eos_coef=eos_coef, losses=losses)\n\n\nsize = 128\ncoco = untar_data(URLs.COCO_TINY)\nimages, lbl_bbox = get_annotations(coco/'train.json') #'annotations/train_sample.json'\nimg2bbox = dict(zip(images, lbl_bbox))\nget_y_func = lambda o:img2bbox[o.name]\n\ndata = (ObjectItemList.from_folder(coco)\n #Where are the images? -> in coco\n .random_split_by_pct()\n #How to split in train/valid? -> randomly with the default 20% in valid\n .label_from_func(get_y_func)\n #How to find the labels? -> use get_y_func\n .transform(get_transforms(), tfm_y=True, size=size)\n #Data augmentation? -> Standard transforms with tfm_y=True\n .databunch(bs=16, collate_fn=bb_pad_collate)) #, num_workers=1\n #Finally we convert to a DataBunch and we use bb_pad_collate\n\n\nlearn = Learner(data, model, loss_func=crit, callback_fns=[ShowGraph, BBMetrics]) #,metrics=[voc]\n\nlearn.fit_one_cycle(3, 1e-3)\n\nprint()","sub_path":"object_detection_fastai/examples/DetrExample.py","file_name":"DetrExample.py","file_ext":"py","file_size_in_byte":2016,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"374450847","text":"from zope.interface import Interface\nfrom zope import schema\n\nfrom plone.app.registry.browser.controlpanel import RegistryEditForm\nfrom plone.app.registry.browser.controlpanel import ControlPanelFormWrapper\nfrom plone.z3cform import layout\n\nfrom dexterity.membrane import _\n\nlocal_roles_desc = u\"\"\"\nThe list of additional local roles members will be granted in the context\nof their own profile objects\n\"\"\"\nuse_email_as_username_desc = u\"\"\"\nIf checked, the value in the \"email\" field will be used as a username/login.\nIf unchecked, your content type must provide a \"username\" field.\n\"\"\"\nuse_uuid_as_userid_desc = u\"\"\"\nIf checked, the UUID value for the adapted object will be used for a userid.\nOtherwise, the username will be used for the userid.\n\"\"\"\n\n\nclass IDexterityMembraneSettings(Interface):\n \"\"\" Enables through-the-web configuration of some aspects of the\n dexterity.membrane behaviours.\n \"\"\"\n\n properties_whitelist = schema.Set(\n title=_(u'Properties whitelist'),\n description=_(u'The list of properties to fetch in the user object.'),\n value_type=schema.ASCIILine(title=_(u'Property')),\n required=False,\n missing_value=set([]),\n default=set([]),\n )\n\n local_roles = schema.Set(\n title=_(u'Local Roles'),\n description=_(u'local_roles',\n default=local_roles_desc),\n value_type=schema.TextLine(),\n required=False,\n missing_value=set([]),\n default=set([])\n )\n\n use_email_as_username = schema.Bool(\n title=_(u'Use email address for username?'),\n description=_(u'use_email_address_for_username',\n default=use_email_as_username_desc),\n required=False\n )\n\n use_uuid_as_userid = schema.Bool(\n title=_(u'Use object UUID for the userid?'),\n description=_(u'use_uuid_as_userid_desc',\n default=use_uuid_as_userid_desc),\n required=False\n )\n\n\nclass DexterityMembraneControlPanelForm(RegistryEditForm):\n schema = IDexterityMembraneSettings\n\n\nDexterityMembraneControlPanelView = layout.wrap_form(\n DexterityMembraneControlPanelForm, ControlPanelFormWrapper)\n","sub_path":"dexterity/membrane/behavior/settings.py","file_name":"settings.py","file_ext":"py","file_size_in_byte":2182,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"14727152","text":"class Solution:\n\n def depthFirst(self, sr, sc):\n\n # out of limit\n if not (0 <= sr < len(self.color)) or not (0 <= sc < len(self.color[0])):\n return False\n\n # if it is not the pond\n if self.color[sr][sc] != self.oldColor:\n return False\n\n # print(sr, sc, self.color[sr][sc])\n if self.color[sr][sc] == self.oldColor:\n self.color[sr][sc] = self.newColor\n self.depthFirst(sr - 1, sc)\n self.depthFirst(sr + 1, sc)\n self.depthFirst(sr, sc - 1)\n self.depthFirst(sr, sc + 1)\n\n return True\n\n def floodFill(self, image: List[List[int]], sr: int, sc: int, newColor: int) -> List[List[int]]:\n\n # if the new color and the color of the cluster is the same\n if image[sr][sc] == newColor:\n return image\n\n self.color = image\n self.oldColor = image[sr][sc]\n self.newColor = newColor\n self.depthFirst(sr, sc)\n return self.color","sub_path":"easy/Flood_Fill/source/dfs.py","file_name":"dfs.py","file_ext":"py","file_size_in_byte":1007,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"499931228","text":"import sys\nsys.stdin = open('input.txt')\n\nT = int(input())\nresult = [0]*T\ndef min_fee(month, fee):\n global total\n if month > 12:\n if total > fee:\n total = fee\n else:\n for i in range(3):\n if i == 0:\n min_fee(month +periods[i], fee + (fees[i]*infos[month]))\n else:\n min_fee(month +periods[i], fee + fees[i])\nfor t in range(T):\n fees = list(map(int, input().split()))\n infos = [0] + list(map(int, input().split()))\n periods = [1,1,3]\n total = fees[3]\n min_fee(1,0)\n result[t] = total\nfor r in range(T):\n print('#{} {}'.format(r+1, result[r]))","sub_path":"swea/1952/1952_김주현 코드.py","file_name":"1952_김주현 코드.py","file_ext":"py","file_size_in_byte":646,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"54362879","text":"from handler import Handler\nfrom google.appengine.ext import db\nimport hashlib, string, random, json\nfrom datetime import datetime\nfrom utils import *\nfrom data import *\n\nCACHE = {}\nfront_page_key = \"front page\"\ndef get_all_posts():\n if front_page_key in CACHE:\n return CACHE[front_page_key][0]\n else:\n posts = db.GqlQuery(\"SELECT * FROM Post \"\n \"ORDER BY created DESC\")\n CACHE[front_page_key] = (posts, datetime.now())\n return posts\n\ndef get_home_query_diff():\n if front_page_key in CACHE:\n return (datetime.now() - CACHE[front_page_key][1]).seconds\n else:\n return 0\n\ndef get_post(post_id):\n if post_id in CACHE:\n return CACHE[post_id][0]\n else:\n post = Post.get_by_id(post_id, parent=None)\n CACHE[post_id] = (post, datetime.now())\n return post\n\ndef get_query_diff(post_id):\n if post_id in CACHE:\n return (datetime.now() - CACHE[post_id][1]).seconds\n else:\n return 0\n\nclass Blog(Handler):\n def get(self):\n difference = get_home_query_diff()\n posts = get_all_posts()\n self.render(\"blog.html\", posts=posts, seconds=difference)\n\nclass NewPost(Handler):\n def render_page(self, subject=\"\", content=\"\", error=\"\"):\n self.render(\"blog_new_post.html\", subject=subject, content=content,\n error=error)\n\n def get(self):\n self.render_page()\n\n def post(self):\n subject = self.request.get(\"subject\")\n content = self.request.get(\"content\")\n\n if subject and content:\n post = Post(subject=subject, content=content)\n post.put()\n\n CACHE.pop(front_page_key, None)\n\n self.redirect(\"/blog/\" + str(post.key().id()))\n else:\n error = \"Please enter both a subject and content!\"\n self.render_page(subject, content, error)\n\nclass BlogPost(Handler):\n def render_page(self, blog_id=None, seconds=0):\n blog_post = get_post(blog_id)\n self.render(\"blog_post.html\", blog_post=blog_post,\n created_date=blog_post.created.date,\n seconds=seconds)\n\n def get(self, blog_id):\n self.render_page(int(blog_id), get_query_diff(int(blog_id)))\n\nclass BlogFlush(Handler):\n def get(self):\n CACHE.clear()\n self.redirect('/blog/')\n\nclass BlogJSON(Handler):\n def get(self):\n posts = Post.all()\n posts = list(posts)\n\n results = []\n for post in posts:\n results.append({'content' : post.content,\n 'subject' : post.subject,\n 'created' : str(post.created)\n })\n self.response.headers['Content-Type'] = \"application/json\"\n self.response.out.write(json.dumps(results))\n\nclass BlogPostJSON(Handler):\n def get(self, blog_id):\n post = Post.get_by_id(int(blog_id), parent=None)\n\n if post:\n self.response.headers['Content-Type'] = \"application/json\"\n self.response.out.write(json.dumps({'content' : post.content,\n 'subject' : post.subject,\n 'created' : str(post.created)\n }))\n else:\n self.response.out.write(\"Invalid post id\")\n","sub_path":"python/blog.py","file_name":"blog.py","file_ext":"py","file_size_in_byte":3370,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"326114870","text":"import json\n\n## Delete these values when the programm works!\nstats = [1000, 1000, 0, 0, 0]\ntime = 0\nconfig = json.load(open('DATA\\\\Warrior\\\\config'))\nskill = json.load(open('DATA\\\\Warrior\\\\Skills\\\\Longbow\\\\2'))\n\n\nenemy = {\n 'hitpoints': 10000000,\n 'armor': 1200,\n 'conditions': config['enemy_conditions']\n}\n\n\nplayer = {\n 'ressources': {\n 'hitpoints': 100,\n 'endurance': 100,\n 'adrenalin': 0\n },\n 'stats': stats,\n 'class_mechanics': config['class_mechanics'],\n 'active_weapon': 1,\n 'boons': config['boons']\n}\n\n## For now we use the higher weaponstrength, also find where dmg is for an arbitrary skill\ndef cast(enemy, player, skill, time):\n i = 0,\n while skill['facts'][i]['text'] != 'Damage':\n i = i+1\n\n base_damage = config['weapons']['mainhand' + str(player['active_weapon'])]['weaponstrength'][1] * player['stats'][1] * skill['facts'][i]['dmg_multiplier'] /enemy['armor']\n full_damage = base_damage * (1+enemy['conditions']['vulnerability'][T]*0.01)\n\ncast(enemy, player, skill, time)","sub_path":"SkillCaster.py","file_name":"SkillCaster.py","file_ext":"py","file_size_in_byte":1100,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"170019382","text":"import names\nimport random\nfrom random import randint\nfrom datetime import date, timedelta\nfrom randomtimestamp import randomtimestamp\n\n\njob_title_list = [\"Manager\", \"Salesperson\", \"Engineer\", \"Secretary\"]\nmanager_id_list = [90001, 90002, 90003, 90004, 90005, 90006]\n\n\ndepartments = [\n {'Department ID': 1, 'Department Name': \"Management\", 'Location': \"London\"},\n {'Department ID': 2, 'Department Name': \"Engineering\",\n 'Location': \"Cardiff\"},\n {'Department ID': 3, 'Department Name': \"Research & Development\",\n 'Location': \"Edinburgh\"},\n {'Department ID': 4, 'Department Name': \"Sales\", 'Location': \"Belfast\"}\n]\n\n\ndef get_department_by_id(departments, id):\n return [department for department in departments if department['Department ID'] == id]\n\n\ndef get_department_by_location(departments, location):\n return [department for department in departments if department['Location'] == location]\n\n\ndef get_employees_by_department(employees, department_id):\n return [employee for employee in employees if employee['Department ID'] == department_id]\n\n\ndef generate_department_report(employees, department_id):\n employees_by_department = get_employees_by_department(\n employees, department_id)\n\n newList = []\n for employee in employees_by_department:\n newList.append({'Employee ID': employee['Employee ID'],\n 'Employee Name': employee['Employee Name'], 'Job Title': employee['Job Title'], 'Salary': employee['Salary']})\n\n return newList\n\n\ndef generate_location_report(employees, location):\n department = get_department_by_location(departments, location)[0]\n employees_by_location = get_employees_by_department(\n employees, department['Department ID'])\n\n newList = []\n for employee in employees_by_location:\n newList.append({'Employee ID': employee['Employee ID'],\n 'Employee Name': employee['Employee Name'], 'Job Title': employee['Job Title'],\n 'Salary': employee['Salary'], 'Department Name': department['Department Name']})\n\n return newList\n\n\ndef generate_full_report(employees):\n departments_keyed_by_id = {1: get_department_by_id(departments, 1)[0],\n 2: get_department_by_id(departments, 2)[0],\n 3: get_department_by_id(departments, 3)[0],\n 4: get_department_by_id(departments, 4)[0]}\n\n newList = []\n for employee in employees:\n employee_department_id = employee['Department ID']\n\n department = {}\n if employee_department_id in departments_keyed_by_id.keys():\n department = departments_keyed_by_id[employee_department_id]\n else:\n department = {'Department ID': employee_department_id,\n 'Department Name': '',\n 'Location': ''\n }\n\n newList.append({'Employee ID': employee['Employee ID'],\n 'Employee Name': employee['Employee Name'],\n 'Job Title': employee['Job Title'],\n 'Manager ID': employee['Manager ID'],\n 'Salary': employee['Salary'],\n 'Department ID': department['Department ID'],\n 'Department Name': department['Department Name'],\n 'Location': department['Location']})\n\n return newList\n","sub_path":"utilities.py","file_name":"utilities.py","file_ext":"py","file_size_in_byte":3437,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"441010394","text":"#!/usr/bin/python3\n# -*- coding: utf-8 -*-\n# @Time : 2020/11/3 9:36\n# @Author : jun.chen\n# @Email : jun.chen_8480@foxmail.com\n# @File : TestClassB.py\n# @Software: PyCharm\nfrom core.dir1.TestClassA import ClassA\n\n\nclass ClassB:\n def get_root_path(self):\n classA = ClassA()\n return classA.get_root_path()\n\n def printMsg(self, msg):\n print(\"\\033[0;36m%s\\033[0m\" % msg)\n\n\nif \"__main__\" == __name__:\n classB = ClassB()\n classB.printMsg(\"ClassB_Print:\\t\\t\" + classB.get_root_path())\n","sub_path":"core/dir2/TestClassB.py","file_name":"TestClassB.py","file_ext":"py","file_size_in_byte":519,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"207508000","text":"\"\"\"4th migration\n\nRevision ID: d39dbd4edde0\nRevises: fd7147f7a026\nCreate Date: 2020-12-03 17:53:12.566140\n\n\"\"\"\nfrom alembic import op\nimport sqlalchemy as sa\n\n\n# revision identifiers, used by Alembic.\nrevision = 'd39dbd4edde0'\ndown_revision = 'fd7147f7a026'\nbranch_labels = None\ndepends_on = None\n\n\ndef upgrade():\n # ### commands auto generated by Alembic - please adjust! ###\n op.add_column('catagories', sa.Column('owner', sa.Integer(), nullable=False))\n op.create_foreign_key(None, 'catagories', 'users', ['owner'], ['id'])\n # ### end Alembic commands ###\n\n\ndef downgrade():\n # ### commands auto generated by Alembic - please adjust! ###\n op.drop_constraint(None, 'catagories', type_='foreignkey')\n op.drop_column('catagories', 'owner')\n # ### end Alembic commands ###\n","sub_path":"migrations/versions/20201203_175312_4th_migration.py","file_name":"20201203_175312_4th_migration.py","file_ext":"py","file_size_in_byte":796,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"24531723","text":"# -*- coding: utf-8 -*-\n\nfrom django.conf import settings\n\nfrom django.middleware.csrf import get_token\n\n\n__all__ = [\n\t'SoucheSessionMiddleware',\n\t'EnsureCsrfCookieMiddleware',\n]\n\n\n\nclass SoucheSessionMiddleware(object):\n ''' Process souche session includes car contrast.'''\n\n def process_request(self, request):\n if settings.CAR_CONTRAST_SESSION_NAME not in request.session:\n request.session[settings.CAR_CONTRAST_SESSION_NAME] = []\n\n\nclass EnsureCsrfCookieMiddleware(object):\n\t''' Ensure the csrf_token is in the cookie.'''\n\n\tdef process_view(self, request, callback, callback_args, callback_kwargs):\n\t\tget_token(request)\n\t\treturn None\n","sub_path":"souche/apps/core/middlewares.py","file_name":"middlewares.py","file_ext":"py","file_size_in_byte":662,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"455867208","text":"#!/usr/bin/env python\n# \n# tournament.py -- implementation of a Swiss-system tournament\n#\n\nimport psycopg2\n\n\ndef connect():\n \"\"\"Connect to the PostgreSQL database. Returns a database connection.\"\"\"\n return psycopg2.connect(\"dbname=tournament\")\n\n\ndef deleteMatches():\n \"\"\"Remove all the match records from the database.\"\"\"\n\n #connect to the database \n conn = connect() \n\n #conn.cursor() returns a cursor object, which can be used to execute queries\n c = conn.cursor()\n\n #execute perform the query specified as argument\n #DELETE FROM matches delete all records from matches\n c.execute(\"DELETE FROM matches\")\n\n #commit the changes\n conn.commit()\n \n #close the database connection\n conn.close()\n\n\ndef deletePlayers():\n \"\"\"Remove all the player records from the database.\"\"\"\n \n #connect to the database\n conn = connect() \n\n #conn.cursor() returns a cursor object, which can be used to execute queries\n c = conn.cursor()\n\n #execute perform the query specified as argument\n #DELETE FROM matches delete all records from players\n c.execute(\"DELETE FROM players\")\n\n conn.commit()\n\n conn.close()\n\n\ndef countPlayers():\n \"\"\"Returns the number of players currently registered.\"\"\"\n \n #connect to the database\n conn = connect() \n \n #conn.cursor() returns a cursor object, which can be used to execute queries\n c = conn.cursor()\n \n #execute perform the query specified as argument\n #SELECT COUNT(*) FROM players returns the number of players \n c.execute(\"SELECT COUNT(*) FROM players\")\n \n #fetchone fetches one row\n result = c.fetchone()\n \n #close the database connection\n conn.close()\n \n #access first element of the row\n return result[0]\n\ndef registerPlayer(name):\n \"\"\"Adds a player to the tournament database.\n \n The database assigns a unique serial id number for the player. (This\n should be handled by your SQL database schema, not in your Python code.)\n \n Args:\n name: the player's full name (need not be unique).\n \"\"\"\n #connect to the database\n conn = connect() \n\n #conn.cursor() returns a cursor object, which can be used to execute queries \n c = conn.cursor()\n\n #the following INSERT INTO query insert the name of the players\n #the id is added and incremented automatically by the database\n #%s string format specifier, similar to C-like languages\n #comma needed after name to block SQL injections\n c.execute(\"INSERT INTO players (name) VALUES (%s);\", (name,))\n\n #commit the changes\n conn.commit()\n\n #close the database connection\n conn.close() \n\n\ndef playerStandings():\n \"\"\"Returns a list of the players and their win records, sorted by wins.\n\n The first entry in the list should be the player in first place, or a player\n tied for first place if there is currently a tie.\n\n Returns:\n A list of tuples, each of which contains (id, name, wins, matches):\n id: the player's unique id (assigned by the database)\n name: the player's full name (as registered)\n wins: the number of matches the player has won\n matches: the number of matches the player has played\n \"\"\"\n #connect to the database \n conn = connect() \n\n #conn.cursor() returns a cursor object, which can be used to execute queries\n c = conn.cursor()\n\n #select all rows from standings\n c.execute(\"SELECT * FROM standings\")\n\n #result contains all the rows returned by the query\n result = c.fetchall()\n\n #return rows\n return result\n\n #close the database connection\n conn.close()\n\n\n\ndef reportMatch(winner, loser):\n \"\"\"Records the outcome of a single match between two players.\n\n Args:\n winner: the id number of the player who won\n loser: the id number of the player who lost\n \"\"\"\n #connect to the database\n conn = connect() \n\n #conn.cursor() returns a cursor object, which can be used to execute queries\n c = conn.cursor()\n\n #execute specified as argument\n c.execute(\"INSERT INTO matches (winner_id, loser_id) VALUES (%s, %s);\", (winner,loser,))\n \n #commit changes \n conn.commit()\n \n #close the connection\n conn.close() \n \ndef swissPairings():\n \"\"\"Returns a list of pairs of players for the next round of a match.\n \n Assuming that there are an even number of players registered, each player\n appears exactly once in the pairings. Each player is paired with another\n player with an equal or nearly-equal win record, that is, a player adjacent\n to him or her in the standings.\n \n Returns:\n A list of tuples, each of which contains (id1, name1, id2, name2)\n id1: the first player's unique id\n name1: the first player's name\n id2: the second player's unique id\n name2: the second player's name\n \"\"\"\n # standings (list) stored in standings\n standings = playerStandings()\n\n # number of players (int) stored in num_of_players\n num_of_players = countPlayers()\n\n # make a new list of only even indexes to iterate in standings\n even_indexes = [x for x in range(num_of_players) if x%2==0]\n\n #make an empty list to store the pairs\n list_of_pairs = []\n \n #for all even indexes of standings do...\n for x in even_indexes:\n # here we get the id and name of the player at index 0\n # and we pair it with the player at index 1\n # then we take player at index 2 with player at index 3, etc.\n id1 = standings[x][0]\n name1 = standings[x][1]\n id2 = standings[x + 1][0]\n name2 = standings[x + 1][1]\n pair = (id1, name1, id2, name2)\n # append the pair in the list_of_pairs\n list_of_pairs.append(pair)\n\n # return list of pairs\n return list_of_pairs\n\n","sub_path":"tournament.py","file_name":"tournament.py","file_ext":"py","file_size_in_byte":5834,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"459490848","text":"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Tue Jan 14 20:30:03 2020\r\n\r\n@author: Anthony Paech 2016\r\n\"\"\"\r\n\r\n# To support both python 2 and python 3\r\nfrom __future__ import division, print_function, unicode_literals\r\n\r\n# Common imports\r\nimport numpy as np\r\nimport pandas as pd\r\nimport os\r\n\r\n# to make this notebook's output stable across runs\r\ndef reset_graph(seed=42):\r\n tf.reset_default_graph()\r\n tf.set_random_seed(seed)\r\n np.random.seed(seed)\r\n\r\n# To plot pretty figures\r\n#%matplotlib inline\r\nimport matplotlib\r\nimport matplotlib.pyplot as plt\r\nplt.rcParams['axes.labelsize'] = 14\r\nplt.rcParams['xtick.labelsize'] = 12\r\nplt.rcParams['ytick.labelsize'] = 12\r\n\r\n# Where to save the figures\r\nPROJECT_ROOT_DIR = \".\"\r\nCHAPTER_ID = \"rnn\"\r\n\r\ntry:\r\n import tensorflow.compat.v1 as tf\r\nexcept Exception:\r\n pass\r\n \r\n # #tf.enable_eager_execution()\r\n # tf.compat.v1.enable_eager_execution(\r\n # config=None,\r\n # device_policy=None,\r\n # execution_mode=None\r\n # )\r\n \r\n # tf.enable_v2_behavior()\r\n \r\n \r\n \r\n #import tensorflow as tf\r\n \r\n #import tensorflow.compat.v1 as tf\r\ntf.disable_v2_behavior()\r\nprint(\"tensorflow:\",tf.__version__)\r\n \r\n\r\n \r\ndef next_batch(sales,product_row_no,batch_size,n_steps,n_inputs):\r\n return sales[product_row_no,:-1].reshape(-1,n_steps,n_inputs),sales[product_row_no,1:].reshape(-1,n_steps,n_inputs) \r\n \r\n\r\n \r\ndef load_data(filename): #,mask_text): #,batch_size,n_steps,n_inputs): \r\n df=pd.read_excel(filename,-1) # -1 means all rows\r\n\r\n\r\n # create a pivot table of code, product, day delta and predicted qty and export back to excel\r\n\r\n df[\"week\"]=df.date.dt.to_period('W')\r\n \r\n\r\n mask=((df[\"product\"]==\"SJ300\") | (df[\"product\"]==\"AJ300\"))\r\n\r\n # mask=(df[\"product\"]==\"SJ300\")\r\n table = pd.pivot_table(df[mask], values='qty', index=['product'],columns=['week'], aggfunc=np.sum, margins=False, fill_value=0) #, observed=True)\r\n print(\"\\ntable=\\n\",table.head(5))# # f.write(\"\\n\\n\"+table.to_string())\r\n print(\"table created.\")\r\n \r\n product_names=list(table.index) #\"t\" #list(table[table[\"product\"]])\r\n #print(\"product names=\",product_names)\r\n sales=table.to_numpy()\r\n \r\n # print(\"sales=\\n\",sales,sales.shape) \r\n return sales,product_names\r\n\r\n\r\n\r\ndef main(): \r\n print(\"\\n\\nSales prediction tool using a neural network - By Anthony Paech 16/2/20\\n\")\r\n \r\n # \r\n\r\n # n_rows=1\r\n batch_size=1 #4 #the number of mini batches at each time step\r\n \r\n # n_steps = 10 # number of time steps of a week each.\r\n # n_inputs = 1 # number of different product unit sales for that time period\r\n n_neurons = 105\r\n # batch_size= 5 #the number of mini batches at each time step\r\n # n_outputs=1\r\n learning_rate=0.001\r\n n_iterations=1000\r\n product_row_no=0\r\n n_predict_steps=80\r\n t_start=3\r\n t_finish=102\r\n \r\n sales,product_names=load_data(\"NAT-raw310120all.xlsx\") #,batch_size,n_steps,n_inputs)\r\n print(\"All sales=\\n\",sales,sales.shape) \r\n print(\"\\nProduct names\",product_names)\r\n # sales=sales[:,-(total_size+1):]\r\n # n_start_inputs=sales.shape[1]\r\n # total_size=n_inputs*n_steps\r\n n_steps=sales.shape[1]-1\r\n n_rows=sales.shape[0]\r\n \r\n n_inputs=2 #105\r\n n_outputs=1\r\n\r\n print(\"\\nTotal number of time steps=\",n_steps,\",Total number of products\",n_rows)\r\n \r\n x_axis=np.arange(0,n_steps+1)\r\n\r\n \r\n plt.figure(figsize=(11,4))\r\n plt.subplot(121)\r\n plt.title(\"A unit sales series\", fontsize=14)\r\n plt.plot(x_axis, sales[product_row_no,x_axis], label=r\"$unit sales$\")\r\n # plt.plot(x_axis[:-1], sales[product_row_no,x_axis[:-1]], \"b-\", linewidth=3, label=\"A training instance\")\r\n plt.legend(loc=\"best\", fontsize=14)\r\n # plt.axis([0, 30, -17, 13])\r\n plt.xlabel(\"Week\")\r\n plt.ylabel(\"UnitSales\")\r\n\r\n plt.subplot(122)\r\n plt.title(\"A training instance\", fontsize=14)\r\n plt.plot(x_axis[:-1], sales[product_row_no,:-1], \"bo\", markersize=10, label=\"instance\")\r\n plt.plot(x_axis[1:], sales[product_row_no,1:], \"w*\", markersize=10, label=\"target\")\r\n plt.legend(loc=\"best\")\r\n plt.xlabel(\"Week\")\r\n\r\n\r\n #save_fig(\"time_series_plot\")\r\n plt.show()\r\n\r\n \r\n \r\n \r\n reset_graph()\r\n \r\n \r\n # batch_size should be n_steps\r\n X = tf.placeholder(tf.float32, [None, n_steps, n_inputs])\r\n y = tf.placeholder(tf.float32, [None, n_steps, n_outputs])\r\n\r\n # one layer\r\n ##cell = tf.nn.rnn_cell.BasicRNNCell(num_units=n_neurons, activation=tf.nn.relu)\r\n cell = tf.nn.rnn_cell.BasicRNNCell(num_units=n_neurons, activation=tf.nn.relu)\r\n ##cell = tf.nn.rnn_cell.GRUCell(num_units=n_neurons)\r\n \r\n # cell = tf.contrib.rnn.OutputProjectionWrapper(\r\n # tf.nn.rnn_cell.BasicRNNCell(num_units=n_neurons, activation=tf.nn.relu),\r\n # output_size=n_outputs)\r\n\r\n# outputs, states = tf.nn.dynamic_rnn(cell, X, dtype=tf.float32)\r\n \r\n \r\n \r\n \r\n rnn_outputs, states = tf.nn.dynamic_rnn(cell, X, dtype=tf.float32)\r\n\r\n stacked_rnn_outputs = tf.reshape(rnn_outputs, [-1, n_neurons])\r\n stacked_outputs = tf.layers.dense(stacked_rnn_outputs, n_outputs)\r\n # outputs = tf.reshape(stacked_outputs, [-1, n_steps, n_outputs])\r\n outputs = tf.reshape(stacked_outputs, [-1,n_steps, n_outputs])\r\n # full_outputs = tf.reshape(stacked_outputs, [-1,n_steps, n_outputs])\r\n\r\n \r\n #multi layers\r\n #layers=[tf.nn.rnn_cell.BasicRNNCell(num_units=n_neurons, activation=tf.nn.relu) for layer in range(n_layers)]\r\n #layers=[tf.nn.rnn_cell.GRUCell(num_units=n_neurons) for layer in range(n_layers)]\r\n\r\n #multi_layer_cell = tf.nn.rnn_cell.MultiRNNCell(layers)\r\n\r\n #outputs, states = tf.nn.dynamic_rnn(multi_layer_cell, X, dtype=tf.float32)\r\n\r\n\r\n\r\n loss = tf.reduce_mean(tf.square(outputs - y))\r\n optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)\r\n #optimizer = tf.train.MomentumOptimizer(learning_rate=learning_rate, momentum=0.9, use_nesterov=True)\r\n training_op = optimizer.minimize(loss)\r\n\r\n init = tf.global_variables_initializer()\r\n saver = tf.train.Saver()\r\n\r\n\r\n step=0\r\n with tf.Session() as sess:\r\n init.run()\r\n step=0\r\n for iteration in range(n_iterations):\r\n X_batch, y_batch = next_batch(sales,product_row_no,batch_size,n_steps,n_inputs)\r\n # print(\"X_batch=\\n\",X_batch,\"\\ny_batch=\\n\",y_batch)\r\n # print(\"X_batch=\\n\",X_batch.shape,\"\\ny_batch=\\n\",y_batch.shape)\r\n sess.run(training_op, feed_dict={X: X_batch, y: y_batch})\r\n if iteration % 100 == 0:\r\n mse = loss.eval(feed_dict={X: X_batch, y: y_batch})\r\n print(iteration, \"\\tMSE:\", mse)\r\n # print(\"X_batch=\\n\",X_batch,\"\\ny_batch=\\n\",y_batch)\r\n\r\n\r\n X_new=sales[product_row_no,1:].reshape(-1,n_steps, n_inputs)\r\n \r\n# X_new=sales[product_row_no,1:].reshape(-1, n_steps, n_inputs)\r\n # X_new = monthno_instance.reshape(-1, n_steps, n_inputs)\r\n \r\n # print(\"X_new=\",X_new,X_new.shape)\r\n\r\n y_pred = sess.run(outputs, feed_dict={X: X_new})\r\n \r\n saver.save(sess, \"./my_time_series_model\")\r\n \r\n # print(\"y_pred[0,:,0]=\", y_pred[0,:,0])\r\n\r\n plt.title(\"Testing the model\", fontsize=14)\r\n \r\n# plt.plot(x_axis[:-1], sales[0,x_axis[:-1]], \"bo\", markersize=10, label=\"instance\")\r\n# plt.plot(x_axis[1:], sales[0,x_axis[1:]], \"w*\", markersize=10, label=\"target\")\r\n plt.plot(x_axis[2:], sales[product_row_no,2:], \"bo\", markersize=10, label=\"instance\")\r\n plt.plot(x_axis[3:], sales[product_row_no,-n_steps+2:], \"w*\", markersize=10, label=\"target\")\r\n\r\n # print(\"3 y_pred=\",y_pred) #[:,-n_steps:,:]\r\n \r\n plt.plot(x_axis[3:]+1, y_pred[product_row_no,2:,0], \"r.\", markersize=10, label=\"prediction\")\r\n\r\n\r\n plt.legend(loc=\"best\")\r\n plt.xlabel(\"Week\")\r\n\r\n plt.show()\r\n\r\n###############################################################\r\n \r\n# x_axis=np.arange(0,n_steps+n_predict_steps)\r\n \r\n # Creative prediction\r\n##############################\r\n with tf.Session() as sess: # not shown in the book\r\n saver.restore(sess, \"./my_time_series_model\") # not shown\r\n \r\n # last_sales_val=sales[n_steps-1].astype(float)\r\n # sequence = [last_sales_val] * n_steps\r\n\r\n #sequence = [10000.] * n_steps\r\n #sequence = sales[-n_steps:].tolist()\r\n sequence=sales[product_row_no,x_axis].reshape(n_outputs,-1)\r\n # print(\"start sequence=\",sequence,sequence.shape)\r\n\r\n #nexts=sequence[-1]+1\r\n #print(\"sq=\",sequence,\"nexts\",nexts,\"n_steps=\",n_steps)\r\n\r\n for iteration in range(0,n_predict_steps):\r\n X_batch=sequence[product_row_no,-n_steps:].reshape(-1, n_steps, n_inputs)\r\n # X_batch = np.array(sequence[0,-training_length:]).reshape(1,training_length,n_inputs)\r\n y_pred = sess.run(outputs, feed_dict={X: X_batch})\r\n # print(\"x_batch=\\n\",X_batch,\"y_pred=\\n\",y_pred)\r\n # print(\"i=\",iteration,\"y_pred=\",y_pred[0,-1,0])\r\n sequence=np.concatenate((sequence,y_pred[product_row_no, -1, 0].reshape(n_outputs,-1)),axis=1)\r\n # print(\"sequence.shape=\",sequence,sequence.shape)\r\n\r\n # monthno=np.append(monthno,monthno.shape[0]+1)\r\n # print(\"monthno=\",monthno)\r\n \r\n #sequence=sequence.ravel() \r\n# print(\"sequence=\\n\",sequence)\r\n #lensequence=len(sequence)\r\n # print(\"sequence.shape=\",sequence.shape)\r\n # print(\"y_pred=\\n\",y_pred[0,:,0]) \r\n\r\n\r\n######\r\n pred_axis=np.arange(n_steps+1,n_steps+n_predict_steps+1) \r\n plt.figure(figsize=(8,4))\r\n # plt.plot(x_axis[:n_steps+1], sequence[product_row_no,:n_steps+1], \"b-\", linewidth=1)\r\n plt.plot(x_axis, sales[product_row_no,:], linewidth=2,label=r\"$unit sales$\")\r\n plt.plot(pred_axis, sequence[product_row_no,-n_predict_steps:], \"r-\",linewidth=3,label=r\"$unit sales$\")\r\n\r\n # plt.plot(monthno_instance, y_pred[0,:,0], \"r.\", markersize=10, label=\"prediction\")\r\n\r\n # plt.plot(monthno[-lensequence:],sequence,\"b-\", linewidth=3)\r\n plt.xlabel(\"Week\")\r\n plt.ylabel(\"Qty\")\r\n plt.title(\"Unit sales: \"+str(product_names[product_row_no]),fontsize=14)\r\n plt.show()\r\n \r\n \r\n \r\n \r\n \r\n return\r\n\r\n \r\n\r\nif __name__ == '__main__':\r\n main()\r\n\r\n \r\n \r\n \r\n","sub_path":"AG_sales_pred_v3-10.py","file_name":"AG_sales_pred_v3-10.py","file_ext":"py","file_size_in_byte":10306,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"476218110","text":"\"\"\"\nCompile Tensorflow Models\n=========================\nThis article is an introductory tutorial to deploy tensorflow models with NNVM.\n\nFor us to begin with, tensorflow module is required to be installed.\n\nA quick solution is to install tensorlfow from\n\nhttps://www.tensorflow.org/install/install_sources\n\"\"\"\n\nimport nnvm\nimport tvm\nimport numpy as np\nimport os.path\n\n# Tensorflow imports\nimport tensorflow as tf\nfrom tensorflow.core.framework import graph_pb2\nfrom tensorflow.python.framework import dtypes\nfrom tensorflow.python.framework import tensor_util\n\nimport nnvm.testing.tf\n\nrepo_base = 'https://github.com/dmlc/web-data/raw/master/tensorflow/models/InceptionV1/'\nimg_name = 'elephant-299.jpg'\nimage_url = os.path.join(repo_base, img_name)\nmodel_name = 'classify_image_graph_def-with_shapes.pb'\nmodel_url = os.path.join(repo_base, model_name)\nmap_proto = 'imagenet_2012_challenge_label_map_proto.pbtxt'\nmap_proto_url = os.path.join(repo_base, map_proto)\nlable_map = 'imagenet_synset_to_human_label_map.txt'\nlable_map_url = os.path.join(repo_base, lable_map)\n\n\n######################################################################\n# Download processed tensorflow model\n# -----------------------------------\n# In this section, we download a pretrained Tensorflow model and classify an image.\nfrom mxnet.gluon.utils import download\n\ndownload(image_url, img_name)\ndownload(model_url, model_name)\ndownload(map_proto_url, map_proto)\ndownload(lable_map_url, lable_map)\n\n\n######################################################################\n# Creates graph from saved graph_def.pb.\n# --------------------------------------\n\nwith tf.gfile.FastGFile(os.path.join(\n \"./\", model_name), 'rb') as f:\n graph_def = tf.GraphDef()\n graph_def.ParseFromString(f.read())\n graph = tf.import_graph_def(graph_def, name='')\n # Call the utility to import the graph definition into default graph.\n graph_def = nnvm.testing.tf.ProcessGraphDefParam(graph_def)\n\n\n######################################################################\n# Decode image\n# ------------\nfrom PIL import Image\nimage = Image.open(img_name).resize((299, 299))\n\ndef transform_image(image):\n image = np.array(image)\n return image\n\nx = transform_image(image)\n\n######################################################################\n# Import the graph to NNVM\n# ------------------------\nsym, params = nnvm.frontend.from_tensorflow(graph_def)\n\n######################################################################\n# Now compile the graph through NNVM\nimport nnvm.compiler\ntarget = 'llvm'\nshape_dict = {'DecodeJpeg/contents': x.shape}\ndtype_dict = {'DecodeJpeg/contents': 'uint8'}\ngraph, lib, params = nnvm.compiler.build(sym, target, shape_dict, dtype=dtype_dict, params=params)\n\n######################################################################\n# Execute the portable graph on TVM\n# ---------------------------------\n# Now, we would like to reproduce the same forward computation using TVM.\nfrom tvm.contrib import graph_runtime\nctx = tvm.cpu(0)\ndtype = 'uint8'\nm = graph_runtime.create(graph, lib, ctx)\n# set inputs\nm.set_input('DecodeJpeg/contents', tvm.nd.array(x.astype(dtype)))\nm.set_input(**params)\n# execute\nm.run()\n# get outputs\ntvm_output = m.get_output(0, tvm.nd.empty(((1, 1008)), 'float32'))\n\n\n######################################################################\n# Process the output to human readable\n# ------------------------------------\npredictions = tvm_output.asnumpy()\npredictions = np.squeeze(predictions)\n\n# Creates node ID --> English string lookup.\nnode_lookup = nnvm.testing.tf.NodeLookup(label_lookup_path=os.path.join(\"./\", map_proto),\n uid_lookup_path=os.path.join(\"./\", lable_map))\n\ntop_k = predictions.argsort()[-5:][::-1]\nfor node_id in top_k:\n human_string = node_lookup.id_to_string(node_id)\n score = predictions[node_id]\n print('%s (score = %.5f)' % (human_string, score))\n\n######################################################################\n# Run the same graph with tensorflow and dump output.\n# ---------------------------------------------------\n\ndef create_graph():\n \"\"\"Creates a graph from saved GraphDef file and returns a saver.\"\"\"\n # Creates graph from saved graph_def.pb.\n with tf.gfile.FastGFile(model_name, 'rb') as f:\n graph_def = tf.GraphDef()\n graph_def.ParseFromString(f.read())\n graph = tf.import_graph_def(graph_def, name='')\n # Call the utility to import the graph definition into default graph.\n graph_def = nnvm.testing.tf.ProcessGraphDefParam(graph_def)\n\ndef run_inference_on_image(image):\n \"\"\"Runs inference on an image.\n\n Parameters\n ----------\n image: String\n Image file name.\n\n Returns\n -------\n Nothing\n \"\"\"\n if not tf.gfile.Exists(image):\n tf.logging.fatal('File does not exist %s', image)\n image_data = tf.gfile.FastGFile(image, 'rb').read()\n\n # Creates graph from saved GraphDef.\n create_graph()\n\n with tf.Session() as sess:\n softmax_tensor = sess.graph.get_tensor_by_name('softmax:0')\n predictions = sess.run(softmax_tensor,\n {'DecodeJpeg/contents:0': image_data})\n\n predictions = np.squeeze(predictions)\n\n # Creates node ID --> English string lookup.\n node_lookup = nnvm.testing.tf.NodeLookup(label_lookup_path=os.path.join(\"./\", map_proto),\n uid_lookup_path=os.path.join(\"./\", lable_map))\n\n top_k = predictions.argsort()[-5:][::-1]\n print (\"===== TENSORFLOW RESULTS =======\")\n for node_id in top_k:\n human_string = node_lookup.id_to_string(node_id)\n score = predictions[node_id]\n print('%s (score = %.5f)' % (human_string, score))\n\nrun_inference_on_image (img_name)\n","sub_path":"tutorials/nnvm/from_tensorflow.py","file_name":"from_tensorflow.py","file_ext":"py","file_size_in_byte":5841,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"400498853","text":"from django.shortcuts import render\nfrom user import models\nfrom django.http import JsonResponse, HttpResponse\n\n\ndef m_show(request):\n \"\"\"界面\"\"\"\n return render(request, \"maintenance/show.html\")\n\n\ndef statefailure(request):\n \"\"\"故障状态设备列表\"\"\"\n equipments = models.Equipment.objects.all().filter(eState=\"故障\")\n return render(request, \"maintenance/equipmentlist.html\", {\"equipments\": equipments})\n\n\ndef service(request):\n \"\"\"维修状态设备列表\"\"\"\n equipments = models.Equipment.objects.all().filter(eState=\"维修\")\n return render(request, \"maintenance/equipmentlist.html\", {\"equipments\": equipments})\n\n\ndef servicelist(request):\n \"\"\"维修状态设备列表\"\"\"\n services = models.Service.objects.all()\n return render(request, \"maintenance/servicelist.html\", {\"services\": services})\n\n\ndef breakequipmentlist(request):\n \"\"\"设备列表\"\"\"\n breakequipments = models.BreakEquipment.objects.all()\n return render(request, \"maintenance/breakequipmentlist.html\", {\"breakequipments\": breakequipments})\n\n\ndef edit(request):\n \"\"\"同意维修申请\"\"\"\n eid = request.GET[\"eid\"]\n breakequipment = models.BreakEquipment.objects.get(BreakEquipmentNum=int(eid))\n return render(request, \"maintenance/agree.html\", {\"breakequipment\": breakequipment})\n\n\ndef save(request):\n \"\"\"保存设备信息\"\"\"\n eid = request.GET[\"eid\"]\n be = models.BreakEquipment.objects.get(BreakEquipmentNum=eid)\n e = models.Equipment.objects.get(eNum=be.eNum.eNum)\n e.eState = \"维修\"\n ServiceNum = request.POST[\"ServiceNum\"]\n ServiceTxt = request.POST[\"ServiceTxt\"]\n Change = request.POST[\"Change\"]\n ServiceCost = request.POST[\"ServiceCost\"]\n ServiceName = request.POST[\"ServiceName\"]\n try:\n models.Service.objects.create(eNum=e, BreakEquipmentNum=be, ServiceNum=ServiceNum, ServiceTxt=ServiceTxt,\n Change=Change, ServiceCost=ServiceCost, ServiceName=ServiceName)\n e.save()\n except Exception:\n return JsonResponse({\"code\": 1})\n else:\n return JsonResponse({\"code\": 2})\n\n\ndef success(request):\n \"\"\"维修成功\"\"\"\n eid = request.GET[\"eid\"]\n se = models.Service.objects.get(ServiceNum=eid)\n be = models.BreakEquipment.objects.get(BreakEquipmentNum=se.BreakEquipmentNum.BreakEquipmentNum)\n e = models.Equipment.objects.get(eNum=se.eNum.eNum)\n e.eState = \"可借\"\n try:\n e.save()\n be.delete()\n se.delete()\n except Exception:\n return HttpResponse(\"确认失败！\")\n else:\n return HttpResponse(\"确认成功！\")\n\n\ndef fail(request):\n \"\"\"维修失败\"\"\"\n eid = request.GET[\"eid\"]\n se = models.Service.objects.get(ServiceNum=eid)\n be = models.BreakEquipment.objects.get(BreakEquipmentNum=se.BreakEquipmentNum.BreakEquipmentNum)\n e = models.Equipment.objects.get(eNum=se.eNum.eNum)\n e.eState = \"报销\"\n try:\n e.save()\n be.delete()\n se.delete()\n except Exception:\n return HttpResponse(\"确认失败！\")\n else:\n return HttpResponse(\"确认成功！\")\n\n\ndef search(request):\n \"\"\"设备搜索\"\"\"\n sear = request.GET[\"sear\"]\n try:\n int(sear)\n except Exception:\n equipments = models.Equipment.objects.all().filter(eName=sear)\n content = {'equipments': equipments}\n return render(request, \"teacher/search.html\", content)\n else:\n equipments = models.Equipment.objects.all().filter(eNum=sear)\n content = {'equipments': equipments}\n return render(request, \"teacher/search.html\", content)","sub_path":"maintenance/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":3605,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"237688513","text":"# -*- coding: utf-8 -*-\n\"\"\"\nbitfinex 比特币和莱特币价格爬取价格爬取\n\"\"\"\nimport time\nfrom selenium import webdriver\nfrom bs4 import BeautifulSoup\n\n\ndef dictionary_generator(dic_data):\n '格式化比特币或莱特币的价格信息。'\n name = dic_data.find(class_='col-info').get_text()\n data = dic_data.findAll(class_='col-currency')\n return {'货币对': name,\n '上次交易': data[0].get_text().strip(),\n '24小时前': data[1].get_text().strip(),\n '24小时变化': data[2].get_text().split(),\n '7天前': data[3].get_text().strip(),\n '7天变化': data[4].get_text().split(),\n '30天前': data[5].get_text().strip(),\n '30天变化': data[6].get_text().split()}\n\n\ndef get_stats():\n print('正在获取bitfinex价格数据......')\n\n # 驱动初始化\n driver = webdriver.PhantomJS(executable_path='C:/Users/Omou/Desktop/giot/bitcoin_scrapy/phantomjs.exe',\n service_log_path='C:/Users/Omou/Desktop/giot/bitcoin_scrapy/phantomjs.log')\n driver.get(\"https://www.bitfinex.com/stats\")\n time.sleep(5)\n STR_READY_STATE = ''\n # 等待页面加载完成\n while STR_READY_STATE != 'complete':\n time.sleep(5)\n STR_READY_STATE = driver.execute_script('return document.readyState')\n html = BeautifulSoup(driver.page_source, 'lxml')\n # 表格数据获取\n data = html.find(class_='pub-wrapper').tbody\n data = data.findAll(name='tr')\n # 数据格式化\n bitcoin = dictionary_generator(data[0])\n litecoin = dictionary_generator(data[1])\n driver.quit()\n print('bitfinex价格数据获取完毕。' + '\\n')\n for k, v in bitcoin.items():\n print(k + ': ' + str(v) + ';')\n for k, v in litecoin.items():\n print(k + ': ' + str(v) + ';')\n return {'bitcoin': bitcoin, 'litecoin': litecoin}\n\n\nif __name__ == '__main__':\n get_stats()\n","sub_path":"bitcoin_scrapy/bitfinex.py","file_name":"bitfinex.py","file_ext":"py","file_size_in_byte":1937,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"594787466","text":"# 引入openpyxl需要安装openpyxl 有安装文件\n# r'C:\\Users\\xlg\\Desktop\\abc.xlsx'\n\n\n# openpyxl 不能处理xls文件，可以处理xlsx文件\n\nfrom openpyxl.reader.excel import load_workbook\n\ndef readExcelFile(path):\n # 打开文件\n file = load_workbook(filename=path)\n # 获取文件中所有表格的名称\n # print(file.get_sheet_names())\n sheets = file.get_sheet_names()\n # sheets[0] === 'Sheet1' # 第一个表的名字\n # 获取一个表格\n sheet = file.get_sheet_by_name(sheets[0])\n\n # 获取当前表的最大行数\n # print(sheet.max_row)\n # 获取当前表的最大列数\n # print(sheet.max_column)\n # 获取表名\n # print(sheet.title)\n\n # excel 下标从1开始\n # 获取表格中数据\n for lineNum in range(1, sheet.max_row + 1):\n # print(lineNum)\n listLine = []\n for columnNum in range(1, sheet.max_column + 1):\n # 取出数据\n value = sheet.cell(row = lineNum, column = columnNum).value\n # print(value)\n listLine.append(value)\n print(listLine)\n\n# 将一个文件中所有的表中的内容全部取出出来\n# 把每个表对的什么数据要有明确展示\n\npath = r'C:\\Users\\xlg\\Desktop\\abc.xlsx'\nreadExcelFile(path)\n\n\n\n\n\n\n","sub_path":"python/FileReadAndWrite/6-读取xlsx文件中的一个表格.py","file_name":"6-读取xlsx文件中的一个表格.py","file_ext":"py","file_size_in_byte":1281,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"525403904","text":"import falcon\n\nfrom hyuga.api.common import base\nfrom hyuga.api.v1 import records, users\nfrom hyuga.core.errors import AppError\nfrom hyuga.core.log import logger\nfrom hyuga.middleware import GlobalFilter, HandleCORS, PeeweeConnection\n\n\nclass App(falcon.API):\n def __init__(self, *args, **kwargs):\n super(App, self).__init__(*args, **kwargs)\n logger.info('API Server is starting')\n # index\n self.add_route('/', base.BaseResource())\n # users\n self.add_route('/v1/users', users.Users())\n self.add_route('/v1/users/{user_id:int}', users.UsersItem())\n # users self\n self.add_route('/v1/users/self', users.UsersSelf())\n self.add_route('/v1/users/self/login', users.UsersSelfOperation())\n # records\n self.add_route('/v1/records', records.Records())\n self.add_route('/v1/users/self/records', records.UsersSelfRecords())\n\n self.add_error_handler(AppError, AppError.handle)\n\n\ndef create_app(testing=False):\n middlewares = [HandleCORS(), PeeweeConnection()]\n if testing is False:\n middlewares.append(GlobalFilter())\n return App(middleware=middlewares)\n","sub_path":"hyuga/app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":1158,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"64136259","text":"from git import GitCommandError, Repo, Actor\nfrom conda_build.metadata import MetaData\nimport github\nimport os\nimport subprocess\nfrom .utils import tmp_directory\nfrom .linting import compute_lint_message, comment_on_pr, set_pr_status\nfrom .update_teams import update_team\nfrom .circle_ci import update_circle\nfrom conda_smithy import __version__ as conda_smithy_version\nimport textwrap\n\nADD_NOARCH_MSG = \"please add noarch: python\"\nRERENDER_MSG = \"please rerender\"\nLINT_MSG = \"please lint\"\nUPDATE_TEAM_MSG = \"please update team\"\nUPDATE_CIRCLECI_KEY_MSG = \"please update circle\"\n\ndef check_for_bot(comment):\n return \"@conda-forge-admin\" in comment or \"@conda-forge-linter\" in comment\n\n\ndef pr_comment(org_name, repo_name, issue_num, comment):\n if not check_for_bot(comment):\n return\n gh = github.Github(os.environ['GH_TOKEN'])\n repo = gh.get_repo(\"{}/{}\".format(org_name, repo_name))\n pr = repo.get_pull(int(issue_num))\n pr_detailed_comment(org_name, repo_name, pr.head.user.login, pr.head.repo.name, pr.head.ref, issue_num, comment)\n\n\ndef pr_detailed_comment(org_name, repo_name, pr_owner, pr_repo, pr_branch, pr_num, comment):\n is_staged_recipes = (repo_name == \"staged-recipes\")\n if not (repo_name.endswith(\"-feedstock\") or is_staged_recipes):\n return\n\n if not check_for_bot(comment):\n return\n\n pr_commands = [LINT_MSG]\n if not is_staged_recipes:\n pr_commands += [ADD_NOARCH_MSG, RERENDER_MSG]\n\n if not any(command in comment.lower() for command in pr_commands):\n return\n\n with tmp_directory() as tmp_dir:\n feedstock_dir = os.path.join(tmp_dir, repo_name)\n repo_url = \"https://{}@github.com/{}/{}.git\".format(os.environ['GH_TOKEN'],\n pr_owner, pr_repo)\n repo = Repo.clone_from(repo_url, feedstock_dir, branch=pr_branch)\n\n if ADD_NOARCH_MSG in comment.lower():\n make_noarch(repo)\n rerender(repo, pr_num)\n if RERENDER_MSG in comment.lower():\n rerender(repo, pr_num)\n if LINT_MSG in comment.lower():\n relint(org_name, repo_name, pr_num)\n\n repo.remotes.origin.push()\n\n\ndef issue_comment(org_name, repo_name, issue_num, title, comment):\n if not repo_name.endswith(\"-feedstock\"):\n return\n\n comment = comment.lower()\n title = title.lower()\n\n if not check_for_bot(comment + title):\n return\n\n issue_commands = [UPDATE_TEAM_MSG, ADD_NOARCH_MSG, UPDATE_CIRCLECI_KEY_MSG]\n\n if not any(command in (comment+title) for command in issue_commands):\n return\n\n gh = github.Github(os.environ['GH_TOKEN'])\n repo = gh.get_repo(\"{}/{}\".format(org_name, repo_name))\n issue = repo.get_issue(int(issue_num))\n\n if UPDATE_TEAM_MSG in comment + title:\n update_team(org_name, repo_name)\n if UPDATE_TEAM_MSG in title:\n issue.edit(state=\"closed\")\n message = textwrap.dedent(\"\"\"\n Hi! This is the friendly automated conda-forge-webservice.\n\n I just wanted to let you know that I updated the team with maintainers from master.\n \"\"\")\n issue.create_comment(message)\n\n if UPDATE_CIRCLECI_KEY_MSG in comment + title:\n update_circle(org_name, repo_name)\n if UPDATE_CIRCLECI_KEY_MSG in title:\n issue.edit(state=\"closed\")\n message = textwrap.dedent(\"\"\"\n Hi! This is the friendly automated conda-forge-webservice.\n\n I just wanted to let you know that I updated the circle-ci deploy key and followed the project.\n \"\"\")\n issue.create_comment(message)\n\n forked_user = gh.get_user().login\n forked_repo = gh.get_user().create_fork(repo)\n\n with tmp_directory() as tmp_dir:\n feedstock_dir = os.path.join(tmp_dir, repo_name)\n repo_url = \"https://{}@github.com/{}/{}.git\".format(os.environ['GH_TOKEN'],\n forked_user, repo_name)\n git_repo = Repo.clone_from(repo_url, feedstock_dir)\n forked_repo_branch = 'conda_forge_admin_{}'.format(issue_num)\n new_branch = git_repo.create_head(forked_repo_branch)\n new_branch.checkout()\n\n if ADD_NOARCH_MSG in comment + title:\n make_noarch(git_repo)\n rerender(git_repo, issue_num)\n git_repo.git.push(\"origin\", forked_repo_branch)\n msg = \"MNT: Add noarch: python\"\n pr = repo.create_pull(msg, \"As instructed in #{}\".format(issue_num),\n \"master\", \"{}:{}\".format(forked_user, forked_repo_branch))\n\n if ADD_NOARCH_MSG in title:\n issue.edit(state=\"closed\")\n\n message = textwrap.dedent(\"\"\"\n Hi! This is the friendly automated conda-forge-webservice.\n\n I just wanted to let you know that I made the recipe noarch: python in {}/{}#{}.\n \"\"\".format(org_name, repo_name, pr.number))\n issue.create_comment(message)\n\n\ndef rerender(repo, pr_num):\n subprocess.call([\"conda\", \"smithy\", \"rerender\"], cwd=repo.working_dir)\n if repo.is_dirty():\n author = Actor(\"conda-forge-admin\", \"pelson.pub+conda-forge@gmail.com\")\n repo.index.commit(\"MNT: Re-rendered with conda-smithy {}\".format(conda_smithy_version), author=author, committer=author)\n else:\n message = textwrap.dedent(\"\"\"\n Hi! This is the friendly automated conda-forge-webservice.\n\n I rerendered the feedstock and it seems to be already up-to-date.\n \"\"\")\n repo.get_issue(pr_num).create_comment(message)\n\n\ndef make_noarch(repo):\n meta_yaml = os.path.join(repo.working_dir, \"recipe\", \"meta.yaml\")\n with open(meta_yaml, 'r') as fh:\n lines = [line for line in fh]\n with open(meta_yaml, 'w') as fh:\n build_line = False\n for line in lines:\n if build_line:\n spaces = len(line) - len(line.lstrip())\n line = \"{}noarch: python\\n{}\".format(\" \"*spaces, line)\n build_line = False\n if line.rstrip() == 'build:':\n build_line = True\n fh.write(line)\n repo.index.add([meta_yaml])\n author = Actor(\"conda-forge-admin\", \"pelson.pub+conda-forge@gmail.com\")\n repo.index.commit(\"Add noarch:python option\", author=author)\n\n\ndef relint(owner, repo_name, pr_num):\n pr = int(pr_num)\n lint_info = compute_lint_message(owner, repo_name, pr, False)\n if not lint_info:\n print('Linting was skipped.')\n else:\n msg = comment_on_pr(owner, repo_name, pr, lint_info['message'])\n set_pr_status(owner, repo_name, lint_info, target_url=msg.html_url)\n\n","sub_path":"conda_forge_webservices/commands.py","file_name":"commands.py","file_ext":"py","file_size_in_byte":6623,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"21992527","text":"from django.contrib import admin\nfrom django import forms\nfrom searchableselect.widgets import SearchableSelect\nfrom .models import Event, Team, Value\n\n# User = user_model()\n\n\nclass EventAdmin(admin.ModelAdmin):\n list_display = ['title', 'start_date', 'end_date']\n list_filter = ['title', 'start_date', 'end_date']\n\n\nadmin.site.register(Event, EventAdmin)\n\n\n# class TeamForm(forms.ModelForm):\n# class Meta:\n# model = Team\n# exclude = ()\n# widgets = {\n# 'members': SearchableSelect(model='users.User',\n# search_field='username',\n# many=True,\n# limit=20\n# )\n# }\n\nclass TeamAdmin(admin.ModelAdmin):\n # form = TeamForm\n list_display = ['title', 'leader', 'all_members', 'description']\n list_filter = ['title', 'description']\n\n\nadmin.site.register(Team, TeamAdmin)\n\n\nclass ValueAdmin(admin.ModelAdmin):\n list_display = ['event', 'team', 'user', 'category', 'votes']\n list_filter = ['event', 'team', 'user', 'category', 'votes']\n ordering = ['event']\n\n\nadmin.site.register(Value, ValueAdmin)\n","sub_path":"voting/votingmachine/admin.py","file_name":"admin.py","file_ext":"py","file_size_in_byte":1218,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"492682813","text":"import tkinter as tk\n\n\ndef cria_tela():\n\tmyWindow = tk.Tk()\n\tmyWindow.title(\"VOLT\")\n\tmyWindow.configure(bg=\"#1E90FF\")\n\tmyWindow.geometry(\"800x600\")\n\n\treturn myWindow\n\ndef main():\n\ttela = cria_tela()\n\ttela.mainloop()\n\nmain()\n# class SimpleApp(object):\n# def __init__(self, master, **kwargs):\n# title=kwargs.pop('title')\n# frame=tk.Frame(master, **kwargs)\n# frame.pack()\n# self.label = tk.Label(frame, text=title)\n# self.label.pack(padx=500,pady=500)\n\n\n# if __name__=='__main__':\n# root = tk.Tk()\n# app = SimpleApp(root,title='Hello, world')\n# root.mainloop()","sub_path":"GUI/examples.py","file_name":"examples.py","file_ext":"py","file_size_in_byte":613,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"264429928","text":"# class Animal:\n# def __init__(self, name):\n# self.name = name\n \n# def walk(self):\n# print(f'{self.name}! 걷는다!')\n\n# def eat(self):\n# print(f'{self.name}! 먹는다!')\n\n\n# class Dog(Animal):\n# def __init__(self, name):\n# super().__init__(name)\n\n# def bark(self):\n# print(f'{self.name}! 짖는다')\n\n# class Bird(Animal):\n# def __init__(self, name):\n# super().__init__(name)\n\n# def fly(self):\n# print(f'{self.name}! 푸드덕')\n\n\n# dog = Dog('멍멍이')\n# dog.walk()\n# dog.bark()\n\n# bird = Bird('구구')\n# bird.walk()\n# bird.eat()\n# bird.fly()\n\n\n\nclass Point:\n def __init__(self, x, y):\n self.x = x\n self.y = y\n \n\nclass Rectangle:\n def __init__(self, p1, p2):\n self.p1 = p1\n self.p2 = p2\n \n def get_area(self):\n return self.p1 * self.p2\n \n def get_perimeter(self):\n return (self.p1 + self.p2) * 2\n\n def is_square(self):\n if self.p1 == self.p2:\n return True\n else:\n return False\n\np1 = Point(1,3)\np2 = Point(3,1)\nr1 = Rectangle(p1,p2)\nprint(r1.get_area())\nprint(r1.get_perimeter())\nprint(r1.is_square())\np3 = Point(3,7)\np4 = Point(6,4)\nr2 = Rectangle(p3,p4)\nprint(r2.get_area())\nprint(r2.get_perimeter())\nprint(r2.is_square())\n\n\n\n","sub_path":"trainning/0729hws.py","file_name":"0729hws.py","file_ext":"py","file_size_in_byte":1323,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"317978967","text":"from django.urls import path\n\nfrom apps.clients.views import ClientListView, ClientDetailView, \\\n ClientDeleteView, ClientCreateView, ClientVotingView\n\napp_name = 'clients'\n\nurlpatterns = [\n path('', ClientListView.as_view(), name='list'),\n path('/', ClientDetailView.as_view(), name='detail'),\n path('create/', ClientCreateView.as_view(), name='create'),\n path('/delete/', ClientDeleteView.as_view(), name='delete'),\n path('voting/', ClientVotingView.as_view(), name='voting')\n]\n","sub_path":"src/apps/clients/urls/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":514,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"573745860","text":"#!/usr/bin/env python3\n\n'''\n A Simple mjpg stream http server for the Raspberry Pi Camera\n inspired by https://gist.github.com/n3wtron/4624820\n'''\nfrom http.server import BaseHTTPRequestHandler,HTTPServer\nimport io\nimport time\nimport picam\nimport algo\nimport os\nimport sys\nimport cv2\nimport logging\nimport argparse\nimport comm\nimport traceback\nimport config\n\ns_args=None\ns_config=None\ns_comm=None\ns_first=True\ns_jpgQuality = 80 # used by direct streaming, quality differs from opencv\ns_jpgParam = [int(cv2.IMWRITE_JPEG_QUALITY), 50] # used by opencv\ns_mainPage=\"\"\"\n\n\n\n\n![](\"/cam.mjpg\"/)
\n\"\"\"\n\nclass CamHandler(BaseHTTPRequestHandler):\n def do_GET(self):\n # we respond with a stream if the url ends in either .mjpg or .mjpeg\n # we select between direct or algorithm-filtered streams based\n # on the filename. If the algostr (below) is \"direct.mjpeg\", we\n # get fast/raw/direct streaming. Otherwise the algostr is passed\n # to the algo entrypoint.\n if self.path.endswith('.mjpg') or self.path.endswith('.mjpeg'):\n algostr = os.path.basename(self.path).split(\".\")[0]\n self.send_response(200)\n self.send_header('Content-type',\n 'multipart/x-mixed-replace; boundary=--jpgboundary')\n self.end_headers()\n cam = None\n try:\n time.sleep(1) # wait for shutdown of alt stream\n cam = picam.PiCam(s_config[\"picam\"])\n if not cam:\n raise Exception(\"Hey no camera!\")\n if algostr == \"direct\":\n self.streamDirect(cam)\n else:\n self.streamAlgo(cam, algostr)\n\n except BrokenPipeError:\n logging.warning(\"broken pipe error\")\n\n except KeyboardInterrupt:\n logging.info(\"keyboard interrupt\")\n\n except Exception as e:\n # Critical for anything that happens in algo or below\n exc_info = sys.exc_info()\n logging.error(\"algo exception: \" + str(e))\n traceback.print_exception(*exc_info)\n\n finally:\n logging.info(\"done streaming ----------------------\")\n if cam:\n cam.stop() # triggers PiCamera.close()\n else:\n logging.info(\"(cam init problem)\")\n else:\n self.send_response(200)\n self.send_header('Content-type','text/html')\n self.end_headers()\n self.wfile.write(bytes(s_mainPage,'utf-8'))\n return\n\n def streamDirect(self, cam):\n logging.info(\"direct streaming\")\n stream = io.BytesIO()\n try:\n for i in cam.cam.capture_continuous(stream, \"jpeg\",\n quality=s_jpgQuality,\n use_video_port=True):\n self.wfile.write(bytes(\"--jpgboundary\\n\",'utf-8'))\n self.send_header('Content-type','image/jpeg')\n self.send_header('Content-length',len(stream.getvalue()))\n self.end_headers()\n val = stream.getvalue()\n self.wfile.write(val)\n stream.seek(0)\n stream.truncate()\n\n finally:\n stream.seek(0)\n stream.truncate()\n # cam.stop() called above\n\n def streamAlgo(self, cam, algoselector):\n global s_first\n (algoselector + \" algo streaming\")\n cam.start()\n while True:\n camframe = cam.next()\n target,frame = algo.processFrame(camframe, algoselector,\n cfg=s_config[\"algo\"],\n display=True, debug=False)\n if target != None:\n logging.debug(str(target))\n else:\n logging.info(\"no target\");\n\n if s_comm != None:\n if target != None:\n s_comm.UpdateVisionState(\"Acquired\")\n target.send()\n else:\n s_comm.UpdateVisionState(\"Searching\")\n\n rc,jpg = cv2.imencode('.jpg', frame, s_jpgParam)\n if not rc:\n continue\n if s_first:\n logging.debug(\"jpg file size: %s\" % jpg.size)\n s_first = False\n self.wfile.write(bytes(\"--jpgboundary\\n\",\"utf-8\"))\n self.send_header('Content-type','image/jpeg')\n self.send_header('Content-length', jpg.size)\n self.end_headers()\n self.wfile.write(jpg.tostring())\n time.sleep(0.05)\n\ndef main():\n global s_args\n global s_comm\n global s_config\n try:\n parser = argparse.ArgumentParser(description=\"Start the picam streamer\")\n parser.add_argument(\"--robot\", dest=\"robot\",\n help=\"robot (none, localhost, roborio) [none]\",\n default=\"none\")\n parser.add_argument(\"--debug\", dest=\"debug\",\n help=\"debug: [0,1] \",\n default=0)\n parser.add_argument(\"--config\", dest=\"config\",\n help=\"config: default,greenled,noled...\",\n default=\"default\")\n s_args = parser.parse_args()\n s_config = getattr(config, s_args.config)\n if s_args.robot != \"none\":\n if s_args.robot == \"roborio\":\n ip = \"10.49.15.2\"\n else:\n ip = s_args.robot\n s_comm = comm.Comm(ip)\n logFmt = \"streamer %(levelname)-6s %(message)s\"\n dateFmt = \"%H:%M\"\n if s_args.debug:\n loglevel = logging.DEBUG\n else:\n loglevel = logging.INFO\n logging.basicConfig(level=loglevel, format=logFmt, datefmt=dateFmt)\n server = HTTPServer(('',5080),CamHandler)\n logging.info (\"server started with config \" + s_args.config)\n server.serve_forever()\n except KeyboardInterrupt:\n logging.warning(\"aborting server\")\n server.socket.close()\n\nif __name__ == '__main__':\n main()\n\n","sub_path":"2019/picamStreamer.py","file_name":"picamStreamer.py","file_ext":"py","file_size_in_byte":6203,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"438093235","text":"# uncompyle6 version 3.6.7\n# Python bytecode 2.7 (62211)\n# Decompiled from: Python 3.8.2 (tags/v3.8.2:7b3ab59, Feb 25 2020, 23:03:10) [MSC v.1916 64 bit (AMD64)]\n# Embedded file name: /home/jake/CRAPtion/craption/utils.py\n# Compiled at: 2018-05-18 03:22:54\nimport craption.settings, datetime, os, pkg_resources, pyperclip, random, re, subprocess, sys, tempfile, time\n\ndef set_clipboard(data):\n pyperclip.copy(data)\n\n\ndef screenshot():\n path = tempfile.mktemp('.png')\n if sys.platform.startswith('linux'):\n run(['scrot', '-s', path])\n else:\n run(['screencapture', '-ix', path])\n return path\n\n\ndef get_filename():\n conf = craption.settings.get_conf()\n filename = conf['file']['name']\n now = time.time()\n for match in re.finditer('{r(\\\\d+)}', filename):\n chars = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890'\n random_string = ('').join([ random.choice(chars) for _ in range(int(match.group(1))) ])\n filename = filename.replace(match.group(0), random_string)\n\n filename = filename.replace('{u}', str(int(now)))\n filename = filename.replace('{d}', datetime.datetime.fromtimestamp(now).strftime(conf['file']['datetime_format']))\n return filename + '.png'\n\n\ndef install():\n craption.settings.write_template()\n exit(0)\n\n\ndef run(args):\n devnull = open(os.devnull, 'wb')\n p = subprocess.Popen(args, stdout=devnull, stderr=devnull)\n p.wait()","sub_path":"pycfiles/crapy-0.0.2-py3-none-any/utils.py","file_name":"utils.py","file_ext":"py","file_size_in_byte":1436,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"498051418","text":"class Solution(object):\n def nextPermutation(self, nums):\n \"\"\"\n :type nums: List[int]\n :rtype: None Do not return anything, modify nums in-place instead.\n \"\"\"\n if nums == []:\n return\n\n # 先检查nums是否为最大字典序\n max_flag = True\n for i in range(len(nums)-1):\n if nums[i] < nums[i+1]:\n max_flag = False\n break\n if max_flag:\n for i in range(len(nums)//2):\n reverse_index = len(nums) - 1 - i\n nums[i], nums[reverse_index] = nums[reverse_index], nums[i]\n return\n\n # 找到一般情况下的下一个字典序\n # 1.从右至左找到第一个左邻比右邻小的数\n for i in range(len(nums)-1, 0, -1):\n if nums[i-1] < nums[i]:\n # 2.从右至左找到第一个比nums[i-1]大的数\n for j in range(len(nums)-1, i-1, -1):\n if nums[j] > nums[i-1]:\n # 3.交换nums[i-1]和nums[j]\n nums[j], nums[i-1] = nums[i-1], nums[j]\n # 4.对nums[i-1]后面的数，从小到大排序\n for k in range(i, len(nums)):\n for m in range(i, len(nums) - (k - i) -1):\n if nums[m] > nums[m+1]:\n nums[m], nums[m+1] = nums[m+1], nums[m]\n return\n\nif __name__ == '__main__':\n # nums = [4,1,5,2,3]\n nums = [1,3,2]\n Solution().nextPermutation(nums)\n print(nums)\n\n","sub_path":"leetcode/1-50/_31_next_permutation.py","file_name":"_31_next_permutation.py","file_ext":"py","file_size_in_byte":1612,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"335692624","text":"### L1_prescale_xml2csv.py\n# Author: Thiago R. F. P. Tomei\n# Date: 2018-06-22\n# Version: v2\n\n# This script takes two XMLs as input: the RunSettings key (i.e. the L1 prescales)\n# and the L1Menu. It outputs into stdout the same information as the XML but in CSV\n# format. We pad out unused bits with empty names and columns of zeros.\n# This can then be pasted back into the GoogleDocs for book-keeping.\n# Mostly useful for when the L1 menu changes.\n# The logic is: L1 Menu maps numbersToNames, RunSettings key maps namesToColumns\n# Changed to be compatible with python3\n# Now adding warnings in stderr for L1 bits missing either in the RunSettings key\n# or in the L1Menu XML itself.\n\nfrom __future__ import print_function\nimport xml.etree.ElementTree as ET\nimport sys\n\n\ndef eprint(*args, **kwargs):\n print(*args, file=sys.stderr, **kwargs)\n\n\nclass bcolors:\n HEADER = \"\\033[95m\"\n OKBLUE = \"\\033[94m\"\n OKGREEN = \"\\033[92m\"\n WARNING = \"\\033[93m\"\n FAIL = \"\\033[91m\"\n ENDC = \"\\033[0m\"\n BOLD = \"\\033[1m\"\n UNDERLINE = \"\\033[4m\"\n\n\nL1PrescalesName = \"BSRT_update.xml\"\nL1MenuName = \"L1Menu_Collisions2022_v1_3_0\"\n\nnumbersToNames = dict()\nnamesToColumns = dict()\n\n# L1 Prescales\nL1PrescalesTree = ET.parse(L1PrescalesName)\nL1Prescales = L1PrescalesTree.getroot()\ncolumnsrow = L1Prescales[0][1][0].text.split(\",\")\ncolumnNames = [x.split(\":\")[1] for x in columnsrow[1:]]\nnColumns = len(columnNames)\ndefaultColumn = int(L1Prescales[0][0].text)\n\n# Using XPath, find everything named \"row\" in the tree\nlistOfPrescales = L1Prescales.findall(\".//row\")\nfor row in listOfPrescales:\n row2 = row.text.split(\",\")\n # We strip whitespace at the beginning and end of the bitName\n bitName = row2[0].strip()\n prescaleRow = [int(ps) for ps in row2[1:]]\n namesToColumns[bitName] = prescaleRow\n\n# L1 Menu\nL1MenuTree = ET.parse(L1MenuName)\nL1Menu = L1MenuTree.getroot()\nlistOfAlgos = L1Menu.findall(\"algorithm\")\nfor algo in listOfAlgos:\n bitNumber = int(algo.find(\"index\").text)\n bitName = algo.find(\"name\").text\n numbersToNames[bitNumber] = bitName\n\n# We need to prepend the column names with a single quote to ensure that GoogleDocs\n# doesn't transform strings like \"2.0E34\" into numbers...\nmaxAlgo = max(numbersToNames.keys())\nprint(\"Default\" + \",\" + columnNames[defaultColumn])\nprint(\"Bit\" + \",\" + \"Algo name\" + \",\" + (\",\".join([\"'\" + cn for cn in columnNames])))\n\n# We print into stdout\nfor bit in range(0, maxAlgo + 1):\n if bit in numbersToNames.keys(): # This bit is defined in the L1 menu\n bitName = numbersToNames[bit]\n if bitName in namesToColumns: # We have prescales for this bit\n prescaleRow = namesToColumns[bitName]\n del namesToColumns[bitName]\n print(\n str(bit)\n + \",\"\n + bitName\n + \",\"\n + (\",\".join([str(ps) for ps in prescaleRow]))\n )\n else: # We don't have prescales for this bit. Put 0 for the time being\n eprint(\n bcolors.WARNING\n + bitName\n + bcolors.ENDC\n + \" is not defined in the original XML\"\n )\n print(str(bit) + \",\" + bitName + \",\" + (\",\".join([\"0\"] * nColumns)))\n else: # L1 doesn't define this bit. Put 0\n print(str(bit) + \",\" + \" \" + \",\" + (\",\".join([\"0\"] * nColumns)))\n\n# Let's see if there is some bit that we wanted to add, but couldn't\nif namesToColumns:\n for bitName in namesToColumns:\n eprint(\n bcolors.FAIL + bitName + bcolors.ENDC + \" was not found in the new L1 XML!\"\n )\n","sub_path":"hltpro/L1_prescale_xml2csv.py","file_name":"L1_prescale_xml2csv.py","file_ext":"py","file_size_in_byte":3606,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"638408692","text":"class Solution(object):\n def combine(self, n, k):\n \"\"\"\n :type n: int\n :type k: int\n :rtype: List[List[int]]\n \"\"\"\n self.res = []\n out = []\n self.helper(n, k, 1, out)\n return self.res\n\n def helper(self, n, k, start, out: list):\n if len(out) == k:\n self.res.append(out[:])\n return\n for i in range(start, n + 1): # try each possibility number in current position\n out.append(i)\n self.helper(n, k, i + 1, out)\n out.pop()\n\n def combine2(self, n, k):\n if k == 0:\n return [[]]\n return [x + [tail] for tail in range(n, k - 1, -1) for x in self.combine(tail - 1, k - 1)]\n\n def combine2(self, n, k):\n res = []\n\n\n\nn = 4\nk = 2\nsolution = Solution()\nreT = solution.combine(n, k)\nprint(reT)\n","sub_path":"Medium/Combinations.py","file_name":"Combinations.py","file_ext":"py","file_size_in_byte":856,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"555394636","text":"from __future__ import print_function\n\nimport argparse\nimport json\nimport logging\nimport os\nimport shutil\nimport subprocess\nimport sys\nimport textwrap\nfrom uuid import uuid4\nfrom bd2k.util.exceptions import require\n\nlogging.basicConfig(level=logging.INFO)\nlog = logging.getLogger()\n\n\ndef call_pipeline(mount, args):\n work_dir = os.path.join(mount, 'Toil-RNAseq-' + str(uuid4()))\n os.makedirs(work_dir)\n log.info('Temporary directory created: {}'.format(work_dir))\n config_path = os.path.join(work_dir, 'toil-rnaseq.config')\n job_store = os.path.join(args.resume, 'jobStore') if args.resume else os.path.join(work_dir, 'jobStore')\n with open(config_path, 'w') as f:\n f.write(generate_config(args.star, args.rsem, args.kallisto, mount,\n args.disable_cutadapt, args.save_bam, args.save_wiggle))\n command = ['toil-rnaseq', 'run',\n job_store,\n '--config', config_path,\n '--workDir', work_dir,\n '--retryCount', '1']\n if args.resume:\n command.append('--restart')\n if args.cores:\n command.append('--maxCores={}'.format(args.cores))\n command.append('--samples')\n command.extend('file://' + x for x in args.samples)\n try:\n subprocess.check_call(command)\n except subprocess.CalledProcessError as e:\n print(e.message, file=sys.stderr)\n finally:\n log.info('Pipeline terminated, changing ownership of output files from root to user.')\n stat = os.stat(mount)\n subprocess.check_call(['chown', '-R', '{}:{}'.format(stat.st_uid, stat.st_gid), mount])\n if not args.no_clean:\n log.info('Cleaning up temporary directory: {}'.format(work_dir))\n shutil.rmtree(work_dir)\n else:\n log.info('Flag \"--no-clean\" was used, therefore {} was not deleted.'.format(work_dir))\n\n\ndef generate_config(star_path, rsem_path, kallisto_path, output_dir, disable_cutadapt, save_bam, save_wiggle):\n cutadapt = True if not disable_cutadapt else False\n return textwrap.dedent(\"\"\"\n star-index: file://{star_path}\n kallisto-index: file://{kallisto_path}\n rsem-ref: file://{rsem_path}\n output-dir: {output_dir}\n cutadapt: {cutadapt}\n fastqc: true\n fwd-3pr-adapter: AGATCGGAAGAG\n rev-3pr-adapter: AGATCGGAAGAG\n ssec:\n gtkey:\n wiggle: {save_wiggle}\n save-bam: {save_bam}\n ci-test:\n \"\"\"[1:].format(**locals()))\n\n\ndef main():\n \"\"\"\n Computational Genomics Lab, Genomics Institute, UC Santa Cruz\n Dockerized Toil RNA-seq pipeline\n\n RNA-seq fastqs are combined, aligned, and quantified with 2 different methods (RSEM and Kallisto)\n\n General Usage:\n docker run -v $(pwd):$(pwd) -v /var/run/docker.sock:/var/run/docker.sock \\\n quay.io/ucsc_cgl/rnaseq-cgl-pipeline --samples sample1.tar\n\n Please see the complete documentation located at:\n https://github.com/BD2KGenomics/cgl-docker-lib/tree/master/rnaseq-cgl-pipeline\n or inside the container at: /opt/rnaseq-pipeline/README.md\n\n\n Structure of RNA-Seq Pipeline (per sample)\n\n 3 -- 4 -- 5\n / |\n 0 -- 1 -- 2 ---- 6 -- 8\n \\ |\n 7 ---------\n\n 0 = Download sample\n 1 = Unpack/Merge fastqs\n 2 = CutAdapt (adapter trimming)\n 3 = STAR Alignment\n 4 = RSEM Quantification\n 5 = RSEM Post-processing\n 6 = Kallisto\n 7 = FastQC\n 8 = Consoliate output and upload to S3\n =======================================\n Dependencies\n Docker\n \"\"\"\n # Define argument parser for\n parser = argparse.ArgumentParser(description=main.__doc__, formatter_class=argparse.RawTextHelpFormatter)\n parser.add_argument('--samples', nargs='+', required=True,\n help='Absolute path(s) to sample tarballs.')\n parser.add_argument('--star', type=str, required=True,\n help='Absolute path to STAR index tarball.')\n parser.add_argument('--rsem', type=str, required=True,\n help='Absolute path to rsem reference tarball.')\n parser.add_argument('--kallisto', type=str, required=True,\n help='Absolute path to kallisto index (.idx) file.')\n parser.add_argument('--disable-cutadapt', action='store_true', default=False,\n help='Cutadapt fails if samples are improperly paired. Use this flag to disable cutadapt.')\n parser.add_argument('--save-bam', action='store_true', default='false',\n help='If this flag is used, genome-aligned bam is written to output.')\n parser.add_argument('--save-wiggle', action='store_true', default='false',\n help='If this flag is used, wiggle files (.bg) are written to output.')\n parser.add_argument('--no-clean', action='store_true',\n help='If this flag is used, temporary work directory is not cleaned.')\n parser.add_argument('--resume', type=str, default=None,\n help='Pass the working directory that contains a job store to be resumed.')\n parser.add_argument('--cores', type=int, default=None,\n help='Will set a cap on number of cores to use, default is all available cores.')\n args = parser.parse_args()\n # If no arguments provided, print full help menu\n if len(sys.argv) == 1:\n parser.print_help()\n sys.exit(1)\n # Get name of most recent running container. If socket is mounted, should be this one.\n try:\n name = subprocess.check_output(['docker', 'ps', '--format', '{{.Names}}']).split('\\n')[0]\n except subprocess.CalledProcessError as e:\n raise RuntimeError('No container detected, ensure Docker is being run with: '\n '\"-v /var/run/docker.sock:/var/run/docker.sock\" as an argument. \\n\\n{}'.format(e.message))\n # Get name of mounted volume\n blob = json.loads(subprocess.check_output(['docker', 'inspect', name]))\n mounts = blob[0]['Mounts']\n # Ensure docker.sock is mounted correctly\n sock_mount = [x['Source'] == x['Destination'] for x in mounts if 'docker.sock' in x['Source']]\n require(len(sock_mount) == 1, 'Missing socket mount. Requires the following: '\n 'docker run -v /var/run/docker.sock:/var/run/docker.sock')\n '''\n # Ensure formatting of command for 2 mount points\n if len(mounts) == 2:\n require(all(x['Source'] == x['Destination'] for x in mounts),\n 'Docker Src/Dst mount points, invoked with the -v argument, '\n 'must be the same if only using one mount point aside from the docker socket.')\n work_mount = [x['Source'] for x in mounts if 'docker.sock' not in x['Source']]\n else:\n # Ensure only one mirror mount exists aside from docker.sock\n mirror_mounts = [x['Source'] for x in mounts if x['Source'] == x['Destination']]\n work_mount = [x for x in mirror_mounts if 'docker.sock' not in x]\n require(len(work_mount) == 1, 'Wrong number of mirror mounts provided, see documentation.')\n '''\n\n# if \"TMPDIR\" in os.environ:\n# log.info('Setting work mount to TMPDIR which is: {}'.format(os.environ['TMPDIR']))\n# work_dir = os.environ['TMPDIR']\n# else:\n# log.info('TMPDIR not set; setting work mount to cwd which is: {}'.format(os.getcwd()))\n# work_dir = os.getcwd()\n \n\n# work_mount = list(os.getenv('TMPDIR', os.getcwd()))\n\n # workdir is the cwd so CWL can collect the output\n work_dir = os.getcwd()\n \n # If sample is given as relative path, assume it's in the work directory\n if not all(x.startswith('/') for x in args.samples):\n args.samples = [os.path.join(work_mount[0], x) for x in args.samples if not x.startswith('/')]\n log.info('\\nSample given as relative path, assuming sample is in work directory: {}'.format(work_mount[0]))\n # Enforce file input standards\n require(all(x.startswith('/') for x in args.samples),\n \"Sample inputs must point to a file's full path, \"\n \"e.g. '/full/path/to/sample1.tar'. You provided %s\", str(args.samples))\n require(all(x.startswith('/') for x in [args.star, args.kallisto, args.rsem]),\n \"Sample inputs must point to a file's full path, \"\n \"e.g. '/full/path/to/kallisto_hg38.idx'.\")\n # Output log information\n log.info('The work mount is: {}'.format(work_dir))\n# log.info('The work mount is: {}'.format(work_mount[0]))\n log.info('Samples to run: {}'.format('\\t'.join(args.samples)))\n log.info('Pipeline input locations: \\n{}\\n{}\\n{}'.format(args.star, args.rsem, args.kallisto))\n call_pipeline(work_dir, args)\n# call_pipeline(work_mount[0], args)\n\n\n\nif __name__ == '__main__':\n main()\n","sub_path":"rnaseq-cgl-pipeline/wrapper.py","file_name":"wrapper.py","file_ext":"py","file_size_in_byte":8818,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"264699576","text":"import numpy as np\nfrom scipy.misc import imresize\nfrom os import path\nimport sys\n\n#define desired resolutions of input and target data\nheight = 480\nwidth = 640\n\n#check that an argument has been provided\nif len(sys.argv) == 1:\n print(\"\\n ** No data selected, please run:\\n\\tpython upsample_predict.py ** \\n\")\n exit()\n\n#manipulate argument for file naming\ndata_path = sys.argv[1]\nfile_name, ext = path.splitext(data_path)\nfile_name = '%s_resized2' % file_name\n\n# load data\ndata = np.load(data_path)\ndepths = data['depths']\ndepths = np.squeeze(depths, axis=3)\n\n#initialise resized arrays\ndepths_resized = np.zeros([0, height, width], dtype=np.float32)\nfor i in range(depths.shape[0]):\n #resize depth image to the desired resolution\n de_temp = imresize(depths[i], [height, width], 'bicubic')\n #convert to float32\n de_temp = np.float32(de_temp)\n #set minimum value to zero\n #de_temp = de_temp + abs(np.amin(de_temp))\n #normalise so that all images have the same maximum brightness\n #de_temp = (de_temp/np.max(de_temp))*255.0\n #append the processed image to the output array\n depths_resized = np.append(depths_resized, np.expand_dims(de_temp, axis=0), axis=0)\n #print every 25 sets of images so you can see it's working\n if (i+1) % 25 == 0:\n print('%d depth images resized' % (i+1))\n\n#rearrange into proper columns\ndepths_resized = np.transpose(depths_resized, [1, 2, 0])\n\n#check data shapes\nprint(depths_resized.shape)\n\n#save to .npz\nnp.savez(file_name, depths=depths_resized)\n","sub_path":"KuzNet/upsample2.py","file_name":"upsample2.py","file_ext":"py","file_size_in_byte":1534,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"485358148","text":"import numpy as np\nimport matplotlib.pyplot as plt\n\nu_S_i = np.array([0.0368, 0.0364, 0.0370, 0.0168, 0.0432, 0.0320, 0.0525, 0.0262, 0.0167, 0.1036, 100000.0]) # Paper\n\nk_i = np.array(\n [10.4571, 23.6702, 19.4110, 7.6675, 37.6126, 41.2519, 36.6254, 49.9662, 64.0682, 24.7827, -1.2808]) # Paper\n\n\n#k_i = np.array(\n# [2.29716861e+01, -4.36550347e+00, -1.99334559e+00, -1.29153970e+00, -9.55228295e-01, -7.57879676e-01, -6.28112624e-01, -5.36287441e-01, -4.67886127e-01, -8.54072144e-01, 1.88134943e-02])\n#u_S_i = np.abs(np.array([1.49751455e-01, -1.58986949e+00, -5.24724374e+00, -1.08548350e+01, -1.84695742e+01, -2.81728596e+01, -4.00705566e+01, -5.42929977e+01, -7.09949830e+01, -4.39002791e+01, 1.00000000e+04]))\n\n#k_i = np.array([1, 1])\n\n#u_S_i = np.array([15, 1.00000000e+04])\n\nn = 10\nmax_voltage = 2.5\n\nsimtime = 20.0 # second\nsimstep = 0.1 # seconds\n\ntimes = np.arange(0, simtime, simstep)\n\nx_0 = 0\nx_end = 1\nx = np.zeros(len(times))\nx[0] = x_0\nq_i = np.zeros((n + 1, len(times)))\nq_dot_i = np.zeros((n + 1, len(times)))\nu_i = np.zeros((n + 1, len(times)))\n\nx_step = (x_end - x_0) / len(times)\n\nu = np.zeros(len(times))\nu[0] = 0.0 # V\ndv_dt_0 = 2*max_voltage/ simtime # 1V / s\nu_max = u[0] + dv_dt_0 * simtime\n\ndv_dt = np.ones(len(times)) * dv_dt_0\ndv_dt[len(dv_dt)/2:] *= -1.0\n\n#u_i[:, 0] = u[0] / (k_i * np.sum(1.0 / k_i))\nq_dot_i[:, 0] = 0.0\nprint(q_dot_i[:, 0])\nprint(u_i[:, 0])\n\nfor index, time in enumerate(times[1:], start=1):\n delta_v = dv_dt[index] * simstep\n u[index] = u[index - 1] + delta_v\n print(\"U is: {}\".format(u[index]))\n #determine, if the current element is (and will stay) unsaturated in this step\n\n k_unsat = np.abs(u_i[:, index - 1]) < u_S_i\n k_unsat_new = np.sign(delta_v)*np.sign(k_i) != np.sign(u_i[:, index - 1]+1e-6) # Adding 1e-6 here, just so sign always returns -1 or 1\n k_unsat = k_unsat | k_unsat_new\n print(\"k_unsat_new: {}\".format(k_unsat_new))\n print(\"k_unsat: {}\".format(k_unsat))\n print(\"Time {}\".format(index))\n #for all k do\n for i in range(len(k_i)):\n print(\"Element {}:\".format(i))\n #print(\"Will stay: {}\".format(np.sign(delta_v)*np.sign(k_i[i]) == np.sign(u_i[i, index - 1])))\n if not k_unsat[i]:\n u_i[i, index] = u_i[i, index - 1]\n print(\"k stays saturated\".format(i))\n else:\n delta_u_i = delta_v * ((1.0 / k_i[i]) / np.sum(np.abs(1.0 / k_i[k_unsat])))\n u_new = u_i[i, index - 1] + delta_u_i\n print(\"Delta u: {}\".format(delta_u_i))\n # = np.delete(k_i, i)\n #u_new = u_i[i, index - 1] + delta_v * (1.0 - np.sum(1.0 / np.abs(k_without_current))/np.sum(1.0 / np.abs(k_i[k_unsat])))\n #print(\"U_new_{} is {} - U_new_old_{} is {} - U_sat_{} is {}\".format(i, u_new, i, u_new_old, i, u_S_i[i]))\n if np.abs(u_new) > u_S_i[i]:\n print(\"ureached sat\".format(i))\n u_i[i, index] = np.sign(u_new)*u_S_i[i]\n else:\n u_i[i, index] = u_new\n q_dot_i[i, index] = k_i[i] * (u_i[i, index] - u_i[i, index - 1]) / simstep\n #print(\"Q_dot_{}: {}\".format(i, q_dot_i[i, index]))\n #x[index] = x[index - 1] + q_dot_i[len(k_i) - 1, index] * simstep\n\n #print(np.sum(k_i * np.sum(1.0/np.abs(k_i[k_unsat]))))\n #d_u_dx = delta_v / q_dot_i[len(k_i)-1, index]\n #print(\"d_u_dx: {}\".format(d_u_dx))\n x[index] = k_i[-1]*u_i[-1, index]\n #print(\"X: {} X_simple: {}\".format(x[index], x_simple))\n\n print(\"U sum is: {} V\".format(np.sum(u_i[:, index])))\n\nfig, ax = plt.subplots(2, 2, constrained_layout=True)\nfig.suptitle(\"Maxwell Slip Simulation\")\nfig.set_size_inches(13, 9)\n\nax[0][0].plot(times, u, label=\"U\")\nax[0][1].plot(times, x, label=\"qdot\")\n\nfor i in range(len(k_i)):\n ax[0][0].plot(times, u_i[i], label=\"u_{}\".format(i))\n ax[1][0].plot(times, q_dot_i[i], label=\"qdot_{}\".format(i))\n\nax[0][0].grid(True)\nax[0][0].legend(loc='right')\nax[0][0].set_title('Voltages')\nax[0][0].set_xlabel('Time [s]')\nax[0][0].set_ylabel('Voltage')\n\nax[1][0].grid(True)\nax[1][0].legend(loc='right')\nax[1][0].set_title('Delta Q')\nax[1][0].set_xlabel('Time [s]')\nax[1][0].set_ylabel('dq/dt*Te')\n\nax[0][1].grid(True)\nax[0][1].legend(loc='right')\nax[0][1].set_title('Travel x')\nax[0][1].set_xlabel('Time [s]')\nax[0][1].set_ylabel('Travel x')\n\n# Voltage vs x\nax[1][1].plot(u, x, label=\"u_ext\")\nax[1][1].grid(True)\nax[1][1].legend(loc='right')\nax[1][1].set_title('Voltage vs Travel')\nax[1][1].set_xlabel('Voltage [V]')\nax[1][1].set_ylabel(\"Travel x\")\n\nplt.show()\n","sub_path":"Digitale_Abgabe/2-Quellcode/Sim_Scripts/Hysteresis_and_Creep_Modeling.py","file_name":"Hysteresis_and_Creep_Modeling.py","file_ext":"py","file_size_in_byte":4524,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"108750574","text":"from typing import List\n\n\nclass Solution:\n def findAnagrams(self, s: str, p: str) -> List[int]:\n def compare(a, b):\n for i in range(26):\n if a[i] != b[i]:\n return False\n return True\n \n if len(s) < len(p):\n return []\n \n n1, n2 = len(s), len(p)\n f1, f2 = [0] * 26, [0] * 26\n \n for c in p:\n f2[ord(c) - ord('a')] += 1\n \n for i in range(n2 - 1):\n f1[ord(s[i]) - ord('a')] += 1\n \n ans = []\n for i in range(n2 - 1, n1):\n f1[ord(s[i]) - ord('a')] += 1\n if i - n2 >= 0:\n f1[ord(s[i - n2]) - ord('a')] -= 1\n \n if compare(f1, f2):\n ans.append(i - n2 + 1)\n \n return ans\n\n\nif __name__ == '__main__':\n s = Solution()\n print(s.findAnagrams(\"cbaebabacd\", \"abc\"))\n","sub_path":"leetcode/medium/find-all-anagrams-in-a-string.py","file_name":"find-all-anagrams-in-a-string.py","file_ext":"py","file_size_in_byte":941,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"534737654","text":"import subprocess\n\n\nclass OpenProgram(object):\n def __init__(self):\n pass\n\n def run(self, program, parameters):\n output_file = open('./temp/outputs', mode='w+')\n command_line = ''\n if not parameters:\n command_line = f'{program} &'\n else:\n command_line = f'{program} {parameters} &'\n subprocess.run(\n command_line,\n shell=True,\n stdout=output_file,\n stderr=output_file,\n universal_newlines=True\n )\n\n def find_program(self, user_input, programs_bd):\n possible_program = ''\n for program in programs_bd:\n nickname = program['nickname']\n if nickname in user_input and nickname > possible_program:\n possible_program = program['value']\n\n return possible_program\n\n def find_params(self, user_input, parameters_bd):\n parameters = []\n for parameter in parameters_bd:\n if parameter['nickname'] in user_input:\n parameters.append(parameter['value'])\n\n return ' '.join(parameters)\n","sub_path":"app/modules/open_program.py","file_name":"open_program.py","file_ext":"py","file_size_in_byte":1110,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"228518951","text":"# -*- coding: utf-8 -*-\nimport os\nimport flask.views\nimport application\nimport magic\nfrom handlers import FileManagerHandler\n\n\nclass IndexView(flask.views.View):\n methods = ['GET', 'POST']\n\n def dispatch_request(self, file_name=None):\n handler = FileManagerHandler()\n if flask.request.method == 'GET':\n return handler.get(flask.request, file_name)\n elif flask.request.method == 'POST':\n return handler.post(flask.request)\n else:\n # This code is never reached: The @app.route decorator\n # handles this automatically.\n return flask.jsonify(\n error=405,\n text='Not Allowed'\n )\n\n\nclass PreviewAPI(flask.views.MethodView):\n methods = ['GET']\n\n def get(self, file_name):\n path = application.app.config['PREVIEW_DIR'] + file_name\n if os.path.exists(path):\n with open(path, 'r') as file:\n try:\n content = file.read()\n except os.error:\n flask.abort(500)\n finally:\n file.close()\n response = flask.make_response(content)\n response.headers['Content-Type'] = \\\n FileManagerHandler.MIME_PDF\n return response\n else:\n flask.abort(404)\n\nclass DownloadAPI(flask.views.MethodView):\n \"\"\"\n For now we have one method for downloading from the working directory and another for the DIP directory\n at least until I can figure out how to multiplex the switching parameter in the url\n (The url is in the form protocol://hostname:port/{dd,wd}/relative_path. The switching parameters, {dd,wd} are\n abbreviations for the respective directories, {DIP and working} directory\n \"\"\"\n methods = ['GET']\n\n def get(self, file_name):\n d_path = application.app.config['WORKING_DIR'] + file_name\n w_path = application.app.config['DATA_DIR'] + file_name\n #tenary test for the file paths\n path = d_path if os.path.exists(d_path) else w_path\n print('\\n\\n(4)-> the path to download from is: ', path, '\\n\\n')\n if os.path.exists(path):\n try:\n with open(path, 'r') as file:\n content = file.read()\n except os.error:\n flask.abort(500)\n finally:\n #Get file mimetype\n mime = magic.from_file(path, mime=True)\n file.close()\n response = flask.make_response(content)\n response.headers['Content-Type'] = mime\n return response\n else:\n flask.abort(404)\n","sub_path":"views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":2720,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"58905182","text":"from concurrent.futures import ThreadPoolExecutor\nimport logging\nimport threading\n\nfrom slamon.agent.handlers import TaskHandler\n\n\nclass Executor(object):\n \"\"\"\n Task executor pool to run task handlers asynchronously.\n To provide clean shutdown, Executor is a python context manager and\n performs shutdown routines on context exit.\n\n Example:\n Executing tasks in existing list ``task_list`` with two concurrent executors:\n\n from slamon.agent.executor import Executor\n\n def result_callback(task_id, task_data=None, task_error=none):\n if task_data:\n print('Task {0} finished with data: {1}'.format(task_id, task_data))\n else:\n print('Task {0} finished with error: {1}'.format(task_id, task_error))\n\n with Executor(max_executors=2) as executor:\n for task in task_list:\n executor.submit_task(task, result_callback)\n\n \"\"\"\n\n def __init__(self, max_executors=2):\n self._max_executors = max_executors\n self._active_executors = 0\n self._lock = threading.Lock()\n self._logger = logging.getLogger('Executor')\n\n def __enter__(self):\n \"\"\"\n Context manager entry function to start thread pool.\n \"\"\"\n self._logger.debug('Starting executor with %d threads', self._max_executors)\n self._thread_pool = ThreadPoolExecutor(self._max_executors)\n return self\n\n def __exit__(self, exc_type, exc_val, exc_tb):\n \"\"\"\n Context manager exit function to shutdown thread pool.\n \"\"\"\n self._logger.debug('Stopping executor')\n self._thread_pool.shutdown()\n self._thread_pool = None\n\n def _run_task(self, task, callback):\n try:\n self._logger.debug('Creating task handler for task %s', task['task_id'])\n handler = TaskHandler.create(task['task_type'], task['task_version'])\n\n self._logger.debug('Executing task handler for task %s', task['task_id'])\n result = handler(task['task_data'])\n\n self._logger.debug('Task executed successfully: %s', task['task_id'])\n callback(task['task_id'], task_data=result)\n\n except Exception as e:\n self._logger.warning('Execution of task %s raised an exception: %s', task['task_id'], str(e))\n callback(task['task_id'], task_error=str(e))\n\n finally:\n with self._lock:\n self._active_executors -= 1\n\n def submit_task(self, task, callback):\n \"\"\"\n Queue task for asynchronous execution. The callback will receive\n task id as first positional parameter and either task_data or task_error\n named parameter describing the output.\n\n :param task: dictionary describing the task\n :param callback: callable that will receive results\n \"\"\"\n with self._lock:\n self._thread_pool.submit(lambda: self._run_task(task, callback))\n self._active_executors += 1\n\n def available_executors(self):\n \"\"\"\n Get number of available executors. (max executors - active executors)\n\n :return: number of available executors\n \"\"\"\n with self._lock:\n return max(self._max_executors - self._active_executors, 0)\n","sub_path":"slamon/agent/executor.py","file_name":"executor.py","file_ext":"py","file_size_in_byte":3318,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"313114544","text":"import matplotlib.cm\nfrom h5py import Group\nfrom matplotlib.figure import Figure\n\n\ndef show_cmatrix(fig: Figure, grp: Group):\n fig.clear()\n try:\n cmat = grp['correlmatrix']\n curvesgrp = grp['curves']\n except KeyError:\n return\n ax = fig.add_subplot(1, 1, 1)\n img = ax.imshow(cmat, cmap=matplotlib.cm.coolwarm, interpolation='nearest')\n fig.colorbar(img, ax=ax)\n fsns = sorted([curvesgrp[ds].attrs['fsn'] for ds in curvesgrp.keys()])\n ax.set_xticks(list(range(len(fsns))))\n ax.set_xticklabels([str(f) for f in fsns], rotation='vertical')\n ax.set_yticks(list(range(len(fsns))))\n ax.set_yticklabels([str(f) for f in fsns])\n","sub_path":"cct/processing/display/correlmatrix.py","file_name":"correlmatrix.py","file_ext":"py","file_size_in_byte":673,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"467992990","text":"import logging\nimport time\n\nimport boto3\nimport dns.resolver\nfrom retrying import retry\n\nlogger = logging.getLogger(__name__)\n\n\ndef get_cluster_id():\n \"\"\"Determine EMR cluster ID via DNS\"\"\"\n resolver = dns.resolver.Resolver()\n cluster_id = resolver.query('dataproc.rasterfoundry.com', 'TXT')[0]\n return cluster_id.to_text().strip('\"')\n\n\n@retry(wait_exponential_multiplier=2000, wait_exponential_max=30000, stop_max_attempt_number=5)\ndef wait_for_emr_success(step_id, cluster_id):\n \"\"\"Wait for batch success/failure given an initial EMR response\n\n Args:\n step_id (str): EMR step ID\n cluster_id (str): EMR cluster ID to check status of step in\n\n Returns:\n boolean\n \"\"\"\n emr = boto3.client('emr')\n get_description = lambda: emr.describe_step(ClusterId=cluster_id, StepId=step_id)\n logger.info('Starting to check for status updates for step %s', step_id)\n step_description = get_description()\n current_status = step_description['Step']['Status']['State']\n logger.info('Initial status: %s', current_status)\n while current_status not in ['COMPLETED', 'FAILED']:\n description = get_description()\n status = description['Step']['Status']['State']\n if status != current_status:\n logger.info('Updating status of %s. Old Status: %s New Status: %s',\n step_id, current_status, status)\n current_status = status\n time.sleep(30)\n is_success = (current_status == 'COMPLETED')\n if is_success:\n logger.info('Successfully completed step id: %s', step_id)\n return True\n else:\n logger.error('Something went wrong with %s. Current Status: %s', step_id, current_status)\n raise Exception('Step {} failed'.format(step_id))","sub_path":"app-tasks/rf/src/rf/utils/emr.py","file_name":"emr.py","file_ext":"py","file_size_in_byte":1771,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"437988590","text":"def numb_to_dig(n):\r\n\tc = []\r\n\twhile n:\r\n\t\tc.append(n%10)\r\n\t\tn /= 10\r\n\treturn c\r\n\r\ndigits = set([1,2,3,4,5,6,7,8,9,0])\r\nfout = open('o_large.txt', 'w')\r\nwith open('A-large.in') as f:\r\n\tt = int(f.readline())\r\n\tfor i in range(int(t)):\r\n\t\tn = int(f.readline())\r\n\t\tif n == 0:\r\n\t\t\tfout.write('CASE #'+str(i+1)+': INSOMNIA\\n')\r\n\t\telse:\r\n\t\t\tz = set(numb_to_dig(n))\r\n\t\t\tcount = 2\r\n\t\t\twhile z != digits:\r\n\t\t\t\tlast_num = n*count\r\n\t\t\t\tz.update(numb_to_dig(last_num))\r\n\t\t\t\tcount+=1\r\n\t\t\tfout.write('CASE #'+str(i+1)+': '+str(last_num)+'\\n')\r\n\r\n","sub_path":"codes/CodeJamCrawler/16_0_1_neat/16_0_1_pikochip_CJ2016_A.py","file_name":"16_0_1_pikochip_CJ2016_A.py","file_ext":"py","file_size_in_byte":531,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"306218927","text":"from django.http import HttpResponse\nfrom django.shortcuts import get_object_or_404, render\nfrom django.core import serializers\nfrom django.views import generic\nfrom django.utils import timezone\nfrom django.contrib.auth.models import User\nfrom rest_framework import viewsets\nimport json, datetime\nfrom locations.serializers import UserSerializer, LocationSerializer\n\nfrom locations.models import Location\n\nclass IndexView(generic.ListView):\n template_name = 'locations/index.html'\n context_object_name = 'user_list'\n\n def get_queryset(self):\n return User.objects.filter(\n registered_date__lte=timezone.now())[:5]\n\n\ndef details(request, pid):\n u = get_object_or_404(User, pid__iexact=pid)\n locs = Location.objects.filter(user = u)\n return render(request, 'locations/details.html', {\n 'user': u,\n 'location_list':locs,\n })\n\n\ndef current_locations(request):\n res = []\n user_list = User.objects.all();\n for user in user_list:\n last_location = Location.objects.filter(user=user).order_by('-timestamp')\n if last_location:\n tmp = {}\n tmp['user'] = user\n tmp['last_location'] = last_location[0]\n res.append(tmp)\n return render(request, 'locations/current_locations.html', {\n 'last_location_list':res,\n })\n\ndef get_user_locations(request, pid):\n user = get_object_or_404(User, pid__iexact=pid)\n location_list = Location.objects.filter(user=user)\n serialized_location_list = serializers.serialize('json', location_list)\n context = { 'pid': user.pid, 'location_list': serialized_location_list }\n return HttpResponse(json.dumps(context), content_type=\"application/json\")\n\ndef save_user_locations(request):\n if request.method == 'POST':\n user = get_object_or_404(User, pid__iexact=request.POST.get('pid'))\n location = Location(user = user,\n latitude = request.POST.get('latitude'),\n longitude = request.POST.get('longitude'),\n timestamp = datetime.datetime.fromtimestamp(float(request.POST.get('timestamp'))))\n location.save()\n return HttpResponse(\"OK\")\n\ndef get_current_locations(request):\n res = []\n user_list = User.objects.all();\n for user in user_list:\n last_location = Location.objects.filter(user=user).order_by('-timestamp')[0]\n tmp = (user.pid, user.first_name, user.last_name, last_location.latitude, last_location.longitude, str(last_location.timestamp))\n res.append(tmp)\n return HttpResponse(json.dumps(res), content_type=\"application/json\")\n\nclass UserViewSet(viewsets.ModelViewSet):\n queryset = User.objects.all()\n serializer_class = UserSerializer\n\n\nclass LocationViewSet(viewsets.ModelViewSet):\n queryset = Location.objects.all()\n serializer_class = LocationSerializer\n\n","sub_path":"locations/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":2918,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"175023702","text":"from bus import Bus\nfrom vehicle import Vehicle\nfrom bear import Bear\nfrom wolf import Wolf\nfrom school import School\nfrom school_bus import SchoolBus\nfrom city import City\nfrom call_sum import Sum\nfrom my_order import MyOrder\nfrom calculate import Calculate\nimport inspect\n\nif inspect.isclass(Vehicle):\n print('# 1. Vehicle class created with the following methods: \\n\\t', sorted(dir(Vehicle), reverse=True))\n\nif inspect.isclass(Bus):\n print('# 2. Bus class created with the following methods: \\n\\t', sorted(dir(Bus), reverse=True))\n\n# 3. Determine which class a given Bus object belongs to (Check type of an object)\n# from bus import Bus\nairport_bus = Bus(80, 90000, 22)\nprint('# 3: ', type(airport_bus))\n\n# 4. Determine if School_bus is also an instance of the Vehicle class\nSchool_bus = Bus(70, 90000, 34)\nprint('# 4:', isinstance(School_bus, Vehicle))\n\nif inspect.isclass(School):\n print('# 5. School class created with the following methods: \\n\\t', sorted(dir(School), reverse=True))\n\nif inspect.isclass(SchoolBus):\n print('# 6. SchoolBus class created with the following methods: \\n\\t', sorted(dir(SchoolBus), reverse=True))\n\n# 7. Polymorphism: Create two classes: Bear, Wolf. Both of them should have make_sound method.\n# Create two instances, one of Bear and one of Wolf,\n# make a tuple of it and by using for call their action using the same method.\nwhite_bear = Bear('Growl!')\narctic_wolf = Wolf('Howl!')\n\nprint('# 7:')\nfor animal in (white_bear, arctic_wolf):\n print('\\t', animal.make_sound())\n\n# 8. Create class City with name, population instance attributes, return a new instance only when population > 1500,\n# otherwise return message: \"Your city is too small\".\nprint('# 8:')\nlondon = City('London', 20000)\nprint('\\t', london)\n\nkyiv = City('Kyiv', 100)\nprint('\\t', kyiv)\n\n# Set value into private attribute\nprint('\\t # Additional ways to assign value to a private attribute:')\nlondon.set_budget(23424311434)\nprint('\\t\\t With getter and setter', london.get_budget())\nlondon._City__budget = 2982989101\nprint('\\t\\t With _object._class__variable', london._City__budget)\n\n# 9. Override a printable string representation of the City class\n# and return: The population of the city {name} is {population}\nlviv = City('Lviv', 1000000)\nprint('# 9:', str(lviv))\n\n# 10*. Override magic method __add__() to perform the additional action as 'multiply' (*)\n# the value which is greater than 10. And perform this add (+) of two instances.\n\n# I created a class called Calculate for this logic\na = Calculate(15)\nb = Calculate(7)\nprint('# 10:', a + b)\n\n# 11. The __call__ method enables Python programmers to write classes\n# where the instances behave like functions and can be called like a function.\n# Create a new class with __call__ method and define this call to return sum.\nfind_sum = Sum(1)\nprint('# 11:', find_sum(4, 5))\n\n# 12*. Making Your Objects Truthy or Falsey Using __bool__().\nprint('# 12:')\norder_1 = MyOrder(['a', 'b', 'c'], 'd')\nprint('\\t', bool(order_1))\n\norder_2 = MyOrder([], 'a')\nprint('\\t', bool(order_2))\n","sub_path":"homeworks/oop_1/hw4_theptinh_oop/hw4.py","file_name":"hw4.py","file_ext":"py","file_size_in_byte":3041,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"230667476","text":"import sys\n\ntry:\n import os\n import shutil\n from platform import system\n from pyfiglet import figlet_format\n from termcolor import colored\nexcept ModuleNotFoundError as error:\n print(colored(error, color=\"red\"))\n input(colored(\"[!]Press Any Key To Exit ....\", color=\"red\"))\n sys.exit()\n\nclear = lambda: os.system(\"cls\") if system() == \"Windows\" else os.system(\"clear\")\n\nimageExtension = (\"png\", \"jpg\", \"jpeg\", \"gif\", \"ico\")\nvideoExtension = (\"mp4\", \"webm\", \"mov\", \"wmv\", \"avi\", \"mkv\")\ncodeExtension = (\"py\", \"html\", \"css\", \"js\", \"php\", \"cpp\", \"bat\", \"c\", \"vb\")\naudioExtension = (\"mp3\", \"ogg\", \"aac\")\ndocExtension = (\"pdf\", \"docx\", \"xlsx\", \"accdb\", \"pptx\")\nappExtension = (\"dmg\", \"exe\")\narchiveExtension = (\"zip\", \"rar\")\ntextExtension = \"txt\"\n\n\ndef organizeYourFiles(path: str) -> None:\n os.chdir(path)\n currentDir = os.getcwd()\n for filename in os.listdir(currentDir):\n if filename.endswith(imageExtension):\n if not os.path.exists(\"Images\"):\n os.mkdir(\"Images\")\n shutil.copy(filename, \"Images\")\n os.remove(filename)\n print(colored(f\"[+]Done {filename}\", color=\"blue\"))\n\n elif filename.endswith(videoExtension):\n if not os.path.exists(\"Videos\"):\n os.mkdir(\"Videos\")\n shutil.copy(filename, \"Videos\")\n os.remove(filename)\n print(colored(f\"[+]Done {filename}\", color=\"blue\"))\n\n elif filename.endswith(audioExtension):\n if not os.path.exists(\"Audios\"):\n os.mkdir(\"Audios\")\n shutil.copy(filename, \"Audios\")\n os.remove(filename)\n print(colored(f\"[+]Done {filename}\", color=\"blue\"))\n\n elif filename.endswith(codeExtension):\n if not os.path.exists(\"Codes\"):\n os.mkdir(\"Codes\")\n shutil.copy(filename, \"Codes\")\n os.remove(filename)\n print(colored(f\"[+]Done {filename}\", color=\"blue\"))\n\n elif filename.endswith(docExtension):\n if not os.path.exists(\"Docs\"):\n os.mkdir(\"Docs\")\n shutil.copy(filename, \"Docs\")\n os.remove(filename)\n print(colored(f\"[+]Done {filename}\", color=\"blue\"))\n \n elif filename.endswith(appExtension):\n if not os.path.exists(\"Apps\"):\n os.mkdir(\"Apps\")\n shutil.copy(filename, \"Apps\")\n os.remove(filename)\n print(colored(f\"[+]Done {filename}\", color=\"blue\"))\n \n elif filename.endswith(archiveExtension):\n if not os.path.exists(\"Archives\"):\n os.mkdir(\"Archives\")\n shutil.copy(filename, \"Archives\")\n os.remove(filename)\n print(colored(f\"[+]Done {filename}\", color=\"blue\"))\n \n elif filename.endswith(textExtension):\n if not os.path.exists(\"Texts\"):\n os.mkdir(\"Texts\")\n shutil.copy(filename, \"Texts\")\n os.remove(filename)\n print(colored(f\"[+]Done {filename}\", color=\"blue\"))\n \n else:\n print(colored(f\"[!]Not Found {filename}\", color=\"red\"))\n\n print(\"\\n\")\n print(colored(\"[++]DONE ALL\", color=\"blue\"))\n\n\nif __name__ == '__main__':\n clear()\n print()\n print(colored(figlet_format(\"Folder Organizer\"), color=\"blue\"))\n print(\"\\n\")\n folderPath = input(colored(\"[+]Folder Path: \", color=\"blue\"))\n print(\"\\n\")\n organizeYourFiles(path=folderPath)\n","sub_path":"folderOrganizer.py","file_name":"folderOrganizer.py","file_ext":"py","file_size_in_byte":3482,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"646769044","text":"#!/usr/bin/env python\r\nimport numpy as np\r\n\r\ndef getModelData():\r\n\t\"\"\" Returns dictionaries containing data about the polymer-water system\r\n\t and about the different cutoffs used in the system\r\n\t\"\"\"\r\n\tpoly_dict = { \"N_mon\": 25, \"N_poly\": 1, \"N_water\" : 1700,\r\n \t \"blength\" : 1.5300, \"Mass_mon\" : 16.0427,\r\n \t \"Kbond\" : 400, \t \"r0\" : 1.53,\r\n \t \"Kangle\" : 55.17204, \r\n \t \"theta0\" : 111.00*(np.pi/180.0),\r\n \t \"LJEpsilon\" : 0.13986, \"LJSigma\" : 3.73}\r\n\r\n\tcut_dict = {\"SPCut\": 7.0, \"LJCut\" : 10.0, \"WCACut\" : 4.187,\n\t\t\t\t\"LDCut\": 6.5, \"LDLowerCut\" : 4.635}\n\t\t\t\t\n\tTempSet = 298.0\n\tret = {'poly_dict': poly_dict, 'cut_dict': cut_dict, 'TempSet': TempSet}\n\treturn ret\r\n \r\n","sub_path":"chem_data.py","file_name":"chem_data.py","file_ext":"py","file_size_in_byte":820,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"71478072","text":"#!/usr/bin/env python\n# -*- coding:utf-8 -*-\n\nfrom .models import Comment\nfrom django import forms\n\n\nclass CommentForm(forms.ModelForm):\n class Meta:\n model = Comment\n fields = ['name', 'text']\n widgets = {\n 'text': forms.Textarea(attrs={'row': 100, 'cols': 100})\n }\n\n","sub_path":"comments/forms.py","file_name":"forms.py","file_ext":"py","file_size_in_byte":310,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"603384573","text":"# coding: utf-8\n\nfrom sqlalchemy.orm.exc import NoResultFound\nfrom sqlalchemy.orm.exc import MultipleResultsFound\n\nfrom .. import session # noqa\nfrom .. import db_delete # noqa\n\n\nclass QueryMixin(object):\n \"\"\"Mixin with common method available to model classes \"\"\"\n\n @classmethod\n def get(cls, id=None, code=None):\n query = cls._query()\n if id is not None:\n query = query.filter(cls.id == id)\n if code is not None:\n query = query.filter(cls.code == code)\n return query.one()\n\n @classmethod\n def query(cls, *args, **kwargs):\n return cls._query(*args, **kwargs).all()\n\n @classmethod\n def count(cls, *args, **kwargs):\n return cls._query(*args, **kwargs).count()\n\n @classmethod\n def exists(cls, *args, **kwargs):\n try:\n cls.get(*args, **kwargs)\n return True\n except NoResultFound:\n return False\n except MultipleResultsFound:\n return True\n\n @classmethod\n def iterquery(cls, batch=50, **kwargs):\n return cls._query(**kwargs).yield_per(batch)\n\n @classmethod\n def _query(cls, order_by=None, offset=None, limit=None):\n query = session.query(cls)\n if order_by is not None:\n query = query.order_by(order_by)\n if offset is not None:\n query = query.offset(offset)\n if limit is not None:\n query = query.limit(limit)\n\n return query\n\n def delete(self):\n db_delete(self)\n\n def __repr__(self):\n if hasattr(self, 'name') and self.name:\n identifier = self.name.encode('utf-8')\n elif hasattr(self, 'title') and self.title:\n identifier = self.title.encode('utf-8')\n elif self.id:\n identifier = '[id: %d]' % self.id\n else:\n identifier = '[new]'\n return \"<%s: %s>\" % (self.__class__.__name__, identifier)\n","sub_path":"src/lib/dbtools/models/query_mixin.py","file_name":"query_mixin.py","file_ext":"py","file_size_in_byte":1918,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"616049404","text":"from django.contrib import admin\nfrom ecommerce_shop.models import Category, Product\n\n\n@admin.register(Product)\nclass ProductAdmin(admin.ModelAdmin):\n list_display = ('title', 'slug')\n prepopulated_fields = {'slug': ('title',)}\n fieldsets = (\n (\"Название\", {\n \"fields\": ((\"title\", \"slug\"), (\"description\",))\n }),\n (\"Управление\", {\n \"fields\": (\"draft\", \"category\", \"image\")\n }),\n (\"Цена\", {\n \"fields\": (\"price\", \"discount\")\n }),\n\n )\n\n\n@admin.register(Category)\nclass CategoryAdmin(admin.ModelAdmin):\n list_display = ('title', 'slug')\n prepopulated_fields = {'slug': ('title',)}\n","sub_path":"ecommerce_shop/admin.py","file_name":"admin.py","file_ext":"py","file_size_in_byte":692,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"119999255","text":"# -*- coding: utf-8 -*-\nfrom Qt.QtWidgets import *\nfrom Qt.QtCore import *\nfrom Qt.QtGui import *\nimport resource\n\n\nclass Ui_ThumbnailWidget(object):\n def setupUi(self, ThumbnailWidget):\n ThumbnailWidget.setObjectName(\"ThumbnailWidget\")\n ThumbnailWidget.resize(347, 266)\n ThumbnailWidget.setStyleSheet(\"\")\n self.thumbnail = QLabel(ThumbnailWidget)\n self.thumbnail.setGeometry(QRect(210, 190, 81, 61))\n self.thumbnail.setMinimumSize(QSize(0, 0))\n self.thumbnail.setMaximumSize(QSize(16777215, 16777215))\n self.thumbnail.setStyleSheet(\"\")\n self.thumbnail.setText(\"\")\n self.thumbnail.setScaledContents(False)\n self.thumbnail.setAlignment(Qt.AlignCenter)\n self.thumbnail.setObjectName(\"thumbnail\")\n self.buttons_frame = QFrame(ThumbnailWidget)\n self.buttons_frame.setGeometry(QRect(40, 30, 211, 191))\n self.buttons_frame.setStyleSheet(\"#buttons_frame {\\n\"\n\"border-radius: 2px;\\n\"\n\"background-color: rgba(0,0,0, 64);\\n\"\n\"}\")\n self.buttons_frame.setFrameShape(QFrame.NoFrame)\n self.buttons_frame.setFrameShadow(QFrame.Plain)\n self.buttons_frame.setLineWidth(0)\n self.buttons_frame.setObjectName(\"buttons_frame\")\n self.verticalLayout_2 = QVBoxLayout(self.buttons_frame)\n self.verticalLayout_2.setContentsMargins(0, 0, 0, 0)\n self.verticalLayout_2.setObjectName(\"verticalLayout_2\")\n spacerItem = QSpacerItem(20, 52, QSizePolicy.Minimum, QSizePolicy.Expanding)\n self.verticalLayout_2.addItem(spacerItem)\n self.horizontalLayout_2 = QHBoxLayout()\n self.horizontalLayout_2.setObjectName(\"horizontalLayout_2\")\n spacerItem1 = QSpacerItem(20, 20, QSizePolicy.Expanding, QSizePolicy.Minimum)\n self.horizontalLayout_2.addItem(spacerItem1)\n self.camera_btn = QPushButton(self.buttons_frame)\n sizePolicy = QSizePolicy(QSizePolicy.Preferred, QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.camera_btn.sizePolicy().hasHeightForWidth())\n self.camera_btn.setSizePolicy(sizePolicy)\n self.camera_btn.setMinimumSize(QSize(64, 64))\n self.camera_btn.setMaximumSize(QSize(16777215, 16777215))\n self.camera_btn.setCursor(Qt.PointingHandCursor)\n self.camera_btn.setStyleSheet(\"#camera_btn {\\n\"\n\" background-color: rgba( 0, 0, 0, 0 );\\n\"\n\" image: url(:/images/camera.png);\\n\"\n\" margin: 5px;\\n\"\n\" border: none;\\n\"\n\"}\\n\"\n\"#camera_btn:hover {\\n\"\n\" image: url(:/images/camera_hl.png);\\n\"\n\"}\\n\"\n\"#camera_btn:focus:pressed {\\n\"\n\" image: url(:/images/camera_hl.png);\\n\"\n\"}\\n\"\n\"\\n\"\n\"\")\n self.camera_btn.setText(\"\")\n self.camera_btn.setIconSize(QSize(64, 64))\n self.camera_btn.setFlat(True)\n self.camera_btn.setObjectName(\"camera_btn\")\n self.horizontalLayout_2.addWidget(self.camera_btn)\n spacerItem2 = QSpacerItem(20, 20, QSizePolicy.Expanding, QSizePolicy.Minimum)\n self.horizontalLayout_2.addItem(spacerItem2)\n self.horizontalLayout_2.setStretch(0, 1)\n self.horizontalLayout_2.setStretch(1, 2)\n self.horizontalLayout_2.setStretch(2, 1)\n self.verticalLayout_2.addLayout(self.horizontalLayout_2)\n spacerItem3 = QSpacerItem(20, 51, QSizePolicy.Minimum, QSizePolicy.Expanding)\n self.verticalLayout_2.addItem(spacerItem3)\n self.verticalLayout_2.setStretch(0, 1)\n self.verticalLayout_2.setStretch(1, 2)\n self.verticalLayout_2.setStretch(2, 1)\n\n self.retranslateUi(ThumbnailWidget)\n QMetaObject.connectSlotsByName(ThumbnailWidget)\n\n def retranslateUi(self, ThumbnailWidget):\n try:\n ThumbnailWidget.setWindowTitle(QApplication.translate(\"ThumbnailWidget\", \"Screen Shot\", None, QApplication.UnicodeUTF8))\n except:\n ThumbnailWidget.setWindowTitle(QApplication.translate(\"ThumbnailWidget\", \"Screen Shot\", None))\n\nif __name__ == \"__main__\":\n pass\n","sub_path":"mliber_qt_components/screen_shot/screen_shot_ui.py","file_name":"screen_shot_ui.py","file_ext":"py","file_size_in_byte":4032,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"305882065","text":"from typing import Optional\n\nfrom anubis.models import Config\nfrom anubis.utils.cache import cache\n\n\n@cache.memoize(timeout=10, source_check=True)\ndef get_config_str(key: str, default: Optional[str] = None) -> Optional[str]:\n \"\"\"\n Get a config str entry for a given config key. Optionally specify a\n default value for if the key does not exist in the config table.\n\n :param key:\n :param default:\n :return:\n \"\"\"\n\n # Query database for config row\n config_value: Config = Config.query.filter(Config.key == key).first()\n\n # Check that the config value exists\n if config_value is None:\n\n # Return default if entry was not found\n return default\n\n # Return the string value if it exists\n return config_value.value\n\n\n@cache.memoize(timeout=10, source_check=True)\ndef get_config_int(key: str, default: Optional[int] = None) -> Optional[int]:\n \"\"\"\n Get a config int entry for a given config key. Optionally specify a\n default value for if the key does not exist in the config table.\n\n :param key:\n :param default:\n :return:\n \"\"\"\n\n # Query database for config row\n config_value: Config = Config.query.filter(Config.key == key).first()\n\n # Check that the config value exists\n if config_value is None:\n # Return default if entry was not found\n return default\n\n # Attempt to convert and return the entry as an int\n try:\n # Try to convert the value to an int. This will raise a value\n # exception if there is any issue with the format with the\n # value.\n config_value_int = int(config_value.value.strip())\n\n # Pass back the converted integer value\n return config_value_int\n\n # ValueError will be raised if the underlying config value could\n # not be converted to an int.\n except ValueError:\n\n # If there was any issue, return default\n return default\n","sub_path":"api/anubis/utils/config.py","file_name":"config.py","file_ext":"py","file_size_in_byte":1906,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"248368651","text":"import math\n\n\ndef heuristic(first_point, second_point):\n return abs(first_point.x - second_point.x) + abs(first_point.y - second_point.y)\n\n\nclass Point:\n def __init__(self, x, y, blocked=False):\n self.x = x\n self.y = y\n self.blocked = blocked\n self.gScore = math.inf\n self.fScore = math.inf\n self.hScore = math.inf\n self.neighbours = []\n self.beginning = False\n self.target = False\n self.previous = None\n\n\nclass AStar:\n def __init__(self, start_point, end_point, map_array):\n self.width = len(map_array[0])\n self.height = len(map_array)\n self.collisions = self.parseCollisions(map_array)\n self.start = self.collisions[start_point.y][start_point.x]\n self.end = self.collisions[end_point.y][end_point.x]\n self.openSet = []\n self.closedSet = []\n self.init()\n\n def parseCollisions(self, map_array):\n newCollisions = []\n for h in range(self.height):\n newCollisions.append([])\n for w in range(self.width):\n newCollisions[h].append(Point(w, h, map_array[h][w] == 1))\n\n return newCollisions\n\n def addNeighbours(self):\n for h in range(self.height):\n for w in range(self.width):\n self.collisions[h][w] = self.addPointNeighbours(self.collisions[h][w])\n\n def addPointNeighbours(self, node):\n x = node.x\n y = node.y\n neighbours = []\n\n if x > 0:\n neighbours.append(self.collisions[y][x - 1]) # lewo\n if y > 0:\n neighbours.append(self.collisions[y - 1][x]) # góra\n if x < self.width - 1:\n neighbours.append(self.collisions[y][x + 1]) # prawo\n if y < self.height - 1:\n neighbours.append(self.collisions[y + 1][x]) # dół\n if x > 0 and y > 0:\n neighbours.append(self.collisions[y - 1][x - 1]) # lewo, góra\n if y > 0 and x < self.width - 1:\n neighbours.append(self.collisions[y - 1][x + 1]) # prawo, góra\n if x > 0 and y < self.height - 1:\n neighbours.append(self.collisions[y + 1][x - 1]) # lewo, dół\n if x < self.width - 1 and y < self.height - 1:\n neighbours.append(self.collisions[y + 1][x + 1]) # prawo, dół\n\n node.neighbours = neighbours\n\n return node\n\n def getLowestFScore(self):\n lowestIndex = 0\n for idx, node in enumerate(self.openSet):\n if node.fScore < self.openSet[lowestIndex].fScore:\n lowestIndex = idx\n\n return lowestIndex\n\n def reconstructPath(self):\n path = []\n currentNode = self.end\n\n while currentNode is not self.start:\n path.append(currentNode)\n currentNode = currentNode.previous\n\n path.append(self.start)\n path.reverse()\n return path\n\n def findPath(self):\n while len(self.openSet) > 0:\n currentIndex = self.getLowestFScore()\n currentNode = self.openSet[currentIndex]\n if currentNode == self.end:\n return self.reconstructPath()\n\n self.openSet.remove(self.openSet[currentIndex])\n self.closedSet.append(currentNode)\n\n for neighbour in currentNode.neighbours:\n if neighbour in self.closedSet:\n continue\n\n isBetter = False\n tentativeScore = currentNode.gScore + 1\n\n if self.end is self.collisions[neighbour.y][neighbour.x]:\n self.openSet.append(neighbour)\n neighbour.hScore = heuristic(neighbour, self.end)\n isBetter = True\n\n elif neighbour not in self.openSet and neighbour.blocked is False:\n self.openSet.append(neighbour)\n neighbour.hScore = heuristic(neighbour, self.end)\n isBetter = True\n\n elif tentativeScore < neighbour.gScore and neighbour.blocked is False:\n isBetter = True\n\n if isBetter:\n neighbour.previous = currentNode\n neighbour.gScore = tentativeScore\n neighbour.fScore = neighbour.gScore + neighbour.hScore\n\n return []\n\n def init(self):\n self.start.beginning = True\n self.start.gScore = 0\n self.start.fScore = heuristic(self.start, self.end)\n\n self.end.target = True\n self.end.gScore = 0\n\n self.openSet.append(self.start)\n\n self.addNeighbours()\n\n\nmy_map = [\n [0, 0, 0, 0, 0, 0, 0, 0],\n [0, 1, 0, 0, 0, 0, 0, 0],\n [0, 1, 0, 0, 0, 0, 1, 0],\n [0, 0, 1, 0, 0, 0, 1, 0],\n [0, 0, 1, 0, 0, 0, 1, 0],\n [0, 0, 1, 0, 0, 0, 1, 0],\n [0, 0, 1, 0, 1, 1, 0, 0],\n [0, 0, 0, 0, 1, 0, 0, 0],\n]\n\nstart = Point(0, 0)\nend = Point(7, 7)\n\nroad = AStar(start, end, my_map).findPath()\n\nif len(road) == 0:\n print(\"Nie znaleziono trasy.\")\nelse:\n for index, point in enumerate(road):\n print(f\"Krok {index + 1}: ({point.x}, {point.y})\")","sub_path":"Astar.py","file_name":"Astar.py","file_ext":"py","file_size_in_byte":5073,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"339818212","text":"#!/usr/bin/env python\n# -*- coding:utf-8 -*-\n# Author:ZhengzhengLiu\n \nimport numpy as np\n \n#sigmoid激活函数\ndef sigmoid(Z):\n \"\"\"\n param :\n Z: 任意维度的numpy数组\n return:\n A -- sigmoid(Z)的输出，与Z的维度相同\n cache -- 返回Z，存储起来在反向传播时使用\n \"\"\"\n A = 1/(1+np.exp(-Z))\n cache = Z\n \n return A,cache\n \n# ReLU激活函数\ndef relu(Z):\n \"\"\"\n param :\n Z -- 任意维度,线性层的输出\n return:\n A -- 激活后的结果, 与Z的维度相同\n cache -- python字典包含\"A\" ,存储起来以便高效执行反向传播\n \"\"\"\n A = np.maximum(0,Z)\n \n # Python中的assert断言用起来非常简单，可在assert后面跟上任意判断条件\n # 如果断言失败则会抛出异常\n assert (A.shape == Z.shape)\n cache = Z\n \n return A,cache\n \n#利用ReLU单元计算反向传播\ndef relu_backward(dA,cache):\n \"\"\"\n param :\n dA -- 任意维度,损失函数对A的梯度\n cache -- Z，存储起来在反向传播时使用\n return:\n dZ -- 损失函数对Z的梯度 = 损失函数对A的梯度 * relu激活函数对Z的梯度\n \"\"\"\n Z = cache\n dZ = np.array(dA,copy=True) #relu激活函数在Z>0时梯度为1\n \n #当Z<=0时，将dZ设置为0\n dZ[Z <= 0] = 0\n assert (dZ.shape == Z.shape)\n \n return dZ\n \n#利用sigmoid单元计算反向传播\ndef sigmoid_backward(dA,cache):\n \"\"\"\n param :\n dA -- 任意维度,损失函数对A的梯度\n cache -- Z，存储起来在反向传播时使用\n return:\n dZ -- 损失函数对Z的梯度 = 损失函数对A的梯度 * sigmoid激活函数对Z的梯度\n \"\"\"\n Z = cache\n s = 1/(1+np.exp(-Z))\n \n dZ = dA * s * (1 - s)\n \n assert (dZ.shape == Z.shape)\n return dZ\n","sub_path":"NeuralNetworks/dnn_utils.py","file_name":"dnn_utils.py","file_ext":"py","file_size_in_byte":1779,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"173589979","text":"def sol(data):\n count = 1\n stack = []\n result = []\n for i in range(len(data)):\n while count <= data[i]:\n stack.append(count)\n count += 1\n result.append('+')\n if stack[-1] == data[i]:\n stack.pop()\n result.append('-')\n\n else:\n return 'no'\n return result\n\n\n\n\n\ndata = [ 4 , 3, 6 , 8 , 7, 5, 2, 1]\n\nprint(sol(data))","sub_path":"09_test/t03.py","file_name":"t03.py","file_ext":"py","file_size_in_byte":412,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"58699660","text":"from flask import Flask, render_template, request\nfrom final_project.machinetranslation.translator import translate_en_to_fr, translate_fr_to_en\n\napp = Flask(\"Web Translator\")\n\n\n@app.route(\"/englishToFrench\")\ndef englishToFrench():\n textToTranslate = request.args.get('textToTranslate')\n return translate_en_to_fr(textToTranslate)\n\n\n@app.route(\"/frenchToEnglish\")\ndef frenchToEnglish():\n textToTranslate = request.args.get('textToTranslate')\n return translate_fr_to_en(textToTranslate)\n\n\n@app.route(\"/\")\ndef homepage():\n return render_template(\"index.html\")\n\n\nif __name__ == \"__main__\":\n app.run(host=\"0.0.0.0\", port=8081)\n","sub_path":"final_project/server.py","file_name":"server.py","file_ext":"py","file_size_in_byte":641,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"517721384","text":"import time\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.distributions import Categorical\n\nimport rlberry.spaces as spaces\nfrom rlberry.agents import IncrementalAgent\n\n# choose device\ndevice = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n\n\nclass ValueNet(nn.Module):\n def __init__(self, state_dim, hidden_size=64):\n super(ValueNet, self).__init__()\n # critic\n self.critic = nn.Sequential(\n nn.Linear(state_dim, hidden_size),\n nn.Tanh(),\n nn.Linear(hidden_size, hidden_size),\n nn.Tanh(),\n nn.Linear(hidden_size, 1)\n )\n\n def forward(self, state):\n state_value = self.critic(state)\n return torch.squeeze(state_value)\n\n\nclass PolicyNet(nn.Module):\n def __init__(self, state_dim, action_dim, hidden_size=64):\n super(PolicyNet, self).__init__()\n # actor\n self.actor = nn.Sequential(\n nn.Linear(state_dim, hidden_size),\n nn.Tanh(),\n nn.Linear(hidden_size, hidden_size),\n nn.Tanh(),\n nn.Linear(hidden_size, action_dim)\n )\n self.softmax = nn.Softmax(dim=-1)\n\n def forward(self, state):\n action_probs = self.softmax(self.actor(state))\n dist = Categorical(action_probs)\n return dist\n\n def action_scores(self, state):\n action_scores = self.actor(state)\n return action_scores\n\n\nclass Memory:\n def __init__(self):\n self.actions = []\n self.states = []\n self.logprobs = []\n self.rewards = []\n self.is_terminals = []\n\n def clear_memory(self):\n del self.actions[:]\n del self.states[:]\n del self.logprobs[:]\n del self.rewards[:]\n del self.is_terminals[:]\n\n\nclass PPOAgent(IncrementalAgent):\n \"\"\"\n References\n ----------\n Schulman, J., Wolski, F., Dhariwal, P., Radford, A. & Klimov, O. (2017).\n \"Proximal Policy Optimization Algorithms.\"\n arXiv preprint arXiv:1707.06347.\n\n Schulman, J., Levine, S., Abbeel, P., Jordan, M., & Moritz, P. (2015).\n \"Trust region policy optimization.\"\n In International Conference on Machine Learning (pp. 1889-1897).\n \"\"\"\n\n name = \"PPO\"\n fit_info = (\"n_episodes\", \"episode_rewards\")\n\n def __init__(self, env,\n n_episodes=4000,\n batch_size=8,\n horizon=256,\n gamma=0.99,\n learning_rate=0.01,\n eps_clip=0.2,\n k_epochs=5,\n verbose=1,\n **kwargs):\n \"\"\"\n env : Model\n Online model with continuous (Box) state space and discrete actions\n n_episodes : int\n Number of episodes\n batch_size : int\n Number of episodes to wait before updating the policy.\n horizon : int\n Horizon.\n gamma : double\n Discount factor in [0, 1].\n learning_rate : double\n Learning rate.\n eps_clip : double\n PPO clipping range (epsilon).\n k_epochs : int\n Number of epochs per update.\n verbose : int\n Controls the verbosity, if non zero, progress messages are printed.\n \"\"\"\n IncrementalAgent.__init__(self, env, **kwargs)\n\n self.n_episodes = n_episodes\n self.batch_size = batch_size\n self.horizon = horizon\n self.gamma = gamma\n self.learning_rate = learning_rate\n self.eps_clip = eps_clip\n self.k_epochs = k_epochs\n\n self.state_dim = self.env.observation_space.dim\n self.action_dim = self.env.action_space.n\n self.verbose = verbose\n\n # check environment\n assert isinstance(self.env.observation_space, spaces.Box)\n assert isinstance(self.env.action_space, spaces.Discrete)\n\n self.cat_policy = None # categorical policy function\n\n # initialize\n self.reset()\n\n def reset(self, **kwargs):\n self.cat_policy = PolicyNet(self.state_dim, self.action_dim).to(device)\n self.policy_optimizer = torch.optim.Adam(self.cat_policy.parameters(),\n lr=self.learning_rate,\n betas=(0.9, 0.999))\n\n self.value_net = ValueNet(self.state_dim).to(device)\n self.value_optimizer = torch.optim.Adam(self.value_net.parameters(),\n lr=self.learning_rate,\n betas=(0.9, 0.999))\n\n self.cat_policy_old = \\\n PolicyNet(self.state_dim, self.action_dim).to(device)\n self.cat_policy_old.load_state_dict(self.cat_policy.state_dict())\n\n self.MseLoss = nn.MSELoss()\n\n self.memory = Memory()\n\n self.episode = 0\n\n # useful data\n self._rewards = np.zeros(self.n_episodes)\n self._cumul_rewards = np.zeros(self.n_episodes)\n\n # logging config\n self._last_printed_ep = 0\n self._time_last_log = time.process_time()\n if self.verbose == 1:\n self._log_interval = 60 # in seconds\n elif self.verbose == 2:\n self._log_interval = 30\n elif self.verbose == 3:\n self._log_interval = 15\n elif self.verbose > 3:\n self._log_interval = 5\n\n def policy(self, state, **kwargs):\n assert self.cat_policy is not None\n state = torch.from_numpy(state).float().to(device)\n action_dist = self.cat_policy_old(state)\n action = action_dist.sample().item()\n return action\n\n def fit(self, **kwargs):\n info = {}\n for k in range(self.n_episodes):\n self._run_episode()\n\n info[\"n_episodes\"] = self.n_episodes\n info[\"episode_rewards\"] = self._rewards\n return info\n\n def partial_fit(self, fraction, **kwargs):\n assert fraction > 0.0 and fraction <= 1.0\n n_episodes_to_run = int(np.ceil(fraction*self.n_episodes))\n count = 0\n while count < n_episodes_to_run and self.episode < self.n_episodes:\n self._run_episode()\n count += 1\n\n info = {}\n info[\"n_episodes\"] = self.episode\n info[\"episode_rewards\"] = self._rewards[:self.episode]\n return info\n\n def _logging(self):\n if self.verbose > 0:\n t_now = time.process_time()\n time_elapsed = t_now - self._time_last_log\n if time_elapsed >= self._log_interval:\n self._time_last_log = t_now\n print(self._info_to_print())\n self._last_printed_ep = self.episode - 1\n\n def _info_to_print(self):\n prev_episode = self._last_printed_ep\n episode = self.episode - 1\n reward_per_ep = self._rewards[prev_episode:episode + 1].sum() \\\n / max(1, episode - prev_episode)\n time_per_ep = self._log_interval * 1000.0 \\\n / max(1, episode - prev_episode)\n time_per_ep = max(0.01, time_per_ep) # avoid div by zero\n fps = int((self.horizon / time_per_ep) * 1000)\n\n to_print = \"[{}] episode = {}/{} \".format(self.name, episode+1,\n self.n_episodes) \\\n + \"| reward/ep = {:0.2f} \".format(reward_per_ep) \\\n + \"| time/ep = {:0.2f} ms\".format(time_per_ep) \\\n + \"| fps = {}\".format(fps)\n return to_print\n\n def _select_action(self, state):\n state = torch.from_numpy(state).float().to(device)\n action_dist = self.cat_policy_old(state)\n action = action_dist.sample()\n action_logprob = action_dist.log_prob(action)\n\n self.memory.states.append(state)\n self.memory.actions.append(action)\n self.memory.logprobs.append(action_logprob)\n\n return action.item()\n\n def _run_episode(self):\n # interact for H steps\n episode_rewards = 0\n state = self.env.reset()\n for t in range(self.horizon):\n # running policy_old\n action = self._select_action(state)\n next_state, reward, done, _ = self.env.step(action)\n\n # save in batch\n self.memory.rewards.append(reward)\n self.memory.is_terminals.append(done)\n episode_rewards += reward\n\n if done:\n break\n\n # update state\n state = next_state\n\n # update\n ep = self.episode\n self._rewards[ep] = episode_rewards\n self._cumul_rewards[ep] = episode_rewards \\\n + self._cumul_rewards[max(0, ep - 1)]\n self.episode += 1\n self._logging()\n\n #\n if self.episode % self.batch_size == 0:\n self._update()\n self.memory.clear_memory()\n\n return episode_rewards\n\n def _update(self):\n # monte carlo estimate of rewards\n rewards = []\n discounted_reward = 0\n for reward, is_terminal in zip(reversed(self.memory.rewards),\n reversed(self.memory.is_terminals)):\n if is_terminal:\n discounted_reward = 0\n discounted_reward = reward + (self.gamma * discounted_reward)\n rewards.insert(0, discounted_reward)\n\n # normalizing the rewards\n rewards = torch.tensor(rewards).to(device).float()\n rewards = (rewards - rewards.mean()) / (rewards.std() + 1e-5)\n\n # convert list to tensor\n old_states = torch.stack(self.memory.states).to(device).detach()\n old_actions = torch.stack(self.memory.actions).to(device).detach()\n old_logprobs = torch.stack(self.memory.logprobs).to(device).detach()\n\n # optimize policy for K epochs\n for _ in range(self.k_epochs):\n # evaluate old actions and values\n action_dist = self.cat_policy(old_states)\n logprobs = action_dist.log_prob(old_actions)\n state_values = self.value_net(old_states)\n dist_entropy = action_dist.entropy()\n\n # find ratio (pi_theta / pi_theta__old)\n ratios = torch.exp(logprobs - old_logprobs.detach())\n\n # find surrogate loss\n advantages = rewards - state_values.detach()\n surr1 = ratios * advantages\n surr2 = torch.clamp(ratios, 1 - self.eps_clip,\n 1 + self.eps_clip) * advantages\n loss = -torch.min(surr1, surr2) \\\n + 0.5 * self.MseLoss(state_values, rewards) \\\n - 0.01 * dist_entropy\n\n # take gradient step\n self.policy_optimizer.zero_grad()\n self.value_optimizer.zero_grad()\n\n loss.mean().backward()\n\n self.policy_optimizer.step()\n self.value_optimizer.step()\n\n # copy new weights into old policy\n self.cat_policy_old.load_state_dict(self.cat_policy.state_dict())\n\n #\n # For hyperparameter optimization\n #\n @classmethod\n def sample_parameters(cls, trial):\n batch_size = trial.suggest_categorical('batch_size',\n [1, 4, 8, 16, 32, 64])\n learning_rate = trial.suggest_loguniform('learning_rate', 1e-5, 1)\n return {\n 'batch_size': batch_size,\n 'learning_rate': learning_rate,\n }\n","sub_path":"rlberry/agents/ppo/ppo.py","file_name":"ppo.py","file_ext":"py","file_size_in_byte":11336,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"427203571","text":"import numpy as np\nimport sys,time,pickle,random,configparser\nfrom sklearn.feature_extraction.text import TfidfVectorizer\nsys.path.append('./Base_Line')\nsys.path.append('../../Base_Line')\nfrom base_data_process import Base_Process\n\nclass parameters():\n def __init__(self):\n self.learning_rate = 0.0001\n # self.is_training = True\n # self.update_embedding = True\n # self.num_train_epochs = 10\n # self.batch_size = 64\n # self.shuffle = True\n # self.dropout_rate = 0.9\n # self.display_per_step = 100\n # self.evaluation_per_step = 500\n # self.require_improvement = 1\n\nclass Date_Process(Base_Process):\n\n # 初始化模型,构造分词器、训练语料分词、生成embedding矩阵\n def init(self):\n \"\"\"\n 初始化参数，主要为4步：\n 1、初始化分词器\n 2、读取数据\n 3、数据处理\n 4、产生预训练的embedding矩阵\n :param feature_selection_name: 使用的预训练矩阵名称\n :return:\n \"\"\"\n self.tokenizer, self.stopwords = self.make_tokenizer()\n self.read_data()\n self.data_process()\n\n\n def parse_config(self,config_path):\n \"\"\"\n 解析config文件，根据不同的参数，解析情况可能不一致\n :return:\n \"\"\"\n # 基础分词器参数\n self.config = configparser.ConfigParser()\n self.config.read(config_path,encoding=\"utf-8-sig\")\n self.uerdict_path = self.config.get('DEFAULT', 'uerdict_path')\n self.stopwords_path = self.config.get('DEFAULT', 'stopwords_path')\n self.tokenizer_name = self.config.get('DEFAULT', 'tokenizer_name')\n\n # 数据处理所需参数\n self.file_path = self.config.get('DATA_PROCESS', 'file_path')\n self.save_path = self.config.get('DATA_PROCESS', 'save_path')\n\n # 模型所需参数\n self.param = parameters()\n self.param.lr = self.config.getfloat('MODEL', 'lr')\n self.param.epoch = self.config.getint('MODEL', 'epoch')\n self.param.wordNgrams = self.config.getint('MODEL', 'wordNgrams')\n self.param.minCount = self.config.getint('MODEL', 'minCount')\n\n # 数据处理（头条）\n def data_process(self):\n \"\"\"\n 获得word2id，tag2id，将原始数据按比例切割。\n :return:\n \"\"\"\n all_tag = []\n for i in self.raw_data:\n if i[-1] not in all_tag:\n all_tag.append(i[-1])\n self.tag2id = {all_tag[i]: i for i in range(len(all_tag))}\n self.id2tag = {v: k for k, v in self.tag2id.items()}\n\n for snentence_1, snentence_2, tag in self.raw_data:\n seg_list = self.tokenizer.cut(snentence_2)\n seg_list = [i for i in seg_list if i not in self.stopwords]\n self.all_data.append([seg_list, tag])\n\n\n random.seed(1)\n random.shuffle(self.all_data)\n data_len = len(self.all_data)\n train = int(data_len * 0.8)\n self.train_data = self.all_data[:train]\n self.test_data = self.all_data[train:]\n\n # 解析数据，将数据变为数字表示\n def parse_data(self, data):\n \"\"\"\n 将原始数据转变为数字id的形式，并进行填充\n :param data:\n :param word2id:\n :param tag2id:\n :param max_length:\n :return:\n \"\"\"\n time_spot = time.time()\n time_spot = str(time_spot).replace(\".\", \"\")[-13:]\n train_file_name = time_spot + \"_train_\" + \".txt\"\n with open(train_file_name, 'w', encoding='utf-8') as f:\n for seg_list, tag in data:\n seg_list = \" \".join(seg_list)\n tag = self.tag2id[tag]\n one_line = seg_list + \"\\t__label__\" + str(tag) + \"\\n\"\n f.write(one_line)\n return train_file_name\n\n # 将数据按批次输出\n def get_batch(self, data, batch_size, max_seq_length, shuffle=False):\n \"\"\"\n :param data:\n :param batch_size:\n :param vocab:\n :param tag2label:\n :param shuffle:\n :return:\n \"\"\"\n if shuffle:\n random.shuffle(data)\n for i in range(len(data) // batch_size):\n data_size = data[i * batch_size: (i + 1) * batch_size]\n seqs, labels, sentence_legth = [], [], []\n for (sent_, tag_, seq_legth) in data_size:\n seqs.append(sent_)\n labels.append(tag_)\n if seq_legth > max_seq_length:\n seq_legth = max_seq_length\n sentence_legth.append(seq_legth)\n yield np.array(seqs), np.array(labels), sentence_legth\n remainder = len(data) % batch_size\n if remainder != 0:\n data_size = data[-remainder:]\n seqs, labels, sentence_legth = [], [], []\n for (sent_, tag_, seq_legth) in data_size:\n seqs.append(sent_)\n labels.append(tag_)\n if seq_legth > max_seq_length:\n seq_legth = max_seq_length\n sentence_legth.append(seq_legth)\n yield np.array(seqs), np.array(labels), sentence_legth\n\n # 保存模型\n def save_model(self, save_path):\n with open(save_path, 'wb') as f:\n pickle.dump((self.train_data, self.test_data,\n self.tag2id, self.id2tag, self.word2id, self.id2word, self.embedding_mat), f)\n\n # 恢复模型\n def load_model(self, load_path):\n with open(load_path, 'rb') as f:\n self.train_data, self.test_data, \\\n self.tag2id, self.id2tag, self.word2id, self.id2word, self.embedding_mat = pickle.load(f)\n\n\n\nif __name__ == '__main__':\n dp = Date_Process()\n dp.parse_config(\"./default.cfg\")\n dp.param.aaaa = 11\n print(dir(dp.param))\n for i in dir(dp.param):\n if \"__\" not in i:\n print(str(i)+\" \"+str(getattr(dp.param, i)))\n","sub_path":"Texts_Classification/fasttext_文本分类/data_process.py","file_name":"data_process.py","file_ext":"py","file_size_in_byte":5939,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"309897204","text":"from jsonschema import validate, ValidationError\nfrom fog05 import Schemas\nfrom dstore import Store\nfrom enum import Enum\nimport re\nimport uuid\nimport json\nimport fnmatch\nimport time\n\nclass FOSStore(object):\n\n \"Helper class to interact with the Store\"\n\n def __init__(self, aroot, droot, home):\n '''\n\n Initialize the Store with root and home\n\n :param aroot: actual store root\n :param droot: desired store root\n :param home: store home also used to generate store id\n '''\n\n self.aroot = aroot # 'dfos://{}'\n self.ahome = str('{}/{}'.format(aroot, home)) # str('dfos://{}/{}' % self.uuid)\n\n self.droot = droot # 'dfos://{}'\n self.dhome = str('{}/{}'.format(droot, home)) # str('dfos://{}/{}' % self.uuid)\n\n self.actual = Store('a{}'.format(home), self.aroot, self.ahome, 1024)\n self.desired = Store('d{}'.format(home), self.droot, self.dhome, 1024)\n\n def close(self):\n '''\n Close the store\n\n :return: None\n '''\n self.actual.close()\n self.desired.close()\n\n\n\n\nclass API(object):\n '''\n This class allow the interaction with fog05 using simple Python3 API\n Need the distributed store\n '''\n\n def __init__(self, sysid=0, store_id=\"python-api\"):\n\n self.a_root = 'afos://{}'.format(sysid)\n self.d_root = 'dfos://{}'.format(sysid)\n self.store = FOSStore(self.a_root, self.d_root, store_id)\n\n self.manifest = self.Manifest(self.store)\n self.node = self.Node(self.store)\n self.plugin = self.Plugin(self.store)\n self.network = self.Network(self.store)\n self.entity = self.Entity(self.store)\n self.image = self.Image(self.store)\n self.flavor = self.Flavor(self.store)\n self.onboard = self.add\n self.offload = self.remove\n\n def add(self, manifest):\n manifest.update({'status': 'define'})\n nodes = self.node.list()\n\n for n in nodes:\n u = n[0]\n uri = \"{}/{}/onboard/{}\".format(self.d_root, u, manifest.get('uuid'))\n value = json.dumps(manifest)\n self.store.desired.put(uri, value)\n\n instances_uuids = {}\n networks_uuid = []\n\n try:\n validate(manifest, Schemas.entity_schema)\n except ValidationError as ve:\n print(ve.message)\n exit(-1)\n nws = manifest.get('networks')\n # print('networks: {}'.format(nws))\n for n in nws:\n for node in nodes:\n res = self.network.add(manifest=n, node_uuid=node[0])\n if not res:\n raise Exception('Error on define network {} -> {} on {} (RES={})'.format(n.get('uuid'), manifest.get('uuid'), node[0],res))\n networks_uuid.append(n.get('uuid'))\n c_list = self.resolve_dependencies(manifest.get('components'))\n for c in c_list:\n search = [x for x in manifest.get(\"components\") if x.get('name') == c]\n if len(search) > 0:\n component = search[0]\n # print('Onboarding: {}'.format(component))\n mf = component.get('manifest')\n res = self.entity.define(manifest=mf, node_uuid=component.get('node'), wait=True)\n # print(res)\n if not res:\n raise Exception('Error on define entity {} -> {} on {} (RES={})'.format(manifest.get('uuid'), mf.get('uuid'), component.get('node'), res))\n time.sleep(0.5)\n c_i_uuid = '{}'.format(uuid.uuid4())\n res = self.entity.configure(mf.get('uuid'), component.get('node'), instance_uuid=c_i_uuid, wait=True)\n # print(res)\n if not res:\n raise Exception('Error on define entity {} -> {} on {} (RES={})'.format(manifest.get('uuid'), mf.get('uuid'), component.get('node'), res))\n res = self.entity.run(mf.get('uuid'), component.get('node'), instance_uuid=c_i_uuid, wait=True)\n # print(res)\n time.sleep(2)\n if not res:\n raise Exception('Error on define entity {} -> {} on {} (RES={})'.format(manifest.get('uuid'), mf.get('uuid'), component.get('node'), res))\n instances_uuids.update({mf.get('uuid'): c_i_uuid})\n\n return {'entity': {manifest.get('uuid'): instances_uuids}, 'networks': networks_uuid }\n\n def remove(self, entity_uuid):\n nodes = self.node.list()\n if len(nodes)>0:\n u = nodes[0][0]\n uri = \"{}/{}/onboard/{}\".format(self.a_root, u, entity_uuid)\n data = self.store.actual.resolve(uri)\n entities = self.entity.list() # {node uuid: {entity uuid: [instance list]} list}\n # print('entities {}'.format(entities))\n if data is not None and len(data) > 0:\n data = json.loads(data)\n # print('Data {}'.format(data))\n for c in data.get('components'):\n # print('C {}'.format(c))\n eid = c.get('manifest').get('uuid')\n # print('eid {}'.format(eid))\n for nid in entities:\n # print('entities.get(nid) {}'.format(entities.get(nid)))\n if eid in entities.get(nid):\n instances = entities.get(nid).get(eid)\n # print('instances {}'.format(instances))\n for inst in instances:\n # print('I should stop {} -> {} -> {}'.format(inst,eid, nid))\n self.entity.stop(eid, nid, inst, wait=True)\n # print('I should clean {} -> {} -> {}'.format(inst, eid, nid))\n self.entity.clean(eid, nid, inst, wait=True)\n # print('I should undefine {} -> {}'.format(eid, nid))\n self.entity.undefine(eid, nid, wait=True)\n for n in nodes:\n u = n[0]\n uri = \"{}/{}/onboard/{}\".format(self.d_root, u, entity_uuid)\n # print('I should remove {}'.format(uri))\n self.store.desired.remove(uri)\n\n\n\n\n def resolve_dependencies(self, components):\n '''\n The return list contains component's name in the order that can be used to deploy\n @TODO: should use less cycle to do this job\n :rtype: list\n :param components: list like [{'name': 'c1', 'need': ['c2', 'c3']}, {'name': 'c2', 'need': ['c3']}, {'name': 'c3', 'need': ['c4']}, {'name': 'c4', 'need': []}, {'name': 'c5', 'need': []}]\n\n no_dependable_components -> list like [[{'name': 'c4', 'need': []}, {'name': 'c5', 'need': []}], [{'name': 'c3', 'need': []}], [{'name': 'c2', 'need': []}], [{'name': 'c1', 'need': []}], []]\n :return: list like ['c4', 'c5', 'c3', 'c2', 'c1']\n '''\n c = list(components)\n no_dependable_components = []\n for i in range(0, len(components)):\n no_dependable_components.append([x for x in c if len(x.get('need')) == 0])\n # print (no_dependable_components)\n c = [x for x in c if x not in no_dependable_components[i]]\n for y in c:\n n = y.get('need')\n n = [x for x in n if x not in [z.get('name') for z in no_dependable_components[i]]]\n y.update({\"need\": n})\n\n order = []\n for i in range(0, len(no_dependable_components)):\n n = [x.get('name') for x in no_dependable_components[i]]\n order.extend(n)\n return order\n\n class Manifest(object):\n '''\n This class encapsulates API for manifests\n\n '''\n def __init__(self, store=None):\n if store is None:\n raise RuntimeError('store cannot be none in API!')\n self.store = store\n\n def check(self, manifest, manifest_type):\n '''\n\n This method allow you to check if a manifest is write in the correct way\n\n\n :param manifest: a dictionary rapresenting the JSON manifest\n :param manifest_type: the manifest type from API.Manifest.Type\n :return: boolean\n '''\n if manifest_type == self.Type.ENTITY:\n t = manifest.get('type')\n try:\n if t == 'vm':\n validate(manifest.get('entity_data'), Schemas.vm_schema)\n elif t == 'container':\n validate(manifest.get('entity_data'), Schemas.container_schema)\n elif t == 'native':\n validate(manifest.get('entity_data'), Schemas.native_schema)\n elif t == 'ros2':\n validate(manifest.get('entity_data'), Schemas.ros2_schema)\n elif t == 'usvc':\n return False\n else:\n return False\n except ValidationError as ve:\n return False\n if manifest_type == self.Type.NETWORK:\n try:\n validate(manifest, Schemas.network_schema)\n except ValidationError as ve:\n return False\n if manifest_type == self.Type.ENTITY:\n try:\n validate(manifest, Schemas.entity_schema)\n except ValidationError as ve:\n return False\n\n return True\n\n class Type(Enum):\n '''\n Manifest types\n '''\n ENTITY = 0\n IMAGE = 1\n FLAVOR = 3\n NETWORK = 4\n PLUGIN = 5\n\n class Node(object):\n '''\n\n This class encapsulates the command for Node interaction\n\n '''\n\n def __init__(self, store=None):\n if store is None:\n raise RuntimeError('store cannot be none in API!')\n self.store = store\n\n def list(self):\n '''\n Get all nodes in the current system/tenant\n\n :return: list of tuples (uuid, hostname)\n '''\n nodes = []\n uri = '{}/*'.format(self.store.aroot)\n infos = self.store.actual.resolveAll(uri)\n for i in infos:\n if len(i[0].split('/')) == 4:\n node_info = json.loads(i[1])\n nodes.append((node_info.get('uuid'), node_info.get('name')))\n return nodes\n\n def info(self, node_uuid):\n \"\"\"\n Provide all information about a specific node\n\n :param node_uuid: the uuid of the node you want info\n :return: a dictionary with all information about the node\n \"\"\"\n if node_uuid is None:\n return None\n uri = '{}/{}'.format(self.store.aroot, node_uuid)\n infos = self.store.actual.resolve(uri)\n if infos is None:\n return None\n return json.loads(infos)\n\n def plugins(self, node_uuid):\n '''\n\n Get the list of plugin installed on the specified node\n\n :param node_uuid: the uuid of the node you want info\n :return: a list of the plugins installed in the node with detailed informations\n '''\n uri = '{}/{}/plugins'.format(self.store.aroot, node_uuid)\n response = self.store.actual.get(uri)\n if response is not None:\n return json.loads(response).get('plugins')\n else:\n return None\n\n def search(self, search_dict):\n '''\n\n Will search for a node that match information provided in the parameter\n\n :param search_dict: dictionary contains all information to match\n :return: a list of node matching the dictionary\n '''\n pass\n\n class Plugin(object):\n '''\n This class encapsulates the commands for Plugin interaction\n\n '''\n def __init__(self, store=None):\n if store is None:\n raise RuntimeError('store cannot be none in API!')\n self.store = store\n\n def add(self, manifest, node_uuid=None):\n '''\n\n Add a plugin to a node or to all node in the system/tenant\n\n :param manifest: the dictionary representing the plugin manifes\n :param node_uuid: optional the node in which add the plugin\n :return: boolean\n '''\n\n\n manifest.update({'status':'add'})\n plugins = {\"plugins\": [manifest]}\n plugins = json.dumps(plugins)\n if node_uuid is None:\n uri = '{}/*/plugins'.format(self.store.droot)\n else:\n uri = '{}/{}/plugins'.format(self.store.droot, node_uuid)\n\n res = self.store.desired.dput(uri, plugins)\n if res:\n return True\n else:\n return False\n\n def remove(self, plugin_uuid, node_uuid=None):\n '''\n\n Will remove a plugin for a node or all nodes\n\n :param plugin_uuid: the plugin you want to remove\n :param node_uuid: optional the node that will remove the plugin\n :return: boolean\n '''\n pass\n\n def list(self, node_uuid=None):\n '''\n\n Same as API.Node.Plugins but can work for all node un the system, return a dictionary with key node uuid and value the plugin list\n\n :param node_uuid: can be none\n :return: dictionary {node_uuid, plugin list }\n '''\n if node_uuid is not None:\n\n uri = '{}/{}/plugins'.format(self.store.aroot, node_uuid)\n response = self.store.actual.get(uri)\n if response is not None:\n return {node_uuid:json.loads(response).get('plugins')}\n else:\n return None\n\n plugins = {}\n uri = '{}/*/plugins'.format(self.store.aroot)\n response = self.store.actual.resolveAll(uri)\n for i in response:\n id = i[0].split('/')[2]\n pl = json.loads(i[1]).get('plugins')\n plugins.update({id: pl})\n return plugins\n\n def search(self, search_dict, node_uuid=None):\n '''\n\n Will search for a plugin matching the dictionary in a single node or in all nodes\n\n :param search_dict: dictionary contains all information to match\n :param node_uuid: optional node uuid in which search\n :return: a dictionary with {node_uuid, plugin uuid list} with matches\n '''\n pass\n\n class Network(object):\n '''\n\n This class encapsulates the command for Network element interaction\n\n '''\n\n def __init__(self, store=None):\n if store is None:\n raise RuntimeError('store cannot be none in API!')\n self.store = store\n\n def __get_all_node_plugin(self, node_uuid):\n uri = '{}/{}/plugins'.format(self.store.aroot, node_uuid)\n response = self.store.actual.resolve(uri)\n if response is not None and response != '':\n return json.loads(response).get('plugins')\n else:\n return None\n\n def add(self, manifest, node_uuid=None):\n '''\n\n Add a network element to a node o to all nodes\n\n\n :param manifest: dictionary representing the manifest of that network element\n :param node_uuid: optional the node uuid in which add the network element\n :return: boolean\n '''\n\n manifest.update({'status': 'add'})\n json_data = json.dumps(manifest)\n\n if node_uuid is not None:\n all_plugins = self.__get_all_node_plugin(node_uuid)\n if all_plugins is None:\n print('Error on receive plugin from node')\n return False\n nws = [x for x in all_plugins if x.get('type') == 'network']\n if len(nws) == 0:\n print('No network plugin loaded on node, aborting')\n return False\n brctl = nws[0].get('uuid') # will use the first plugin\n uri = '{}/{}/network/{}/networks/{}'.format(self.store.droot, node_uuid, brctl, manifest.get('uuid'))\n else:\n uri = '{}/*/network/*/networks/{}'.format(self.store.droot, manifest.get('uuid'))\n\n res = self.store.desired.put(uri, json_data)\n if res >= 0:\n return True\n else:\n return False\n\n def remove(self, net_uuid, node_uuid=None):\n '''\n\n Remove a network element form one or all nodes\n\n :param net_uuid: uuid of the network you want to remove\n :param node_uuid: optional node from which remove the network element\n :return: boolean\n '''\n\n if node_uuid is not None:\n all_plugins = yield from self.__get_all_node_plugin(node_uuid)\n if all_plugins is None:\n print('Error on receive plugin from node')\n return False\n nws = [x for x in all_plugins if x.get('type') == 'network']\n if len(nws) == 0:\n print('No network plugin loaded on node, aborting')\n return False\n brctl = nws[0] # will use the first plugin\n uri = '{}/{}/network/{}/networks/{}'.format(self.store.droot, node_uuid, brctl, net_uuid)\n else:\n uri = '{}/*/network/*/networks/{}'.format(self.store.droot, net_uuid)\n\n res = self.store.desired.remove(uri)\n if res:\n return True\n else:\n return False\n\n def list(self, node_uuid=None):\n '''\n\n List all network element available in the system/teneant or in a specified node\n\n :param node_uuid: optional node uuid\n :return: dictionary {node uuid: network element list}\n '''\n\n if node_uuid is not None:\n n_list = []\n uri = '{}/{}/network/*/networks/'.format(self.store.aroot, node_uuid)\n response = self.store.actual.resolveAll(uri)\n for i in response:\n n_list.append(json.loads(i[1]))\n return {node_uuid: n_list}\n\n nets = {}\n uri = '{}/*/network/*/networks/'.format(self.store.aroot)\n response = self.store.actual.resolveAll(uri)\n for i in response:\n id = i[0].split('/')[2]\n net = json.loads(i[1])\n net_list = nets.get(id, None)\n if net_list is None:\n net_list = []\n net_list.append(net)\n nets.update({id: net_list})\n return nets\n\n def search(self, search_dict, node_uuid=None):\n '''\n\n Will search for a network element matching the dictionary in a single node or in all nodes\n\n :param search_dict: dictionary contains all information to match\n :param node_uuid: optional node uuid in which search\n :return: a dictionary with {node_uuid, network element uuid list} with matches\n '''\n pass\n\n class Entity(object):\n '''\n\n This class encapsulates the api for interaction with entities\n\n '''\n\n def __init__(self, store=None):\n if store is None:\n raise RuntimeError('store cannot be none in API!')\n self.store = store\n\n def __search_plugin_by_name(self, name, node_uuid):\n uri = '{}/{}/plugins'.format(self.store.aroot, node_uuid)\n all_plugins = self.store.actual.resolve(uri)\n if all_plugins is None or all_plugins == '':\n print('Cannot get plugin')\n return None\n all_plugins = json.loads(all_plugins).get('plugins')\n search = [x for x in all_plugins if name.upper() in x.get('name').upper()]\n if len(search) == 0:\n return None\n else:\n return search[0]\n\n def __get_entity_handler_by_uuid(self, node_uuid, entity_uuid):\n uri = '{}/{}/runtime/*/entity/{}'.format(self.store.aroot, node_uuid, entity_uuid)\n all = self.store.actual.resolveAll(uri)\n for i in all:\n k = i[0]\n if fnmatch.fnmatch(k, uri):\n # print('MATCH {0}'.format(k))\n # print('Extracting uuid...')\n regex = uri.replace('/', '\\/')\n regex = regex.replace('*', '(.*)')\n reobj = re.compile(regex)\n mobj = reobj.match(k)\n uuid = mobj.group(1)\n # print('UUID {0}'.format(uuid))\n\n return uuid\n\n def __get_entity_handler_by_type(self, node_uuid, t):\n handler = None\n handler = self.__search_plugin_by_name(t, node_uuid)\n if handler is None:\n print('type not yet supported')\n return handler\n\n def __wait_atomic_entity_state_change(self, node_uuid, handler_uuid, entity_uuid, state):\n while True:\n time.sleep(1)\n uri = '{}/{}/runtime/{}/entity/{}'.format(self.store.aroot, node_uuid, handler_uuid, entity_uuid)\n data = self.store.actual.get(uri)\n if data is not None:\n entity_info = json.loads(data)\n if entity_info is not None and entity_info.get('status') == state:\n return\n\n def __wait_atomic_entity_instance_state_change(self, node_uuid, handler_uuid, entity_uuid, instance_uuid, state):\n while True:\n time.sleep(1)\n uri = '{}/{}/runtime/{}/entity/{}/instance/{}'.format(self.store.aroot, node_uuid, handler_uuid, entity_uuid, instance_uuid)\n data = self.store.actual.get(uri)\n if data is not None:\n entity_info = json.loads(data)\n if entity_info is not None and entity_info.get('status') == state:\n return\n\n def define(self, manifest, node_uuid, wait=False):\n '''\n\n Defines an atomic entity in a node, this method will check the manifest before sending the definition to the node\n\n :param manifest: dictionary representing the atomic entity manifest\n :param node_uuid: destination node uuid\n :param wait: if wait that the definition is complete before returning\n :return: boolean\n '''\n\n manifest.update({'status': 'define'})\n handler = None\n t = manifest.get('type')\n try:\n if t in ['kvm', 'xen']:\n handler = self.__search_plugin_by_name(t, node_uuid)\n validate(manifest.get('entity_data'), Schemas.vm_schema)\n elif t in ['container', 'lxd']:\n handler = self.__search_plugin_by_name(t, node_uuid)\n validate(manifest.get('entity_data'), Schemas.container_schema)\n elif t == 'native':\n handler = self.__search_plugin_by_name('native', node_uuid)\n validate(manifest.get('entity_data'), Schemas.native_schema)\n elif t == 'ros2':\n handler = self.__search_plugin_by_name('ros2', node_uuid)\n validate(manifest.get('entity_data'), Schemas.ros2_schema)\n elif t == 'usvc':\n print('microservice not yet')\n else:\n print('type not recognized')\n\n if handler is None:\n print('Handler not found!! (Is none)')\n return False\n except ValidationError as ve:\n print('Validation error: {}'.format(ve.message))\n return False\n\n if handler.get('uuid') is None:\n print('Handler not found!! (Cannot get handler uuid)')\n return False\n\n entity_uuid = manifest.get('uuid')\n entity_definition = manifest\n json_data = json.dumps(entity_definition)\n uri = '{}/{}/runtime/{}/entity/{}'.format(self.store.droot, node_uuid, handler.get('uuid'), entity_uuid)\n\n res = self.store.desired.put(uri, json_data)\n # print('RES is {}'.format(res))\n if res >= 0:\n if wait:\n self.__wait_atomic_entity_state_change(node_uuid,handler.get('uuid'), entity_uuid, 'defined')\n return True\n else:\n return False\n\n def undefine(self, entity_uuid, node_uuid, wait=False):\n '''\n\n This method undefine an atomic entity in a node\n\n :param entity_uuid: atomic entity you want to undefine\n :param node_uuid: destination node\n :param wait: if wait before returning that the entity is undefined\n :return: boolean\n '''\n handler = self.__get_entity_handler_by_uuid(node_uuid, entity_uuid)\n uri = '{}/{}/runtime/{}/entity/{}'.format(self.store.droot, node_uuid, handler, entity_uuid)\n\n res = self.store.desired.remove(uri)\n return True\n # if res >= 0:\n # return True\n # else:\n # return False\n\n def configure(self, entity_uuid, node_uuid, instance_uuid=None, wait=False):\n '''\n\n Configure an atomic entity, creation of the instance\n\n :param entity_uuid: entity you want to configure\n :param node_uuid: destination node\n :param instance_uuid: optional if preset will use that uuid for the atomic entity instance otherwise will generate a new one\n :param wait: optional wait before returning\n :return: intstance uuid or none in case of error\n '''\n handler = self.__get_entity_handler_by_uuid(node_uuid, entity_uuid)\n if instance_uuid is None:\n instance_uuid = '{}'.format(uuid.uuid4())\n\n uri = '{}/{}/runtime/{}/entity/{}/instance/{}#status=configure'.format(self.store.droot, node_uuid, handler, entity_uuid, instance_uuid)\n res = self.store.desired.dput(uri)\n # print('RES is {}'.format(res))\n if res >= 0:\n if wait:\n self.__wait_atomic_entity_instance_state_change(node_uuid, handler, entity_uuid, instance_uuid, 'configured')\n return instance_uuid\n else:\n return None\n\n def clean(self, entity_uuid, node_uuid, instance_uuid, wait=False):\n '''\n\n Clean an atomic entity instance, this will destroy the instance\n\n :param entity_uuid: entity for which you want to clean an instance\n :param node_uuid: destionation node\n :param instance_uuid: instance you want to clean\n :param wait: optional wait before returning\n :return: boolean\n '''\n handler = yield from self.__get_entity_handler_by_uuid(node_uuid, entity_uuid)\n uri = '{}/{}/runtime/{}/entity/{}/instance/{}'.format(self.store.aroot, node_uuid, handler, entity_uuid, instance_uuid)\n res = self.store.desired.remove(uri)\n # if res >= 0:\n # return True\n # else:\n # return False\n return True\n\n def run(self, entity_uuid, node_uuid, instance_uuid, wait=False):\n '''\n\n Starting and atomic entity instance\n\n :param entity_uuid: entity for which you want to run the instance\n :param node_uuid: destination node\n :param instance_uuid: instance you want to start\n :param wait: optional wait before returning\n :return: boolean\n '''\n handler = self.__get_entity_handler_by_uuid(node_uuid, entity_uuid)\n uri = '{}/{}/runtime/{}/entity/{}/instance/{}#status=run'.format(self.store.droot, node_uuid, handler, entity_uuid, instance_uuid)\n res = self.store.desired.dput(uri)\n # print('RES is {}'.format(res))\n if res >= 0:\n if wait:\n state = \"run\"\n while True:\n time.sleep(1)\n uri = '{}/{}/runtime/{}/entity/{}/instance/{}'.format(self.store.aroot, node_uuid, handler, entity_uuid, instance_uuid)\n data = self.store.actual.get(uri)\n if data is not None:\n entity_info = json.loads(data)\n if entity_info is not None:\n if entity_info.get('status') == state:\n break\n elif entity_info.get('status') != \"starting\":\n uri = '{}/{}/runtime/{}/entity/{}/instance/{}#status=run'.format(self.store.droot, node_uuid, handler, entity_uuid, instance_uuid)\n self.store.desired.dput(uri)\n return True\n else:\n return False\n\n def stop(self, entity_uuid, node_uuid, instance_uuid, wait=False):\n '''\n\n Shutting down an atomic entity instance\n\n :param entity_uuid: entity for which you want to shutdown the instance\n :param node_uuid: destination node\n :param instance_uuid: instance you want to shutdown\n :param wait: optional wait before returning\n :return: boolean\n '''\n\n handler = self.__get_entity_handler_by_uuid(node_uuid, entity_uuid)\n uri = '{}/{}/runtime/{}/entity/{}/instance/{}#status=stop'.format(self.store.droot, node_uuid, handler, entity_uuid, instance_uuid)\n res = self.store.desired.dput(uri)\n if res >= 0:\n if wait:\n self.__wait_atomic_entity_instance_state_change(node_uuid, handler, entity_uuid, instance_uuid, 'stop')\n return True\n else:\n return False\n\n def pause(self, entity_uuid, node_uuid, instance_uuid, wait=False):\n '''\n\n Pause the exectution of an atomic entity instance\n\n :param entity_uuid: entity for which you want to pause the instance\n :param node_uuid: destination node\n :param instance_uuid: instance you want to pause\n :param wait: optional wait before returning\n :return: boolean\n '''\n handler = self.__get_entity_handler_by_uuid(node_uuid, entity_uuid)\n uri = '{}/{}/runtime/{}/entity/{}/instance/{}#status=pause'.format(self.store.droot, node_uuid, handler, entity_uuid, instance_uuid)\n res = self.store.desired.dput(uri)\n if res >= 0:\n if wait:\n self.__wait_atomic_entity_instance_state_change(node_uuid, handler, entity_uuid, instance_uuid, 'pause')\n return True\n else:\n return False\n\n def resume(self, entity_uuid, node_uuid, instance_uuid, wait=False):\n '''\n\n resume the exectution of an atomic entity instance\n\n :param entity_uuid: entity for which you want to resume the instance\n :param node_uuid: destination node\n :param instance_uuid: instance you want to resume\n :param wait: optional wait before returning\n :return: boolean\n '''\n\n\n handler = self.__get_entity_handler_by_uuid(node_uuid, entity_uuid)\n uri = '{}/{}/runtime/{}/entity/{}/instance/{}#status=resume'.format(self.store.droot, node_uuid, handler, entity_uuid, instance_uuid)\n res = self.store.desired.dput(uri)\n if res >= 0:\n if wait:\n self.__wait_atomic_entity_instance_state_change(node_uuid, handler, entity_uuid, instance_uuid, 'run')\n return True\n else:\n return False\n\n def migrate(self, entity_uuid, instance_uuid, node_uuid, destination_node_uuid, wait=False):\n '''\n\n Live migrate an atomic entity instance between two nodes\n\n The migration is issued when this command is sended, there is a little overhead for the copy of the base image and the disk image\n\n\n :param entity_uuid: ntity for which you want to migrate the instance\n :param instance_uuid: instance you want to migrate\n :param node_uuid: source node for the instance\n :param destination_node_uuid: destination node for the instance\n :param wait: optional wait before returning\n :return: boolean\n '''\n\n\n handler = self.__get_entity_handler_by_uuid(node_uuid, entity_uuid)\n uri = '{}/{}/runtime/{}/entity/{}/instance/{}'.format(self.store.aroot, node_uuid, handler, entity_uuid, instance_uuid)\n\n entity_info = self.store.actual.get(uri)\n if entity_info is None:\n return False\n\n entity_info = json.loads(entity_info)\n\n entity_info_src = entity_info.copy()\n entity_info_dst = entity_info.copy()\n\n entity_info_src.update({\"status\": \"taking_off\"})\n entity_info_src.update({\"dst\": destination_node_uuid})\n\n entity_info_dst.update({\"status\": \"landing\"})\n entity_info_dst.update({\"dst\": destination_node_uuid})\n\n destination_handler = self.__get_entity_handler_by_type(destination_node_uuid, entity_info_dst.get('type'))\n if destination_handler is None:\n return False\n\n uri = '{}/{}/runtime/{}/entity/{}/instance/{}'.format(self.store.droot, destination_node_uuid, destination_handler.get('uuid'), entity_uuid, instance_uuid)\n\n res = self.store.desired.put(uri, json.dumps(entity_info_dst))\n if res >= 0:\n uri = '{}/{}/runtime/{}/entity/{}/instance/{}'.format(self.store.droot, node_uuid, handler, entity_uuid, instance_uuid)\n res_dest = yield from self.store.desired.dput(uri, json.dumps(entity_info_src))\n if res_dest:\n if wait:\n self.__wait_atomic_entity_instance_state_change(destination_node_uuid, destination_handler.get('uuid'), entity_uuid, instance_uuid, 'run')\n return True\n else:\n print(\"Error on destination node\")\n return False\n else:\n print(\"Error on source node\")\n return False\n\n def search(self, search_dict, node_uuid=None):\n pass\n\n def list(self, node_uuid=None):\n '''\n\n List all entity element available in the system/teneant or in a specified node\n\n :param node_uuid: optional node uuid\n :return: dictionary {node uuid: {entity uuid: instance list} list}\n '''\n\n if node_uuid is not None:\n entity_list = {}\n uri = '{}/{}/runtime/*/entity/*'.format(self.store.aroot, node_uuid)\n response = self.store.actual.resolveAll(uri)\n for i in response:\n rid = i[0]\n en_uuid = rid.split('/')[7]\n if en_uuid not in entity_list:\n entity_list.update({en_uuid:[]})\n if len(rid.split('/')) == 8 and en_uuid in entity_list:\n pass\n if len(rid.split('/')) == 10:\n entity_list.get(en_uuid).append(rid.split('/')[9])\n\n return {node_uuid: entity_list}\n\n entities = {}\n uri = '{}/*/runtime/*/entity/*'.format(self.store.aroot)\n response = self.store.actual.resolveAll(uri)\n for i in response:\n node_id = i[0].split('/')[3]\n elist = self.list(node_id)\n entities.update({node_id: elist.get(node_id)})\n return entities\n\n\n class Image(object):\n '''\n\n This class encapsulates the action on images\n\n\n '''\n def __init__(self, store=None):\n if store is None:\n raise RuntimeError('store cannot be none in API!')\n self.store = store\n\n def add(self, manifest, node_uuid=None):\n '''\n\n Adding an image to a node or to all nodes\n\n :param manifest: dictionary representing the manifest for the image\n :param node_uuid: optional node in which add the image\n :return: boolean\n '''\n manifest.update({'status': 'add'})\n json_data = json.dumps(manifest)\n if node_uuid is None:\n uri = '{}/*/runtime/*/image/{}'.format(self.store.droot, manifest.get('uuid'))\n else:\n uri = '{}/{}/runtime/*/image/{}'.format(self.store.droot, node_uuid, manifest.get('uuid'))\n res = self.store.desired.put(uri, json_data)\n if res:\n return True\n else:\n return False\n\n def remove(self, image_uuid, node_uuid=None):\n '''\n\n remove an image for a node or all nodes\n\n :param image_uuid: image you want to remove\n :param node_uuid: optional node from which remove the image\n :return: boolean\n '''\n\n if node_uuid is None:\n uri = '{}/*/runtime/*/image/{}'.format(self.store.droot, image_uuid)\n else:\n uri = '{}/{}/runtime/*/image/{}'.format(self.store.droot, node_uuid, image_uuid)\n res = self.store.desired.remove(uri)\n if res:\n return True\n else:\n return False\n\n def search(self, search_dict, node_uuid=None):\n pass\n\n class Flavor(object):\n '''\n This class encapsulates the action on flavors\n\n '''\n def __init__(self, store=None):\n if store is None:\n raise RuntimeError('store cannot be none in API!')\n self.store = store\n\n def add(self, manifest, node_uuid=None):\n '''\n\n Add a computing flavor to a node or all nodes\n\n :param manifest: dictionary representing the manifest for the flavor\n :param node_uuid: optional node in which add the flavor\n :return: boolean\n '''\n manifest.update({'status': 'add'})\n json_data = json.dumps(manifest)\n if node_uuid is None:\n uri = '{}/*/runtime/*/flavor/{}'.format(self.store.droot, manifest.get('uuid'))\n else:\n uri = '{}/{}/runtime/*/flavor/{}'.format(self.store.droot, node_uuid, manifest.get('uuid'))\n res = self.store.desired.put(uri, json_data)\n if res:\n return True\n else:\n return False\n\n def remove(self, flavor_uuid, node_uuid=None):\n '''\n\n Remove a flavor from all nodes or a specified node\n\n :param flavor_uuid: flavor to remove\n :param node_uuid: optional node from which remove the flavor\n :return: boolean\n '''\n if node_uuid is None:\n uri = '{}/*/runtime/*/flavor/{}'.format(self.store.droot, flavor_uuid)\n else:\n uri = '{}/{}/runtime/*/flavor/{}'.format(self.store.droot, node_uuid, flavor_uuid)\n res = self.store.desired.remove(uri)\n if res:\n return True\n else:\n return False\n\n def search(self, search_dict, node_uuid=None):\n pass\n\n '''\n Methods\n \n - manifest\n -check\n - node\n - list\n - info\n - plugins\n - search\n - plugin\n - add\n - remove\n - info\n - list\n - search\n - network\n - add\n - remove\n - list\n - search\n - entity\n - add\n - remove\n - define\n - undefine\n - configure\n - clean\n - run\n - stop\n - pause\n - resume\n - migrate\n - search\n - list\n - images\n - add\n - remove \n - search\n - list\n - flavor\n - list\n - add\n - remove\n - search\n\n \n '''\n","sub_path":"fog05/api.py","file_name":"api.py","file_ext":"py","file_size_in_byte":41038,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"186804966","text":"# nox_adb pull\n# /data/data/com.tencent.mm/MicroMsg/87c8969adadf852b441173a366e2be9e/EnMicroMsg.db\n# D:\\Files\\Wechat\n\n# _auth_uin: -658348984\n# IMEI: 866174010501548\n# md5: 9c22ae0bf93a298f8650534459d6ebf3[:7]\n\n\nimport datetime as dt\nimport json\nimport re\nimport sys\n\nfrom pysqlcipher3 import dbapi2 as sqlite\n\npara = [i for i in sys.argv]\n\nDB_PATH = para[1] if len(para) > 1 else 'EnMicroMsg.db'\npwd = '9c22ae0'\nsql = '''\nselect m.createTime, m.content, c.nickname \n from message as m, rcontact as c \n where m.type=49 \n and m.talker in (select chatroomname from chatroom) \n and m.msgId in (select msgId from AppMessage where type=5) \n and m.talkerId=c.rowid;\n'''\n\nconn = sqlite.connect(DB_PATH)\ncurs = conn.cursor()\ncurs.execute(\"PRAGMA key='\" + pwd + \"';\")\ncurs.execute(\"PRAGMA kdf_iter = '4000';\")\ncurs.execute(\"PRAGMA cipher_use_hmac = OFF;\")\ncurs.execute(sql)\n# ret = curs.fetchall()\nret = []\nfor row in curs:\n ret.append({\n \"date\": dt.datetime.fromtimestamp(int(row[0] / 1000)).strftime(\"%Y-%m-%d %H:%M:%S\"),\n # 正则表达式+*后加?表示非贪婪\n \"title\": re.findall('([\\s\\S]*?)<\\/title>', row[1])[0],\n \"url\": re.findall('<url>([\\s\\S]*?)<\\/url>', row[1])[0],\n \"group\": row[2]\n })\n # break\n\n\nconn.close()\n\n# print(ret)\nprint(json.dumps(ret))\n","sub_path":"code/python/wechat.py","file_name":"wechat.py","file_ext":"py","file_size_in_byte":1311,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"186178188","text":"from threading import Thread\nimport GetData as gd\nimport ICP as icp\nimport VisualPoint as vp\n\npoint_cloud = []\ntransfomred = []\n\n# construct the object \nget_data = gd.GetData()\nicp = icp.ICP() \nvisual_point = vp.VisualPoint()\n\ndef save_data():\n global point_cloud, get_data\n point_cloud = get_data.point\n print(point_cloud)\n\ndef run_icp():\n global point_cloud, transfomred, icp\n transfomred = icp.icp_algorithm(point_cloud)\n\ndef render_addpoint():\n global transfomred, visual_point\n visual_point.add_view(transfomred)\n\n\n#visual_point.render()\nwhile True:\n th1 = Thread(target = get_data.capture, args = ())\n th2 = Thread(target = save_data, args = ())\n th3 = Thread(target = run_icp, args = (icp))\n th4 = Thread(target = render_addpoint, args = (visual_point))\n th5 = Thread(target = visual_point.render, args = ())\n th1.start()\n th2.start()\n th3.start()\n th4.start()\n th5.start()\n th1.join()\n th2.join()\n th3.join()\n th4.join()\n th5.join()","sub_path":"ICP_realtime/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":1006,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"504294166","text":"from flask import Flask, request\nfrom flask.json import dumps\nfrom flask.globals import current_app\nfrom sqlalchemy.orm import sessionmaker\nfrom sqlalchemy import create_engine, desc\nimport model\nimport math\n\nMIME_TYPE = 'application/vnd.api+json'\nmodels = {}\nSession = None\n\ndef response(status, *args, **kwargs):\n return current_app.response_class(dumps(dict(*args, **kwargs), indent=None if request.is_xhr else 2), status=status, mimetype=MIME_TYPE)\n\ndef accessDeniedResponse(method, resource):\n return response(403, {\"error\":\"access denied\"})\n\ndef resultResponse(*args, **kwargs):\n return response(200, *args, **kwargs)\n\nparam_names = set(['include', 'page', 'per_page', 'sort', 'fields'])\n\napp = Flask(__name__)\n\n# GET queries\n@app.route('/<path:path>', methods=['GET', 'DELETE'])\ndef handle(path):\n \"\"\"Handle resources requested as per JSONAPI\n \"\"\"\n filters = {k:v for k,v in request.args.items() if k not in param_names}\n resources = path.split('/')\n if request.method == 'GET':\n # custom pagination implementation\n per_page = int(request.args.get('per_page', '100'))\n page = int(request.args.get('page', '1'))\n includes = [] if 'include' not in request.args else request.args['include'].split(',')\n sorts = [] if 'sort' not in request.args else request.args['sort'].split(',')\n fields = [] if 'fields' not in request.args else request.args['fields'].split(',')\n\n # resources\n session = Session()\n name = resources.pop(0)\n cls = models.get(name)\n if not cls:\n return accessDeniedResponse(request.method, name)\n query = session.query(cls)\n if resources:\n # specific id(s)\n ids = resources.pop(0).split(',')\n query = query.filter(cls.id.in_(ids))\n if resources:\n if resources.pop(0) == \"links\":\n links_name = resources.pop(0)\n cls = getattr(cls, links_name).property.argument.class_\n if not cls:\n return accessDeniedResponse(request.method, links_name)\n query = session.query(cls).join(query.subquery())\n\n # add filter\n if filters:\n query = query.filter(*[getattr(cls, k) == v for k,v in filters.items()])\n\n # pagination?\n if request.method == 'GET':\n total = query.count()\n meta = {'total': total, 'pages': math.ceil(total / per_page)}\n\n # sort\n if sorts:\n query = query.order_by(*[desc(sort[1:]) if sort.startswith('-') else sort for sort in sorts])\n\n # run query\n start = (page - 1) * per_page\n stop = page * per_page\n query = query.slice(start, stop)\n\n # run query\n resources = query.all()\n for resource in resources:\n if not resource.allow(request.method):\n return accessDeniedResponse(request.method, resource)\n\n if request.method == 'GET':\n # linked resources\n linked = {}\n for include in includes:\n include_cls = getattr(cls, include).property.argument\n include_query = session.query(include_cls).join(query.subquery())\n include_resources = include_query.all()\n\n # security check\n for resource in include_resources:\n if not resource.allow(request.method):\n return accessDeniedResponse(request.method, resource)\n linked[include] = [resource.to_dict() for resource in include_resources]\n\n # respond\n resources = [resource.to_dict() for resource in resources]\n if len(resources) == 1:\n resources = resources[0]\n result = {cls.__name__: resources, 'linked': linked, 'meta': meta}\n elif request.method == 'DELETE':\n query.delete()\n result = {}\n session.commit()\n return resultResponse(**result)\n\n\n# POST inserts\n@app.route('/<name>', methods=['POST'])\ndef post(name):\n cls = models.get(name)\n values = request.get_json(force=True)[name]\n resources = [cls.from_dict(value) for value in values]\n\n # security check\n for resource in resources:\n if not resource.allow(request.method):\n return accessDeniedResponse(request.method, resource)\n\n session = Session()\n session.insert(cls, values=values)\n session.commit()\n\n\ndef prep(dbpath):\n # prep database\n engine = create_engine(dbpath)\n model.Model.prepare(engine, reflect=True, name_for_collection_relationship=lambda base, local_cls, referred_cls, constraint: referred_cls.__name__.lower())\n global Session\n Session = sessionmaker(bind=engine)\n global models\n models = {model.__name__:model for model in model.Model.__subclasses__()}\n\n","sub_path":"server.py","file_name":"server.py","file_ext":"py","file_size_in_byte":4635,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"344625571","text":"import subprocess\nimport codecs\nimport math\nimport os,sys\nfrom pathlib import Path\nfrom tqdm import tqdm\ntry:\n CUDA_PREFIX = os.environ['CUDA_PREFIX']\nexcept:\n print('No CUDA_PREFIX set, set it to /usr/local/cuda/')\n CUDA_PREFIX=\"/usr/local/cuda/\"\ndef build_switch(H,W):\n R = 3\n S = 3\n Ho = H - (R-1)\n Wo = W - (S-1)\n template = '\\t\\tcase {}:\\n\\t\\t\\t#pragma unroll\\n\\t\\t\\tfor ( int r = {}; r < {}; r++) {{\\n\\t\\t\\t\\t#pragma unroll\\n\\t\\t\\t\\tfor ( int s = {}; s < {}; s++) {{' \\\n '\\n\\t\\t\\t\\t\\tfloat result = v * temp_kernel[r*S+s];\\n\\t\\t\\t\\t\\ttemp_result[({}-r)*{}+({}-s)] += result;\\n\\t\\t\\t\\t}}\\n\\t\\t\\t}}\\n\\t\\tbreak;\\n'\n line = '__device__ void switch_function( unsigned int switch_condition,float *temp_kernel,float v,float *temp_result){\\n' \\\n '\\tswitch (switch_condition) {\\n'\n for h in range(H):\n for w in range(W):\n r_end = R\n s_end = S\n id = h*W+w\n r_start_condition = (h - Ho + 1)\n r_end_condition = (h+1)\n s_start_condition = (w - Wo + 1)\n s_end_condition = (w+1)\n r_end = min(r_end,r_end_condition)\n r_start = max(0,r_start_condition)\n s_end = min(s_end,s_end_condition)\n s_start = max(0,s_start_condition)\n case_line = template.format(id,r_start,r_end,s_start,s_end,h,(Wo),w)\n line +=case_line\n line += '\\n\\t}'\n line += '\\n}'\n return line\ndef generate_code(N,C,H,W,TC,TH,TW):\n func_reader = codecs.open('template.cu','r','utf-8')\n switch_func_lines = build_switch(TH+2,TW+2)\n func_lines = func_reader.readlines()\n content = ''\n for line in func_lines:\n content += line\n content = content.replace('#define TH place holder', '#define TH {}'.format(TH))\n content = content.replace('#define TW place holder', '#define TW {}'.format(TW))\n content = content.replace('#define TC place holder', '#define TC {}'.format(TC))\n content = content.replace('#define H place holder', '#define H {}'.format(H))\n content = content.replace('#define W place holder', '#define W {}'.format(W))\n content = content.replace('#define C place holder', '#define C {}'.format(C))\n content = content.replace('#define N place holder', '#define N {}'.format(N))\n #switch_function_place_holder\n content = content.replace('switch_function_place_holder', switch_func_lines)\n writter = codecs.open('temp.cu','w','utf-8')\n writter.write(content)\n writter.close()\n\nif __name__ == '__main__':\n shape_list = [(64,32,224,224),\n (64,32,112,112),\n (32,32,56,56),\n (64,32,56,56),\n (64,64,56,56),\n (32,32,28,28),\n (64,32,28,28),\n (96,64,28,28),\n (160,96,28,28),\n (192,96,28,28),\n (32,32,14,14),\n (64,32,14,14),\n (128,96,14,14),\n (192,96,14,14),\n (32,32,7,7),\n (64,32,7,7),\n (96,64,7,7),\n (192,160,7,7)]\n ths = [1,2,3,4,5,6,7,8,9,10,11,12]\n tws = [1,2,3,4,5,6,7,8,9,10,11,12]\n tcs = [1,2,4,8,16,32]\n for shape in shape_list:\n c = shape[0]\n n = shape[1]\n h = shape[2]\n w = shape[3]\n blk_dim = ((n - 1)//32 + 1) * 32\n for th in ths:\n if th >= h:\n continue\n for tw in tws:\n if tw>= h:\n continue\n for tc in tcs:\n if tc>=c:\n continue\n generate_code(n,c,h,w,tc,th,tw)\n exc_file = './conv'\n subprocess.run(\n [\"nvcc\", \"-std=c++11\", \"-O3\", \"-I\", CUDA_PREFIX + \"include\", \"-L\",\n CUDA_PREFIX + \"lib64\", \"-L\", CUDA_PREFIX + \"lib\", 'temp.cu', \"-o\",\n exc_file, \"-lcudnn\", \"-Xcompiler\", \"-fopenmp\" ])\n subprocess.run([exc_file])","sub_path":"A100-evaluation/Gen-occupancy/gen.py","file_name":"gen.py","file_ext":"py","file_size_in_byte":4068,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"207016994","text":"import ipywidgets as widgets\nfrom traitlets import Unicode, Bool, validate, TraitError, Int, List, Dict, Float\nimport asyncio\nimport re as _re\nimport os\nimport time as _time\nimport copy\nfrom datetime import datetime\nimport json\n\n\ndef pause(delay = 1.0):\n \"\"\"Pause for delay seconds.\"\"\"\n _time.sleep(delay)\n\n_directions = [ (0, 1), (-1, 0), (0, -1), (1, 0) ]\n_orient_dict = { 'E': 3, 'S': 2, 'W': 1, 'N': 0}\n\n\nclass _Beeper(object):\n \"\"\"One ore more beepers at a crossing in the world.\"\"\"\n def __init__(self, world, radius, av, st, num = 1):\n self.av = av\n self.st = st\n self.num = num\n self.world = world\n\n def set_number(self, num):\n self.num = num\n # self.world.update_beeper(self)\n\n\nclass Robot(object):\n def init(self, world, avenue = 1, street = 1, orientation = 'E', beepers = 0, index = 0):\n self._dir = _orient_dict[orientation]\n self._x = avenue\n self._y = street\n self._beeper_bag = beepers\n self._flag_bag = 0\n self._trace = True\n self._delay = 0\n self._steps = 0\n self.my_index = index\n self.world = world\n self._update_pos()\n \n def _update_pos(self):\n x, y = self.world.cr2xy(2 * self._x - 1, 2 * self._y - 1)\n self.world.move_to(self.my_index, x,y)\n\n def _trace_pos(self):\n x, y = self.world.cr2xy(2 * self._x - 1, 2 * self._y - 1)\n xr, yr = _directions[(self._dir - 1) % 4]\n xb, yb = _directions[(self._dir - 2) % 4]\n return x + 5 * (xr + xb), y - 5 * (yr + yb)\n \n def _update_trace(self):\n if self._trace:\n x, y = self._trace_pos()\n self.world.add_point(self.my_index, x,y)\n \n def set_trace(self, color = None):\n \"\"\"Without color argument, turn off tracing.\n With color argument, start a new trace in that color.\"\"\"\n if not color:\n if self._trace:\n self.world.remove_trace(self.my_index)\n self._trace = None\n else:\n self._trace = True\n x, y = self._trace_pos()\n self.world.set_trace(self.my_index, x, y, color)\n # self._trace = _g.Path([_g.Point(x, y)])\n # self._trace.setBorderColor(color)\n # _scene.add(self._trace)\n\n def set_pause(self, delay = 0):\n \"\"\"Set a pause to be made after each move.\"\"\"\n self._delay = delay\n self.world.set_pause(self.my_index, delay)\n\n def get_pos(self):\n \"\"\"Returns current robot position.\"\"\"\n return self._x, self._y\n \n def turn_left(self):\n \"\"\"Rotate left by 90 degrees.\"\"\"\n # self._image[self._dir].moveTo(-100, -100)\n self.world.rotate_left(self.my_index)\n self._dir = (self._dir + 1) % 4\n self._update_pos()\n self._update_trace()\n\n def _move(self):\n if self.front_is_clear():\n xx, yy = _directions[self._dir]\n self._x += xx\n self._y += yy\n self._update_pos()\n self._update_trace() \n\n def move(self, step=1):\n \"\"\"Move one street/avenue in direction where robot is facing.\"\"\"\n for x in range(step):\n self._move()\n\n\n \n\n def front_is_clear(self):\n \"\"\"Returns True if no wall or border in front of robot.\"\"\"\n col = 2 * self._x - 1\n row = 2 * self._y - 1\n xx, yy = _directions[self._dir]\n return self.world.is_clear(col + xx, row + yy)\n\n def left_is_clear(self):\n \"\"\"Returns True if no walls or borders are to the immediate left\n of the robot.\"\"\"\n col = 2 * self._x - 1\n row = 2 * self._y - 1\n xx, yy = _directions[(self._dir + 1) % 4]\n return self.world.is_clear(col + xx, row + yy)\n\n def right_is_clear(self):\n \"\"\"Returns True if no walls or borders are to the immediate right\n of the robot.\"\"\"\n col = 2 * self._x - 1\n row = 2 * self._y - 1\n xx, yy = _directions[(self._dir - 1) % 4]\n return self.world.is_clear(col + xx, row + yy)\n\n def facing_north(self):\n \"\"\"Returns True if Robot is facing north.\"\"\"\n return (self._dir == 0)\n\n def carries_beepers(self):\n \"\"\"Returns True if some beepers are left in Robot's bag.\"\"\"\n return (self._beeper_bag > 0)\n \n def on_beeper(self):\n \"\"\"Returns True if beepers are present at current robot position.\"\"\"\n return ((self._x, self._y) in self.world.beepers)\n \n def on_flag(self):\n return ((self._x, self._y) in self.world.flags)\n\n def pick_beeper(self):\n \"\"\"Robot picks one beeper up at current location.\"\"\"\n if self.on_beeper():\n self.world.remove_beeper(self._x, self._y)\n self._beeper_bag += 1\n \n def pick_flag(self):\n if self.on_flag():\n self.world.remove_flag(self._x, self._y)\n self._flag_bag +=1\n\n def drop_flag(self):\n if self.carries_flags():\n self._flag_bag -= 1\n self.world.add_flag(self._x, self._y)\n \n def flags_count(self):\n return self._flag_bag\n \n def carries_flags(self):\n return (self._flag_bag > 0)\n\n def drop_beeper(self):\n \"\"\"Robot drops one beeper down at current location.\"\"\"\n if self.carries_beepers():\n self._beeper_bag -= 1\n self.world.add_beeper(self._x, self._y)\n\ndef _check_world(contents):\n # safety check\n safe = contents[:]\n # only allow known keywords\n keywords = [\"avenues\", \"streets\", \"walls\", \"beepers\", \"robot\",\"flags\",\n \"'s'\", \"'S'\", '\"s\"', '\"S\"',\n \"'e'\", \"'E'\", '\"e\"', '\"E\"',\n \"'w'\", \"'W'\", '\"w\"', '\"W\"',\n \"'n'\", \"'N'\", '\"n\"', '\"N\"', ]\n for word in keywords:\n safe = safe.replace(word, '')\n safe = list(safe)\n for char in safe:\n if char.isalpha():\n raise ValueError(\"Invalid word or character in world file\")\n\n\ndef load_world(filename):\n txt = open(filename, 'r').read()\n txt = _re.sub('\\r\\n', '\\n', str(txt))\n txt = _re.sub('\\r', '\\n', str(txt))\n _check_world(txt)\n try:\n robot = None\n wd = locals()\n exec(txt, globals(), wd)\n\n w = Maze(\n avenues= wd[\"avenues\"], \n walls= wd[\"walls\"], \n beepers= wd.get(\"beepers\", {}), \n streets= wd[\"streets\"],\n robot=wd[\"robot\"],\n flags=wd.get(\"flags\", []))\n return w\n except:\n raise ValueError(\"Error interpreting world file.\")\n\n\n@widgets.register\nclass Maze(widgets.DOMWidget):\n\n # Name of the widget view class in front-end\n _view_name = Unicode('MazeView').tag(sync=True)\n # Name of the widget model class in front-end\n _model_name = Unicode('MazeModel').tag(sync=True)\n _view_module = Unicode('ttgtcanvas').tag(sync=True)\n\n # Name of the front-end module containing widget model\n _model_module = Unicode('ttgtcanvas').tag(sync=True)\n\n _view_module_version = Unicode('^0.3.0').tag(sync=True)\n # Version of the front-end module containing widget model\n _model_module_version = Unicode('^0.3.0').tag(sync=True)\n\n current_call = Unicode('{}').tag(sync=True)\n method_return = Unicode('{}').tag(sync=True)\n\n\n def js_call(self, method_name, params): \n # print(\"calling method: \" + method_name)\n cb = datetime.now().strftime('%f')\n self.current_call = json.dumps({'method_name': method_name, 'params': params, 'cb': cb})\n\n \n def __init__(self, **kwargs):\n super(Maze, self).__init__(**kwargs)\n options = {\"avenues\": 10, \"streets\": 10, \"beepers\": {}, \"walls\": [], \"robot\": (8, 1, 'E', 0), \"flags\": []}\n options.update(kwargs)\n\n self._beepers = options[\"beepers\"]\n self._flags = options[\"flags\"]\n self.av = options[\"avenues\"]\n self.st = options[\"streets\"]\n self.robot = options[\"robot\"] \n self.width = self.av * 50\n self.height = self.st * 50\n self.num_cols = 2*self.av + 1\n self.num_rows = 2*self.st + 1\n self.walls = options[\"walls\"]\n self._bot = None\n for (col, row) in self.walls:\n if not (col+row) % 2:\n raise RuntimeError(\"Wall in impossible position (%d, %d).\" % (col,row))\n self.borders = []\n self.set_borders()\n \n display(self)\n _time.sleep(1)\n\n self.init()\n\n def set_borders(self):\n \"\"\"The world is surrounded by a continuous wall. This function\n sets the corresponding \"wall\" or \"border\" based on the world's\n dimensions.\"\"\"\n for col in range(1, self.num_cols-1, 2):\n if (col, 0) not in self.borders:\n self.borders.append( (col, 0) )\n if (col, self.num_rows) not in self.borders:\n self.borders.append( (col, self.num_rows-1) )\n for row in range(1, self.num_rows-1, 2):\n if (0, row) not in self.borders:\n self.borders.append( (0, row) )\n if (self.num_cols, row) not in self.borders:\n self.borders.append( (self.num_cols-1, row) )\n \n def cr2xy(self, col, row):\n x = self.left + self.ts * col\n y = self.bottom - self.ts * row\n return x, y\n \n def toggle_wall(self, col, row):\n \"\"\"This function is intended for adding or removing a\n wall from a GUI world editor.\"\"\"\n if (col+row) % 2 : # safety check\n if (col, row) in self.walls: # toggle value\n self.walls.remove((col, row))\n else:\n self.walls.append((col, row))\n else:\n raise RuntimeError(\"Wall in impossible position (%d, %d).\" % (col,row))\n\n def is_clear(self, col, row):\n \"\"\"Returns True if there is no wall or border here.\"\"\"\n return not ((col, row) in self.walls or (col, row) in self.borders)\n \n def _create_beeper(self, av, st):\n num = self.beepers[(av, st)]\n bp = _Beeper(self, 0.6 * self.ts, av, st, num)\n self.beeper_icons[(av, st)] = bp\n return bp\n \n\n\n def init(self, src='./robot-design.svg'):\n self.beepers = self._beepers.copy()\n self.flags = self._flags.copy()\n self.total_flags = self.flags_count()\n self.total_beepers = self.beepers_count()\n self.beeper_icons = {}\n tsx = self.width / (self.num_cols + 2)\n tsy = self.height / (self.num_rows + 2)\n self.ts = min(tsx, tsy)\n self.left = 2 * self.ts\n self.right = self.left + 2 * self.ts * self.av\n self.bottom = self.height - 2 * self.ts\n self.top = self.bottom - 2 * self.ts * self.st\n\n\n #UI Add layer\n ##Add Beepers\n _beepers = []\n for (av, st) in self.beepers:\n _beeper = self._create_beeper(av, st)\n _beepers.append({'key':[av, st], 'value': _beeper.num})\n \n self.js_call('draw_grid', [self.width, self.height, self.av, self.st, self.ts, self.walls, _beepers, self.flags, self.robot])\n\n self.init_robot(src)\n # add_robot\n return self\n\n def move_to(self, rindex , x, y):\n self.js_call('move_to', [rindex, x,y])\n _time.sleep(0.1)\n if self._bot.on_flag():\n self._bot.pick_flag()\n\n def add_point(self, rindex , x, y):\n self.js_call('add_point', [rindex, x,y])\n \n ##init robot\n def init_robot(self, src):\n avenue, street, orientation, beepers = self.robot\n self.js_call('add_robot', [0, src, avenue, street,orientation, beepers])\n self._bot = self._bot or Robot()\n self._bot.init(self, avenue, street, orientation, beepers, 0)\n self.js_call('init_robot', [0])\n self._bot._update_pos()\n return self._bot\n\n def bot(self):\n return self._bot\n\n def remove_trace(self, rindex):\n self.js_call(\"remove_trace\", [rindex])\n \n def set_pause(self, rindex, delay):\n self.js_call('set_pause', [rindex, delay])\n \n def set_trace(self, rindex, x,y, color):\n self.js_call('set_trace', [rindex, x, y, color])\n \n def set_number(self, beeper):\n self.js_call('set_beeper_number', [beeper.av, beeper.st, beeper.num])\n\n def rotate_left(self, rindex):\n self.js_call('rotate_left', [rindex])\n\n def beepers_count(self):\n return len(self.beepers)\n\n def flags_count(self):\n return len(self.flags)\n \n def check(self):\n ret = (self.beepers_count() == 0) and (self.flags_count() == 0)\n if ret == True:\n self.js_call('success_msg', [\"Congrats, Task Completed.\"])\n else:\n self.js_call('failed_msg', [\"Oops, Task Failed.\"])\n return ret\n\n def add_beeper(self, av, st):\n x, y = self.cr2xy(2 * av - 1, 2 * st - 1)\n \"\"\"Add a single beeper.\"\"\"\n if (av, st) in self.beepers:\n self.beepers[(av, st)] += 1\n bp = self.beeper_icons[(av,st)]\n bp.set_number(self.beepers[(av, st)])\n self.js_call('update_beeper', [av, st, self.beepers[(av, st)]])\n else:\n self.beepers[(av, st)] = 1\n self._create_beeper(av, st)\n self.js_call('add_beeper', [av, st, x, y, self.beepers[(av, st)]])\n\n def remove_beeper(self, av, st):\n \"\"\"Remove a beeper (does nothing if no beeper here).\"\"\"\n x, y = self.cr2xy(2 * av - 1, 2 * st - 1)\n \n if (av, st) in self.beepers:\n self.beepers[(av, st)] -= 1\n if self.beepers[(av, st)] == 0:\n del self.beepers[(av, st)]\n del self.beeper_icons[(av,st)]\n self.js_call('remove_beeper', [av, st])\n else:\n bp = self.beeper_icons[(av,st)]\n bp.set_number(self.beepers[(av, st)])\n self.js_call('update_beeper', [av, st, self.beepers[(av, st)]])\n \n\n def remove_flag(self, av, st):\n if (av, st) in self.flags:\n _flag_index = self.flags.index((av, st))\n self.flags.pop(_flag_index)\n self.js_call('remove_flag', [av, st])\n \n def add_flag(self, av, st):\n x, y = self.cr2xy(2 * av - 1, 2 * st - 1)\n if not ((av, st) in self.flags):\n self.flags.append((av, st))\n self.js_call('add_flag', [av, st, x, y])\n","sub_path":"ttgtcanvas/modules/maze.py","file_name":"maze.py","file_ext":"py","file_size_in_byte":14331,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"462232994","text":"\"\"\"\nFikri Ghazi\nCIS177\nJune 24, 2016\n\nProgram: Fizbiz\nDescription: A Tkinter game about finding a match for an unknown card.\n And here's the game diagram:\n\n Main Window _______________________________\n | [X] | = Frame-1\n | GUESS THE CARD! | = Frame-1\n | |\n | [3] [4] [A] [5] [7] [K] [3] [Q] [8] [J] | = Frame-2\n | _________ ____ |\n | Player_1: Bot: | = Frame-3\n | 15 20 | = Frame-3\n | RESET GAME | = Frame-footer\n |_________________________________________|\n\"\"\"\n\nfrom tkinter import *\nfrom tkinter import messagebox\nimport random\nfrom player import Player\n\n\nclass FizbizGUI:\n N_CARDS = 10 # number of side-up cards\n MAX_SCORE = 7\n\n def __init__(self):\n\n \"\"\" #######################################################################\n Game setup:\n - Create game's main window\n - Create game's main UI containers: Frame-1, Frame-2, Frame-3, Frame-footer\n \"\"\"\n\n # Create the main Window for this GUI called mainWindow\n self.__mainWindow = Tk()\n self.__mainWindow.configure(background=\"white\", borderwidth=50)\n self.__mainWindow.title(\"Fizbiz\")\n\n # Create Frames\n frame_1 = Frame(self.__mainWindow)\n frame_2 = Frame(self.__mainWindow)\n frame_3 = Canvas(self.__mainWindow, bg='red')\n\n frame_footer = Frame(self.__mainWindow)\n\n # Attach frames to the game's main-window\n frame_1.pack()\n frame_2.pack()\n frame_3.pack(fill=BOTH, expand=1)\n frame_footer.pack()\n\n \"\"\" #######################################################################\n Game setup Pt.2:\n Setup game's attributes\n \"\"\"\n\n ## Store PhotoImages to make Labels of cards ---------------------------\n\n self.__deckOfCards_imgs = [] # Create an empty array then,\n\n # Append 52 PhotoImages of cards into array\n for i in range(52):\n self.__deckOfCards_imgs.append( PhotoImage(file=\"cards_gif/\"+str(i+1)+\".gif\") )\n random.shuffle(self.__deckOfCards_imgs)\n\n # Create a PhotoImage of a closed-card\n self.__closedCard_img = PhotoImage(file=\"cards_gif/b1fv.gif\")\n\n ## Store Labels -------------------------------------------------------\n\n self.__deckOfCards_lbls = [] # Create an empty array to store Labels then,\n\n # Append 52 Labels of cards into the array\n for i in range(52):\n self.__deckOfCards_lbls.append( Label(frame_2, image=self.__deckOfCards_imgs[i]) )\n\n # Create a Label of a closed card\n self.__unknownCard_lbl = Label(frame_1, image=self.__closedCard_img)\n\n # Create answer to the unknown card\n self.__unknownCardAnswer_lbl = self.__deckOfCards_lbls[random.randint(0,self.N_CARDS-1)]\n\n # Track whether the unknown card is open or closed\n self.__isUnknownCardOpen = False\n\n # Track whether the unknown card is found or not\n self.isUnknownCardFound = False\n\n \"\"\" #######################################################################\n frame_1: contains a closed-card Label and a text Label\n \"\"\"\n\n # Create text Label which will appear at the initial state of the game\n self.__gameGreeting = Label(frame_1, text=\"-\\nGUESS THE CARD!\\n\", font=(\"Helvetica\", 32))\n\n # Populate frame_1 with widgets\n self.__unknownCard_lbl.pack()\n self.__gameGreeting.pack()\n\n # When the unknown card is clicked, then open the card\n self.__unknownCard_lbl.bind(\"<Button-1>\", self.__openTheUnknownCard)\n\n \"\"\" #######################################################################\n frame_2: contains n open cards, where n is the constant value of N_CARDS\n \"\"\"\n\n # Populate n Labels of cards into Frame 2\n for i in range(self.N_CARDS):\n\n self.__deckOfCards_lbls[i].grid(row=0, column=i)\n\n # When an open card is clicked, then check if the card is a match\n self.__deckOfCards_lbls[i].bind(\"<Button-1>\", self.__checkGuessedCard)\n\n \"\"\" #######################################################################\n frame_3: contains the scoreboard of two players\n \"\"\"\n\n # Create frame_3 children frames\n frame_3_1_left = Frame(frame_3, width=1, height=1, bd=40)\n frame_3_1_right = Frame(frame_3, width=1, height=1, bd=40)\n\n # Create 2 players\n self.__Yoda = Player(name=\"YODA\", score=self.MAX_SCORE, turn=True)\n self.__Robot = Player(name=\"R2D2\", score=self.MAX_SCORE)\n\n # Create Yoda's box score ---------------------------------\n self.Yoda_lbl = Label(frame_3_1_left,\n text = self.__Yoda.getPlayersName(),\n font = (\"Helvetica\", 24),\n )\n self.YodasScore_lbl = Label(frame_3_1_left,\n text=self.__Yoda.getPlayersScores(),\n font=(\"Helvetica\", 24)\n )\n\n # Create R2D2's box score ---------------------------------\n self.Robot_lbl = Label(frame_3_1_right,\n text = self.__Robot.getPlayersName(),\n font = (\"Helvetica\", 24),\n #bg=\"blue\"\n )\n self.RobotsScore_lbl = Label(frame_3_1_right,\n text=self.__Robot.getPlayersScores(),\n font=(\"Helvetica\", 24)\n )\n\n # Attach box-scores to frame_3 children frames\n self.Yoda_lbl.pack()\n self.YodasScore_lbl.pack()\n self.Robot_lbl.pack()\n self.RobotsScore_lbl.pack()\n\n # Attach frame_3's childern frames to frame_3\n frame_3_1_left.pack(fill=BOTH, side=LEFT, expand=True)\n frame_3_1_right.pack(fill=BOTH, side=LEFT, expand=True)\n\n # Set Yoda to always be the first player.\n if self.__Yoda.isTurn:\n self.__changeBackgroundColor(self.Yoda_lbl, \"yellow\")\n\n \"\"\" #######################################################################\n frame_footer: only contains the reset button\n \"\"\"\n\n # Create and attach the button to frame_footer\n reset_btn = Button(frame_footer, text=\"RESET GAME\", command=self.__resetGame)\n reset_btn.pack()\n\n ## loop the game ##########################\n self.__mainWindow.mainloop()\n\n # End of initializer\n\n \"\"\"\n FizbizGUI private functions: -----------------------------------------------------------------------\n \"\"\"\n\n def __checkGuessedCard(self, event):\n # Print to Console for testing\n print(\"__checkGuessedCard() is called:\")\n\n self.isUnknownCardFound = True if event.widget == self.__unknownCardAnswer_lbl else False\n\n # Show feedback to user everytime he/she tries to match a card\n self.__showFeedback(self.isUnknownCardFound)\n\n # If Yoda Found the card, prompt a congrats message\n if self.__Yoda.isTurn and self.isUnknownCardFound:\n self.__openTheUnknownCard(event)\n messagebox.showinfo(\"CONGRATULATIONS\", \"YODA WINS\\nGAME OVER\")\n\n # If Yoda could not find the card, then subtract his score and let R2D2 play\n elif self.__Yoda.isTurn and self.isUnknownCardFound==False:\n self.__Yoda.subtractScores(pt=1)\n self.YodasScore_lbl[\"text\"] = self.__Yoda.getPlayersScores()\n self.__Yoda.isTurn = False\n self.__Robot.isTurn = True\n self.__changeBackgroundColor(self.Yoda_lbl, \"white\")\n self.__changeBackgroundColor(self.Robot_lbl, \"PaleTurquoise1\")\n\n # If RT2D2 Found the card, prompt a congrats message\n elif self.__Robot.isTurn and self.isUnknownCardFound:\n self.__openTheUnknownCard(event)\n messagebox.showinfo(\"CONGRATULATIONS\", \"R2D2 WINS.\\nGAME OVER\")\n\n # If R2D2 could not find the card, then subtract his score and let YODA play\n elif self.__Robot.isTurn and self.isUnknownCardFound==False:\n self.__Robot.subtractScores(pt=1)\n self.RobotsScore_lbl[\"text\"] = self.__Robot.getPlayersScores()\n self.__Robot.isTurn = False\n self.__Yoda.isTurn = True\n self.__changeBackgroundColor(self.Yoda_lbl, \"yellow\")\n self.__changeBackgroundColor(self.Robot_lbl, \"white\")\n\n def __openTheUnknownCard(self, event):\n # Print to Console for testing\n print(\"__openTheUnknownCard() is called:\")\n print(self.__unknownCard_lbl[\"image\"], self.__unknownCardAnswer_lbl[\"image\"])\n\n self.__isUnknownCardOpen = True\n print(\"isUnknownCardOpen=\", self.__isUnknownCardOpen)\n\n # Open the card\n self.__unknownCard_lbl[\"image\"] = self.__unknownCardAnswer_lbl[\"image\"]\n\n def __showFeedback(self, isUnknownCardFound):\n nopeMsgs = [\"NOPE\", \"VERY CLOSE\", \"ALMOST\", \"TRY AGAIN\"]\n yesMsgs = [\"YAHOO!!!\", \"WOHOOO\", \"THERE YOU GO!\"]\n\n if isUnknownCardFound == False:\n self.__gameGreeting[\"text\"] = \"-\\n\" + nopeMsgs[ random.randint( 1,len(nopeMsgs)-1 ) ] + \"\\n\"\n else:\n self.__gameGreeting[\"text\"] = \"-\\n\" + yesMsgs[random.randint(1, len(yesMsgs) - 1)] + \"\\n\"\n\n def __changeBackgroundColor(self, widget, color):\n widget[\"bg\"] = color\n\n def __resetGame(self):\n self.__mainWindow.destroy()\n self.__init__()\n\n\nFizbizGUI()\n","sub_path":"app/fizbiz.py","file_name":"fizbiz.py","file_ext":"py","file_size_in_byte":9799,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"585932437","text":"import re, pyperclip\n'''\nMoves are always exactly one house to the\nnorth (^), south (v), east (>), or west (<).\nAfter each move,\nhe delivers another present\nto the house at his new location.\n'''\n\ntext = pyperclip.paste()\n\n\nUnique_houses = 0\nx=y=0\nMatrix = {}\nMatrix[x,y] = 1\nfor i in text:\n if i == \"^\":\n\n y += 1\n\n elif i == \"v\":\n\n x -= 1\n\n elif i == \"<\":\n\n y -= 1\n\n elif i == \">\":\n\n x -= 1\n\n Matrix[x,y] = 1\n\nfor i in Matrix:\n Unique_houses += 1\nprint (Unique_houses)\n","sub_path":"adventcode1_3-1py.py","file_name":"adventcode1_3-1py.py","file_ext":"py","file_size_in_byte":516,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"543954725","text":"\"\"\"\n56. 共参照解析\nStanford Core NLPの共参照解析の結果に基づき，文中の参照表現（mention）を代表参照表現\n（representative mention）に置換せよ．ただし，置換するときは，「代表参照表現（参照表現）」\nのように，元の参照表現が分かるように配慮せよ．\n--- 秋山 Note\n<head>は、主幹？、多分 the とかを飛ばした始まり？ で使用せず。\nElement Tree, Stanford Core NLP の使い方等、素人の１００本ノックさん等を参考にした。\nそれを元に、Element Treeの呼び方工夫、デバックの為に文を指定出来るよう、ループの簡素化等の改編\n\n\"\"\"\n# coding: utf-8\n#from collections import defaultdict\n\nimport re\nimport xml.etree.ElementTree as ET\nfrom collections import defaultdict\n\nxml_root = ET.parse('nlp.txt.xml')\n\nbeg = 2\nend = 3\n\nrepre_d = defaultdict(lambda: 0)\n\n\nfor ii, coref in enumerate(xml_root.iterfind('./document/coreference/coreference')):\n if (ii+1 >= beg) and (ii+1 <= end):\n #print(*coref)\n for coref_mem in coref.findall('mention'):\n if coref_mem.get('representative') == 'true':\n rep_word = coref.findtext('./mention/text')\n #print(rep_word)\n #print(coref_mem.get('representative', 'false'))\n else:\n sent_id = int(coref_mem.findtext('sentence'))\n start = int(coref_mem.findtext('start'))\n end = int(coref_mem.findtext('end'))\n\n if repre_d[(sent_id,start)] == 0:\n # use defaultdict, so not check with 'in'\n repre_d[(sent_id,start)] = (end, rep_word)\n #無いなら、辞書型[文番号,開始単語ID]=(終了単語ID,元単語)\n\nfor sentence in xml_root.iterfind('./document/sentences/sentence'):\n sent_id = int(sentence.get('id'))\n #To edit sentence, get sentence itself\n\n if (sent_id >= beg) and (sent_id <= end):\n rep_rest =0\n for token in sentence.iterfind('./tokens/token'):\n token_id = int(token.get('id'))\n\n\n if rep_rest == 0 and (sent_id, token_id) in repre_d:\n #(文番号,単語ID)が、参照先辞書にあるか？\n\n (end, rep_text) = repre_d[(sent_id, token_id)]\n #あれば、終了単語IDと代表参照表現（参照元表現）を取り出す\n\n print('[' + rep_text + '] (', end = '')\n #まず、代表参照表現と括弧達\n rep_rest = end - token_id\n #参照先終了IDXから、開始IDX引いてRepTextに入れる。\n\n\n print(token.findtext('word'), end = '')\n #参照に関係ない所は単語ごとに、文を印刷\n\n if rep_rest > 0:\n rep_rest -= 1\n if rep_rest == 0:\n print(')', end = '')\n #参照元のオリジナル表現の最後に括弧入れる為に、残りを計算\n\n\n print(' ', end = '')\n #単語間の空白\n\n print()\n","sub_path":"kohei4/chapter06/knock56.py","file_name":"knock56.py","file_ext":"py","file_size_in_byte":3113,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"613558224","text":"# Task Overview:\r\n# You have to write a function that accepts three parameters:\r\n#\r\n# cap is the amount of people the bus can hold excluding the driver.\r\n# on is the number of people on the bus excluding the driver.\r\n# wait is the number of people waiting to get on to the bus excluding the driver.\r\n# If there is enough space, return 0, and if there isn't, return the number of passengers he can't take.\r\n#\r\n# Usage Examples:\r\n# cap = 10, on = 5, wait = 5 --> 0 # He can fit all 5 passengers\r\n# cap = 100, on = 60, wait = 50 --> 10 # He can't fit 10 of the 50 waiting\r\n\r\ndef enough(cap, on, wait):\r\n a = cap - on - wait\r\n if a < 0:\r\n return abs(a)\r\n else:\r\n return 0\r\n\r\nprint(enough(10, 5, 5))\r\nprint(enough(100, 60, 50))\r\nprint(enough(20, 5, 5))","sub_path":"Will there be enough space.py","file_name":"Will there be enough space.py","file_ext":"py","file_size_in_byte":770,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"530288104","text":"# a partial order is a set of events together with the causality relation\n# we only store information about direct causality\n\nfrom Exceptions import*\nfrom Relations import *\nfrom Structures import *\n\ndef lpo(E,causality):\n\n lpo={}\n lpo[\"events\"]=E\n lpo[\"cau\"]=causality\n \n return lpo\n\ndef is_lpo(lpo):\n\n try:\n if not (list(lpo.keys())==[\"cau\",\"events\"] or list(lpo.keys())==[\"events\",\"cau\"]):\n raise not_LPO\n \n if not acyclic(lpo[\"cau\"]):\n raise not_Partial_Order\n\n if not diff_events(lpo[\"events\"]):\n raise not_Set_of_Events\n\n if not relation_over_events(lpo[\"cau\"],lpo[\"events\"]):\n raise extra_Event\n \n\n return True\n\n except not_LPO:\n print(\"there are more than events and causality\")\n\n except not_Partial_Order:\n print(\"causality is not acyclic\")\n\n except not_Set_of_Events:\n print(\"some event is defined twice with different labels\")\n\n except extra_Event:\n print(\"some event in causality is not specified\")\n\n return\n\n# it renames all the events (and its appearances in causality) of the LPO\n# adding \"string\" ath the beggining fo the name\ndef rename_lpo(string,target_lpo):\n\n new_lpo=lpo([],[])\n\n for x in target_lpo[\"events\"]:\n new_lpo[\"events\"].append((string + x[0],x[1]))\n \n for x in target_lpo[\"cau\"]:\n new_lpo[\"cau\"].append((string + x[0], string + x[1]))\n\n return new_lpo\n\n# it returns the minimal (w.r.t <) elements of the LPO\ndef minimals(lpo):\n\n is_min={}\n for x in lpo[\"events\"]:\n is_min[x[0]]=True\n\n for (x,y) in lpo[\"cau\"]:\n is_min[y]=False\n\n res=[i for i in is_min.keys() if is_min[i]]\n \n return res\n\n","sub_path":"LPO.py","file_name":"LPO.py","file_ext":"py","file_size_in_byte":1734,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"348828412","text":"\"\"\"\nImplementation of a API specific HTTP service view.\n\"\"\"\n\nimport colander\nfrom ipaddress import ip_address\nimport simplejson as json\n\nfrom ichnaea.api.exceptions import (\n DailyLimitExceeded,\n InvalidAPIKey,\n ParseError,\n)\nfrom ichnaea.api.rate_limit import rate_limit_exceeded\nfrom ichnaea.exceptions import GZIPDecodeError\nfrom ichnaea.models.api import ApiKey\nfrom ichnaea.models.constants import VALID_APIKEY_REGEX\nfrom ichnaea import util\nfrom ichnaea.webapp.view import BaseView\n\n\nclass BaseAPIView(BaseView):\n \"\"\"Common base class for all API related views.\"\"\"\n\n check_api_key = True # Should API keys be checked?\n error_on_invalidkey = True # Deny access for invalid API keys?\n metric_path = None # Dotted URL path, for example v1.submit.\n schema = None # An instance of a colander schema to validate the data.\n view_type = None # The type of view, for example submit or locate.\n\n def __init__(self, request):\n super(BaseAPIView, self).__init__(request)\n self.raven_client = request.registry.raven_client\n self.redis_client = request.registry.redis_client\n self.stats_client = request.registry.stats_client\n\n def log_unique_ip(self, valid_key):\n addr = self.request.client_addr\n if isinstance(addr, bytes): # pragma: no cover\n addr = addr.decode('ascii')\n try:\n ip = str(ip_address(addr))\n except ValueError: # pragma: no cover\n ip = None\n if ip:\n redis_key = 'apiuser:{api_type}:{api_key}:{date}'.format(\n api_type=self.view_type,\n api_key=valid_key,\n date=util.utcnow().date().strftime('%Y-%m-%d'),\n )\n with self.redis_client.pipeline() as pipe:\n pipe.pfadd(redis_key, ip)\n pipe.expire(redis_key, 691200) # 8 days\n pipe.execute()\n\n def log_count(self, valid_key, log_ip):\n if valid_key is None:\n valid_key = 'none'\n\n self.stats_client.incr(\n self.view_type + '.request',\n tags=['path:' + self.metric_path,\n 'key:' + valid_key])\n\n if self.request.client_addr and log_ip:\n try:\n self.log_unique_ip(valid_key)\n except Exception: # pragma: no cover\n self.raven_client.captureException()\n\n def check(self):\n api_key = None\n api_key_text = self.parse_apikey()\n skip_check = False\n\n if api_key_text is None:\n self.log_count(None, False)\n if self.error_on_invalidkey:\n raise self.prepare_exception(InvalidAPIKey())\n\n if api_key_text is not None:\n try:\n session = self.request.db_session\n api_key = ApiKey.get(session, api_key_text)\n except Exception:\n # if we cannot connect to backend DB, skip api key check\n skip_check = True\n self.raven_client.captureException()\n\n if api_key is not None and api_key.allowed(self.view_type):\n self.log_count(api_key.valid_key, True)\n\n rate_key = 'apilimit:{key}:{path}:{time}'.format(\n key=api_key_text,\n path=self.metric_path,\n time=util.utcnow().strftime('%Y%m%d')\n )\n\n should_limit = rate_limit_exceeded(\n self.redis_client,\n rate_key,\n maxreq=api_key.maxreq\n )\n\n if should_limit:\n raise self.prepare_exception(DailyLimitExceeded())\n elif skip_check:\n pass\n else:\n if api_key_text is not None:\n self.log_count('invalid', False)\n if self.error_on_invalidkey:\n raise self.prepare_exception(InvalidAPIKey())\n\n # If we failed to look up an ApiKey, create an empty one\n # rather than passing None through\n api_key = api_key or ApiKey(valid_key=None,\n allow_fallback=False,\n allow_locate=True,\n allow_transfer=False,\n store_sample_locate=100,\n store_sample_submit=100)\n return self.view(api_key)\n\n def parse_apikey(self):\n try:\n api_key_text = self.request.GET.get('key', None)\n except Exception: # pragma: no cover\n api_key_text = None\n # check length against DB column length and restrict\n # to a known set of characters\n if (api_key_text and (3 < len(api_key_text) < 41) and\n VALID_APIKEY_REGEX.match(api_key_text)):\n return api_key_text\n return None\n\n def preprocess_request(self):\n errors = []\n\n request_content = self.request.body\n if self.request.headers.get('Content-Encoding') == 'gzip':\n # handle gzip self.request bodies\n try:\n request_content = util.decode_gzip(self.request.body)\n except GZIPDecodeError as exc:\n errors.append({'name': None, 'description': repr(exc)})\n\n request_data = {}\n try:\n request_data = json.loads(\n request_content, encoding=self.request.charset)\n except ValueError as exc:\n errors.append({'name': None, 'description': repr(exc)})\n\n validated_data = {}\n try:\n validated_data = self.schema.deserialize(request_data)\n except colander.Invalid as exc:\n errors.append({'name': None, 'description': exc.asdict()})\n\n if request_content and errors:\n raise self.prepare_exception(ParseError())\n\n return (validated_data, errors)\n\n def __call__(self):\n \"\"\"Execute the view and return a response.\"\"\"\n if self.check_api_key:\n return self.check()\n else:\n api_key = ApiKey(\n valid_key=None, allow_fallback=False,\n allow_locate=True, allow_transfer=False,\n store_sample_locate=100, store_sample_submit=100)\n # Only use the unchecked API key in the request for simple\n # logging purposes.\n self.log_count(self.parse_apikey(), False)\n return self.view(api_key)\n","sub_path":"ichnaea/api/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":6378,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"579209165","text":"# 1) if an error occured:\n # try > except > finaly\n\n# 2) if no error:\n # try > else > finally\n\n# if there are such constructions like continue or break -- finally block will execute before them no matter what\n\ndef ask_for_int():\n\n while True:\n try:\n num = int(input(\"Enter a number: \"))\n # manualy throw\n raise NameError\n\n except ValueError:\n print(\"Whoops, you entered a wrong integer\\n\")\n continue\n except NameError:\n pass\n else:\n print(\"else\")\n break\n finally:\n print(\"Finaly\\n\")\n\n\n\n# ask_for_int()\n\n\nfor i in ['a','b','c']:\n try:\n print(i**2)\n except TypeError:\n print(\"Unsupported type\\n\")\n\n\n\nx = 5\ny = 0\n\ntry:\n z = x/y\nexcept ZeroDivisionError:\n print(\"Cannot divide by zero\\n\")\nfinally:\n print(\"All done\\n\")\n\n\nwhile True:\n try:\n num = int(input(\"Input an integer: \"))\n squared = num * num\n except ValueError:\n print(\"An error occurred! Please try again!\")\n continue\n else:\n print(f\"Thank you, your number squared is: {squared}\")\n break","sub_path":"py_z_h/exceptions.py","file_name":"exceptions.py","file_ext":"py","file_size_in_byte":1164,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"82179429","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Jun 29 10:28:54 2017\n\n@author: Chenli Zhang\n\"\"\"\nimport TextUtils\nimport Dictionarys\nfrom Government import Organization\n\n\nclass Config:\n def __init__(self):\n self.names=[]\n self.locations=[]\n self.orgnizations = []\n\n def getNames(self):\n return self.names\n \n def getLoc(self):\n return self.locations\n \n def addName(self,n):\n if n not in self.names:\n self.names.append(n)\n \n def addLocation(self,l):\n if l not in self.locations:\n self.locations.append(l)\n\n def parseName(self,line):\n if line[0:5] != 'name:':\n return\n \n names = line[5:]\n ns = names.split(',')\n for n in ns:\n n=n.decode('utf-8')\n if n not in self.names and len(n)>0:\n self.names.append(n)\n \n def parseLoc(self,line):\n if line[0:9] != 'location:':\n return\n \n names = line[9:]\n ns = names.split(',')\n for n in ns:\n n=n.decode('utf-8')\n if n not in self.locations and len(n)>0:\n self.locations.append(n)\n \n def parseGov(self,line):\n if line[0:9] != 'governor:':\n return\n \n gov = Organization()\n sub = line[9:]\n pos=0\n while(True):\n pos = sub.find(':')\n if pos == -1:\n break\n name = sub[0:pos]\n name=name.decode('utf-8')\n gov.setName(name)\n sub= sub[pos+1:]\n \n ps = sub.split(',')\n for p in ps: \n p=p.decode('utf-8')\n gov.addPosition(p)\n self.orgnizations.append(gov)\n \n \n def parse(self,config):\n fp = open(config,'r')\n \n for line in fp:\n \n #print(line)\n if line.find('name:') != -1:\n self.parseName(line)\n elif line.find('location:') != -1:\n self.parseLoc(line)\n elif line.find('governor:') != -1:\n self.parseGov(line)\n fp.close()\n #print(self.names)\n \n def dump(self,config):\n fp = open(config,'w')\n if len(self.names)> 0:\n fp.write('name:')\n for n in self.names:\n fp.write(n+',')\n \n if len(self.locations)>0:\n fp.write('location:')\n for n in self.locations:\n fp.write(n+',')\n \n if len(self.orgnizations)>0: \n for g in self.orgnizations:\n fp.write('governor:')\n for n in g.name:\n fp.write(n+':')\n for p in g.position:\n fp.write(p+',')\n\n fp.close()\n ","sub_path":"BookReader/Config.py","file_name":"Config.py","file_ext":"py","file_size_in_byte":2907,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"200817880","text":"\"\"\"\n Simultaneous or Batch fit page\n\"\"\"\n# Note that this is used for both Simultaneous/Constrained fit AND for\n# combined batch fit. This is done through setting of the batch_on parameter.\n# There are the a half dozen or so places where an if statement is used as in\n# if not batch_on:\n# xxxx\n# else:\n# xxxx\n# This is just wrong but dont have time to fix this go. Proper approach would be\n# to strip all parts of the code that depend on batch_on and create the top\n# level class from which a contrained/simultaneous fit page and a combined\n# batch page inherit.\n#\n# 04/09/2017 --PDB\n\nimport sys\nfrom collections import namedtuple\n\nimport wx\nimport wx.lib.newevent\nfrom wx.lib.scrolledpanel import ScrolledPanel\n\nfrom sas.sascalc.fit.pagestate import SimFitPageState\nfrom sas.sasgui.guiframe.events import StatusEvent, PanelOnFocusEvent\nfrom sas.sasgui.guiframe.panel_base import PanelBase\nfrom sas.sasgui.guiframe.utils import IdList\nfrom sas.sasgui.guiframe.documentation_window import DocumentationWindow\n\n# Control panel width\nif sys.platform.count(\"darwin\") == 0:\n PANEL_WID = 420\n FONT_VARIANT = 0\nelse:\n PANEL_WID = 490\n FONT_VARIANT = 1\n\n\n# Each constraint requires five widgets and sizer. Package them in\n# a named tuple for easy access.\nConstraintLine = namedtuple('ConstraintLine',\n 'model_cbox param_cbox egal_txt constraint btRemove sizer')\n\n\ndef get_fittableParam(model):\n \"\"\"\n return list of fittable parameters from a model\n\n :param model: the model used\n\n \"\"\"\n fittable_param = []\n for item in model.getParamList():\n if not item in model.getDispParamList():\n if not item in model.non_fittable:\n fittable_param.append(item)\n\n for item in model.fixed:\n fittable_param.append(item)\n\n return fittable_param\n\nclass SimultaneousFitPage(ScrolledPanel, PanelBase):\n \"\"\"\n Simultaneous fitting panel\n All that needs to be defined are the\n two data members window_name and window_caption\n \"\"\"\n # Internal name for the AUI manager\n window_name = \"Simultaneous Fit Page\"\n # Title to appear on top of the window\n window_caption = \"Simultaneous Fit Page\"\n ID_DOC = wx.NewId()\n ID_SET_ALL = wx.NewId()\n ID_FIT = wx.NewId()\n ID_ADD = wx.NewId()\n _id_pool = IdList()\n\n def __init__(self, parent, page_finder={}, id=wx.ID_ANY, batch_on=False,\n *args, **kwargs):\n ScrolledPanel.__init__(self, parent, id=id,\n style=wx.FULL_REPAINT_ON_RESIZE,\n *args, **kwargs)\n PanelBase.__init__(self, parent)\n \"\"\"\n Simultaneous page display\n \"\"\"\n self._ids = iter(self._id_pool)\n self.SetupScrolling()\n # Font size\n self.SetWindowVariant(variant=FONT_VARIANT)\n self.uid = wx.NewId()\n self.parent = parent\n self.batch_on = batch_on\n # store page_finder\n self.page_finder = page_finder\n # list containing info to set constraint\n # look like self.constraint_dict[page_id]= page\n self.constraint_dict = {}\n # item list\n # self.constraints_list=[combobox1, combobox2,=,textcrtl, button ]\n self.constraints_list = []\n # list of current model\n self.model_list = []\n # selected model to fit\n self.model_to_fit = []\n # Control the fit state\n self.fit_started = False\n # number of constraint\n self.nb_constraint = 0\n self.state = SimFitPageState()\n self.model_cbox_left = None\n self.model_cbox_right = None\n # draw page\n self.define_page_structure()\n self.draw_page()\n self._set_save_flag(False)\n\n def define_page_structure(self):\n \"\"\"\n Create empty sizers, their hierarchy and set the sizer for the panel\n \"\"\"\n self.vbox = wx.BoxSizer(wx.VERTICAL)\n self.data_selection_sizer = wx.BoxSizer(wx.VERTICAL)\n self.constraints_sizer = wx.BoxSizer(wx.VERTICAL)\n self.run_fit_sizer = wx.BoxSizer(wx.VERTICAL)\n\n self.data_selection_sizer.SetMinSize((PANEL_WID, -1))\n self.constraints_sizer.SetMinSize((PANEL_WID, -1))\n self.run_fit_sizer.SetMinSize((PANEL_WID, -1))\n self.vbox.Add(self.data_selection_sizer)\n self.vbox.Add(self.constraints_sizer)\n self.vbox.Add(self.run_fit_sizer)\n self.SetSizer(self.vbox)\n self.Centre()\n\n def set_state(self):\n \"\"\"\n Define a set of state parameters for saving simultaneous fits.\n \"\"\"\n self._set_constraint()\n self.state.fit_page_no = self.uid\n self.state.select_all = self.cb1.GetValue()\n self.state.model_list = self.model_list\n self.state.model_to_fit = self.model_to_fit\n self.state.no_constraint = self.nb_constraint\n self.state.constraint_dict = self.constraint_dict\n self.state.constraints_list = self.constraints_list\n return self.get_state()\n\n def get_state(self):\n \"\"\"\n Return the state of the current page\n :return: self.state\n \"\"\"\n return self.state\n\n def load_from_save_state(self, sim_state):\n \"\"\"\n Load in a simultaneous/constrained fit from a save state\n :param fit: Fitpanel object\n :return: None\n \"\"\"\n init_map = {}\n final_map = {}\n # Process each model and associate old M# with new M#\n i = 0\n for model in self.model_list:\n model_id = self._format_id(list(model[1].keys())[0])\n for saved_model in sim_state.model_list:\n save_id = saved_model.pop('name')\n saved_model['name'] = save_id\n save_id = self._format_id(save_id)\n if save_id == model_id:\n inter_id = str(i)*5\n init_map[saved_model.pop('fit_page_source')] = inter_id\n final_map[inter_id] = model[3].name\n check = bool(saved_model.pop('checked'))\n self.model_list[i][0].SetValue(check)\n break\n i += 1\n\n self.check_model_name(None)\n\n if len(sim_state.constraints_list) > 0:\n self.hide_constraint.SetValue(False)\n self.show_constraint.SetValue(True)\n self._display_constraint(None)\n\n for index, item in enumerate(sim_state.constraints_list):\n model_cbox = item.pop('model_cbox')\n if model_cbox != \"\":\n constraint_value = item.pop('constraint')\n param = item.pop('param_cbox')\n equality = item.pop('egal_txt')\n for key, value in list(init_map.items()):\n model_cbox = model_cbox.replace(key, value)\n constraint_value = constraint_value.replace(key, value)\n for key, value in list(final_map.items()):\n model_cbox = model_cbox.replace(key, value)\n constraint_value = constraint_value.replace(key, value)\n\n self.constraints_list[index][0].SetValue(model_cbox)\n self._on_select_model(None)\n self.constraints_list[index][1].SetValue(param)\n self.constraints_list[index][2].SetLabel(equality)\n self.constraints_list[index][3].SetValue(constraint_value)\n self._on_add_constraint(None)\n self._manager.sim_page = self\n\n def _format_id(self, original_id):\n original_id = original_id.rstrip('1234567890.')\n new_id_list = original_id.split()\n new_id = ' '.join(new_id_list)\n return new_id\n\n\n\n def draw_page(self):\n \"\"\"\n Construct the Simultaneous/Constrained fit page. fills the first\n region (sizer1) with the list of available fit page pairs of data\n and models. Then fills sizer2 with the checkbox for adding\n constraints, and finally fills sizer3 with the fit button and\n instructions.\n \"\"\"\n\n # create blank list of constraints\n self.model_list = []\n self.model_to_fit = []\n self.constraints_list = []\n self.constraint_dict = {}\n self.nb_constraint = 0\n self.model_cbox_left = None\n self.model_cbox_right = None\n\n if len(self.model_list) > 0:\n for item in self.model_list:\n item[0].SetValue(False)\n self.manager.schedule_for_fit(value=0, uid=item[2])\n\n #-------------------------------------------------------\n # setup sizer1 (which fitpages to include)\n self.data_selection_sizer.Clear(True)\n box_description = wx.StaticBox(self, wx.ID_ANY, \"Fit Combinations\")\n boxsizer1 = wx.StaticBoxSizer(box_description, wx.VERTICAL)\n sizer_title = wx.BoxSizer(wx.HORIZONTAL)\n sizer_couples = wx.GridBagSizer(5, 5)\n\n # The wx GUI has a flag to enable a menu item, but can still be\n # reached via scripting. There is no guearantee future GUI\n # implementations force this check, either.\n # IMHO, this if statement should stay -- JRK 2016-OCT-05\n if len(self.page_finder) == 0:\n msg = \" No fit combinations are found! \\n\\n\"\n msg += \" Please load data and set up \"\n msg += \"at least one fit panels first...\"\n sizer_title.Add(wx.StaticText(self, wx.ID_ANY, msg))\n else:\n # store model\n self._store_model()\n\n self.cb1 = wx.CheckBox(self, wx.ID_ANY, 'Select all')\n self.cb1.SetValue(False)\n wx.EVT_CHECKBOX(self, self.cb1.GetId(), self.check_all_model_name)\n\n sizer_title.Add((10, 10), 0,\n wx.TOP | wx.BOTTOM | wx.EXPAND | wx.ADJUST_MINSIZE, border=5)\n sizer_title.Add(self.cb1, 0,\n wx.TOP | wx.BOTTOM | wx.LEFT | wx.EXPAND | wx.ADJUST_MINSIZE,\n border=5)\n\n # draw list of model and data names\n self._fill_sizer_model_list(sizer_couples)\n\n boxsizer1.Add(sizer_title, flag=wx.TOP | wx.BOTTOM, border=5)\n boxsizer1.Add(sizer_couples, 1, flag=wx.TOP | wx.BOTTOM, border=5)\n self.data_selection_sizer.Add(boxsizer1, 1, wx.EXPAND | wx.ALL, 10)\n # self.sizer1.Layout()\n\n #--------------------------------------------------------\n # set up the other 2 sizers: the constraints list and the\n # buttons (fit, help etc) sizer at the bottom of the page.\n # Note: the if statement should be removed along with the above\n # if statement as soon as it can be properly tested.\n # Nov. 22 2015 --PDB\n # As above, this page can be accessed through other means than the\n # base SasView GUI.\n # Oct. 5, 2016 --JRK\n if len(self.page_finder) > 0:\n # draw the sizer containing constraint info\n if not self.batch_on:\n self._fill_sizer_constraint()\n # draw fit button sizer\n self._fill_sizer_fit()\n\n def _fill_sizer_model_list(self, sizer):\n \"\"\"\n Receive a dictionary containing information to display model name\n \"\"\"\n ix = 0\n iy = 0\n sizer.Clear(True)\n\n new_name = wx.StaticText(self, wx.ID_ANY, ' Model Title ',\n style=wx.ALIGN_CENTER)\n new_name.SetBackgroundColour('orange')\n new_name.SetForegroundColour(wx.WHITE)\n sizer.Add(new_name, (iy, ix), (1, 1),\n wx.LEFT | wx.EXPAND | wx.ADJUST_MINSIZE, 15)\n ix += 2\n model_type = wx.StaticText(self, wx.ID_ANY, ' Model ')\n model_type.SetBackgroundColour('grey')\n model_type.SetForegroundColour(wx.WHITE)\n sizer.Add(model_type, (iy, ix), (1, 1),\n wx.EXPAND | wx.ADJUST_MINSIZE, 0)\n ix += 1\n data_used = wx.StaticText(self, wx.ID_ANY, ' Data ')\n data_used.SetBackgroundColour('grey')\n data_used.SetForegroundColour(wx.WHITE)\n sizer.Add(data_used, (iy, ix), (1, 1),\n wx.EXPAND | wx.ADJUST_MINSIZE, 0)\n ix += 1\n tab_used = wx.StaticText(self, wx.ID_ANY, ' FitPage ')\n tab_used.SetBackgroundColour('grey')\n tab_used.SetForegroundColour(wx.WHITE)\n sizer.Add(tab_used, (iy, ix), (1, 1),\n wx.EXPAND | wx.ADJUST_MINSIZE, 0)\n for id, value in self.page_finder.items():\n if id not in self.parent.opened_pages:\n continue\n\n if self.batch_on != self.parent.get_page_by_id(id).batch_on:\n continue\n\n data_list = []\n model_list = []\n # get data name and model objetta\n for fitproblem in value.get_fit_problem():\n\n data = fitproblem.get_fit_data()\n if not data.is_data:\n continue\n name = '-'\n if data is not None and data.is_data:\n name = str(data.name)\n data_list.append(name)\n\n model = fitproblem.get_model()\n if model is None:\n continue\n model_list.append(model)\n\n if len(model_list) == 0:\n continue\n # Draw sizer\n ix = 0\n iy += 1\n model = model_list[0]\n name = '_'\n if model is not None:\n name = str(model.name)\n cb = wx.CheckBox(self, wx.ID_ANY, name)\n cb.SetValue(False)\n cb.Enable(model is not None and data.is_data)\n sizer.Add(cb, (iy, ix), (1, 1),\n wx.LEFT | wx.EXPAND | wx.ADJUST_MINSIZE, 15)\n wx.EVT_CHECKBOX(self, cb.GetId(), self.check_model_name)\n ix += 2\n model_type = wx.StaticText(self, wx.ID_ANY,\n model.__class__.__name__)\n sizer.Add(model_type, (iy, ix), (1, 1),\n wx.EXPAND | wx.ADJUST_MINSIZE, 0)\n if self.batch_on:\n data_used = wx.ComboBox(self, wx.ID_ANY, style=wx.CB_READONLY)\n data_used.AppendItems(data_list)\n data_used.SetSelection(0)\n else:\n data_used = wx.StaticText(self, wx.ID_ANY, data_list[0])\n\n ix += 1\n sizer.Add(data_used, (iy, ix), (1, 1),\n wx.EXPAND | wx.ADJUST_MINSIZE, 0)\n ix += 1\n caption = value.get_fit_tab_caption()\n tab_caption_used = wx.StaticText(self, wx.ID_ANY, str(caption))\n sizer.Add(tab_caption_used, (iy, ix), (1, 1),\n wx.EXPAND | wx.ADJUST_MINSIZE, 0)\n\n self.model_list.append([cb, value, id, model])\n\n iy += 1\n sizer.Add((20, 20), (iy, ix), (1, 1),\n wx.LEFT | wx.EXPAND | wx.ADJUST_MINSIZE, 15)\n\n def _fill_sizer_constraint(self):\n \"\"\"\n Fill sizer containing constraint info\n \"\"\"\n msg = \"Select at least 1 model to add constraint \"\n wx.PostEvent(self.parent.parent, StatusEvent(status=msg))\n\n self.constraints_sizer.Clear(True)\n if self.batch_on:\n if self.constraints_sizer.IsShown():\n self.constraints_sizer.Show(False)\n return\n box_description = wx.StaticBox(self, wx.ID_ANY, \"Fit Constraints\")\n box_sizer1 = wx.StaticBoxSizer(box_description, wx.VERTICAL)\n sizer_title = wx.BoxSizer(wx.HORIZONTAL)\n self.sizer_all_constraints = wx.BoxSizer(wx.HORIZONTAL)\n self.sizer_constraints = wx.BoxSizer(wx.VERTICAL)\n sizer_button = wx.BoxSizer(wx.HORIZONTAL)\n\n self.hide_constraint = wx.RadioButton(self, wx.ID_ANY, 'No', (10, 10),\n style=wx.RB_GROUP)\n self.show_constraint = wx.RadioButton(self, wx.ID_ANY, 'Yes', (10, 30))\n self.Bind(wx.EVT_RADIOBUTTON, self._display_constraint,\n id=self.hide_constraint.GetId())\n self.Bind(wx.EVT_RADIOBUTTON, self._display_constraint,\n id=self.show_constraint.GetId())\n if self.batch_on:\n self.hide_constraint.Enable(False)\n self.show_constraint.Enable(False)\n self.hide_constraint.SetValue(True)\n self.show_constraint.SetValue(False)\n\n sizer_title.Add(wx.StaticText(self, wx.ID_ANY, \" Model\"))\n sizer_title.Add((10, 10))\n sizer_title.Add(wx.StaticText(self, wx.ID_ANY, \" Parameter\"))\n sizer_title.Add((10, 10))\n sizer_title.Add(wx.StaticText(self, wx.ID_ANY, \" Add Constraint?\"))\n sizer_title.Add((10, 10))\n sizer_title.Add(self.show_constraint)\n sizer_title.Add(self.hide_constraint)\n sizer_title.Add((10, 10))\n\n self.btAdd = wx.Button(self, self.ID_ADD, 'Add')\n self.btAdd.Bind(wx.EVT_BUTTON, self._on_add_constraint,\n id=self.btAdd.GetId())\n self.btAdd.SetToolTipString(\"Add another constraint?\")\n self.btAdd.Hide()\n\n text_hint = wx.StaticText(self, wx.ID_ANY,\n \"Example: [M0][parameter] = M1.parameter\")\n sizer_button.Add(text_hint, 0,\n wx.LEFT | wx.EXPAND | wx.ADJUST_MINSIZE, 10)\n sizer_button.Add(self.btAdd, 0,\n wx.LEFT | wx.EXPAND | wx.ADJUST_MINSIZE, 10)\n\n box_sizer1.Add(sizer_title, flag=wx.TOP | wx.BOTTOM, border=10)\n box_sizer1.Add(self.sizer_all_constraints, flag=wx.TOP | wx.BOTTOM,\n border=10)\n box_sizer1.Add(self.sizer_constraints, flag=wx.TOP | wx.BOTTOM,\n border=10)\n box_sizer1.Add(sizer_button, flag=wx.TOP | wx.BOTTOM, border=10)\n\n self.constraints_sizer.Add(box_sizer1, 0, wx.EXPAND | wx.ALL, 10)\n\n def _fill_sizer_fit(self):\n \"\"\"\n Draw fit button\n \"\"\"\n self.run_fit_sizer.Clear(True)\n box_description = wx.StaticBox(self, wx.ID_ANY, \"Fit \")\n boxsizer1 = wx.StaticBoxSizer(box_description, wx.VERTICAL)\n sizer_button = wx.BoxSizer(wx.HORIZONTAL)\n\n # Fit button\n self.btFit = wx.Button(self, self.ID_FIT, 'Fit', size=wx.DefaultSize)\n self.btFit.Bind(wx.EVT_BUTTON, self.on_fit, id=self.btFit.GetId())\n self.btFit.SetToolTipString(\"Perform fit.\")\n\n # General Help button\n self.btHelp = wx.Button(self, wx.ID_HELP, 'HELP')\n if self.batch_on:\n self.btHelp.SetToolTipString(\"Combined Batch Fitting help.\")\n else:\n self.btHelp.SetToolTipString(\"Simultaneous/Constrained Fitting help.\")\n self.btHelp.Bind(wx.EVT_BUTTON, self._on_help)\n\n # hint text on button line\n if self.batch_on:\n text = \" Fit in Parallel all Data sets\\n\"\n text += \"and model selected.\"\n else:\n text = \" At least one set of model and data\\n\"\n text += \" must be selected for fitting.\"\n text_hint = wx.StaticText(self, wx.ID_ANY, text)\n\n sizer_button.Add(text_hint)\n sizer_button.Add(self.btFit, 0, wx.LEFT | wx.ADJUST_MINSIZE, 10)\n sizer_button.Add(self.btHelp, 0, wx.LEFT | wx.ADJUST_MINSIZE, 10)\n\n boxsizer1.Add(sizer_button, flag=wx.TOP | wx.BOTTOM, border=10)\n self.run_fit_sizer.Add(boxsizer1, 0, wx.EXPAND | wx.ALL, 10)\n\n def on_remove(self, event):\n \"\"\"\n Remove constraint fields\n \"\"\"\n if len(self.constraints_list) == 1:\n self.hide_constraint.SetValue(True)\n self._hide_constraint()\n return\n if len(self.constraints_list) == 0:\n return\n wx.CallAfter(self._remove_after, event.GetId())\n # self._onAdd_constraint(None)\n\n def _remove_after(self, id):\n for item in self.constraints_list:\n if id == item.btRemove.GetId():\n self.sizer_constraints.Hide(item.sizer)\n item.sizer.Clear(True)\n self.sizer_constraints.Remove(item.sizer)\n self.constraints_list.remove(item)\n self.nb_constraint -= 1\n self.constraints_sizer.Layout()\n self.FitInside()\n break\n\n def on_fit(self, event):\n \"\"\"\n signal for fitting\n\n \"\"\"\n if self.fit_started:\n self._stop_fit()\n self.fit_started = False\n return\n\n flag = False\n # check if the current page a simultaneous fit page or a batch page\n if self == self._manager.sim_page:\n flag = (self._manager.sim_page.uid == self.uid)\n\n # making sure all parameters content a constraint\n if not self.batch_on and self.show_constraint.GetValue():\n if not self._set_constraint():\n return\n # model was actually selected from this page to be fit\n if len(self.model_to_fit) >= 1:\n self.manager._reset_schedule_problem(value=0)\n for item in self.model_list:\n if item[0].GetValue():\n self.manager.schedule_for_fit(value=1, uid=item[2])\n try:\n self.fit_started = True\n wx.CallAfter(self.set_fitbutton)\n if not self.manager.onFit(uid=self.uid):\n return\n except:\n msg = \"Select at least one parameter to fit in the FitPages.\"\n wx.PostEvent(self.parent.parent, StatusEvent(status=msg))\n else:\n msg = \"Select at least one model check box to fit \"\n wx.PostEvent(self.parent.parent, StatusEvent(status=msg))\n self.set_state()\n\n def _on_fit_complete(self):\n \"\"\"\n Set the completion flag and display the updated fit button label.\n \"\"\"\n self.fit_started = False\n self.set_fitbutton()\n\n def _stop_fit(self, event=None):\n \"\"\"\n Attempt to stop the fitting thread\n\n :param event: Event handler when stop fit is clicked\n \"\"\"\n if event is not None:\n event.Skip()\n self.manager.stop_fit(self.uid)\n self.manager._reset_schedule_problem(value=0)\n self._on_fit_complete()\n\n def set_fitbutton(self):\n \"\"\"\n Set fit button label depending on the fit_started\n \"\"\"\n label = \"Stop\" if self.fit_started else \"Fit\"\n color = \"red\" if self.fit_started else \"black\"\n\n self.btFit.SetLabel(label)\n self.btFit.SetForegroundColour(color)\n self.btFit.Enable(True)\n\n def _on_help(self, event):\n \"\"\"\n Bring up the simultaneous Fitting Documentation whenever the HELP\n button is clicked.\n\n Calls DocumentationWindow with the path of the location within the\n documentation tree (after /doc/ ....\". Note that when using old\n versions of Wx (before 2.9) and thus not the release version of\n installers, the help comes up at the top level of the file as\n web browser does not pass anything past the # to the browser when it is\n running \"file:///....\"\n\n :param event: Triggers on clicking the help button\n \"\"\"\n _TreeLocation = \"user/sasgui/perspectives/fitting/fitting_help.html\"\n if not self.batch_on:\n _PageAnchor = \"#simultaneous-fit-mode\"\n _doc_viewer = DocumentationWindow(self, self.ID_DOC, _TreeLocation,\n _PageAnchor,\n \"Simultaneous/Constrained Fitting Help\")\n else:\n _PageAnchor = \"#combined-batch-fit-mode\"\n _doc_viewer = DocumentationWindow(self, self.ID_DOC, _TreeLocation,\n _PageAnchor,\n \"Combined Batch Fit Help\")\n\n def set_manager(self, manager):\n \"\"\"\n set panel manager\n\n :param manager: instance of plugin fitting\n \"\"\"\n self.manager = manager\n\n def check_all_model_name(self, event=None):\n \"\"\"\n check all models names\n \"\"\"\n self.model_to_fit = []\n if self.cb1.GetValue():\n for item in self.model_list:\n if item[0].IsEnabled():\n item[0].SetValue(True)\n self.model_to_fit.append(item)\n\n # constraint info\n self._store_model()\n if not self.batch_on:\n # display constraint fields\n if (self.show_constraint.GetValue() and\n len(self.constraints_list) == 0):\n self._show_all_constraint()\n self._show_constraint()\n else:\n for item in self.model_list:\n item[0].SetValue(False)\n\n if not self.batch_on:\n # constraint info\n self._hide_constraint()\n\n self._update_easy_setup_cb()\n self.FitInside()\n\n def check_model_name(self, event):\n \"\"\"\n Save information related to checkbox and their states\n \"\"\"\n self.model_to_fit = []\n for item in self.model_list:\n if item[0].GetValue():\n self.model_to_fit.append(item)\n else:\n if item in self.model_to_fit:\n self.model_to_fit.remove(item)\n self.cb1.SetValue(False)\n\n # display constraint fields\n if len(self.model_to_fit) >= 1:\n self._store_model()\n if not self.batch_on and self.show_constraint.GetValue() and\\\n len(self.constraints_list) == 0:\n self._show_all_constraint()\n self._show_constraint()\n\n elif len(self.model_to_fit) < 1:\n # constraint info\n self._hide_constraint()\n\n self._update_easy_setup_cb()\n # set the value of the main check button\n if len(self.model_list) == len(self.model_to_fit):\n self.cb1.SetValue(True)\n self.FitInside()\n return\n else:\n self.cb1.SetValue(False)\n self.FitInside()\n\n def _update_easy_setup_cb(self):\n \"\"\"\n Update easy setup combobox on selecting a model\n \"\"\"\n if self.model_cbox_left is None or self.model_cbox_right is None:\n return\n\n models = [(item[3].name, item[3]) for item in self.model_to_fit]\n setComboBoxItems(self.model_cbox_left, models)\n setComboBoxItems(self.model_cbox_right, models)\n for item in self.constraints_list:\n setComboBoxItems(item[0], models)\n if self.model_cbox_left.GetSelection() == wx.NOT_FOUND:\n self.model_cbox_left.SetSelection(0)\n self.constraints_sizer.Layout()\n\n def _store_model(self):\n \"\"\"\n Store selected model\n \"\"\"\n if len(self.model_to_fit) < 1:\n return\n for item in self.model_to_fit:\n model = item[3]\n page_id = item[2]\n self.constraint_dict[page_id] = model\n\n def _display_constraint(self, event):\n \"\"\"\n Show fields to add constraint\n \"\"\"\n if len(self.model_to_fit) < 1:\n msg = \"Select at least 1 model to add constraint \"\n wx.PostEvent(self.parent.parent, StatusEvent(status=msg))\n # hide button\n self._hide_constraint()\n return\n if self.show_constraint.GetValue():\n self._show_all_constraint()\n self._show_constraint()\n self.FitInside()\n return\n else:\n self._hide_constraint()\n return\n\n def _show_all_constraint(self):\n \"\"\"\n Show constraint fields\n \"\"\"\n box_description = wx.StaticBox(self, wx.ID_ANY, \"Easy Setup \")\n box_sizer = wx.StaticBoxSizer(box_description, wx.HORIZONTAL)\n sizer_constraint = wx.BoxSizer(wx.HORIZONTAL)\n self.model_cbox_left = wx.ComboBox(self, wx.ID_ANY, style=wx.CB_READONLY)\n self.model_cbox_left.Clear()\n self.model_cbox_right = wx.ComboBox(self, wx.ID_ANY, style=wx.CB_READONLY)\n self.model_cbox_right.Clear()\n wx.EVT_COMBOBOX(self.model_cbox_left, wx.ID_ANY, self._on_select_modelcb)\n wx.EVT_COMBOBOX(self.model_cbox_right, wx.ID_ANY, self._on_select_modelcb)\n egal_txt = wx.StaticText(self, wx.ID_ANY, \" = \")\n self.set_button = wx.Button(self, self.ID_SET_ALL, 'Set All')\n self.set_button.Bind(wx.EVT_BUTTON, self._on_set_all_equal,\n id=self.set_button.GetId())\n set_tip = \"Add constraints for all the adjustable parameters \"\n set_tip += \"(checked in FitPages) if exist.\"\n self.set_button.SetToolTipString(set_tip)\n self.set_button.Disable()\n\n for id, model in self.constraint_dict.items():\n # check if all parameters have been selected for constraint\n # then do not allow add constraint on parameters\n self.model_cbox_left.Append(str(model.name), model)\n self.model_cbox_left.Select(0)\n for id, model in self.constraint_dict.items():\n # check if all parameters have been selected for constraint\n # then do not allow add constraint on parameters\n self.model_cbox_right.Append(str(model.name), model)\n box_sizer.Add(self.model_cbox_left,\n flag=wx.RIGHT | wx.EXPAND, border=10)\n # box_sizer.Add(wx.StaticText(self, wx.ID_ANY, \".parameters\"),\n # flag=wx.RIGHT | wx.EXPAND, border=5)\n box_sizer.Add(egal_txt, flag=wx.RIGHT | wx.EXPAND, border=5)\n box_sizer.Add(self.model_cbox_right,\n flag=wx.RIGHT | wx.EXPAND, border=10)\n # box_sizer.Add(wx.StaticText(self, wx.ID_ANY, \".parameters\"),\n # flag=wx.RIGHT | wx.EXPAND, border=5)\n box_sizer.Add((20, -1))\n box_sizer.Add(self.set_button, flag=wx.RIGHT | wx.EXPAND, border=5)\n sizer_constraint.Add(box_sizer, flag=wx.RIGHT | wx.EXPAND, border=5)\n self.sizer_all_constraints.Insert(before=0,\n item=sizer_constraint,\n flag=wx.TOP | wx.BOTTOM | wx.EXPAND, border=5)\n self.FitInside()\n\n def _on_select_modelcb(self, event):\n \"\"\"\n On select model left or right combobox\n \"\"\"\n event.Skip()\n flag = True\n if self.model_cbox_left.GetValue().strip() == '':\n flag = False\n if self.model_cbox_right.GetValue().strip() == '':\n flag = False\n if (self.model_cbox_left.GetValue() ==\n self.model_cbox_right.GetValue()):\n flag = False\n self.set_button.Enable(flag)\n\n def _on_set_all_equal(self, event):\n \"\"\"\n On set button\n \"\"\"\n event.Skip()\n length = len(self.constraints_list)\n if length < 1:\n return\n param_list = []\n param_list_b = []\n selection = self.model_cbox_left.GetCurrentSelection()\n model_left = self.model_cbox_left.GetValue()\n model = self.model_cbox_left.GetClientData(selection)\n selection_b = self.model_cbox_right.GetCurrentSelection()\n model_right = self.model_cbox_right.GetValue()\n model_b = self.model_cbox_right.GetClientData(selection_b)\n for id, dic_model in self.constraint_dict.items():\n if model == dic_model:\n param_list = self.page_finder[id].get_param2fit()\n if model_b == dic_model:\n param_list_b = self.page_finder[id].get_param2fit()\n if len(param_list) > 0 and len(param_list_b) > 0:\n break\n num_cbox = 0\n has_param = False\n for param in param_list:\n num_cbox += 1\n if param in param_list_b:\n item = self.constraints_list[-1]\n item.model_cbox.SetStringSelection(model_left)\n self._on_select_model(None)\n item.param_cbox.Clear()\n item.param_cbox.Append(str(param), model)\n item.param_cbox.SetStringSelection(str(param))\n item.constraint.SetValue(str(model_right + \".\" + str(param)))\n has_param = True\n if num_cbox == (len(param_list) + 1):\n break\n self._show_constraint()\n\n self.FitInside()\n if not has_param:\n msg = \" There is no adjustable parameter (checked to fit)\"\n msg += \" either one of the models.\"\n wx.PostEvent(self.parent.parent, StatusEvent(info=\"warning\",\n status=msg))\n else:\n msg = \" The constraints are added.\"\n wx.PostEvent(self.parent.parent, StatusEvent(info=\"info\",\n status=msg))\n\n def _show_constraint(self):\n \"\"\"\n Show constraint fields\n :param dict: dictionary mapping constraint values\n \"\"\"\n self.btAdd.Show(True)\n if len(self.constraints_list) != 0:\n nb_fit_param = 0\n for id, model in self.constraint_dict.items():\n nb_fit_param += len(self.page_finder[id].get_param2fit())\n # Don't add anymore\n if len(self.constraints_list) == nb_fit_param:\n msg = \"Cannot add another constraint. Maximum of number \"\n msg += \"Parameters name reached %s\" % str(nb_fit_param)\n wx.PostEvent(self.parent.parent, StatusEvent(status=msg))\n self.sizer_constraints.Layout()\n self.constraints_sizer.Layout()\n return\n if len(self.model_to_fit) < 1:\n msg = \"Select at least 1 model to add constraint \"\n wx.PostEvent(self.parent.parent, StatusEvent(status=msg))\n self.sizer_constraints.Layout()\n self.constraints_sizer.Layout()\n return\n\n sizer_constraint = wx.BoxSizer(wx.HORIZONTAL)\n\n # Model list\n model_cbox = wx.ComboBox(self, wx.ID_ANY, style=wx.CB_READONLY)\n model_cbox.Clear()\n for id, model in self.constraint_dict.items():\n # check if all parameters have been selected for constraint\n # then do not allow add constraint on parameters\n model_cbox.Append(str(model.name), model)\n wx.EVT_COMBOBOX(model_cbox, wx.ID_ANY, self._on_select_model)\n\n # Parameters in model\n param_cbox = wx.ComboBox(self, wx.ID_ANY, style=wx.CB_READONLY,\n size=(100, -1))\n param_cbox.Hide()\n wx.EVT_COMBOBOX(param_cbox, wx.ID_ANY, self._on_select_param)\n\n egal_txt = wx.StaticText(self, wx.ID_ANY, \" = \")\n\n # Parameter constraint\n constraint = wx.TextCtrl(self, wx.ID_ANY)\n\n # Remove button\n #btRemove = wx.Button(self, self.ID_REMOVE, 'Remove')\n bt_remove = wx.Button(self, next(self._ids), 'Remove')\n bt_remove.Bind(wx.EVT_BUTTON, self.on_remove,\n id=bt_remove.GetId())\n bt_remove.SetToolTipString(\"Remove constraint.\")\n bt_remove.Hide()\n\n # Hid the add button, if it exists\n if hasattr(self, \"btAdd\"):\n self.btAdd.Hide()\n\n sizer_constraint.Add((5, -1))\n sizer_constraint.Add(model_cbox, flag=wx.RIGHT | wx.EXPAND, border=10)\n sizer_constraint.Add(param_cbox, flag=wx.RIGHT | wx.EXPAND, border=5)\n sizer_constraint.Add(egal_txt, flag=wx.RIGHT | wx.EXPAND, border=5)\n sizer_constraint.Add(constraint, flag=wx.RIGHT | wx.EXPAND, border=10)\n sizer_constraint.Add(bt_remove, flag=wx.RIGHT | wx.EXPAND, border=10)\n\n self.sizer_constraints.Insert(before=self.nb_constraint,\n item=sizer_constraint, flag=wx.TOP | wx.BOTTOM | wx.EXPAND,\n border=5)\n c = ConstraintLine(model_cbox, param_cbox, egal_txt,\n constraint, bt_remove, sizer_constraint)\n self.constraints_list.append(c)\n\n self.nb_constraint += 1\n self.sizer_constraints.Layout()\n self.constraints_sizer.Layout()\n self.Layout()\n\n def _hide_constraint(self):\n \"\"\"\n hide buttons related constraint\n \"\"\"\n for id in self.page_finder.keys():\n self.page_finder[id].clear_model_param()\n\n self.nb_constraint = 0\n self.constraint_dict = {}\n if hasattr(self, \"btAdd\"):\n self.btAdd.Hide()\n self._store_model()\n if self.model_cbox_left is not None:\n self.model_cbox_left.Clear()\n self.model_cbox_left = None\n if self.model_cbox_right is not None:\n self.model_cbox_right.Clear()\n self.model_cbox_right = None\n self.constraints_list = []\n self.sizer_all_constraints.Clear(True)\n self.sizer_all_constraints.Layout()\n self.sizer_constraints.Clear(True)\n self.sizer_constraints.Layout()\n self.constraints_sizer.Layout()\n self.Layout()\n self.FitInside()\n\n def _on_select_model(self, event):\n \"\"\"\n fill combo box with list of parameters\n \"\"\"\n if not self.constraints_list:\n return\n\n # This way PC/MAC both work, instead of using event.GetClientData().\n model_cbox = self.constraints_list[-1].model_cbox\n n = model_cbox.GetCurrentSelection()\n if n == wx.NOT_FOUND:\n return\n\n model = model_cbox.GetClientData(n)\n param_list = []\n for id, dic_model in self.constraint_dict.items():\n if model == dic_model:\n param_list = self.page_finder[id].get_param2fit()\n break\n\n param_cbox = self.constraints_list[-1].param_cbox\n param_cbox.Clear()\n # insert only fittable paramaters\n for param in param_list:\n param_cbox.Append(str(param), model)\n param_cbox.Show(True)\n\n bt_remove = self.constraints_list[-1].btRemove\n bt_remove.Show(True)\n self.btAdd.Show(True)\n# self.Layout()\n self.FitInside()\n\n def _on_select_param(self, event):\n \"\"\"\n Store the appropriate constraint in the page_finder\n \"\"\"\n # This way PC/MAC both work, instead of using event.GetClientData().\n # n = self.param_cbox.GetCurrentSelection()\n # model = self.param_cbox.GetClientData(n)\n # param = event.GetString()\n\n if self.constraints_list:\n self.constraints_list[-1].egal_txt.Show(True)\n self.constraints_list[-1].constraint.Show(True)\n\n def _on_add_constraint(self, event):\n \"\"\"\n Add another line for constraint\n \"\"\"\n if not self.show_constraint.GetValue():\n msg = \" Select Yes to add Constraint \"\n wx.PostEvent(self.parent.parent, StatusEvent(status=msg))\n return\n # check that a constraint is added\n # before allow to add another constraint\n for item in self.constraints_list:\n if item.model_cbox.GetString(0) == \"\":\n msg = \" Select a model Name! \"\n wx.PostEvent(self.parent.parent, StatusEvent(status=msg))\n return\n if item.param_cbox.GetString(0) == \"\":\n msg = \" Select a parameter Name! \"\n wx.PostEvent(self.parent.parent, StatusEvent(status=msg))\n return\n if item.constraint.GetValue().lstrip().rstrip() == \"\":\n model = item.param_cbox.GetClientData(\n item.param_cbox.GetCurrentSelection())\n if model is not None:\n msg = \" Enter a constraint for %s.%s! \" % (model.name,\n item.param_cbox.GetString(0))\n else:\n msg = \" Enter a constraint\"\n wx.PostEvent(self.parent.parent, StatusEvent(status=msg))\n return\n # some model or parameters can be constrained\n self._show_constraint()\n self.FitInside()\n\n def _set_constraint(self):\n \"\"\"\n get values from the constraint textcrtl ,parses them into model name\n parameter name and parameters values.\n store them in a list self.params .when when params is not empty\n set_model uses it to reset the appropriate model\n and its appropriates parameters\n \"\"\"\n for item in self.constraints_list:\n select0 = item.model_cbox.GetSelection()\n if select0 == wx.NOT_FOUND:\n continue\n model = item.model_cbox.GetClientData(select0)\n select1 = item.param_cbox.GetSelection()\n if select1 == wx.NOT_FOUND:\n continue\n param = item.param_cbox.GetString(select1)\n constraint = item.constraint.GetValue().lstrip().rstrip()\n if param.lstrip().rstrip() == \"\":\n param = None\n msg = \" Constraint will be ignored!. missing parameters\"\n msg += \" in combobox to set constraint! \"\n wx.PostEvent(self.parent.parent, StatusEvent(status=msg))\n for id, value in self.constraint_dict.items():\n if model == value:\n if constraint == \"\":\n msg = \" Constraint will be ignored!. missing value\"\n msg += \" in textcrtl to set constraint! \"\n wx.PostEvent(self.parent.parent,\n StatusEvent(status=msg))\n constraint = None\n if str(param) in self.page_finder[id].get_param2fit():\n msg = \" Checking constraint for parameter: %s \", param\n wx.PostEvent(self.parent.parent,\n StatusEvent(info=\"info\", status=msg))\n else:\n model_name = item[0].GetLabel()\n fitpage = self.page_finder[id].get_fit_tab_caption()\n msg = \"All constrainted parameters must be set \"\n msg += \" adjustable: '%s.%s' \" % (model_name, param)\n msg += \"is NOT checked in '%s'. \" % fitpage\n msg += \" Please check it to fit or\"\n msg += \" remove the line of the constraint.\"\n wx.PostEvent(self.parent.parent,\n StatusEvent(info=\"error\", status=msg))\n return False\n\n for fid in self.page_finder[id].keys():\n # wrap in param/constraint in str() to remove unicode\n self.page_finder[id].set_model_param(str(param),\n str(constraint), fid=fid)\n break\n return True\n\n def on_set_focus(self, event=None):\n \"\"\"\n The derivative class is on focus if implemented\n \"\"\"\n if self.parent is not None:\n if self.parent.parent is not None:\n wx.PostEvent(self.parent.parent, PanelOnFocusEvent(panel=self))\n self.page_finder = self.parent._manager.get_page_finder()\n\n\ndef setComboBoxItems(cbox, items):\n assert isinstance(cbox, wx.ComboBox)\n selected = cbox.GetStringSelection()\n cbox.Clear()\n for k, (name, value) in enumerate(items):\n cbox.Append(name, value)\n cbox.SetStringSelection(selected)\n","sub_path":"jhub37_mantid_baseline/sasview-5.0.3/src/sas/sasgui/perspectives/fitting/simfitpage.py","file_name":"simfitpage.py","file_ext":"py","file_size_in_byte":43608,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"511713070","text":"import math,string,itertools,fractions,heapq,collections,re,array,bisect,random\n\nclass SandwichBar:\n def whichOrder(self, available, orders):\n for i,o in enumerate(orders):\n o = o.split(\" \")\n if set(available).intersection(set(o)) == set(o):\n return i\n\n return -1\n\n# BEGIN KAWIGIEDIT TESTING\n# Generated by KawigiEdit-pf 2.3.0\nimport sys\nimport time\ndef KawigiEdit_RunTest(testNum, p0, p1, hasAnswer, p2):\n\tsys.stdout.write(str(\"Test \") + str(testNum) + str(\": [\") + str(\"{\"))\n\tfor i in range(len(p0)):\n\t\tif (i > 0):\n\t\t\tsys.stdout.write(str(\",\"))\n\t\t\n\t\tsys.stdout.write(str(\"\\\"\") + str(p0[i]) + str(\"\\\"\"))\n\t\n\tsys.stdout.write(str(\"}\") + str(\",\") + str(\"{\"))\n\tfor i in range(len(p1)):\n\t\tif (i > 0):\n\t\t\tsys.stdout.write(str(\",\"))\n\t\t\n\t\tsys.stdout.write(str(\"\\\"\") + str(p1[i]) + str(\"\\\"\"))\n\t\n\tsys.stdout.write(str(\"}\"))\n\tprint(str(\"]\"))\n\tobj = SandwichBar()\n\tstartTime = time.clock()\n\tanswer = obj.whichOrder(p0, p1)\n\tendTime = time.clock()\n\tres = True\n\tprint(str(\"Time: \") + str((endTime - startTime)) + str(\" seconds\"))\n\tif (hasAnswer):\n\t\tprint(str(\"Desired answer:\"))\n\t\tprint(str(\"\\t\") + str(p2))\n\t\n\tprint(str(\"Your answer:\"))\n\tprint(str(\"\\t\") + str(answer))\n\tif (hasAnswer):\n\t\tres = answer == p2\n\t\n\tif (not res):\n\t\tprint(str(\"DOESN'T MATCH!!!!\"))\n\telif ((endTime - startTime) >= 2):\n\t\tprint(str(\"FAIL the timeout\"))\n\t\tres = False\n\telif (hasAnswer):\n\t\tprint(str(\"Match :-)\"))\n\telse:\n\t\tprint(str(\"OK, but is it right?\"))\n\t\n\tprint(str(\"\"))\n\treturn res\n\nall_right = True\ntests_disabled = False\n\n\n# ----- test 0 -----\ndisabled = False\np0 = (\"ham\",\"cheese\",\"mustard\")\np1 = (\"ham cheese\",)\np2 = 0\nall_right = (disabled or KawigiEdit_RunTest(0, p0, p1, True, p2) ) and all_right\ntests_disabled = tests_disabled or disabled\n# ------------------\n\n# ----- test 1 -----\ndisabled = False\np0 = (\"cheese\",\"mustard\",\"lettuce\")\np1 = (\"cheese ham\",\"cheese mustard lettuce\",\"ketchup\",\"beer\")\np2 = 1\nall_right = (disabled or KawigiEdit_RunTest(1, p0, p1, True, p2) ) and all_right\ntests_disabled = tests_disabled or disabled\n# ------------------\n\n# ----- test 2 -----\ndisabled = False\np0 = (\"cheese\",\"cheese\",\"cheese\",\"tomato\")\np1 = (\"ham ham ham\",\"water\",\"pork\",\"bread\",\"cheese tomato cheese\",\"beef\")\np2 = 4\nall_right = (disabled or KawigiEdit_RunTest(2, p0, p1, True, p2) ) and all_right\ntests_disabled = tests_disabled or disabled\n# ------------------\n\n# ----- test 3 -----\ndisabled = False\np0 = (\"foo\",\"bar\",\"baz\",\"gazonk\",\"quux\",\"bat\",\"xyzzy\",\"shme\",\"hukarz\",\"grault\",\"waldo\",\"bleh\")\np1 = (\"kalatehas\",\"spam eggs\",\"needle haystack\",\"bleh blarg\",\"plugh\",\"the best sandwich in the universe\")\np2 = -1\nall_right = (disabled or KawigiEdit_RunTest(3, p0, p1, True, p2) ) and all_right\ntests_disabled = tests_disabled or disabled\n# ------------------\n\nif (all_right):\n\tif (tests_disabled):\n\t\tprint(str(\"You're a stud (but some test cases were disabled)!\"))\n\telse:\n\t\tprint(str(\"You're a stud (at least on given cases)!\"))\n\t\nelse:\n\tprint(str(\"Some of the test cases had errors.\"))\n\n# PROBLEM STATEMENT\n# It's time to get something to eat and I've come across a sandwich bar. Like most people, I prefer certain types of sandwiches. In fact, I keep a list of the types of sandwiches I like.\n# \n# The sandwich bar has certain ingredients available. I will list the types of sandwiches I like in order of preference and buy the first sandwich the bar can make for me. In order for the bar to make a sandwich for me, it must include all of the ingredients I desire.\n# \n# Given a tuple (string) available, a list of ingredients the sandwich bar can use, and a tuple (string) orders, the types of sandwiches I like, in order of preference (most preferred first), return the 0-based index of the sandwich I will buy. Each element of orders represents one type of sandwich I like as a space-separated list of ingredients in the sandwich. If the bar can make no sandwiches I like, return -1.\n# \n# DEFINITION\n# Class:SandwichBar\n# Method:whichOrder\n# Parameters:tuple (string), tuple (string)\n# Returns:integer\n# Method signature:def whichOrder(self, available, orders):\n# \n# \n# CONSTRAINTS\n# -available will contain between 1 and 50 elements, inclusive.\n# -Each element of available will contain between 1 and 50 lowercase letters ('a' - 'z'), inclusive.\n# -orders will contain between 1 and 50 elements, inclusive.\n# -Each element of orders will contain between 1 and 50 lowercase letters ('a' - 'z') and spaces, inclusive.\n# -Each element of orders will represent a list of desired ingredients separated by single spaces, with no leading or trailing spaces.\n# \n# \n# EXAMPLES\n# \n# 0)\n# { \"ham\", \"cheese\", \"mustard\" }\n# { \"ham cheese\" }\n# \n# Returns: 0\n# \n# I only like plain ham and cheese sandwiches, and since both ham and cheese are available, I'll take that.\n# \n# 1)\n# { \"cheese\", \"mustard\", \"lettuce\" }\n# { \"cheese ham\", \"cheese mustard lettuce\", \"ketchup\", \"beer\" }\n# \n# Returns: 1\n# \n# They've run out of ham, but I'll consider other options now.\n# \n# 2)\n# { \"cheese\", \"cheese\", \"cheese\", \"tomato\" }\n# { \"ham ham ham\", \"water\", \"pork\", \"bread\", \"cheese tomato cheese\", \"beef\" }\n# \n# Returns: 4\n# \n# Ignore any duplicate elements in the lists.\n# \n# 3)\n# { \"foo\", \"bar\", \"baz\", \"gazonk\", \"quux\", \"bat\", \"xyzzy\",\n# \"shme\", \"hukarz\", \"grault\", \"waldo\", \"bleh\" }\n# { \"kalatehas\", \"spam eggs\", \"needle haystack\", \"bleh blarg\", \"plugh\", \n# \"the best sandwich in the universe\" }\n# \n# Returns: -1\n# \n# END KAWIGIEDIT TESTING\n#Powered by KawigiEdit-pf 2.3.0!\n","sub_path":"uncategorized/SandwichBar.py","file_name":"SandwichBar.py","file_ext":"py","file_size_in_byte":5480,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"252287215","text":"import numpy as np\nimport torch\nimport torch.nn as nn\nfrom collections import OrderedDict\n\n\n# def make_divisible(v, divisor, min_val=None):\n# \"\"\"\n# This function is taken from the original tf repo.\n# It ensures that all layers have a channel number that is divisible by 8\n# It can be seen here:\n# https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet/mobilenet.py\n# :param v:\n# :param divisor:\n# :param min_val:\n# :return:\n# \"\"\"\n# if min_val is None:\n# min_val = divisor\n# new_v = max(min_val, int(v + divisor / 2) // divisor * divisor)\n# # Make sure that round down does not go down by more than 10%.\n# if new_v < 0.9 * v:\n# new_v += divisor\n# return new_v\n\nclass SEModule(nn.Module):\n REDUCTION = 4\n\n def __init__(self, channel):\n super(SEModule, self).__init__()\n\n self.channel = channel\n self.reduction = SEModule.REDUCTION\n\n num_mid = 72\n\n self.fc = nn.Sequential(OrderedDict([\n ('reduce', nn.Conv2d(self.channel, num_mid, 1, 1, 0, bias=True)),\n ('relu', nn.ReLU(inplace=True)),\n ('expand', nn.Conv2d(num_mid, self.channel, 1, 1, 0, bias=True)),\n ('h_sigmoid', Hsigmoid(inplace=True)),\n ]))\n\n def forward(self, x):\n y = x.mean(3, keepdim=True).mean(2, keepdim=True)\n y = self.fc(y)\n return x * y\n\nnet = SEModule(3)\n_ = net(torch.Tensor(1, 3, 224, 224))\ntrace_model = torch.jit.trace(net, (torch.Tensor(1, 3, 224, 224), ))\ntrace_model.save('./assets/se.jit')","sub_path":"jiangrong/jit-se.py","file_name":"jit-se.py","file_ext":"py","file_size_in_byte":1578,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"465321193","text":"import timeit\nimport tkinter as tk\nimport tracemalloc\nfrom tkinter import *\nimport tkinter.messagebox as tkMsg\nfrom tkinter import filedialog as fd\n\nimport numpy as np\nfrom func_timeout import func_timeout, FunctionTimedOut\nimport matplotlib.colors\nimport matplotlib.pyplot as plt\n\nimport Automa\nimport Constant\nimport Link\nimport SalvaRiassunto\nimport Transizione\nimport SpazioComportamentale\nimport SpazioComportamentaleOsservazione\nimport CaricaRete\n\nclass MainW(tk.Tk):\n\n def MostraReteCreata(self, NomeRete, PercorsoSalvataggio, NomiAutomi):\n NomeRete = NomeRete.split('.')[0]\n finestraCreazioneDati = tk.Toplevel(self)\n finestraCreazioneDati.title(\"Dati della nuova rete\")\n finestraCreazioneDati.configure(background=\"white\")\n\n frameRete = tk.Frame(finestraCreazioneDati)\n\n hScrollbar = tk.Scrollbar(frameRete, orient=HORIZONTAL)\n vScrollbar = tk.Scrollbar(frameRete, orient=VERTICAL)\n\n canvasRete = tk.Canvas(frameRete, yscrollcommand=vScrollbar.set, xscrollcommand=hScrollbar.set)\n vScrollbar.config(command=canvasRete.yview)\n hScrollbar.config(command=canvasRete.xview)\n\n frameRete.pack(fill=BOTH, expand=1)\n\n canvasRete = tk.Canvas(frameRete)\n canvasRete.pack(side=LEFT, fill=BOTH, expand=1)\n\n yScrollbarRete = tk.Scrollbar(frameRete, orient=VERTICAL, command=canvasRete.yview)\n yScrollbarRete.pack(side=RIGHT, fill=Y)\n xScrollbarRete = tk.Scrollbar(frameRete, orient=HORIZONTAL, command=canvasRete.xview)\n xScrollbarRete.pack(side=BOTTOM, fill=X)\n\n canvasRete.configure(yscrollcommand=yScrollbarRete.set)\n canvasRete.configure(xscrollcommand=xScrollbarRete.set)\n canvasRete.bind('<Configure>', lambda e: canvasRete.configure(scrollregion=canvasRete.bbox(\"all\")))\n\n second_frame = tk.Frame(canvasRete)\n\n canvasRete.create_window((0,0), window=second_frame, anchor=\"nw\")\n\n count = 1\n for automa in NomiAutomi:\n labelAutoma = tk.Label(second_frame, text=automa)\n labelAutoma.grid(row=count, column=0)\n\n automaImmagine = tk.PhotoImage(file=\"\" + PercorsoSalvataggio + automa + \".gv.png\")\n labelAutomaImg = tk.Label(second_frame, image=automaImmagine)\n labelAutomaImg.image = automaImmagine\n labelAutomaImg.grid(row=count, column=1)\n\n count += 1\n\n count += 1\n labelTopologia = tk.Label(second_frame, text=\"Topologia\")\n labelTopologia.grid(row=count, column=0)\n topologiaImg = tk.PhotoImage(file=\"\" + PercorsoSalvataggio + \"topologia.gv.png\")\n labelTopologiaImg = tk.Label(second_frame, image=topologiaImg)\n labelTopologiaImg.image = topologiaImg\n labelTopologiaImg.grid(row=count, column=1)\n\n count += 1\n labelSpazioComportamentale = tk.Label(second_frame, text=\"Spazio Comportamentale\")\n labelSpazioComportamentale.grid(row=count, column=0)\n spazioComportamentaleImg = tk.PhotoImage(file=\"\" + PercorsoSalvataggio + NomeRete + \".gv.png\")\n labelSpazioComportamentaleImg= tk.Label(second_frame, image=spazioComportamentaleImg)\n labelSpazioComportamentaleImg.image = spazioComportamentaleImg\n labelSpazioComportamentaleImg.grid(row=count, column=1)\n\n count += 1\n labelSpazioComportamentalePotato = tk.Label(second_frame, text=\"Spazio Comportamentale Potato\")\n labelSpazioComportamentalePotato.grid(row=count, column=0)\n spzCompPotatoImg = tk.PhotoImage(file=\"\" + PercorsoSalvataggio + NomeRete + \"Pot.gv.png\")\n labelSpazioComportamentalePotatoImg = tk.Label(second_frame, image=spzCompPotatoImg)\n labelSpazioComportamentalePotatoImg.image = spzCompPotatoImg\n labelSpazioComportamentalePotatoImg.grid(row=count, column=1)\n\n count += 1\n labelSpzPotatoRidenominato = tk.Label(second_frame, text=\"Spazio Comportamentale Potato e Ridenominato\")\n labelSpzPotatoRidenominato.grid(row=count, column=0)\n spzCompPotRidenImg = tk.PhotoImage(file=\"\" + PercorsoSalvataggio + NomeRete + \"PotRid.gv.png\")\n labelSpzPotRidenImg = tk.Label(second_frame, image=spzCompPotRidenImg)\n labelSpzPotRidenImg.image = spzCompPotRidenImg\n labelSpzPotRidenImg.grid(row=count, column=1)\n\n def CreaRete(self):\n\n def apriAutoma():\n path = fd.askopenfilename()\n labelAutomaPath.config(text=path)\n if path != \"\":\n buttonLink['state'] = 'normal'\n\n def apriLink():\n path = fd.askopenfilename()\n labelLinkPath.config(text=path)\n if path != \"\":\n buttonTransizioni['state'] = 'normal'\n\n def apriTransizione():\n path = fd.askopenfilename()\n labelTransizioniPath.config(text=path)\n if path != \"\":\n buttonSalvaRete['state'] = 'normal'\n\n def controlloOsservazione(lista_transizioni):\n osservazione_lineare = entryOsservazione.get()\n osservazione_lineare = osservazione_lineare.split(',')\n for oss in osservazione_lineare:\n if not str(oss).isalnum():\n tkMsg.showerror(title=\"Osservazione errata\",\n message=\"L'osservazione lineare contiene caratteri non ammessi\")\n return 1\n trovato = False\n for transizione in lista_transizioni:\n if transizione.observability == oss:\n trovato = True\n break\n if not trovato:\n tkMsg.showerror(title=\"Errore osservazione\",\n message=\"L'osservazione lineare contiene elementi non presenti nello spazio\")\n return 1\n return 0\n\n def importaFile(AutomaDaCaricare, LinkDaCaricare, TransizioniDaCaricare, NomeRete, PercorsoSalvataggio):\n # listaMem, listaPic):\n #Importo gli automi\n automi = []\n value = Automa.Automa.importaAutomiDaFile(automi, AutomaDaCaricare)\n if value != 0:\n # Qualcosa è andato storto\n tkMsg.showerror(title=\"Errore\", message=\"Qualcosa è andato storto, ricontrollare il file degli automi inserito\")\n return -1, -1\n # Disegno degli automi\n nomiAutomi = []\n for automa in automi:\n nomiAutomi.append(automa.name)\n automa.disegnaAutoma(automa.edges, automa.final_states, PercorsoSalvataggio)\n # Importo dei link\n links = []\n value = Link.importaLinkDaFile(links, LinkDaCaricare)\n if value != 0:\n tkMsg.showerror(title=\"Errore\", message=\"Qualcosa è andato storto, ricontrollare il file dei link inserito\")\n return -1, -1\n # Disegno della topologia\n Link.Link.disegnaTopologia(links, PercorsoSalvataggio);\n # Importo delle transizioni\n lista_transizioni = []\n transizioni = []\n value = Transizione.importaTransizioniDaFile(lista_transizioni, transizioni, TransizioniDaCaricare)\n if value != 0:\n tkMsg.showerror(title=\"Errore\", message=\"Qualcosa è andato storto, ricontrollare il file delle transizioni inserito\")\n return -1, -1\n #Controllo che sia stata inserita un'osservazione lineare (se non è stata inserita allora non è richiesta)\n if entryOsservazione.var.get() == \"\":\n # Creazione dello spazio comportamentale\n lista_stati = []\n lista_link = []\n stato_comportamentale = []\n arco_comportamentale = []\n try:\n # tracemalloc.start()\n func_timeout(Constant.TIMEOUT, func=SpazioComportamentale.creaSpazioComportamentale,\n args=(automi, transizioni, links, lista_stati,\n lista_link, lista_transizioni, stato_comportamentale, arco_comportamentale))\n # first_item, second_item = tracemalloc.get_traced_memory()\n # listaMem.append(first_item)\n # listaPic.append(second_item)\n # tracemalloc.stop()\n except FunctionTimedOut:\n tkMsg.showerror(title=Constant.titleTimeOut, message=Constant.messageTimeOut)\n return -1, -1\n # Disegno dello spazio comportamentale\n # tracemalloc.start()\n SpazioComportamentale.ArcoComportamentale.disegnaSpazioComportamentale(arco_comportamentale,\n PercorsoSalvataggio + NomeRete.split('.')[0])\n # first_item, second_item = tracemalloc.get_traced_memory()\n # listaMem.append(first_item)\n # listaPic.append(second_item)\n # tracemalloc.stop()\n # Potatura\n try:\n # tracemalloc.start()\n func_timeout(Constant.TIMEOUT, func=SpazioComportamentale.Potatura,\n args=(stato_comportamentale, arco_comportamentale))\n # first_item, second_item = tracemalloc.get_traced_memory()\n # listaMem.append(first_item)\n # listaPic.append(second_item)\n # tracemalloc.stop()\n except FunctionTimedOut:\n tkMsg.showerror(title=Constant.titleTimeOut, message=Constant.messageTimeOut)\n return -1, -1\n\n # Ridenominazione\n stato_comportamentale_ridenominato = []\n arco_comportamentale_ridenominato = arco_comportamentale.copy()\n # tracemalloc.start()\n SpazioComportamentale.Ridenomina(stato_comportamentale, stato_comportamentale_ridenominato,\n arco_comportamentale_ridenominato)\n # first_item, second_item = tracemalloc.get_traced_memory()\n # listaMem.append(first_item)\n # listaPic.append(second_item)\n # tracemalloc.stop()\n\n # stato_comportamentale_ridenominato, arco_comportamentale_ridenominato = SpazioComportamentale.Ridenomina(\n # stato_comportamentale, stato_comportamentale_ridenominato, arco_comportamentale_ridenominato)\n\n # Costruzione e salvataggio del sommario\n summary = SalvaRiassunto.PreparaSommario(automi, links, lista_transizioni,\n stato_comportamentale_ridenominato, arco_comportamentale_ridenominato, osservato=False)\n SalvaRiassunto.Salva(PercorsoSalvataggio + NomeRete.split('.')[0], summary)\n\n # Salvataggio su txt dello spazio comportamentale (normale)\n SpazioComportamentale.ArcoComportamentale.salvaSpazioComportamentale(arco_comportamentale, stato_comportamentale,\n PercorsoSalvataggio + NomeRete, labelAutomaPath.cget(\"text\"), labelLinkPath.cget(\"text\"),labelTransizioniPath.cget(\"text\"))\n\n # Disegno dello spazio comportamentale potato\n nomeRetePotata = PercorsoSalvataggio + NomeRete.split('.')[0] + \"Pot\"\n\n # tracemalloc.start()\n SpazioComportamentale.ArcoComportamentale.disegnaSpazioComportamentale(arco_comportamentale,\n nomeRetePotata)\n # first_item, second_item = tracemalloc.get_traced_memory()\n # listaMem.append(first_item)\n # listaPic.append(second_item)\n # tracemalloc.stop()\n # Disegno dello spazio comportamentale potato e ridenominato\n nomeReteRidenominata = PercorsoSalvataggio + NomeRete.split('.')[0] + \"PotRid\"\n # tracemalloc.start()\n SpazioComportamentale.ArcoComportamentale.disegnaSpazioComportamentaleRidenominato(\n arco_comportamentale_ridenominato, nomeReteRidenominata)\n # first_item, second_item = tracemalloc.get_traced_memory()\n # listaMem.append(first_item)\n # listaPic.append(second_item)\n # tracemalloc.stop()\n\n return NomeRete, nomiAutomi\n else:\n esito = controlloOsservazione(lista_transizioni)\n if esito != 0:\n return -1, -1\n osservazione_lineare = entryOsservazione.get()\n osservazioneLineare = osservazione_lineare.split(',')\n\n lista_stati_oss = []\n lista_link_oss = []\n stato_comportamentale_oss = []\n arco_comportamentale_oss = []\n try:\n # tracemalloc.start()\n func_timeout(Constant.TIMEOUT, func=SpazioComportamentaleOsservazione.creaSpazioComportamentaleOsservazioneLineare,\n args=(automi, transizioni, links, lista_stati_oss, lista_link_oss, lista_transizioni,\n stato_comportamentale_oss, arco_comportamentale_oss, osservazioneLineare))\n # first_item, second_item = tracemalloc.get_traced_memory()\n # listaMem.append(first_item)\n # listaPic.append(second_item)\n # tracemalloc.stop()\n except FunctionTimedOut:\n tkMsg.showerror(title=Constant.titleTimeOut, message=Constant.messageTimeOut)\n return -1, -1\n '''\n Controllo che la rete comportamentale prodotta dall'osservazione abbia stati terminali\n '''\n terminale = False\n for stato in stato_comportamentale_oss:\n if getattr(stato, 'finale'):\n terminale = True\n break\n if not terminale:\n tkMsg.showerror(title=\"Errore osservazione\",\n message=\"L'osservazione inserita non produce una rete con stati terminali, correggere \"\n \"l'input, per favore.\")\n return -1, -1\n\n max_indice = len(osservazioneLineare)\n titoloOss = \"\".join(osservazioneLineare)\n\n # Disegno dello spazio comportamentale relativo ad un'osservazione lineare\n nome_oss = NomeRete.split('.')[0] + \"Oss\" + titoloOss\n # tracemalloc.start()\n SpazioComportamentaleOsservazione.ArcoComportamentaleOsservazione.disegnaSpazioComportamentaleIndiceOsservazione(\n arco_comportamentale_oss, PercorsoSalvataggio + nome_oss)\n # first_item, second_item = tracemalloc.get_traced_memory()\n # listaMem.append(first_item)\n # listaPic.append(second_item)\n # tracemalloc.stop()\n\n # Potatura Osservazione\n try:\n # tracemalloc.start()\n func_timeout(Constant.TIMEOUT, func=SpazioComportamentaleOsservazione.PotaturaOss,\n args=(stato_comportamentale_oss, arco_comportamentale_oss))\n # first_item, second_item = tracemalloc.get_traced_memory()\n # listaMem.append(first_item)\n # listaPic.append(second_item)\n # tracemalloc.stop()\n except FunctionTimedOut:\n tkMsg.showerror(title=Constant.titleTimeOut, message=Constant.messageTimeOut)\n return -1, -1\n\n # Ridenominazione Osservazione\n stato_comportamentale_ridenominato_oss = []\n arco_comportamentale_ridenominato_oss = arco_comportamentale_oss.copy()\n # tracemalloc.start()\n SpazioComportamentaleOsservazione.RidenominaOss(stato_comportamentale_oss,\n stato_comportamentale_ridenominato_oss, arco_comportamentale_ridenominato_oss, max_indice)\n # first_item, second_item = tracemalloc.get_traced_memory()\n # listaMem.append(first_item)\n # listaPic.append(second_item)\n # tracemalloc.stop()\n\n # Costruzione e salvataggio del sommario\n summary = SalvaRiassunto.PreparaSommario(automi, links, lista_transizioni,\n stato_comportamentale_ridenominato_oss, arco_comportamentale_ridenominato_oss, osservato=True)\n SalvaRiassunto.Salva(PercorsoSalvataggio + nome_oss, summary)\n if summary == -1:\n # Non può avvenire più perché ora se esiste lo elimino manualmente\n print(\"Il file esiste già\")\n\n # Disegno dello spazio comportamentale relativo ad un'osservazione lineare potato\n nome_pot_oss = PercorsoSalvataggio + NomeRete.split('.')[0] + \"Oss\" + titoloOss + \"Pot\"\n # tracemalloc.start()\n SpazioComportamentaleOsservazione.ArcoComportamentaleOsservazione.disegnaSpazioComportamentaleIndiceOsservazione(\n arco_comportamentale_oss, nome_pot_oss)\n # first_item, second_item = tracemalloc.get_traced_memory()\n # listaMem.append(first_item)\n # listaPic.append(second_item)\n # tracemalloc.stop()\n # Disegno dello spazio comportamentale relativo ad un'osservazione lineare potato e ridenominato\n nomeReteRidenominataOss = PercorsoSalvataggio + NomeRete.split('.')[0] + \"Oss\" + titoloOss + \"PotRid\"\n # tracemalloc.start()\n SpazioComportamentaleOsservazione.ArcoComportamentaleOsservazione.disegnaSpazioComportamentaleRidenominatoOss(\n arco_comportamentale_ridenominato_oss, nomeReteRidenominataOss)\n # first_item, second_item = tracemalloc.get_traced_memory()\n # listaMem.append(first_item)\n # listaPic.append(second_item)\n # tracemalloc.stop()\n\n # Salvo la rete dello spazio comportamentale osservato\n SpazioComportamentaleOsservazione.ArcoComportamentaleOsservazione.salvaSpazioComportamentaleOss(\n arco_comportamentale_oss, stato_comportamentale_oss,\n PercorsoSalvataggio + NomeRete.split('.')[0] + \"Oss\" + titoloOss,\n labelAutomaPath.cget(\"text\"), labelLinkPath.cget(\"text\"), labelTransizioniPath.cget(\"text\"),\n osservazioneLineare)\n return nome_oss, nomiAutomi\n\n # Questo metodo fa dei controlli sui file per vedere se esistono\n def confermaCreazione():\n # salvo il percorso del punto in cui salvare\n nome_file = fd.asksaveasfilename(title=\"NuovaRete\", defaultextension=\".txt\")\n if nome_file is None or nome_file == \"\":\n return\n path_salvataggio = nome_file.split('/')\n nome_rete = path_salvataggio.pop()\n path_salvataggio = \"/\".join(path_salvataggio) + \"/\"\n\n if nome_rete is None:\n tkMsg.showerror(title=\"Errore\",\n message=\"Inserire un nome valido\")\n return\n\n AutomaDaCaricare = labelAutomaPath.cget(\"text\")\n try:\n with open(AutomaDaCaricare) as f:\n pass\n except Exception:\n tkMsg.showerror(title=\"Errore\", message=\"Il file degli automi inserito non è stato trovato\")\n return\n LinkDaCaricare = labelLinkPath.cget(\"text\")\n try:\n with open(LinkDaCaricare) as f:\n pass\n except Exception:\n tkMsg.showerror(title=\"Errore\", message=\"Il file dei link inserito non è stato trovato\")\n return\n TransizioniDaCaricare = labelTransizioniPath.cget(\"text\")\n try:\n with open(TransizioniDaCaricare) as f:\n pass\n except Exception:\n tkMsg.showerror(title=\"Errore\", message=\"Il file delle transizioni inserito non è stato trovato\")\n return\n\n # listaTempi = timeit.repeat(stmt=lambda: importaFile(AutomaDaCaricare, LinkDaCaricare, TransizioniDaCaricare,\n # nome_rete, path_salvataggio), setup='pass', number=1, repeat=100)\n # x = np.linspace(0, len(listaTempi), 100)\n # plt.scatter(x, listaTempi)\n # plt.xlabel(\"Esecuzioni\")\n # plt.ylabel(\"Tempi\")\n # plt.savefig(\"C:/Users/Alessandro/Desktop/ReteComportamentale/\" + nome_rete + \".png\", dpi=100)\n # plt.show()\n #\n # avg = sum(listaTempi) / len(listaTempi)\n # print(avg)\n\n nomeRete, nomiAutomi = importaFile(AutomaDaCaricare, LinkDaCaricare, TransizioniDaCaricare, nome_rete,\n path_salvataggio)\n\n # listaAvg = []\n # listaPic = []\n # listaColori = ['#d0ff8f', '#94ff00', '#46ff03', '#4cb543', '#35732f', '#053800']\n # i = 0\n # while i<10:\n # nomeRete, nomiAutomi = importaFile(AutomaDaCaricare, LinkDaCaricare, TransizioniDaCaricare, nome_rete,\n # path_salvataggio, listaAvg, listaPic)\n # i += 1\n # barlist = plt.bar(range(0, len(listaAvg)), listaAvg, edgecolor='black', linewidth=1)\n # i = 0\n # for i in range(len(barlist)):\n # barlist[i].set_color(matplotlib.colors.hex2color(listaColori[i % 6]))\n # i += 1\n # plt.xlabel(\"Casi\")\n # plt.ylabel(\"Occupazione Media - byte\")\n # plt.savefig(\"C:/Users/Alessandro/Desktop/ReteComportamentale/\" + nome_rete + \"Memoria.png\", dpi=100)\n # plt.show()\n # barlist = plt.bar(range(0, len(listaPic)), listaPic, edgecolor='black', linewidth=1)\n # i = 0\n # for i in range(len(barlist)):\n # barlist[i].set_color(matplotlib.colors.hex2color(listaColori[i % 6]))\n # i += 1\n # plt.xlabel(\"Casi\")\n # plt.ylabel(\"Occupazione Picchi - byte\")\n # plt.savefig(\"C:/Users/Alessandro/Desktop/ReteComportamentale/\" + nome_rete + \"Picchi.png\", dpi=100)\n # plt.show()\n\n if nomeRete == -1 and nomiAutomi == -1: # C'è stato un errore in importaFile --> esco\n return\n MainW.MostraReteCreata(self, nomeRete, path_salvataggio, nomiAutomi)\n\n finestraCreazione = tk.Toplevel(self)\n finestraCreazione.resizable(False, False)\n finestraCreazione.title(\"Crea una nuova rete\")\n finestraCreazione.configure(background=\"white\")\n\n indicazioniCreazione = \"Menu creazione rete - Inserire i nomi dei file txt per importarli.\\n\" \\\n \"Una volta creata la rete comportamentale i file degli automi, link e\\n\" \\\n \"transizioni non andranno più spostati perché i loro percorsi saranno salvati.\\n\"\n etichettaAvvioCreazione = tk.Label(finestraCreazione, text=indicazioniCreazione, bg=\"white\", font=(\"Helvetica\", 10))\n etichettaAvvioCreazione.grid(row=0, column=0, columnspan=2)\n\n buttonAutoma = tk.Button(finestraCreazione, text=\"Apri automa\", command=apriAutoma)\n buttonAutoma.grid(row=1, column=0)\n labelAutomaPath = tk.Label(finestraCreazione, text=\"\")\n labelAutomaPath.grid(row=1, column=1)\n\n buttonLink = tk.Button(finestraCreazione, text=\"Apri Link\", state=tk.DISABLED, command=apriLink)\n buttonLink.grid(row=2, column=0)\n labelLinkPath = tk.Label(finestraCreazione, text=\"\")\n labelLinkPath.grid(row=2, column=1)\n\n buttonTransizioni = tk.Button(finestraCreazione, text=\"Apri Transizione\", state=tk.DISABLED, command=apriTransizione)\n buttonTransizioni.grid(row=3, column=0)\n labelTransizioniPath = tk.Label(finestraCreazione, text=\"\")\n labelTransizioniPath.grid(row=3, column=1)\n\n labelOsservazione = tk.Label(finestraCreazione,\n text=\"Inserisci un'osservazione lineare, se la desideri, o lascia altrimenti vuoto.\\n\"\n \"L'osservazione lineare deve essere inserita usando la virgola come separatore tra\\n\"\n \"ogni singola osservabilità. Sono ammessi solo caratteri alfanumerici.\")\n labelOsservazione.grid(row=4, column=0, columnspan=2)\n entryOsservazione = tk.Entry(finestraCreazione, width=100)\n entryOsservazione.var = tk.StringVar()\n entryOsservazione['textvariable'] = entryOsservazione.var\n entryOsservazione.grid(row=5, column=0, columnspan=2)\n\n buttonSalvaRete = tk.Button(finestraCreazione, text=\"Salva Rete\", state=\"disabled\", command=confermaCreazione)\n buttonSalvaRete.grid(row=6, column=0)\n indietroButton = tk.Button(finestraCreazione, text=\"Chiudi\", command=finestraCreazione.destroy)\n indietroButton.grid(row=6, column=1)\n\n finestraCreazione.mainloop()\n\n def __init__(self, parent):\n tk.Tk.__init__(self, parent)\n self.parent = parent\n self.FinestraPrincipale()\n\n def FinestraPrincipale(self):\n\n self.title(\"Pagina Principale - Algoritmi e Strutture Dati\")\n self.configure(background=\"white\")\n istruzioniBase = \"Questo programma aiuta nella creazione e visualizzazione di reti di automi finiti.\\n\" \\\n \"Sarà possibile caricare una rete già esistente o crearne una nuova. In questo caso \\n\" \\\n \"si ricorda che è necessario avere a disposizione i file degli automi dei link e le \" \\\n \"specifiche delle transizioni.\"\n\n etichettaAvvio = tk.Label(self, text=istruzioniBase, bg=\"white\", font=(\"Helvetica\", 12))\n etichettaAvvio.pack()\n\n creaReteButton = tk.Button(self, text=\"Crea una rete\", command=self.CreaRete)\n creaReteButton.pack()\n\n caricaReteButton = tk.Button(self, text=\"Carica una rete\", command=lambda : CaricaRete.CaricaRete.CaricaRete(self))\n caricaReteButton.pack()\n\n chiudiButton = tk.Button(self, text=\"Esci\", command=self.destroy).pack()\n\nif __name__==\"__main__\":\n app = MainW(None)\n app.mainloop()\n","sub_path":"ASD/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":26850,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"8926262","text":"import requests\r\nfrom bs4 import BeautifulSoup\r\nimport pandas as pd\r\n\r\n#request information from the website (returns 200, which is good)\r\nr = requests.get('https://whnt.com/weather/').text\r\n#get actual content from website using our url (r) and html parser (lxml)\r\nsoup = BeautifulSoup(r, 'lxml')\r\n\r\ndays = [] #list for days\r\nforecast = [] #list for weather\r\nhighlow = [] #list for high/low temperatures\r\nchanceofrain = [] #list for chance of rain\r\ni = 0 #variable to increment to print out each days forecast\r\n\r\n#pulls each day from webpage into our list\r\nfor day in soup.find_all(\"div\", class_=\"date\"):\r\n days.append(day.text)\r\n\r\n#pulls each day's forecast into out list\r\nfor weather in soup.find_all(\"strong\", class_=\"day-description\"):\r\n forecast.append(weather.text)\r\n\r\n#pulls each day's high/low temps into our list (strips extra \\t and \\n)\r\nfor highnlow in soup.find_all(\"div\", class_=\"day-hi-low\"):\r\n highlow.append(highnlow.text.strip('\\t\\n'))\r\n\r\n#pulls each day's chance of rain into our list (strips extra \\n and \\t and also\r\n#just reads where the precipitation chance is as opposed to wind as well\r\nfor precip in soup.find_all(\"div\", class_=\"day-details\"):\r\n chanceofrain.append(precip.text[8:11].strip('\\n\\t'))\r\n\r\n#LONG line, ***NEEDS FIXING WITH A LOOP OR SOMETHING***\r\ndata = {'Weather:':[forecast[0], forecast[1], forecast[2], forecast[3], forecast[4], forecast[5], forecast[6]], 'LO/HI:':[highlow[0], highlow[1], highlow[2], highlow[3], highlow[4], highlow[5], highlow[6]], 'Chance of Rain:':[chanceofrain[0], chanceofrain[1], chanceofrain[2], chanceofrain[3], chanceofrain[4], chanceofrain[5], chanceofrain[6]]}\r\n\r\ndf = pd.DataFrame(data, columns = ['Weather:', 'LO/HI:', 'Chance of Rain:'], index = days)\r\nprint(df)\r\n\r\nexit = input()\r\n","sub_path":"WeatherApp.py","file_name":"WeatherApp.py","file_ext":"py","file_size_in_byte":1767,"program_lang":"python","lang":"en","doc_type":"code","dataset":"code-starcoder2","pt":"68"}
+{"seq_id":"79132496","text":"from __future__ import print_function\n\nimport os\nimport json\nimport base64\nfrom multiprocessing import Process\nimport hashlib\nimport webbrowser\nimport warnings\n\nfrom .GanjaScene import GanjaScene\n\nfrom .color import Color\n\nCEFAVAILABLE = False\ntry:\n from .cefwindow import *\n CEFAVAILABLE = True\nexcept:\n warnings.warn(\n 'Failed to import cef_gui, cef functions will be unavailable',\n stacklevel=2)\n\nJUPYTERAVAILABLE = False\ntry:\n from IPython.display import display, Javascript\n from IPython import get_ipython\n JUPYTERAVAILABLE = True\nexcept:\n warnings.warn(\n 'Failed to import ipython, notebook rendering will be unavailable',\n stacklevel=2)\n\n\ndef html_to_data_uri(html):\n html = html.encode(\"utf-8\", \"replace\")\n b64 = base64.b64encode(html).decode(\"utf-8\", \"replace\")\n ret = \"data:text/html;base64,{data}\".format(data=b64)\n return ret\n\n\ndef read_ganja():\n dir_name = os.path.dirname(os.path.abspath(__file__))\n ganja_filename = dir_name + '/static/ganja.js/ganja.js'\n with open(ganja_filename, 'r', encoding='utf8') as ganja_file:\n output = ganja_file.read()\n return output\n\n\ndef generate_notebook_js(scene, sig=None, grid=True, scale=1.0, gl=True,\n default_color=Color.DEFAULT, default_static=False):\n script_json = _to_scene_string(scene, default_color=default_color, default_static=default_static)\n if sig is not None:\n p = (sig > 0).sum().item() # convert to json-compatible scalar\n q = (sig < 0).sum().item() # convert to json-compatible scalar\n r = len(sig) - p - q\n else:\n p = 4\n q = 1\n r = 0\n mv_length = str(2 ** (p + q + r))\n\n # not the best way to test conformal, as it prevents non-euclidean geometry\n if q != 0:\n conformal = True\n else:\n conformal = False\n\n if (p, q, r) in [(4, 1, 0), (3, 1, 0), (3, 0, 0), (3, 0, 1)]:\n if p - q == 2:\n gl = False # 2d\n opts = dict(\n p=p, q=q, r=r, gl=gl, conformal=conformal, grid=grid, scale=scale,\n mv_length=mv_length\n )\n js = read_ganja()\n js += \"\"\"\n // take a closure on element before the next cell replaces it\n (function(element) {\n (requirejs||require)(['Algebra'], function(Algebra) {\n var opts = \"\"\" + json.dumps(opts) + \"\"\"; // injected from python\n var output = Algebra({p: opts.p, q: opts.q, r: opts.r, baseType: Float64Array}).inline((opts)=>{\n var data = \"\"\" + script_json + \"\"\"; // injected from python\n\n // When we get a file, we load and display.\n var canvas;\n var h=0, p=0;\n // convert arrays of floats back to CGA elements.\n data = data.map(x=>x.length==opts.mv_length?new Element(x):x);\n // add the graph to the page.\n canvas = this.graph(data, {gl: opts.gl, conformal: opts.conformal, grid: opts.grid, scale: opts.scale, useUnnaturalLineDisplayForPointPairs: true});\n canvas.options.h = h;\n canvas.options.p = p;\n // make it big.\n canvas.style.width = '100%';\n canvas.style.height = '50vh';\n return canvas;\n })(opts);\n element.append(output);\n\n var a = document.createElement(\"button\");\n var t = document.createTextNode(\"\\N{FLOPPY DISK} Save\");\n a.appendChild(t);\n function screenshot(){\n //output.width = 1920; output.height = 1080;\n output.update(output.value);\n output.toBlob(function(blob) {\n var url = URL.createObjectURL(blob);\n window.open(url, '_blank');\n });\n }\n window.addEventListener('resize', function() {\n output.update(output.value);\n });\n a.onclick = screenshot\n var butnelem = element.append(a);\n });\n\n })(element);\n \"\"\"\n else:\n raise ValueError('Algebra not yet supported')\n return Javascript(js)\n\n\ndef generate_full_html(scene, sig=None, grid=True, scale=1.0, gl=True,\n default_color=Color.DEFAULT, default_static=False):\n script_json = _to_scene_string(scene, default_color=default_color, default_static=default_static)\n if sig is not None:\n p = (sig > 0).sum()\n q = (sig < 0).sum()\n r = len(sig) - p - q\n else:\n p = 4\n q = 1\n r = 0\n sig_short = '%i,%i,%i' % (p, q, r)\n print(sig_short)\n mv_length = str(2 ** (p + q + r))\n\n # not the best way to test conformal, as it prevents non-euclidean geometry\n conformal = 'false'\n if q!=0:\n conformal = 'true'\n\n if sig_short in ['4,1,0', '3,0,0', '3,0,1']:\n if grid:\n gridstr = 'true'\n else:\n gridstr = 'false'\n scalestr = str(scale)\n\n script_string = \"\"\"\n Algebra(\"\"\"+sig_short+\"\"\",()=>{\n var canvas = this.graph((\"\"\" + script_json + \"\"\").map(x=>x.length==\"\"\"+mv_length+\"\"\"?new Element(x):x),\n {conformal:\"\"\"+conformal+\"\"\",gl:\"\"\"+str(gl).lower()+\"\"\",grid:\"\"\"+gridstr+\"\"\",scale:\"\"\"+scalestr+\"\"\",useUnnaturalLineDisplayForPointPairs:true});\n canvas.style.width = '100vw';\n canvas.style.height = '100vh';\n document.body.appendChild(canvas);\n });\n \"\"\"\n full_html = \"\"\"<!DOCTYPE html>\n <html lang=\"en\" style=\"height:100%;\">\n <HEAD>\n <meta charset=\"UTF-8\">\n <title>pyganja\n \n \n \n \n \n