diff --git "a/4674.jsonl" "b/4674.jsonl" new file mode 100644--- /dev/null +++ "b/4674.jsonl" @@ -0,0 +1,1002 @@ +{"seq_id":"18388872926","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Oct 7 11:15:20 2018\n\n@author: yashkumararora\n\"\"\"\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom IPython.display import Image, display \ntrain = pd.read_csv('train.csv')\ndisplay(train.head())\ntrain = train.set_index('PassengerId')\ntest = pd.read_csv('test.csv')\ndisplay(test.head())\ntrain.shape\ntrain.head()\n\ndatadict = pd.DataFrame(train.dtypes)\ndatadict\n\ndatadict['MissingVal'] = train.isnull().sum()\ndatadict\n\ndatadict['NUnique']=train.nunique()\ndatadict\n\ndatadict['Count']=train.count()\ndatadict\n\ndatadict = datadict.rename(columns={0:'DataType'})\ndatadict\n\ntrain.describe(include=['object'])\n\ntrain.describe(include=['number'])\n\ntrain.Survived.value_counts(normalize=True)\n\nfigbi, axesbi = plt.subplots(2, 2, figsize=(16, 10))\ntrain.groupby('Pclass')['Survived'].mean().plot(kind='barh',ax=axesbi[0,0],xlim=[0,1])\ntrain.groupby('Sex')['Survived'].mean().plot(kind='barh',ax=axesbi[0,1],xlim=[0,1])\nsns.boxplot(x=\"Survived\", y=\"Age\", data=train,ax=axesbi[1,0])\nsns.boxplot(x=\"Survived\", y=\"Fare\", data=train,ax=axesbi[1,1])\n'''\nSummary\n1: We can clearly visualize that male survial rates is around 20% where as female survial rate is about 75% which suggests that gender has a strong relationship with the survival rates.\n2: There is also a marginal relationship between the fare and survial rate.\n3: There is also a clear relationship between Pclass and the survival by referring to first plot below. Passengers on Pclass1 had a better survial rate of approx 60% whereas passengers on pclass3 had the worst survial rate of approx 22%\n4. There is also a clear relationship between the age of the passengers i.e. children are given more preference than adults\n5: I have quantified the above relationships further in the last statsical modelling section\n'''","repo_name":"arora-yash/Data-Visualisation","sub_path":"titanic visualization.py","file_name":"titanic visualization.py","file_ext":"py","file_size_in_byte":1876,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"14565506076","text":"from typing import List\n\n\nclass Solution:\n def sortArrayByParity(self, nums: List[int]) -> List[int]:\n odd, even = 0, len(nums) - 1\n while odd < even:\n while odd < even and nums[odd] % 2 == 0:\n odd += 1\n while odd < even and nums[even] % 2 == 1:\n even -= 1\n if odd < even:\n nums[odd], nums[even] = nums[even], nums[odd]\n odd += 1\n even -= 1\n return nums\n\n\nif __name__ == '__main__':\n print(Solution().sortArrayByParity(nums=[0, 1]))\n","repo_name":"ccctw-ma/leetcode","sub_path":"src/Easy/ArrayTest/sortArrayByParity.py","file_name":"sortArrayByParity.py","file_ext":"py","file_size_in_byte":568,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"21236603849","text":"from enum import Enum, IntEnum\n\n\nclass SleepTime(IntEnum):\n SHORT_SLEEP_TIME = 2\n LONG_SLEEP_TIME = 5\n\n\nclass ErrorMessage(Enum):\n FACEBOOK_PAGE_OPEN_ERROR = \"Could not open the Facebook login page.\"\n FACEBOOK_LOGIN_ERROR= \"Could not login to the Facebook account.\"\n START_PLAYING_ERROR = \"Could not access the playing page.\"\n SCRAPE_ERROR = \"Could not scrape the player stats.\"\n\nclass Mode(Enum):\n NUMBER_FIVE = \"Number_Five\"\n AVERAGE = \"Average\"","repo_name":"kyu-kuanwei/nba_prediction","sub_path":"src/utils/enum.py","file_name":"enum.py","file_ext":"py","file_size_in_byte":471,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"74366680402","text":"from functools import reduce\nimport itertools\nimport sys\nfrom dataclasses import dataclass\n\n\n@dataclass\nclass Item:\n name: str\n cost: int\n damage: int\n armor: int\n\n\nweapons = [\n Item('Dagger', 8, 4, 0),\n Item('Shortsword', 10, 5, 0),\n Item('Warhammer', 25, 6, 0),\n Item('Longsword', 40, 7, 0),\n Item('Greataxe', 74, 8, 0),\n]\n\narmors = [\n Item(\"Leather\", 13, 0, 1),\n Item(\"Chainmail\", 31, 0, 2),\n Item(\"Splintmail\", 53, 0, 3),\n Item(\"Bandedmail\", 75, 0, 4),\n Item(\"Platemail\", 102, 0, 5)\n]\n\nrings = [\n Item(\"Damage + 1\", 25, 1, 0),\n Item(\"Damage + 2\", 50, 2, 0),\n Item(\"Damage + 3\", 100, 3, 0),\n Item(\"Defense + 1\", 20, 0, 1),\n Item(\"Defense + 2\", 40, 0, 2),\n Item(\"Defense + 3\", 80, 0, 3)\n]\n\n\n@dataclass\nclass Character:\n hitPoints: int\n damage: int\n armor: int\n\n @staticmethod\n def from_lines(lines):\n return Character(\n int(lines[0].split(':')[1]),\n int(lines[1].split(':')[1]),\n int(lines[2].split(':')[1]),\n )\n\n def copy(self):\n return Character(self.hitPoints, self.damage, self.armor)\n\n def add_item(self, item: Item | None):\n if item is None:\n return\n\n self.damage += item.damage\n self.armor += item.armor\n\n\ndef simulate(me: Character, enemy: Character) -> bool:\n while True:\n enemy.hitPoints -= max(1, me.damage - enemy.armor)\n if enemy.hitPoints <= 0:\n return True\n me.hitPoints -= max(1, enemy.damage - me.armor)\n if me.hitPoints <= 0:\n return False\n\n\nlines = sys.stdin.read().splitlines()\n\nenemy = Character.from_lines(lines)\nme = Character(100, 0, 0)\n\nmin_cost = None\nmax_cost = None\n\nfor weapon in weapons:\n for armor in [None, *armors]:\n for ring1, ring2 in itertools.combinations([None, None, *rings], 2):\n tmp_me = me.copy()\n tmp_me.add_item(weapon)\n tmp_me.add_item(armor)\n tmp_me.add_item(ring1)\n tmp_me.add_item(ring2)\n\n items = [weapon, armor, ring1, ring2]\n non_nulls = [x for x in items if x is not None]\n cost = reduce(lambda acc, item: acc + item.cost, non_nulls, 0)\n\n if simulate(tmp_me, enemy.copy()):\n if min_cost is None or cost < min_cost:\n min_cost = cost\n else:\n if max_cost is None or cost > max_cost:\n max_cost = cost\n\n\nprint(min_cost)\nprint(max_cost)\n","repo_name":"Zeko369/Advent-of-code-2015","sub_path":"day-21/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":2493,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"12783327272","text":"from urllib import request, parse\nfrom fake_useragent import UserAgent\nimport json,pymysql,time\n\n\ndef lagouspider(url, formdata, headers):\n \"\"\"\n\n :param url: 目标url\n :param formdata: 表单参数\n :param headers: 请求头\n :return:\n \"\"\"\n formdata = parse.urlencode(formdata).encode('Utf-8')\n req = request.Request(url, headers=headers, data=formdata)\n response = request.urlopen(req)\n result = response.read().decode('Utf-8')\n return result\n\n\ndef load_page_data(url, formdata, headers):\n response = lagouspider(url, formdata, headers)\n data = json.loads(response)\n if data[\"success\"] == True:\n print(\"请求成功\")\n postionJobs = data[\"content\"][\"positionResult\"][\"result\"]\n for jobinfo in postionJobs:\n jobdata = {}\n jobdata[\"positionName\"] = jobinfo[\"positionName\"]\n jobdata[\"formatCreateTime\"] = jobinfo[\"formatCreateTime\"]\n jobdata[\"companyShortName\"] = jobinfo[\"companyShortName\"]\n jobdata[\"salary\"] = jobinfo[\"salary\"]\n jobdata[\"positionAdvantage\"] = jobinfo[\"positionAdvantage\"]\n jobdata[\"workYear\"] = jobinfo[\"workYear\"]\n jobdata[\"education\"] = jobinfo[\"education\"]\n jobdata[\"industryField\"] = jobinfo[\"industryField\"]\n jobdata[\"financeStage\"] = jobinfo[\"financeStage\"]\n jobdata[\"companySize\"] = jobinfo[\"companySize\"]\n jobdata[\"companyLabelList\"] = ','.join(jobinfo[\"companyLabelList\"])\n save_data_to_DB(jobdata)\n\n\n # 当前页面\n cur_page = int(data[\"content\"][\"pageNo\"])\n # 每页数据数量\n page_size = data[\"content\"][\"pageSize\"]\n # 数据总量\n totalcount = data[\"content\"][\"positionResult\"][\"totalCount\"]\n\n if cur_page*int(page_size) < int(totalcount):\n print('数据不够，继续请求！！！')\n next_page = cur_page+1\n formdata['pn'] = next_page\n # 回掉函数\n load_page_data(url,formdata,headers)\n else:\n print('请求不成功,休息一会儿继续请求!!!')\n time.sleep(10)\n print('重新发起第'+str(formdata['pn']+\"页请求\"))\n lagouspider(url,formdata,headers)\n\ndef save_data_to_DB(jobdata):\n \"\"\"\n\n :param jobdata: 存储的数据\n :return:\n \"\"\"\n connect = pymysql.Connect('127.0.0.1', \"root\", \"abcd1234\", \"1712B\", 3306, charset=\"utf8\")\n keys = ','.join(jobdata.keys())\n sql = \"\"\"INSERT INTO lagou({columns}) values ({values})\"\"\".format(columns=keys,values=(','.join([\"%s\"]*len(jobdata))))\n cr = connect.cursor()\n cr.execute(sql,list(jobdata.values()))\n connect.commit()\n cr.close()\n connect.close()\n\nif __name__ == '__main__':\n '''\n mysql> create table lagou(id int auto_increment primary key,\n -> positionName varchar(225) not null,\n -> formatCreateTime varchar(125),\n -> companyShortName varchar(225),\n -> salary char(225),\n -> positionAdvantage varchar(225),\n -> workYear varchar(220),\n -> education varchar(222),\n -> industryField varchar(222),\n -> financeStage varchar(222),\n -> companySize varchar(222),\n -> companyLabelList varchar(222));\nQuery OK, 0 rows affected (0.30 sec)\n\n '''\n\n\n url = \"https://www.lagou.com/jobs/positionAjax.json?needAddtionalResult=false\"\n formdata = {\n 'first': 'true',\n 'pn': 1,\n 'kd': 'c++',\n }\n headers = {'User-Agent': UserAgent().chrome}\n load_page_data(url, formdata, headers)\n","repo_name":"aini626204777/spider","sub_path":"第一周/第三天/lagou.py","file_name":"lagou.py","file_ext":"py","file_size_in_byte":3514,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"20818984046","text":"\nimport unittest\nfrom selenium import webdriver\nfrom selenium.webdriver.chrome.options import Options as ChromeOptions\n\nfrom POM_2.Funciones.Funciones import Funciones_Globales\nfrom Excel_Openpyxl import *\n\ntg = 1\n\nclass base_test_Excel(unittest.TestCase):\n\n @classmethod\n def setUpClass(self):\n # Configuraciones para el navegador\n self.options = ChromeOptions()\n # options.add_argument(\"--headless\")\n self.driver = webdriver.Chrome(options=self.options)\n\n def test_example(self):\n driver = self.driver\n f = Funciones_Globales(driver)\n fe = Fun_excel(driver)\n f.Navegar_T(\"https://demoqa.com/text-box\", tg)\n ruta = \"C://Users//Smavodev//Desktop//Selenium Python//Selenium_python//ExcelPath//Datos_ok.xlsx\"\n filas = fe.getRowCount(ruta, \"Hoja1\")\n\n for r in range(2, filas+1):\n nombre = fe.readData(ruta, \"Hoja1\", r, 1)\n email = fe.readData(ruta, \"Hoja1\", r, 2)\n dir1 = fe.readData(ruta, \"Hoja1\", r, 3)\n dir2 = fe.readData(ruta, \"Hoja1\", r, 4)\n\n f.Texto_TYPE(\"id\", \"userName\", nombre, tg)\n # f.Texto_ID(\"userName\", nombre, tg)\n f.Texto_TYPE(\"id\", \"userEmail\", email, tg)\n # f.Texto_ID(\"userEmail\", email, tg)\n f.Texto_TYPE(\"id\", \"currentAddress\", dir1, tg)\n # f.Texto_ID(\"currentAddress\", dir1, tg)\n f.Texto_TYPE(\"id\", \"permanentAddress\", dir2, tg)\n # f.Texto_ID(\"permanentAddress\", dir2, tg)\n f.Button_TYPE(\"id\", \"submit\", tg)\n\n e = f.Existe_Selector(\"id\", \"name\", tg)\n if e == \"Existe\":\n print(\"El elemento se inserto correctamente\")\n print(\"====================== SE FINALIZA LA EJECUCIÓN DE LA INSERCIÓN ======================\")\n print(\" \")\n fe.writeData(ruta, \"Hoja1\", r, 5, \"Insertado\")\n else:\n print(\"No se Inserto\")\n fe.writeData(ruta, \"Hoja1\", r, 5, \"Error\")\n\n @classmethod\n def tearDownClass(self):\n self.driver.close()\n self.driver.quit()\n\nif __name__ == '__main__':\n unittest.main()\n","repo_name":"smavo/selenium_python_test","sub_path":"Data Driver (Excel)/01_Test_Sample_Excel.py","file_name":"01_Test_Sample_Excel.py","file_ext":"py","file_size_in_byte":2173,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"11813369597","text":"import sys\nimport logging\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\n\nfrom dadmatools.models.common.trainer import Trainer as BaseTrainer\n\nfrom .model import Tokenizer\nfrom .vocab import Vocab\n\nlogger = logging.getLogger('stanza')\n\nclass Trainer(BaseTrainer):\n def __init__(self, args=None, vocab=None, model_file=None, use_cuda=False):\n self.use_cuda = use_cuda\n if model_file is not None:\n # load everything from file\n self.load(model_file)\n else:\n # build model from scratch\n self.args = args\n self.vocab = vocab\n self.model = Tokenizer(self.args, self.args['vocab_size'], self.args['emb_dim'], self.args['hidden_dim'], dropout=self.args['dropout'])\n self.criterion = nn.CrossEntropyLoss(ignore_index=-1)\n if use_cuda:\n self.model.cuda()\n self.criterion.cuda()\n else:\n self.model.cpu()\n self.criterion.cpu()\n self.parameters = [p for p in self.model.parameters() if p.requires_grad]\n self.optimizer = optim.Adam(self.parameters, lr=self.args['lr0'], betas=(.9, .9), weight_decay=self.args['weight_decay'])\n self.feat_funcs = self.args.get('feat_funcs', None)\n self.lang = self.args['lang'] # language determines how token normalization is done\n\n def update(self, inputs):\n self.model.train()\n units, labels, features, _ = inputs\n\n if self.use_cuda:\n units = units.cuda()\n labels = labels.cuda()\n features = features.cuda()\n\n pred = self.model(units, features)\n\n self.optimizer.zero_grad()\n classes = pred.size(2)\n loss = self.criterion(pred.view(-1, classes), labels.view(-1))\n\n loss.backward()\n nn.utils.clip_grad_norm_(self.model.parameters(), self.args['max_grad_norm'])\n self.optimizer.step()\n\n return loss.item()\n\n def predict(self, inputs):\n self.model.eval()\n units, labels, features, _ = inputs\n\n if self.use_cuda:\n units = units.cuda()\n labels = labels.cuda()\n features = features.cuda()\n\n pred = self.model(units, features)\n\n return pred.data.cpu().numpy()\n\n def save(self, filename):\n params = {\n 'model': self.model.state_dict() if self.model is not None else None,\n 'vocab': self.vocab.state_dict(),\n 'config': self.args\n }\n try:\n torch.save(params, filename, _use_new_zipfile_serialization=False)\n logger.info(\"Model saved to {}\".format(filename))\n except BaseException:\n logger.warning(\"Saving failed... continuing anyway.\")\n\n def load(self, filename):\n try:\n checkpoint = torch.load(filename, lambda storage, loc: storage)\n except BaseException:\n logger.error(\"Cannot load model from {}\".format(filename))\n raise\n self.args = checkpoint['config']\n if self.args.get('use_mwt', None) is None:\n # Default to True as many currently saved models\n # were built with mwt layers\n self.args['use_mwt'] = True\n self.model = Tokenizer(self.args, self.args['vocab_size'], self.args['emb_dim'], self.args['hidden_dim'], dropout=self.args['dropout'])\n self.model.load_state_dict(checkpoint['model'])\n self.vocab = Vocab.load_state_dict(checkpoint['vocab'])\n","repo_name":"Dadmatech/DadmaTools","sub_path":"dadmatools/models/tokenization/trainer.py","file_name":"trainer.py","file_ext":"py","file_size_in_byte":3484,"program_lang":"python","lang":"en","doc_type":"code","stars":115,"dataset":"github-code","pt":"3"} +{"seq_id":"35971089615","text":"from odf.opendocument import OpenDocumentText\nfrom odf.style import PageLayout, MasterPage, Header, Footer, Style, TextProperties, ParagraphProperties, PageLayoutProperties, TabStop, TabStops\nfrom odf.text import P,H,Span,LineBreak\nfrom odf import teletype, opendocument,text\n\nclass Estilo():\t\n\tdef __init__(self):\n\t\tself.textDoc = OpenDocumentText()\n\t\tself.h = Header()\n\t\tself.f = Footer()\n\t\tself.s = self.textDoc.styles\t\t\n\t\tself.pl = PageLayout(name=\"pagelayout\")\n\t\t#margenes para la pagina (PageLayout)\n\t\tself.pl.addElement(PageLayoutProperties(margintop=\"1cm\"))\n\t\tself.textDoc.automaticstyles.addElement(self.pl)\n\t\tself.mp = MasterPage(name=\"Standard\", pagelayoutname=self.pl)\n\t\tself.textDoc.masterstyles.addElement(self.mp)\n\t\tself.estilos = {}\t\t\n\t\tself.ConfigurarEstilos()\n\tdef ConfigurarEstilos(self):\n\t\tnombre = \"Linea horizontal gruesa\"\n\t\t###############\n\t\t### Estilos ###\n\t\t###############\t\t\n\t\t#H1\n\t\tH1 = \"Heading 1\"\n\t\testilo = Style(name = H1, family=\"paragraph\")\t\t\n\t\testilo.addElement(TextProperties(attributes={'fontsize':\"14pt\",'fontweight':\"bold\",'fontfamily' : \"helvetica\"}))\n\t\testilo.addElement(ParagraphProperties(attributes={'textalign' : \"Left\", 'paddingtop' : \"0cm\"}))\n\t\tself.UpdateEstilos(H1,estilo)\n\t\t#H2\n\t\tH2 = \"Heading 2\"\n\t\testilo = Style(name=H2, family=\"paragraph\", parentstylename = H1)\n\t\testilo.addElement(TextProperties(attributes={\"fontsize\": \"12pt\"}))\n\t\tself.UpdateEstilos(H2,estilo)\n\t\t#BASE\n\t\tbase = \"Base\"\n\t\testilo = Style(name=base, family=\"paragraph\")\n\t\testilo.addElement(ParagraphProperties(textalign = \"justify\", padding = \"0cm\", marginleft = \"2cm\",marginright = \"5cm\"))\n\t\testilo.addElement(TextProperties(fontfamily = \"helvetica\", fontsize = \"12pt\"))\n\t\tself.UpdateEstilos(base,estilo)\n\t\t#Capitulo\n\t\tCAP = \"Capitulo\"\n\t\testilo = Style(name=CAP, family=\"paragraph\", parentstylename = base)\n\t\testilo.addElement(TextProperties(attributes={'fontsize':\"10pt\",'fontweight':\"bold\",'fontfamily' : \"helvetica\", 'backgroundcolor' : '#a2f2f5'}))\n\t\tself.UpdateEstilos(CAP,estilo)\n\t\t#Subcapitulo\n\t\tSUBCAP = \"SubCapitulo\"\n\t\testilo = Style(name=SUBCAP, family=\"paragraph\", parentstylename = CAP)\n\t\testilo.addElement(TextProperties(attributes={\"fontsize\": \"10pt\"}))\n\t\tself.UpdateEstilos(SUBCAP,estilo)\t\t\n\t\t#normal\n\t\tnormal = \"Normal\"\n\t\testilo = Style(name = normal, family=\"paragraph\", parentstylename = base)\n\t\testilo.addElement(TextProperties(fontsize = \"8pt\"))\n\t\tself.UpdateEstilos(normal,estilo)\n\t\t#texto\n\t\ttexto = \"Texto\"\n\t\testilo = Style(name = texto, family=\"paragraph\", parentstylename = base)\n\t\testilo.addElement(ParagraphProperties(textalign = \"justify\"))\n\t\testilo.addElement(TextProperties(fontsize = \"8pt\"))\n\t\tself.UpdateEstilos(texto,estilo)\n\t\t#negritas\n\t\tnegritas = \"Negritas\"\n\t\testilo = Style(name = negritas, family=\"paragraph\", parentstylename = base)\n\t\testilo.addElement(TextProperties(fontsize = \"9pt\",fontweight =\"bold\"))\n\t\testilo.addElement(ParagraphProperties(marginleft = \"cm\"))\n\t\tself.UpdateEstilos(negritas,estilo)\n\t\t#normal parrafo\n\t\tnormal_parrafo = \"NormalP\"\n\t\testilo = Style(name = normal_parrafo, family=\"paragraph\")\n\t\testilo.addElement(TextProperties(fontfamily = \"helvetica\", fontsize = \"10pt\"))\n\t\tself.UpdateEstilos(normal_parrafo,estilo)\t\t\n\t\t#negritas parrafo\n\t\tnegritas_parrafo = \"NegritasP\"\n\t\testilo = Style(name = negritas_parrafo, family=\"paragraph\", parentstylename=normal_parrafo)\n\t\testilo.addElement(TextProperties(fontweight =\"bold\"))\n\t\tself.UpdateEstilos(negritas_parrafo,estilo)\t\t\t\n\t\t#conjunto de tabuladores 1 (PARA EL LISTADO DE CAPITULOS)\n\t\ttabstops_list = TabStops()\n\t\t#Cada tabulador\n\t\ttabstop1 = TabStop(position=\"4.5cm\")\n\t\ttabstops_list.addElement(tabstop1)\n\t\ttabstop1 = TabStop(position=\"5.5cm\")\n\t\ttabstops_list.addElement(tabstop1)\n\t\ttabstop1 = TabStop(position=\"6.5cm\")\n\t\ttabstops_list.addElement(tabstop1)\n\t\ttabstop1 = TabStop(position=\"7.5cm\")\n\t\ttabstops_list.addElement(tabstop1)\n\t\ttabstop1 = TabStop(position=\"8.5cm\")\n\t\ttabstops_list.addElement(tabstop1)\n\t\ttabstop1 = TabStop(position=\"9.5cm\")\n\t\ttabstops_list.addElement(tabstop1)\n\t\ttabstop1 = TabStop(position=\"11.5cm\")\n\t\ttabstops_list.addElement(tabstop1)\n\t\ttabstop1 = TabStop(position=\"13.5cm\")\n\t\ttabstops_list.addElement(tabstop1)\n\t\ttabstoppar_mediciones = ParagraphProperties()\n\t\ttabstoppar_mediciones.addElement(tabstops_list)\n\t\t#estilo tabuladores normal\n\t\ttabuladores_normal = \"Tabuladores Lineas Medicion\"\n\t\testilo = Style(name = tabuladores_normal, family=\"paragraph\",parentstylename = texto)\n\t\testilo.addElement(tabstoppar_mediciones)\n\t\testilo.addElement(ParagraphProperties(marginright = \"0cm\", marginleft = \"2cm\"))\n\t\tself.UpdateEstilos(tabuladores_normal,estilo)\n\t\t#estilo tabuladores negritas\n\t\ttabuladores_negritas = \"Tabuladores Hoja Listados Negritas\"\n\t\testilo = Style(name = tabuladores_negritas, family=\"paragraph\", parentstylename = tabuladores_normal)\n\t\testilo.addElement(TextProperties(fontweight =\"bold\", fontstyle=\"italic\"))\n\t\tself.UpdateEstilos(tabuladores_negritas,estilo)\n\t\t#tabuladores linea total capitulos\n\t\ttabstops_list_total_capitulos = TabStops()\n\t\ttabstop = TabStop(position=\"15.5cm\", type = \"char\", char = \",\", leaderstyle=\"dotted\")\n\t\ttabstops_list_total_capitulos.addElement(tabstop)\n\t\ttabstoppar_total_capitulo = ParagraphProperties()\n\t\ttabstoppar_total_capitulo.addElement(tabstops_list_total_capitulos)\n\t\ttabuladores_total_capitulos = \"Tabuladores Linea Total Capitulo\"\n\t\testilo = Style(name = tabuladores_total_capitulos, family=\"paragraph\",parentstylename = negritas)\n\t\testilo.addElement(tabstoppar_total_capitulo)\n\t\testilo.addElement(ParagraphProperties(marginright = \"0cm\", marginleft = \"0cm\"))\n\t\tself.UpdateEstilos(tabuladores_total_capitulos,estilo)\n\t\t#linea horizontal gruesa\n\t\tlinea_horizontal_gruesa = \"Linea horizontal gruesa\"\n\t\testilo = Style(name = linea_horizontal_gruesa, displayname=\"Horizontal Line Thick\", family=\"paragraph\", parentstylename=\"Standard\")\n\t\testilo.addElement(ParagraphProperties(margintop=\"0cm\", marginbottom=\"0cm\", marginright=\"0cm\", marginleft=\"0cm\", \\\n\t\t\tcontextualspacing=\"false\", borderlinewidthbottom=\"0cm 0.030cm 0.06cm\", padding=\"0cm\", borderleft=\"none\", borderright=\"none\", \\\n\t\t\tbordertop=\"none\", borderbottom=\"0.06pt double #3a3b3d\", numberlines=\"false\", linenumber=\"0\", joinborder=\"false\"))\n\t\tself.UpdateEstilos(linea_horizontal_gruesa,estilo)\n\t\t#linea horizontal sumatoria\n\t\tlinea_horizontal_sumatoria = \"Linea horizontal sumatoria\"\n\t\testilo = Style(name = linea_horizontal_sumatoria, displayname=\"Horizontal Line Sumatory\", family=\"paragraph\")\n\t\testilo.addElement(TextProperties(attributes={\"fontsize\": \"8pt\"}))\n\t\testilo.addElement(ParagraphProperties(margintop=\"0cm\", marginbottom=\"0cm\", marginright=\"0cm\", marginleft=\"10cm\", \\\n\t\t\tcontextualspacing=\"false\", borderlinewidthbottom=\"0cm 0.030cm 0.01cm\", padding=\"0cm\", borderleft=\"none\", borderright=\"none\", \\\n\t\t\tborderbottom=\"none\", bordertop=\"0.06pt double #3a3b3d\", numberlines=\"false\", linenumber=\"0\", joinborder=\"false\"))\n\t\tself.UpdateEstilos(linea_horizontal_sumatoria,estilo)\n\t\t#salto de pagina\n\t\tsalto_pagina = \"Salto de Pagina\"\n\t\testilo = Style(name = salto_pagina, parentstylename=\"Standard\", family=\"paragraph\")\n\t\testilo.addElement(ParagraphProperties(breakbefore=\"page\"))\n\t\tself.UpdateEstilos(salto_pagina,estilo)\t\t\n\tdef Documento(self):\n\t\treturn self.textDoc\t\n\tdef Estilos(self,nombre):\n\t\treturn self.estilos[nombre]\n\tdef UpdateEstilos (self, nombre, estilo):\n\t\tself.s.addElement(estilo)\n\t\tself.estilos.update({nombre : estilo})\n\tdef ListaEstilos(self):\n\t\treturn self.estilos\n\t\t\n\t\t\n\t\t\nif __name__ == \"__main__\":\n\tInstancia = Estilos()\n\tdoc = Instancia.Documento()\n\tlinea = \"La prueba definitiva\"\n\tparrafo = P(stylename=Instancia.Estilo(\"Heading 1\"))\n\tteletype.addTextToElement(parrafo, linea)\n\tdoc.text.addElement(parrafo)\n\t\n\tlinea1 = \"La prueba definitiva 2\"\n\tparrafo = P(stylename=Instancia.Estilo(\"Heading 2\"))\n\tteletype.addTextToElement(parrafo, linea1)\n\tdoc.text.addElement(parrafo)\n\t\n\tlinea2 = \"Hola\\tEsto\\tson\\ttabuladores\\taqui\\tpuestos\"\n\tparrafo = P(stylename=Instancia.Estilo(\"Negritas con tabuladores\"))\n\tteletype.addTextToElement(parrafo, linea2)\n\tdoc.text.addElement(parrafo)\n\t\n\tdoc.save(\"kkk.odt\")\n","repo_name":"exodehm/SDMed2","sub_path":"python/plugins_impresion/C4/estilos.py","file_name":"estilos.py","file_ext":"py","file_size_in_byte":8088,"program_lang":"python","lang":"es","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"2587170014","text":"# -*- coding:utf-8 -*-\nimport threading\nimport time\nimport tkinter as tk\nfrom tkinter import ttk\nfrom logging import (\n getLogger\n , DEBUG\n , INFO\n)\n\n# my modules and packages\nfrom tkinter_console.log_console import LogConsoleExFrame\n\nif __name__ == '__main__':\n # create a logger object and set logger level\n logger = getLogger(__name__)\n logger.setLevel(DEBUG)\n\n # define loglog method for using button as thread\n def loglog():\n\n def wrapper():\n while True:\n logger.debug('debug message')\n logger.info('info message')\n logger.warning('warn message')\n logger.error('error message')\n logger.critical('critical message')\n time.sleep(1)\n\n # start thread\n threading.Thread(target=wrapper, daemon=True).start()\n\n\n # create root object\n root = tk.Tk()\n root.title('Threading Sample')\n\n # create console frame\n console_frame = LogConsoleExFrame(root, logger, level=None)\n\n # set log format\n console_frame.log_formatter = '%(asctime)s\\t[%(levelname)-8s]\\t%(thread)+5s\\t%(message)s'\n\n\n # check flag only debug\n console_frame.selector_inner_frame.set_checkbutton_flag(DEBUG, True)\n\n # initialize console frame\n console_frame.init()\n\n # for test\n button_frame = tk.LabelFrame(root, text='LOGLOG', foreground='white', background=\"blue\", height=20, pady=5)\n button_frame.pack(fill=tk.BOTH)\n button = ttk.Button(button_frame, text=\"LOGGING\", command=loglog)\n button.pack(fill=tk.X, expand=True)\n\n\n\n # mainloop\n root.mainloop()\n\n","repo_name":"BlackHatD/tkinter-console","sub_path":"docs/log_console/03_threading_sample.py","file_name":"03_threading_sample.py","file_ext":"py","file_size_in_byte":1615,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"22004101040","text":"from sys import stdin,setrecursionlimit\nimport sys\n\nsetrecursionlimit(10000)\n\n#jose david gutierrez\ndef solve(inOrder,preOrder):\n\tglobal ans\n\tif len(inOrder) == 1:\n\t\tans.append(preOrder[0])\n\telif len(inOrder) > 1:\n\t\tmid = inOrder.index(preOrder[0])\n\t\tsolve(inOrder[:mid],preOrder[1:mid+1])\n\t\tsolve(inOrder[mid+1:],preOrder[mid+1:])\n\t\tans.append(preOrder[0])\n\t\n\ndef main():\n\tglobal ans\n\ttrasversal= [str(i) for i in stdin.readline().strip().split() ]\n\twhile len(trasversal) != 0:\n\t\tans=[]\n\t\tpreOrder = trasversal[0]\n\t\tinOrder = trasversal[1]\n\t\tsolve(inOrder,preOrder)\n\t\tfor i in ans:\n\t\t\tprint(i, end='')\n\t\tprint()\n\t\ttrasversal= [str(i) for i in stdin.readline().strip().split() ]\n\t\t\n\t\nmain()","repo_name":"joseuribe0624/Data_Structure","sub_path":"hw/recovery.py","file_name":"recovery.py","file_ext":"py","file_size_in_byte":690,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"34036220941","text":"#stats constants\nST_HP = 0\nST_ATTACK = 1\nST_DEFENSE = 2\nST_SPEED = 3\nST_SPATTACK = 4\nST_SPDEFENSE = 5\n\nST_ACCURACY = 6\nST_EVASION = 7\n\n#import\n__all__ = (\"ST_HP\",\n \"ST_ATTACK\",\n \"ST_DEFENSE\",\n \"ST_SPEED\",\n \"ST_SPATTACK\",\n \"ST_SPDEFENSE\",\n\t\t \"ST_ACCURACY\",\n\t\t \"ST_EVASION\")\n","repo_name":"andrew-turner/Ditto","sub_path":"eng/constants/stats.py","file_name":"stats.py","file_ext":"py","file_size_in_byte":327,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"2772761270","text":"class BichinoVirtual:\r\n def __init__(self, nome, idade, fome , saude, humor = 10):\r\n self.nome = nome\r\n self.fome = fome\r\n self.saude = saude\r\n self.idade = idade\r\n self.humor = humor\r\n\r\n def alt_nome(self, nome):\r\n self.nome = nome\r\n print(self.nome)\r\n\r\n def ret_nome(self):\r\n return self.nome\r\n\r\n def comer(self, quant_comida):\r\n for x in range(0, quant_comida):\r\n if self.fome > 0:\r\n self.fome -= 1\r\n\r\n def alt_saude(self, saude):\r\n self.saude += saude\r\n print(self.saude)\r\n\r\n def alt_idade(self, idade):\r\n self.idade = idade\r\n print(self.idade)\r\n\r\n def hmor(self):\r\n self.humor = self.saude - self.fome\r\n if self.humor >= 10:\r\n print('Muito feliz')\r\n elif 5 < self.humor < 10:\r\n print('Feliz')\r\n elif self.humor < 5:\r\n print('Triste')\r\n\r\n def brincar(self, tempo):\r\n for x in range(0, tempo):\r\n if self.humor < 15:\r\n self.saude += 1\r\n\r\n def __str__(self):\r\n return (f'Nome: {self.nome}'\r\n f'Idade: {self.idade}'\r\n f'\\nFome: {self.fome}'\r\n f'\\nSaude: {self.saude}'\r\n f'\\nIdade: {self.idade}'\r\n f'\\nHumor: {self.humor}')\r\n\r\n\r\nanimal2 = BichinoVirtual('Lups', 1, 10, 4, 4)\r\nanimal3 = BichinoVirtual('Fern', 2, 5, 5)\r\nanimal4 = BichinoVirtual('Jup', 1, 15, 11, 3)\r\nanimal5 = BichinoVirtual('Lil', 3, 11, 12, 13)\r\nanimal6 = BichinoVirtual('Carl', 4, 1, 6, 8)\r\n\r\nfazenda = [animal2, animal3, animal4, animal5, animal6]\r\n\r\nfor an in fazenda:\r\n print()\r\n an.hmor()\r\nfor an in fazenda:\r\n an.brincar(10)\r\nfor an in fazenda:\r\n an.comer(10)\r\nfor an in fazenda:\r\n print()\r\n an.hmor()\r\nprint()\r\nfor an in fazenda:\r\n print()\r\n print(an)\r\n\r\n","repo_name":"natalinoqueba/exercicios-python","sub_path":"08_Classes/17_bichinho_virtual4.py","file_name":"17_bichinho_virtual4.py","file_ext":"py","file_size_in_byte":1880,"program_lang":"python","lang":"pt","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"71438360402","text":"import hashlib\nimport io\nimport json\nimport os\nimport pathlib\nimport pickle\nimport urllib.error\nimport urllib.request\nimport warnings\n\n# 3rd party\nimport appdirs\nimport numpy\nfrom chemistry_tools.constants import API_BASE\nfrom chemistry_tools.lookup import get_compounds\nfrom domdf_python_tools.paths import maybe_make\nfrom flask import Flask, render_template, request, send_file\nfrom indigo import Indigo\nfrom indigo.renderer import IndigoRenderer\nfrom mathematical.utils import rounders\n\n# This package\nfrom GuiV2.GSMatch2_Core.Project import ConsolidatedPeak, ConsolidatedSearchResult\n\napp = Flask(__name__)\n\n\ndef prepare_cache_dir():\n\tcache_dir = pathlib.Path(appdirs.user_cache_dir(\"GunShotMatch\"))\n\tif not cache_dir.exists():\n\t\tcache_dir.mkdir()\n\tcache_dir = cache_dir / \"data_viewer_cache\"\n\tif not cache_dir.exists():\n\t\tcache_dir.mkdir()\n\t\n\treturn cache_dir\n\ncache_dir = prepare_cache_dir()\n\n\n@app.context_processor\ndef inject_functions():\n\t\"\"\"\n\tAdds certain Python functions to the jinja2 global scope\n\t\n\t:return: Dictionary of Python functions\n\t:rtype: dict\n\t\"\"\"\n\t\n\treturn dict(rounders=rounders, np=numpy, len=len)\n\n\n@app.route(\"/\")\ndef peak_data(samples):\n\tprint(request.args)\n\tsamples = samples.split(\"/\")\n\t\n\tif \"data\" in request.args:\n\t\tprint(request.args.get(\"data\", type=str))\n\t\tpeak = ConsolidatedPeak.from_quoted_string(request.args.get(\"data\", type=str))\n\t\tprint(peak)\n\t\t\n\t\tCAS = peak.hits[0].cas\n\t\tName = peak.hits[0].name\n\t\trt = peak.rt\n\t\t\n\t\tif CAS.replace(\"-\", '').replace(\"0\", '') == '':\n\t\t\t# CAS Number is all zeros\n\t\t\tpickle_name = hashlib.md5(Name.encode(\"utf-8\")).hexdigest()\n\t\t\t# html_file_name = os.path.join(html_file_directory, f\"{pickle_name}_{rt}.html\")\n\t\t\t\n\t\t\tif (cache_dir / pickle_name).exists():\n\t\t\t\twith open(cache_dir / pickle_name, \"rb\") as f:\n\t\t\t\t\tcomp = pickle.load(f)\n\t\t\telse:\n\t\t\t\t# if True:\n\t\t\t\tcomp = get_compounds(Name, 'name')[0]\n\t\t\t\t# Save to cache\n\t\t\t\twith open(cache_dir / pickle_name, \"wb\") as f:\n\t\t\t\t\tpickle.dump(comp, f)\n\t\t\n\t\telse:\n\t\t\tif (cache_dir / CAS).exists():\n\t\t\t\twith open(cache_dir / CAS, \"rb\") as f:\n\t\t\t\t\tcomp = pickle.load(f)\n\t\t\telse:\n\t\t\t\t# if True:\n\t\t\t\tcomp = get_compounds(CAS, 'name')[0]\n\t\t\t\t# Save to cache\n\t\t\t\twith open(cache_dir / CAS, \"wb\") as f:\n\t\t\t\t\tpickle.dump(comp, f)\n\t\t\n\t\treturn render_template(\n\t\t\t\t\"properties_template_2.html\",\n\t\t\t\tcomp=comp,\n\t\t\t\tpeak=peak,\n\t\t\t\tsamples=samples,\n\t\t\t\t)\n\t\t\n\telse:\n\t\t# Legacy mode\n\t\t\n\t\tindex = request.args.get(\"index\", 0, type=int)\n\t\tfilename = request.args.get(\"filename\", '', type=str)\n\t\t\n\t\tpeak_data = []\n\t\t\n\t\tif filename == '':\n\t\t\treturn \"Please provide a filename with ?filename=\", 400\n\t\t\n\t\twith open(os.path.join(filename), \"r\") as jsonfile:\n\t\t\tfor i, peak in enumerate(jsonfile):\n\t\t\t\tif i == index:\n\t\t\t\t\tpeak_data = json.loads(peak)\n\t\t\n\t\tif not peak_data:\n\t\t\t# Index was out of range\n\t\t\treturn \"Peak index out of range\", 400\n\t\t\n\t\tCAS = peak_data[\"hits\"][0][\"CAS\"]\n\t\tName = peak_data[\"hits\"][0][\"Name\"]\n\t\trt = peak_data[\"average_rt\"]\n\t\t\n\t\tif CAS.replace(\"-\", '').replace(\"0\", '') == '':\n\t\t\t# CAS Number is all zeros\n\t\t\tpickle_name = hashlib.md5(Name.encode(\"utf-8\")).hexdigest()\n\t\t\t# html_file_name = os.path.join(html_file_directory, f\"{pickle_name}_{rt}.html\")\n\t\t\t\n\t\t\tif (cache_dir / pickle_name).exists():\n\t\t\t\twith open(cache_dir / pickle_name, \"rb\") as f:\n\t\t\t\t\tcomp = pickle.load(f)\n\t\t\telse:\n\t\t\t\t# if True:\n\t\t\t\tcomp = get_compounds(Name, 'name')[0]\n\t\t\t\t# Save to cache\n\t\t\t\twith open(cache_dir / pickle_name, \"wb\") as f:\n\t\t\t\t\tpickle.dump(comp, f)\n\t\t\n\t\telse:\n\t\t\tif (cache_dir / CAS).exists():\n\t\t\t\twith open(cache_dir / CAS, \"rb\") as f:\n\t\t\t\t\tcomp = pickle.load(f)\n\t\t\telse:\n\t\t\t\t# if True:\n\t\t\t\tcomp = get_compounds(CAS, 'name')[0]\n\t\t\t\t# Save to cache\n\t\t\t\twith open(cache_dir / CAS, \"wb\") as f:\n\t\t\t\t\tpickle.dump(comp, f)\n\t\t\n\t\treturn render_template(\n\t\t\t\t\"properties_template.html\",\n\t\t\t\tcomp=comp,\n\t\t\t\tdata=peak_data,\n\t\t\t\tsamples=samples,\n\t\t\t\t)\n\n\n@app.route(\"/hit/\")\ndef hit_data(samples):\n\t# print(request.args)\n\tsamples = samples.split(\"/\")\n\t\n\tmaybe_make(\"cache\") # Internal Cache Directory\n\t\n\tif \"data\" in request.args:\n\t\t# print(request.args.get(\"data\", type=str))\n\t\thit = ConsolidatedSearchResult.from_quoted_string(request.args.get(\"data\", type=str))\n\t\t# print(hit)\n\t\t\n\t\tCAS = hit.cas\n\t\tName = hit.name\n\t\t\n\t\tif CAS.replace(\"-\", '').replace(\"0\", '') == '':\n\t\t\t# CAS Number is all zeros\n\t\t\tpickle_name = hashlib.md5(Name.encode(\"utf-8\")).hexdigest()\n\t\t\t# html_file_name = os.path.join(html_file_directory, f\"{pickle_name}_{rt}.html\")\n\t\t\t\n\t\t\tif (cache_dir / pickle_name).exists():\n\t\t\t\twith open(cache_dir / pickle_name, \"rb\") as f:\n\t\t\t\t\tcomp = pickle.load(f)\n\t\t\telse:\n\t\t\t\t# Check that a connection an be established to PubChem server\n\t\t\t\ttry:\n\t\t\t\t\turllib.request.urlopen(API_BASE, timeout=2)\n\t\t\t\t\n\t\t\t\texcept urllib.error.HTTPError as e:\n\t\t\t\t\tif e.code == 400:\n\t\t\t\t\t\tpass\n\t\t\t\t\telse:\n\t\t\t\t\t\traise e\n\t\t\t\t\t\n\t\t\t\texcept urllib.error.URLError:\n\t\t\t\t\twarnings.warn(\"Unable to connect to PubChem server. Check your internet connection and try again.\")\n\t\t\t\t\treturn render_template(\n\t\t\t\t\t\t\t\"properties_template_offline.html\",\n\t\t\t\t\t\t\thit=hit,\n\t\t\t\t\t\t\tsamples=samples,\n\t\t\t\t\t\t\t)\n\t\t\t\t\n\t\t\t\ttry:\n\t\t\t\t\tcomp = get_compounds(CAS, 'name')[0]\n\t\t\t\texcept IndexError:\n\t\t\t\t\tcomp = None\n\t\t\t\t\t\n\t\t\t\t# Save to cache\n\t\t\t\twith open(cache_dir / pickle_name, \"wb\") as f:\n\t\t\t\t\tpickle.dump(comp, f)\n\t\t\n\t\telse:\n\t\t\tif (cache_dir / CAS).exists():\n\t\t\t\twith open(cache_dir / CAS, \"rb\") as f:\n\t\t\t\t\tcomp = pickle.load(f)\n\t\t\telse:\n\t\t\t\t# if True:\n\t\t\t\ttry:\n\t\t\t\t\tcomp = get_compounds(CAS, 'name')[0]\n\t\t\t\texcept IndexError:\n\t\t\t\t\tcomp = None\n\t\t\t\t\n\t\t\t\t# Save to cache\n\t\t\t\twith open(cache_dir / CAS, \"wb\") as f:\n\t\t\t\t\tpickle.dump(comp, f)\n\t\t\n\t\t# TODO: Combine information from hit.reference_data and comp, e.g. synonyms\n\t\t\n\t\treturn render_template(\n\t\t\t\t\"properties_template_2.html\",\n\t\t\t\tcomp=comp,\n\t\t\t\thit=hit,\n\t\t\t\tsamples=samples,\n\t\t\t\t)\n\t\t\n\telse:\n\t\t# Legacy mode\n\t\t\n\t\tindex = request.args.get(\"index\", 0, type=int)\n\t\tfilename = request.args.get(\"filename\", '', type=str)\n\t\t\n\t\tpeak_data = []\n\t\t\n\t\tif filename == '':\n\t\t\treturn \"Please provide a filename with ?filename=\", 400\n\t\t\n\t\twith open(os.path.join(filename), \"r\") as jsonfile:\n\t\t\tfor i, peak in enumerate(jsonfile):\n\t\t\t\tif i == index:\n\t\t\t\t\tpeak_data = json.loads(peak)\n\t\t\n\t\tif not peak_data:\n\t\t\t# Index was out of range\n\t\t\treturn \"Peak index out of range\", 400\n\t\t\n\t\tCAS = peak_data[\"hits\"][0][\"CAS\"]\n\t\tName = peak_data[\"hits\"][0][\"Name\"]\n\t\trt = peak_data[\"average_rt\"]\n\t\t\n\t\tif CAS.replace(\"-\", '').replace(\"0\", '') == '':\n\t\t\t# CAS Number is all zeros\n\t\t\tpickle_name = hashlib.md5(Name.encode(\"utf-8\")).hexdigest()\n\t\t\t# html_file_name = os.path.join(html_file_directory, f\"{pickle_name}_{rt}.html\")\n\t\t\t\n\t\t\tif (cache_dir / pickle_name).exists():\n\t\t\t\twith open(cache_dir / pickle_name, \"rb\") as f:\n\t\t\t\t\tcomp = pickle.load(f)\n\t\t\telse:\n\t\t\t\t# if True:\n\t\t\t\tcomp = get_compounds(Name, 'name')[0]\n\t\t\t\t# Save to cache\n\t\t\t\twith open(cache_dir / pickle_name, \"wb\") as f:\n\t\t\t\t\tpickle.dump(comp, f)\n\t\t\n\t\telse:\n\t\t\tif (cache_dir / CAS).exists():\n\t\t\t\twith open(cache_dir / CAS, \"rb\") as f:\n\t\t\t\t\tcomp = pickle.load(f)\n\t\t\telse:\n\t\t\t\t# if True:\n\t\t\t\tcomp = get_compounds(CAS, 'name')[0]\n\t\t\t\t# Save to cache\n\t\t\t\twith open(cache_dir / CAS, \"wb\") as f:\n\t\t\t\t\tpickle.dump(comp, f)\n\t\t\n\t\treturn render_template(\n\t\t\t\t\"properties_template.html\",\n\t\t\t\tcomp=comp,\n\t\t\t\tdata=peak_data,\n\t\t\t\tsamples=samples,\n\t\t\t\t)\n\n\n@app.route(\"/favicon.ico\")\ndef favicon():\n\treturn ''\n\n\n@app.route(\"/\")\n@app.route(\"/index.html\")\ndef home():\n\treturn render_template(\"index.html\")\n\n\n@app.route(\"/no_hit\")\n@app.route(\"/no-hit\")\ndef no_hit():\n\treturn render_template(\"no_hit.html\")\n\n\n@app.route(\"/smiles/\")\ndef smiles(smiles_string):\n\t# Render SMILES to PNG\n\tindigo = Indigo()\n\trenderer = IndigoRenderer(indigo)\n\t\n\tmol = indigo.loadMolecule(smiles_string)\n\tmol.layout() # if not called, will be done automatically by the renderer\n\tindigo.setOption(\"render-output-format\", \"png\")\n\tindigo.setOption(\"render-image-size\", 250, 250)\n\tindigo.setOption(\"render-background-color\", 1.0, 1.0, 1.0)\n\tindigo.setOption(\"render-coloring\", True)\n\t\n\tindigo.setOption(\"aromaticity-model\", \"generic\")\n\tmol.dearomatize()\n\t\n\tbuf = renderer.renderToBuffer(mol)\n\tbuf = io.BytesIO(buf)\n\t\n\treturn send_file(\n\t\t\tbuf,\n\t\t\tmimetype='image/png',\n\t\t\tas_attachment=False,\n\t\t\t)\n\n\nif __name__ == \"__main__\":\n\tprint(f\"Data Viewer Server using '{cache_dir}' as cache directory\")\n\t\n\tapp.run(debug=True)\n","repo_name":"domdfcoding/GunShotMatch","sub_path":"GSMatch/data_viewer_server/__init__.py","file_name":"__init__.py","file_ext":"py","file_size_in_byte":8375,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"33258466554","text":"# URL: https://leetcode.com/problems/valid-palindrome/\nclass Solution:\n def isPalindrome(self, s: str) -> bool:\n # Use two pointers from left and right and compare the chars at them,\n # making sure to check for non alpha characters\n # O(n) time complexity\n # O(1) space complexity\n left = 0\n right = len(s) - 1\n \n while left < right:\n while left < right and not s[left].isalnum():\n left += 1\n while left < right and not s[right].isalnum():\n right -= 1\n \n if s[left].lower() != s[right].lower():\n return False\n \n left += 1\n right -= 1\n \n return True\n \n","repo_name":"aaronfox/LeetCode-Work","sub_path":"ValidPalindrome.py","file_name":"ValidPalindrome.py","file_ext":"py","file_size_in_byte":757,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"11812651445","text":"# -*- coding: utf-8 -*-\n# @Time : 19-4-17 下午1:55\n# @Author : Redtree\n# @File : zf_role_nlp_qa_type.py\n# @Desc : 角色语料权限表\n\n\nimport json\nfrom __init__ import Base_xxcxb\nfrom sqlalchemy import (Column, String, Integer, Text)\n\n\nclass Zf_role_nlp_qa_type(Base_xxcxb):\n __tablename__ = 'zf_role_nlp_qa_type'\n\n zfid = Column(Integer, primary_key=True)\n qa_code = Column(String(50)) # 语料代码\n role_code = Column(String(50)) # 角色代码\n auth_type = Column(Integer) #0为只读 1为读写\n created_time = Column(Integer)\n updated_time = Column(Integer)\n\n def __repr__(self):\n get_data = {\n \"zfid\": self.zfid,\n \"qa_code\": self.qa_code,\n \"role_code\": self.role_code,\n \"auth_type\": self.auth_type,\n \"created_time\": self.created_time,\n \"updated_time\": self.updated_time\n }\n get_data = json.dumps(get_data)\n return get_data\n","repo_name":"redtreeai/irony-man-server","sub_path":"database/sqlalchemy/orm_models/zf_role_nlp_qa_type.py","file_name":"zf_role_nlp_qa_type.py","file_ext":"py","file_size_in_byte":964,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"29045649557","text":"# coding: utf-8\n__author__ = 'yuelyasheva'\n\nimport datetime\n\nimport hamcrest\nimport pytest\n\nfrom btestlib import utils\nfrom balance import balance_db as db\nfrom balance import balance_steps as steps\nfrom btestlib.data.defaults import Date\nfrom btestlib.constants import PersonTypes, Paysyses, Services, Export, InvoiceType, Products, Firms, NdsNew\nfrom btestlib.utils import XmlRpc, Decimal\nfrom btestlib.matchers import contains_dicts_equal_to, contains_dicts_with_entries, has_entries_casted\n\n# перенесено из джавы ru.yandex.autotests.balance.tests.paystep.paystepRules.oldCatalogRequests\n@pytest.mark.parametrize('service_id, product_id',\n [(Services.CATALOG1.id, Products.CATALOG1_87.id, ),\n (Services.CATALOG2.id, Products.CATALOG2_1636.id),\n ],\n ids=['Catalog 5',\n 'Catalog 6']\n )\ndef test_not_old_catalog_orders(service_id, product_id):\n NOW = datetime.datetime.now()\n PAYSYS_ID = Paysyses.BANK_UR_RUB.id\n QTY = Decimal('50')\n\n client_id = steps.ClientSteps.create()\n\n # создаем плательщика с непроверенными документами\n person_id = steps.PersonSteps.create(client_id, PersonTypes.UR.code)\n service_order_id = steps.OrderSteps.next_id(service_id=service_id)\n\n order_id = steps.OrderSteps.create(client_id, service_order_id, service_id=service_id,\n product_id=product_id, params={'AgencyID': None})\n orders_list = [{'ServiceID': service_id, 'ServiceOrderID': service_order_id, 'Qty': QTY, 'BeginDT': NOW}]\n\n # сдвигаем дату заказа на 5 дней - 10 минут\n delta = 120./86400 - 5\n steps.OrderSteps.move_order_dt(service_order_id=service_order_id, service_id=service_id,\n delta=Decimal(delta))\n request_id = steps.RequestSteps.create(client_id, orders_list, additional_params=dict(InvoiceDesireDT=NOW))\n\n invoice_id, _, _ = steps.InvoiceSteps.create(request_id, person_id, PAYSYS_ID)\n expected_invoice_data = steps.CommonData.create_expected_invoice_data(None, person_id, Decimal('0'),\n InvoiceType.PREPAYMENT, PAYSYS_ID,\n Firms.YANDEX_1)\n expected_invoice_data.update({'effective_sum': get_product_price_with_nds(product_id) * QTY})\n invoice_data = steps.InvoiceSteps.get_all_invoice_data_by_id(invoice_id)\n\n utils.check_that(invoice_data, has_entries_casted(expected_invoice_data),\n u'Сравниваем данные из ивойсов с шаблоном')\n\n\ndef get_product_price_with_nds(product_id):\n query = \"select price, tax from t_price where product_id = :product_id order by dt desc\"\n params = {'product_id': product_id}\n res = db.balance().execute(query, params)[0]\n price, tax = res['price'], res['tax']\n if tax == 0:\n price = price * NdsNew.DEFAULT.koef_on_dt(datetime.datetime.today())\n return price","repo_name":"Alexander-Berg/2022-tests-examples","sub_path":"billing/balance_tests/balance/tests/invoice/test_old_order.py","file_name":"test_old_order.py","file_ext":"py","file_size_in_byte":3177,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"34077768086","text":"#!/usr/bin/env python\nimport rospy, numpy as np,math,matplotlib.pyplot as plt\n# from ParametersInitialization import *\n# from EKF_estimation_algorithm import *\nfrom nav_msgs.msg import Odometry\nfrom geometry_msgs.msg import Twist, Pose, Point, Quaternion\nfrom ackermann_msgs.msg import AckermannDriveStamped,AckermannDrive\nfrom tf.transformations import quaternion_from_euler, euler_from_quaternion\n# globaling variables\nglobal new_msg1, new_msg2,EKF,fpositionx,fpositiony,fnewxhat1,fnewyhat1,yaw,fnewthetahat1;\nmp = np.array([[1,0,0],[0,1,0],[0,0,0.3]]);\nfpositionx = list();fpositiony = list();yaw=list();fnewxhat1 = [];fnewyhat1 = [];fnewthetahat1=[]\n# Plotting Variables\ndef plot_x(fpositionx,fpositiony,fnewxhat1,fnewyhat1):\n global counter\n if counter % 10 == 0:\n plt.subplot(1,2,1)\n plt.plot(fpositionx,fpositiony,'b')\n plt.title('odom')\n plt.subplot(1,2,2)\n plt.plot(fnewxhat1,fnewyhat1,'r')\n plt.title('gps_by_tf')\n plt.draw()\n plt.pause(0.000000001)\n\n counter += 1\n# declaring the data types\nnew_msg1 = Odometry()\nnew_msg2 = Odometry()\nEKF = Odometry()\nEKF_estimated_Pose = Odometry()\n\n# subscriber call back function\ndef robot_to_map_callback(msg):\n global new_msg1\n new_msg1 = msg\ndef cmd_vel_callback(msg):\n global new_msg2\n #print(msg)\n new_msg2 = msg\n\n#initializing node and subscribing and publishing\nrospy.init_node('gps')\nsub1 = rospy.Subscriber('odom',Odometry, robot_to_map_callback,queue_size=10)\nsub2 = rospy.Subscriber('gps_tf',Odometry, cmd_vel_callback,queue_size=1)\n\n\nrate = rospy.Rate(100)\nwhile not rospy.is_shutdown():\n counter = 0\n fnewxhat = new_msg2.pose.pose.position.x;\n fnewyhat = new_msg2.pose.pose.position.y;\n \n ##plotting data\n fpositionx.append(new_msg1.pose.pose.position.x);\n fpositiony.append(new_msg1.pose.pose.position.y);\n \n fnewxhat1.append(fnewxhat)\n fnewyhat1.append(fnewyhat)\n fnewthetahat1.append(fnewthetahat1)\n plot_x(fpositionx,fpositiony,fnewxhat1,fnewyhat1)\n plt.ion()\n rate.sleep()\nrospy.spin()","repo_name":"the-genco-ibis/odom_to_gps","sub_path":"src/gps_tf.py","file_name":"gps_tf.py","file_ext":"py","file_size_in_byte":2078,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"6573462276","text":"\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Sep 4 13:57:53 2019\n\n@author: AVyas\n\nTHIS CODE IS COMBINATION OF HUMAN_DETECTION.PY AND RECORD_15 FOR EASE OF USE.\nGO THROUGHT README FOR HOW TO CAPTURE/OBSERVE DATA.\n\"\"\"\n\n#importingh Copy library to copy data\nimport copy\n#Importing Some Global Functions\nfrom global_functions import findCheckerboardCoordinates,rescale,thresholding,find_red,remove_value,iterate,find_concurrent,apply_cascade\n#Importing RealSense SDK\nimport pyrealsense2 as rs\n# Import Numpy for easy array manipulation\nimport numpy as np\n# Import OpenCV for easy image rendering\nimport cv2\n# Importing pandas for data storage\nimport pandas as pd\n\n#FACE DLIB ITERATION\nfrom imutils import face_utils\nimport dlib\nimport imutils\nfrom collections import OrderedDict\n\n#pickle for data storage\nimport pickle \n\ndef mouse_callback(event, x, y, flags, params):\n global ix\n if event ==1:\n print(\"LEFT_CLICK_MADE\") \n ix=True\n if event == 2:\n ix=False\n print([x,y])\n \ndef record_15():\n global ix\n # Create a pipeline\n pipeline = rs.pipeline()\n \n #Create a config and configure the pipeline to stream\n # different resolutions of color and depth streams\n config = rs.config()\n config.enable_stream(rs.stream.depth, 1280, 720, rs.format.z16, 30)\n config.enable_stream(rs.stream.color, 1280, 720, rs.format.bgr8, 30)\n \n # Start streaming\n profile = pipeline.start(config)\n \n # Getting the depth sensor's depth scale (see rs-align example for explanation)\n depth_sensor = profile.get_device().first_depth_sensor()\n \n #Enabling High Accuracy Preset\n depth_sensor.set_option(rs.option.visual_preset, 3.0)\n preset_name = depth_sensor.get_option_value_description(rs.option.visual_preset, 3.0)\n \n #Enabling Emitter To increase accuracy\n enable_ir_emitter = True\n depth_sensor.set_option(rs.option.emitter_enabled, 1 if enable_ir_emitter else 0)\n \n #GET the depth scale from the SDK\n depth_scale = depth_sensor.get_depth_scale()\n print(\"Depth Scale is: \" , depth_scale)\n \n # We will be removing the background of objects more than\n # clipping_distance_in_meters meters away\n clipping_distance_in_meters = 6 #10 meter\n clipping_distance = clipping_distance_in_meters / depth_scale\n \n # Create an align object\n # rs.align allows us to perform alignment of depth frames to others frames\n # The \"align_to\" is the stream type to which we plan to align depth frames.\n align_to = rs.stream.color\n align = rs.align(align_to)\n \n colorizer = rs.colorizer() # TO colorize the depth image\n \n #FILTERS\n dec_filter = rs.decimation_filter () # Decimation - reduces depth frame density\n dec_filter.set_option(rs.option.filter_magnitude, 4)\n \n spat_filter = rs.spatial_filter() # Spatial - edge-preserving spatial smoothing\n spat_filter.set_option(rs.option.filter_magnitude, 5)\n spat_filter.set_option(rs.option.filter_smooth_alpha, 1)\n spat_filter.set_option(rs.option.filter_smooth_delta, 50)\n spat_filter.set_option(rs.option.holes_fill, 3)\n \n temp_filter = rs.temporal_filter() # Temporal - reduces temporal noise\n \n hole_filling = rs.hole_filling_filter() #FIll ALL THE HOLES\n #FILTERS END\n \n out = cv2.VideoWriter('data/read.avi',cv2.VideoWriter_fourcc('M','J','P','G'), 10, (1280,780))\n \n \n #Some Variables\n count = 0\n answer = {}\n \n cv2.namedWindow(\"W\")\n cv2.setMouseCallback(\"W\",mouse_callback)\n ix=False\n \n \n # Streaming loop\n try:\n while True:\n key = cv2.waitKey(1)\n # Press esc or 'q' to close the image window\n if key & 0xFF == ord('q') or key == 27:\n cv2.destroyAllWindows()\n break\n \n # Get frameset of color and depth\n frames = pipeline.wait_for_frames()\n # frames.get_depth_frame() is a 1280x720 depth image\n \n # Align the depth frame to color frame\n aligned_frames = align.process(frames)\n \n # Get aligned frames\n aligned_depth_frame = aligned_frames.get_depth_frame() # aligned_depth_frame is a 640x480 depth image\n \n # aligned_depth_frame = dec_filter.process(aligned_depth_frame)\n aligned_depth_frame = spat_filter.process(aligned_depth_frame) #Applying Filter\n aligned_depth_frame = temp_filter.process(aligned_depth_frame) #Applying Filter \n aligned_depth_frame = hole_filling.process(aligned_depth_frame)#Applying Filter \n \n color_frame = aligned_frames.get_color_frame() #Getting RGB frame\n \n # Validate that both frames are valid\n if not aligned_depth_frame or not color_frame:\n continue\n \n depth_image = np.asanyarray(aligned_depth_frame.get_data()) #Getting final depth image\n \n #Colorize the depth image\n colorized_depth = np.asanyarray(colorizer.colorize(aligned_depth_frame).get_data()) \n \n # #See the depth image\n # cv2.imshow(\"colorized depth\",rescale(colorized_depth,50))\n \n depth_image[depth_image>5000]=0\n \n color_image = np.asanyarray(color_frame.get_data()) #Getting final RGB frame\n \n if count == 0:\n answer[count]=[depth_image,color_image] #0 is the first image. can be used for background subtraction\n count+=1\n continue\n if ix:\n color_image1,check,values=apply_cascade(color_image.copy(),'models/cascades/haarcascade_lefteye_2splits.xml')\n if check:\n answer[count]=[depth_image,color_image]\n count+=1\n cv2.imshow('W', rescale(color_image,90))\n if len(answer)==15:\n break\n \n finally:\n pipeline.stop() #Turn off the camera\n cv2.destroyAllWindows() #Remove all the windows\n out.release()\n \n import pickle \n output = open('data/record_15.pkl', 'wb')\n pickle.dump(answer, output)\n output.close()\n\ndef find_highest(image): #unit8 single layer\n lowest=0\n for i in range(image.shape[0]):\n for j in range(image.shape[1]):\n if image[i][j]>lowest:\n return [j,i]\n return [0,0] \n\ndef find_lowest(image): #unit8 single layer\n lowest=0\n for i in range(image.shape[0]-1,-1,-1):\n for j in range(image.shape[1]-1,-1,-1):\n if image[i][j]>lowest:\n return [j,i]\n return [0,0] \n \ndef find_face_points(image):\n detector = dlib.get_frontal_face_detector()\n predictor = dlib.shape_predictor(\"models/cascades/shape_predictor_68_face_landmarks.dat\")\n gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n rects = detector(gray, 1)\n dic={}\n # loop over the face detections\n for (i, rect) in enumerate(rects):\n # determine the facial landmarks for the face region, then\n # convert the facial landmark (x, y)-coordinates to a NumPy\n # array\n shape = predictor(gray, rect)\n shape = face_utils.shape_to_np(shape)\n # convert dlib's rectangle to a OpenCV-style bounding box\n # [i.e., (x, y, w, h)], then draw the face bounding box\n (x, y, w, h) = face_utils.rect_to_bb(rect)\n cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)\n \t# show the face number\n cv2.putText(image, \"Face #{}\".format(i + 1), (x - 10, y - 10),\n cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)\n for (x, y) in shape:\n cv2.circle(image, (x, y), 3, (0, 255, 255), -1)\n dic[i]=shape\n return dic,image\n \n \ndef get_area(image,list1,tuple_list,depthimage):\n (j,k) = tuple_list\n pts = list1[j:k]\n hull = cv2.convexHull(pts)\n# cv2.drawContours(image, [hull], -1, (19,199,109), -1)\n rect = cv2.boundingRect(hull)\n cv2.rectangle(image,(rect[0],rect[1]),(rect[0]+rect[2],rect[1]+rect[3]),(0,255,0),3)\n\n area = depthimage[rect[1]-3:rect[1]+rect[3],rect[0]:rect[0]+rect[2]]\n return image,area,rect[0]\n\n \n \n\n#divider \n#%%\n \ndef detect():\n pkl_file = open('data/record_15.pkl', 'rb')\n record_15 = pickle.load(pkl_file)\n pkl_file.close()\n \n #Some Variables\n ix=False\n depth_scale=0.0010000000474974513\n \n first_depth,first_color = record_15[0]\n \n FACIAL_LANDMARKS_IDXS = OrderedDict([\n \t(\"mouth\", (48, 68)),\n \t(\"right_eyebrow\", (17, 22)),\n \t(\"left_eyebrow\", (22, 27)),\n \t(\"right_eye\", (36, 42)),\n \t(\"left_eye\", (42, 48)),\n \t(\"nose\", (27, 35)),\n \t(\"jaw\", (0, 17))\n ])\n\n \n answer=[]\n \n df = pd.DataFrame()\n temp = {}\n try:\n \n for i in range(1,len(record_15)):\n key = cv2.waitKey(1)\n # Press esc or 'q' to close the image window\n if key & 0xFF == ord('q') or key == 27:\n cv2.destroyAllWindows()\n break\n \n depth,color = record_15[i]\n dic1,image1 = find_face_points(color.copy())\n if len(dic1)<1:\n continue\n \n image,area,loc1 = get_area(color.copy(),dic1[0],FACIAL_LANDMARKS_IDXS[\"right_eye\"],depth) \n size = area.shape[0]*area.shape[1]\n re = iterate(area)*depth_scale*100\n \n image,area,loc2 = get_area(color.copy(),dic1[0],FACIAL_LANDMARKS_IDXS[\"left_eye\"],depth) \n size2 = area.shape[0]*area.shape[1]\n le = iterate(area)*depth_scale*100\n \n if min([size,size2])/max([size,size2])<0.8:\n continue\n# print([size,size2])\n \n \n if np.isnan(le) or np.isnan(re):\n continue\n \n loc = min(loc1,loc2)\n error = -1\n le+=error\n re+=error\n \n threshold = 70\n image3 = cv2.subtract(first_color,color)\n ret,a= cv2.threshold(image3,threshold,255,cv2.THRESH_BINARY)\n grayImage = cv2.cvtColor(a, cv2.COLOR_BGR2GRAY)\n grayImage[grayImage>threshold]=255\n grayImage[grayImage<=threshold]=0\n [x1,y1]=find_highest(grayImage)\n [x2,y2]=find_lowest(grayImage)\n height = abs(y2-y1)\n cv2.line(color,(0,y1),(1280,y1),(0,255,255),2) \n cv2.line(color,(0,y2),(1280,y2),(0,255,255),2) \n real_height1 = le*height/916.364501953125\n real_height2 = re*height/916.364501953125\n expected = 177.8*916.364501953125/height\n cv2.imshow(\"image\",rescale(color,75))\n temp = {\"Eye_l\":le,\"Eye_R\":re,\"pixel_height\":height,'expected':expected,'location':loc,'E_R':real_height2,'E_L':real_height1}\n df=df.append(temp,ignore_index=True)\n print(temp)\n \n finally:\n cv2.destroyAllWindows()\n return df\n#DIVIDER\n#%%\nrecord_15()\n\n#DIVIDER\n#%%\ndf = detect()","repo_name":"adityavyasbme/HeightMeasurement","sub_path":"distance_measurement/record_and_detect.py","file_name":"record_and_detect.py","file_ext":"py","file_size_in_byte":11069,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"31051733195","text":"import typing as T\nfrom qtpy import QtCore\nimport json\n\nfrom .node import Node\nfrom .edge import Edge\nfrom ..utils import layout_graph\nfrom ..utils.serialization import (\n serialize_nodes_and_edges,\n deserialize_graph\n)\n\nif T.TYPE_CHECKING:\n from ..graphics.scene import GraphicsScene\n from ..node_editor import NodeEditor\n\n\nclass Graph(QtCore.QObject):\n elements_changed = QtCore.Signal()\n node_added = QtCore.Signal(Node)\n node_removed = QtCore.Signal(Node)\n edge_added = QtCore.Signal(Edge)\n edge_removed = QtCore.Signal(Edge)\n\n def __init__(\n self,\n scene: T.Optional[\"GraphicsScene\"] = None,\n ) -> None:\n super().__init__()\n self.nodes: T.List[Node] = []\n self.edges: T.List[Edge] = []\n self.scene: T.Optional[\"GraphicsScene\"] = scene\n\n def add_node(self, node: Node):\n self.nodes.append(node)\n if self.scene:\n editor = self.scene.editor # type: ignore\n setting = editor.setting.node_item_setting\n if node.item is None:\n node.create_item(setting)\n assert node.item is not None\n self.scene.addItem(node.item)\n self.node_added.emit(node)\n self.elements_changed.emit() # type: ignore\n\n def add_nodes(self, *nodes: Node):\n for node in nodes:\n self.add_node(node)\n\n def remove_node(self, node: Node):\n if node not in self.nodes:\n return\n self.nodes.remove(node)\n if self.scene:\n assert node.item is not None\n self.scene.removeItem(node.item)\n for edge in node.input_edges + node.output_edges:\n self.remove_edge(edge)\n self.node_removed.emit(node)\n self.elements_changed.emit() # type: ignore\n\n def add_edge(self, edge: Edge):\n if edge in self.edges:\n return\n self.edges.append(edge)\n edge.source_port.edge_added.emit(edge)\n edge.target_port.edge_added.emit(edge)\n if self.scene:\n editor = self.scene.editor # type: ignore\n setting = editor.setting.edge_item_setting\n if edge.item is None:\n edge.create_item(setting)\n assert edge.item is not None\n self.scene.addItem(edge.item)\n self.edge_added.emit(edge)\n self.elements_changed.emit() # type: ignore\n\n def add_edges(self, *edges: Edge):\n for edge in edges:\n self.add_edge(edge)\n\n def remove_edge(self, edge: Edge):\n if edge not in self.edges:\n return\n self.edges.remove(edge)\n edge.source_port.edge_removed.emit(edge)\n edge.target_port.edge_removed.emit(edge)\n if self.scene:\n assert edge.item is not None\n self.scene.removeItem(edge.item)\n self.edge_removed.emit(edge)\n self.elements_changed.emit() # type: ignore\n\n def create_items(self):\n if self.scene:\n es = self.scene.editor.setting\n for node in self.nodes:\n node.create_item(es.node_item_setting)\n self.scene.addItem(node.item)\n for edge in self.edges:\n edge.create_item(es.edge_item_setting)\n self.scene.addItem(edge.item)\n\n def auto_layout(\n self,\n direction: str = \"LR\",\n padding_level: int = 100,\n padding_node: int = 20,\n ) -> None:\n if self.scene:\n layout_graph(\n self, direction=direction,\n padding_level=padding_level,\n padding_node=padding_node\n )\n else:\n raise ValueError(\"Scene is not set\")\n\n def sub_graph(self, nodes: T.List[Node]) -> \"SubGraph\":\n return SubGraph(nodes)\n\n def serialize(self) -> str:\n data = serialize_nodes_and_edges(self.nodes, self.edges)\n return json.dumps(data)\n\n @staticmethod\n def deserialize(\n data_str: str,\n editor: \"NodeEditor\",\n add_to_editor: bool = True,\n ) -> 'Graph':\n data = json.loads(data_str)\n return deserialize_graph(data, editor, add_to_editor)\n\n\nclass SubGraph:\n def __init__(\n self,\n nodes: T.List[Node],\n ) -> None:\n self.nodes = nodes\n self.edges = self.get_edges()\n\n def get_edges(self) -> T.List[Edge]:\n edges = set()\n for node in self.nodes:\n for edge in node.input_edges + node.output_edges:\n s_node = edge.source_port.node\n t_node = edge.target_port.node\n if (s_node in self.nodes) and (t_node in self.nodes):\n edges.add(edge)\n return list(edges)\n\n def _get_nodes_item_bounding_rect(self) -> QtCore.QRectF:\n rect = QtCore.QRectF()\n for node in self.nodes:\n assert node.item is not None\n rect = rect.united(node.item.sceneBoundingRect())\n return rect\n\n def join(\n self,\n graph: Graph,\n pos: T.Optional[QtCore.QPointF] = None,\n ) -> None:\n graph.add_nodes(*self.nodes)\n if pos is not None:\n bounding_rect = self._get_nodes_item_bounding_rect()\n top_left = bounding_rect.topLeft()\n for node in self.nodes:\n assert node.item is not None\n attr_pos = node.attrs.get(\"pos\")\n if attr_pos is not None:\n p = QtCore.QPointF(*attr_pos)\n node.item.setPos(p)\n offset = node.item.pos() - top_left\n new_pos = pos + offset\n node.item.setPos(new_pos)\n graph.add_edges(*self.edges)\n scene = graph.scene\n assert scene is not None\n scene.clearSelection()\n for node in self.nodes:\n assert node.item is not None\n node.item.setSelected(True)\n","repo_name":"Nanguage/easy-node","sub_path":"easynode/model/graph.py","file_name":"graph.py","file_ext":"py","file_size_in_byte":5952,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"3"} +{"seq_id":"8669916301","text":"from typing import Optional\nimport base64\n\n\nCLUSTER_NAME_HEADER = 'x-k8s-aws-id'\nTOKEN_PREFIX = 'k8s-aws-v1.'\nTOKEN_EXPIRATION_MINS = 14\nURL_TIMEOUT = 60\n\n\ndef get_presigned_url(sts_client, cluster_name, url_timeout: Optional[int] = None):\n if url_timeout is None:\n url_timeout = URL_TIMEOUT\n return sts_client.generate_presigned_url(\n 'get_caller_identity',\n Params={'ClusterName': cluster_name},\n ExpiresIn=url_timeout,\n HttpMethod='GET',\n )\n\n\ndef get_token(sts_client, cluster_name):\n _register_cluster_name_handlers(sts_client)\n url = get_presigned_url(sts_client, cluster_name)\n token = TOKEN_PREFIX + base64.urlsafe_b64encode(url.encode('utf-8')).decode('utf-8').rstrip('=')\n return token\n\n\n# The following function is excluded from code coverage because it is an event handler.\ndef _inject_cluster_name_header(request, **_kwargs): # pragma: no cover\n if 'eks_cluster' in request.context:\n request.headers[\n CLUSTER_NAME_HEADER] = request.context['eks_cluster']\n\n\ndef _register_cluster_name_handlers(sts_client):\n sts_client.meta.events.register(\n 'provide-client-params.sts.GetCallerIdentity',\n _retrieve_cluster_name\n )\n sts_client.meta.events.register(\n 'before-sign.sts.GetCallerIdentity',\n _inject_cluster_name_header\n )\n\n\n# The following function is excluded from code coverage because it is an event handler.\ndef _retrieve_cluster_name(params, context, **_kwargs): # pragma: no cover\n if 'ClusterName' in params:\n context['eks_cluster'] = params.pop('ClusterName')","repo_name":"animus-bi/scabbard","sub_path":"src/pantry/k8s/create/aws/eks/gettoken.py","file_name":"gettoken.py","file_ext":"py","file_size_in_byte":1606,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"41617749145","text":"\"\"\"\nThis module defines the all the table names of the database.\n\"\"\"\n\n__author__ = \"Marc Bermejo\"\n__credits__ = [\"Marc Bermejo\"]\n__license__ = \"GPL-3.0\"\n__version__ = \"0.1.0\"\n__maintainer__ = \"Marc Bermejo\"\n__email__ = \"mbermejo@bcn3dtechnologies.com\"\n__status__ = \"Development\"\n\n\n##################\n# PRINTER TABLES #\n##################\n\nPRINTER_MODELS_TABLE = 'printer_known_models'\nPRINTER_STATES_TABLE = 'printer_states'\nPRINTER_EXTRUDER_TYPES_TABLE = 'printer_extruder_types'\nPRINTER_MATERIALS_TABLE = 'printer_materials'\nPRINTER_EXTRUDERS_TABLE = 'printer_extruders'\nPRINTERS_TABLE = 'printers'\n\n\n##############\n# JOB TABLES #\n##############\n\nJOB_STATES_TABLE = 'job_states'\nJOB_ALLOWED_MATERIALS_TABLE = 'job_allowed_materials'\nJOB_ALLOWED_EXTRUDERS_TABLE = 'job_allowed_extruders'\nJOB_EXTRUDERS_TABLE = 'job_extruders'\nJOBS_TABLE = 'jobs'\n\n\n###############\n# USER TABLES #\n###############\n\nUSERS_TABLE = 'users'\n\n\n###############\n# FILE TABLES #\n###############\n\nFILES_TABLE = 'files'\n","repo_name":"markBETA/Queue-Manager-App-Database","sub_path":"models/table_names.py","file_name":"table_names.py","file_ext":"py","file_size_in_byte":993,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"37722042891","text":"# region IMPORTS\nfrom pathlib import Path\n\nfrom pyppeteer.page import Page\n\nfrom wplay.utils import target_search\nfrom wplay.utils.Logger import Logger\nfrom wplay.utils.helpers import whatsapp_selectors_dict\n# endregion\n\n\n# region FOR SCRIPTING\nasync def manual_select_target(page: Page, hide_groups: bool = False):\n __print_manual_selection_info()\n await __open_new_chat(page)\n target_focused_title = await __get_focused_target_title(page)\n await __wait_for_message_area(page)\n __print_selected_target_title(target_focused_title)\n complete_target_info = await target_search.__get_complete_info_on_target(page)\n target_search.__print_complete_target_info(complete_target_info)\n await __close_contact_info_page(page)\n return target_focused_title\n# endregion\n\n\n# region SELECT TARGET\ndef __print_manual_selection_info():\n print(f\"You've to go to whatsapp web and select target manually\")\n\n\ndef __print_selected_target_title(target_focused_title: str):\n print(f\"You've selected the target named by: {target_focused_title}\")\n\n\nasync def __close_contact_info_page(page: Page):\n try:\n await page.waitForSelector(\n whatsapp_selectors_dict['contact_info_page_close_button'],\n visible=True,\n timeout=5000\n )\n await page.click(whatsapp_selectors_dict['contact_info_page_close_button'])\n except Exception as e:\n print(e)\n\n\nasync def __open_new_chat(page: Page):\n await page.waitForSelector(\n whatsapp_selectors_dict['new_chat_button'],\n visible=True,\n timeout=0\n )\n\n\nasync def __get_focused_target_title(page: Page):\n try:\n await page.waitForSelector(whatsapp_selectors_dict['target_focused_title'], visible=True, timeout=0)\n target_focused_title = await page.evaluate(f'document.querySelector(\"{whatsapp_selectors_dict[\"target_focused_title\"]}\").getAttribute(\"title\")')\n except Exception as e:\n print(f'No target selected! Error: {str(e)}')\n exit()\n return target_focused_title\n\n\nasync def __wait_for_message_area(page: Page):\n try:\n await page.waitForSelector(whatsapp_selectors_dict['message_area'], timeout=0)\n except Exception as e:\n print(f\"You don't belong this group anymore! Error: {str(e)}\")\n# endregion\n","repo_name":"whatsplay/whatsapp-play","sub_path":"wplay/utils/target_select.py","file_name":"target_select.py","file_ext":"py","file_size_in_byte":2288,"program_lang":"python","lang":"en","doc_type":"code","stars":397,"dataset":"github-code","pt":"3"} +{"seq_id":"36634782462","text":"def bmi(weight, height):\n bmi = weight / (height/100) ** 2\n return bmi\n\n\ndef calculator():\n print(\"Let’s calculate your BMI (kg/m2)\")\n user_weight = float(input(\"What is your weight in kg?\"))\n user_height = float(input(\"What is your height in cm?\"))\n\n user_bmi = round(bmi(user_weight, user_height))\n\n if user_bmi < 18.5:\n print(f\"Your BMI is {user_bmi}. You are underweight\")\n elif user_bmi > 25:\n print(f\"Your BMI is {user_bmi}. You are overweight\")\n else:\n print(f\"Your BMI is {user_bmi}. You have normal weight\")\n\n\ncalculator()","repo_name":"TatianaPan/JavaScript-Exercises_new","sub_path":"Week3/day2/BMI_Calculator.py","file_name":"BMI_Calculator.py","file_ext":"py","file_size_in_byte":581,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"3649308530","text":"import imageio\nimport os\n\nfolder = \"PCiDS/sFCM/gifs\"\nims = []\nfor (s, w, files) in os.walk(folder):\n for f in sorted(list(files), key = lambda x : int(x.split('.')[0])):\n ims.append(os.path.join(folder, f))\n print(f)\n\nimages = [imageio.imread(f) for f in ims]\n\nimageio.mimsave(os.path.join(folder, 'out.gif'), images, duration = 1)","repo_name":"Lingermania/Project-Course-in-Data-Science","sub_path":"sFCM/gif_create.py","file_name":"gif_create.py","file_ext":"py","file_size_in_byte":348,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"3"} +{"seq_id":"21454558247","text":"\"\"\"\nGrid Transfer class for the induction\nmachine model \"im_3kW\". (https://gitlab.onelab.info/doc/models/-/wikis/Electric-machines)\n\nFor more details see: https://arxiv.org/abs/1912.03106\n\nInterpolation: standard finite element interpolation\nRestriction: injection\n\"\"\"\n\nimport copy\n\nimport numpy as np\n\nfrom pymgrit.core.grid_transfer import GridTransfer\nfrom pymgrit.induction_machine.vector_machine import VectorMachine\nfrom pymgrit.induction_machine.helper import check_version, compute_data, interpolation_factors, compute_mesh_transfer\n\n\nclass GridTransferMachine(GridTransfer):\n \"\"\"\n Grid Transfer class for the induction machine im_3kW\n Interpolation: standard finite element interpolation\n Restriction: injection\n \"\"\"\n\n def __init__(self, coarse_grid, fine_grid, path_meshes):\n \"\"\"\n Constructor. Compute the transfer grid between both given grids in both directions.\n\n :param coarse_grid: Coarse grid name\n :param fine_grid: Fine grid name\n :param path_meshes: Path to meshes\n \"\"\"\n super().__init__()\n data_coarse_pre = path_meshes + coarse_grid + '.pre'\n data_coarse_msh = path_meshes + coarse_grid + '.msh'\n check_version(msh_file=data_coarse_msh)\n data_coarse = compute_data(data_coarse_pre, data_coarse_msh, 0)\n\n data_fine_pre = path_meshes + fine_grid + '.pre'\n data_fine_msh = path_meshes + fine_grid + '.msh'\n check_version(msh_file=data_fine_msh)\n data_fine = compute_data(data_fine_pre, data_fine_msh, len(data_coarse['corToUn']))\n\n self.transfer_data = interpolation_factors(data_coarse=data_coarse, data_fine=data_fine)\n\n def restriction(self, u: VectorMachine) -> VectorMachine:\n \"\"\"\n Restriction\n\n :param u: approximate solution vector\n :return: input solution vector u restricted to a coarse grid\n \"\"\"\n ret = copy.deepcopy(u)\n ret.u_middle = ret.u_middle[:self.transfer_data['sizeLvlStart']]\n ret.u_middle_size = self.transfer_data['sizeLvlStart']\n return ret\n\n def interpolation(self, u: VectorMachine) -> VectorMachine:\n \"\"\"\n Interpolation\n\n :param u: approximate solution vector\n :return: input solution vector u interpolated to a fine grid\n \"\"\"\n ret = copy.deepcopy(u)\n\n new_middle = np.zeros(self.transfer_data['sizeLvlStop'] - self.transfer_data['sizeLvlStart'])\n\n new_u_inner = compute_mesh_transfer(\n u.u_middle[self.transfer_data['mappingInner']], self.transfer_data['vtxInner'],\n self.transfer_data['wtsInner'], self.transfer_data['addBoundInner'], 0)\n\n new_u_outer = compute_mesh_transfer(\n u.u_middle[self.transfer_data['mappingOuter']], self.transfer_data['vtxOuter'],\n self.transfer_data['wtsOuter'], self.transfer_data['addBoundOuter'], 0)\n new_middle[:len(u.u_middle)] = u.u_middle\n new_middle[self.transfer_data['mappingInnerNew']] = new_u_inner\n new_middle[self.transfer_data['mappingOuterNew']] = new_u_outer\n ret.u_middle = np.append(ret.u_middle, new_middle)\n ret.u_middle_size = len(ret.u_middle)\n return ret\n","repo_name":"pymgrit/pymgrit","sub_path":"src/pymgrit/induction_machine/grid_transfer_machine.py","file_name":"grid_transfer_machine.py","file_ext":"py","file_size_in_byte":3202,"program_lang":"python","lang":"en","doc_type":"code","stars":15,"dataset":"github-code","pt":"3"} +{"seq_id":"31320523466","text":"f = open(\"input.txt\", \"r\")\r\nlines = f.readlines()\r\nlines = list(map(int, lines))\r\nprevious = 100000000\r\ncount = 0\r\nfor i in range(len(lines)-2):\r\n window = lines[i] + lines[i+1] + lines[i+2]\r\n if window > previous:\r\n count += 1\r\n previous = window\r\nprint(count)\r\n","repo_name":"hng12/advent-of-code","sub_path":"2021/day1/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":279,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"6390603976","text":"from cv2 import cv2 as cv\nimport numpy as np\n\n#corners of wanting image = 109,159 - 346,259 - 350,460 - 100,570\nimg = cv.imread(\"Photos\\perspective.jfif\")\n\nwidth,height = 400,400\npts1 = np.float32([[109,159], [346,259], [100,570], [350,460]])\npts2 = np.float32([[0,0], [width,0], [0,height], [width,height]])\nmatrix = cv.getPerspectiveTransform(pts1,pts2)\nimgout = cv.warpPerspective(img, matrix, (width,height))\n\ncv.imshow(\"Img\", img)\ncv.imshow(\"NewImg\", imgout)\n\ncv.waitKey(0)\n","repo_name":"emresagir/OpenCV_LearningProjects","sub_path":"LearningScripts/WarpPerspective.py","file_name":"WarpPerspective.py","file_ext":"py","file_size_in_byte":479,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"12572081409","text":"import funciones\n\n\ningreso = 1\n\nwhile(ingreso==1):\n funciones.ejemplo2()\n\n entrada = int(input(\"\\nDesea volver a repetir el proceso:\\n 1 = SI\\n 2= NO\\n\"))\n\n if(entrada ==2):\n ingreso=2\n\n\n\n","repo_name":"bsalmeron/Ufide_Ejemplos_IIC","sub_path":"semana9/main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":204,"program_lang":"python","lang":"es","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"9949560135","text":"import numpy as np\nfrom scipy.ndimage.morphology import distance_transform_edt\nfrom skimage import measure\n\n\ndef distance_label(label):\n \"\"\" Cell and neigbhor distance label creation (Euclidean distance).\n\n :param label: Intensity-coded instance segmentation label image.\n :type label:\n\n :return: Cell distance label image, neighbor distance label image.\n \"\"\"\n\n # Preallocation\n label_dist = np.zeros(shape=label.shape, dtype=np.float)\n\n # Find centroids, crop image, calculate distance transforms\n props = measure.regionprops(label)\n for i in range(len(props)):\n\n # Get nucleus and Euclidean distance transform for each nucleus\n nucleus = (label == props[i].label)\n centroid, mal = np.round(props[i].centroid), int(1.2 * np.ceil(props[i].major_axis_length))\n if mal <= 1:\n continue\n nucleus_crop = nucleus[\n int(max(centroid[0] - mal, 0)):int(min(centroid[0] + mal, label.shape[0])),\n int(max(centroid[1] - mal, 0)):int(min(centroid[1] + mal, label.shape[1]))\n ]\n nucleus_crop_dist = distance_transform_edt(nucleus_crop)\n if np.max(nucleus_crop_dist) > 0:\n nucleus_crop_dist = nucleus_crop_dist / np.max(nucleus_crop_dist)\n label_dist[\n int(max(centroid[0] - mal, 0)):int(min(centroid[0] + mal, label.shape[0])),\n int(max(centroid[1] - mal, 0)):int(min(centroid[1] + mal, label.shape[1]))\n ] += nucleus_crop_dist\n\n return label_dist.astype(np.float32)\n","repo_name":"Team-ciscNet/ciscNet-CoNIC-Challenge-2022","sub_path":"segmentation/training/train_data_representations.py","file_name":"train_data_representations.py","file_ext":"py","file_size_in_byte":1555,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"3"} +{"seq_id":"40519728806","text":"import mysql.connector\n\nclass Initial():\n def __init__(self):\n self.conn = mysql.connector.connect(user='root', password='root',\n host='127.0.0.1',\n port=3306,\n database='streamapp')\n self.initial_database()\n\n\n\n def checkTableExists(self, tablename):\n cursor = self.conn.cursor()\n cursor.execute(\"\"\"\n SELECT COUNT(*)\n FROM information_schema.tables\n WHERE table_name = '{0}'\n \"\"\".format(tablename.replace('\\'', '\\'\\'')))\n if cursor.fetchone()[0] == 1:\n cursor.close()\n return True\n\n cursor.close()\n return False\n\n def initial_database(self):\n exist = self.checkTableExists('files') \n\n if not exist:\n qs = [\"\"\"\n CREATE TABLE users (\n id int not null AUTO_INCREMENT,\n name varchar(25) not null,\n email varchar(50) not null,\n last_name varchar(50) not null,\n birth_date datetime not null,\n genre varchar(2) not null,\n approved bit, \n role varchar(10), \n password varchar(25) not null, \n token varchar(60), \n PRIMARY KEY(id)\n )\n \"\"\",\n \"\"\"\n CREATE TABLE files (\n id int not null AUTO_INCREMENT,\n id_user int not null,\n name varchar(25) not null,\n ext varchar(50) not null,\n size_file_kb int not null,\n public bit not null,\n base64 BLOB,\n FOREIGN KEY (id_user) REFERENCES users(id),\n PRIMARY KEY(id) \n )\n \"\"\",\n \"\"\"\n CREATE TABLE file_share (\n id int not null AUTO_INCREMENT,\n id_user_share int not null,\n id_user_shared int not null,\n id_file int not null,\n date datetime not null, \n FOREIGN KEY (id_file) REFERENCES files(id),\n FOREIGN KEY (id_user_share) REFERENCES users(id),\n FOREIGN KEY (id_user_shared) REFERENCES users(id), \n PRIMARY KEY(id)\n ) \n \"\"\",\n \"\"\"\n CREATE TABLE logs (\n id int not null AUTO_INCREMENT,\n date_start datetime not null,\n date_end datetime not null,\n status varchar(10) not null,\n conteudo varchar(200), \n PRIMARY KEY(id)\n ) \n \"\"\"]\n\n cursor = self.conn.cursor()\n for q in qs: \n cursor.execute(q)\n self.conn.close()\n\n","repo_name":"igor-fortaleza/DriveFile","sub_path":"database.py","file_name":"database.py","file_ext":"py","file_size_in_byte":2909,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"41356009463","text":"import matplotlib\nfrom matplotlib import pyplot as plt\n\n\ndef pred_v_target_plot(timegap, outputdim, output_timesteps, preds, target,\n saveloc, scaler, lag: int = -1, outputdim_names : list = [], typeofplot: str = 'train'):\n\n\tif not outputdim_names:\n\t\toutputdim_names = ['Output']*outputdim\n\n\tplt.rcParams[\"figure.figsize\"] = (15, 5*outputdim*output_timesteps)\n\tfont = {'size':16}\n\tplt.rc('font',**font)\n\tplt.rc('legend',**{'fontsize':14})\n\n\t# Inerse scaling the data for each time step\n\tfor j in range(output_timesteps):\n\t\tpreds[:,j,:] = scaler.inverse_transform(preds[:,j,:])\n\t\ttarget[:,j,:] = scaler.inverse_transform(target[:,j,:])\n\n\n\t# training output\n\tfig, axs = plt.subplots(nrows = outputdim*output_timesteps, squeeze=False)\n\tfor i in range(outputdim):\n\t\tfor j in range(output_timesteps):\n\t\t\t# plot predicted\n\t\t\taxs[i+j, 0].plot(preds[:, j, i], 'r--', label='Predicted'+outputdim_names[i])\n\t\t\t# plot target\n\t\t\taxs[i+j, 0].plot(target[:, j, i], 'g--', label='Actual'+outputdim_names[i])\n\t\t\t# Plot Properties\n\t\t\taxs[i+j, 0].set_title('Predicted vs Actual at time = t + {} for {}'.format(-1*lag+j, outputdim_names[i]))\n\t\t\taxs[i+j, 0].set_xlabel('Time points at {} minute(s) intervals'.format(timegap))\n\t\t\taxs[i+j, 0].set_ylabel('Actual Energy')\n\t\t\taxs[i+j, 0].grid(which='both',alpha=100)\n\t\t\taxs[i+j, 0].legend()\n\t\t\taxs[i+j, 0].minorticks_on()\n\tfig.savefig(saveloc+str(timegap)+'_LSTM_'+typeofplot+'prediction.pdf', bbox_inches='tight')\n\tplt.close(fig)","repo_name":"AvisekNaug/labproj1","sub_path":"dataprocess/plotutils.py","file_name":"plotutils.py","file_ext":"py","file_size_in_byte":1457,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"27575825485","text":"import io, random\nimport keras\nimport numpy\nfrom keras.models import Sequential\nfrom keras.layers import Dense, Dropout, Activation\nfrom sklearn.model_selection import train_test_split\n\nchunk_size = 480\n\nmodel = Sequential()\nmodel.add(Dense(128, activation='tanh', input_dim=(chunk_size//2)))\nmodel.add(Dropout(0.25))\nfor x in range(3):\n model.add(Dense(128, activation='tanh'))\nmodel.add(Dense(1, activation='sigmoid'))\nmodel.compile(loss='binary_crossentropy',\n optimizer='rmsprop',\n metrics=['accuracy'])\n\nX = numpy.load('./data/samples.npy')\ny = numpy.load('./data/labels.npy')\n\nX_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n\nmodel.fit(X_train, y_train, epochs=50, batch_size=32, validation_data=(X_test, y_test))\n\nmodel.save(\"vad.h5\")\n#print(model.to_yaml())\n","repo_name":"stephan-dowding/mlvad","sub_path":"learn.py","file_name":"learn.py","file_ext":"py","file_size_in_byte":821,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"28646587984","text":"import logging\n\nfrom ask_sdk.standard import StandardSkillBuilder\nfrom ask_sdk_core.handler_input import HandlerInput\nfrom ask_sdk_core.utils import is_intent_name, is_request_type\nfrom ask_sdk_model import Response\nfrom ask_sdk_model.ui import SimpleCard\n\nsb = StandardSkillBuilder()\n\nlogger = logging.getLogger(__name__)\nlogger.setLevel(logging.INFO)\n\n\n@sb.request_handler(can_handle_func=is_request_type(\"LaunchRequest\"))\ndef launch_request_handler(handler_input: HandlerInput) -> Response:\n \"\"\"スキルを起動するハンドラー\"\"\"\n\n request_envelope = handler_input.request_envelope\n service_client_factory = handler_input.service_client_factory\n\n permissions = request_envelope.context.system.user.permissions # type: ignore\n logger.info(permissions)\n\n if not (permissions and permissions.consent_token):\n # TODO パーミッションがない場合の処理\n logger.info(\"パーミッションなし\")\n else:\n # タイマーをセットする\n logger.info(\"パーミッションあり\")\n\n timer1 = {\n \"duration\": \"PT3M\",\n \"timerLabel\": \"タイマー1\",\n \"creationBehavior\": {\"displayExperience\": {\"visibility\": \"VISIBLE\"}},\n \"triggeringBehavior\": {\n \"operation\": {\n \"type\": \"ANNOUNCE\",\n \"textToAnnounce\": [\n {\"locale\": \"ja-JP\", \"text\": \"火を止めて、スープの素を入れてください。\"}\n ],\n },\n \"notificationConfig\": {\"playAudible\": True},\n },\n }\n\n timer2 = {\n \"duration\": \"PT5M\",\n \"timerLabel\": \"タイマー2\",\n \"creationBehavior\": {\"displayExperience\": {\"visibility\": \"VISIBLE\"}},\n \"triggeringBehavior\": {\n \"operation\": {\n \"type\": \"ANNOUNCE\",\n \"textToAnnounce\": [{\"locale\": \"ja-JP\", \"text\": \"料理完了です。\"}],\n },\n \"notificationConfig\": {\"playAudible\": True},\n },\n }\n\n try:\n logger.info(\"タイマー作成開始\")\n\n timer_service_client = service_client_factory.get_timer_management_service()\n timer_response = timer_service_client.create_timer(timer1) # type: ignore\n logger.info(timer_response)\n\n timer_response = timer_service_client.create_timer(timer2) # type: ignore\n logger.info(timer_response)\n\n except Exception as e:\n logger.error(\"タイマー作成エラー\", e)\n\n speech_text = \"カレーうどんのタイマーを開始します。\"\n\n return (\n handler_input.response_builder.speak(speech_text)\n .set_card(SimpleCard(\"カレーうどんのタイマー\", speech_text))\n .set_should_end_session(False)\n .response\n )\n\n\n@sb.request_handler(can_handle_func=is_intent_name(\"AMAZON.HelpIntent\"))\ndef help_intent_handler(handler_input: HandlerInput) -> Response:\n \"\"\"Helpインテントのハンドラー。\"\"\"\n speech_text = \"こんにちは。と言ってみてください。\"\n\n return (\n handler_input.response_builder.speak(speech_text)\n .ask(speech_text)\n .set_card(SimpleCard(\"カレーうどんのタイマー\", speech_text))\n .response\n )\n\n\n@sb.request_handler(\n can_handle_func=lambda handler_input: is_intent_name(\"AMAZON.CancelIntent\")(\n handler_input\n )\n or is_intent_name(\"AMAZON.StopIntent\")(handler_input)\n)\ndef cancel_and_stop_intent_handler(handler_input: HandlerInput) -> Response:\n \"\"\"CancelおよびStopインテントの単一ハンドラー。\"\"\"\n speech_text = \"さようなら\"\n\n return (\n handler_input.response_builder.speak(speech_text)\n .set_card(SimpleCard(\"カレーうどんのタイマー\", speech_text))\n .response\n )\n\n\n@sb.request_handler(can_handle_func=is_intent_name(\"AMAZON.FallbackIntent\"))\ndef fallback_handler(handler_input: HandlerInput) -> Response:\n \"\"\"\n このハンドラーは、サポートされていないロケールではトリガーされません。\n そのため、どのロケールでも安全にデプロイできます。\n \"\"\"\n speech = \"カレーうどんのタイマースキルは、お手伝いできません。\" \"こんにちは。と言ってみてください。\"\n reprompt = \"こんにちは。と言ってみてください。\"\n handler_input.response_builder.speak(speech).ask(reprompt)\n return handler_input.response_builder.response\n\n\n@sb.request_handler(can_handle_func=is_request_type(\"SessionEndedRequest\"))\ndef session_ended_request_handler(handler_input: HandlerInput) -> Response:\n \"\"\"セッション終了のハンドラー。\"\"\"\n return handler_input.response_builder.response\n\n\n@sb.exception_handler(can_handle_func=lambda i, e: True)\ndef all_exception_handler(\n handler_input: HandlerInput, exception: Exception\n) -> Response:\n \"\"\"すべての例外ハンドラーを取得し、例外をログに記録して、\n カスタムメッセージで応答します。\n \"\"\"\n logger.error(exception, exc_info=True)\n\n speech = \"申し訳ありません。問題が発生しました。後でもう一度試してください。\"\n handler_input.response_builder.speak(speech).ask(speech)\n\n return handler_input.response_builder.response\n\n\nhandler = sb.lambda_handler()\n","repo_name":"tanny-pm/alexa-curry-udon-timer","sub_path":"src/lambda_function.py","file_name":"lambda_function.py","file_ext":"py","file_size_in_byte":5458,"program_lang":"python","lang":"ja","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"4970079539","text":"def solution(today, terms, privacies):\n t_year, t_month, t_day = map(int, today.split(\".\"))\n t_date = t_year*12 + t_month\n duration = {}\n for term in terms:\n name, date = term.split()\n duration[name] = int(date)\n answer = []\n tmp = 1\n for privacy in privacies:\n date, m_term = privacy.split()\n m_year, m_month, m_day = map(int, date.split(\".\"))\n m_date = m_year*12 + m_month + duration[m_term]\n if m_date < t_date:\n answer.append(tmp)\n elif m_date == t_date and m_day <= t_day:\n answer.append(tmp)\n tmp += 1\n return answer","repo_name":"goeom77/algorithm","sub_path":"프로그래머스/unrated/150370. 개인정보 수집 유효기간/개인정보 수집 유효기간.py","file_name":"개인정보 수집 유효기간.py","file_ext":"py","file_size_in_byte":624,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"32687218222","text":"# -*-coding:utf8-*-\n# 自己的解法\ndef check_bit(string):\n isEven = False\n num = 0\n for x in xrange(len(string) - 1):\n if string[i] is '1':\n num += 1\n if num % 2 == 0: isEven = True\n return isEven\n\ndef parity_bit(binary):\n lst = binary.split(\" \")\n for i in xrange(len(lst)):\n if check_bit(lst[i]):\n if lst[i][7] == '0':\n lst[i] = lst[i][:7]\n else:\n lst[i] = \"error\"\n else:\n if lst[i][7] == '1':\n lst[i] = lst[i][:7]\n else:\n lst[i] = \"error\"\n return ' '.join(lst)\n\n# 简化程序\ndef parity_bit(binary):\n res = ''\n for b in binary.split(' '):\n if b[:-1].count('1') % 2 == int(b[-1]):\n res += b[:-1] + ' '\n else:\n res += 'error '\n return res[:-1]\n\n# 使用函数\ndef parity_bit(binary):\n # your code here!\n def change(b):\n if b.count('1') % 2 == 0:\n return b[:-1]\n return 'error'\n\n res = map(change, binary.split())\n return \" \".join(res)\n\n# 一行代码\ndef parity_bit(binary):\n return ' '.join([w[:-1] if w[:-1].count('1') % 2 == int(w[-1]) else 'error' for w in binary.split()])","repo_name":"q13245632/CodeWars","sub_path":"ParitybitErrordetectingcode.py","file_name":"ParitybitErrordetectingcode.py","file_ext":"py","file_size_in_byte":1226,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"3697690876","text":"n = int(input())\na = list(map(int, input().split()))\nif sum(a)%len(a) == 0:\n ave = sum(a)/len(a)\n d_sum = 0\n bridge = len(a)\n for i in a:\n d_sum += i - ave\n if d_sum == 0:\n bridge -= 1\n print(bridge)\nelse:\n print(-1)\n","repo_name":"sakakazu2468/AtCoder_py","sub_path":"abc/027/b.py","file_name":"b.py","file_ext":"py","file_size_in_byte":260,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"7315807961","text":"import asyncio\n\nfrom common import common_config_ini\nfrom common import common_logging_elasticsearch_httpx\n\n\n# works fine hitting the database and doing the db_connection thing\n# passing NONE as it's NOT the pool webapp!!!!\n\nasync def main(loop):\n await common_logging_elasticsearch_httpx.com_es_httpx_post_async(message_type='info',\n message_text='START',\n index_name='testtest')\n # open the database\n option_config_json, db_connection = \\\n await common_config_ini.com_config_read_async(loop=loop,\n as_pool=False,\n force_local=True)\n db_result = await db_connection.db_table_count(table_name='mm_sync',\n db_connection=None)\n print(db_result)\n\n\nif __name__ == \"__main__\":\n loop = asyncio.get_event_loop()\n loop.run_until_complete(main(loop))\n","repo_name":"MediaKraken/MediaKraken_Deployment","sub_path":"source/test_asyncpg_mkdbclass.py","file_name":"test_asyncpg_mkdbclass.py","file_ext":"py","file_size_in_byte":1062,"program_lang":"python","lang":"en","doc_type":"code","stars":10,"dataset":"github-code","pt":"3"} +{"seq_id":"7536952856","text":"def min_skew(text):\n skew = 0\n min_skew_value = 0\n skew_indexes = list()\n for i, c in enumerate(text, 1):\n if c == 'C':\n skew -= 1\n elif c == 'G':\n skew += 1\n if skew < min_skew_value:\n min_skew_value = skew\n skew_indexes = [i]\n elif skew == min_skew_value:\n skew_indexes.append(i)\n return skew_indexes\n\nif __name__ == '__main__':\n with open('in.txt', 'r') as f:\n text = f.readline()\n skew_indexes = min_skew(text)\n with open('out.txt', 'w') as f:\n f.write(' '.join(map(str, skew_indexes)))\n","repo_name":"okainov/bioinf-algo-2015","sub_path":"_01_06_min_skew.py","file_name":"_01_06_min_skew.py","file_ext":"py","file_size_in_byte":612,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"3"} +{"seq_id":"31763560996","text":"import os\n\nclass Ifc():\n config = {\n 'FAM':{\n 'geometry_settings': False,\n 'params': {\n 'tag': ('Tekla Assembly', 'Assembly/Cast unit Mark'),\n 'cwp': ('Default', 'USER_FIELD_1'),\n }\n },\n 'EMALTO':{\n 'geometry_settings': False,\n 'params': {\n 'tag': ('Tekla Assembly', 'ASSEMBLY_POS'),\n 'cwp': ('Tekla Assembly', 'USER_FIELD_1'),\n 'fabricante': ('Tekla Assembly', 'USER_FIELD_2'),\n }\n },\n 'CODEME':{\n 'geometry_settings': False,\n 'params': {\n 'tag': ('Default', 'USER_FIELD_3'),\n 'cwp': ('Default', 'USER_FIELD_4'),\n }\n },\n 'SINOSTEEL':{\n 'geometry_settings': True,\n 'params': {\n 'tag': ('Tekla Assembly', 'Assembly/Cast unit Mark'),\n 'cwp': ('Default', 'USER_FIELD_1'),\n }\n }\n }\n\n\nclass Project():\n REPOSITORY_BRANCH = r'\\BI\\02. Repositório de Arquivos'\n DASHBOARD_BRANCH = r'\\BI\\01. Dashboards Ativos'\n\n def __init__(self, name:str, PROJECT_BRANCH:str) -> None:\n self.name = name\n self.PROJECT_PATH = os.environ['ROOT_PATH'] + PROJECT_BRANCH\n self.REPOSITORY_PATH = self.PROJECT_PATH + self.__class__.REPOSITORY_BRANCH\n self.DASHBOARD_PATH = self.PROJECT_PATH + self.__class__.DASHBOARD_BRANCH\n\n self.MEMORIA_CALCULO_PATH = os.path.dirname(os.environ['ROOT_PATH']) + r'\\02.Prazo\\Proj - Capanema\\_Old\\02. Cronograma AWP\\Memória de Cálculo'\n self.REPORTS_PATH = self.PROJECT_PATH + r'\\SMAT\\REPORT'\n self.SUMMARY_PATH = self.REPOSITORY_PATH+ r'\\Cronogramas\\Summary'\n self.LX_PATH = self.PROJECT_PATH + r'\\SMAT\\LX'\n self.LX_REPOSITORY_PATH = self.REPOSITORY_PATH + r'\\LX\\LX Geral'\n self.MAPPER_PATH = self.REPOSITORY_PATH + r'\\LX'\n self.MASTERPLAN_PATH = self.REPOSITORY_PATH + r'\\Cronogramas\\Masterplan'\n self.FORNECEDORES_PATH = self.REPOSITORY_PATH + r'\\Cronogramas\\Fornecedores'\n self.MONTADORA_PATH = self.REPOSITORY_PATH + r'\\Cronogramas\\Montadora'\n self.TRACER_PATH = self.REPOSITORY_PATH + r'\\Modelos BIM\\Stagging'\n self.PRODUCAO_PATH = self.REPOSITORY_PATH + r'\\Status de Producao'\n self.ROMANEIO_PATH = self.REPOSITORY_PATH + r'\\Romaneio'\n self.PQ_PATH = self.REPOSITORY_PATH + r'\\PQ'\n self.IFC_PATH = self.REPOSITORY_PATH + r'\\Modelos BIM\\IFC'\n self.DB_PATH = self.REPOSITORY_PATH + r'\\Modelos BIM\\DB Tracer'\n self.STAGGING_PATH = self.REPOSITORY_PATH + r'\\Modelos BIM\\Stagging'\n self.FEDERATED_PATH = self.REPOSITORY_PATH + r'\\Modelos BIM\\IFC com status'\n self.VCAD_PATH = self.REPOSITORY_PATH + r'\\VCad'\n\n self.OUTPUT_FAM = self.DASHBOARD_PATH + r'\\Fornecimento\\FAM Steel'\n self.OUTPUT_EMALTO = self.DASHBOARD_PATH + r'\\Fornecimento\\Emalto'\n self.OUTPUT_CODEME = self.DASHBOARD_PATH + r'\\Fornecimento\\Codeme'\n self.OUTPUT_SINOSTEEL = self.DASHBOARD_PATH + r'\\Fornecimento\\Sinosteel'\n self.OUTPUT_MONTAGEM_ELETROMECANICA = self.DASHBOARD_PATH + r'\\Montagem Eletromecanica'\n self.OUTPUT_GESTAO_MATERIAIS = self.DASHBOARD_PATH + r'\\Gestão de Materiais'\n self.OUTPUT_ML_LX = self.DASHBOARD_PATH + r'\\Checagem de LX'\n self.OUTPUT_FEDERADO = self.DASHBOARD_PATH + r'\\Modelo Federado'\n \n\n def __repr__(self) -> str:\n return self.name\n\n def dump(self):\n for key, value in self.__dict__.items():\n os.environ[f'{key}_{self.name}'] = value\n\n \ndef run_config():\n newsteel = Project('NEWSTEEL', r'\\Proj - New Steel')\n newsteel.dump()\n\n capanema = Project('CAPANEMA', r'\\Proj - Capanema')\n capanema.dump()\n\n","repo_name":"emmanuel-verum/SudestCraft","sub_path":"app/config/config.py","file_name":"config.py","file_ext":"py","file_size_in_byte":3807,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"12615718593","text":"\"\"\"\nTests for verified_track_content/partition_scheme.py.\n\"\"\"\n\n\nfrom datetime import datetime, timedelta\n\nimport pytz\nimport pytest\nfrom common.djangoapps.course_modes.models import CourseMode\nfrom common.djangoapps.student.models import CourseEnrollment\nfrom common.djangoapps.student.tests.factories import UserFactory\nfrom xmodule.modulestore.tests.django_utils import SharedModuleStoreTestCase # lint-amnesty, pylint: disable=wrong-import-order\nfrom xmodule.modulestore.tests.factories import CourseFactory # lint-amnesty, pylint: disable=wrong-import-order\nfrom xmodule.partitions.partitions import MINIMUM_STATIC_PARTITION_ID, UserPartition, ReadOnlyUserPartitionError # lint-amnesty, pylint: disable=wrong-import-order\n\nfrom ..partition_scheme import ENROLLMENT_GROUP_IDS, EnrollmentTrackPartitionScheme, EnrollmentTrackUserPartition\n\n\nclass EnrollmentTrackUserPartitionTest(SharedModuleStoreTestCase):\n \"\"\"\n Tests for the custom EnrollmentTrackUserPartition (dynamic groups).\n \"\"\"\n\n @classmethod\n def setUpClass(cls):\n super().setUpClass()\n cls.course = CourseFactory.create()\n\n def test_only_default_mode(self):\n partition = create_enrollment_track_partition(self.course)\n groups = partition.groups\n assert 1 == len(groups)\n assert 'Audit' == groups[0].name\n\n def test_multiple_groups(self):\n create_mode(self.course, CourseMode.AUDIT, \"Audit Enrollment Track\", min_price=0)\n # Note that the verified mode is expired-- this is intentional.\n create_mode(\n self.course, CourseMode.VERIFIED, \"Verified Enrollment Track\", min_price=1,\n expiration_datetime=datetime.now(pytz.UTC) + timedelta(days=-1)\n )\n # Note that the credit mode is not selectable-- this is intentional so we\n # can test that it is filtered out.\n create_mode(self.course, CourseMode.CREDIT_MODE, \"Credit Mode\", min_price=2)\n\n partition = create_enrollment_track_partition(self.course)\n groups = partition.groups\n assert 2 == len(groups)\n assert self.get_group_by_name(partition, 'Audit Enrollment Track') is not None\n assert self.get_group_by_name(partition, 'Verified Enrollment Track') is not None\n\n def test_to_json_supported(self):\n user_partition_json = create_enrollment_track_partition(self.course).to_json()\n assert 'Test Enrollment Track Partition' == user_partition_json['name']\n assert 'enrollment_track' == user_partition_json['scheme']\n assert 'Test partition for segmenting users by enrollment track' == user_partition_json['description']\n\n def test_from_json_not_supported(self):\n user_partition_json = create_enrollment_track_partition(self.course).to_json()\n with pytest.raises(ReadOnlyUserPartitionError):\n UserPartition.from_json(user_partition_json)\n\n def test_group_ids(self):\n \"\"\"\n Test that group IDs are all less than MINIMUM_STATIC_PARTITION_ID (to avoid overlapping\n with group IDs associated with cohort and random user partitions).\n \"\"\"\n for mode in ENROLLMENT_GROUP_IDS:\n assert ENROLLMENT_GROUP_IDS[mode]['id'] < MINIMUM_STATIC_PARTITION_ID\n\n @staticmethod\n def get_group_by_name(partition, name):\n \"\"\"\n Return the group in the EnrollmentTrackUserPartition with the given name.\n If no such group exists, returns `None`.\n \"\"\"\n for group in partition.groups:\n if group.name == name:\n return group\n return None\n\n\nclass EnrollmentTrackPartitionSchemeTest(SharedModuleStoreTestCase):\n \"\"\"\n Tests for EnrollmentTrackPartitionScheme.\n \"\"\"\n\n @classmethod\n def setUpClass(cls):\n super().setUpClass()\n cls.course = CourseFactory.create()\n cls.student = UserFactory()\n\n def test_get_scheme(self):\n \"\"\"\n Ensure that the scheme extension is correctly plugged in (via entry point in setup.py)\n \"\"\"\n assert UserPartition.get_scheme('enrollment_track') == EnrollmentTrackPartitionScheme\n\n def test_create_user_partition(self):\n user_partition = UserPartition.get_scheme('enrollment_track').create_user_partition(\n 301, \"partition\", \"test partition\", parameters={\"course_id\": str(self.course.id)}\n )\n assert isinstance(user_partition, EnrollmentTrackUserPartition)\n assert user_partition.name == 'partition'\n\n groups = user_partition.groups\n assert 1 == len(groups)\n assert 'Audit' == groups[0].name\n\n def test_not_enrolled(self):\n assert self._get_user_group() is None\n\n def test_default_enrollment(self):\n CourseEnrollment.enroll(self.student, self.course.id)\n assert 'Audit' == self._get_user_group().name\n\n def test_enrolled_in_nonexistent_mode(self):\n CourseEnrollment.enroll(self.student, self.course.id, mode=CourseMode.VERIFIED)\n assert 'Audit' == self._get_user_group().name\n\n def test_enrolled_in_verified(self):\n create_mode(self.course, CourseMode.VERIFIED, \"Verified Enrollment Track\", min_price=1)\n CourseEnrollment.enroll(self.student, self.course.id, mode=CourseMode.VERIFIED)\n assert 'Verified Enrollment Track' == self._get_user_group().name\n\n def test_enrolled_in_expired(self):\n create_mode(\n self.course, CourseMode.VERIFIED, \"Verified Enrollment Track\",\n min_price=1, expiration_datetime=datetime.now(pytz.UTC) + timedelta(days=-1)\n )\n CourseEnrollment.enroll(self.student, self.course.id, mode=CourseMode.VERIFIED)\n assert 'Verified Enrollment Track' == self._get_user_group().name\n\n def test_enrolled_in_non_selectable(self):\n create_mode(self.course, CourseMode.CREDIT_MODE, \"Credit Enrollment Track\", min_price=1)\n CourseEnrollment.enroll(self.student, self.course.id, mode=CourseMode.CREDIT_MODE)\n\n # The default mode is returned because Credit mode is filtered out, and no verified mode exists.\n assert 'Audit' == self._get_user_group().name\n\n # Now create a verified mode and check that it is returned for the learner enrolled in Credit.\n create_mode(self.course, CourseMode.VERIFIED, \"Verified Enrollment Track\", min_price=1)\n assert 'Verified Enrollment Track' == self._get_user_group().name\n\n def test_credit_after_upgrade_deadline(self):\n create_mode(self.course, CourseMode.CREDIT_MODE, \"Credit Enrollment Track\", min_price=1)\n CourseEnrollment.enroll(self.student, self.course.id, mode=CourseMode.CREDIT_MODE)\n\n # Create a verified mode and check that it is returned for the learner enrolled in Credit.\n # Make the mode \"expired\" to ensure that credit users can still see verified-only content after\n # the upgrade deadline has passed (see EDUCATOR-1511 for why this matters).\n create_mode(\n self.course, CourseMode.VERIFIED, \"Verified Enrollment Track\", min_price=1,\n expiration_datetime=datetime.now(pytz.UTC) + timedelta(days=-1)\n )\n assert 'Verified Enrollment Track' == self._get_user_group().name\n\n def _get_user_group(self):\n \"\"\"\n Gets the group the user is assigned to.\n \"\"\"\n user_partition = create_enrollment_track_partition(self.course)\n return user_partition.scheme.get_group_for_user(self.course.id, self.student, user_partition)\n\n\ndef create_enrollment_track_partition(course):\n \"\"\"\n Create an EnrollmentTrackUserPartition instance for the given course.\n \"\"\"\n enrollment_track_scheme = UserPartition.get_scheme(\"enrollment_track\")\n partition = enrollment_track_scheme.create_user_partition(\n id=1,\n name=\"Test Enrollment Track Partition\",\n description=\"Test partition for segmenting users by enrollment track\",\n parameters={\"course_id\": str(course.id)}\n )\n return partition\n\n\ndef create_mode(course, mode_slug, mode_name, min_price=0, expiration_datetime=None):\n \"\"\"\n Create a new course mode for the given course.\n \"\"\"\n return CourseMode.objects.get_or_create(\n course_id=course.id,\n mode_display_name=mode_name,\n mode_slug=mode_slug,\n min_price=min_price,\n suggested_prices='',\n _expiration_datetime=expiration_datetime,\n currency='usd'\n )\n","repo_name":"openedx/edx-platform","sub_path":"openedx/core/djangoapps/verified_track_content/tests/test_partition_scheme.py","file_name":"test_partition_scheme.py","file_ext":"py","file_size_in_byte":8367,"program_lang":"python","lang":"en","doc_type":"code","stars":6774,"dataset":"github-code","pt":"3"} +{"seq_id":"41494985691","text":"import numpy as np\nfrom PIL import Image\nimport rctobject.palette as pal\n\n\nclass Sprite:\n def __init__(self, image: Image.Image, coords: tuple = None, palette: pal.Palette = pal.orct, dither: bool = True, transparent_color: tuple = None):\n\n if image:\n image = pal.addPalette(image, palette, dither, transparent_color)\n\n bbox = image.getbbox()\n image = image.crop(bbox)\n\n else:\n image = Image.new('RGBA', (1, 1))\n\n self.image = image\n self.image_base = image\n if coords:\n self.x, self.y = coords\n self.x_base, self.y_base = coords\n else:\n self.x = -int(image.size[0]/2)\n self.y = -int(image.size[1]/2)\n self.x_base = int(self.x)\n self.y_base = int(self.y)\n\n self.palette = palette\n\n @classmethod\n def fromFile(cls, path: str, coords: tuple = None, palette: pal.Palette = pal.orct, dither: bool = True,\n transparent_color: tuple = None):\n \"\"\"Instantiates a new Sprite from an image file.\"\"\"\n image = Image.open(path).convert('RGBA')\n return cls(\n image=image, coords=coords, palette=palette, dither=dither, transparent_color=transparent_color)\n\n def save(self, path: str, keep_palette: bool = False):\n # Sprites should always be saved in the orct palette so that they can be read properly by the game\n if not keep_palette and self.palette is not pal.orct:\n self.switchPalette(pal.orct)\n self.image.save(path)\n\n def show(self, first_remap: str = 'NoColor', second_remap: str = 'NoColor', third_remap: str = 'NoColor'):\n return colorRemaps(self.image, first_remap, second_remap, third_remap)\n\n def giveProtectedPixelMask(self, color: str or list):\n return protectColorMask(self.image, color, self.palette)\n\n def resetSprite(self):\n self.image = self.image_base\n self.resetOffsets()\n\n def resetOffsets(self):\n self.x = int(self.x_base)\n self.y = int(self.y_base)\n\n def overwriteOffsets(self, x, y):\n self.x = x\n self.y = y\n self.x_base = x\n self.y_base = y\n\n def checkPrimaryColor(self):\n return checkPrimaryColor(self.image, self.palette)\n\n def checkSecondaryColor(self):\n return checkSecondaryColor(self.image, self.palette)\n\n def checkTertiaryColor(self):\n return checkTertiaryColor(self.image, self.palette)\n\n def checkColor(self, color_name: str):\n return checkColor(self.image, color_name, self.palette)\n\n def switchPalette(self, palette_new: pal.Palette, include_sparkles=True):\n self.image = pal.switchPalette(\n self.image, self.palette, palette_new, include_sparkles)\n self.palette = palette_new\n\n def changeBrightness(self, step: int, include_sparkles: bool = False):\n self.image = changeBrightness(\n self.image, step, self.palette, include_sparkles)\n\n def changeBrightnessColor(self, step: int, color):\n self.image = changeBrightnessColor(\n self.image, step, color, self.palette)\n\n def removeColor(self, color: str or list):\n self.image = removeColor(self.image, color, self.palette)\n\n def remapColor(self, color_name_old: str, color_name_new: str):\n self.image = remapColor(\n self.image, color_name_old, color_name_new, self.palette)\n\n def crop(self):\n bbox = self.image.getbbox()\n\n self.image = self.image.crop(bbox)\n self.x = self.x + bbox[0]\n self.y = self.y + bbox[1]\n\n def giveShade(self, coords):\n if coords[0] < 0 or coords[1] < 0:\n return None\n\n try:\n r, g, b, a = self.image.getpixel(coords)\n except IndexError:\n return None\n\n if a == 0:\n return None\n\n arr = self.palette.arr()\n red, green, blue = arr[:, :, 0], arr[:, :, 1], arr[:, :, 2]\n truth_arr = (red == r) & (green == g) & (blue == b)\n\n index = list(truth_arr.flatten()).index(True)\n\n color = list(self.palette.color_dict.keys())[int(index/12)]\n\n return (color, index % 12)\n\n\ndef pasteOnMask(mask: Image.Image, pic_in: Image.Image):\n mask_ar = np.array(mask)\n pic_ar = np.array(pic_in)\n pic_ar[:, :, 3] = mask_ar[:, :, 3]\n return Image.fromarray(pic_ar)\n\n\ndef mergeSprites(image1: Image.Image, image2: Image.Image, palette: pal.Palette = pal.orct):\n im = Image.alpha_composite(image2, image1)\n im = pal.addPalette(im, palette, dither=True)\n return im\n\n\ndef checkPrimaryColor(image: Image.Image, palette: pal.Palette = pal.orct):\n data = np.array(image)\n colors = palette.getColor('1st Remap')\n for color in colors:\n if np.equal(color, data[:, :, :3]).all(axis=2).any():\n return True\n\n return False\n\n\ndef checkSecondaryColor(image: Image.Image, palette: pal.Palette = pal.orct):\n data = np.array(image)\n colors = palette.getColor('2nd Remap')\n for color in colors:\n if np.equal(color, data[:, :, :3]).all(axis=2).any():\n return True\n\n return False\n\n\ndef checkTertiaryColor(image: Image.Image, palette: pal.Palette = pal.orct):\n data = np.array(image)\n colors = palette.getColor('3rd Remap')\n for color in colors:\n if np.equal(color, data[:, :, :3]).all(axis=2).any():\n return True\n\n return False\n\n\ndef checkColor(image: Image.Image, color_name: str, palette: pal.Palette = pal.orct):\n data = np.array(image)\n colors = palette.getColor(color_name)\n for shade in colors:\n if np.equal(shade, data[:, :, :3]).all(axis=2).any():\n return True\n\n return False\n\n\ndef remapColor(image: Image.Image, color_name_old: str, color_name_new: str, palette: pal.Palette = pal.orct):\n data_in = np.array(image)\n data_out = np.array(data_in)\n\n color_old = palette.getColor(color_name_old)\n color_new = palette.getColor(color_name_new)\n\n for i in range(12):\n\n r1, g1, b1 = color_old[i] # Original value\n r2, g2, b2 = color_new[i] # Value that we want to replace it with\n red, green, blue = data_in[:, :, 0], data_in[:, :, 1], data_in[:, :, 2]\n mask = (red == r1) & (green == g1) & (blue == b1)\n data_out[:, :, :][mask] = [r2, g2, b2, 255]\n\n return Image.fromarray(data_out)\n\n\ndef colorRemaps(image: Image.Image, first_remap: str, second_remap: str, third_remap: str, palette: pal.Palette = pal.orct):\n data_in = np.array(image)\n data_out = np.array(data_in)\n\n for color_names in [['1st Remap', first_remap], ['Pink', second_remap], ['Yellow', third_remap]]:\n if color_names[1] == 'NoColor':\n continue\n\n color_old = palette.getColor(color_names[0])\n color_new = palette.getRemapColor(color_names[1])\n\n for i in range(12):\n\n r1, g1, b1 = color_old[i] # Original value\n r2, g2, b2 = color_new[i] # Value that we want to replace it with\n red, green, blue = data_in[:, :,\n 0], data_in[:, :, 1], data_in[:, :, 2]\n mask = (red == r1) & (green == g1) & (blue == b1)\n data_out[:, :, :3][mask] = [r2, g2, b2]\n\n return Image.fromarray(data_out)\n\n\ndef colorFirstRemap(image: Image.Image, color_name: str, palette: pal.Palette = pal.orct):\n data_in = np.array(image)\n data_out = np.array(data_in)\n\n if color_name == 'NoColor':\n return image\n\n color_old = palette.getColor('1st Remap')\n color_new = palette.getRemapColor(color_name)\n\n for i in range(12):\n\n r1, g1, b1 = color_old[i] # Original value\n r2, g2, b2 = color_new[i] # Value that we want to replace it with\n red, green, blue = data_in[:, :, 0], data_in[:, :, 1], data_in[:, :, 2]\n mask = (red == r1) & (green == g1) & (blue == b1)\n data_out[:, :, :3][mask] = [r2, g2, b2]\n\n return Image.fromarray(data_out)\n\n\ndef colorSecondRemap(image: Image.Image, color_name: str, palette: pal.Palette = pal.orct):\n data_in = np.array(image)\n data_out = np.array(data_in)\n\n if color_name == 'NoColor':\n return image\n\n color_old = palette.getColor('Pink')\n color_new = palette.getRemapColor(color_name)\n\n for i in range(12):\n\n r1, g1, b1 = color_old[i] # Original value\n r2, g2, b2 = color_new[i] # Value that we want to replace it with\n red, green, blue = data_in[:, :, 0], data_in[:, :, 1], data_in[:, :, 2]\n mask = (red == r1) & (green == g1) & (blue == b1)\n data_out[:, :, :3][mask] = [r2, g2, b2]\n\n return Image.fromarray(data_out)\n\n\ndef colorThirdRemap(image: Image.Image, color_name: str, palette: pal.Palette = pal.orct):\n data_in = np.array(image)\n data_out = np.array(data_in)\n\n if color_name == 'NoColor':\n return image\n\n color_old = palette.getColor('Yellow')\n color_new = palette.getRemapColor(color_name)\n\n for i in range(12):\n\n r1, g1, b1 = color_old[i] # Original value\n r2, g2, b2 = color_new[i] # Value that we want to replace it with\n red, green, blue = data_in[:, :, 0], data_in[:, :, 1], data_in[:, :, 2]\n mask = (red == r1) & (green == g1) & (blue == b1)\n data_out[:, :, :3][mask] = [r2, g2, b2]\n\n return Image.fromarray(data_out)\n\n\ndef _decrBr(data_in, color):\n data_out = np.array(data_in)\n\n for i in range(12):\n j = i\n if (i > 0):\n j -= 1\n r1, g1, b1 = color[i] # Original value\n r2, g2, b2 = color[j] # Value that we want to replace it with\n red, green, blue = data_in[:, :, 0], data_in[:, :, 1], data_in[:, :, 2]\n mask = (red == r1) & (green == g1) & (blue == b1)\n data_out[:, :, :3][mask] = [r2, g2, b2]\n\n return data_out\n\n\ndef _incrBr(data_in, color):\n data_out = np.array(data_in)\n\n for i in range(12):\n j = i\n if (i < 11):\n j += 1\n r1, g1, b1 = color[i] # Original value\n r2, g2, b2 = color[j] # Value that we want to replace it with\n red, green, blue = data_in[:, :, 0], data_in[:, :, 1], data_in[:, :, 2]\n mask = (red == r1) & (green == g1) & (blue == b1)\n data_out[:, :, :3][mask] = [r2, g2, b2]\n\n return data_out\n\n\ndef changeBrightnessColor(image: Image.Image, value: int, color: str or list, palette: pal.Palette = pal.orct):\n data_in = np.array(image)\n data_out = np.array(data_in)\n\n if isinstance(color, str):\n color = [color]\n\n for color_name in color:\n\n color = palette.getColor(color_name)\n\n if not isinstance(color, np.ndarray):\n continue\n\n if (value < 0):\n for step in range(-value):\n for i in range(12):\n j = i\n if (i > 0):\n j -= 1\n r1, g1, b1 = color[i] # Original value\n # Value that we want to replace it with\n r2, g2, b2 = color[j]\n red, green, blue = data_in[:, :,\n 0], data_in[:, :, 1], data_in[:, :, 2]\n mask = (red == r1) & (green == g1) & (blue == b1)\n data_out[:, :, :3][mask] = [r2, g2, b2]\n else:\n for step in range(value):\n for i in range(12):\n j = i\n if (i < 11):\n j += 1\n r1, g1, b1 = color[i] # Original value\n # Value that we want to replace it with\n r2, g2, b2 = color[j]\n red, green, blue = data_in[:, :,\n 0], data_in[:, :, 1], data_in[:, :, 2]\n mask = (red == r1) & (green == g1) & (blue == b1)\n data_out[:, :, :3][mask] = [r2, g2, b2]\n\n return Image.fromarray(data_out)\n\n\ndef changeBrightness(image: Image.Image, step: int, palette: pal.Palette = pal.orct, include_sparkles=False):\n\n if include_sparkles and palette.has_sparkles:\n image = changeBrightnessColor(image, step, 'Sparkles', palette)\n elif include_sparkles:\n raise TypeError(\n 'Asked to include sparkles but given palette has no sparkles.')\n\n image = changeBrightnessColor(\n image, step, list(palette.color_dict), palette)\n\n return image\n\n\ndef removeColor(image: Image.Image, color: str or list, palette: pal.Palette = pal.orct):\n data_in = np.array(image)\n data_out = np.array(data_in)\n\n mask = np.full(image.size, False).T\n\n if isinstance(color, str):\n color = [color]\n\n for color_name in color:\n\n if color_name not in palette.color_dict:\n continue\n color_arr = palette.getColor(color_name)\n\n for shade in color_arr:\n r1, g1, b1 = shade # Original value\n red, green, blue = data_in[:, :,\n 0], data_in[:, :, 1], data_in[:, :, 2]\n mask = mask | ((red == r1) & (green == g1) & (blue == b1))\n\n data_out[:, :, :][mask] = [0, 0, 0, 0]\n\n return Image.fromarray(data_out)\n\n\ndef protectColorMask(image: Image.Image, color: str or list, palette: pal.Palette = pal.orct):\n data_in = np.array(image)\n\n mask = np.full(image.size, True).T\n\n if isinstance(color, str):\n color = [color]\n\n for color_name in color:\n\n if color_name not in palette.color_dict:\n continue\n color_arr = palette.getColor(color_name)\n\n for shade in color_arr:\n r1, g1, b1 = shade # Original value\n red, green, blue = data_in[:, :,\n 0], data_in[:, :, 1], data_in[:, :, 2]\n mask = mask & ~((red == r1) & (green == g1) & (blue == b1))\n\n return Image.fromarray(~mask)\n","repo_name":"danielmeinert/objectcreator","sub_path":"rctobject/rctobject/sprites.py","file_name":"sprites.py","file_ext":"py","file_size_in_byte":13802,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"27650029057","text":"import sys\nsys.path.append(\"trainer\")\n\nfrom datetime import datetime\n\nimport matplotlib.pyplot as plt\nimport wandb\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader\nfrom torchvision import transforms\n\nfrom my_dataset import myDataset\n\ndef train():\n with wandb.init() as run:\n\n now = datetime.now().isoformat(timespec='seconds')\n \n run.name = f\"sweep-{now}\"\n print(run.name)\n \n hparams = run.config\n hparams.NOW = now\n \n device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')\n print (\"torch version ::: %s\"%(torch.__version__))\n print (\"device ::: %s\"%(device))\n\n mnist_train = myDataset(\n name=\"MNIST_train\",\n data_path=hparams.DATA_PATH,\n train=True,\n transforms=transforms.ToTensor(),\n download=True\n )\n mnist_test = myDataset(\n name=\"MNIST_test\",\n data_path=hparams.DATA_PATH,\n train=False,\n transforms=transforms.ToTensor(),\n download=True\n )\n print (\"Dataset\")\n\n tr_loader = DataLoader(\n mnist_train,\n batch_size=hparams.BATCH_SIZE,\n shuffle=True,\n num_workers=hparams.NUM_WORKERS\n )\n val_loader = DataLoader(\n mnist_test,\n batch_size=hparams.BATCH_SIZE,\n shuffle=True,\n num_workers=hparams.NUM_WORKERS\n )\n print (\"DataLoader\")\n\n\n class simpleNetwork(nn.Module):\n def __init__(self):\n super(simpleNetwork,self).__init__()\n\n self.flatten = nn.Flatten()\n self.fc = nn.Linear(1*28*28, 10)\n \n def forward(self,x):\n x = self.flatten(x)\n x = self.fc(x)\n \n return x\n\n\n net = simpleNetwork().to(device)\n print(\"Model\")\n\n loss = nn.CrossEntropyLoss()\n print (\"loss\")\n opt = optim.Adam(net.parameters(), lr=hparams.LEARNING_RATE)\n print (\"opt\")\n\n\n\n\n for epoch in range(hparams.EPOCHS):\n tr_loss_sum, tr_acc_sum = 0, 0\n net.train() \n for X, y in tr_loader:\n X, y = X.to(device), y.to(device)\n \n y_pred = net(X)\n loss_out = loss(y_pred, y)\n \n opt.zero_grad()\n loss_out.backward()\n opt.step()\n \n tr_loss_sum += loss_out\n tr_acc_sum += (y_pred.argmax(axis=1)==y).sum().item()/len(y)\n tr_loss_avg = tr_loss_sum/len(tr_loader)\n tr_acc_avg = tr_acc_sum/len(tr_loader)\n print(f\"tr_loss_avg ::: {tr_loss_avg}, tr_acc_avg ::: {tr_acc_avg}\")\n wandb.log({\"train_loss\":tr_loss_avg, \"train_acc\":tr_acc_avg})\n\n val_loss_sum, val_acc_sum = 0, 0\n with torch.no_grad():\n net.eval()\n for X, y in val_loader:\n X, y = X.to(device), y.to(device)\n \n y_pred = net(X)\n loss_out = loss(y_pred, y)\n \n val_loss_sum += loss_out\n val_acc_sum += (y_pred.argmax(axis=1)==y).sum().item()/len(y)\n val_loss_avg = val_loss_sum/len(val_loader)\n val_acc_avg = val_acc_sum/len(val_loader)\n print(f\"val_loss_avg ::: {val_loss_avg}, val_acc_avg ::: {val_acc_avg}\")\n wandb.log({\"val_loss_avg\":val_loss_avg, \"val_acc_avg\":val_acc_avg})\n\n\n print (\"training finishes\")\n\n\n\n with torch.no_grad():\n net.eval() # to evaluation mode \n X, y = next(iter(val_loader))\n y_pred = net(X.to(device))\n y_pred = y_pred.argmax(axis=1)\n \n fig, ax = plt.subplots(5,5,figsize=(10,10))\n for i,(X,y_p) in enumerate(zip(X,y_pred)):\n div, mod = divmod(i,5)\n ax[div][mod].imshow(X.permute(1,2,0), cmap='gray')\n ax[div][mod].axis('off')\n ax[div][mod].set_title(f\"Prediction:{y_p}\")\n if i == 24:\n break\n wandb.log({\"plot\": fig})\n plt.savefig(hparams.SAVEFIG_NAME)\n\n print (\"result png\")\n\n print(\"done\")","repo_name":"hyun06000/MyTorchTemplate","sub_path":"trainer/trainer.py","file_name":"trainer.py","file_ext":"py","file_size_in_byte":4458,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"72912905040","text":"'''318最大单词长度成绩:\n\t给定一个字符串数组 words，找到 length(word[i]) * length(word[j]) 的最大值，并且这两个单词不含有公共字母。你可以认为每个单词只包含小写字母。如果不存在这样的两个单词，返回 0。\n'''\n'''本题主要问题是判断两个字符串是否含相同字符，由于字符串只含有小写字符，总共 26 位，因此可以用一个 32 位的整数来存储每个字符是否出现过。'''\n'''将ASCII字符转换为对应的数值即‘a’-->65，使用ord函数,ord('a')\n\n\n反正，使用chr函数，将数值转换为对应的ASCII字符，chr(65)'''\n\nclass Solution:\n def maxProduct(self, words: List[str]) -> int:\n ret = [0] * len(words)\n for i in range(len(words)):\n for j in words[i]:\n ret[i] |=1 << (ord(j)-ord('a'))\n \n res = 0\n for i in range(len(words)):\n for j in range(i+1, len(words)):\n if ret[i]&ret[j] == 0:\n res = max(res, len(words[i]) * len(words[j]))\n \n return res\n","repo_name":"AndongWen/leetcode","sub_path":"0109maxProduct.py","file_name":"0109maxProduct.py","file_ext":"py","file_size_in_byte":1111,"program_lang":"python","lang":"zh","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"28734131413","text":"\"\"\" Merge two sorted lists \"\"\"\ndef merge(list_a, list_b):\n c = []\n while list_a and list_b:\n if (list_a[0] < list_b[0]):\n c.append(list_a.pop(0))\n else:\n c.append(list_b.pop(0))\n if list_a:\n c = c + list_a\n elif list_b:\n c = c + list_b\n \n return c\n \n\ndef merge_sort(list):\n if len(list) == 1:\n return list\n left_list = list[0:len(list) // 2]\n right_list = list[len(list) // 2:]\n return merge(merge_sort(left_list), merge_sort(right_list))\n\nlist = [2, 13, 45, 21, 3, 56, 10, 7, 41, 9]\nprint(merge_sort(list))","repo_name":"JoaoPauloLousada/algorithms","sub_path":"python/05_merge_sort/merge_sort.py","file_name":"merge_sort.py","file_ext":"py","file_size_in_byte":545,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"28156429707","text":"from collections import defaultdict\nfrom string import punctuation\nimport sys\n\n# sites will insert an empty set when we try to call sites[k]\n# when k not in sites\nsites = defaultdict(set) \n\nfor file_name in sys.argv[1:]:\n for line in open(file_name):\n i = 0\n while True:\n site = None\n i = line.find(\"http://\", i)\n if i > -1:\n i += len(\"http://\")\n for j in range(i, len(line)):\n if not (line[j].isalnum() or line[j] in \".-\"):\n site = line[i:j].lower()\n i = j\n break\n if site and \".\" in site:\n sites[site.rstrip(punctuation)].add(file_name)\n else:\n break\n\nprint(sites)\n\n\"\"\"\nThere are three files to test on in ./data\nUsage: python Ch03Ex01.py data/file1.txt data/file2.txt data/file3.txt\n\"\"\"\n","repo_name":"LachlanMarnham/SolutionsToProgrammingInPython3","sub_path":"Chapter 03/Ch03Ex01.py","file_name":"Ch03Ex01.py","file_ext":"py","file_size_in_byte":918,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"29755072494","text":"import pytest\nfrom snake import application\nfrom snake import core\nfrom snake import user_interface\nfrom tests.fixtures import (\n fake_curses,\n fake_stdscr,\n)\nfrom tests.util import (\n fake_game_over,\n fake_getch_app,\n fake_pause\n)\n\n\n@pytest.mark.parametrize(\n \"attr, value\",\n [\n [\"LINES\", user_interface.PLAYGROUND_HEIGHT - 1],\n [\"COLS\", user_interface.PLAYGROUND_WIDTH - 1],\n ],\n)\ndef test_ensuring_terminal_size(\n monkeypatch, fake_curses, fake_stdscr, attr, value\n):\n monkeypatch.setattr(fake_curses, attr, value)\n with pytest.raises(AssertionError):\n application.main(fake_stdscr)\n\n\ndef test_user_input(monkeypatch, fake_curses, fake_stdscr):\n monkeypatch.setattr(fake_stdscr, \"getch\", fake_getch_app)\n monkeypatch.setattr(core.Game, \"pause\", fake_pause)\n with pytest.raises(SystemExit):\n application.main(fake_stdscr)\n","repo_name":"overclockworked64/snake.py","sub_path":"tests/test_application.py","file_name":"test_application.py","file_ext":"py","file_size_in_byte":894,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"32350344232","text":"class Solution: \n def findprime(self,n): #print primes upto n\n ans=[]\n for i in range(2,n+1):\n count1=0\n count2=0\n for j in range(2,int(i**0.5)+1):\n count1+=1\n if i%j!=0:\n count2+=1\n if count1==count2:\n ans.append(i) \n return ans \n def justgreater(self,primes,val): #find just greater element in prime using binary search\n start=0\n end=len(primes)-1\n candi=primes[0]\n while start<=end:\n mid=(start+end)//2\n if primes[mid]<=val: \n start=mid+1\n else:\n candi=primes[mid]\n end=mid-1\n return candi \n def primeSubOperation(self, nums: List[int]) -> bool:\n primes=self.findprime(1001) #print primes upto 1000\n for i in range(len(nums)-2,-1,-1):\n counter=0\n val=nums[i]\n if nums[i]= 0 and x < self._cap:\n return self[x]\n else:\n return False\n\n def add(self, x):\n if not self._ro:\n if x not in self:\n self._len += 1\n self[x] = True\n return x\n return False\n else:\n raise AttributeError(\"Set is read only\")\n\n def freeze(self):\n self._ro = True\n\n def __iter__(self):\n n = 0\n for x in range(self._cap):\n if n >= self._len:\n break\n if self[x]:\n n += 1\n yield x\n\n def __len__(self):\n return self._len\n\n def __str__(self):\n return repr(self)\n\n def __repr__(self):\n return f\"{{{', '.join(str(x) for x in iter(self))}}}\"\n\nclass TokenMatcher:\n def __init__(self, pat, tok=None, val=None, lookahead=None):\n self._creg = re.compile(pat)\n if self._creg.match(b\"\"):\n raise ValueError(\"Token regex may not match empty string\")\n self._val = val\n self._tok = tok\n self._lookahead = lookahead\n\n @property\n def ident(self):\n return self._tok\n\n def match(self, stream):\n m = self._creg.match(stream)\n if m and (self._lookahead is None or self._lookahead.match(stream)):\n n = m.end() - m.start()\n if callable(self._val):\n return n, self._val(m.group(0))\n else:\n return n, self._val\n\nclass Lexer:\n def __init__(self, grammar):\n # for this prototype, we read\n # the entire buffer into memory\n self._tokens = []\n self._grammar = grammar\n self._buf = None\n self._idx = 0\n\n @property\n def buf(self):\n return self._buf[self._idx:]\n\n def tokenize(self, buf):\n self._buf = memoryview(buf)\n self._idx = 0\n\n def token(self, pat, tok=None, val=None, lookahead=None):\n if tok is not None:\n if not self._grammar.isterm(tok):\n raise ValueError(\"Invalid token\")\n self._tokens.append(TokenMatcher(pat, tok, val, lookahead))\n return tok\n\n def nexttok(self):\n if self._buf is None:\n raise ValueError(\"Lexer has no input to tokenize\")\n\n ttok = None\n found = True\n\n while self.buf and found and ttok is None:\n tlen = 0\n tval = None\n found = False\n for tok in self._tokens:\n m = tok.match(self.buf)\n if m:\n if m[0] > tlen or not found:\n found = True\n tlen, tval = m\n ttok = tok.ident\n if not found:\n raise UnexpectedCharacter(chr(self.buf[0]), self._idx)\n if tlen:\n self._idx += tlen\n\n if ttok is not None:\n return ttok, tval\n else:\n return self._grammar.EOF, None\n\n def __iter__(self):\n return self\n\n def __next__(self):\n return self.nexttok()\n\nclass _GrammarBuilder:\n def __init__(self):\n self.symbols = 0\n self.productions = None\n\n self.names = []\n self.lookup = []\n self.rules = []\n self.actions = []\n\n def add_tok(self, name):\n # all tokens must be added first\n assert(self.productions is None)\n\n id = self.symbols\n self.symbols += 1\n self.names.append(name)\n return id\n\n\n def add_prod(self, name):\n if self.productions is None:\n self.productions = self.symbols\n\n id = self.symbols\n self.symbols += 1\n self.lookup.append([])\n self.names.append(name)\n return id\n\n def add_rule(self, rhs, lhs, action):\n # productions must be added first\n assert(self.productions is not None)\n\n id = len(self.rules)\n self.rules.append((rhs, lhs))\n self.actions.append(action)\n self.lookup[rhs - self.productions].append(id)\n\nclass GrammarMeta(type):\n def __new__(cls, classname, bases, classdict, **kwargs):\n\n # XXX: Not sure if its faster to loop through\n # the whole list every time (tok, prod, rules)\n # or to seperate everything into lists (allocations)\n # then iter each list. both ways would be O(N).\n # Not going to worry about it until its noticable.\n builder = _GrammarBuilder()\n syms = dict()\n pids = list()\n\n tokstart = builder.symbols\n\n # first add each token\n for name, member in classdict.items():\n if isinstance(member, _TokenID):\n id = builder.add_tok(name)\n syms[member.id] = id\n classdict[name] = id\n\n classdict[\"EOF\"] = builder.add_tok(\"EOF\")\n classdict[\"EPSILON\"] = builder.add_tok(\"EPSILON\")\n\n tokend = builder.symbols\n prodstart = builder.symbols\n\n goal = None\n\n # then each production\n for name, member in classdict.items():\n ispid = isinstance(member, _ProductionID)\n isgid = isinstance(member, _GoalID)\n\n if ispid or isgid:\n # add the production\n id = builder.add_prod(name)\n\n if isgid:\n if goal is not None:\n raise ValueError(\"Grammar cannot have multiple goals\")\n else:\n goal = id\n\n syms[member.id] = id\n classdict[name] = id\n pids.append(id)\n\n if goal is not None:\n # create an augmented grammar from the goal\n id = builder.add_prod(\"S'\")\n classdict[\"_goal\"] = id\n builder.add_rule(id, [goal], lambda x: x)\n\n # note production end point\n prodend = builder.symbols\n\n # now, add production rules for each _ProductionMethod\n for name, member in classdict.items():\n isrule = isinstance(member, rule)\n ismeth = isinstance(member, _ProductionMethod)\n\n # convert any rules to _ProductionMethods first\n if isrule:\n member = member(lambda *_: None)\n\n if isrule or ismeth:\n # add the rule to the builder\n lhs = syms[member.lhs.id]\n rhs = [syms[x.id] for x in member.rhs]\n builder.add_rule(lhs, rhs, member.fn)\n classdict[name] = member.fn\n\n # now ensure no empty Productions exist\n for id in pids:\n if not builder.lookup[id - prodstart]:\n raise ValueError(f\"Empty production: {builder.names[id]}\")\n\n # now add the builder lists to the new class\n # this is not perfect -- these lists are still\n # mutable, but we have the only reference to them\n # due to the builder reference being dropped after\n # this function. it would be nice to have them\n # as immutable without copying them to tuples\n # or something, but at a certain point, this\n # is python\n classdict[\"_names\"] = builder.names\n classdict[\"_rules\"] = builder.rules\n classdict[\"_lookup\"] = builder.lookup\n classdict[\"_actions\"] = builder.actions\n classdict[\"_tokstart\"] = tokstart\n classdict[\"_tokend\"] = tokend\n classdict[\"_prodstart\"] = prodstart\n classdict[\"_prodend\"] = prodend\n\n return type.__new__(cls, classname, bases, classdict)\n\n# Fake ID that gets replaced in GrammarMeta\nclass _TokenID(typing.NamedTuple):\n id: int\n\n# Fake ID that gets replaced in GrammarMeta\nclass _ProductionID(typing.NamedTuple):\n id: int\n\n# Fake ID that gets replaced in GrammarMeta\nclass _GoalID(typing.NamedTuple):\n id: int\n\n# Method wrapper to signify a decorated method for GrammarMeta\nclass _ProductionMethod(typing.NamedTuple):\n fn: types.MethodType\n lhs: _ProductionID\n rhs: typing.Sequence[_ProductionID]\n\n# adds a new production to the grammar. takes two arguments:\n# lhs: the left hand side of the production, a production id\n# rhs: the right hand side, a list of production and token ids\n#\n# may be used as a decorator or the return value may be assigned\n# as a class attribute\nclass rule:\n def __init__(self, lhs, rhs):\n self.lhs, self.rhs = lhs, rhs\n def __call__(self, fn):\n return _ProductionMethod(fn, self.lhs, self.rhs)\n\nclass Grammar(metaclass=GrammarMeta):\n _sid = 0\n\n @classmethod\n def newtok(cls):\n id = cls._sid\n cls._sid += 1\n return _TokenID(cls._sid)\n\n @classmethod\n def newprod(cls):\n id = cls._sid\n cls._sid += 1\n return _ProductionID(cls._sid)\n\n @classmethod\n def newgoal(cls):\n id = cls._sid\n cls._sid += 1\n return _GoalID(cls._sid)\n\n @classmethod\n def rules(cls, lhs):\n if lhs < cls._prodstart:\n raise IndexError\n return cls._lookup[lhs - cls._prodstart]\n\n @classmethod\n def action(cls, rndx):\n return cls._actions[rndx]\n\n @classmethod\n def rule(cls, rndx):\n return cls._rules[rndx]\n\n @classmethod\n def isterm(cls, id):\n if type(id) != int:\n breakpoint()\n if 0 <= id < cls._prodstart:\n return True\n elif id < cls._prodend:\n return False\n else:\n breakpoint()\n raise IndexError\n\n @classmethod\n def isprod(cls, id):\n return not cls.isterm(id)\n\n @classmethod\n def name(cls, id):\n return cls._names[id]\n\n @classmethod\n def productions(cls):\n return range(cls._prodstart, cls._prodend)\n\n @classmethod\n def tokens(cls):\n return range(cls._tokstart, cls._tokend)\n\n @classmethod\n def symbols(cls):\n return range(cls._tokstart, cls._prodend)\n\n @property\n def goal(cls):\n return cls._goal\n\n def __init__(self):\n if self.goal is None:\n raise ValueError(\"Missing goal for grammar\")\n\n def __len__(self):\n return self._prodend - self._tokstart\n\nclass Item:\n def __init__(self, grammar, rule, cursor):\n self.lhs, self.rhs = grammar.rule(rule)\n self.rule = rule\n self.cursor = cursor\n\n lname = grammar.name(self.lhs)\n rnames = [grammar.name(x) for x in self.rhs]\n lrname = \" \".join(x for x in rnames[:cursor])\n rrname = \" \".join(x for x in rnames[cursor:])\n self.description = f\"{lname} -> {lrname} . {rrname}\"\n\n def sym(self):\n if self.cursor >= 0 and self.cursor < len(self.rhs):\n return self.rhs[self.cursor]\n\n def __hash__(self):\n return hash((self.rule, self.cursor))\n\n def __eq__(self, other):\n return hash(self) == hash(other)\n\n def __str__(self):\n return self.description\n\n def __repr__(self):\n return f\"<{self.description}>\"\n\n# production table, either a list of FIRST or FOLLOW sets\nclass SymbolLookup(list):\n def __init__(self, grammar, *args, **kwargs):\n # initial max capacity/length\n self._cap = len(grammar)\n self._len = 0\n\n # load the initial list with the default values\n values = (self._default(grammar, x) for x in range(self._cap))\n super(SymbolLookup, self).__init__(values)\n\n # calculate the sets\n # for each production\n self._populate(grammar, *args, **kwargs)\n\n # now make each set frozen (readonly)\n for x in grammar.productions():\n self[x].freeze()\n\n def __contains__(self, x):\n if x >= 0 and x < self._cap:\n return bool(self[x])\n else:\n return False\n\n def __setitem__(self, k, v):\n raise AttributeError(\"first set is read-only\")\n\n def __call__(self, x):\n return super(SymbolLookup, self).__getitem__(x)\n\n def _default(self, grammar, sym):\n return None\n\n def _populate(self, grammar, *args, **kwargs):\n # populate each production set as necessary\n raise NotImplementedError\n\nclass First(SymbolLookup):\n def __init__(self, prsr):\n # prodtab init takes *args/**kwargs,\n # doing this to generate a better\n # error on invalid arguments\n super(First, self).__init__(prsr)\n\n def _default(self, prsr, sym):\n if prsr.isterm(sym):\n return frozenset((sym,))\n else:\n return intset(self._cap)\n\n def _populate(self, prsr):\n # add all productions to queue\n q = deque(prsr.productions())\n\n while q:\n # consume one value from queue,\n # re-add it to end of queue if it\n # caused a change in the set\n prod = q.popleft()\n fl = len(self[prod])\n if self._partial(prsr, prod) or not self[prod]:\n q.append(prod)\n\n # calculate the partial first set for one production\n def _partial(self, prsr, prod):\n added = False\n # first deal with terminals\n for rndx in prsr.rules(prod):\n r = prsr.rule(rndx)[1]\n # if the rule is of the form X: EPSILON\n a = all(i == prsr.EPSILON for i in r)\n # if the rule is of the form X: t B where t is a token != EPSILON\n b = prsr.isterm(r[0]) and r[0] != prsr.EPSILON\n if a or b:\n added |= bool(self[prod].add(r[0]))\n\n # now deal with productions\n for rndx in prsr.rules(prod):\n r = prsr.rule(rndx)[1]\n # loop productions until EPSILON not in rp\n for rp in r:\n if prsr.isprod(rp) and rp != prod:\n # add all values from first(rp)\n # that arent EPSILON\n for s in self[rp]:\n # dont add EPSILON here,\n # only if all rp have EPSILON.\n if s != prsr.EPSILON:\n added |= bool(self[prod].add(s))\n\n # add each nonterminal's first set to\n # prod's first as long as EPSILON is in\n # the nonterminal's first set. we break\n # when we have used all leading EPSILONs\n if (prsr.isterm(rp) and rp != prsr.EPSILON) or prsr.EPSILON not in self[rp]:\n break\n else:\n # for/else: this only triggers if EPSILON\n # was in every rp (break was never hit)\n # this means that every production in r\n # had EPSILON in its first set, implying\n # this also has EPSILON in its first set\n added |= bool(self[prod].add(prsr.EPSILON))\n\n return added\n\n\nclass Follow(SymbolLookup):\n def __init__(self, prsr, first):\n # prodtab init takes *args/**kwargs,\n # doing this to generate a better\n # error on invalid arguments\n super(Follow, self).__init__(prsr, first)\n\n def _default(self, prsr, sym):\n if prsr.isterm(sym):\n return None\n else:\n return intset(self._cap)\n\n def _populate(self, prsr, first):\n self[prsr.goal].add(prsr.EOF)\n\n # add all productions to queue\n q = deque(prsr.productions())\n\n while q:\n # consume one value from queue,\n # re-add it to end of queue if it\n # caused a change in the set\n prod = q.popleft()\n fl = len(self[prod])\n if self._partial(prsr, first, prod) or not self[prod]:\n q.append(prod)\n\n # calculate the partial follow set for one production\n def _partial(self, prsr, first, prod):\n added = False\n\n # for each rule starting with prod\n for rndx in prsr.rules(prod):\n rhs = prsr.rule(rndx)[1]\n # we want to track how far backward\n # into the rule EPSILON is in the first sets.\n # as long as EPSILON is in the first set\n # for the current production and all future\n # productions in the rule, then we need to add\n # the follow of the lhs to the follow of the\n # production.\n #\n # e.g.\n #\n # A -> BCDE\n # where EPSILON in FIRST(D) and FIRST(E),\n # then FOLLOW(C) has FOLLOW(A)\n #\n # Note: the EPSILON flag should always be true\n # for E, because its the end of the rule.\n # EPSILON may or may not be in FOLLOW(E) in\n # this example\n #\n # Also note: EPSILON is never added to a FOLLOW\n # set.\n eflag = True\n\n # iterate backwards so we have an EPSILON flag\n for x in reversed(range(len(rhs))):\n if prsr.isterm(rhs[x]):\n eflag = rhs[x] == prsr.EPSILON\n # FOLLOW is only for non-terminals\n # add nothing\n continue\n elif eflag:\n # update EPSILON flag for next iter\n eflag = prsr.EPSILON in first[rhs[x]]\n # Add FOLLOW(prod) - EPSILON to FOLLOW(rhs[x])\n for sp in self[prod]:\n if sp != prsr.EPSILON:\n added |= self[rhs[x]].add(sp)\n\n # at this point, we are either mid rule\n # ac, or at the end of the rule (ab)\n # if we are at the end of the rule, we're done.\n # otherwise, everything in FIRST(rhs[x+1]) is\n # placed into FOLLOW(rhs[x]) except EPSILON\n if x < len(rhs) - 1:\n # case aX\n # add first(X)) - EPSILON to FOLLOW(B)\n for fp in first[rhs[x+1]]:\n if fp != prsr.EPSILON:\n added |= self[rhs[x]].add(fp)\n return added\n\nclass ItemSets:\n def __init__(self, grammar):\n r0 = list(grammar.rules(grammar.goal))[0]\n i0 = Item(grammar, r0, 0)\n # list of item sets\n self._itemsets = [self._closure(grammar, [i0])]\n # lookup table for item sets\n self._lookup = []\n # load the items\n self._items(grammar)\n\n def goto(self, state, sym):\n return self._lookup[state][sym]\n\n def __getitem__(self, x):\n return self._itemsets[x]\n\n def _closure(self, grammar, items):\n c = intset(len(grammar))\n iset = set((x for x in items))\n\n dirty = True\n while dirty:\n # save the initial length\n n = len(c)\n # get each item in the set\n for i in list(iset):\n # get the symbol pointed to by the item in the rhs\n s = i.sym()\n if s is not None and grammar.isprod(s) and s not in c:\n # if its a new production, add each rule of the symbol\n # as a nonkernel item\n for r in grammar.rules(s):\n # add the new item to the itemset,\n # mark it as done\n c.add(s)\n iset.add(Item(grammar, r, 0))\n\n # update the dirty bit to reflect\n # if anything was added\n dirty = n != len(c)\n\n return tuple(iset)\n\n def _goto(self, grammar, items, sym):\n fwd = set()\n for i in items:\n if i.sym() == sym:\n fwd.add(Item(grammar, i.rule, i.cursor + 1))\n return self._closure(grammar, fwd)\n\n def _items(self, grammar):\n dirty = True\n while dirty:\n n = len(self._itemsets)\n # iterate current set of items in the closure\n # using an index. we only append to the list,\n # so this is safe to iterate\n for x in range(n):\n for s in grammar.symbols():\n # create the goto set\n d = self._goto(grammar, self._itemsets[x], s)\n if d:\n try:\n j = self._itemsets.index(d)\n self._add_lookup(grammar, x, s, j)\n except ValueError:\n self._itemsets.append(d)\n self._add_lookup(grammar, x, s, len(self._itemsets) - 1)\n else:\n self._add_lookup(grammar, x, s, -1)\n dirty = n != len(self._itemsets)\n\n def _add_lookup(self, grammar, state, sym, trans):\n if len(self._lookup) < len(self._itemsets):\n amt = len(self._itemsets) - len(self._lookup)\n arys = (array(\"I\", [len(grammar)]) for _ in range(amt))\n self._lookup.extend(arys)\n\n if grammar.isprod(sym):\n self._lookup[state][sym] = trans\n else:\n self._lookup[state][sym] = trans\n\n def __len__(self):\n return len(self._itemsets)\n\n def __iter__(self):\n return iter(self._itemsets)\n\nclass ActionEnum(enum.IntEnum):\n ACCEPT = 0\n REJECT = 1\n SHIFT = 2\n REDUCE = 3\n\nclass Action:\n def __init__(self, act, *args):\n self.action = ActionEnum(act)\n if self.action == ActionEnum.ACCEPT:\n if args:\n raise ValueError(\"Action ACCEPT expected zero arguments\")\n elif self.action == ActionEnum.REJECT:\n if args:\n raise ValueError(\"Action REJECT expected zero arguments\")\n elif self.action == ActionEnum.SHIFT:\n if len(args) != 1:\n raise ValueError(\"Action SHIFT expected one argument\")\n (self.state,) = args\n elif self.action == ActionEnum.REDUCE:\n if len(args) != 1:\n raise ValueError(\"Action REDUCE expected one argument\")\n (self.rule,) = args\n\n def __str__(self):\n if self.action == ActionEnum.ACCEPT:\n return \"acc\"\n elif self.action == ActionEnum.REJECT:\n return \"\"\n elif self.action == ActionEnum.SHIFT:\n return f\" s{self.state}\"\n elif self.action == ActionEnum.REDUCE:\n return f\" r{self.rule}\"\n\nclass ParsingTable:\n def __init__(self, grammar):\n self._first = First(grammar)\n self._follow = Follow(grammar, self._first)\n self._items = ItemSets(grammar)\n self._grammar = grammar\n\n self._actions = [\n [Action(ActionEnum.REJECT) for _ in range(len(grammar.tokens()))]\n for _ in range(len(self._items))]\n\n self._goto = [\n [\"\" for _ in range(len(grammar.productions()) - 1)]\n for _ in range(len(self._items))]\n\n self._minprod = len(grammar.tokens())\n for s in range(len(self._items)):\n for p in grammar.productions():\n if p == grammar.goal:\n continue\n x = p - self._minprod\n if self._items.goto(s, p) >= 0:\n self._goto[s][x] = self._items.goto(s, p)\n\n self._populate(grammar)\n\n def _populate(self, grammar):\n for i, iset in enumerate(self._items):\n for item in iset:\n s = item.sym()\n if s is not None:\n # terminal -- apply shift rule\n if grammar.isterm(s):\n j = self._items.goto(i, s)\n self._actions[i][s] = Action(ActionEnum.SHIFT, j)\n else:\n if item.lhs != grammar.goal:\n # end of production, add follow set of the lhs\n # (not including S')\n last = item.rhs[-1]\n for a in self._follow(item.lhs):\n if self._actions[i][a].action != ActionEnum.REJECT:\n raise ValueError(\"Grammar is not SLR(1)\")\n self._actions[i][a] = Action(ActionEnum.REDUCE, item.rule)\n else:\n if self._actions[i][grammar.EOF].action != ActionEnum.REJECT:\n raise ValueError(\"Grammar is not SLR(1)\")\n self._actions[i][grammar.EOF] = Action(ActionEnum.ACCEPT)\n\n def action(self, state, tok):\n return self._actions[state][tok]\n\n def goto(self, state, prod):\n return self._goto[state][prod - self._minprod]\n\n def actionstab(self):\n import tabulate\n toks = [self._grammar.name(x) for x in self._grammar.tokens()]\n return tabulate.tabulate(self._actions, headers=toks)\n\n def gototab(self):\n import tabulate\n prods = [self._grammar.name(x) for x in self._grammar.productions()]\n return tabulate.tabulate(self._goto, headers=prods)\n\nclass Parser:\n def __init__(self, lexer, grammar):\n self._grammar = grammar\n self._tab = ParsingTable(self._grammar)\n self._lexer = lexer\n\n def parse(self, input):\n self._lexer.tokenize(input)\n self._stack = [(0,None)]\n\n tok, val = next(self._lexer)\n\n while True:\n # get the action for current state + token\n state = self._peek()\n act = self._tab.action(state, tok)\n\n if act.action == ActionEnum.SHIFT:\n # add next state to the stack\n self._push((act.state, val))\n # update the current token\n tok, val = next(self._lexer)\n\n elif act.action == ActionEnum.REDUCE:\n # get the rule to reduce by and pop\n # |rhs| off the stack\n lhs, rhs = self._grammar.rule(act.rule)\n args = self._pop(len(rhs))\n # get new top of stack\n top = self._peek()\n # goto by lhs\n goto = self._tab.goto(top, lhs)\n assert(goto >= 0)\n # call the associated action\n rv = self._grammar.action(act.rule)(self._grammar, *args)\n self._push((goto, rv))\n\n elif act.action == ActionEnum.ACCEPT:\n return self._pop()[0]\n else:\n raise SyntaxError(f\"Invalid syntax: unexpected {tok.name}\")\n\n def _push(self, state):\n self._stack.append(state)\n\n def _pop(self, n=1):\n return [self._stack.pop()[1] for _ in range(n)]\n\n def _peek(self):\n return self._stack[-1][0]\n","repo_name":"krornus/larpy","sub_path":"larpy.py","file_name":"larpy.py","file_ext":"py","file_size_in_byte":27206,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"29478346816","text":"'''\nname = \"Presh\"\nx = '4'\nnick = 'Presh'\nessay = '''\n#This is my story an i want you to listen\n'''\nprint(essay)\n\nprint(\"Obi is a boy, isn't he?\")\n#using escape characters\nprint(\"The girl said\\t\\t\\t\\tObi is a boy, isn't he\\\"\")\nname = \"Presh\"\n\nprint('p'.upper() in name)\n'''\n'''\nname = \" Emmanuel is a boy\"\nprint(name[0:8])\n'''\n\n#Modifying strings\nname = 'Presh is a king'\nname = 'Presh is a man'\nprint(name)\n\n#strings concatenation\nname = 'Presh'\nSentence = ' is a man'\n\nprint(f'{name} {Sentence} and he is 25 years old')","repo_name":"Suzcerp/itechfor-bootcamp","sub_path":"strings.py","file_name":"strings.py","file_ext":"py","file_size_in_byte":521,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"32152268680","text":"#!/usr/bin/env python3\n#\n# PmUtils/pmdisco\n#\n'''\nCreated on Mar 2, 2020\n\n@author: kovi\n'''\nfrom os.path import isdir\nimport glob\n\n\nclass Discovery:\n\n BIAS_FOLDER = None\n DARK_FOLDER = None\n FLAT_FOLDER = None\n FLAT_BIAS_FOLDER = None\n FLAT_DARK_FOLDER = None\n LIGHT_FOLDERS = None\n\n def __init__(self, opt, pplSetup):\n self.flatOnly = opt['flatOnly']\n self.nonFlatFolderOnly = opt['useMasterFlat']\n self.folderPattern = opt['baseFolder']\n self.calibFolder = opt['calibFolder']\n self.ppl = pplSetup\n\n def findFolders(self, baseFolder, folderName):\n FOLDERS = None\n if baseFolder:\n FOLDERS = glob.glob('*' + baseFolder + '*/' + folderName)\n else:\n FOLDERS = glob.glob(folderName)\n return FOLDERS\n\n def discoverFolder(self, baseFolder, folderName, title):\n FOLDERS = self.findFolders(baseFolder, folderName)\n\n if len(FOLDERS) == 0:\n print(\"Error: no %s folder found; add one, and rerun this script.\" % (title))\n exit(1)\n\n if len(FOLDERS) != 1:\n print(\"Error: more than one %s folder found; remove on of them, and rerun this script.\" % (title))\n print(\" --> \" + ' '.join(FOLDERS))\n exit(1)\n\n if not isdir(FOLDERS[0]):\n print(\"Error: %s folder %s is not exist ot not a directory.\" % (title, FOLDERS[0]))\n exit(1)\n\n print(\"%s folder discovered: %s\" % (title, FOLDERS[0]))\n return FOLDERS[0]\n\n # discover Bias folder\n def discoverBiasFolder(self, baseFolder):\n self.BIAS_FOLDER = self.discoverFolder(baseFolder if not self.calibFolder else self.calibFolder, self.ppl['BIAS_FOLDER_NAME'], 'Bias')\n\n # discover Dark folder\n def discoverDarkFolder(self, baseFolder):\n self.DARK_FOLDER = self.discoverFolder(baseFolder if not self.calibFolder else self.calibFolder, self.ppl['DARK_FOLDER_NAME'], 'Dark')\n\n def discover(self):\n if not self.flatOnly:\n self.discoverBiasFolder(self.folderPattern)\n self.discoverDarkFolder(self.folderPattern)\n\n if not self.nonFlatFolderOnly:\n\n # discover flat bias folder\n FLAT_BIAS_FOLDERS = self.findFolders(self.folderPattern if not self.calibFolder else self.calibFolder, self.ppl['FLAT_BIAS_FOLDER_NAME'])\n if len(FLAT_BIAS_FOLDERS) > 1:\n print(\"Error: more than one %s folder found; remove on of them, and rerun this script.\" % ('Flat Bias'))\n print(\" --> \" + ' '.join(FLAT_BIAS_FOLDERS))\n exit(1)\n\n if len(FLAT_BIAS_FOLDERS) == 0 or not isdir(FLAT_BIAS_FOLDERS[0]):\n if self.flatOnly:\n self.discoverBiasFolder(self.folderPattern)\n self.FLAT_BIAS_FOLDER = self.BIAS_FOLDER\n else:\n self.FLAT_BIAS_FOLDER = FLAT_BIAS_FOLDERS[0]\n print(\"Flat Bias folder discovered: %s\" % (self.FLAT_BIAS_FOLDER))\n\n # discover flat dark folder\n FLAT_DARK_FOLDERS = self.findFolders(self.folderPattern if not self.calibFolder else self.calibFolder, self.ppl['FLAT_DARK_FOLDER_NAME'])\n if len(FLAT_DARK_FOLDERS) > 1:\n print(\"Error: more than one %s folder found; remove on of them, and rerun this script.\" % ('Flat Dark'))\n print(\" --> \" + ' '.join(FLAT_DARK_FOLDERS))\n exit(1)\n\n if len(FLAT_DARK_FOLDERS) == 0 or not isdir(FLAT_DARK_FOLDERS[0]):\n if self.flatOnly:\n self.discoverDarkFolder(self.folderPattern)\n self.FLAT_DARK_FOLDER = self.DARK_FOLDER\n else:\n self.FLAT_DARK_FOLDER = FLAT_DARK_FOLDERS[0]\n print(\"Flat Bias folder discovered: %s\" % (self.FLAT_DARK_FOLDER))\n\n # discover flat folder\n self.FLAT_FOLDER = self.discoverFolder(self.folderPattern if not self.calibFolder else self.calibFolder, self.ppl['FLAT_FOLDER_NAME'], 'Flat')\n\n if not self.flatOnly:\n\n # discovery Light folders\n self.LIGHT_FOLDERS = self.findFolders(self.folderPattern, self.ppl['LIGHT_FOLDER_NAME'])\n\n print(\"Light folders discovered:\" + ' '.join(self.LIGHT_FOLDERS))\n\n","repo_name":"kovihome/pmutil","sub_path":"pmutil/src/main/python/pmdisco.py","file_name":"pmdisco.py","file_ext":"py","file_size_in_byte":4268,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"6041089662","text":"from django import forms \nfrom .models import Input, MONTHS\n\nclass InputForm(forms.ModelForm): \n\n attrs = {'class ' : 'form−control ',\n 'onchange ' : 'this.form.submit() '}\n\n month = forms.ChoiceField(choices=MONTHS, required=True,\n widget=forms.Select(attrs = attrs))\n class Meta:\n model = Input\n fields = ['month']\n","repo_name":"Yawen17/NYC_uber","sub_path":"nyc/forms.py","file_name":"forms.py","file_ext":"py","file_size_in_byte":385,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"73381688402","text":"\"\"\"\nTopic: Monotonic Decreasing Stack\nGiven an array of integers temperatures represents the daily temperatures, return an array answer such that answer[i] is the number of days you have to wait after the ith day to get a warmer temperature.\nIf there is no future day for which this is possible, keep answer[i] == 0 instead.\nExample 1:\nInput: temperatures = [73,74,75,71,69,72,76,73]\nOutput: [1,1,4,2,1,1,0,0]\n\"\"\"\nfrom typing import List\n\n\nclass Solution:\n def dailyTemperatures(self, temperatures: List[int]) -> List[int]:\n \"\"\"\n .. doctest::\n >>> s = Solution()\n >>> s.dailyTemperatures([73,74, 75, 71, 69, 72, 76, 73])\n [1, 1, 4, 2, 1, 1, 0, 0]\n \"\"\"\n res = [0] * len(temperatures)\n stack = [] # pair [temp, index]\n\n for index, temp in enumerate(temperatures):\n while stack and temp > stack[-1][0]:\n stackTemp, stackIndex = stack.pop()\n res[stackIndex] = index - stackIndex\n stack.append([temp, index])\n return res\n\n\nif __name__ == \"__main__\":\n import doctest\n\n doctest.testmod()\n","repo_name":"erdenezul/leetcode","sub_path":"src/stack/daily_temperature.py","file_name":"daily_temperature.py","file_ext":"py","file_size_in_byte":1122,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"33016229525","text":"from translate import Translator\r\nfrom textblob import TextBlob\r\n\r\n\r\nclass Translation:\r\n\r\n def __init__(self, text):\r\n self.text = text\r\n\r\n def translate_word(self):\r\n\r\n lang = TextBlob(self.text)\r\n if lang.detect_language() == 'en':\r\n\r\n translator = Translator(from_lang='en', to_lang='hi')\r\n translation = translator.translate(self.text)\r\n return translation\r\n else:\r\n translator = Translator(from_lang='hi', to_lang='en')\r\n translation = translator.translate(self.text)\r\n return translation\r\n","repo_name":"vertika6/Learn-English","sub_path":"translator.py","file_name":"translator.py","file_ext":"py","file_size_in_byte":596,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"19697095330","text":"from threading import Thread\nfrom multiprocessing import Queue\nimport os\nimport cv2\nimport time\nimport qiniu\nfrom ava_auth import AuthFactory\nimport requests\nimport json\nfrom argparse import ArgumentParser\n\nstop_signal = False\nframe_data_queue = Queue()\nframe_url_queue = Queue()\n\n###########functions about get frame and add frame to frame data queue###############\n\ndef set_cap():\n cap = cv2.VideoCapture(0)\n cap.set(3,1280)\n cap.set(4,720)\n time.sleep(2)\n return cap\n \ndef get_frames(cap):\n global stop_signal\n while not stop_signal:\n _, frame = cap.read()\n framename = str(\"%.07f\" %time.time())\n frame_data_queue.put((framename,frame))\n cv2.imshow(\"capture\", frame)\n if cv2.waitKey(50) & 0xff == ord(\"q\"):\n stop_signal = True\n\n############functions about save frame and upload them to bucket and add url to frame_url_queue#######\n\nupload_access_key = \"********************************\"\nupload_secret_key = \"********************************\"\nbucket_name = \"framedecpose\"\nbucket_url = \"your bucket url like http://pargr4az5.bkt.clouddn.com/\"\nupload_auth = qiniu.Auth(upload_access_key, upload_secret_key)\n\ndef save_frame(frame_data, dir):\n if not os.path.exists(dir):\n os.mkdir(dir)\n\n filename = frame_data[0] + \".jpg\"\n filepath = os.path.join(dir, filename)\n frame = frame_data[1]\n cv2.imwrite(filepath, frame)\n filelistpath = os.path.join(dir, \"frame_list.txt\")\n with open(filelistpath, \"a\") as f:\n f.write(filename + \"\\n\")\n\n return filepath\n\ndef upload_single_frame(filepath):\n filename = os.path.basename(filepath)\n upload_token = upload_auth.upload_token(bucket_name, filename, 3600)\n ret, _ = qiniu.put_file(upload_token, filename, filepath)\n return ret[\"hash\"] == qiniu.etag(filepath)\n \ndef upload_frame(filepath, reupload=3):\n upload_success = False\n while not upload_success and reupload:\n upload_success = upload_single_frame(filepath)\n reupload -= 1\n if upload_success:\n frame_url = bucket_url + os.path.basename(filepath)\n frame_url_queue.put(frame_url)\n print(\"upload-> \" + frame_url + \" sucess!\")\n else:\n print(\"upload-> \" + frame_url + \" failed!\")\n return upload_success\n\ndef save_frames(frames_dir):\n while not stop_signal or not frame_data_queue.empty():\n if not frame_data_queue.empty():\n frame_data = frame_data_queue.get()\n filepath = save_frame(frame_data, frames_dir)\n upload_frame(filepath)\n\n\n###############functions about process frames\n\nprocess_access_key = \"******************************\"\nprocess_secret_key = \"******************************\"\nheader = {\"Content-Type\":\"application/json\"}\n\ndetect_url = \"http://serve.atlab.ai/v1/eval/facex-detect\"\npose_url = \"http://serve.atlab.ai/v1/eval/facex-pose\"\nprocess_auth = AuthFactory(process_access_key, process_secret_key).get_qiniu_auth()\n\ndef detect_frame(fileurl):\n data = {\"data\":{\"uri\":fileurl}}\n r = requests.post(detect_url, None, data, headers=header, auth=process_auth)\n contentObj = json.loads(r.content)\n # print(\"detected-> \" + fileurl)\n return contentObj[\"result\"]\n \ndef pose_frame(fileurl, det_rst):\n if len(det_rst[\"detections\"]) != 0:\n data = {\"data\":{\"uri\":fileurl, \"attribute\":det_rst}}\n r = requests.post(pose_url, None, data, headers=header, auth=process_auth)\n contentObj = json.loads(r.content)\n # print(\"posed-> \" + fileurl)\n # print(json.dumps(data))\n # print(r.content)\n if \"error\" in contentObj.keys():\n return {\"landmarks\":[]}\n else:\n return contentObj[\"result\"]\n else:\n return {\"landmarks\":[]}\n\ndef save_result(rstdir, fileurl, det_rst, pose_rst):\n if not os.path.exists(rstdir):\n os.mkdir(rstdir)\n with open(os.path.join(rstdir, \"detect_result.json\"), \"a\") as f:\n result = {\"url\":fileurl, \"result\":det_rst}\n f.write(json.dumps(result) + \"\\n\")\n with open(os.path.join(rstdir, \"pose_result.json\"), \"a\") as f:\n result = {\"url\":fileurl, \"result\":pose_rst}\n f.write(json.dumps(result) + \"\\n\")\n\ndef mark_frame_from_frame(frame, filename, rstdir, det_rst, pose_rst):\n if not os.path.exists(rstdir):\n os.mkdir(rstdir)\n for detection in det_rst[\"detections\"]:\n if detection[\"class\"] == \"face\":\n topleft = (int(detection[\"pts\"][0][0]), int(detection[\"pts\"][0][1]))\n bottomright = (int(detection[\"pts\"][2][0]), int(detection[\"pts\"][2][1]))\n cv2.rectangle(frame, topleft, bottomright, (255, 255, 0), 2)\n for landmark in pose_rst[\"landmarks\"]:\n topleftpoint = [99999, 99999]\n for point in landmark[\"landmark\"]:\n point = (int(point[0]), int(point[1]))\n cv2.circle(frame, point, 1, (0, 255, 255), 1)\n if point[0] < topleftpoint[0]:\n topleftpoint[0] = point[0]\n if point[1] < topleftpoint[1]:\n topleftpoint[1] = point[1]\n # print(topleftpoint)\n text = str(int(landmark[\"pos\"][0])) + \", \" + str(int(landmark[\"pos\"][1])) + \", \" + str(int(landmark[\"pos\"][2]))\n cv2.putText(frame, text, (topleftpoint[0], topleftpoint[1]), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 255, 255), 2)\n \n cv2.imwrite(os.path.join(rstdir, os.path.basename(filename)), frame)\n\ndef mark_frame_from_file(srcfilepath, rstdir, det_rst, pose_rst):\n if not os.path.exists(rstdir):\n os.mkdir(rstdir)\n frame = cv2.imread(srcfilepath)\n for detection in det_rst[\"detections\"]:\n if detection[\"class\"] == \"face\":\n topleft = (int(detection[\"pts\"][0][0]), int(detection[\"pts\"][0][1]))\n bottomright = (int(detection[\"pts\"][2][0]), int(detection[\"pts\"][2][1]))\n cv2.rectangle(frame, topleft, bottomright, (255, 255, 0), 2)\n for landmark in pose_rst[\"landmarks\"]:\n topleftpoint = [99999, 99999]\n for point in landmark[\"landmark\"]:\n point = (int(point[0]), int(point[1]))\n cv2.circle(frame, point, 1, (0, 255, 255), 1)\n if point[0] < topleftpoint[0]:\n topleftpoint[0] = point[0]\n if point[1] < topleftpoint[1]:\n topleftpoint[1] = point[1]\n text = str(int(landmark[\"pos\"][0])) + \", \" + str(int(landmark[\"pos\"][1])) + \", \" + str(int(landmark[\"pos\"][2]))\n cv2.putText(frame, text, (topleftpoint[0], topleftpoint[1]), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 255, 255), 2)\n\n cv2.imwrite(os.path.join(rstdir, os.path.basename(srcfilepath)), frame)\n print(\"marked-> \" + srcfilepath)\n\ndef process_frames(srcdir, rstdir):\n while not stop_signal or not frame_url_queue.empty():\n if not frame_url_queue.empty():\n frameurl = frame_url_queue.get()\n det_rst = detect_frame(frameurl)\n pose_rst = pose_frame(frameurl, det_rst)\n save_result(rstdir, frameurl, det_rst, pose_rst)\n srcfilepath = os.path.join(srcdir, os.path.basename(frameurl))\n mark_frame_from_file(srcfilepath, rstdir, det_rst, pose_rst)\n\n#######################combine the frames into video\n\ndef combine_frames_into_video(srcdir, rstdir):\n framefiles = []\n with open(os.path.join(srcdir, \"frame_list.txt\")) as f:\n framefiles = [line.strip() for line in f.readlines()]\n frames_time = float(os.path.splitext(framefiles[-1])[0]) - float(os.path.splitext(framefiles[0])[0])\n fps = int(len(framefiles)/frames_time)\n fourcc = cv2.VideoWriter_fourcc('m','p','4','v') \n src_video_writer = cv2.VideoWriter(os.path.join(srcdir, \"src_video.mp4\"), fourcc, fps, (1280, 720))\n rst_video_writer = cv2.VideoWriter(os.path.join(rstdir, \"rst_video.mp4\"), fourcc, fps, (1280, 720))\n for framefile in framefiles:\n srcframe = cv2.imread(os.path.join(srcdir, framefile))\n rstframe = cv2.imread(os.path.join(rstdir, framefile))\n # print(srcframe)\n src_video_writer.write(srcframe)\n rst_video_writer.write(rstframe)\n src_video_writer.release()\n rst_video_writer.release()\n\n\n\nif __name__ == \"__main__\":\n ap = ArgumentParser('draw boxs and points')\n ap.add_argument('-d', '--dir', required=True, type=str,\n help='dir to save frames data')\n args = ap.parse_args()\n dir = args.dir\n\n if os.path.exists(dir):\n print(\"dir already exists!\")\n os._exit(0)\n else:\n os.mkdir(dir)\n srcdir = os.path.join(dir, \"src_dir\")\n rstdir = os.path.join(dir, \"rst_dir\")\n # get_frame_thread = Thread(target = get_frames, args=(set_cap(),))\n save_frame_thread = Thread(target = save_frames, args=(srcdir,))\n process_frame_thread = Thread(target = process_frames, args=(srcdir, rstdir))\n \n # get_frame_thread.start()\n save_frame_thread.start()\n process_frame_thread.start()\n\n get_frames(set_cap())\n\n while save_frame_thread.is_alive() or process_frame_thread.is_alive():\n # print(\"There are already \" + str(frame_data_queue.qsize()) + \" frames last to upload!\")\n # print(\"There are already \" + str(frame_url_queue.qsize()+frame_data_queue.qsize()) + \" frames last to process!\")\n time.sleep(5)\n print(\"Combining frames into video...\")\n combine_frames_into_video(srcdir, rstdir)\n print(\"All is done!\")\n\n\n","repo_name":"miyaxu0312/mark_det_pose","sub_path":"demo_py27/mark_det_pose.py","file_name":"mark_det_pose.py","file_ext":"py","file_size_in_byte":9333,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"21481221695","text":"# coding: utf-8\r\n\r\nimport logging, time, os\r\nfrom logging.handlers import RotatingFileHandler\r\nfrom logging import handlers\r\n\r\npath = os.getcwd()\r\n\r\ne_path = os.path.join(path, 'logs')\r\nr_path = os.path.join(path, 'logs')\r\n\r\n# time_now = time.strftime('%y%m%d', time.localtime(time.time()))\r\ntime_now = str(int(time.time()))\r\nelog_name = os.path.join(e_path, 'excute') + time_now + '.log'\r\nrlog_name = os.path.join(r_path, 'excute') + time_now + '.log'\r\n\r\nif os.path.exists(os.path.dirname(elog_name)):\r\n pass\r\nelse:\r\n os.mkdir(os.path.dirname(elog_name))\r\n\r\nif os.path.exists(os.path.dirname(rlog_name)):\r\n pass\r\nelse:\r\n os.mkdir(os.path.dirname(rlog_name))\r\n\r\n\r\ndef excute_log(info_msg='', error_msg='', warning_msg=''):\r\n logger = logging.getLogger(__name__)\r\n logger.setLevel(level=logging.INFO)\r\n log_handle = RotatingFileHandler(elog_name, maxBytes=100 * 1024 * 1024, backupCount=20, )\r\n format = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s')\r\n log_handle.setFormatter(format)\r\n logger.addHandler(log_handle)\r\n try:\r\n if info_msg:\r\n logger.info(info_msg)\r\n elif error_msg:\r\n logger.error(error_msg)\r\n elif warning_msg:\r\n logger.warning(warning_msg)\r\n except Exception as e:\r\n print(e)\r\n\r\n logger.removeHandler(log_handle)\r\n\r\n\r\ndef result_log(msg):\r\n logger = logging.getLogger(__name__)\r\n logger.setLevel(level=logging.INFO)\r\n log_handle = logging.FileHandler(rlog_name, mode='a')\r\n format = logging.Formatter('%(asctime)s - %(message)s')\r\n log_handle.setFormatter(format)\r\n logger.addHandler(log_handle)\r\n\r\n try:\r\n logger.info(msg)\r\n print('\\n')\r\n except Exception as e:\r\n print(e)\r\n\r\n logger.removeHandler(log_handle)\r\n\r\n# msg = 'this is msg'\r\n# excute_log(msg)\r\n# print get_cases()[0]\r\n","repo_name":"StevenTang1010/edit_pcap","sub_path":"log.py","file_name":"log.py","file_ext":"py","file_size_in_byte":1860,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"3"} +{"seq_id":"74452964562","text":"import cv2.cv2 as cv2\nimport pandas as pd\n\ndef main():\n\t# df_labels = pd.read_csv('parsed_data.csv', index_col='frame', header=0)\n\tdf_labels = pd.read_csv('data/parsed_data.csv')\n\n\t## checking for NaNs\n\t# print(df_labels.isnull().sum().sum())\n\t# df_labels.dropna(inplace=True)\n\n\tcap = cv2.VideoCapture('data/top-100-shots-rallies-2018-atp-season.mp4')\n\n\tclass_index = 0\n\ttrain_size = 30000\n\twith open(\"data/object_detection/box_score_train.lst\", \"w+\") as file_out_train, open(\"data/object_detection/box_score_test.lst\", \"w\") as file_out_test:\n\n\t\tframe_counter = 0\n\t\tid_entry = 0\n\t\twhile True:\n\t\t\tout_file = file_out_train if frame_counter0 and len(y_0)>0 and len(x_1)>0 and len(y_1)>0:\n\t\t\t\t\t\tcv2.imwrite(f'data/object_detection/images/frame_{str(frame_counter).zfill(6)}.png', frame)\n\t\t\t\t\t\tout_file.write(f\"{id_entry}\\t{4}\\t{5}\\t{frame.shape[1]:}\\t{frame.shape[0]}\")\n\t\t\t\t\t\tx_0 = (x_0.iloc[0]/width)\n\t\t\t\t\t\ty_0 = (y_0.iloc[0]/height)\n\t\t\t\t\t\tx_1 = (x_1.iloc[0]/width)\n\t\t\t\t\t\ty_1 = (y_1.iloc[0]/height)\n\t\t\t\t\t\tout_file.write(f\"\\t{class_index}\\t{x_0:0.4f}\\t{y_0:0.4f}\\t{x_1:0.4f}\\t{y_1:0.4f}\\tframe_{str(frame_counter).zfill(6)}.png\\n\")\n\t\t\t\t\t\t# print(f'frame: {frame_counter} - x_0: {x_0}, y_0: {y_0}')\n\t\t\t\t\t\t# frame = cv2.rectangle(frame, (x_0,y_0), (x_1,y_1), (0,0,255), 4)\n\t\t\t\t\t\tid_entry += 1\n\n\n\t\t\t\tcv2.imshow('output', frame)\n\t\t\t\tframe_counter += 1\n\n\tcap.release()\n\tcv2.destroyAllWindows()\n\nif __name__ == '__main__':\n\tmain()","repo_name":"LewsTherin511/ocr","sub_path":"obj_det_generate_data.py","file_name":"obj_det_generate_data.py","file_ext":"py","file_size_in_byte":2019,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"6543802241","text":"\nfrom electrum.i18n import _\n\nfrom PyQt5.QtGui import *\nfrom PyQt5.QtCore import *\nfrom PyQt5.QtWidgets import QSlider, QToolTip\n\nimport threading\n\nclass FeeSlider(QSlider):\n\n def __init__(self, window, config, callback):\n QSlider.__init__(self, Qt.Horizontal)\n self.config = config\n self.window = window\n self.callback = callback\n self.dyn = False\n self.lock = threading.RLock()\n self.update()\n self.valueChanged.connect(self.moved)\n\n def moved(self, pos):\n with self.lock:\n fee_rate = self.config.dynfee(pos) if self.dyn else self.config.static_fee(pos)\n tooltip = self.get_tooltip(pos, fee_rate)\n QToolTip.showText(QCursor.pos(), tooltip, self)\n self.setToolTip(tooltip)\n self.callback(self.dyn, pos, fee_rate)\n\n def get_tooltip(self, pos, fee_rate):\n from electrum.util import fee_levels\n rate_str = self.window.format_fee_rate(fee_rate) if fee_rate else _('unknown')\n if self.dyn:\n tooltip = fee_levels[pos] + '\\n' + rate_str\n else:\n tooltip = 'Fixed rate: ' + rate_str\n if self.config.has_fee_estimates():\n i = self.config.reverse_dynfee(fee_rate)\n tooltip += '\\n' + (_('Low fee') if i < 0 else 'Within %d blocks'%i)\n return tooltip\n\n def update(self):\n with self.lock:\n self.dyn = self.config.is_dynfee()\n if self.dyn:\n pos = self.config.get('fee_level', 2)\n fee_rate = self.config.dynfee(pos)\n self.setRange(0, 4)\n self.setValue(pos)\n else:\n fee_rate = self.config.fee_per_kb()\n pos = self.config.static_fee_index(fee_rate)\n self.setRange(0, 9)\n self.setValue(pos)\n tooltip = self.get_tooltip(pos, fee_rate)\n self.setToolTip(tooltip)\n","repo_name":"lbtcio/lbtc-lightwallet-client","sub_path":"gui/qt/fee_slider.py","file_name":"fee_slider.py","file_ext":"py","file_size_in_byte":1952,"program_lang":"python","lang":"en","doc_type":"code","stars":22,"dataset":"github-code","pt":"3"} +{"seq_id":"70491201683","text":"from selectolax.parser import HTMLParser\nfrom typing import List\n\n\ndef parse_files(files: List[str], names: List[str]) -> List[str]:\n messages = []\n for file_name in files:\n with open(file_name) as file:\n body = file.read()\n\n messages += parse(body, names)\n\n return messages\n\n\ndef parse(body: str, names: List[str]) -> List[str]:\n messages = []\n for node in HTMLParser(body).css('div.msg_item'):\n if node.css_first('div.from').css_first('b').text() in names:\n subnode = node.css_first('div.msg_body')\n if subnode is None:\n continue\n\n text = subnode.text()\n print(text)\n messages.append(text)\n\n return messages\n\n\nif __name__ == '__main__':\n files = ['history.html', 'history_ls.html', 'history_potok.html']\n names = ['Anton Morozov']\n\n messages = parse_files(files, names)\n print(len(messages))\n\n with open('quotes.txt', 'w') as output:\n for message in messages:\n output.write(message + '\\n')\n","repo_name":"AntonyMoes/cyberhelper","sub_path":"parser.py","file_name":"parser.py","file_ext":"py","file_size_in_byte":1045,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"30421318241","text":"from pirate import Armada, Ship\nimport secrets\n\narmada1 = Armada()\narmada2 = Armada()\n\nfor i in range(200):\n rand = secrets.randbelow(100)\n ship = Ship()\n ship.fill_ship()\n\n if rand % 2 == 0:\n armada1.fleet.append(ship)\n else:\n armada2.fleet.append(ship)\n\narmada1.war(armada2)\n","repo_name":"green-fox-academy/hanzs_solo","sub_path":"Foundation/week_02-week_04/PythonBasicsProject/week_03/oop/pirates/war_app.py","file_name":"war_app.py","file_ext":"py","file_size_in_byte":306,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"12115728362","text":"from selenium import webdriver\nfrom selenium.webdriver.common.keys import Keys\nsites = [\n \"https://www.amazon.com/PlayStation-5-Console/dp/B08FC5L3RG?ref_=ast_sto_dp\"\n ,\"https://www.bestbuy.com/site/sony-playstation-5-console/6426149.p?skuId=6426149\"\n ,\"https://www.target.com/p/playstation-5-console/-/A-81114595\"\n ,\"https://www.walmart.com/ip/PlayStation5-Console/363472942\"\n ,\"https://deals.dell.com/en-us/compare/64x0\"\n ,\"https://www.newegg.com/p/N82E16868110292\"\n ,\"https://www.gamestop.com/video-games/playstation-5/consoles/products/playstation-5/11108140.html\"\n]\nlookFor = [\n [\"Currently unavailable.\",\"$499\"]\n ,\"Sold Out\"\n ,\"Out of stock\"\n ,[\"Out of stock\",\"online only at\"]\n ,\"Sorry, this deal has sold out.\"\n ,\"OUT OF STOCK.\"\n ,\"OUT OF STOCK\"\n ]\nstatus = {}\n#from twilio.rest import Client\n#client = Client(\"your_twillio_keys\", \"your_twillio_id\")\ndriver = webdriver.Chrome(\"'PathToDriver'/chromedriver.exe\")\nfor currentSite in range(len(sites)):\n driver.get(sites[currentSite])\n print(\"Checking:\" + driver.title)\n el = driver.find_element_by_tag_name('body')\n str1=el.text \n if (type(lookFor[currentSite]) == list):\n if(str1.find(lookFor[currentSite][0])!=-1):\n status[driver.title] = \"Not Available\"\n elif (str1.find(lookFor[currentSite][1])!=-1):\n status[driver.title] = \"In Stock\"\n else:\n status[driver.title] = \"In Stock from Scalpers, or restock scheduled\"\n else:\n if(str1.find(lookFor[currentSite])!=-1):\n status[driver.title] = \"Not Available\"\n else:\n status[driver.title] = \"In Stock\"\n\nprint (status)\ndriver.close()\n","repo_name":"ChristianRemwood/PS5_Alert_Bot","sub_path":"Alert_Bot.py","file_name":"Alert_Bot.py","file_ext":"py","file_size_in_byte":1688,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"37574937550","text":"def solve():\n n,m=map(int,input().split())\n weight=list(map(lambda x:int(x),input().split()))\n edges=[[0 for i in range(n)] for j in range(n)]\n\n # 初始化边\n cur=[]\n for i in range(n-1):\n edge=list(map(int,input().split()))\n edges[edge[0]-1][edge[1]-1]=1\n edges[edge[1]-1][edge[0]-1]=1\n\n # 寻找路线方法\n def find(fr,to,p):\n nonlocal cur\n if fr==to:\n cur= p\n return\n for ne in range(n):\n if edges[fr][ne]==1 and not (ne in p):\n find(ne,to,p+[ne])\n\n def getV(p,k):\n ws=list(map(lambda x:weight[x],p))\n ws.sort()\n return ws[k-1]\n\n last=0\n for i in range(m):\n u,v,k=map(int,input().split())\n ru=u ^ last\n find(ru-1,v-1,[ru-1])\n here=getV(cur,k)\n last=here\n print(here)\n\nif __name__ == '__main__':\n solve()","repo_name":"jingjiecb/python","sub_path":"5_7_24.py","file_name":"5_7_24.py","file_ext":"py","file_size_in_byte":899,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"15961077988","text":"# LeetCode Problem 21: Merge Two Sorted Lists\r\n# You are given the heads of two sorted linked lists list1 and list2.\r\n# Merge the two lists in a one sorted list. The list should be made by \r\n# splicing together the nodes of the first two lists.\r\n# Return the head of the merged linked list.\r\n\r\n# Definition for singly-linked list.\r\nclass ListNode:\r\n def __init__(self, val=0, next=None):\r\n self.val = val\r\n self.next = next\r\n\r\nfrom typing import Optional\r\n\r\nclass Solution:\r\n def mergeTwoLists(self, list1: Optional[ListNode], list2: Optional[ListNode]) -> Optional[ListNode]:\r\n\r\n # Instantiate the answer list with head and tail pointers on a dummy node\r\n head = tail = ListNode()\r\n\r\n # While nodes exist in both lists, compare the two current values and append \r\n # the lower one to the answer list\r\n while list1 and list2:\r\n if list1.val < list2.val:\r\n tail.next = list1\r\n list1 = list1.next\r\n else:\r\n tail.next = list2\r\n list2 = list2.next\r\n\r\n tail = tail.next\r\n\r\n # If one list runs out of nodes, append the rest of the remaining list to the\r\n # answer's tail. This works because both lists are already ordered.\r\n if list1:\r\n tail.next = list1\r\n elif list2:\r\n tail.next = list2\r\n\r\n # Head was pointing to a dummy value, so returning head.next\r\n # will be the first node in our answer\r\n return head.next\r\n","repo_name":"tkinneen/leetcodeProblems","sub_path":"Problem_021_Merge_Two_Sorted_Lists/Solution.py","file_name":"Solution.py","file_ext":"py","file_size_in_byte":1541,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"32342535004","text":"import pygame #파이게임 임포트\nfrom pygame.locals import QUIT, Rect, KEYDOWN, K_UP, K_LEFT, K_RIGHT, K_DOWN\n #종료,직각,키 종료,위,왼쪽,오른쪽,아래\n##########################################################################################\nimport random # 랜덤 파일 임포트\nimport sys # 시스템 파일 임포트\n\n#2. 게임 설정\nscore = 0\npygame.init()\nscreen = pygame.display.set_mode((1000, 1000))\nframe = pygame.time.Clock()\n\nfood = [] #음식 위치 저장\nsnake = [] #뱀 꼬리 위치 저장\n(width, height) = (33, 35) # 가로 x 세로\n\n#3.함수 만들기\n#3-1. 음식 생성\ndef food_create():\n while True:\n pos = (random.randint(0, width-1), random.randint(0, height-1))\n if pos in food or pos is snake:\n continue\n food.append(pos)\n break\n#3-2. 음식 이동\ndef food_move(pos):\n i = food.index(pos)\n del food[i]\n food_create()\n#3-3. 음식 그리기\ndef draw(message):\n global screen\n screen.blit(background, (0, 0))\n for f in food:\n pygame.draw.ellipse(screen, (0, 255, 0), Rect( (f[0])*30, (f[1])*30, 30, 30 ) )\n for body in snake:\n pygame.draw.rect(screen, (0, 255, 255), Rect(body[0]*30, body[1]*30, 30, 30))\n for index in range(34):\n pygame.draw.line(screen, (64, 64, 64), (index * 30, 0), (index * 30, 1000))\n pygame.draw.line(screen, (64, 64, 64), (0, index * 30), (1000, index * 30))\n if message != None:\n screen.blit(message, (500, 500))\n pygame.display.update()\n\n#4.게임 실행\n\nbackground = pygame.image.load(\"background.png\")\n\nmyfont = pygame.font.SysFont(None, 80)\nkey = K_DOWN\nmessage = None\ngameover = False\nsnake.append( (int(width/2), int(height/2)) )\nfor i in range(10):\n food_create()\n\nwhile True:\n score = len(snake) - 1\n for event in pygame.event.get():\n if event.type == QUIT:\n pygame.quit()\n sys.exit()\n elif event.type == KEYDOWN:\n key = event.key\n if not gameover:\n if key == K_LEFT:\n head = (snake[0][0] - 1, snake[0][1])\n elif key == K_RIGHT:\n head = (snake[0][0] + 1, snake[0][1])\n elif key == K_UP:\n head = (snake[0][0], snake[0][1] - 1)\n elif key == K_DOWN:\n head = (snake[0][0], snake[0][1] + 1)\n if head in snake or head[0] < 0 or head[0] >= width or head[1] < 0 or head[1] >= height:\n message = myfont.render(\"Game over\", True, (255, 255, 0))\n gameover = True\n snake.insert(0, head)\n if head in food:\n food_move(head)\n else:\n snake.pop()\n\n draw(message)\n frame.tick(score//10*5 + 5)","repo_name":"name165/300prob","sub_path":"game/뱀게임.py","file_name":"뱀게임.py","file_ext":"py","file_size_in_byte":2700,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"33746456764","text":"from datetime import datetime, timedelta\nfrom html import escape\nimport hashlib\nimport json\nfrom time import time\nfrom urllib.parse import urlparse\nfrom uuid import uuid4\n\nfrom flask import Flask, render_template, request, redirect, jsonify, url_for, session\nimport pymysql\nimport hashlib\nimport bcrypt\nimport jwt\nfrom flask_jwt_extended import (\n JWTManager, jwt_required, jwt_optional, create_access_token, get_jwt_identity, get_jwt_claims)\nfrom pip._vendor import requests\n\napp = Flask(__name__)\napp.secret_key = b'1234wqerasdfzxcv'\ndb = pymysql.connect(host = 'localhost' , port = 3306 , user = 'root' , passwd = '8813' , db = 'hackaton' , charset = 'utf8') # db 접속 본인 환경맞춰 설정\ncursor = db.cursor() # 객체에 담기\n\n\nclass Blockchain:\n def __init__(self):\n self.current_transactions = []\n self.chain = []\n self.nodes = set()\n\n \n self.new_block(previous_hash='1', proof=100)\n\n def register_node(self, address):\n \"\"\"\n Add a new node to the list of nodes\n\n :param address: Address of node. Eg. 'http://192.168.0.5:5000'\n \"\"\"\n\n parsed_url = urlparse(address)\n \n if parsed_url.netloc:\n self.nodes.add(parsed_url.netloc)\n elif parsed_url.path:\n \n self.nodes.add(parsed_url.path)\n \n else:\n raise ValueError('Invalid URL')\n\n\n def valid_chain(self, chain):\n \n last_block = chain[0]\n \n current_index = 1\n \n while current_index < len(chain):\n block = chain[current_index]\n print(f'{last_block}')\n print(f'{block}')\n print(\"\\n-----------\\n\")\n \n last_block_hash = self.hash(last_block)\n if block['previous_hash'] != last_block_hash:\n return False\n\n \n if not self.valid_proof(last_block['proof'], block['proof'], last_block_hash):\n return False\n\n last_block = block\n current_index += 1\n\n return True\n\n def resolve_conflicts(self):\n \n \n neighbours = self.nodes\n \n new_chain = None\n\n \n max_length = len(self.chain)\n\n \n for node in neighbours:\n response = requests.get(f'http://{node}/chain')\n \n if response.status_code == 200:\n length = response.json()['length']\n chain = response.json()['chain']\n\n \n if length > max_length and self.valid_chain(chain):\n max_length = length\n \n new_chain = chain\n\n \n if new_chain:\n self.chain = new_chain\n return True\n \n return False\n\n def new_block(self, proof, previous_hash):\n \n \n block = {\n 'index': len(self.chain) + 1,\n 'timestamp': time(),\n 'transactions': self.current_transactions,\n 'proof': proof,\n 'previous_hash': previous_hash or self.hash(self.chain[-1]),\n }\n\n \n self.current_transactions = []\n \n self.chain.append(block)\n return block\n \n def new_transaction(self, sender, recipient, amount):\n \n \n self.current_transactions.append({\n 'sender': sender,\n 'recipient': recipient,\n 'amount': amount,\n })\n \n return self.last_block['index'] + 1\n\n @property\n \n def last_block(self):\n return self.chain[-1]\n \n @staticmethod\n def hash(block):\n \n \n block_string = json.dumps(block, sort_keys=True).encode()\n return hashlib.sha256(block_string).hexdigest()\n\n def proof_of_work(self, last_block):\n \n # 위에서 설정한 last_block의 proof 값은 last_proof으로 설정\n last_proof = last_block['proof']\n # 마지막 블록을 해시한 것이 마지막 해시값\n last_hash = self.hash(last_block)\n # valid proof가 옳게될 때까지 proof 값을 더한다. \n proof = 0\n while self.valid_proof(last_proof, proof, last_hash) is False:\n proof += 1\n\n return proof\n # 위에서 말한 valid proof\n @staticmethod\n def valid_proof(last_proof, proof, last_hash):\n \n guess = f'{last_proof}{proof}{last_hash}'.encode()\n guess_hash = hashlib.sha256(guess).hexdigest()\n # 첫 4개가 0이 되어야만 통과\n return guess_hash[:4] == \"0000\"\n\napp = Flask(__name__)\n\n\nnode_identifier = str(uuid4()).replace('-', '')\n\n\nblockchain = Blockchain()\n\n# 처음 index 시작 ----------------------------------------\n@app.route('/')\ndef index():\n return render_template('index.html')\n# 상단 메뉴바 href ----------------------------------------\n@app.route('/logo_index')\ndef logo_index():\n return render_template('index.html')\n\n@app.route('/teamplay')\ndef teamplay():\n return render_template('teamplay.html')\n\n@app.route('/outsourcing')\ndef outsourcing():\n return render_template('outsourcing.html')\n\n@app.route('/mypage')\ndef mypage():\n return render_template('/mypage.html')\n\n@app.route('/loginpage')\ndef loginpage():\n return render_template('login.html')\n\n@app.route('/login' , methods=['POST'])\ndef login():\n if request.method == 'POST':\n login_info = request.form\n email = login_info['email']\n password = login_info['password']\n print(email + password)\n sql = \"SELECT * FROM Userinfo WHERE email = %s\"\n rows_count = cursor.execute(sql , email)\n if rows_count > 0:\n user_info = cursor.fetchone() # 일치하는 정보 객체에 담기\n name = user_info[3] \n mile = user_info[7] \n is_pw_correct = bcrypt.checkpw(password.encode('UTF-8') , user_info[2].encode('UTF-8')) # 패스워드 맞는지 확인\n if is_pw_correct: # 일치하게되면\n # email 이라는 세션을 저장\n session['name'] = name\n session['email'] = email\n session['mile'] = mile\n return redirect('/mypage')\n else: # 비밀번호가 일치하지 않는다면\n return redirect('/loginpage')\n else:\n print('User does not exist')\n return redirect('/loginpage')\n\n\n@app.route('/logout')\ndef logout():\n session.clear()\n return render_template('index.html')\n\n@app.route('/registerpage')\ndef regit():\n return render_template('/register.html')\n\n@app.route('/register' , methods=['POST']) # 회원가입부분\ndef register():\n if(request.method == 'POST'):\n register_info = request.form\n email = register_info['email']\n hased_password = bcrypt.hashpw(register_info['password'].encode('utf-8') , bcrypt.gensalt())\n name = register_info['name']\n department = register_info['department']\n sno = register_info['sno']\n sex = register_info['sex']\n\n sql = \"\"\"\n INSERT INTO Userinfo (email, hashed_password, name, sex, department, student_number) VALUES (%s , %s , %s , %s, %s, %s);\n \"\"\"\n # 아이디 겹치면 try 구문 사용해서 오류 반환해주기 ... 구현해야함\n # cursor.execute(sql , (username , hased_password, email , department)) # sql 실행\n print(register_info)\n cursor.execute(sql , (email , hased_password , name , sex, department, sno))\n db.commit() #데이터 삽입 , 삭제 등의 구문에선 commit 해주어야함\n db.close() # 연결 해제 return redirect(request.url)\n return render_template('/login.html')\n\n\n@app.route('/find')\ndef find():\n return render_template('/find.html')\n\n#---------------------------------------------------------\n@app.route('/goboard1')\ndef goboard1():\n return render_template('/board.html')\n\n@app.route('/mine', methods=['GET'])\ndef mine():\n \n last_block = blockchain.last_block\n proof = blockchain.proof_of_work(last_block)\n\n \n \n blockchain.new_transaction(\n sender=\"0\",\n recipient=node_identifier,\n amount=1,\n )\n\n \n previous_hash = blockchain.hash(last_block)\n block = blockchain.new_block(proof, previous_hash)\n \n response = {\n 'message': \"New Block Forged\",\n 'index': block['index'],\n 'transactions': block['transactions'],\n 'proof': block['proof'],\n 'previous_hash': block['previous_hash'],\n }\n return jsonify(response), 200\n\n\n@app.route('/transactions/new')\ndef new_transaction():\n values = {\n 'sender' : '안재현' , \n 'recipient' : '강홍구' , \n 'amount' : 20\n }\n print('dsafasdfasdfasdfasdf')\n cursor.execute(\"update userinfo set milegea = 180 where id = 3\")\n cursor.execute(\"update userinfo set milegea = 620 where id = 5\")\n print('asdfasdfsdfsdfasdfasdfendendendend')\n required = ['sender', 'recipient', 'amount']\n if not all(k in values for k in required):\n return 'Missing values', 400\n\n #index = blockchain.new_transaction(values['sender'], values['recipient'], values['amount'])\n #response = {'message': f'Transaction will be added to Block {index}'}\n #return jsonify(response), 201\n return redirect('/mine')\n \n@app.route('/chain', methods=['GET'])\ndef full_chain():\n response = {\n 'chain': blockchain.chain,\n 'length': len(blockchain.chain),\n } \n return jsonify(response), 200\n\n\n@app.route('/nodes/register', methods=['POST'])\ndef register_nodes():\n values = request.get_json()\n\n nodes = values.get('nodes')\n if nodes is None:\n return \"Error: Please supply a valid list of nodes\", 400\n\n for node in nodes:\n blockchain.register_node(node)\n\n response = {\n 'message': 'New nodes have been added',\n 'total_nodes': list(blockchain.nodes),\n }\n return jsonify(response), 201\n\n\n@app.route('/nodes/resolve', methods=['GET'])\ndef consensus():\n replaced = blockchain.resolve_conflicts()\n\n if replaced:\n response = {\n 'message': 'Our chain was replaced',\n 'new_chain': blockchain.chain\n }\n else:\n response = {\n 'message': 'Our chain is authoritative',\n 'chain': blockchain.chain\n }\n\n return jsonify(response), 200\n\nif __name__ == '__main__':\n from argparse import ArgumentParser\n\n app.secret_key = b'1234wqerasdfzxcv'\n \n parser = ArgumentParser()\n parser.add_argument('-p', '--port', default=5000, type=int, help='port to listen on')\n args = parser.parse_args()\n port = args.port\n\n app.run(host='127.0.0.1', port=port)\n#---------------------------------------------------------\n\n \n","repo_name":"hanjo8813/Hackathon_2020","sub_path":"app.py","file_name":"app.py","file_ext":"py","file_size_in_byte":10824,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"3"} +{"seq_id":"23833825755","text":"from contextlib import contextmanager\nfrom urllib.parse import urljoin, urlparse\n\ntry:\n from bokeh_django.consumers import AutoloadJsConsumer, DocConsumer\nexcept Exception:\n from bokeh.server.django.consumers import AutoloadJsConsumer, DocConsumer\n\nfrom ..util import edit_readonly\nfrom .resources import Resources\nfrom .server import autoload_js_script, server_html_page_for_session\nfrom .state import state\n\n\nasync def doc_handle(self, body):\n session = await self._get_session()\n resources = Resources.from_bokeh(self.resources())\n page = server_html_page_for_session(\n session, resources=resources, title=session.document.title,\n template=session.document.template,\n template_variables=session.document.template_variables\n )\n await self.send_response(200, page.encode(), headers=[(b\"Content-Type\", b\"text/html\")])\n\n\n@contextmanager\ndef _session_prefix(consumer):\n prefix = consumer.scope.get('root_path', '').replace(consumer.application_context._url, '')\n if not prefix.endswith('/'):\n prefix += '/'\n base_url = urljoin('/', prefix)\n rel_path = '/'.join(['..'] * consumer.application_context._url.strip('/').count('/'))\n old_url, old_rel = state.base_url, state.rel_path\n\n # Handle autoload.js absolute paths\n abs_url = consumer.get_argument('bokeh-absolute-url', default=None)\n if abs_url is not None:\n app_path = consumer.get_argument('bokeh-app-path', default='')\n rel_path = abs_url.replace(app_path, '')\n\n with edit_readonly(state):\n state.base_url = base_url\n state.rel_path = rel_path\n try:\n yield\n finally:\n with edit_readonly(state):\n state.base_url = old_url\n state.rel_path = old_rel\n\n\nasync def autoload_handle(self, body):\n with _session_prefix(self):\n session = await self._get_session()\n\n element_id = self.get_argument(\"bokeh-autoload-element\", default=None)\n if not element_id:\n raise RuntimeError(\"No bokeh-autoload-element query parameter\")\n\n app_path = self.get_argument(\"bokeh-app-path\", default=\"/\")\n absolute_url = self.get_argument(\"bokeh-absolute-url\", default=None)\n\n if absolute_url:\n server_url = '{uri.scheme}://{uri.netloc}/'.format(uri=urlparse(absolute_url))\n else:\n server_url = None\n\n absolute = server_url not in absolute_url\n resources = self.resources(server_url)\n js = autoload_js_script(\n session.document, resources, session.token, element_id, app_path, absolute_url, absolute=absolute\n )\n\n headers = [\n (b\"Access-Control-Allow-Headers\", b\"*\"),\n (b\"Access-Control-Allow-Methods\", b\"PUT, GET, OPTIONS\"),\n (b\"Access-Control-Allow-Origin\", b\"*\"),\n (b\"Content-Type\", b\"application/javascript\")\n ]\n await self.send_response(200, js.encode(), headers=headers)\n\n\nDocConsumer.handle = doc_handle\nAutoloadJsConsumer.handle = autoload_handle\n","repo_name":"holoviz/panel","sub_path":"panel/io/django.py","file_name":"django.py","file_ext":"py","file_size_in_byte":2984,"program_lang":"python","lang":"en","doc_type":"code","stars":3266,"dataset":"github-code","pt":"3"} +{"seq_id":"40738269865","text":"import re\nimport requests\nfrom bs4 import BeautifulSoup\nimport traceback\n\n\ndef getHTMLtext(url, code='utf-8'):\n try:\n html = requests.get(url)\n html.raise_for_status()\n html.encoding = code\n #html.encoding = html.apparent_encoding\n return html.text.encode('gbk', 'ignore')\n except:\n return \"\"\n\n\ndef getStockList(nlst, stockURL):\n html = getHTMLtext(stockURL) #'GB2312'\n soup = BeautifulSoup(html, 'html.parser')\n a = soup.find_all('a')\n for item in a:\n try:\n href = item.attrs['href']\n nlst.append(re.findall(r\"[s][hz]\\d{6}\", href)[0])\n except:\n continue\n #print(nlst)\n\ndef getStockInfo(lst, stockURL, fpath):\n count = 0\n testlst = [lst[0]]\n for stock in testlst:\n url = stockURL + stock + \".html\"\n html = getHTMLtext(url)\n #print(url)\n #print(html)\n try:\n if html == \"\":\n continue\n infoDict = {}\n soup = BeautifulSoup(html, 'html.parser')\n #print(soup.prettify(encoding='utf-8'))\n stockInfo = soup.find('div', attrs={'class':'stock-bets'})\n\n name = stockInfo.find_all(attrs={'class':'bets-name'})[0]\n print(name)\n infoDict.update({'股票名称': name.text.split()[0]})\n\n keyList = stockInfo.find_all('dt')\n valueList = stockInfo.find_all('dd')\n for i in range(len(keyList)):\n key = keyList[i].text\n val = valueList[i].text\n infoDict[key] = val\n print(infoDict)\n\n with open(fpath, 'w+', encoding='utf-8') as f:\n f.write(str(infoDict) + '\\n')\n count +=1\n #print('\\r当前速度{:.2f}%'.format(count*100/len(lst)),end='')'''\n except:\n count +=1\n '''\n print('\\r当前速度{:.2f}%'.format(count*100/len(lst)),end='')\n traceback.print_exc()'''\n\ndef main():\n stock_list_url = 'http://quote.eastmoney.com/stocklist.html'\n stock_info_url = 'https://gupiao.baidu.com/stock/'\n output_file = 'BaiduStockInfo.txt'\n slist =[]\n getStockList(slist, stock_list_url)\n getStockInfo(slist, stock_info_url, output_file)\n\nmain()\n","repo_name":"SevenXue/Spiders-travel","sub_path":"re/stock.py","file_name":"stock.py","file_ext":"py","file_size_in_byte":2281,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"18750971224","text":"from taskcoachlib import operating_system\nfrom taskcoachlib.thirdparty import customtreectrl as customtree, hypertreelist\nfrom taskcoachlib.widgets import itemctrl, draganddrop\nimport wx\n\n\n# pylint: disable=E1101,E1103\n\nclass HyperTreeList(draganddrop.TreeCtrlDragAndDropMixin, \n hypertreelist.HyperTreeList):\n # pylint: disable=W0223\n\n def __init__(self, *args, **kwargs):\n super(HyperTreeList, self).__init__(*args, **kwargs)\n if operating_system.isGTK():\n self.Bind(wx.EVT_TREE_ITEM_COLLAPSED, self.__on_item_collapsed)\n\n def __on_item_collapsed(self, event):\n event.Skip()\n # On Ubuntu, when the user has scrolled to the bottom of the tree\n # and collapses an item, the tree is not redrawn correctly. Refreshing\n # solves this. See http://trac.wxwidgets.org/ticket/11704\n wx.CallAfter(self.MainWindow.Refresh) \n\n def GetSelections(self): # pylint: disable=C0103\n ''' If the root item is hidden, it should never be selected. \n Unfortunately, CustomTreeCtrl and HyperTreeList allow it to be \n selected. Override GetSelections to fix that. '''\n selections = super(HyperTreeList, self).GetSelections()\n if self.HasFlag(wx.TR_HIDE_ROOT):\n root_item = self.GetRootItem()\n if root_item and root_item in selections:\n selections.remove(root_item)\n return selections\n\n def GetMainWindow(self, *args, **kwargs): # pylint: disable=C0103\n ''' Have a local GetMainWindow so we can create a MainWindow \n property. '''\n return super(HyperTreeList, self).GetMainWindow(*args, **kwargs)\n \n MainWindow = property(fget=GetMainWindow)\n \n def HitTest(self, point): # pylint: disable=W0221, C0103\n ''' Always return a three-tuple (item, flags, column). '''\n if type(point) == type(()):\n point = wx.Point(point[0], point[1])\n hit_test_result = super(HyperTreeList, self).HitTest(point)\n if len(hit_test_result) == 2:\n hit_test_result += (0,)\n if hit_test_result[0] is None:\n hit_test_result = (wx.TreeItemId(),) + hit_test_result[1:]\n return hit_test_result\n \n def isClickablePartOfNodeClicked(self, event):\n ''' Return whether the user double clicked some part of the node that\n can also receive regular mouse clicks. '''\n return self.__is_collapse_expand_button_clicked(event)\n \n def __is_collapse_expand_button_clicked(self, event):\n flags = self.HitTest(event.GetPosition())[1]\n return flags & wx.TREE_HITTEST_ONITEMBUTTON\n\n def select(self, selection):\n for item in self.GetItemChildren(recursively=True):\n self.SelectItem(item, self.GetItemPyData(item) in selection)\n \n def clear_selection(self):\n self.UnselectAll()\n self.selectCommand()\n\n def select_all(self):\n if self.GetItemCount() > 0:\n self.SelectAll()\n self.selectCommand()\n \n def isAnyItemCollapsable(self):\n for item in self.GetItemChildren():\n if self.__is_item_collapsable(item): \n return True\n return False\n \n def isAnyItemExpandable(self):\n for item in self.GetItemChildren():\n if self.__is_item_expandable(item): \n return True\n return False\n \n def __is_item_expandable(self, item):\n return self.ItemHasChildren(item) and not self.IsExpanded(item)\n \n def __is_item_collapsable(self, item):\n return self.ItemHasChildren(item) and self.IsExpanded(item)\n \n def IsLabelBeingEdited(self):\n return bool(self.GetLabelTextCtrl())\n \n def StopEditing(self):\n if self.IsLabelBeingEdited():\n self.GetLabelTextCtrl().StopEditing()\n \n def GetLabelTextCtrl(self):\n return self.GetMainWindow()._editCtrl # pylint: disable=W0212\n \n def GetItemCount(self):\n root_item = self.GetRootItem()\n return self.GetChildrenCount(root_item, recursively=True) \\\n if root_item else 0\n \n\nclass TreeListCtrl(itemctrl.CtrlWithItemsMixin, itemctrl.CtrlWithColumnsMixin, \n itemctrl.CtrlWithToolTipMixin, HyperTreeList):\n # TreeListCtrl uses ALIGN_LEFT, ..., ListCtrl uses LIST_FORMAT_LEFT, ... for\n # specifying alignment of columns. This dictionary allows us to map from the\n # ListCtrl constants to the TreeListCtrl constants:\n alignmentMap = {wx.LIST_FORMAT_LEFT: wx.ALIGN_LEFT, \n wx.LIST_FORMAT_CENTRE: wx.ALIGN_CENTRE,\n wx.LIST_FORMAT_CENTER: wx.ALIGN_CENTER,\n wx.LIST_FORMAT_RIGHT: wx.ALIGN_RIGHT}\n ct_type = 0\n \n def __init__(self, parent, columns, selectCommand, editCommand, \n dragAndDropCommand, itemPopupMenu=None, columnPopupMenu=None, \n *args, **kwargs): \n self.__adapter = parent\n self.__selection = []\n self.__user_double_clicked = False\n self.__columns_with_images = []\n self.__default_font = wx.NORMAL_FONT\n kwargs.setdefault('resizeableColumn', 0)\n super(TreeListCtrl, self).__init__(parent, style=self.__get_style(), \n agwStyle=self.__get_agw_style(), columns=columns, \n itemPopupMenu=itemPopupMenu,\n columnPopupMenu=columnPopupMenu, *args, **kwargs)\n self.bindEventHandlers(selectCommand, editCommand, dragAndDropCommand)\n\n def bindEventHandlers(self, selectCommand, editCommand, dragAndDropCommand):\n # pylint: disable=W0201\n self.selectCommand = selectCommand\n self.editCommand = editCommand\n self.dragAndDropCommand = dragAndDropCommand\n self.Bind(wx.EVT_TREE_SEL_CHANGED, self.onSelect)\n self.Bind(wx.EVT_TREE_KEY_DOWN, self.onKeyDown)\n self.Bind(wx.EVT_TREE_ITEM_ACTIVATED, self.onItemActivated)\n # We deal with double clicks ourselves, to prevent the default behaviour\n # of collapsing or expanding nodes on double click. \n self.GetMainWindow().Bind(wx.EVT_LEFT_DCLICK, self.onDoubleClick)\n self.Bind(wx.EVT_TREE_BEGIN_LABEL_EDIT, self.onBeginEdit)\n self.Bind(wx.EVT_TREE_END_LABEL_EDIT, self.onEndEdit)\n self.Bind(wx.EVT_TREE_ITEM_EXPANDING, self.onItemExpanding)\n self.Bind(wx.EVT_SET_FOCUS, self.onSetFocus)\n \n def onSetFocus(self, event): # pylint: disable=W0613\n # Send a child focus event to let the AuiManager know we received focus\n # so it will activate our pane\n wx.PostEvent(self._main_win, wx.ChildFocusEvent(self._main_win))\n self.SetFocus()\n\n def getItemTooltipData(self, item, column):\n return self.__adapter.getItemTooltipData(item, column)\n \n def getItemCTType(self, item): # pylint: disable=W0613\n return self.ct_type\n \n def curselection(self):\n return [self.GetItemPyData(item) for item in self.GetSelections()]\n \n def RefreshAllItems(self, count=0): # pylint: disable=W0613\n self.Freeze()\n self.StopEditing()\n self.__selection = self.curselection()\n self.DeleteAllItems()\n self.__columns_with_images = [index for index in range(self.GetColumnCount()) if self.__adapter.hasColumnImages(index)]\n root_item = self.GetRootItem()\n if not root_item:\n root_item = self.AddRoot('Hidden root')\n self._addObjectRecursively(root_item)\n selections = self.GetSelections()\n if selections:\n self.GetMainWindow()._current = self.GetMainWindow()._key_current = selections[0]\n self.ScrollTo(selections[0])\n self.Thaw()\n \n def RefreshItems(self, *objects):\n self.__selection = self.curselection()\n self._refreshTargetObjects(self.GetRootItem(), *objects)\n \n def _refreshTargetObjects(self, parent_item, *target_objects):\n child_item, cookie = self.GetFirstChild(parent_item)\n while child_item:\n item_object = self.GetItemPyData(child_item) \n if item_object in target_objects:\n self._refreshObjectCompletely(child_item, item_object)\n self._refreshTargetObjects(child_item, *target_objects)\n child_item, cookie = self.GetNextChild(parent_item, cookie)\n \n def _refreshObjectCompletely(self, item, *args):\n self.__refresh_aspects(('ItemType', 'Columns', 'Font', 'Colors',\n 'Selection'), item, check=True, *args)\n self.GetMainWindow().RefreshLine(item)\n \n def _addObjectRecursively(self, parent_item, parent_object=None):\n for child_object in self.__adapter.children(parent_object):\n child_item = self.AppendItem(parent_item, '', \n self.getItemCTType(child_object), \n data=child_object)\n self._refreshObjectMinimally(child_item, child_object)\n expanded = self.__adapter.getItemExpanded(child_object)\n if expanded:\n self._addObjectRecursively(child_item, child_object)\n # Call Expand on the item instead of on the tree\n # (self.Expand(childItem)) to prevent lots of events\n # (EVT_TREE_ITEM_EXPANDING/EXPANDED) being sent\n child_item.Expand()\n else:\n self.SetItemHasChildren(child_item,\n self.__adapter.children(child_object))\n\n def _refreshObjectMinimally(self, *args, **kwargs):\n self.__refresh_aspects(('Columns', 'Colors', 'Font', 'Selection'), \n *args, **kwargs)\n\n def __refresh_aspects(self, aspects, *args, **kwargs):\n for aspect in aspects:\n refresh_aspect = getattr(self, '_refresh%s' % aspect)\n refresh_aspect(*args, **kwargs)\n \n def _refreshItemType(self, item, domain_object, check=False):\n ct_type = self.getItemCTType(domain_object)\n if not check or (check and ct_type != self.GetItemType(item)):\n self.SetItemType(item, ct_type)\n \n def _refreshColumns(self, item, domain_object, check=False):\n for column_index in range(self.GetColumnCount()):\n self._refreshColumn(item, domain_object, column_index, check=check)\n \n def _refreshColumn(self, item, domain_object, column_index, check=False):\n aspects = ('Text', 'Image') if column_index in self.__columns_with_images else ('Text',)\n self.__refresh_aspects(aspects, item, domain_object, column_index, \n check=check)\n \n def _refreshText(self, item, domain_object, column_index, check=False):\n text = self.__adapter.getItemText(domain_object, column_index)\n if text.count('\\n') > 3:\n text = '\\n'.join(text.split('\\n')[:4]) + u' ...'\n if not check or (check and text != item.GetText(column_index)):\n item.SetText(column_index, text)\n \n def _refreshImage(self, item, domain_object, column_index, check=False):\n images = self.__adapter.getItemImages(domain_object, column_index)\n for which, image in images.items():\n image = image if image >= 0 else -1\n if not check or (check and image != item.GetImage(which, \n column_index)):\n item.SetImage(column_index, image, which)\n\n def _refreshColors(self, item, domain_object, check=False):\n bg_color = domain_object.backgroundColor(recursive=True) or wx.NullColour\n if not check or (check and bg_color != self.GetItemBackgroundColour(item)):\n self.SetItemBackgroundColour(item, bg_color)\n fg_color = domain_object.foregroundColor(recursive=True) or wx.NullColour\n if not check or (check and fg_color != self.GetItemTextColour(item)):\n self.SetItemTextColour(item, fg_color)\n \n def _refreshFont(self, item, domain_object, check=False):\n font = domain_object.font(recursive=True) or self.__default_font\n if not check or (check and font != self.GetItemFont(item)):\n self.SetItemFont(item, font)\n \n def _refreshSelection(self, item, domain_object, check=False):\n select = domain_object in self.__selection\n if not check or (check and select != item.IsSelected()):\n item.SetHilight(select)\n\n # Event handlers\n \n def onSelect(self, event):\n # Use CallAfter to prevent handling the select while items are \n # being deleted:\n wx.CallAfter(self.selectCommand) \n event.Skip()\n\n def onKeyDown(self, event):\n if event.GetKeyCode() == wx.WXK_RETURN:\n self.editCommand(event)\n elif event.GetKeyCode() == wx.WXK_F2 and self.GetSelections():\n self.EditLabel(self.GetSelections()[0], column=0)\n else:\n event.Skip()\n \n def OnDrop(self, drop_item, drag_items, part):\n drop_item = None if drop_item == self.GetRootItem() else \\\n self.GetItemPyData(drop_item)\n drag_items = list(self.GetItemPyData(drag_item) for drag_item in drag_items)\n wx.CallAfter(self.dragAndDropCommand, drop_item, drag_items, part)\n \n def onItemExpanding(self, event):\n event.Skip()\n item = event.GetItem()\n if self.GetChildrenCount(item, recursively=False) == 0:\n domain_object = self.GetItemPyData(item)\n self._addObjectRecursively(item, domain_object)\n \n def onDoubleClick(self, event):\n self.__user_double_clicked = True\n if self.isClickablePartOfNodeClicked(event):\n event.Skip(False)\n else:\n self.onItemActivated(event)\n \n def onItemActivated(self, event):\n ''' Attach the column clicked on to the event so we can use it \n elsewhere. '''\n column_index = self.__column_under_mouse()\n if column_index >= 0:\n event.columnName = self._getColumn(column_index).name()\n self.editCommand(event)\n event.Skip(False)\n \n def __column_under_mouse(self):\n mouse_position = self.GetMainWindow().ScreenToClient(wx.GetMousePosition())\n item, _, column = self.HitTest(mouse_position)\n if item:\n # Only get the column name if the hittest returned an item,\n # otherwise the item was activated from the menu or by double \n # clicking on a portion of the tree view not containing an item.\n return max(0, column) # FIXME: Why can the column be -1?\n else:\n return -1\n \n # Inline editing\n \n def onBeginEdit(self, event):\n if self.__user_double_clicked:\n event.Veto()\n self.__user_double_clicked = False\n elif self.IsLabelBeingEdited():\n # Don't start editing another label when the user is still editing\n # a label. This prevents left-over text controls in the tree.\n event.Veto()\n else:\n event.Skip()\n \n def onEndEdit(self, event):\n if event._editCancelled: # pylint: disable=W0212\n event.Skip()\n return\n event.Veto() # Let us update the tree\n domain_object = self.GetItemPyData(event.GetItem())\n new_value = event.GetLabel()\n column = self._getColumn(event.GetInt())\n column.onEndEdit(domain_object, new_value)\n \n def CreateEditCtrl(self, item, column_index):\n column = self._getColumn(column_index)\n domain_object = self.GetItemPyData(item)\n return column.editControl(self.GetMainWindow(), item, column_index, \n domain_object)\n \n # Override CtrlWithColumnsMixin with TreeListCtrl specific behaviour:\n \n def _setColumns(self, *args, **kwargs):\n super(TreeListCtrl, self)._setColumns(*args, **kwargs)\n self.SetMainColumn(0)\n for column_index in range(self.GetColumnCount()):\n self.SetColumnEditable(column_index, \n self._getColumn(column_index).isEditable())\n \n # Extend TreeMixin with TreeListCtrl specific behaviour:\n\n @staticmethod\n def __get_style():\n return wx.WANTS_CHARS \n \n @staticmethod \n def __get_agw_style():\n agw_style = wx.TR_DEFAULT_STYLE | wx.TR_HIDE_ROOT | wx.TR_MULTIPLE \\\n | wx.TR_EDIT_LABELS | wx.TR_HAS_BUTTONS | wx.TR_FULL_ROW_HIGHLIGHT \\\n | customtree.TR_HAS_VARIABLE_ROW_HEIGHT\n if operating_system.isMac():\n agw_style |= wx.TR_NO_LINES\n agw_style &= ~hypertreelist.TR_NO_HEADER\n return agw_style\n\n # pylint: disable=W0221\n \n def DeleteColumn(self, column_index):\n self.RemoveColumn(column_index)\n \n def InsertColumn(self, column_index, column_header, *args, **kwargs):\n alignment = self.alignmentMap[kwargs.pop('format', wx.LIST_FORMAT_LEFT)]\n if column_index == self.GetColumnCount():\n self.AddColumn(column_header, *args, **kwargs)\n else:\n super(TreeListCtrl, self).InsertColumn(column_index, column_header, \n *args, **kwargs)\n self.SetColumnAlignment(column_index, alignment)\n self.SetColumnEditable(column_index, \n self._getColumn(column_index).isEditable())\n\n def showColumn(self, *args, **kwargs):\n ''' Stop editing before we hide or show a column to prevent problems\n redrawing the tree list control contents. '''\n self.StopEditing()\n super(TreeListCtrl, self).showColumn(*args, **kwargs)\n\n\nclass CheckTreeCtrl(TreeListCtrl):\n def __init__(self, parent, columns, selectCommand, checkCommand, \n editCommand, dragAndDropCommand, itemPopupMenu=None, \n *args, **kwargs):\n self.__checking = False\n super(CheckTreeCtrl, self).__init__(parent, columns,\n selectCommand, editCommand, dragAndDropCommand, \n itemPopupMenu, *args, **kwargs)\n self.checkCommand = checkCommand\n self.Bind(customtree.EVT_TREE_ITEM_CHECKED, self.onItemChecked)\n self.GetMainWindow().Bind(wx.EVT_LEFT_DOWN, self.onMouseLeftDown)\n self.getIsItemCheckable = parent.getIsItemCheckable if hasattr(parent, 'getIsItemCheckable') else lambda item: True\n self.getIsItemChecked = parent.getIsItemChecked\n self.getItemParentHasExclusiveChildren = parent.getItemParentHasExclusiveChildren\n \n def getItemCTType(self, domain_object):\n ''' Use radio buttons (ct_type == 2) when the object has \"exclusive\" \n children, meaning that only one child can be checked at a time. Use\n check boxes (ct_type == 1) otherwise. '''\n if self.getIsItemCheckable(domain_object):\n return 2 if self.getItemParentHasExclusiveChildren(domain_object) else 1\n else:\n return 0\n \n def CheckItem(self, item, checked=True):\n if self.GetItemType(item) == 2:\n # Use UnCheckRadioParent because CheckItem always keeps at least\n # one item selected, which we don't want to enforce\n self.UnCheckRadioParent(item, checked)\n else:\n super(CheckTreeCtrl, self).CheckItem(item, checked)\n \n def onMouseLeftDown(self, event):\n ''' By default, the HyperTreeList widget doesn't allow for unchecking\n a radio item. Since we do want to support unchecking a radio \n item, we look for mouse left down and uncheck the item and all of\n its children if the user clicks on an already selected radio \n item. '''\n position = self.GetMainWindow().CalcUnscrolledPosition(event.GetPosition())\n item, flags, dummy_column = self.HitTest(position)\n if item and item.GetType() == 2 and \\\n (flags & customtree.TREE_HITTEST_ONITEMCHECKICON) and \\\n self.IsItemChecked(item):\n self.__uncheck_item_recursively(item)\n else:\n event.Skip()\n \n def __uncheck_item_recursively(self, item, parent_is_expanded=True, \n disable_item=False):\n if item.GetType():\n self.__uncheck_item(item, torefresh=parent_is_expanded)\n if disable_item:\n self.EnableItem(item, False, torefresh=parent_is_expanded)\n parent_is_expanded = item.IsExpanded()\n child, cookie = self.GetFirstChild(item) \n while child:\n self.__uncheck_item_recursively(child, parent_is_expanded, \n disable_item=True)\n child, cookie = self.GetNextChild(item, cookie)\n \n def __uncheck_item(self, item, torefresh):\n self.GetMainWindow().CheckItem2(item, checked=False, \n torefresh=torefresh)\n event = customtree.TreeEvent(customtree.wxEVT_TREE_ITEM_CHECKED, \n self.GetId())\n event.SetItem(item)\n event.SetEventObject(self)\n self.GetEventHandler().ProcessEvent(event)\n \n def _refreshObjectCompletely(self, item, domain_object):\n super(CheckTreeCtrl, self)._refreshObjectCompletely(item, domain_object)\n self._refreshCheckState(item, domain_object)\n \n def _refreshObjectMinimally(self, item, domain_object):\n super(CheckTreeCtrl, self)._refreshObjectMinimally(item, domain_object)\n self._refreshCheckState(item, domain_object)\n \n def _refreshCheckState(self, item, domain_object):\n # Use CheckItem2 so no events get sent:\n self.CheckItem2(item, self.getIsItemChecked(domain_object))\n parent = item.GetParent()\n while parent:\n if self.GetItemType(parent) == 2:\n self.EnableItem(item, self.IsItemChecked(parent))\n break\n parent = parent.GetParent()\n\n def onItemChecked(self, event):\n if self.__checking: \n # Ignore checked events while we're making the tree consistent,\n # only invoke the callback:\n self.checkCommand(event)\n return\n self.__checking = True\n item = event.GetItem()\n # Uncheck mutually exclusive children:\n for child in self.GetItemChildren(item):\n if self.GetItemType(child) == 2:\n self.CheckItem(child, False)\n # Recursively uncheck children of mutually exclusive children:\n for grandchild in self.GetItemChildren(child, recursively=True):\n self.CheckItem(grandchild, False)\n # If this item is mutually exclusive, recursively uncheck siblings \n # and parent:\n parent = item.GetParent()\n if parent and self.GetItemType(item) == 2:\n for child in self.GetItemChildren(parent):\n if child == item:\n continue\n self.CheckItem(child, False)\n for grandchild in self.GetItemChildren(child, recursively=True):\n self.CheckItem(grandchild, False)\n if self.GetItemType(parent) != 2:\n self.CheckItem(parent, False)\n self.__checking = False\n self.checkCommand(event)\n \n def onItemActivated(self, event):\n if self.__is_double_clicked(event):\n # Invoke super.onItemActivated to edit the item\n super(CheckTreeCtrl, self).onItemActivated(event)\n else:\n # Item is activated, let another event handler deal with the event \n event.Skip()\n \n @staticmethod \n def __is_double_clicked(event):\n return hasattr(event, 'LeftDClick') and event.LeftDClick()\n","repo_name":"TaskEvolution/Task-Coach-Evolution","sub_path":"taskcoach/taskcoachlib/widgets/treectrl.py","file_name":"treectrl.py","file_ext":"py","file_size_in_byte":23978,"program_lang":"python","lang":"en","doc_type":"code","stars":8,"dataset":"github-code","pt":"3"} +{"seq_id":"6053175760","text":"\"\"\"\nReprojection Algorithm Node\n\"\"\"\n\nfrom __future__ import division, unicode_literals, print_function, absolute_import\n\nfrom six import string_types\n\nimport numpy as np\nimport xarray as xr\nimport traitlets as tl\n\n# Internal dependencies\nfrom podpac.core.node import Node\nfrom podpac.core.coordinates.coordinates import Coordinates, merge_dims\nfrom podpac.core.interpolation.interpolation import Interpolate\nfrom podpac.core.utils import NodeTrait, cached_property\nfrom podpac import settings\n\n\nclass Reproject(Interpolate):\n \"\"\"\n Create a Algorithm that evalutes a Node with one set of coordinates, and then interpolates it.\n This can be used to bilinearly interpolate an averaged dataset, for example.\n\n Attributes\n ----------\n source : Node\n The source node. This node will use it's own, specified interpolation scheme\n interpolation : str\n Type of interpolation method to use for the interpolation\n coordinates : Coordinates, Node, str, dict\n Coordinates used to evaluate the source. These can be specified as a dictionary, json-formatted string,\n PODPAC Coordinates, or a PODPAC Node, where the node MUST implement the 'coordinates' attribute.\n reproject_dims : list\n Dimensions to reproject. The source will be evaluated with the reprojection coordinates in these dims\n and the requested coordinates for any other dims.\n \"\"\"\n\n coordinates = tl.Union(\n [NodeTrait(), tl.Dict(), tl.Unicode(), tl.Instance(Coordinates)],\n help=\"\"\"Coordinates used to evaluate the source. These can be specified as a dictionary,\n json-formatted string, PODPAC Coordinates, or a PODPAC Node, where the node MUST implement\n the 'coordinates' attribute\"\"\",\n ).tag(attr=True)\n\n reproject_dims = tl.List(trait=tl.Unicode(), allow_none=True, default_value=None).tag(attr=True)\n\n @tl.validate(\"coordinates\")\n def _validate_coordinates(self, d):\n val = d[\"value\"]\n if isinstance(val, Node):\n if not hasattr(val, \"coordinates\"):\n raise ValueError(\n \"When specifying the coordinates as a PODPAC Node, this Node must have a 'coordinates' attribute\"\n )\n elif isinstance(val, dict):\n Coordinates.from_definition(self.coordinates)\n elif isinstance(val, string_types):\n Coordinates.from_json(self.coordinates)\n return val\n\n @cached_property\n def reprojection_coordinates(self):\n # get coordinates\n if isinstance(self.coordinates, Coordinates):\n coordinates = self.coordinates\n elif isinstance(self.coordinates, Node):\n coordinates = self.coordinates.coordinates\n elif isinstance(self.coordinates, dict):\n coordinates = Coordinates.from_definition(self.coordinates)\n elif isinstance(self.coordinates, string_types):\n coordinates = Coordinates.from_json(self.coordinates)\n\n # drop non-reprojection dims\n if self.reproject_dims is not None:\n coordinates = coordinates.drop([dim for dim in coordinates if dim not in self.reproject_dims])\n\n return coordinates\n\n def _source_eval(self, coordinates, selector, output=None):\n coords = self.reprojection_coordinates.intersect(coordinates, outer=True)\n extra_eval_coords = coordinates.drop(self.reproject_dims or self.reprojection_coordinates.dims)\n if coords.crs != coordinates.crs:\n # Better to evaluate in reproject coordinate crs than eval crs for next step of interpolation\n extra_eval_coords = extra_eval_coords.transform(coords.crs)\n coords = merge_dims([coords, extra_eval_coords])\n if settings[\"MULTITHREADING\"]:\n # we have to do a new node here to avoid clashing with the source node.\n # What happens is that the non-projected source gets evaluated\n # at the projected source coordinates because we have to set\n # self._requested_coordinates for the datasource to avoid floating point\n # lat/lon disagreement issues\n return Node.from_definition(self.source.definition).eval(coords, output=output, _selector=selector)\n else:\n return self.source.eval(coords, output=output, _selector=selector)\n\n @property\n def base_ref(self):\n return \"{}_reprojected\".format(self.source.base_ref)\n","repo_name":"creare-com/podpac","sub_path":"podpac/core/algorithm/reprojection.py","file_name":"reprojection.py","file_ext":"py","file_size_in_byte":4443,"program_lang":"python","lang":"en","doc_type":"code","stars":43,"dataset":"github-code","pt":"3"} +{"seq_id":"29059422357","text":"\"\"\"\nДанный модуль проверяет корректность обработки запросов от IDM\n\"\"\"\n\nimport json\nimport http\n\nfrom django.urls import reverse\nfrom django.conf import settings\nfrom django.test import modify_settings\n\n\nclass TestIDM:\n def test_info(self, client):\n \"\"\"\n Проверяем получение информациии структуре ролей в системе\n \"\"\"\n\n info_uri = reverse('django_idm_api:info')\n response = client.get(info_uri)\n assert response.status_code == http.HTTPStatus.OK, response.content\n\n expected = {\n 'code': 0,\n 'roles': {\n 'slug': 'role',\n 'name': 'роль',\n 'values': {\n 'superuser': 'суперпользователь',\n 'group-1': 'внут. контроль',\n 'group-2': 'представитель сервиса',\n },\n },\n }\n result = response.json()\n assert result == expected\n\n def test_add_role(self, client):\n \"\"\"\n Проверяем корректность обработки присвоения роли\n \"\"\"\n\n add_role_uri = reverse('django_idm_api:add-role')\n\n data = {\n 'login': 'anybody',\n 'role': json.dumps({'role': 'superuser'}),\n }\n\n # Даже если роль уже присвоена, ответ должен быть 200 OK\n for _ in range(2):\n response = client.post(add_role_uri, data)\n assert response.status_code == http.HTTPStatus.OK, response.content\n\n expected = {'code': 0}\n result = response.json()\n assert result == expected\n\n def test_remove_role(self, client):\n \"\"\"\n Проверяем корректность обработки отвязывания роли\n \"\"\"\n\n remove_role_uri = reverse('django_idm_api:remove-role')\n\n data = {\n 'login': 'anybody',\n 'role': json.dumps({'role': 'superuser'}),\n 'path': '/role/superuser',\n }\n\n # Даже если роль уже отвязана, ответ должен быть 200 OK\n for _ in range(2):\n response = client.post(remove_role_uri, data)\n assert response.status_code == http.HTTPStatus.OK, response.content\n\n expected = {'code': 0}\n result = response.json()\n assert result == expected\n\n def test_get_all_roles(self, client):\n \"\"\"\n Проверяем корректность вывода всех пользователей и их ролей\n \"\"\"\n\n add_role_uri = reverse('django_idm_api:add-role')\n get_all_roles_uri = reverse('django_idm_api:get-all-roles')\n\n data = {\n 'login': 'anybody',\n 'role': json.dumps({'role': 'superuser'}),\n }\n\n response = client.post(add_role_uri, data)\n assert response.status_code == http.HTTPStatus.OK, response.content\n\n response = client.get(get_all_roles_uri)\n assert response.status_code == http.HTTPStatus.OK, response.content\n\n expected = {'code': 0, 'users': [{'login': 'anybody', 'roles': [{'role': 'superuser'}]}]}\n result = response.json()\n assert result == expected\n\n def test_tvm(self, client):\n \"\"\"\n Проверяем, что ручки idm/ корректно закрываются TVM-авторизацией при включении\n \"\"\"\n\n with modify_settings(MIDDLEWARE={'append': settings.IDM_API_TVM_MIDDLEWARE}):\n info_uri = reverse('django_idm_api:info')\n response = client.get(info_uri)\n assert response.status_code == http.HTTPStatus.FORBIDDEN, response\n","repo_name":"Alexander-Berg/2022-tests-examples","sub_path":"billing/tests/small/core/test_idm.py","file_name":"test_idm.py","file_ext":"py","file_size_in_byte":3894,"program_lang":"python","lang":"ru","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"19232225582","text":"# -*- coding: utf-8 -*-\nimport readline\nfrom Queue import Empty\n\nclass ZMQCompleter(object):\n \"\"\"Client-side completion machinery.\n\n How it works: self.complete will be called multiple times, with\n state=0,1,2,... When state=0 it should compute ALL the completion matches,\n and then return them for each value of state.\"\"\"\n \n def __init__(self, shell, km):\n self.shell = shell\n self.km = km\n self.matches = []\n \n def complete_request(self,text):\n line = readline.get_line_buffer()\n cursor_pos = readline.get_endidx()\n \n # send completion request to kernel\n # Give the kernel up to 0.5s to respond\n msg_id = self.km.shell_channel.complete(text=text, line=line,\n cursor_pos=cursor_pos)\n \n msg = self.km.shell_channel.get_msg(timeout=0.5)\n if msg['parent_header']['msg_id'] == msg_id:\n return msg[\"content\"][\"matches\"]\n return []\n \n def rlcomplete(self, text, state):\n if state == 0:\n try:\n self.matches = self.complete_request(text)\n except Empty:\n print('WARNING: Kernel timeout on tab completion.')\n \n try:\n return self.matches[state]\n except IndexError:\n return None\n \n def complete(self, text, line, cursor_pos=None):\n return self.rlcomplete(text, 0)\n","repo_name":"miniBloq/v0.83","sub_path":"source/Bin/Minibloq/lang/PPythonWin/v2.7.5.1/App/Lib/site-packages/IPython/frontend/terminal/console/completer.py","file_name":"completer.py","file_ext":"py","file_size_in_byte":1460,"program_lang":"python","lang":"en","doc_type":"code","stars":82,"dataset":"github-code","pt":"3"} +{"seq_id":"19684317746","text":"#!/usr/bin/env python\n\n\nclass PIDcontroller(object):\n\n def __init__(self, kp=0, ki=0, kd=0, limited=False, ub=0, lb=0):\n self.kp = kp\n self.ki = ki\n self.kd = kd\n\n self.correction = 0\n self.ub = ub\n self.lb = lb\n self.limited = limited\n\n self.err_cur = 0\n self.err_prv = 0\n self.err_sum = 0\n self.err_dif = 0\n\n def set_pid(self, kp=0, ki=0, kd=0):\n self.kp = kp\n self.ki = ki\n self.kd = kd\n\n def update_error(self, setpoint=0, measurement=0, dt=1):\n self.err_prv = self.err_cur\n self.err_cur = setpoint - measurement\n self.err_sum += self.err_cur * dt\n self.err_dif = 0 if dt == 0 else (self.err_cur - self.err_prv)/dt\n\n def clamped(self):\n # checks if integrator should be clamped based on past output and current error\n saturated = self.correction == self.ub or self.correction == self.lb\n samesign = ((self.correction < 0) == (self.err_cur < 0))\n\n return (saturated and samesign) and self.limited\n\n def calculate_correction(self):\n p_val = self.kp * self.err_cur\n i_val = 0 if self.clamped() else self.ki * self.err_sum\n d_val = self.kd * self.err_dif\n\n self.correction = p_val + i_val + d_val\n self.correction = max(min(self.correction, self.ub), self.lb) if self.limited else self.correction\n\n def update(self, setpoint=0, measurement=0, dt=1):\n self.update_error(setpoint, measurement, dt)\n self.calculate_correction()\n","repo_name":"WizErnest/vugc1_control","sub_path":"scripts/vugc1_control/pid.py","file_name":"pid.py","file_ext":"py","file_size_in_byte":1546,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"27057134303","text":"import datetime\nimport pandas as pd\nfrom tradeexecutor.utils.summarydataframe import (\n create_summary_table,\n as_dollar,\n as_duration,\n as_percent,\n as_integer,\n as_bars,\n)\n\n\ndef test_create_summary_table_single_column():\n data = {\n \"Annualised return %\": as_percent(0.1),\n \"Lifetime return %\": as_percent(0.3),\n \"Realised PnL\": as_dollar(320),\n \"Trade period\": as_duration(datetime.timedelta(days=5, hours=2, minutes=3)),\n \"Avg trade duration bars\": as_bars(2.9999),\n }\n\n df = create_summary_table(data, \"\", \"Returns\")\n\n assert df.shape == (5, 1)\n\n data = [\"10.00%\", \"30.00%\", \"$320.00\", \"5 days 2 hours\", \"2 bars\"]\n index = [\"Annualised return %\", \"Lifetime return %\", \"Realised PnL\", \"Trade period\", \"Avg trade duration bars\"]\n manual_df = pd.DataFrame(data, index=index, columns=[\"\"])\n manual_df.index.name = \"Returns\"\n assert df.equals(manual_df)\n\n\ndef test_create_summary_table_multiple_columns():\n data = {\n \"Number of positions\": [\n as_integer(3),\n as_integer(5),\n as_integer(8),\n ],\n \"% of total\": [\n as_percent(0.375),\n as_percent(0.625),\n as_percent(1),\n ],\n \"Average PnL %\": [\n as_percent(0.06),\n as_percent(-0.02),\n as_percent(0.03),\n ],\n }\n\n df = create_summary_table(data, [\"Winning\", \"Losing\", \"Total\"], \"Closed Positions\")\n\n assert df.shape == (3, 3)\n\n data = [\n [\"3\", \"5\", \"8\"],\n [\"37.50%\", \"62.50%\", \"100.00%\"],\n [\"6.00%\", \"-2.00%\", \"3.00%\"],\n ]\n index = [\"Number of positions\", \"% of total\", \"Average PnL %\"]\n manual_df = pd.DataFrame(data, index=index, columns=[\"Winning\", \"Losing\", \"Total\"])\n manual_df.index.name = \"Closed Positions\"\n assert df.equals(manual_df)\n","repo_name":"tradingstrategy-ai/trade-executor","sub_path":"tests/units_tests/test_create_summary_table.py","file_name":"test_create_summary_table.py","file_ext":"py","file_size_in_byte":1859,"program_lang":"python","lang":"en","doc_type":"code","stars":66,"dataset":"github-code","pt":"3"} +{"seq_id":"10880240954","text":"\ndef compareTriplets(Achallengerating, Bchallengerating):\n ab = []\n\n alicepoint = 0\n bobpoint = 0\n\n if Achallengerating[0] > Bchallengerating[0]:\n alicepoint = alicepoint+1\n elif Achallengerating[0] Bchallengerating[1]:\n alicepoint = alicepoint+1\n elif Achallengerating[1] < Bchallengerating[1]:\n bobpoint = bobpoint+1\n\n if Achallengerating[2] > Bchallengerating[2]:\n alicepoint = alicepoint+1\n elif Achallengerating[2] < Bchallengerating[2]:\n bobpoint = bobpoint+1\n\n ab.append(alicepoint)\n ab.append(bobpoint)\n\n return ab\n\n\nif __name__ == '__main__':\n\n x = 0\n while x == 0:\n alice = input()\n alicelist = alice.split(\" \")\n for i in range(3):\n if int(alicelist[i]) < 0 or int(alicelist[i]) > 100:\n print(\"invalid values\")\n else:\n a = (int(alicelist[0]), int(alicelist[1]), int(alicelist[2]))\n x = 1\n break\n\n y = 0\n while y == 0:\n bob = input()\n boblist = bob.split(\" \")\n for i in range(3):\n if int(boblist[i]) < 0 or int(boblist[i]) > 100:\n print(\"invalid values\")\n else:\n b = (int(boblist[0]), int(boblist[1]), int(boblist[2]))\n y = 1\n break\n\n print(\"Alice Triplet:\", a)\n print(\"Bob Triplet:\", b)\n\n print(compareTriplets(a, b))\n","repo_name":"ilaydacitak/YZ_Akademi","sub_path":"YZ_Akdemi.py","file_name":"YZ_Akdemi.py","file_ext":"py","file_size_in_byte":1504,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"71335320082","text":"import aioftp\nimport asyncio\nimport csv\nimport os\nfrom ftplib import error_perm\nimport glob\nimport time\n\n\nclass Gutenberg():\n def __init__(self):\n self.request_url = ''\n self.csv_file_path = 'ingest_file/Gutenberg_files.csv'\n self.csv_data = []\n self.cwd = os.getcwd()\n self.ftp_uri = 'aleph.gutenberg.org'\n self.ftp_object = None\n self.download_uris = []\n self.file_download_locattion = 'downloads/'\n\n def load_csv_file(self):\n absolute_path = self.cwd\n file = self.csv_file_path\n with open(f'{absolute_path}/{file}', 'r') as file:\n data = csv.reader(file, delimiter=',')\n next(data, None)\n for row in data:\n self.csv_data.append({\"author\": row[0],\n \"FileNumber\": row[1],\n \"Title\": row[2]})\n\n def iterate_csv_file(self):\n for row in self.csv_data:\n yield row\n\n def ftp_login(self):\n self.ftp_object = aioftp.Client()\n self.ftp_object.connect(self.ftp_uri)\n self.ftp_object.login()\n print('logged into gutenberg ftp mirror')\n\n @staticmethod\n def obtain_directory_location(file_number: str):\n \"\"\"Files are structured into directories by splitting each number, up UNTIL the last number. Then a folder\n named with the file number. So if a file number is 418, it is located at 4/1/418.\n Below 10 is just 0/filenumber.\"\"\"\n file_location = ''\n for char in file_number[:-1]:\n file_location = file_location+char+'/'\n return file_location+file_number\n\n @staticmethod\n def find_text_file(file: object, row: dict) -> object:\n if row[\"FileNumber\"]+'.txt' in file:\n return file\n elif row[\"FileNumber\"]+'-0.txt' in file:\n return file\n elif '.txt' in file:\n return file\n\n @staticmethod\n def iter_lines(open_file: object, write_file: object) -> None:\n lines = open_file.readlines()\n start = False\n end = False\n for line in lines:\n if 'START OF THIS PROJECT' in line:\n start = True\n if 'End of Project' in line:\n end = True\n elif end:\n break\n elif start:\n if 'START OF THIS PROJECT' in line:\n continue\n write_file.write(line + '\\n')\n\n @property\n def iter_files(self):\n for file in glob.glob(self.file_download_locattion+'*.txt'):\n with open(file.replace('.txt','-mod.txt'), 'w', encoding='utf-8') as write_file:\n with open(file, 'r', encoding='ISO-8859-1') as open_file:\n self.iter_lines(open_file, write_file)\n\n\nasync def download_file(gutenberg, file: str, filename: str) -> None:\n async with aioftp.ClientSession(gutenberg.ftp_uri) as client:\n try:\n await client.download(file, 'downloads/'+filename+'.txt', write_into=True)\n except error_perm as e:\n print(f'failed to download {filename} located at {file} with error {e}')\n\n\nasync def run(gutenberg):\n files = []\n rows = gutenberg.iterate_csv_file()\n for row in rows:\n file_location = gutenberg.obtain_directory_location(row[\"FileNumber\"])\n files.append(file_location)\n async with aioftp.ClientSession(gutenberg.ftp_uri) as client:\n tasks = []\n for file_to_download in files:\n for path, info in (await client.list(file_to_download, raw_command='LIST')):\n text_file = gutenberg.find_text_file(str(path), row)\n if text_file:\n print(file_to_download)\n file_name = file_to_download[file_to_download.rfind('/')+1:]\n task = asyncio.ensure_future(download_file(gutenberg, text_file, file_name))\n tasks.append(task)\n results = await asyncio.gather(*tasks)\n return results\n\n\ndef main():\n t0 = time.time()\n ingest = Gutenberg()\n ingest.load_csv_file()\n t3 = time.time()\n loop = asyncio.get_event_loop()\n future = asyncio.ensure_future(run(ingest))\n results = loop.run_until_complete(future)\n t4 = time.time()\n ingest.iter_files\n t1 = time.time()\n total = t1-t0\n downloadtime = t4-t3\n print(f'total time {total}')\n print(f'download time {downloadtime}')\n\n\nif __name__ == '__main__':\n main()\n","repo_name":"danielbeach/pyGutenberg","sub_path":"src/main_async.py","file_name":"main_async.py","file_ext":"py","file_size_in_byte":4479,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"9999362716","text":"from django.urls import path\nfrom .views import (IndexView,BlogList,BlogDetail,\n CommentEditView,NewsLetterView,\n SearchView,ExploreTagView,CommentView,\n CategoriesListView,AboutUsView,\n CategoryDetailView,AuthorProfileView,\n CommentReplyView,ContactView,ContactTemplate)\n\n\nurlpatterns=[\n path('',IndexView.as_view(),name='home_page'),\n path('blogs/all/',BlogList.as_view(),name='blog_list'),\n path('blog/detail//',BlogDetail.as_view(),name='blog_detail'),\n path('blog//comment/',CommentView.as_view(),name='comments'),\n path('blog//comment/edit/',CommentEditView.as_view(),name='comment_edit'),\n path('p//comment/reply/',CommentReplyView.as_view(),name='comment_reply'),\n path('newsleter/',NewsLetterView.as_view(),name='newsletter'),\n path('contact',ContactView.as_view(),name='contact'),\n path('contact/home/',ContactTemplate.as_view(),name='contact_template'),\n path('search/',SearchView.as_view(),name='search'),\n path('explore/tags/',ExploreTagView.as_view(),name='tag'),\n path('categories/all/',CategoriesListView.as_view(),name='categories'),\n path('category//',CategoryDetailView.as_view(),name='category_detail'),\n path('about-us/',AboutUsView.as_view(),name='about'),\n path('profile//',AuthorProfileView.as_view(),name='profile')\n]\n","repo_name":"DeFidelity/heedngrow","sub_path":"blog/urls.py","file_name":"urls.py","file_ext":"py","file_size_in_byte":1450,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"3"} +{"seq_id":"37646738944","text":"from collections import Counter\nfrom itertools import islice\n\nSTART_SYMBOL = \"*\"\nSTOP_SYMBOL = \"STOP\"\n\n\ndef join(str_list):\n return \" \".join(str_list)\n\n\ndef combinations(seq, n=2):\n \"Returns a sliding window (of width n) over data from the iterable\"\n \" s -> (s0,s1,...s[n-1]), (s1,s2,...,sn), ... \"\n it = iter(seq)\n result = tuple(islice(it, n))\n if len(result) == n:\n yield result\n for elem in it:\n result = result[1:] + (elem,)\n yield result\n\n\ndef get_q(t1, t2, t3, lambda_values, q_dic):\n l1, l2, l3 = lambda_values\n if t1 == START_SYMBOL:\n pred1 = 0\n else:\n pred1 = l1 * q_dic.get(join([t1, t2, t3]), 0)\n if t2 == START_SYMBOL:\n pred2 = 0\n else:\n pred2 = l2 * q_dic.get(join([t2, t3]), 0)\n if t3 == STOP_SYMBOL:\n pred3 = 0\n else:\n pred3 = l3 * q_dic.get(t3, 0)\n return pred1 + pred2 + pred3\n\n\ndef get_q_dict(q_mle):\n with open(q_mle, encoding=\"utf8\") as file:\n lines = [line for line in file]\n q_dict = {}\n for line, next_line in zip(lines[::2], lines[1::2]):\n tags, count = line.split('\\t')\n tags = tags[:-1]\n count = count.split(\"\\n\")[0]\n next_tags, next_count = next_line.split('\\t')\n next_count = next_count.split(\"\\n\")[0]\n if float(count) is 0 or float(next_count) is 0: # might be better way for handling division by 0\n q_dict[tags] = 0\n else:\n prob = float(count) / float(next_count)\n q_dict[tags] = prob\n return q_dict\n\n\ndef get_e_dict(e_mle):\n with open(e_mle, encoding=\"utf8\") as file:\n lines = [line for line in file]\n e_dict = {}\n for line, next_line in zip(lines[::2], lines[1::2]):\n word_and_tag, count = line.split('\\t')\n word_and_tag = word_and_tag[:-1]\n count = count.split(\"\\n\")[0]\n next_tags, next_count = next_line.split('\\t')\n next_count = next_count.split(\"\\n\")[0]\n if float(count) is 0 or float(next_count) is 0: # might be better way for handling division by 0\n e_dict[word_and_tag] = 0\n else:\n prob = float(count) / float(next_count)\n e_dict[word_and_tag] = prob\n return e_dict\n\n\ndef get_e(w, t, e_dict):\n return e_dict.get(join([w, t]), 0)\n\n\ndef get_unknown_e(w, t, e_dict):\n unk = classify_unknown(w)\n return e_dict.get(join([unk, t]), 1 / len(e_dict))\n\n\ndef create_possible_tags(tags, f_name):\n tags_dict = Counter(tags)\n tags_list = sorted(tags_dict, key=tags_dict.get, reverse=True)\n with open(f_name, \"w\") as file:\n for tag in tags_list:\n file.write(tag + '\\n')\n\n\ndef get_possible_tags(f_name):\n tags = []\n with open(f_name, \"r\") as file:\n for line in file:\n tags.append(line.split(\"\\n\")[0])\n return tags\n\n\ndef classify_unknown(word):\n suffix_1 = [\"s\"]\n suffix_2 = [\"ly\", \"ed\", \"al\", \"ul\", \"er\", \"es\", \"ty\", \"en\"]\n suffix_3 = [\"ing\", \"ous\", \"age\", \"ies\", \"ive\", \"ery\", \"ers\", \"ity\", \"ist\", \"ent\", \"ian\", \"ism\", \"ary\", \"ory\",\n \"phy\", \"ate\", \"est\"]\n suffix_4 = [\"ness\", \"tial\", \"tion\", \"sion\", \"able\", \"ence\", \"ance\"]\n\n current_str = \"^unk\"\n if word[0].isupper():\n current_str = \"^Unk\"\n\n if word[-4:] in suffix_4:\n current_str += word[-4:]\n elif word[-3:] in suffix_3:\n current_str += word[-3:]\n elif word[-2:] in suffix_2:\n current_str += word[-2:]\n elif word[-1:] in suffix_1:\n current_str += word[-1:]\n elif len(word.split(\"-\")) >= 2:\n subs = word.split(\"-\")\n for sub in subs:\n if is_number(sub):\n current_str += \"-num\"\n else:\n current_str += \"-not_num\"\n elif are_all_numbers(word, \":\") or are_all_numbers(word, \"/\"):\n current_str += \"time\"\n elif are_all_numbers(word, \",\") or are_all_numbers(word, \".\"):\n current_str += \"num\"\n elif \"'\" in word:\n current_str += \"slang\"\n return current_str\n\n\ndef are_all_numbers(str, delim):\n all_num = True\n subs = str.split(delim)\n for sub in subs:\n if not is_number(sub):\n all_num = False\n return all_num\n\n\ndef is_number(str):\n try:\n word = float(str)\n return True\n except ValueError:\n return False\n pass # it was a string, not an float\n\n\n","repo_name":"LioraZ/NLP-Ass1","sub_path":"Ass1/hmm2/HMMutils.py","file_name":"HMMutils.py","file_ext":"py","file_size_in_byte":4353,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"37070430578","text":"\"\"\"\n loops are control structures that allow you\n to execute a block of code multiple times.\n There are two types of loops in Python: for loops and while loops.\n\"\"\"\n\ncount = 1\n\nwhile count <= 5:\n print(count)\n count = count + 1 # count +=1\n\n# # break keyword\n# count = 1\n# while count < 5:\n# print(count)\n# if count == 3:\n# break\n# count = count + 1 # count =+1\n\n#break\ni = 0\n\nwhile i < 10:\n i += 1\n if i == 6:\n continue\n print(i)\n","repo_name":"codingstrade/Python-Full-Course","sub_path":"whileloops.py","file_name":"whileloops.py","file_ext":"py","file_size_in_byte":474,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"24969952465","text":"\"\"\"\npil模块\n遗憾的是原作者早在2009年就停止了维护\n感叹的是，中国无人，这些伟大的开源项目都是国外人发明的。\n看看中国的人，是多么的浮躁，国家也是处于虚强。如果我有能力\n我也想移民美国。毕竟在温水里，怎么可能有善终。\n\"\"\"\nfrom PIL import Image, ImageEnhance, ImageFilter\nfrom PIL.ExifTags import TAGS, GPSTAGS\nfrom io import BytesIO\nimport pytesseract\nfrom PYSTUDY.debuglib import trace_info\n\n\nfrom PYSTUDY.html_parserlib import ReParser\n\ndef get_img_from_bytes(content):\n \"\"\"\n 从二进制数据中返回一张图片对象\n :param content: 图片二进制数据\n :return: Image\n \"\"\"\n return Image.open(BytesIO(content))\n\ndef open_img(filename):\n \"\"\"\n 从文件中打开图片\n 如果文件打开错误，返回 IOError 错误。\n :param filename: 图片文件名\n :return: Image\n \"\"\"\n return Image.open(filename)\n\ndef convert_other_format(filename, format):\n \"\"\"\n 转换为png图片\n :param filename: 图片文件名\n :return:\n \"\"\"\n img = Image.open(filename)\n rp = ReParser()\n c_filename = rp.replace(r'\\..*$', format, filename)\n img.save(c_filename)\n\n\ndef recognition(img):\n \"\"\"\n 识别图片\n :param img: Image\n :return: 字符串\n \"\"\"\n return pytesseract.image_to_string(img)\n\ndef remove_grayscale(image):\n \"\"\"\n 转化为灰度\n :param image:\n :return:\n \"\"\"\n return image.convert('L')\n\ndef binarizing(img,threshold):\n \"\"\"\n 二值化\n :param img:\n :param threshold:\n :return:\n \"\"\"\n pixdata = img.load()\n w, h = img.size\n for y in range(h):\n for x in range(w):\n if pixdata[x, y] < threshold:\n pixdata[x, y] = 0\n else:\n pixdata[x, y] = 255\n return img\n\ndef remove_interference_line(img):\n \"\"\"\n 去除干扰线\n :param img:\n :return:\n \"\"\"\n pixdata = img.load()\n w,h = img.size\n for y in range(1,h-1):\n for x in range(1,w-1):\n count = 0\n if pixdata[x,y-1] > 245:\n count = count + 1\n if pixdata[x,y+1] > 245:\n count = count + 1\n if pixdata[x-1,y] > 245:\n count = count + 1\n if pixdata[x+1,y] > 245:\n count = count + 1\n if count > 2:\n pixdata[x,y] = 255\n return img\n\ndef remove_noise(img):\n \"\"\"\n 去噪点\n :param img: 图片对象\n :return: 去除背景的图片\n \"\"\"\n return ImageEnhance.Sharpness(img).enhance(3)\n\ndef get_img_properties(img):\n \"\"\"\n 获取文件的属性\n >>> from __future__ import print_function\n >>> print(im.format, im.size, im.mode)\n PPM (512, 512) RGB\n format 这个属性标识了图像来源。如果图像不是从文件读取它的值就是None, 也就是这个图片是什么类型的图片，比如a.tif, 那么就是TIFF\n size属性是一个二元tuple，包含width和height（宽度和高度，单位都是px)。\n mode 属性定义了图像bands的数量和名称，以及像素类型和深度。常见的modes\n 有 “L” (luminance) 表示灰度图像, “RGB” 表示真彩色图像, and “CMYK” 表示出版图像。\n :param img: 加载过的图片对象\n :return: (format, size, mode)\n \"\"\"\n return (img.format, img.size, img.mode)\n\ndef show(img):\n \"\"\"\n 显示图像\n 注解 标准的 show() 效率并不高，它需要保存图像到临时文件\n 然后通过 xv 显示图像。你需要先安装 xv ，显示图像有助于调试和测试。\n :param img: 加载到内存中的图片\n :return:\n \"\"\"\n img.show()\n\ndef create_thumbnail(img, width, height):\n \"\"\"\n 创建缩略图\n 缩略图的意思就是缩小\n :param img: 图片对象\n :param width: 宽\n :param height: 高\n :return:\n \"\"\"\n size = (width, height)\n img.thumbnail(size)\n return img\n\ndef cut(img, left, above, right, down):\n \"\"\"\n 从图像中复制出一个矩形选区\n\n box = (100, 100, 400, 400)\n region = im.crop(box)\n 矩形选区有一个4元元组定义，分别表示左、上、右、下的坐标。这个库以左上角为坐标原点，\n 单位是px，所以上诉代码复制了一个 300x300 pixels 的矩形选区\n\n :param img: 加载到内存的图片\n :param left: 左\n :param above: 上\n :param right: 右\n :param down: 下\n :return:\n \"\"\"\n box = (left, above, right, down)\n region = img.crop(box)\n return region\n\ndef paste(region, img, left, above, right, down):\n \"\"\"\n 将扣的图粘贴到制定图片上\n 当你粘贴矩形选区的时候必须保证尺寸一致。此外，矩形选区不能在图像外。然而你不必保证矩形选区和原图的颜色模式一致，\n 因为矩形选区会被自动转换颜色，遗憾的是，只能扣矩形图。\n\n :param region: 扣出的图\n :param img: 指定图片\n :param left: 左\n :param above: 上\n :param right: 右\n :param down: 下\n :return: 被修改过的图片对象，还在内存中，未保存。\n \"\"\"\n region = region.transpose(Image.ROTATE_180)\n box = (left, above, right, down)\n img.paste(region, box)\n return img\n\ndef split_color_channel(img):\n \"\"\"\n 分离颜色通道\n :param img: 加载到内存的图片\n :return: 颜色通道\n \"\"\"\n return img.split()\n\ndef merge_color_channel(mode, *params):\n \"\"\"\n 合并颜色通道\n :param mode: 颜色通道\n :param params: 颜色通道元组参数\n :return: 合并后的图像\n \"\"\"\n return Image.merge(mode, params)\n\ndef resize(img, width, height):\n \"\"\"\n 更改图片大小，只能更改磁盘空间的大小。\n :param img:\n :param width:\n :param height:\n :return: 更改后的图片\n \"\"\"\n return img.resize((width, height), Image.ANTIALIAS)\n\ndef rotate(img, angle):\n \"\"\"\n 旋转图片\n :param img: 图片\n :param angle: 度数\n :return: 新图片\n \"\"\"\n return img.rotate(angle)\n\ndef filter(img, filter_class):\n \"\"\"\n 图像滤波\n\n TODO：由于关于滤波方面的图像处理技术，历史可以追溯到1980年左右，所以，学些这方面的算法的时间需要一定的时间，看来源码\n 原作者写了很多的滤波器，所以，得研究下每种滤波器的优缺点，使用场景。\n :param img:\n :param filter_class:\n :return:\n \"\"\"\n pass\n\nclass GPS:\n def get_exif_data(self, image):\n \"\"\"Returns a dictionary from the exif data of an PIL Image item. Also converts the GPS Tags\"\"\"\n exif_data = {}\n info = image._getexif()\n if info:\n for tag, value in info.items():\n decoded = TAGS.get(tag, tag)\n if decoded == \"GPSInfo\":\n gps_data = {}\n for t in value:\n sub_decoded = GPSTAGS.get(t, t)\n gps_data[sub_decoded] = value[t]\n\n exif_data[decoded] = gps_data\n else:\n exif_data[decoded] = value\n\n return exif_data\n\n def _get_if_exist(self, data, key):\n if key in data:\n return data[key]\n\n return None\n\n def _convert_to_degress(self, value):\n \"\"\"Helper function to convert the GPS coordinates stored in the EXIF to degress in float format\"\"\"\n d0 = value[0][0]\n d1 = value[0][1]\n d = float(d0) / float(d1)\n\n m0 = value[1][0]\n m1 = value[1][1]\n m = float(m0) / float(m1)\n\n s0 = value[2][0]\n s1 = value[2][1]\n s = float(s0) / float(s1)\n\n return d + (m / 60.0) + (s / 3600.0)\n\n def get_lat_lon(self, exif_data):\n \"\"\"Returns the latitude and longitude, if available, from the provided exif_data (obtained through get_exif_data above)\"\"\"\n lat = None\n lon = None\n\n if \"GPSInfo\" in exif_data:\n gps_info = exif_data[\"GPSInfo\"]\n\n gps_latitude = self._get_if_exist(gps_info, \"GPSLatitude\")\n gps_latitude_ref = self._get_if_exist(gps_info, 'GPSLatitudeRef')\n gps_longitude = self._get_if_exist(gps_info, 'GPSLongitude')\n gps_longitude_ref = self._get_if_exist(gps_info, 'GPSLongitudeRef')\n\n if gps_latitude and gps_latitude_ref and gps_longitude and gps_longitude_ref:\n lat = self._convert_to_degress(gps_latitude)\n if gps_latitude_ref != \"N\":\n lat = 0 - lat\n\n lon = self._convert_to_degress(gps_longitude)\n if gps_longitude_ref != \"E\":\n lon = 0 - lon\n\n return lat, lon\n\n def get_gps(self, image):\n \"\"\"获取经度，纬度\"\"\"\n exif_data = self.get_exif_data(image)\n return self.get_lat_lon(exif_data)\n\n def set_gps(self, image, lat, lon):\n pass\n\ndef get_size(img):\n \"\"\"\"\"\"\n return img.size\n\ndef save(filename, img):\n img.save(filename)\n","repo_name":"shi-cong/PYSTUDY","sub_path":"PYSTUDY/image/pillib.py","file_name":"pillib.py","file_ext":"py","file_size_in_byte":9029,"program_lang":"python","lang":"zh","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"29174220797","text":"import os\n\n\nIS_ARCADIA = 'ARCADIA_SOURCE_ROOT' in os.environ\n\nif not IS_ARCADIA:\n # import awacs first to let it call gevent monkeypatch\n import awacs # noqa\n from awacs.model.objects import L7HeavyConfig\n\n # then hack threading module to prevent the following error when importing pdb or ipython:\n # The 'save_flag' trait of a HistoryManager instance must be a _Event or None, but a value of class 'gevent.event.Event'\n import threading\n\n\n threading._Event = threading.Event # noqa\n\n # rewrite asserts in utility functions, need to call this before import\n import pytest\n\n\n pytest.register_assert_rewrite('awtest') # noqa\n\n import socket\n import time\n import logging\n import copy\n import pexpect\n import six\n from kazoo.exceptions import NoNodeError\n from sepelib.core import config as app_config\n from infra.swatlib.cmdutil import setup_logging, setup_logging_to_stdout\n from infra.swatlib import metrics\n from awacs.app.base import ApplicationBase\n from awacs.lib import zookeeper_client, context, nannyclient, mongo, racktables\n from awacs.lib.models import classes as model_classes\n from awacs.model import db, cache as c, apicache as c2, storage_modern as zks\n from awacs.model.dao import Dao, IDao\n from awacs.model.zk import ZkStorage, IZkStorage\n from awacs.web.app import create_app\n from awtest.network import socket_allow_hosts, get_local_ip_v4, get_local_ip_v6, worker_id_to_offset\n from awtest.mocks.httpbin_server import Httpbin\n from awtest.mocks.racktables import RacktablesMockClient\n from awtest.mocks.yp_sd import SdStub\n from awtest.api import create_namespace\n from awtest.core import Checker\n from awtest import xdist\n from awtest.mocks import mongo as mongomock, zookeeper as zookeepermock\n from awtest.ctl_runner import CtlRunner\n from awtest.mocks.abc_client import AbcMockClient\n from awtest.mocks.dns_manager_client import DnsResolverMock, DnsManagerClientMock\n from awtest.mocks.l3mgr_client import L3MgrMockClient\n from awtest.mocks.nanny_client import NannyMockClient\n from awtest.mocks.nanny_rpc_client import NannyRpcMockClient\n from awtest.mocks.yp_lite_client import YpLiteMockClient\n\n\n def pytest_sessionstart(session):\n if session.config.getoption(u'--vcr-record-mode') in (u'all', u'new_episodes'):\n return\n allowed = session.config.getoption(u'--allow-hosts')\n hosts = set()\n if allowed:\n hosts |= {host.strip() for host in allowed.split(u',')}\n if u'local_ip_v4' in hosts:\n hosts.discard(u'local_ip_v4')\n local_ip_v4 = get_local_ip_v4()\n if local_ip_v4:\n hosts.add(local_ip_v4)\n if u'local_ip_v6' in hosts:\n hosts.discard(u'local_ip_v6')\n local_ip_v6 = get_local_ip_v6()\n if local_ip_v6:\n hosts.add(local_ip_v6)\n socket_allow_hosts(hosts)\n\n\n if not IS_ARCADIA:\n def monkeypatch_execnet():\n # allows us to avoid errors like\n # Exception KeyError: KeyError(140283530475792,) in ignored # noqa\n # see https://stackoverflow.com/questions/8774958/keyerror-in-module-threading-after-a-successful-py-test-run for details # noqa\n import execnet.gateway_io\n\n patch_string = 'import gevent.monkey;gevent.monkey.patch_all(Event=True);'\n if not execnet.gateway_io.popen_bootstrapline.startswith(patch_string):\n execnet.gateway_io.popen_bootstrapline = patch_string + execnet.gateway_io.popen_bootstrapline\n\n\n def pytest_cmdline_main(config): # noqa\n if config.option.numprocesses:\n monkeypatch_execnet()\n config.option.tx = ['popen//execmodel=gevent'] * config.option.numprocesses\n\n\n def pytest_addoption(parser):\n parser.addoption('--zookeeper', help='path to ZooKeeper directory', default='/opt/zookeeper-3.4.14/')\n parser.addoption('--config', '--cfg', help='path to awacs config')\n parser.addoption('--balancer', help='path to balancer executable')\n parser.addoption('--runslow', action='store_true', default=False, help='run slow tests')\n parser.addoption(\n '--allow-hosts',\n dest='allow_hosts',\n metavar='ALLOWED_HOSTS_CSV',\n help='Only allow specified hosts through socket.socket.connect((host, port)).',\n default='127.0.0.1,::1,local_ip_v4,local_ip_v6,localhost'\n )\n\n\n if IS_ARCADIA:\n @pytest.fixture(scope='module')\n def vcr_cassette_dir(request):\n from yatest import common\n return common.source_path('infra/awacs/vendor/awacs/tests/cassettes')\n\n\n def pytest_configure(config):\n config.option.verbose = True\n config.addinivalue_line(\"markers\", \"allow_hosts([hosts]): Restrict socket connection to defined list of hosts\")\n config.addinivalue_line(\"markers\", \"slow: marks tests as slow\")\n if IS_ARCADIA:\n from yatest import common\n config.option.vcr_record = common.get_param('vcr-record-mode')\n\n\n def pytest_ignore_collect(path, config):\n path_str = six.text_type(path)\n return 'tests/fixtures' in path_str or 'tests/cassettes' in path_str\n\n\n def pytest_collection_modifyitems(config, items):\n if config.getoption(\"--runslow\"):\n # --runslow given in cli: do not skip slow tests\n return\n skip_slow = pytest.mark.skip(reason='need --runslow option to run')\n for item in items:\n if 'slow' in item.keywords:\n item.add_marker(skip_slow)\n\n\n def pytest_assertrepr_compare(op, left, right):\n class_name = left.__class__.__name__\n if class_name not in ('L7State', 'L3State', 'DnsRecordState'):\n return\n if right.__class__.__name__ != class_name or op != '==':\n return\n return ['Comparing State instances:'] + str(left).splitlines() + ['------'] + str(right).splitlines()\n\n\n if IS_ARCADIA:\n @pytest.fixture(scope='session')\n def worker_id():\n return 'master'\n\n\n @pytest.fixture(scope='session')\n def sd_stub(tmpdir_factory, worker_id):\n offset = worker_id_to_offset(worker_id)\n sd_stub = SdStub(port=SdStub.port + offset, httpbin_port=Httpbin.port + offset)\n sd_stub.start()\n yield sd_stub\n sd_stub.terminate()\n\n\n @pytest.fixture(scope='session')\n def httpbin(tmpdir_factory, worker_id, sd_stub):\n offset = worker_id_to_offset(worker_id)\n hb = Httpbin(port=Httpbin.port + offset)\n hb.start()\n yield hb\n hb.terminate()\n\n\n @pytest.fixture(scope='session')\n def vcr_config():\n # http://pytest-vcr.readthedocs.io/en/latest/#filtering-saved-requestresponse\n return {\n # Replace the Authorization request header with \"DUMMY\" in cassettes\n 'filter_headers': [('authorization', 'DUMMY')],\n }\n\n\n @pytest.fixture(scope='session')\n def test_config_path(request):\n if IS_ARCADIA:\n return 'deps/cfg_test.yml'\n if request.config.option.config:\n return request.config.option.config\n else:\n return './cfg_test.yml'\n\n\n @pytest.fixture(scope='session')\n def balancer_executable_path(request):\n if IS_ARCADIA:\n from yatest import common\n return common.build_path('infra/awacs/vendor/awacs/tests/deps/balancer')\n return request.config.option.balancer or pexpect.which('balancer')\n\n\n @pytest.fixture(scope='session')\n def zk_prefix(worker_id):\n return '/awacs_test_{}/'.format(worker_id)\n\n\n @pytest.fixture(scope='session')\n def initial_test_config(test_config_path):\n if IS_ARCADIA:\n path = 'deps/cfg_default.yml'\n else:\n from infra.swatlib.cmdutil import DEFAULT_CONFIG_PATH\n path = DEFAULT_CONFIG_PATH\n app_config.load(test_config_path, defaults=path)\n app_config.set_value('run.auth', False)\n return copy.deepcopy(app_config._CONFIG)\n\n\n @pytest.fixture(autouse=True)\n def test_config(initial_test_config):\n app_config._CONFIG = copy.deepcopy(initial_test_config)\n\n\n @pytest.fixture(scope='session')\n def port_manager(request):\n if IS_ARCADIA:\n from yatest.common import network\n yield network.PortManager()\n else:\n yield None\n\n\n @pytest.fixture(scope='session')\n def zk_session_connection(request, tmpdir_factory, worker_id, zk_prefix, initial_test_config, port_manager):\n if IS_ARCADIA:\n from yatest import common\n import os.path\n import tarfile\n import hashlib\n\n def untar(file_path, path='.'):\n tar = tarfile.open(file_path)\n tar.extractall(path)\n tar.close()\n\n uniq = hashlib.md5(os.getcwd().encode(\"utf-8\")).hexdigest()\n # zookeeper_dir_path = os.path.join(os.getcwd(), uniq)\n zookeeper_dir_path = common.output_path(uniq)\n try:\n os.makedirs(zookeeper_dir_path)\n except OSError:\n pass\n zookeeeper_tgz_path = common.build_path('infra/awacs/vendor/awacs/tests/deps/zookeeper.tar.gz')\n untar(zookeeeper_tgz_path, path=zookeeper_dir_path)\n zookeeper_dir_path = os.path.join(zookeeper_dir_path, 'zookeeper-3.4.6')\n else:\n assert request.config.option.zookeeper\n zookeeper_dir_path = request.config.option.zookeeper\n with xdist.run_once(tmpdir_factory, worker_id,\n config_name='zk_config.json',\n config=dict(app_config.get_value('coord'))) as (zk_config, already_running):\n if not already_running:\n server = zookeepermock.ZooKeeper(zookeeper_dir_path, port_manager=port_manager)\n xdist.register_cleanup(request, worker_id, server.disconnect)\n zk_config['hosts'] = server.hosts\n zk_config['zk_root'] = zk_prefix\n zk_identifier = '{}:{}:{}'.format(socket.gethostname(), app_config.get_value('web.http.port'), worker_id)\n zk_client = zookeeper_client.ZookeeperClient(zk_config, identifier=zk_identifier,\n metrics=metrics.ROOT_REGISTRY)\n zk_client.start().wait()\n kazoo_logger = zk_client.client.logger\n kazoo_logger.setLevel(logging.WARN)\n yield zk_client\n zk_client.stop()\n zk_client.close()\n\n\n @pytest.fixture\n def zk(zk_session_connection):\n try:\n children = zk_session_connection.get_children('/')\n except NoNodeError:\n pass\n else:\n for child in children:\n zk_session_connection.delete_file(child, recursive=True)\n yield zk_session_connection\n\n\n @pytest.fixture\n def cache(zk, zk_prefix):\n L7HeavyConfig.cache.clear()\n rv = c.AwacsCache(zk_client=zk, path=zk_prefix, enable_extended_signals=True, proxy_counters_cache_ttl=0,\n structure=zks.construct_full_zk_structure())\n rv.start()\n yield rv\n rv.stop()\n\n\n @pytest.fixture\n def apicache(zk):\n return c2.AwacsApiCache()\n\n\n @pytest.fixture\n def mongo_storage(mongo_connection):\n return db.MongoStorage()\n\n\n @pytest.fixture\n def zk_storage(zk, zk_prefix):\n return ZkStorage(zk, prefix=zk_prefix)\n\n\n @pytest.fixture(scope='session')\n def mongo_session_connection(request, tmpdir_factory, worker_id):\n if IS_ARCADIA:\n from yatest import common\n os.environ['PATH'] += os.pathsep + common.build_path('infra/awacs/vendor/awacs/tests/deps/')\n with xdist.run_once(tmpdir_factory, worker_id,\n config_name='mongodb_config.json',\n config={}) as (mongodb_config, already_running):\n if not already_running:\n mongodb = mongomock.MongoDb()\n xdist.register_cleanup(request, worker_id, mongodb.kill)\n mongodb_config['host'] = mongodb.host\n yield mongo.connect(worker_id, host=mongodb_config['host'])\n mongo.disconnect()\n\n\n @pytest.fixture\n def mongo_connection(worker_id, mongo_session_connection):\n connection = mongo_session_connection\n mongodb = connection[worker_id]\n for collection_name in mongodb.collection_names(include_system_collections=False):\n mongodb[collection_name].remove({})\n yield connection\n\n\n @pytest.fixture\n def dao(zk_storage, mongo_storage, cache):\n return Dao(zk_storage, mongo_storage, cache)\n\n\n @pytest.fixture(scope='session', autouse=True)\n def log():\n console_handler = setup_logging_to_stdout(ApplicationBase.LOG_FORMAT)\n setup_logging({'loglevel': 'DEBUG'}, console_handler, console=1,\n fmt=ApplicationBase.LOG_FORMAT, filter_=ApplicationBase.LOG_FILTER)\n yield\n logging.getLogger().removeHandler(console_handler)\n\n\n @pytest.fixture\n def create_default_namespace(zk_storage, cache):\n return lambda namespace_id: create_namespace(zk_storage, cache, namespace_id)\n\n\n @pytest.fixture\n def nanny_rpc_mock_client():\n return NannyRpcMockClient()\n\n\n @pytest.fixture\n def yp_lite_mock_client():\n return YpLiteMockClient()\n\n\n @pytest.fixture\n def abc_client():\n return AbcMockClient()\n\n\n @pytest.fixture\n def l3_mgr_client():\n return L3MgrMockClient()\n\n\n @pytest.fixture\n def dns_resolver_mock():\n return DnsResolverMock()\n\n\n @pytest.fixture\n def dns_manager_client_mock():\n return DnsManagerClientMock()\n\n\n @pytest.fixture\n def binder(mongo_storage, zk_storage, zk, zk_prefix, cache, apicache, dao, log):\n def configure(b):\n model_classes.ModelZkClient.awtest_set_zk_prefix(zk_prefix.rstrip('/'))\n b.bind(db.IMongoStorage, mongo_storage)\n b.bind(zookeeper_client.IZookeeperClient, zk)\n b.bind(IZkStorage, zk_storage)\n b.bind(c.IAwacsCache, cache)\n b.bind(c2.IAwacsApiCache, apicache)\n b.bind(IDao, dao)\n b.bind(racktables.IRacktablesClient, RacktablesMockClient())\n\n return configure\n\n\n @pytest.fixture\n def binder_with_nanny_client(binder):\n def configure(b):\n b.bind(nannyclient.INannyClient, NannyMockClient(url='https://nanny.yandex-team.ru/v2/', token='DUMMY'))\n binder(b)\n\n return configure\n\n\n @pytest.fixture\n def ctlrunner(zk):\n r = CtlRunner(zk)\n yield r\n r.stop()\n\n\n @pytest.fixture\n def ctx():\n return context.BackgroundCtx().with_op(op_id='test-op', log=logging.getLogger('awacs-tests'))\n\n\n @pytest.fixture(scope='session', autouse=True)\n def flask_app(initial_test_config):\n app = create_app(name='awacsd',\n hostname='localhost',\n version='0.0.1',\n version_timestamp=int(time.time()))\n with app.test_request_context():\n yield app\n\n\n @pytest.fixture(autouse=True)\n def clean_metrics_registry():\n metrics.ROOT_REGISTRY.clear()\n\n\n @pytest.fixture\n def enable_auth():\n prev_value = app_config.get_value('run.auth', False)\n app_config.set_value('run.auth', True)\n yield\n app_config.set_value('run.auth', prev_value)\n\n\n _checker = Checker()\n\n\n @pytest.fixture\n def checker():\n return _checker\n","repo_name":"Alexander-Berg/2022-tests-examples","sub_path":"infra/tests/conftest (6).py","file_name":"conftest (6).py","file_ext":"py","file_size_in_byte":15830,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"42750252674","text":"import random\nimport re\nfrom time import sleep\n\nfrom src.modules import ModuleWrapper\n\nPRIORITY = 3\nSECURE = True\n\nzwischenPattern = re.compile(r\".*(von|zwischen) (-?\\d+) (und|bis) (-?\\d+).*\", re.I)\nbisPattern = re.compile(r\".*(bis|kleiner gleich) (-?\\d+).*\", re.I)\nkleinerPattern = re.compile(r\".*(unter|kleiner) (als)? (-?\\d+).*\", re.I)\n\n\ndef output(text):\n output = \"\"\n text = text.lower()\n t = str.split(text)\n if \"münze\" in text or (\"kopf\" in text and \"oder\" in text and \"zahl\" in text):\n q = random.randint(1, 2)\n if q == 1:\n output = \"kopf\"\n else:\n output = \"zahl\"\n elif \"würfel\" in text or \"alea iacta est\" in text:\n q = random.randint(1, 6)\n if q == 1:\n output = \"eins\"\n elif q == 2:\n output = \"zwei\"\n elif q == 3:\n output = \"drei\"\n elif q == 4:\n output = \"vier\"\n elif q == 5:\n output = \"fünf\"\n else:\n output = \"sechs\"\n elif (\"zufall\" in text or \"zufällig\" in text) and \"zahl\" in text:\n match = zwischenPattern.match(text)\n if output == \"\" and match is not None:\n if int(match.group(2)) < int(match.group(4)):\n output = str(random.randint(int(match.group(2)), int(match.group(4))))\n else:\n output = str(random.randint(int(match.group(4)), int(match.group(2))))\n match = bisPattern.match(text)\n if output == \"\" and match is not None:\n if match.group(2) > 0:\n output = str(random.randint(1, int(match.group(2))))\n else:\n output = str(random.randint(int(match.group(2)), 1))\n match = kleinerPattern.match(text)\n if output == \"\" and match is not None:\n if match.group(3) > 0:\n output = str(random.randrange(1, int(match.group(3))))\n else:\n output = str(random.randrange(int(match.group(3)), 1))\n\n elif \"schere\" in text or \"stein\" in text or \"papier\" in text:\n possibilities = [\"Schere\", \"Stein\", \"Papier\"]\n zufall = random.randint(0, 2)\n output = possibilities[zufall]\n\n elif \"grade\" in text and \"ungerade\" in text:\n possibilities = [\"grade\", \"ungerade\"]\n output = random.choice(possibilities)\n\n if output == \"\":\n output = str(random.randint(1, 100))\n return output\n\n\ndef handle(text: str, wrapper: ModuleWrapper) -> None:\n ausgabe = output(text).strip()\n if ausgabe.startswith(\"-\"):\n ausgabe = \"minus \" + ausgabe[1:]\n wrapper.say(\"drei\")\n sleep(1)\n wrapper.say(\"zwei\")\n sleep(1)\n wrapper.say(\"eins\")\n sleep(1)\n wrapper.say(ausgabe)\n\n\ndef is_valid(text: str) -> bool:\n text = text.lower()\n if (\n \"münze\" in text\n or (\"kopf\" in text and \"oder\" in text and \"zahl\" in text)\n or \"würfel\" in text\n or ((\"zufall\" in text or \"zufällig\" in text) and \"zahl\" in text)\n ):\n return True\n elif \"schere\" in text and \"stein\" in text and \"papier\" in text:\n return True\n elif \"grade\" in text and \"ungerade\" in text:\n return True\n","repo_name":"ukaserge/Jarvis","sub_path":"speechassistant/src/modules/on_call/impl/zufallsgenerator.py","file_name":"zufallsgenerator.py","file_ext":"py","file_size_in_byte":3166,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"16109603734","text":"import logging\n\nfrom aiogram.fsm.context import FSMContext\n\nfrom aiogram import Router, F\nfrom aiogram.filters import Command\nfrom aiogram.types import Message, ReplyKeyboardRemove\n\nfrom Forms.get_points_form import Form\nfrom keyboards.keyboards import get_yes_no_kb, get_duration_kb\n\nfrom funcs.db import check_existing_user, update_user_points, check_need_validation\nfrom secret import CARD_NUM\n\nform_router = Router()\n\n\n@form_router.message(Command(\"get_points\"))\nasync def command_get_points(message: Message, state: FSMContext) -> None:\n user_id = message.from_user.id\n\n existing_user = check_existing_user(user_id)\n\n if existing_user:\n\n if check_need_validation(user_id):\n\n await message.answer(\n f\"Прости,я еще не успел проверить твое старое пополнение!\",\n reply_markup=ReplyKeyboardRemove(),\n )\n await state.clear()\n\n else:\n\n user_name = existing_user[1]\n vpn_number = existing_user[2] # Получаем номер из базы данных\n points = existing_user[3] # Получаем количество поинтов из базы данных\n\n await message.answer(f'{user_name} ({vpn_number}), у тебя еще {points} дней подписки!')\n await message.answer(\n 'Хочешь продлить подписку?',\n reply_markup=get_yes_no_kb()\n )\n await state.set_state(Form.want_to_purchase)\n\n else:\n await message.answer(\n 'Тебя нет в моей базе данных! \\nДля начала нажми /start',\n reply_markup=ReplyKeyboardRemove(),\n )\n\n\n@form_router.message(Command(\"cancel\"))\n@form_router.message(F.text.casefold() == \"cancel\")\nasync def cancel_handler(message: Message, state: FSMContext) -> None:\n \"\"\"\n Allow user to cancel any action\n \"\"\"\n current_state = await state.get_state()\n if current_state is None:\n return\n\n logging.info(\"Cancelling state %r\", current_state)\n await state.clear()\n await message.answer(\n \"Cancelled.\",\n reply_markup=ReplyKeyboardRemove(),\n )\n\n\n@form_router.message(Form.want_to_purchase, F.text.casefold() == \"да\")\nasync def process_want_to_purchase_yes(message: Message, state: FSMContext) -> None:\n\n await message.reply(\n f\"Отлично! На сколько дней ты хочешь продлить подписку?\",\n reply_markup=get_duration_kb(),\n )\n await state.set_state(Form.select_duration)\n\n\n@form_router.message(Form.want_to_purchase, F.text.casefold() == \"нет\")\nasync def process_want_to_purchase_no(message: Message, state: FSMContext) -> None:\n\n await message.reply(\n f\"Это печально(\",\n reply_markup=ReplyKeyboardRemove(),\n )\n await message.answer_sticker('CAACAgIAAxkBAAEKlbtlNs1hWQIfElCygR6Wv9hITQPHGwACfhoAAmZWIEpJ207LaLOGJzAE')\n await state.clear()\n\n\n@form_router.message(Form.want_to_purchase)\nasync def process_unknown_want_to_purchase(message: Message) -> None:\n await message.reply(\"Я не понимаю тебя :(\")\n\n\n@form_router.message(Form.select_duration, F.text.in_({'30', '60'}))\nasync def process_duration(message: Message, state: FSMContext) -> None:\n\n days = message.text\n await state.update_data(duration=days)\n\n await message.reply(\n f\"Ты выбрал {days} дней\",\n reply_markup=get_yes_no_kb(),\n )\n\n\n@form_router.message(Form.select_duration, F.text.casefold() == \"да\")\nasync def process_duration_yes(message: Message, state: FSMContext) -> None:\n\n data = await state.get_data()\n duration = data.get(\"duration\")\n\n await message.reply(\n f\"Хорошо. Вот мои реквизиты\"\n f\"\\nНомер карты: {CARD_NUM} - Александр Ш.\"\n f\"\\nСумма: {int(duration) / 30 * 50}р\",\n reply_markup=ReplyKeyboardRemove(),\n )\n await message.answer(\n \"После оплаты пришли скриншот в чат\"\n \"\\nПринимаю только одну фотографию\"\n )\n await state.set_state(Form.send_photo)\n\n\n@form_router.message(Form.select_duration, F.text.casefold() == \"нет\")\nasync def process_duration_no(message: Message) -> None:\n\n await message.reply(\n f\"Выбор за тобой\",\n reply_markup=get_duration_kb(),\n )\n\n\n@form_router.message(Form.select_duration)\nasync def process_unknown_duration(message: Message) -> None:\n await message.reply(\"Я не понимаю тебя :(\")\n\n\n@form_router.message(Form.send_photo, F.photo)\nasync def process_send_photo(message: Message, state: FSMContext) -> None:\n\n from essentials import bot\n user_id = message.from_user.id\n user = check_existing_user(user_id)\n admin_id = 1298017336\n photo = message.photo[-1].file_id\n data = await state.get_data()\n duration = data.get(\"duration\")\n\n await bot.send_photo(chat_id=admin_id, photo=photo, caption=f'Новый перевод:\\n'\n f'от {user[1]} ({user[2]})\\n'\n f'на {duration} дней')\n db_response = update_user_points(user_id, duration)\n\n if db_response:\n await message.reply(\n f\"Фотографию получил. Подписка будет продлена на {duration} дней после проверки!\",\n reply_markup=ReplyKeyboardRemove(),\n )\n else:\n await message.reply(\n f\"Тебе нужно дождаться, пока я проверю предыдущую фотографию\",\n reply_markup=ReplyKeyboardRemove(),\n )\n await state.clear()\n\n\n@form_router.message(Form.send_photo)\nasync def process_unknown_send_photo(message: Message) -> None:\n await message.reply(\"На данном этапе я принимаю только фотографии\")\n","repo_name":"AlexShmigelskii/vpn_bot","sub_path":"handlers/get_points.py","file_name":"get_points.py","file_ext":"py","file_size_in_byte":6100,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"30333527408","text":"# -*- coding: utf-8 -*-\r\n\r\ndef main():\r\n funcionario = int(input())\r\n horas = int(input())\r\n valor_hora = float(input())\r\n salario = horas * round(valor_hora, 2)\r\n\r\n print('NUMBER = '+str(funcionario))\r\n print('SALARY = U$ {0:.2f}'.format(salario))\r\n\r\n\r\nif __name__ == \"__main__\":\r\n main()","repo_name":"mverzeletti/URI","sub_path":"1008.py","file_name":"1008.py","file_ext":"py","file_size_in_byte":310,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"38454941373","text":"# 10828: 스택\nimport sys\nn = int(sys.stdin.readline())\n\nstk = []\nfor _ in range(n) :\n order = str(sys.stdin.readline())\n if 'push' in order :\n stk.append(int(order.split()[1]))\n\n elif 'pop' in order :\n if len(stk) != 0 :\n print(stk[-1])\n del stk[-1]\n else :\n print(-1)\n\n elif 'size' in order :\n print(len(stk))\n\n elif 'empty' in order :\n if len(stk) == 0 :\n print(1)\n else :\n print(0)\n\n else :\n if len(stk) == 0 :\n print(-1)\n else :\n print(stk[-1])\n","repo_name":"mosePark/BOJ-Algorithm","sub_path":"스택/10828: 스택.py","file_name":"10828: 스택.py","file_ext":"py","file_size_in_byte":603,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"538570854","text":"import sys\nfrom typing import Optional\nimport pygame\n\nfrom Game.directions import Direction\nfrom Game.game_obect_types import GameObjectType\nfrom Game.game_object import GameObject\nfrom Graphics.color_palette import init_palettes\nfrom Graphics.constants import FPS, SPRITE_WIDTH\nfrom Graphics.load_level_from_file import load_level\nfrom Graphics.main_window import MainWindow\n\nw: Optional[MainWindow] = None\n\n\ndef main():\n global w\n\n pygame.init()\n pygame.key.set_repeat(200, 200)\n\n w = MainWindow()\n init_palettes()\n\n level_num = 0\n level = load_level(f\"level{level_num}.txt\")\n # level = load_level(\"levelmake.txt\")\n w.set_playing_level(level)\n\n clock = pygame.time.Clock()\n\n # adding_go = GameObject(level, 0, 0, GameObjectType.ROCK, Direction.NORTH)\n # level.add_go(adding_go)\n\n while True:\n event = pygame.event.poll()\n if event.type == pygame.QUIT:\n # for go in level.gos:\n # print(f\"{go.object_type},{go.x},{go.y}\")\n\n pygame.quit()\n sys.exit(0)\n elif event.type == pygame.KEYDOWN:\n # if event.key == 61:\n # if adding_go.object_type.value != 25:\n # adding_go.object_type = GameObjectType(adding_go.object_type.value + 1)\n # adding_go.get_sprite().object_type = GameObjectType(adding_go.object_type.value)\n # adding_go.get_sprite()._update_images()\n # elif event.key == 45:\n # if adding_go.object_type.value != 0:\n # adding_go.object_type = GameObjectType(adding_go.object_type.value - 1)\n # adding_go.get_sprite().object_type = GameObjectType(adding_go.object_type.value)\n # adding_go.get_sprite()._update_images()\n\n level.receive_input(event.key)\n # elif event.type == pygame.MOUSEBUTTONUP:\n # adding_go = GameObject(level, adding_go.x, adding_go.y, adding_go.object_type, Direction.NORTH)\n # level.add_go(adding_go)\n\n # mx, my = pygame.mouse.get_pos()\n # draw_rect = level.get_tile_grid().get_rect()\n # draw_rect.center = w.screen.get_rect().center\n # gx = (mx - draw_rect.left) // (level.get_tile_grid().scale_factor * SPRITE_WIDTH)\n # gy = (my - draw_rect.top) // (level.get_tile_grid().scale_factor * SPRITE_WIDTH)\n # adding_go.set_x(gx)\n # adding_go.set_y(gy)\n\n level.get_tile_grid().update()\n w.draw_grid()\n pygame.display.flip()\n\n clock.tick(FPS)\n\n if level.won and w.win_counter == -1:\n w.init_win_animation()\n if w.win_counter == -2:\n level_num += 1\n if level_num >= 5:\n break\n level = load_level(f\"level{level_num}.txt\")\n w.set_playing_level(level)\n\n\nif __name__ == '__main__':\n main()\n","repo_name":"Dragon-Hatcher/BabaIsClone","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":2880,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"35913362216","text":"from class_calculator import Calculator\nfrom user_interface import UserInterface\n\nclass DanielCalculator(Calculator , UserInterface):\n def add_new(self, number1 , number2):\n try:\n sum = number1 + number2\n return sum\n except ValueError:\n print(\"Your input must be a integer\")\n \n def minus_new(self, number1 , number2):\n try:\n difference = number1 - number2\n return difference\n except ValueError:\n print(\"Your input must be a integer\")\n \n def multiply_new(self, number1 , number2):\n try:\n product = number1 * number2\n return product\n except ValueError:\n print(\"Your input must be a integer\")\n \n def divide_new(self, number1, number2):\n try:\n quotient = number1 / number2\n return quotient\n except ValueError:\n print(\"Your input must be a integer\")\n except ZeroDivisionError:\n print(\"You are dividing by Zero\")","repo_name":"MoonHunter99/Calculator_as_OOP","sub_path":"daniel_calculator.py","file_name":"daniel_calculator.py","file_ext":"py","file_size_in_byte":1033,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"33524346151","text":"#------------------------------------------------------------------------------------------------------------------------------------------------------------\n#Author: Krishna Chaitanya chavati\n#Email: chaithukrishnazz2@gmail.com\n#Date: 7th March'14\n#Title: Naive_bayes classifier\n#execution time\t: 20 seconds for 500000 training samples and 200000 testing samples with 4 attributes and 2 labels\n#-------------------------------------------------------------------------------------------------------------------------------------------------------------\n\nimport sys\nimport numpy as np\nimport math\n\nclass Naive_Bayes(object):\n\n\tdef __init__(self):\n\t\tself.Accumulator = None\n\t\tself.Predictor = None\n\t\tself.number_of_attributes = None\n\t\tself.number_of_samples = None\n\t\tself.number_of_labels = None\n\t\tself.unique_labels = None\n\t\tself.intermediate_array = None\n\t\tself.normalization_constant = None\n\n\t\"\"\"\tMethod to fit the training data in to the classifier. Builds a model by accumulating the mean and standard deviation\n\t\tfor each attribute for each label and stores it for the purpose of predicting \"\"\"\n\tdef train(self, xtrain, ytrain):\n\t\tself.number_of_attributes = len(xtrain[0])\n\t\tself.number_of_samples = len(xtrain)\n\t\tself.unique_labels = list(set(ytrain))\n\t\tself.number_of_labels = len(self.unique_labels)\n\t\tself.Accumulator = np.zeros((self.number_of_attributes, self.number_of_labels, 2), float)\n\t\tfor i in range(0, self.number_of_attributes):\n\t\t\tfor j in range(0, self.number_of_labels):\n\t\t\t\ttemp_array = [xtrain[n][i] for n in range(0, self.number_of_samples) if ytrain[n] == self.unique_labels[j]]\n\t\t\t\ttemporary_mean = np.mean(temp_array)\n\t\t\t\tself.Accumulator[i][j][0] = temporary_mean\n\t\t\t\tself.Accumulator[i][j][1] = np.std(temp_array)\n\t\t\t\t\n\t\"\"\" This method predicts the labels of the testing data by obtaining the probability distribution functions of each attribute\n\tfor each label and stores it an three dimensional array. Later it gets an estimate of the probablities and predicts the\n\tlabel for which the value is the highest\t\"\"\"\t\n\t\n\tdef predict_label(self, xtest):\n\t\tnumber_of_testing_samples = len(xtest)\n\t\tytest = np.zeros((number_of_testing_samples))\n\t\tPDF = np.zeros((number_of_testing_samples, self.number_of_attributes, self.number_of_labels), float)\n\t\tself.intermediate_array = np.zeros((number_of_testing_samples, self.number_of_labels), float)\n\t\tfor k in range(0, number_of_testing_samples):\t\t\n\t\t\tfor i in range(0, self.number_of_attributes):\n\t\t\t\tfor j in range(0, self.number_of_labels):\n\t\t\t\t\tPDF[k][i][j] = self.calculatePDF(xtest[k][i], self.Accumulator[i][j][0], self.Accumulator[i][j][1])\n\t\tfor l in range(0, number_of_testing_samples):\n\t\t\tfor m in range(0, self.number_of_labels):\n\t\t\t\tself.intermediate_array[l][m] = self.product([PDF[l][s][m] for s in range(0, self.number_of_attributes)])\n\t\tfor n in range(0, number_of_testing_samples):\n\t\t\tmaximum_index = 0\n\t\t\tmaximum_value = self.intermediate_array[n][0]\t\n\t\t\tfor p in range(0, self.number_of_labels):\n\t\t\t\tif(self.intermediate_array[n][p] > maximum_value):\n\t\t\t\t\tmaximum_value = self.intermediate_array[n][p]\n\t\t\t\t\tmaximum_index = p\n\t\t\tytest[n] = int(self.unique_labels[maximum_index])\n\t\treturn ytest\n\n\t\"\"\" calculates the probability distribution function for a given distribution at x with Mean and Standard_Deviation known\n\tIt is necessary to estimate the probabilities of a sample belonging to a label \t\"\"\" \n\t\n\tdef calculatePDF(self, x, Mean, Standard_Deviation):\n\t\tVariance = float(Standard_Deviation)**2 \n\t\tPi = 3.14159\n\t\tDenominator = (2*Pi*Variance)**.5\n\t\tNumerator = 2.71828**(-(float(x)-float(Mean))**2/(2*Variance))\n\t\treturn Numerator/Denominator\n\n\t\"\"\" calculates the mean given an array\t\"\"\"\n\t\n\tdef mean(self, array):\n\t\tlength = len(array)\n\t\tmean_sum = 0\n\t\tfor i in range(0, length):\n\t\t\tmean_sum+=array[i]\t\t\n\t\treturn mean_sum/length\n\t\n\t\"\"\" calculates the standardDeviation given an array and mean . I later moved on to numpy's std method for performance \"\"\"\n\n\tdef standardDeviation(self, array, temp_mean):\n\t\tlength = len(array)\n\t\tsquare_array = []\n\t\tfor i in range(0, length):\n\t\t\tsquare_array.append(array[i]**2) \n\t\treturn ((self.mean(square_array) - ((temp_mean)**2)**0.5))\n\n\t\"\"\" calculates the product of all the elements in the array \"\"\"\n\tdef product(self, array):\n\t\tresult = 1.0\n\t\tfor i in range(0, len(array)):\n\t\t\tresult = result * float(array[i])\n\t\treturn result\n","repo_name":"chaithuzz2/Star-Quasar-Naive-Bayes","sub_path":"Naive_Bayes.py","file_name":"Naive_Bayes.py","file_ext":"py","file_size_in_byte":4364,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"8296366762","text":"from operator import itemgetter\nfrom typing import Optional, Type, Union\n\nfrom pydantic import parse_obj_as\n\nfrom src.models.movie import FIELDS_FOR_SEARCH, Movie, Person\n\n\ndef get_movies_sorting_for_elastic(sort_field: str) -> dict:\n return {\n \"sort\": {\n \"imdb_rating\": {\n \"order\": \"asc\" if sort_field == \"imdb_rating\" else \"desc\"\n }\n }\n }\n\n\ndef get_genres_filter_for_elastic(genres: list[str]) -> dict:\n should = [{\"match\": {\"genres.id\": genre} for genre in genres}]\n return {\n \"query\": {\n \"nested\": {\"path\": \"genres\", \"query\": {\"bool\": {\"should\": should}}}\n }\n }\n\n\ndef get_search_body_for_movies(\n query: str, fields_for_search: Optional[list[str]] = None\n) -> dict:\n if fields_for_search is None:\n fields_for_search = FIELDS_FOR_SEARCH\n return {\n \"query\": {\"multi_match\": {\"query\": query, \"fields\": fields_for_search}}\n }\n\n\ndef parse_objects(doc: dict, schema: Type[Union[Movie, Person]]) -> list:\n if doc and doc.get(\"hits\"):\n return parse_obj_as(\n list[schema],\n list(map(itemgetter(\"_source\"), doc[\"hits\"].get(\"hits\", [])))\n )\n return []\n","repo_name":"anderskate/Fast_API_sprint_1","sub_path":"src/utils/utils.py","file_name":"utils.py","file_ext":"py","file_size_in_byte":1204,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"43196346060","text":"import os\nimport re\n\n\ndef total_number(logs):\n return sum(1 for line in logs)\n\n\ndef check_by_type(logs):\n types = {}\n for line in logs:\n a = line.split()\n if a[5] not in types:\n types[a[5]] = 1\n else:\n types[a[5]] += 1\n return types\n\n\ndef check_by_size(logs):\n top_1 = {}\n lst = [x.rstrip('\\n').split()[0:] for x in logs]\n lst = sorted(lst, key=lambda x: int(x[9]), reverse=True)\n for a in lst:\n a = a[6] + ' ' + a[8] + ' ' + a[9]\n if a not in top_1:\n top_1[a] = 1\n else:\n top_1[a] += 1\n return top_1\n\n\ndef check_by_client(logs):\n top_2 = {}\n for line in logs:\n a = line.split()\n if not re.match(r'4\\d\\d', a[8]):\n continue\n a = a[6] + ' ' + a[8] + ' ' + a[0]\n if a not in top_2:\n top_2[a] = 1\n else:\n top_2[a] += 1\n return top_2\n\n\ndef check_by_redirect(logs):\n top_3 = {}\n for line in logs:\n a = line.split()\n if not re.match(r'3\\d\\d', a[8]):\n continue\n a = a[6] + ' ' + a[8] + ' ' + a[0]\n if a not in top_3:\n top_3[a] = 1\n else:\n top_3[a] += 1\n return top_3\n\n\nif __name__ == \"__main__\":\n print(\"Input directory and file name:\")\n inp = input()\n if not os.path.exists(inp):\n print(\"This file is not exist! Bye...\")\n exit(99)\n f = open(inp, 'r')\n logs = f.readlines()\n f.close()\n if not os.path.exists('./statistick_py.txt'):\n os.system('touch ./statistick_py.txt')\n f = open('./statistick_py.txt', 'w')\n # check total number of requests\n f.write(\"Total number of requests: {num}\\n\\n\".format(num=total_number(logs)))\n # check number of requests by type\n type = check_by_type(logs)\n f.write(\"Number of requests by type:\\nType Number\\n\")\n for k in type:\n f.write(\"{key} {type}\\n\". format(key=k, type=type[k]))\n # top 10 by size\n top = check_by_size(logs)\n f.write(\"\\nTop 10 by size:\\nNumber URL CodeSize Count\\n\")\n count = 1\n for k in top:\n f.write(\"{cnt} {key} {code}\\n\".format(cnt=count, key=k, code=top[k]))\n if count == 10:\n break\n count += 1\n # top 10 by number of requests with client error\n top = check_by_client(logs)\n f.write(\"\\nTop 10 by number of requests with client error:\\nNumber URL CodeIP \"\n \" Count\\n\")\n count = 1\n for k in sorted(top, key=top.get, reverse=True):\n f.write(\"{cnt} {key} {code}\\n\".format(cnt=count, key=k, code=top[k]))\n if count == 10:\n break\n count += 1\n # top 10 by number of requests with redirect\n top = check_by_redirect(logs)\n f.write(\"\\nTop 10 by number of requests with redirect:\\nNumber URL CodeIP \"\n \" Count\\n\")\n count = 1\n for k in sorted(top, key=top.get, reverse=True):\n f.write(\"{cnt} {key} {code}\\n\".format(cnt=count, key=k, code=top[k]))\n if count == 10:\n break\n count += 1\n f.close()\n\n\nclass CheckingLogs(object):\n pass\n","repo_name":"Noname044/2020-1-Atom-QA-Python-O-Akkad","sub_path":"3HW/python_script/check_log.py","file_name":"check_log.py","file_ext":"py","file_size_in_byte":3202,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"17992439477","text":"\"\"\"\n 0.1.0 - Fresh version with the PRM Generator Script.\n\"\"\"\n\napi = 0\nfeature = 1\nbug = 0\n\nmonth = 12\nyear = 2017\n\n__str__ = 'v{:d}.{:d}.{:d} {:d}-{:0d}'.format(api, feature, bug, year, month)\n","repo_name":"soar-telescope/soar_adaptive_module","sub_path":"sam_tools/version.py","file_name":"version.py","file_ext":"py","file_size_in_byte":197,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"2522155407","text":"b = 5.0000000 \na = float(input(\"K: \"))\nv = float(input(\"V: \"))\nr = float(input(\"Round: \"))\ns = float(input(\"Shunt: \"))\ne = float(input(\"External: \"))\nc = v / (s+e)\nprint(c)\nfor a in range (int(b)):\n d = c*a/b\n print(\"KO =\" + str(a) + \" v/s\")\n print(\"Ia = \"+ str(d) + \" A\")\n f = a * (r/60)\n s = f\n f = v - f\n j = f / (2.8+1.2)\n print(str(s) +\" Eb\")\n print(str(j) + \" iA\") \n pin = v * j + v * d\n print(str(pin) +\" W\")\n pout = s * j\n print(str(pout) +\"W\")\n if pout/pin < 1.000000:\n n = pout/pin*100\n else:\n n =\tpin/pout*100\n \n print(\"n \" + str(n))\n\n w = 2*3.14*(r/60)\n t = pout / w\n print(\"w = \" + str(w))\n print(\"rad/s t\"+ str(w))\n print(\"T = \" + str(t) + \" NM \\n \\n\")\n \n","repo_name":"siravijbb/C-work","sub_path":"Motor Calculator/shunt wounded in python.py","file_name":"shunt wounded in python.py","file_ext":"py","file_size_in_byte":853,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"3162364569","text":"\"\"\"Background tasks for handling API requests.\"\"\"\nimport asyncio\nfrom datetime import datetime\nfrom typing import Any, List\nimport aiohttp\n\nfrom sqlalchemy import insert\n\nfrom api.models import UserRequest\nfrom api.utils import CityWeather, WeatherClient\n\n\nclass GetWeatherBackgroundTask:\n \"\"\"Background task to handle weather requests.\"\"\"\n\n def __init__(\n self,\n cities: List[int],\n database: Any,\n weather_client: WeatherClient,\n user_id: int,\n retry_total=3,\n ) -> None:\n \"\"\"Task to get city weather and store it.\n\n Args:\n cities: a list with city ids.\n database: the database session to store the weather data.\n weather_client: the weather client to request for weather data.\n user_id: the user id.\n retry_total: total number of request retries.\n \"\"\"\n self.user_id = user_id\n self.weather_client = weather_client\n self.database = database\n self.cities = cities\n self.retry_total = retry_total\n self._n_coroutines = 0\n self._progress = 0\n self.status = \"Created\"\n\n @property\n def progress(self) -> float:\n \"\"\"Return the task progress.\"\"\"\n if self._n_coroutines > 0:\n return round(self._progress / float(self._n_coroutines) * 100, 2)\n return 0\n\n async def _get_cities_weather(self, cities_id: List[int]) -> List[CityWeather]:\n \"\"\"Request the city weather.\n\n Args:\n cities_id: a list with the cities id.\n\n Returns:\n a list with cities weather\n \"\"\"\n self._n_coroutines = len(cities_id)\n cities_weather: List[CityWeather] = []\n\n async with aiohttp.ClientSession() as session:\n tasks = [self.weather_client.get(session, city_id) for city_id in cities_id]\n\n for task in asyncio.as_completed(tasks):\n weather = await task\n cities_weather.append(weather)\n self._progress += 1\n print(f\"{self._progress} out of {self._n_coroutines}\")\n\n return cities_weather\n\n async def run(self) -> None:\n \"\"\"Run the task.\n\n It will request for city weather and store it in database.\n \"\"\"\n self.status = \"Running\"\n request_time = datetime.utcnow()\n\n # Get cities\n retry, cities_weather, exc = 0, None, None\n while retry < self.retry_total and not cities_weather:\n try:\n cities_weather = await self._get_cities_weather(self.cities)\n except Exception as e:\n retry += 1\n exc = e\n\n if not cities_weather:\n self.status = \"Error\"\n raise exc or Exception(\"Service unavailable\")\n\n # Insert in DB\n await self.database.execute(\n query=insert(UserRequest),\n values={\n \"user_id\": self.user_id,\n \"request_time\": request_time,\n \"data\": [c.to_json() for c in cities_weather],\n },\n )\n self.status = \"Finished\"\n","repo_name":"lccasagrande/open-weather-api","sub_path":"api/tasks.py","file_name":"tasks.py","file_ext":"py","file_size_in_byte":3116,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"46401943738","text":"from boto3.session import Session\nimport numpy as np\nimport cv2\nfrom PIL import Image\nimport io\nimport base64\nimport random\nimport sys\nimport json\nimport requests\n\n\n# SLACK PARAMETERS\nSLACK_USERNAME = \"uptime-robot\"\nSLACK_CHANNEL = \"#uptime_monitor\"\n\n\ndef compare_images(template, testing, delta=0):\n '''\n @template: Template image\n @testing: Testing image (actual screenshot)\n @delta: Max percentage of difference in pixels\n '''\n if template is None or testing is None:\n print(\"[ERROR] Could not read properly the images\")\n return True\n\n if template.shape != testing.shape:\n print(\"[ERROR] Images do not have the same shape\")\n return True\n\n template_gray = cv2.cvtColor(template, cv2.COLOR_RGB2GRAY)\n testing_gray = cv2.cvtColor(testing, cv2.COLOR_RGB2GRAY)\n\n xor = np.bitwise_xor(template_gray, testing_gray)\n ones = cv2.countNonZero(xor)\n pixels = template.shape[1] * template.shape[0]\n\n # If there is at least the same delta difference, the images are different\n result = (ones / pixels) > (delta / 100.0)\n\n return result\n\n\ndef send_to_s3(img, aws_access_key_id, aws_secret_access_key, aws_bucket_data):\n '''\n Sends and store an image in AWS\n @img must be a numpy array\n '''\n try:\n import StringIO\n except:\n from io import StringIO\n\n session = Session(aws_access_key_id=aws_access_key_id,\n aws_secret_access_key=aws_secret_access_key)\n s3 = session.resource(\"s3\")\n\n filename_wo_ext = \"image\"\n filename_ext = \"png\"\n random_number = int(random.getrandbits(32))\n\n file_name = \"image/{0}_{1}.{2}\".format(filename_wo_ext,\n random_number, filename_ext)\n\n # Save image to JPEG\n image = cv2.imencode('.png', img)[1].tobytes()\n\n if sys.version_info[0] < 3:\n\n stream = StringIO.StringIO(image)\n stream.seek(0)\n image = stream.read()\n\n # Update Image to AWS\n s3.Bucket(aws_bucket_data).put_object(\n Key=file_name,\n Body=image,\n ACL=\"public-read\"\n )\n\n image_url = \"https://s3.amazonaws.com/{0}/{1}\".format(\n aws_bucket_data, file_name)\n return image_url\n\n\ndef extract_roi(image, x, y, width, height):\n\n return image[y:y+height, x:x+width]\n\n\ndef b64_to_cv2(image):\n imgdata = base64.b64decode(image)\n buffer = Image.open(io.BytesIO(imgdata))\n return cv2.cvtColor(np.array(buffer), cv2.COLOR_BGR2RGB)\n\n\ndef send_alert(message, check_name, slack_url,\n slack_username=SLACK_USERNAME, slack_channel=SLACK_CHANNEL):\n try:\n # Alert through Slack\n slack_dict = {\"channel\": slack_channel,\n \"username\": slack_username,\n \"text\": \"{} alert\".format(check_name),\n \"attachments\": [{\"fallback\": \"Alert\",\n \"text\": message,\n \"color\": \"#FF0000\"}]}\n\n req = requests.post(slack_url,\n json=slack_dict,\n headers={'content-type': 'application/json'},\n timeout=60)\n # Alert through Twilio\n except Exception as e:\n return {'error': 'slack post failed'}\n\ndef post_ubi_var(token, device=\"checks\", variable=\"check-instance\", value=1):\n try:\n url = \"https://industrial.api.ubidots.com/\"\n url = url + \"api/v1.6/devices/\" + device\n headers = {\"X-Auth-Token\": token, \"Content-Type\": \"application/json\"}\n data = {variable: value}\n response_code = 400\n retries = 0\n\n while (response_code != 200 and retries <= 5):\n req = requests.post(url=url, headers=headers,\n json=data)\n response_code = req.status_code\n if response_code == 200 or response_code == 201:\n return True\n retries += 1\n\n return False\n except Exception as e:\n print(\"[ERROR] {}\".format(e))\n return False\n","repo_name":"jotathebest/websiteTest","sub_path":"websiteTest/utils/tools.py","file_name":"tools.py","file_ext":"py","file_size_in_byte":4032,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"36128928055","text":"def Fibonacci(n):\n # write code here\n if n == 0:\n return 0\n if n == 1:\n return 1\n a = 1\n b = 0\n ret = None\n if n > 1:\n for i in range(n-1):\n ret = a + b\n b = a\n a = ret\n return ret\n\n\nif __name__ == '__main__':\n print(Fibonacci(100))\n","repo_name":"li2ui2/Python_Personal_DEMO","sub_path":"DATA_STRUCTURE/jianzhi_offer/其他/斐波那契数列.py","file_name":"斐波那契数列.py","file_ext":"py","file_size_in_byte":314,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"36096637294","text":"#! /usr/bin/env python3\n\nimport contextlib\nimport os\nimport socket\nimport sys\n\n# ========== Config ===========\nMOSH_SERVER = 'mosh-server'\n# Path to the mosh-server executable.\n\nHARDCODED_SERVER_ADDR = None\n# If the server IP address is fixed and you would like to have it hardcoded,\n# specify it here.\n\nTEST_IPV4_HOST = '8.8.8.8'\n# This address is used when detecting the host address towards the default\n# route. This should be an address not on any local subnet. No actual traffic\n# is sent.\n\n# ==========\n\n\ndef get_default_route_ipv4_address():\n s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\n with contextlib.closing(s):\n s.connect((TEST_IPV4_HOST, 0))\n return s.getsockname()[0]\n\n\ndef main():\n args = sys.argv[1:]\n\n server_addr = HARDCODED_SERVER_ADDR or get_default_route_ipv4_address()\n\n # Replace \"-s\" argument.\n # When invoking mosh without \"--bind-servers\" or explicitly with\n # \"--bind-server=ssh\", mosh-server will be invoked with \"-s\", which tells\n # it to bind to the IP address of the incoming SSH connection. We do not\n # want that, so we will tell mosh-server to bind to the discovered default\n # address instead.\n # This should not prevent other \"--bind-servers\" arguments from working.\n for i, a in enumerate(args):\n if a == '-s':\n args[i:i+1] = ['-i', server_addr]\n break\n\n print('MOSH IP {!s}'.format(server_addr))\n os.execvp(MOSH_SERVER, [MOSH_SERVER] + args)\n\n\nif __name__ == '__main__':\n main()\n","repo_name":"twisteroidambassador/drmosh","sub_path":"dr-mosh-server.py","file_name":"dr-mosh-server.py","file_ext":"py","file_size_in_byte":1514,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"31141684191","text":"import asyncio, aiohttp, aiofiles, re, json, os, shutil, random, logging, argparse\nfrom env import clientid\nfrom typing import Literal\nfrom tqdm.asyncio import tqdm\n\nclass scdl:\n async def extracturls(session: aiohttp.ClientSession, link):\n async with session.get(link) as r:\n rtext = await r.text()\n pattern = r'(\\[\\{\\\"hydratable\\\":\\\"anonymousId\\\",\\\"data\\\":(?:.*?));'\n match = re.findall(pattern, rtext)[0]\n main = json.loads(match)\n data = {}\n isplaylist = False\n for i in main:\n if isinstance(i, dict):\n if i.get('data'):\n if isinstance(i.get('data'), dict):\n if i.get('data').get('tracks'):\n isplaylist = True\n for index, j in enumerate(i['data']['tracks']):\n data[index] = j.get('id')\n data['title'] = i.get('data').get('title')\n logging.debug(data['title'])\n break\n elif i.get('data').get('media'):\n for index, j in enumerate(i['data']['media']['transcodings']):\n data[index] = j\n \n data['title'] = i.get('data').get('title')\n data['user'] = i.get('data').get('user')\n break\n return data, isplaylist\n class novalidformat(Exception):\n def __init__(self, *args: object) -> None:\n super().__init__(*args)\n async def download(link: str, protocol: Literal['hls', 'progressive'] = 'progressive', \n format_audio: Literal['mpeg', 'opus'] = 'mpeg', verbose=False):\n \"\"\"\n link (str): link to a song\n protocol ('hls' or 'progressive') (progressive by default): whether to download segmented version or direct\n format_audio ('mpeg' or 'opus') (mpeg by default): whether to download mpeg encoded (mp3) or opus encoded (ogg) audio\n \"\"\"\n if verbose:\n logging.basicConfig(level=logging.DEBUG, format='%(message)s')\n else:\n logging.basicConfig(level=logging.INFO, format='%(message)s')\n async with aiohttp.ClientSession() as session:\n data, isplaylist = await scdl.extracturls(session, link)\n alldata = []\n if isplaylist:\n ids = [str(x) for x in data.values() if x != 'title']\n chunks, remainder = divmod(len(ids), 10)\n start = 0\n logging.info(f'grabbing info for {len(ids)} songs...')\n for _ in range(chunks):\n\n params = {\n 'ids': ','.join(ids[start:start+10]),\n 'client_id': clientid\n }\n async with session.get('https://api-v2.soundcloud.com/tracks', params=params) as r:\n alldata.append(await r.json())\n start += 10\n if remainder>0:\n params = {\n 'ids': ','.join(ids[start:]),\n 'client_id': clientid\n }\n async with session.get('https://api-v2.soundcloud.com/tracks', params=params) as r:\n alldata.append(await r.json())\n url = None\n params = {\n 'client_id': clientid\n }\n if isplaylist:\n logging.info('downloading playlist...')\n allinfo = {}\n foldername = \"\".join([x for x in data['title'] if x not in '\"\\\\/:*?<>|()'])\n if not os.path.exists(foldername):\n os.mkdir(foldername)\n progress = tqdm(total=len(ids), colour='red')\n for chunk in alldata:\n for medias in chunk:\n exists = False\n for i in os.listdir(foldername):\n if \"\".join([x for x in medias['title'] if x not in '\"\\\\/:*?<>|()']) in i:\n logging.debug(f'{medias[\"title\"]} already in playlist! skipping...')\n progress.update(1)\n exists = True\n break\n if exists:\n continue\n media = medias['media']['transcodings']\n for value in media:\n if value['format'].get('protocol') == protocol and format_audio in value['format'].get('mime_type'):\n url = value.get('url')\n prot = value.get('format').get('protocol')\n async with session.get(url, params=params) as r:\n url = await r.json()\n url = url.get('url')\n break\n if not url:\n logging.info(f'couldnt get right format for {medias[\"title\"]}')\n url = media[0].get('url')\n prot = media[0].get('format').get('protocol')\n async with session.get(url, params=params) as r:\n url = await r.json()\n url = url.get('url')\n filename, data2 = await scdl.downloader(prot, session, url, format_audio, medias, verbose)\n\n try:\n shutil.move(filename, foldername)\n except shutil.Error:\n logging.debug(f'\\noverwritten {filename}...\\n')\n os.remove(os.path.join(foldername, filename))\n shutil.move(filename, foldername)\n allinfo[os.path.join(foldername, filename)] = data2\n progress.update(1)\n progress.close()\n\n return allinfo\n\n\n else:\n for key, value in data.items():\n if isinstance(value, dict):\n if value.get('format'):\n if value['format'].get('protocol') == protocol and format_audio in value['format'].get('mime_type'):\n url = value.get('url')\n async with session.get(url, params=params) as r:\n url = await r.json()\n url = url.get('url')\n break\n if not url:\n raise scdl.novalidformat(f\"no valid format found for settings: {protocol}, {format_audio}\")\n filename, data = await scdl.downloader(protocol, session, url, format_audio, data, verbose)\n return filename, data\n \n\n \n async def downloader(protocol, session: aiohttp.ClientSession, url, format_audio, data, verbose: bool):\n tasks = []\n links = []\n filenames = []\n threads = asyncio.Semaphore(10)\n colours = ['red', 'green', 'yellow', 'blue', 'magenta', 'cyan', 'white', 'black']\n if protocol == 'hls':\n progress = tqdm(total=None, unit='iB', unit_scale=True, colour=random.choice(colours), disable=(not verbose))\n async with session.get(url) as r:\n manifestdata = await r.text()\n for i in manifestdata.split('\\n'):\n if i.startswith('https'):\n links.append(i)\n for index, link in enumerate(links):\n filename = f'segmenta{index}'+ ('.mp3' if format_audio == 'mpeg' else '.ogg')\n filenames.append(filename)\n tasks.append(scdl.downloadworker(link, filename, session, threads, progress))\n await asyncio.gather(*tasks)\n filename = data.get('title') + ('.mp3' if format_audio == 'mpeg' else '.ogg')\n filename = \"\".join([x for x in filename if x not in '\"\\\\/:*?<>|()'])\n filenames = sorted(filenames, key = lambda x: int(x.split('a')[1].split('.')[0]))\n async with aiofiles.open(filename, 'wb') as f1:\n for file in filenames:\n async with aiofiles.open(file, 'rb') as f2:\n await f1.write(await f2.read())\n os.remove(file)\n progress.close()\n else:\n async with session.get(url) as r:\n progress = tqdm(total=int(r.headers.get('content-length')), unit='iB', unit_scale=True, colour=random.choice(colours), disable=(not verbose))\n filename = data.get('title') + ('.mp3' if format_audio == 'mpeg' else '.ogg')\n filename = \"\".join([x for x in filename if x not in '\"\\\\/:*?<>|()'])\n async with aiofiles.open(filename, 'wb') as f1:\n while True:\n chunk = await r.content.read(1024)\n if not chunk:\n break\n await f1.write(chunk)\n progress.update(len(chunk))\n progress.close()\n return filename, data\n \n async def downloadworker(link: str, filename: str, session: aiohttp.ClientSession, \n threads: asyncio.Semaphore, progress: tqdm):\n async with threads:\n async with session.get(link) as r:\n async with aiofiles.open(filename, 'wb') as f1:\n while True:\n chunk = await r.content.read(1024)\n if not chunk:\n break\n await f1.write(chunk)\n progress.update(len(chunk))\n \nif __name__ == \"__main__\":\n parser = argparse.ArgumentParser(description='download soundcloud songs and playlists')\n parser.add_argument(\"link\", help='link to the song/playlist')\n parser.add_argument(\"--protocol\", \"-p\", choices=['hls', 'progressive'], default='progressive', help='which protocol to use to download (hls is fragmented, progressive is direct link)')\n parser.add_argument(\"--format-audio\", \"-f\", choices=['mpeg', 'opus'], default = 'mpeg', help='which format to download, mpeg being mp3, opus being ogg')\n parser.add_argument(\"--verbose\", \"-v\", action=\"store_true\", help=\"whether to directly show downloads happening and whatnot (if off only shows progress of downloading every song in playlist)\")\n args = parser.parse_args()\n asyncio.run(scdl.download(args.link, args.protocol, args.format_audio, args.verbose))","repo_name":"Hecker5556/soundclouddownloader","sub_path":"scdl.py","file_name":"scdl.py","file_ext":"py","file_size_in_byte":10808,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"25221510505","text":"from spaceone.api.inventory.plugin import collector_pb2\nfrom spaceone.core.pygrpc.message_type import *\n\n__all__ = ['PluginInfo', 'ResourceInfo']\n\n\ndef PluginInfo(plugin_data):\n info = {\n 'metadata': change_struct_type(plugin_data['metadata']),\n }\n\n return collector_pb2.PluginInfo(**info)\n\n\ndef ResourceInfo(resource_data):\n info = {\n 'state': resource_data['state'],\n 'message': resource_data.get('message', ''),\n 'resource_type': resource_data['resource_type'],\n 'match_rules': change_struct_type(resource_data.get('match_rules')),\n 'resource': change_struct_type(resource_data.get('resource'))\n }\n\n return collector_pb2.ResourceInfo(**info)\n","repo_name":"cloudforet-io/plugin-aws-config-inven-collector","sub_path":"src/cloudforet/plugin/info/collector_info.py","file_name":"collector_info.py","file_ext":"py","file_size_in_byte":705,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"74801409362","text":"from .const import LAST_DATA, CHANGE_ACTION, NOTE_ACTION, CREATE_GROUP_ACTION, CLEAR_GROUP_ACTION\nfrom .model import Note\nfrom .process import create_group, build_menu\nfrom .helpers import clear_last\nfrom .internalization import get_message\n\n\ndef change_action(update, context, group):\n text = update.message.text\n data = context.user_data.get(LAST_DATA)\n\n note = Note.get_by_id(data.get('note_id'))\n note.message = text\n note.save()\n\n clear_last(context)\n update.message.reply_text(get_message(update, context, 'Changes are saved'),\n reply_markup=build_menu(update, context))\n\n\ndef note_action(update, context, group):\n if check_group_not_null(update, context, group):\n data = context.user_data.get(LAST_DATA)\n Note.create(group=group.id, message=data.get('note'))\n update.message.reply_text(get_message(update, context, 'Note is saved'),\n reply_markup=build_menu(update, context))\n clear_last(context)\n\n\ndef create_group_action(update, context, group):\n text = update.message.text\n clear_last(context)\n create_group(update, context, text)\n\n\ndef check_group_not_null(update, context, group):\n if not group:\n update.message.reply_text('Unknown category', reply_markup=build_menu(update, context))\n return False\n return True\n\n\ndef clear_group_action(update, context, group):\n clear_last(context)\n if check_group_not_null(update, context, group):\n Note.delete_group(group.id)\n update.message.reply_text('Category cleared', reply_markup=build_menu(update, context))\n\n\nACTION_MAPPING = {\n CHANGE_ACTION: change_action,\n NOTE_ACTION: note_action,\n CREATE_GROUP_ACTION: create_group_action,\n CLEAR_GROUP_ACTION: clear_group_action\n}\n","repo_name":"FriendlyEvil/SimpleNoteBot","sub_path":"src/actions.py","file_name":"actions.py","file_ext":"py","file_size_in_byte":1798,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"71583027601","text":"from typing import Iterable, Callable\nfrom itertools import filterfalse\n\n\ndef my_filterfalse(func: Callable, iterable: Iterable) -> None:\n\n def default_func(x):\n\n return x\n\n func = default_func if func is None else func\n\n for i in iterable:\n if not func(i):\n yield i\n\n\nif __name__ == '__main__':\n input_data = input('Пожалуйста введите целые числа разделяя их пробелами: ')\n\n try:\n source_list = tuple(map(int, input_data.split()))\n except ValueError:\n print('Неверно введенные данные')\n exit(1)\n\n print('itertools drophile', list(filterfalse(lambda x: source_list.count(x) > 1, source_list)))\n print('custom drophile', list(my_filterfalse(lambda x: source_list.count(x) > 1, source_list)))\n","repo_name":"LexCruger/geekPython","sub_path":"leson 4/Q4.py","file_name":"Q4.py","file_ext":"py","file_size_in_byte":829,"program_lang":"python","lang":"ru","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"2147753059","text":"# -*- coding: utf-8 -*-\n\"\"\"\nThree-dimensional transport in a uniform flow field \nThis is based on MT3DMS Example problem 7 available here: https://github.com/modflowpy/flopy/blob/develop/examples/Notebooks/flopy3_MT3DMS_examples.ipynb\n\nCreated on Fri May 22 16:50:00 2020\n\n@author: Revised by Christopher Zahasky to add timing and much more commenting\n\n\"\"\"\n\n# All packages called by functions should be imported\nimport sys\nimport os\nimport numpy as np\nfrom scipy import integrate\nimport time\nimport matplotlib.pyplot as plt\n\n# run installed version of flopy or add local path\ntry:\n import flopy\nexcept:\n fpth = os.path.abspath(os.path.join('..', '..'))\n sys.path.append(fpth)\n import flopy\n\n# # uncomment if you want the information about numpy, matplotlib, and flopy printed \n# # print(sys.version)\n# # print('numpy version: {}'.format(np.__version__))\n# # print('matplotlib version: {}'.format(mpl.__version__))\n# # print('flopy version: {}'.format(flopy.__version__))\n\n\ndef mt3d_pulse_injection_sim(dirname, model_ws, raw_hk, prsity_field, grid_size, \n ndummy_in, perlen_mt, nprs, mixelm, exe_name_mf, exe_name_mt):\n # # Model workspace and new sub-directory\n # model_ws = os.path.join(workdir, dirname)\n \n # Call function and time it\n start = time.time() # start a timer\n# =============================================================================\n# UNIT INFORMATION\n# =============================================================================\n # units must be set for both MODFLOW and MT3D, they have different variable names for each\n # time units (itmuni in MODFLOW discretization package)\n # 1 = seconds, 2 = minutes, 3 = hours, 4 = days, 5 = years\n itmuni = 2 # MODFLOW length units\n mt_tunit = 'M' # MT3D units\n # length units (lenuniint in MODFLOW discretization package)\n # 0 = undefined, 1 = feet, 2 = meters, 3 = centimeters\n lenuni = 3 # MODFLOW units\n mt_lunit = 'CM' # MT3D units\n \n# =============================================================================\n# STRESS PERIOD INFO\n# =============================================================================\n perlen_mf = [np.sum(perlen_mt)]\n # number of stress periods (MF input), calculated from period length input\n nper_mf = len(perlen_mf)\n # number of stress periods (MT input), calculated from period length input\n nper = len(perlen_mt)\n \n# =============================================================================\n# MODEL DIMENSION AND MATERIAL PROPERTY INFORMATION\n# =============================================================================\n # Make model dimensions the same size as the hydraulic conductivity field input \n # NOTE: that the there are two additional columns added as dummy slices (representing coreholder faces)\n hk_size = raw_hk.shape\n # determine dummy slice perm based on maximum hydraulic conductivity\n dummy_slice_hk = raw_hk.max()*10\n # define area with hk values above zero\n core_mask = np.ones((hk_size[0], hk_size[1]))\n core_mask = np.multiply(core_mask, raw_hk[:,:,0])\n core_mask[np.nonzero(core_mask)] = 1\n # define hk in cells with nonzero hk to be equal to 10x the max hk\n # This represents the 'coreholder' slices\n dummy_ch = core_mask[:,:, np.newaxis]*dummy_slice_hk\n dummy_ch_por = core_mask[:,:, np.newaxis]*0.15\n \n # Additional dummy inlet to replicate imperfect boundary\n dummy_slice_in =raw_hk[:,:,0]*core_mask\n dummy_slice_in = dummy_slice_in.reshape(hk_size[0], hk_size[1], 1)\n # concantenate dummy slice on hydraulic conductivity array\n ndummy_in = int(ndummy_in)\n if ndummy_in > 0:\n dummy_block = np.repeat(dummy_slice_in, ndummy_in, axis=2)\n hk = np.concatenate((dummy_ch, dummy_block, raw_hk, dummy_ch), axis=2)\n \n # do the same with porosity slices\n dummy_slice_in =prsity_field[:,:,0]*core_mask\n dummy_slice_in = dummy_slice_in.reshape(hk_size[0], hk_size[1], 1)\n dummy_block = np.repeat(dummy_slice_in, ndummy_in, axis=2)\n prsity = np.concatenate((dummy_ch_por, dummy_block, prsity_field, dummy_ch_por), axis=2)\n \n else:\n hk = np.concatenate((dummy_ch, raw_hk, dummy_ch), axis=2)\n prsity = np.concatenate((dummy_ch_por, prsity_field, dummy_ch_por), axis=2)\n \n # hk = raw_hk\n # Model information (true in all models called by 'p01')\n nlay = int(hk_size[0]) # number of layers / grid cells\n nrow = int(hk_size[1]) # number of rows / grid cells\n # ncol = hk_size[2]+2+ndummy_in # number of columns (along to axis of core)\n ncol = int(hk_size[2]+2+ndummy_in) # number of columns (along to axis of core)\n # ncol = hk_size[2] # number of columns (along to axis of core)\n delv = grid_size[0] # grid size in direction of Lx (nlay)\n delr = grid_size[1] # grid size in direction of Ly (nrow)\n delc = grid_size[2] # grid size in direction of Lz (ncol)\n \n laytyp = 0\n # cell elevations are specified in variable BOTM. A flat layer is indicated\n # by simply specifying the same value for the bottom elevation of all cells in the layer\n botm = [-delv * k for k in range(1, nlay + 1)]\n \n # ADDITIONAL MATERIAL PROPERTIES\n # prsity = 0.25 # porosity. float or array of floats (nlay, nrow, ncol)\n prsity = prsity\n al = 0.1 # longitudental dispersivity\n trpt = 0.3 # ratio of horizontal transverse dispersivity to longitudenal dispersivity\n trpv = 0.3 # ratio of vertical transverse dispersivity to longitudenal dispersivity\n \n# =============================================================================\n# BOUNDARY AND INTIAL CONDITIONS\n# =============================================================================\n # backpressure, give this in kPa for conversion\n bp_kpa = 70\n # Injection rate in defined units \n injection_rate = 2 # [cm^3/min]\n \n # Initial concentration (MT input)\n c0 = 0.\n # Stress period 2 concentration\n c1 = 1.0\n \n # Core radius\n core_radius = 2.54 # [cm]\n # Calculation of core area\n core_area = 3.1415*core_radius**2\n # Calculation of mask area\n mask_area = np.sum(core_mask)*grid_size[0]*grid_size[1]\n # total specific discharge or injection flux (rate/area)\n # q = injection_rate*(mask_area/core_area)/np.sum(core_mask)\n # scale injection rate locally by inlet permeability\n q_total = injection_rate*(mask_area/core_area)\n # q_total = injection_rate/core_area\n q = q_total/np.sum(dummy_slice_in)\n \n # MODFLOW head boundary conditions, <0 = specified head, 0 = no flow, >0 variable head\n # ibound = np.ones((nlay, nrow, ncol), dtype=np.int)\n ibound = np.repeat(core_mask[:, :, np.newaxis], ncol, axis=2)\n \n # inlet conditions (currently set with well so inlet is zero)\n # ibound[:, :, 0] = ibound[:, :, -1]*-1\n # outlet conditions\n # ibound[5:15, 5:15, -1] = -1\n ibound[:, :, -1] = ibound[:, :, -1]*-1\n \n # MODFLOW constant initial head conditions\n strt = np.zeros((nlay, nrow, ncol), dtype=float)\n # Lx = (hk_size[2]*delc)\n # Q = injection_rate/(core_area)\n # geo_mean_k = np.exp(np.sum(np.log(hk[hk>0]))/len(hk[hk>0]))\n # h1 = Q * Lx/geo_mean_k\n # print(h1)\n \n # convert backpressure to head units\n if lenuni == 3: # centimeters\n hout = bp_kpa*1000/(1000*9.81)*100 \n else: # elseif meters\n if lenuni == 2: \n hout = bp_kpa*1000/(1000*9.81)\n # assign outlet pressure as head converted from 'bp_kpa' input variable\n # index the inlet cell\n # strt[:, :, 0] = h1+hout\n strt[:, :, -1] = core_mask*hout\n # strt[:, :, -1] = hout\n \n # Stress period well data for MODFLOW. Each well is defined through defintition\n # of layer (int), row (int), column (int), flux (float). The first number corresponds to the stress period\n # Example for 1 stress period: spd_mf = {0:[[0, 0, 1, q],[0, 5, 1, q]]}\n well_info = np.zeros((int(np.sum(core_mask)), 4), dtype=float)\n # Nested loop to define every inlet face grid cell as a well\n index_n = 0\n for layer in range(0, nlay):\n for row in range(0, nrow):\n # index_n = layer*nrow + row\n # index_n +=1\n # print(index_n)\n if core_mask[layer, row] > 0:\n well_info[index_n] = [layer, row, 0, q*dummy_slice_in[layer,row]] \n index_n +=1\n \n \n # geo_mean_k = np.exp(np.sum(np.log(hk[hk>0]))/len(hk[hk>0]))\n \n # # MODFLOW head boundary conditions, <0 = specified head, 0 = no flow, >0 variable head\n # # ibound = np.ones((nlay, nrow, ncol), dtype=np.int)\n # ibound = np.repeat(core_mask[:, :, np.newaxis], ncol, axis=2)\n \n # # inlet conditions (currently set with well so inlet is zero)\n # ibound[:, :, 0] = ibound[:, :, -1]*-1\n # # outlet conditions\n # # ibound[5:15, 5:15, -1] = -1\n # ibound[:, :, -1] = ibound[:, :, -1]*-1\n \n # # MODFLOW constant initial head conditions\n # strt = np.zeros((nlay, nrow, ncol), dtype=np.float)\n # Lx = (hk_size[2]*delc)\n # q = injection_rate/(core_area)\n # h1 = q * Lx/geo_mean_k\n # print(h1)\n \n # # convert backpressure to head units\n # if lenuni == 3: # centimeters\n # hout = bp_kpa*1000/(1000*9.81)*100 \n # else: # elseif meters\n # if lenuni == 2: \n # hout = bp_kpa*1000/(1000*9.81)\n # # assign outlet pressure as head converted from 'bp_kpa' input variable\n # # index the inlet cell\n # strt[:, :, 0] = h1+hout\n # # strt[:, :, -1] = core_mask*hout\n # strt[:, :, -1] = hout\n \n # # Stress period well data for MODFLOW. Each well is defined through defintition\n # # of layer (int), row (int), column (int), flux (float). The first number corresponds to the stress period\n # # Example for 1 stress period: spd_mf = {0:[[0, 0, 1, q],[0, 5, 1, q]]}\n # well_info = np.zeros((int(np.sum(core_mask)), 4), dtype=np.float)\n # # Nested loop to define every inlet face grid cell as a well\n # index_n = 0\n # for layer in range(0, nlay):\n # for row in range(0, nrow):\n # # index_n = layer*nrow + row\n # # index_n +=1\n # # print(index_n)\n # if core_mask[layer, row] > 0:\n # well_info[index_n] = [layer, row, 0, q] \n # index_n +=1\n \n # Now insert well information into stress period data \n # *** TO DO: Generalize this for multiple stress periods\n # This has the form: spd_mf = {0:[[0, 0, 0, q],[0, 5, 1, q]], 1:[[0, 1, 1, q]]}\n spd_mf={0:well_info}\n \n # MT3D stress period data, note that the indices between 'spd_mt' must exist in 'spd_mf' \n # This is used as input for the source and sink mixing package\n # Itype is an integer indicating the type of point source, 2=well, 3=drain, -1=constant concentration\n itype = 2\n cwell_info = np.zeros((int(np.sum(core_mask)), 5), dtype=float)\n # cwell_info = np.zeros((nrow*nlay, 5), dtype=np.float)\n # Nested loop to define every inlet face grid cell as a well\n index_n = 0\n for layer in range(0, nlay):\n for row in range(0, nrow):\n # index_n = layer*nrow + row\n if core_mask[layer, row] > 0:\n cwell_info[index_n] = [layer, row, 0, c0, itype] \n index_n +=1\n # cwell_info[index_n] = [layer, row, 0, c0, itype]\n \n # Second stress period \n cwell_info2 = cwell_info.copy() \n cwell_info2[:,3] = c1 \n # Second stress period \n cwell_info3 = cwell_info.copy() \n cwell_info3[:,3] = c0 \n # Now apply stress period info \n spd_mt = {0:cwell_info, 1:cwell_info2, 2:cwell_info3}\n\n # Concentration boundary conditions, this is neccessary to indicate \n # inactive concentration cells outside of the more\n # If icbund = 0, the cell is an inactive concentration cell; \n # If icbund < 0, the cell is a constant-concentration cell; \n # If icbund > 0, the cell is an active concentration cell where the \n # concentration value will be calculated. (default is 1).\n icbund = np.repeat(core_mask[:, :, np.newaxis], ncol, axis=2)\n # icbund[0, 0, 0] = -1\n # Initial concentration conditions, currently set to zero everywhere\n # sconc = np.zeros((nlay, nrow, ncol), dtype=np.float)\n # sconc[0, 0, 0] = c0\n \n# =============================================================================\n# MT3D OUTPUT CONTROL \n# =============================================================================\n # nprs (int): A flag indicating (i) the frequency of the output and (ii) whether \n # the output frequency is specified in terms of total elapsed simulation \n # time or the transport step number. If nprs > 0 results will be saved at \n # the times as specified in timprs; if nprs = 0, results will not be saved \n # except at the end of simulation; if NPRS < 0, simulation results will be \n # saved whenever the number of transport steps is an even multiple of nprs. (default is 0).\n # nprs = 20\n \n # timprs (list of float): The total elapsed time at which the simulation \n # results are saved. The number of entries in timprs must equal nprs. (default is None).\n timprs = np.linspace(0, np.sum(perlen_mt), nprs, endpoint=False)\n # obs (array of int): An array with the cell indices (layer, row, column) \n # for which the concentration is to be printed at every transport step. \n # (default is None). obs indices must be entered as zero-based numbers as \n # a 1 is added to them before writing to the btn file.\n # nprobs (int): An integer indicating how frequently the concentration at \n # the specified observation points should be saved. (default is 1).\n \n# =============================================================================\n# START CALLING MODFLOW PACKAGES AND RUN MODEL\n# =============================================================================\n # Start callingwriting files\n modelname_mf = dirname + '_mf'\n # same as 1D model\n mf = flopy.modflow.Modflow(modelname=modelname_mf, model_ws=model_ws, exe_name=exe_name_mf)\n dis = flopy.modflow.ModflowDis(mf, nlay=nlay, nrow=nrow, ncol=ncol, nper=nper_mf,\n delr=delr, delc=delc, top=0., botm=botm,\n perlen=perlen_mf, itmuni=itmuni, lenuni=lenuni)\n \n # MODFLOW basic package class\n bas = flopy.modflow.ModflowBas(mf, ibound=ibound, strt=strt)\n # MODFLOW layer properties flow package class\n lpf = flopy.modflow.ModflowLpf(mf, hk=hk, laytyp=laytyp)\n # MODFLOW well package class\n wel = flopy.modflow.ModflowWel(mf, stress_period_data=spd_mf)\n # MODFLOW preconditioned conjugate-gradient package class\n pcg = flopy.modflow.ModflowPcg(mf, mxiter=100, rclose=1e-5, relax=0.97)\n # MODFLOW Link-MT3DMS Package Class (this is the package for solute transport)\n lmt = flopy.modflow.ModflowLmt(mf)\n # # MODFLOW output control package\n oc = flopy.modflow.ModflowOc(mf)\n \n mf.write_input()\n # RUN MODFLOW MODEL, set to silent=False to see output in terminal\n mf.run_model(silent=True)\n \n# =============================================================================\n# START CALLING MT3D PACKAGES AND RUN MODEL\n# =============================================================================\n # RUN MT3dms solute tranport \n modelname_mt = dirname + '_mt'\n\n # MT3DMS Model Class\n # Input: modelname = 'string', namefile_ext = 'string' (Extension for the namefile (the default is 'nam'))\n # modflowmodelflopy.modflow.mf.Modflow = This is a flopy Modflow model object upon which this Mt3dms model is based. (the default is None)\n mt = flopy.mt3d.Mt3dms(modelname=modelname_mt, model_ws=model_ws, \n exe_name=exe_name_mt, modflowmodel=mf)\n \n # Basic transport package class\n btn = flopy.mt3d.Mt3dBtn(mt, icbund=icbund, prsity=prsity, sconc=0, \n tunit=mt_tunit, lunit=mt_lunit, nper=nper, perlen=perlen_mt, \n nprs=nprs, timprs=timprs)\n \n # mixelm is an integer flag for the advection solution option, \n # mixelm = 0 is the standard finite difference method with upstream or \n # central in space weighting.\n # mixelm = 1 is the forward tracking method of characteristics, this seems to result in minimal numerical dispersion.\n # mixelm = 2 is the backward tracking\n # mixelm = 3 is the hybrid method\n # mixelm = -1 is the third-ord TVD scheme (ULTIMATE)\n adv = flopy.mt3d.Mt3dAdv(mt, mixelm=mixelm)\n\n dsp = flopy.mt3d.Mt3dDsp(mt, al=al, trpt=trpt)\n # Reactions package (optional)\n # rct = flopy.mt3d.Mt3dRct(mt, isothm=1, ireact=1, igetsc=0, rhob=rhob, sp1=kd, \n # rc1=lambda1, rc2=lambda1)\n # source and sink mixing package\n ssm = flopy.mt3d.Mt3dSsm(mt, stress_period_data=spd_mt)\n gcg = flopy.mt3d.Mt3dGcg(mt)\n \n mt.write_input()\n fname = os.path.join(model_ws, 'MT3D001.UCN')\n if os.path.isfile(fname):\n os.remove(fname)\n mt.run_model(silent=True)\n \n # Extract concentration information\n fname = os.path.join(model_ws, 'MT3D001.UCN')\n ucnobj = flopy.utils.UcnFile(fname)\n timearray = ucnobj.get_times()\n # print(times)\n conc = ucnobj.get_alldata()\n \n # Extract head information\n fname = os.path.join(model_ws, modelname_mf+'.hds')\n hdobj = flopy.utils.HeadFile(fname)\n heads = hdobj.get_data()\n \n # set inactive cell pressures to zero, by default inactive cells have a pressure of -999\n # heads[heads < -990] = 0\n \n # convert heads to pascals\n if lenuni == 3: # centimeters\n pressures = heads/100*(1000*9.81) \n else: # elseif meters\n if lenuni == 2: \n pressures = heads*(1000*9.81)\n \n \n # crop off extra concentration slices\n conc = conc[:,:,:,ndummy_in+1:-1]\n \n # calculate pressure drop\n # crop off extra pressure slices\n # pressures = pressures[:,:,ndummy_in:-2] # commented out since not returned\n # calculate \n p_inlet = pressures[:, :, ndummy_in+1]*core_mask\n p_inlet = np.mean(p_inlet[p_inlet>1])\n # print(p_inlet)\n p_outlet = pressures[:, :, -1]*core_mask\n p_outlet = np.mean(p_outlet[p_outlet>1])\n dp = p_inlet-p_outlet\n # print('Pressure drop: '+ str(dp/1000) + ' kPa')\n \n # calculate mean permeability from pressure drop\n # water viscosity\n mu_water = 0.00089 # Pa.s\n L = hk_size[2]*delc\n km2_mean = (q_total/mask_area)*L*mu_water/dp /(60*100**2)\n \n print('Core average perm: '+ str(km2_mean/9.869233E-13*1000) + ' mD')\n \n # Option to plot and calculate geometric mean to double check that core average perm in close\n geo_mean_K = np.exp(np.sum(np.log(raw_hk[raw_hk>0]))/len(raw_hk[raw_hk>0]))\n geo_mean_km2 = geo_mean_K/(1000*9.81*100*60/8.9E-4)\n print('Geometric mean perm: ' + str(geo_mean_km2/9.869233E-13*1000) + ' mD')\n\n # Print final run time\n end_time = time.time() # end timer\n # print('Model run time: ', end - start) # show run time\n print(f\"Model run time: {end_time - start:0.4f} seconds\")\n \n return mf, mt, conc, timearray, km2_mean\n\n\n# Much faster quantile calculation \ndef quantile_calc(btc_1d, timearray, quantile):\n # calculate cumulative amount of solute passing by location\n M0i = integrate.cumtrapz(btc_1d, timearray)\n # normalize by total to get CDF\n quant = M0i/M0i[-1]\n # calculate midtimes\n mid_time = (timearray[1:] + timearray[:-1]) / 2.0\n \n # now linearly interpolate to find quantile\n gind = np.argmax(quant > quantile)\n m = (quant[gind] - quant[gind-1])/(mid_time[gind] - mid_time[gind-1])\n b = quant[gind-1] - m*mid_time[gind-1]\n \n tau = (quantile-b)/m\n \n # plot check\n # xp = [mid_time[gind-1], mid_time[gind]]\n # plt.plot(mid_time, quant, '-o')\n # plt.plot(xp, m*xp+b, '-r')\n # plt.plot(tau, quantile, 'ok')\n return tau\n \n\n# Function to calculate the quantile arrival time map\ndef flopy_arrival_map_function(conc, timearray, grid_size, quantile):\n # determine the size of the data\n conc_size = conc.shape\n \n # define area with hk values above zero\n core_mask = np.copy(conc[0,:,:,0])\n core_mask[core_mask<2] = 1\n core_mask[core_mask>2] = 0\n \n # MT3D sets the values of all concentrations in cells outside of the model \n # to 1E30, this sets them to 0\n conc[conc>2]=0\n \n # sum of slice concentrations for calculating inlet and outlet breakthrough\n oned = np.nansum(np.nansum(conc, 1), 1)\n \n # arrival time calculation in inlet slice\n tau_in = quantile_calc(oned[:,0], timearray, quantile)\n \n # arrival time calculation in outlet slice\n tau_out = quantile_calc(oned[:,-1], timearray, quantile)\n\n # core length\n model_length = grid_size[2]*conc_size[3]\n # array of grid cell centers before interpolation\n z_coord_model = np.arange(grid_size[2]/2, model_length, grid_size[2])\n \n # Preallocate arrival time array\n at_array = np.zeros((conc_size[1], conc_size[2], conc_size[3]), dtype=np.float)\n \n for layer in range(0, conc_size[1]):\n for row in range(0, conc_size[2]):\n for col in range(0, conc_size[3]):\n # Check if outside core\n if core_mask[layer, row] > 0:\n cell_btc = conc[:, layer, row, col]\n # check to make sure tracer is in grid cell\n if cell_btc.sum() > 0:\n # call function to find quantile of interest\n tau_vox = quantile_calc(cell_btc, timearray, quantile)\n if tau_vox > 0:\n at_array[layer, row, col] = tau_vox\n else:\n break # if tau can't be calculated then break the nested for loop and run a different model\n else:\n continue\n break\n else:\n continue\n break\n \n if tau_vox == 0: # these set a flag that is used to regenerate training realization\n at_array = 0 \n at_array_norm = 0 \n at_diff_norm = 0\n \n else:\n # v = (model_length-grid_size[2])/(tau_out - tau_in)\n # print('advection velocity: ' + str(v))\n \n # Normalize arrival times\n at_array_norm = (at_array-tau_in)/(tau_out - tau_in)\n \n # vector of ideal mean arrival time based average v\n at_ideal = z_coord_model/z_coord_model[-1]\n\n # Turn this vector into a matrix so that it can simply be subtracted from\n at_ideal_array = np.tile(at_ideal, (conc_size[1], conc_size[2], 1))\n\n # Arrival time difference map\n at_diff_norm = (at_ideal_array - at_array_norm)\n \n # Replace values outside model with zeros\n for col in range(0, conc_size[3]):\n at_array[:,:,col] = np.multiply(at_array[:,:,col], core_mask)\n at_array_norm[:,:,col] = np.multiply(at_array_norm[:,:,col], core_mask)\n at_diff_norm[:,:,col] = np.multiply(at_diff_norm[:,:,col], core_mask)\n\n return at_array, at_array_norm, at_diff_norm\n\n\ndef plot_2d(map_data, dx, dy, colorbar_label, cmap):\n # fontsize\n fs = 18\n hfont = {'fontname':'Arial'}\n r, c = np.shape(map_data)\n # Define grid\n # Lx = c * dx # length of model in selected units \n # Ly = r * dy # length of model in selected units\n # x, y = np.mgrid[slice(0, Lx + dx, dx), slice(0, Ly + dy, dy)]\n \n \n x_coord = np.linspace(0, dx*c, c+1)\n y_coord = np.linspace(0, dy*r, r+1)\n \n X, Y = np.meshgrid(x_coord, y_coord)\n # print(slice(0, Ly + dy, dy))\n # print(c)\n # print(slice(0, Lx + dx, dx))\n # print(r)\n \n # fig, ax = plt.figure(figsize=(10, 10) # adjust these numbers to change the size of your figure\n # ax.axis('equal') \n # fig2.add_subplot(1, 1, 1, aspect='equal')\n # Use 'pcolor' function to plot 2d map of concentration\n # Note that we are flipping map_data and the yaxis to so that y increases downward\n plt.figure(figsize=(12, 4), dpi=200)\n plt.pcolormesh(X, Y, map_data, cmap=cmap, shading = 'nearest', edgecolor ='k', linewidth = 0.01)\n plt.gca().set_aspect('equal') \n # add a colorbar\n cbar = plt.colorbar() \n # plt.clim(cmin, cmax) \n # label the colorbar\n cbar.set_label(colorbar_label, fontsize=fs, **hfont)\n # make colorbar font bigger\n cbar.ax.tick_params(labelsize= (fs-2)) \n # make axis fontsize bigger!\n plt.tick_params(axis='both', which='major', labelsize=fs)\n plt.xlim((0, dx*c)) \n plt.ylim((0, dy*r)) \n # Label x-axis\n plt.gca().invert_yaxis()","repo_name":"zahasky/Neural_network_inversion","sub_path":"training_data_generation/flopy_arrival_time_3d_functions.py","file_name":"flopy_arrival_time_3d_functions.py","file_ext":"py","file_size_in_byte":24778,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"3"} +{"seq_id":"24682830015","text":"\"\"\"\n@file src/tex_editor/buttons.py\n@version 1.1\n@author CN\n@author Gudule\n@date jan 2017\n\nProvides buttons for the commands attached to a TeX editor text zone.\n\n\"\"\"\n\nfrom tkinter import Button, Frame, PhotoImage, E, W, S, N\nfrom resources import RESOURCE\n\nFONT_BUTTONS = 'helvetica', 12, 'bold'\n\nclass ButtonPanel(Frame):\n \"\"\"\n @class ButtonPanel\n\n A panel of buttons that can be attached to a text widget that is a subclass\n of SpecialText (to have all the methods needed).\n\n The formatting buttons control which tag is set and which ones automatically\n removed.\n\n @see SpecialText\n \"\"\"\n\n def __init__(self, textwidget, *args, **kwargs):\n super().__init__(*args, **kwargs)\n self._textw = textwidget\n self.grid(row=0,column=0)\n\n self._italic = PhotoImage(file=RESOURCE.italic)\n self._bold = PhotoImage(file=RESOURCE.bold)\n self._underline = PhotoImage(file=RESOURCE.underline)\n self._center = PhotoImage(file=RESOURCE.center)\n self._right = PhotoImage(file=RESOURCE.right)\n self._left = PhotoImage(file=RESOURCE.left)\n\n Button(self,\n font=FONT_BUTTONS,\n width=50, height=50,\n image=self._italic,\n command=lambda: self._textw._add_remove_tags(\"ITAL\", [\"BOLD\", \"FOOTNOTE\", \"SMALLCAPS\"])\n ).grid(row=0, column=0, sticky=E+W+N+S)\n Button(self,\n font=FONT_BUTTONS,\n width=50, height=50,\n image=self._bold,\n command=lambda: self._textw._add_remove_tags(\"BOLD\", [\"ITAL\", \"FOOTNOTE\", \"SMALLCAPS\"])\n ).grid(row=1, column=0, sticky=E+W+N+S)\n Button(self,\n font=FONT_BUTTONS,\n width=50, height=50,\n image=self._underline,\n command=lambda: self._textw._add_remove_tags(\"UNDERLINE\", [])\n ).grid(row=2, column=0, sticky=E+W+N+S)\n\n\n Button(self, font=FONT_BUTTONS,\n text=\"œ\",\n command=lambda: self._textw.insert_text(\"œ\")\n ).grid(row=3, column=0, sticky=E+W+N+S)\n Button(self, font=FONT_BUTTONS,\n text=\"«\",\n command=lambda: self._textw.insert_text(\"« \")\n ).grid(row=4, column=0, sticky=E+W+N+S)\n Button(self, font=FONT_BUTTONS,\n text=\"»\",\n command=lambda: self._textw.insert_text(\"»\")\n ).grid(row=5, column=0, sticky=E+W+N+S)\n Button(self, font=FONT_BUTTONS,\n text=\"…\",\n command=lambda: self._textw.insert_text(\"…\")\n ).grid(row=6, column=0, sticky=E+W+N+S)\n\n # TODO warning : flusleft is a bit special in LateX\n # for now no flushleft here !\n Button(self,\n font=FONT_BUTTONS,\n width=50, height=50,\n image=self._left,\n command=lambda: self._textw._add_mult_line_tag(\"\", [\"FLUSHRIGHT\", \"CENTER\"])\n ).grid(row=0, column=1, sticky=E+W+N+S)\n Button(self,\n font=FONT_BUTTONS,\n width=50, height=50,\n image=self._right,\n command=lambda: self._textw._add_mult_line_tag(\"FLUSHRIGHT\", [\"FLUSHLEFT\", \"CENTER\"])\n ).grid(row=1, column=1, sticky=E+W+N+S)\n Button(self,\n font=FONT_BUTTONS,\n width=50, height=50,\n image=self._center,\n command=lambda: self._textw._add_mult_line_tag(\"CENTER\", [\"FLUSHRIGHT\", \"FLUSHLEFT\"])\n ).grid(row=2, column=1, sticky=E+W+N+S)\n\n Button(self,\n font=FONT_BUTTONS,\n text=\"Note\",\n command=lambda: self._textw._add_remove_tags(\"FOOTNOTE\", [\"ITAL\", \"BOLD\", \"SMALLCAPS\"])\n ).grid(row=3, column=1, sticky=E+W+N+S)\n Button(self,\n font=FONT_BUTTONS,\n text=\"Déformater\",\n command=lambda: self._textw._add_remove_tags(None, [\"BOLD\", \"ITAL\", \"UNDERLINE\", \"CHAPTER\", \"SECTION\", \"FOOTNOTE\", \"SMALLCAPS\"])\n ).grid(row=4, column=1, sticky=E+W+N+S)\n Button(self,\n font=FONT_BUTTONS,\n text=\"Chapitre\",\n command=lambda: self._textw._add_remove_tags(\"CHAPTER\", [\"SECTION\", \"FOOTNOTE\", \"BOLD\", \"ITAL\", \"SMALLCAPS\"])\n ).grid(row=5, column=1, sticky=E+W+N+S)\n Button(self,\n font=FONT_BUTTONS,\n text=\"Section\",\n command=lambda: self._textw._add_remove_tags(\"SECTION\", [\"CHAPTER\", \"FOOTNOTE\", \"BOLD\", \"ITAL\", \"SMALLCAPS\"])\n ).grid(row=6, column=1, sticky=E+W+N+S)\n Button(self, font=FONT_BUTTONS,\n text=\"Copier\",\n command=lambda: self._textw.on_copy()\n ).grid(row=7, column=1, sticky=E+W+N+S)\n Button(self, font=FONT_BUTTONS,\n text=\"Couper\",\n command=lambda: self._textw.on_cut()\n ).grid(row=8, column=1, sticky=E+W+N+S)\n Button(self, font=FONT_BUTTONS,\n text=\"Coller\",\n command=lambda: self._textw.on_paste()\n ).grid(row=9, column=1, sticky=E+W+N+S)\n Button(self, font=FONT_BUTTONS,\n text=\"Chercher\",\n command=lambda: self._textw.on_find()\n ).grid(row=10, column=1, sticky=E+W+N+S)\n Button(self, font=FONT_BUTTONS,\n text=\"Petites maj.\",\n command=lambda: self._textw._add_small_caps_tag([\"BOLD\", \"ITAL\", \"FOOTNOTE\"])\n ).grid(row=11, column=1, sticky=E+W+N+S)\n\n","repo_name":"ChristopheNolim/versificateur","sub_path":"src/tex_editor/buttons.py","file_name":"buttons.py","file_ext":"py","file_size_in_byte":5608,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"22843222326","text":"\nfrom arma import Arma\nfrom proyectil import Proyectil\n\n\"\"\" y \"\"\"\nclass Alien():\n\n def __init__(self, x_coordinate, y_coordinate):\n self._x_coordinate = x_coordinate\n self._y_coordinate = y_coordinate\n self._health = 3\n self._hited = False\n self._arma = None\n self._num_ID = None\n \n @property\n def health(self):\n return self._health\n \n @property\n def hited(self):\n return self._hited\n \n @property\n def x_coordinate(self):\n return self._x_coordinate\n\n @x_coordinate.setter\n def x_coordinate(self, coordenada_x):\n if isinstance (coordenada_x, int):\n if 0 <= coordenada_x <= 15:\n self._x_coordinate = coordenada_x\n else:\n print(\"Coordenada 'x' ingresada supera limite.\")\n else:\n return False\n \n @property\n def y_coordinate(self):\n return self._y_coordinate\n \n @y_coordinate.setter\n def y_coordinate(self, coordenada_y):\n if isinstance (coordenada_y, int):\n if 0 <= coordenada_y <= 15:\n self._y_coordinate = coordenada_y\n else:\n print(\"Coordenada 'y' ingresada supera limite.\")\n else:\n return False\n \n def hit(self):\n # vida de objeto alien no puedo ser menor a 0\n if self._health >= 1:\n self._health = self._health - 1\n \n @property\n def is_alive(self):\n if self._health > 0:\n return True\n else:\n return False\n \n def teleport(self, value_x, value_y):\n self.x_coordinate = value_x\n self.y_coordinate = value_y\n\n @property\n def collision_detection(self):\n return self._hited\n \n @collision_detection.setter\n def collision_detection(self, punto_de_impacto):\n if isinstance (punto_de_impacto, Proyectil):\n if punto_de_impacto[0] == self._x_coordinate and\\\n punto_de_impacto[1] == self._y_coordinate:\n self._hited = True\n else:\n self._hited = False\n #print(\"No ha recibido impacto.\")\n \n @property\n def arma(self):\n return self._arma\n \n @arma.setter\n def arma(self, arma):\n if isinstance(arma, Arma):\n self._arma = arma\n else:\n self._arma = None\n \n @property\n def num_ID(self):\n return self._num_ID\n \n @num_ID.setter\n def num_ID(self, num):\n if isinstance(num, int):\n self._num_ID = num\n else:\n return False","repo_name":"raioliva21/Guia_8","sub_path":"alien.py","file_name":"alien.py","file_ext":"py","file_size_in_byte":2631,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"33285896552","text":"from ray.experimental import serve\nimport os\nimport ray\nfrom ensemble_profiler.utils import *\nimport time\nfrom ensemble_profiler.server import HTTPActor\nimport subprocess\nfrom ensemble_profiler.constants import (ROUTE_ADDRESS, PROFILE_ENSEMBLE,\n PREDITICATE_INTERVAL)\nfrom ensemble_profiler.tq_simulator import find_tq\nimport time\nfrom threading import Event\nimport requests\nimport json\nimport torch\nimport socket\nimport os\nimport jsonlines\nimport numpy as np\n\npackage_directory = os.path.dirname(os.path.abspath(__file__))\n\n\ndef _calculate_throughput_ensemble(pipeline):\n num_queries = 100\n start_time = time.time()\n futures = [pipeline.remote(data=torch.zeros(1, 1, PREDITICATE_INTERVAL))\n for _ in range(num_queries)]\n result = ray.get(futures)\n end_time = time.time()\n mu_qps = num_queries / (end_time - start_time)\n return mu_qps\n\n\ndef _heuristic_lambda_calculation(mu_qps):\n \"\"\"\n This method heuristically calculates the lambda given a throughput\n rate! Right now the heuristic is set to be 3/4th of mu_qps\n \"\"\"\n return mu_qps * 0.75\n\n\ndef _calculate_latency(file_name, p=95):\n latency_s = []\n with jsonlines.open(file_name) as reader:\n latency_s = [(obj[\"end\"] - obj[\"start\"]) for obj in reader]\n return np.percentile(latency_s, p)\n\n\ndef profile_ensemble(model_list, file_path,\n constraint={\"gpu\": 1, \"npatient\": 1}, http_host=\"0.0.0.0\",\n fire_clients=True, with_data_collector=False):\n if not ray.is_initialized():\n # read constraint\n num_patients = int(constraint[\"npatient\"])\n gpu = int(constraint[\"gpu\"])\n ray.init(object_store_memory=1000000000,\n _internal_config=json.dumps(\n {\"raylet_reconstruction_timeout_milliseconds\": 1000000000,\n \"initial_reconstruction_timeout_milliseconds\": 1000000000}))\n serve.init(blocking=True, http_port=5000)\n nursery_handle = start_nursery()\n if not os.path.exists(str(file_path.resolve())):\n file_path.touch()\n file_name = str(file_path.resolve())\n # create the pipeline\n pipeline, service_handles = create_services(model_list, gpu)\n # create patient handles\n if with_data_collector:\n actor_handles = start_patient_actors(num_patients=num_patients,\n nursery_handle=nursery_handle,\n pipeline=pipeline)\n else:\n # if not data collector then only one client needed\n actor_handles = {f\"patient{i}\": None for i in range(1)}\n\n # start the http server\n obj_id = nursery_handle.start_actor.remote(HTTPActor,\n \"HEALTH_HTTP_SERVER\",\n init_args=[ROUTE_ADDRESS,\n actor_handles,\n pipeline,\n file_name])\n\n http_actor_handle = ray.get(obj_id)[0]\n http_actor_handle.run.remote(host=http_host, port=8000)\n # wait for http actor to get started\n time.sleep(2)\n\n try:\n # warming up the gpu\n warmup_gpu(pipeline, warmup=200)\n\n if not with_data_collector:\n # calculating the throughput\n mu_qps = _calculate_throughput_ensemble(pipeline)\n print(\"Throughput of Ensemble is : {} QPS\".format(mu_qps))\n lambda_qps = _heuristic_lambda_calculation(mu_qps)\n waiting_time_ms = 1000.0/lambda_qps\n print(\"Lambda of Ensemble is: {} QPS,\"\n \" waiting time: {} ms\".format(lambda_qps, waiting_time_ms))\n\n # fire client\n if fire_clients:\n print(\"Firing the clients\")\n if with_data_collector:\n client_path = os.path.join(\n package_directory, \"patient_client.go\")\n cmd = [\"go\", \"run\", client_path]\n else:\n ensembler_path = os.path.join(\n package_directory, \"profile_ensemble.go\")\n cmd = [\"go\", \"run\", ensembler_path]\n\n procs = []\n for patient_name in actor_handles.keys():\n final_cmd = cmd + [patient_name]\n if not with_data_collector:\n final_cmd += [str(waiting_time_ms)]\n ls_output = subprocess.Popen(final_cmd)\n procs.append(ls_output)\n for p in procs:\n p.wait()\n serve.shutdown()\n T_s = _calculate_latency(file_name)\n if not with_data_collector:\n T_q = find_tq(lambda_qps, num_patients, mu_qps, T_s)\n return T_q + T_s\n return T_s\n else:\n gw = os.popen(\"ip -4 route show default\").read().split()\n s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\n s.connect((gw[2], 0))\n # for where the server ray.serve() request will be executed\n IPv4addr = s.getsockname()[0]\n serve_port = 8000\n\n # for client address. In the experiment points to pluto\n url = \"http://130.207.25.143:4000/jsonrpc\"\n print(\"sending RPC request form IPv4 addr: {}\".format(IPv4addr))\n if with_data_collector:\n req_params = {\"npatient\": num_patients, \"serve_ip\": IPv4addr,\n \"serve_port\": serve_port, \"go_client_name\": \"patient_client\"}\n else:\n req_params = {\"npatient\": 1,\n \"serve_ip\": IPv4addr,\n \"serve_port\": serve_port,\n \"go_client_name\": \"profile_ensemble\",\n \"waiting_time_ms\": waiting_time_ms}\n fire_remote_clients(url, req_params)\n print(\"finish firing remote clients\")\n serve.shutdown()\n T_s = _calculate_latency(file_name)\n if not with_data_collector:\n T_q = find_tq(lambda_qps, num_patients, mu_qps, T_s)\n return T_q + T_s\n return T_s\n except Exception as e:\n serve.shutdown()\n print(str(e))\n return None\n\n\ndef fire_remote_clients(url, req_params):\n payload = {\n \"method\": \"fire_client\",\n \"params\": req_params,\n \"jsonrpc\": \"2.0\",\n \"id\": 0\n }\n response = requests.post(url, json=payload).json()\n print(\"{}\".format(response))\n\n\ndef warmup_gpu(pipeline, warmup):\n print(\"warmup GPU\")\n total_data_request = PREDITICATE_INTERVAL\n for _ in range(warmup):\n ray.get(pipeline.remote(data=torch.zeros(1, 1, total_data_request)))\n print(\"finish warming up GPU by firing torch zero {} times\".format(warmup))\n","repo_name":"alindkhare/serve-healthcare","sub_path":"ensemble_profiler/latency.py","file_name":"latency.py","file_ext":"py","file_size_in_byte":7248,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"3"} +{"seq_id":"34309791252","text":"import pandas as pd\nimport numpy as np\nfrom Config import config\nimport sys\n\nclass data_process:\n def __init__(self, config, datapath=''):\n self.datapath = datapath\n self.config = config\n def load_data(self):\n datapath = self.datapath\n test_datapath = 'test.csv'\n train_datapath = 'train.csv'\n print(test_datapath)\n #test data\n test = pd.read_csv(test_datapath)\n test.index = test.building_id\n test.drop(columns = ['building_id'], inplace=True)\n print(test.head(5))\n #train data\n train = pd.read_csv(train_datapath)\n train.index = train.building_id\n train.drop(columns = ['building_id'], inplace=True)\n print(train.head(5))\n #concate data\n df = pd.concat([train,test], axis=0, sort=False)\n self.data = df\n return True\n \n def numpy_triu1(self): \n a = df.values\n r,c = np.triu_indices(a.shape[1],1)\n cols = df.columns\n nm = [cols[i]+\"_\"+cols[j] for i,j in zip(r,c)]\n return pd.DataFrame(a[:,r] - a[:,c], columns=nm, index = df.index)\n\n def numpy_triu2(self): \n a = df.values\n r,c = np.triu_indices(a.shape[1],1)\n cols = df.columns\n nm = [cols[i]+\"/\"+cols[j] for i,j in zip(r,c)]\n return pd.DataFrame(a[:,r] / a[:,c], columns=nm, index = df.index)\n \n def feature_transform(self):\n data = self.data\n data = data.fillna(0)\n for transform in self.config.get_transforms():\n print(transform)\n if transform == 'txn_floor':\n data.drop(columns = ['txn_floor'], inplace=True)\n \n if transform == 'txn_dt_year':\n data['txn_dt_year'] = data.txn_dt // 365\n \n if transform == 'building_complete_dt_year':\n data['building_complete_dt_year'] = data.building_complete_dt // 365\n \n if transform == 'city_population':\n city_population = data[['city','town_population']].groupby('city').sum()\n li = []\n for i in data.index.tolist():\n tmp = data.loc[i, 'city']\n li.append(city_population.loc[tmp].iloc[0])\n data = pd.concat([data, pd.DataFrame(li, index=data.index, columns = ['city_population'])],axis=1)\n \n if transform == 'city_area':\n city_area = data[['city','town_area']].groupby('city').sum()\n li = []\n for i in data.index.tolist():\n tmp = data.loc[i, 'city']\n li.append(city_area.loc[tmp].iloc[0])\n data = pd.concat([data, pd.DataFrame(li, index=data.index, columns = ['city_area'])], axis=1)\n \n if transform == \"city_population_density\":\n data['city_population_density'] = data['city_population'] / data['city_area']\n \n if transform == 'log_total_price':\n data['log_total_price'] = np.log(data.total_price)\n \n if transform == 'doc_num':\n data['doc_num'] = data.doc_rate * data.city_population\n \n if transform == 'bachelor_num':\n data['bachelor_num'] = data.bachelor_rate * data.city_population\n \n if transform == 'highschool_num':\n data['highschool_num'] = data.highschool_rate * data.city_population\n \n if transform == 'jobschool_num':\n data['jobschool_num'] = data.jobschool_rate * data.city_population\n \n if transform == 'junior_num':\n data['junior_num'] = data.junior_rate * data.city_population\n \n if transform == 'elementary_num':\n data['elementary_num'] = data.elementary_rate * data.city_population\n \n if transform == 'born_num':\n data['born_num'] = data.born_rate * data.city_population\n \n if transform == 'death_num':\n data['death_num'] = data.death_rate * data.city_population\n \n if transform == 'marriage_num':\n data['marriage_num'] =data.marriage_rate * data.city_population\n \n if transform == 'divorce_num':\n data['divorce_num'] = data.divorce_rate * data.city_population\n \n if transform == 'town_income_median_mean':\n tmp = data[['town','village_income_median']].groupby('town').mean()\n li = []\n for i in data.index.tolist():\n t = data.loc[i, 'town']\n li.append(tmp.loc[t].iloc[0])\n data = pd.concat([data, pd.DataFrame(li, index=data.index, columns = ['town_income_median_mean'])], axis=1)\n \n if transform == 'town_income_median_min':\n tmp = data[['town','village_income_median']].groupby('town').min()\n li = []\n for i in data.index.tolist():\n t = data.loc[i, 'town']\n li.append(tmp.loc[t].iloc[0])\n data = pd.concat([data, pd.DataFrame(li, index=data.index, columns = ['town_income_median_min'])], axis=1)\n \n if transform == 'town_income_median_max':\n tmp = data[['town','village_income_median']].groupby('town').max()\n li = []\n for i in data.index.tolist():\n t = data.loc[i, 'town']\n li.append(tmp.loc[t].iloc[0])\n data = pd.concat([data, pd.DataFrame(li, index=data.index, columns = ['town_income_median_max'])], axis=1)\n \n if transform == 'town_income_median_median':\n tmp = data[['town','village_income_median']].groupby('town').median()\n li = []\n for i in data.index.tolist():\n t = data.loc[i, 'town']\n li.append(tmp.loc[t].iloc[0])\n data = pd.concat([data, pd.DataFrame(li, index=data.index, columns = ['town_income_median_median'])], axis=1)\n \n self.data = data\n \n def category(self):\n try:\n data = self.data\n data.city = data.city.astype('category')\n data.town = data.town.astype('category')\n data.village = data.village.astype('category')\n data.building_material = data.building_material.astype('category')\n data.building_type = data.building_type.astype('category')\n data.parking_way = data.parking_way.astype('category')\n\n city = pd.get_dummies(data.city, drop_first=True)\n city.columns = ['city_' + str(a) for a in city.columns.tolist()]\n data = pd.concat([data, city], axis=1)\n data.drop(columns = ['city'], inplace=True)\n\n town = pd.get_dummies(data.town, drop_first=True)\n town.columns = ['town_' + str(a) for a in town.columns.tolist()]\n data = pd.concat([data, town], axis=1)\n data.drop(columns = ['town'], inplace=True)\n\n village = pd.get_dummies(data.village, drop_first=True)\n village.columns = ['village_' + str(a) for a in village.columns.tolist()]\n data = pd.concat([data, village], axis=1)\n data.drop(columns = ['village'], inplace=True)\n\n building_material = pd.get_dummies(df.building_material, drop_first=True)\n building_material.columns = ['building_material_' + str(a) for a in building_material.columns.tolist()]\n data = pd.concat([data, building_material], axis=1)\n data.drop(columns = ['building_material'], inplace=True)\n\n building_type = pd.get_dummies(data.building_type, drop_first=True)\n building_type.columns = ['building_type_' + str(a) for a in building_type.columns.tolist()]\n data = pd.concat([data, building_type], axis=1)\n data.drop(columns = ['building_type'], inplace=True)\n\n parking_way = pd.get_dummies(data.parking_way, drop_first=True)\n parking_way.columns = ['parking_way_' + str(a) for a in parking_way.columns.tolist()]\n data = pd.concat([data, parking_way], axis=1)\n data.drop(columns = ['parking_way'], inplace=True)\n\n self.data = data\n except:\n print('Error: category')\n \n def correlation(self, dataset, threshold):\n col_corr = set() # Set of all the names of deleted columns\n corr_matrix = dataset.corr()\n for i in range(len(corr_matrix.columns)):\n for j in range(i):\n if (corr_matrix.iloc[i, j] >= threshold) and (corr_matrix.columns[j] not in col_corr):\n colname = corr_matrix.columns[i] # getting the name of column\n col_corr.add(colname)\n if colname in dataset.columns:\n del dataset[colname] # deleting the column from the dataset\n\n return dataset\n \n def extend_feature(self):\n try:\n data = self.data\n test = data[data.log_total_price.isnull()]\n train = data[~data.log_total_price.isnull()]\n tmp = data[['doc_num','master_num','bachelor_num','highschool_num','junior_num','elementary_num']]\n ttmp = self.numpy_triu1(tmp)\n data = pd.concat([data, ttmp], axis=1)\n tmp = data[['I_10000','II_10000','III_10000','IV_10000','V_10000','VI_10000','VII_10000','VIII_10000','IX_10000','X_10000','XI_10000','XII_10000','XIII_10000','XIV_10000']]\n ttmp = self.numpy_triu1(tmp)\n tttmp = self.numpy_triu1(ttmp)\n corr = pd.concat([self.numpy_triu1(tmp),data.log_total_price], axis=1).T[train.index.tolist()].T.corr().abs()['log_total_price'].sort_values(ascending=False)\n ttmp_df = self.correlation(ttmp.copy(), 0.8)\n tttmp_df = self.correlation(tttmp.copy(), 0.8)\n corr = pd.concat([tttmp_df,data.log_total_price], axis=1).T[train.index.tolist()].T.corr().abs()['log_total_price'].sort_values(ascending=False)\n li = corr[corr > 0.4].index.tolist()\n li.remove('log_total_price')\n tttmp_df= tttmp_df[li]\n data = pd.concat([data, ttmp_df, tttmp_df], axis=1)\n\n tmp = data[['I_5000','II_5000','III_5000','IV_5000','V_5000','VI_5000','VII_5000','VIII_5000','IX_5000','X_5000','XI_5000','XII_5000','XIII_5000','XIV_5000']]\n ttmp = self.numpy_triu1(tmp)\n tttmp = self.numpy_triu1(ttmp)\n ttmp_df = self.correlation(ttmp.copy(), 0.8)\n tttmp_df = self.correlation(tttmp.copy(), 0.8)\n corr = pd.concat([tttmp_df,data.log_total_price], axis=1).T[train.index.tolist()].T.corr().abs()['log_total_price'].sort_values(ascending=False)\n li = corr[corr > 0.4].index.tolist()\n li.remove('log_total_price')\n tttmp_df= tttmp_df[li]\n data = pd.concat([data, ttmp_df, tttmp_df], axis=1)\n\n tmp = data[['I_1000','II_1000','III_1000','IV_1000','V_1000','VI_1000','VII_1000','VIII_1000','IX_1000','X_1000','XI_1000','XII_1000','XIII_1000','XIV_1000']]\n ttmp = self.numpy_triu1(tmp)\n tttmp = self.numpy_triu1(ttmp)\n ttmp_df = self.correlation(ttmp.copy(), 0.8)\n tttmp_df = self.correlation(tttmp.copy(), 0.8)\n corr = pd.concat([tttmp_df,data.log_total_price], axis=1).T[train.index.tolist()].T.corr().abs()['log_total_price'].sort_values(ascending=False)\n li = corr[corr > 0.4].index.tolist()\n li.remove('log_total_price')\n tttmp_df= tttmp_df[li]\n data = pd.concat([data, ttmp_df, tttmp_df], axis=1)\n\n self.data = data\n except:\n print('Error: extend_feature')\n def export(self):\n try:\n data = self.data\n test = data[data.log_total_price.isnull()]\n train = data[~data.log_total_price.isnull()]\n print(test.head(5))\n print(train.head(5))\n # train.to_csv(train1.csv)\n # test.to_csv(test1.csv)\n except:\n print('Error: export')\n def run(self):\n if not self.load_data():\n print('Error')\n if not self.feature_transform():\n print('Error')\n if not self.category():\n print('Error')\n if not self.extend_feature():\n print('Error')\n if not self.export():\n print('Error')\n \nif __name__ == '__main__':\n cf = config()\n if len(sys.argv) >= 2:\n path = sys.argv[1]\n du = data_process(cf, path)\n result = du.run()\n# if result:\n# print(du.Result)\n# else:\n# du.show_log()\n \n ","repo_name":"rickylee318/tbrain_esun_house_price_predict","sub_path":"Data_Process.py","file_name":"Data_Process.py","file_ext":"py","file_size_in_byte":12994,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"33235738744","text":"from __future__ import annotations\n\n\ndef decode_uri(uri: str) -> dict:\n \"\"\"\n - Turn a URI into a dictionary of parameters\n - e.g. `\"postgresql://postgres:password@localhost:5432/name_of_db\"`\n becomes:\n {'db_name': 'name_of_db',\n 'host': 'localhost',\n 'un': 'postgres',\n 'pw': 'password',\n 'port': '5432',\n 'extras': None}\n\n Args:\n uri (str): database connection string\n\n Returns:\n dictionary with individual parameters\n \"\"\"\n\n psql_un_pw, host_port_db = uri.split(\"@\")\n\n # Get username and password\n _, un_pw = psql_un_pw.split(r\"//\")\n un, pw = un_pw.split(\":\")\n\n # Get host, port, database name\n host, port_db = host_port_db.split(\":\")\n port, db_plus = port_db.split(r\"/\")\n\n if \"?\" in db_plus:\n db, extras = db_plus.split(\"?\")\n else:\n db = db_plus\n extras = None\n\n return {\n \"db_name\": db,\n \"host\": host,\n \"un\": un,\n \"pw\": pw,\n \"port\": port,\n \"extras\": extras,\n }\n\n\ndef generate_uri(\n db_name: str,\n host: str = \"localhost\",\n un: str = \"postgres\",\n pw: str = \"\",\n port: int = 5432,\n extras: str | None = None,\n) -> str:\n \"\"\"\n - Turn individual connection parameters into a URI\n\n Args:\n db_name (str): name of database\n host (str): name of host\n un (str): username\n pw (str): password\n port (int): port\n extras (str): optional arguments at the end of the connection string\n\n Returns:\n database connection string\n \"\"\"\n uri = f\"postgresql://{un}:{pw}@{host}:{port}/{db_name}\"\n\n if extras:\n uri += f\"?{extras}\"\n\n return uri\n","repo_name":"aaronfraint/pg-data-etl","sub_path":"pg_data_etl/helpers/uri.py","file_name":"uri.py","file_ext":"py","file_size_in_byte":1691,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"3105907013","text":"# use route target zhttpreq/ipc:///tmp/zhttpreqhandler\n\nimport zmq\nimport tnetstring\n\nzmq_context = zmq.Context()\nsock = zmq_context.socket(zmq.REP)\nsock.connect('ipc:///tmp/zhttpreqhandler')\n\nwhile True:\n\treq = tnetstring.loads(sock.recv()[1:])\n\n\tresp = {\n\t\t'id': req['id'],\n\t\t'code': 200,\n\t\t'reason': 'OK',\n\t\t'headers': [\n\t\t\t['Content-Type', 'text/plain']\n\t\t],\n\t\t'body': 'hello there\\n'\n\t}\n\n\tsock.send('T' + tnetstring.dumps(resp))\n","repo_name":"fastly/pushpin","sub_path":"tools/zhttpreqhandler.py","file_name":"zhttpreqhandler.py","file_ext":"py","file_size_in_byte":434,"program_lang":"python","lang":"en","doc_type":"code","stars":3489,"dataset":"github-code","pt":"3"} +{"seq_id":"3535567260","text":"#!/usr/bin/env python3\nfrom email.message import EmailMessage\nimport os.path\nimport mimetypes\nimport smtplib\nimport getpass\n\n\nmessage = EmailMessage()\nmail_server = smtplib.SMTP('localhost')\n\nsender = \"automation@example.com\"\nreceiver = \"{}@example.com\".format(os.environ.get('USER'))\nmessage['From'] = sender\nmessage['To'] = recipient\n\nmessage['Subject'] = \" Upload Completed - Online Fruit Store\"\nbody = \"All fruits are uploaded to our website successfully. A detailed list is attached to this email.\"\nmessage.set_content(body)\n\nattachment_path = \"processed.pdf\"\nattachment_filename = os.path.basename(attachment_path)\nmime_type, _ = mimetypes.guess_type(attachment_path)\nmime_type, mime_subtype = mime_type.split('/', 1)\nwith open(attachment_path, 'rb') as ap:\n\tmessage.add_attachment(ap.read(),maintype=mime_type,subtype=mime_subtype,filename=os.path.basename(attachment_path))\n\n\nmail_server.send_message(message)\n\n","repo_name":"rohit1717/Google_it_automation","sub_path":"email_python.py","file_name":"email_python.py","file_ext":"py","file_size_in_byte":919,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"40888215933","text":"\"\"\"\nProgrammer: Chris Tralie\nPurpose: To serve as an entry point for Driedger's Musaicing Technique\n\nModified by Alex Russo Nov 7 2020\nPurpose: Add stereo processing and ability to create and use corpus as source\n\"\"\"\nimport argparse\nimport os\nimport sndhdr\nimport wave\nfrom pathlib import Path\n\nimport librosa\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport scipy.io as sio\nimport scipy.ndimage\nfrom pydub import AudioSegment\n\nfrom NMF import *\nfrom SpectrogramTools import *\n\n\ndef doMusaicing(source, sourceCorpus, target, result, mono, sr = 22050, winSize = 2048, hopSize = 1024, \\\n shiftrange=0, NIters = 80, r = 7, p = 10, c = 3, savePlots = True):\n \"\"\"\n :param source: Source audio filename\n :param sourceCorpus: Comma separated list of source audio filenames to be used as a corpus\n :param target: Target audio filename\n :param result: Result wavfile path\n :param winSize: Window Size of STFT in samples\n :param hopSize: Hop size of STFT in samples\n :param shiftrange: The number of halfsteps below and above which \\\n to shift the sound\n :param NIters: Number of iterations of Driedger's technique\n :param r: Width of the repeated activation filter\n :param p: Degree of polyphony; i.e. number of values in each column\\\n of H which should be un-shrunken\n :param c: Half length of time-continuous activation filter\n :param savePlots: Whether to save plots showing progress of NMF \\\n every 20 iterations\n :param mono: If True the unmodified LetItBee source will be used \\\n and a mono file will be returned but you can still use sourceCorpus feature\n \"\"\"\n if sourceCorpus:\n combined = AudioSegment.empty()\n if os.path.isdir(sourceCorpus):\n directory = sourceCorpus\n for filename in os.listdir(directory):\n filename = os.path.join(directory, filename)\n\n # check if file is a valid audio file, if not don't include in corpus\n if sndhdr.what(filename):\n audio_file = AudioSegment.from_file(filename)\n combined += audio_file\n else:\n continue\n else:\n sourceCorpus = sourceCorpus.strip().split(',')\n for audio_file in sourceCorpus:\n audio_file = AudioSegment.from_file(audio_file)\n combined += audio_file\n \n # process and export corpus\n directory = \"./audio_files/corpus/\"\n filename = directory + \"corpus_\" + result\n Path(directory).mkdir(parents=True, exist_ok=True)\n combined.export(filename)\n source = filename\n if not mono:\n print(f\"Starting using stereo processing, sample rate: {sr}, winSize: {winSize}, hopSize: {hopSize}, NIters: {NIters}, r: {r}, p: {p}, c: {c}, savePlots: {savePlots}\")\n # load source, split channels, duplicate if mono, and process data by channel\n X, sr = librosa.load(source, mono=False, sr=sr)\n try:\n print(\"Starting PitchShift L\")\n WComplexL = getPitchShiftedSpecs(X[0], sr, winSize, hopSize, shiftrange)\n print(\"Starting PitchShift R\")\n WComplexR = getPitchShiftedSpecs(X[1], sr, winSize, hopSize, shiftrange)\n except:\n print(\"Starting PitchShift L MONO\")\n WComplexL = getPitchShiftedSpecs(X, sr, winSize, hopSize, shiftrange)\n print(\"Starting PitchShift R MONO\")\n WComplexR = getPitchShiftedSpecs(X, sr, winSize, hopSize, shiftrange)\n WL = np.abs(WComplexL)\n WR = np.abs(WComplexR)\n\n # load target, split channels, duplicate if mono, and process data by channel\n X, sr = librosa.load(target, mono=False, sr=sr)\n try:\n VL = np.abs(STFT(X[0], winSize, hopSize))\n VR = np.abs(STFT(X[1], winSize, hopSize))\n except:\n VL = np.abs(STFT(X, winSize, hopSize))\n VR = np.abs(STFT(X, winSize, hopSize))\n fn = None\n fnw = None\n if savePlots:\n fn = lambda V, W, H, iter, errs: plotNMFSpectra(V, W, H, iter, errs, hopSize)\n fnw = lambda W: plotInitialW(W, hopSize)\n\n # additional processing per channel\n print(\"Starting Driedger Channel L\")\n HL = doNMFDriedger(VL, WL, NIters, r=r, p=p, c=c, plotfn=fn, plotfnw = fnw)\n print(\"Starting Driedger Channel R\")\n HR = doNMFDriedger(VR, WR, NIters, r=r, p=p, c=c, plotfn=fn, plotfnw = fnw)\n HL = np.array(HL, dtype=np.complex)\n HR = np.array(HR, dtype=np.complex)\n V2L = WComplexL.dot(HL)\n V2R = WComplexR.dot(HR)\n\n print(\"Doing phase retrieval L\")\n YL = griffinLimInverse(V2L, winSize, hopSize, NIters=30)\n print(\"Doing phase retrieval R\")\n YR = griffinLimInverse(V2R, winSize, hopSize, NIters=30)\n YL = YL/np.max(np.abs(YL))\n YR = YR/np.max(np.abs(YR))\n \n resultL = result[:-4] + \"L.wav\"\n resultR = result[:-4] + \"R.wav\"\n\n # convert from float64 to 32 for final bounce (bit depth can't be higher than 32)\n YL = YL.astype('float32')\n YR = YR.astype('float32')\n\n # write left and right channels\n sio.wavfile.write(resultL, sr, YL)\n sio.wavfile.write(resultR, sr, YR)\n\n # combine left and right channels\n finalL = AudioSegment.from_file(resultL)\n finalR = AudioSegment.from_file(resultR)\n finalL.export()\n finalR.export()\n final_stereo_file = AudioSegment.from_mono_audiosegments(finalL, finalR)\n # export processed file\n directory = \"./audio_files/processed/\"\n result = directory + result\n Path(directory).mkdir(parents=True, exist_ok=True)\n final_stereo_file.export(result, format='wav')\n # remove left and right files\n os.remove(resultL)\n os.remove(resultR)\n else:\n print(\"Starting using original LetItBee Mono code\")\n # if mono = True use original LetItBee mono code\n X, sr = librosa.load(source, sr=sr)\n WComplex = getPitchShiftedSpecs(X, sr, winSize, hopSize, shiftrange)\n W = np.abs(WComplex)\n X, sr = librosa.load(target, sr=sr)\n V = np.abs(STFT(X, winSize, hopSize))\n fn = None\n fnw = None\n if savePlots:\n fn = lambda V, W, H, iter, errs: plotNMFSpectra(V, W, H, iter, errs, hopSize)\n fnw = lambda W: plotInitialW(W, hopSize)\n H = doNMFDriedger(V, W, NIters, r=r, p=p, c=c, plotfn=fn, plotfnw = fnw)\n H = np.array(H, dtype=np.complex)\n V2 = WComplex.dot(H)\n print(\"Doing phase retrieval...\")\n Y = griffinLimInverse(V2, winSize, hopSize, NIters=30)\n Y = Y/np.max(np.abs(Y))\n sio.wavfile.write(result, sr, Y)\n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser()\n group = parser.add_mutually_exclusive_group(required=True)\n group.add_argument('--source', type=str, help=\"Path to audio file for source sounds\")\n group.add_argument('--sourceCorpus', type=str, help=\"Comma separated list of paths to audio files for source sounds to be used as a corpus\")\n parser.add_argument('--target', type=str, required=True, help=\"Path to audio file for target sound\")\n parser.add_argument('--result', type=str, required=True, help=\"Path to wav file to which to save the result\")\n parser.add_argument('--mono', type=str, default=\"False\", help='If mono is True the unmodified LetItBee code will be used and a mono file will be returned')\n parser.add_argument('--sr', type=int, default=22050, help=\"Sample rate\")\n parser.add_argument('--shiftrange', type=int, default=0, help=\"Amount of pitch shifts to include\")\n parser.add_argument('--winSize', type=int, default=2048, help=\"Window Size in samples\")\n parser.add_argument('--hopSize', type=int, default=512, help=\"Hop Size in samples\")\n parser.add_argument('--NIters', type=int, default=60, help=\"Number of iterations of NMF\")\n parser.add_argument('--r', type=int, default=7, help=\"Width of the repeated activation filter\")\n parser.add_argument('--p', type=int, default=10, help=\"Degree of polyphony; i.e. number of values in each column of H which should be un-shrunken\")\n parser.add_argument('--c', type=int, default=3, help=\"Half length of time-continuous activation filter\")\n parser.add_argument('--saveplots', type=int, default=0, help='Save plots of iterations to disk')\n opt = parser.parse_args()\n doMusaicing(opt.source, opt.sourceCorpus, opt.target, opt.result, opt.mono, sr=opt.sr, shiftrange=opt.shiftrange,\\\n winSize=opt.winSize, hopSize=opt.hopSize, NIters=opt.NIters, r=opt.r, p=opt.p, c=opt.c, \\\n savePlots=opt.saveplots)\n","repo_name":"arussoproductions/PZLetItBee","sub_path":"Musaicing.py","file_name":"Musaicing.py","file_ext":"py","file_size_in_byte":8769,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"18359412131","text":"class Node:\n def __init__(self, key):\n self.key = key\n self.parent = self.left = self.right = None\n self.height = 0 # 높이 정보도 유지함에 유의!!\n\n def __str__(self):\n return str(self.key)\n\n def is_left(self):\n if (self.left == None):\n return False\n else:\n return True\n\n def is_right(self):\n if (self.right == None):\n return False\n else:\n return True\n\n def get_height(self):\n if (self.left == None and self.right == None):\n self.height = 0\n elif (not self.is_left()):\n self.height = self.right.height + 1\n elif (not self.is_right()):\n self.height = self.left.height + 1\n else:\n if (self.left.height > self.right.height):\n self.height = self.left.height + 1\n else:\n self.height = self.right.height + 1\n\n\nclass BST:\n def __init__(self):\n self.root = None\n self.size = 0\n\n def __len__(self):\n return self.size\n\n def preorder(self, v):\n if v != None:\n print(v.key, end=' ')\n self.preorder(v.left)\n self.preorder(v.right)\n\n def inorder(self, v):\n if(v != None):\n self.inorder(v.left)\n print(v.key, end=' ')\n self.inorder(v.right)\n\n def postorder(self, v):\n if(v != None):\n self.postorder(v.left)\n self.postorder(v.right)\n print(v.key, end=' ')\n\n def find_loc(self, key):\n if(self.size == 0):\n return None\n p = None\n v = self.root\n while v:\n if(v.key == key):\n return v\n elif(v.key < key):\n p = v\n v = v.right\n else:\n p = v\n v = v.left\n return p\n\n def search(self, key):\n p = self.find_loc(key)\n if(p and p.key == key):\n return p\n else:\n return None\n\n def insert(self, key):\n # 노드들의 height 정보 update 필요\n p = self.find_loc(key)\n if(p != None and p.key == key):\n return\n if(p == None or p.key != key):\n v = Node(key)\n if(p == None):\n self.root = v\n else:\n v.parent = p\n if(p.key >= key):\n p.left = v\n else:\n p.right = v\n while p:\n p.get_height()\n p = p.parent\n self.size += 1\n return v\n else:\n return None\n\n def deleteByMerging(self, x):\n # 노드들의 height 정보 update 필요\n if (x == None):\n return\n a, b, pt = x.left, x.right, x.parent\n if(a == None):\n c = b\n else:\n c = m = a\n\n while m.right:\n m = m.right\n m.right = b\n if b:\n b.parent = m\n while m:\n m.get_height()\n m = m.parent\n\n if (self.root == x):\n if c:\n c.parent = None\n self.root = c\n else:\n if (pt.left == x):\n pt.left = c\n pt.get_height()\n else:\n pt.right = c\n pt.get_height()\n if c:\n c.parent = pt\n self.size -= 1\n\n def deleteByCopying(self, x):\n # 노드들의 height 정보 update 필요\n if (x == None):\n return\n a, b, pt = x.left, x.right, x.parent\n if a:\n y = a\n while y.right:\n y = y.right\n x.key = y.key\n y_p = y.parent\n\n if y.left:\n y.left.parent = y.parent\n y.left.parent.get_height()\n if y.parent.left is y:\n y.parent.left = y.left\n y.parent.get_height()\n else:\n y.parent.right = y.left\n y.parent.get_height()\n del y\n while y_p:\n y_p.get_height()\n y_p = y_p.parent\n\n elif not a and b:\n y = b\n while y.left:\n y = y.left\n x.key = y.key\n y_p = y.parent\n if y.right:\n y.right.parent = y.parent\n y.parent.get_height()\n if y.parent.left is y:\n y.parent.left = y.right\n y.parent.get_height()\n else:\n y.parent.right = y.right\n y.parent.get_height()\n del y\n while y_p:\n y_p.get_height()\n y_p = y_p.parent\n\n else:\n if(pt == None):\n self.root = None\n else:\n if(pt.left is x):\n pt.left = None\n else:\n pt.right = None\n del x\n while pt:\n pt.get_height()\n pt = pt.parent\n\n def height(self, x): # 노드 x의 height 값을 리턴\n if x == None:\n return -1\n else:\n return x.height\n\n def succ(self, x): # key값의 오름차순 순서에서 x.key 값의 다음 노드(successor) 리턴\n # x의 successor가 없다면 (즉, x.key가 최대값이면) None 리턴\n if(x == None):\n return None\n if(x.right != None):\n temp = x.right\n while(temp.left):\n temp = temp.left\n return temp\n pt = x.parent\n while (pt != None and x == pt.right):\n x = pt\n pt = pt.parent\n return pt\n\n def pred(self, x): # key값의 오름차순 순서에서 x.key 값의 이전 노드(predecssor) 리턴\n # x의 predecessor가 없다면 (즉, x.key가 최소값이면) None 리턴\n if(x == None):\n return None\n if(x.left != None):\n temp = x.left\n while(temp.right):\n temp = temp.right\n return temp\n pt = x.parent\n while (pt != None and x == pt.left):\n x = pt\n pt = pt.parent\n return pt\n\n def rotateLeft(self, z): # 균형이진탐색트리의 1차시 동영상 시청 필요 (height 정보 수정 필요)\n if not z:\n return\n x = z.right\n if(x == None):\n return\n b = x.left\n x.parent = z.parent\n if z.parent:\n if(z.parent.left == z):\n z.parent.left = x\n else:\n z.parent.right = x\n if x:\n x.left = z\n z.parent = x\n z.right = b\n z.get_height()\n x.get_height()\n if b:\n b.parent = z\n z.right = b\n z.get_height()\n x.get_height()\n if(z == self.root and z != None):\n self.root = x\n self.root.get_height()\n\n def rotateRight(self, z): # 균형이진탐색트리의 1차시 동영상 시청 필요 (height 정보 수정 필요)\n if not z:\n return\n x = z.left\n if (x == None):\n return\n b = x.right\n x.parent = z.parent\n if z.parent:\n if (z.parent.left == z):\n z.parent.left = x\n else:\n z.parent.right = x\n if x:\n x.right = z\n z.parent = x\n z.left = b\n z.get_height()\n x.get_height()\n if b:\n b.parent = z\n z.left = b\n z.get_height()\n x.get_height()\n if(z == self.root and z != None):\n self.root = x\n self.root.get_height()\n\n\nT = BST()\nwhile True:\n cmd = input().split()\n if cmd[0] == 'insert':\n v = T.insert(int(cmd[1]))\n print(\"+ {0} is inserted\".format(v.key))\n elif cmd[0] == 'deleteC':\n v = T.search(int(cmd[1]))\n T.deleteByCopying(v)\n print(\"- {0} is deleted by copying\".format(int(cmd[1])))\n elif cmd[0] == 'deleteM':\n v = T.search(int(cmd[1]))\n T.deleteByMerging(v)\n print(\"- {0} is deleted by merging\".format(int(cmd[1])))\n elif cmd[0] == 'search':\n v = T.search(int(cmd[1]))\n if v == None:\n print(\"* {0} is not found!\".format(cmd[1]))\n else:\n print(\"* {0} is found!\".format(cmd[1]))\n elif cmd[0] == 'height':\n h = T.height(T.search(int(cmd[1])))\n if h == -1:\n print(\"= {0} is not found!\".format(cmd[1]))\n else:\n print(\"= {0} has height of {1}\".format(cmd[1], h))\n elif cmd[0] == 'succ':\n v = T.succ(T.search(int(cmd[1])))\n if v == None:\n print(\"> {0} is not found or has no successor\".format(cmd[1]))\n else:\n print(\"> {0}'s successor is {1}\".format(cmd[1], v.key))\n elif cmd[0] == 'pred':\n v = T.pred(T.search(int(cmd[1])))\n if v == None:\n print(\"< {0} is not found or has no predecssor\".format(cmd[1]))\n else:\n print(\"< {0}'s predecssor is {1}\".format(cmd[1], v.key))\n elif cmd[0] == 'Rleft':\n v = T.search(int(cmd[1]))\n if v == None:\n print(\"@ {0} is not found!\".format(cmd[1]))\n else:\n T.rotateLeft(v)\n print(\"@ Rotated left at node {0}\".format(cmd[1]))\n elif cmd[0] == 'Rright':\n v = T.search(int(cmd[1]))\n if v == None:\n print(\"@ {0} is not found!\".format(cmd[1]))\n else:\n T.rotateRight(v)\n print(\"@ Rotated right at node {0}\".format(cmd[1]))\n elif cmd[0] == 'preorder':\n T.preorder(T.root)\n print()\n elif cmd[0] == 'postorder':\n T.postorder(T.root)\n print()\n elif cmd[0] == 'inorder':\n T.inorder(T.root)\n print()\n elif cmd[0] == 'exit':\n break\n else:\n print(\"* not allowed command. enter a proper command!\")\n","repo_name":"panwoo1/DataStructure","sub_path":"pl_with_bst.py","file_name":"pl_with_bst.py","file_ext":"py","file_size_in_byte":10071,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"74107937041","text":"test = int(input())\nwhile test > 0:\n n = int(input())\n flag = 0\n sum = 0\n a = input()\n a = a.split(' ')\n for i in range(n):\n a[i] = float(a[i])\n sum += a[i]\n mean = sum/n\n ans = sum - mean*(n-1)\n for i in range(n):\n if (a[i] == ans):\n flag = 1\n print(i+1)\n break\n if (flag == 0):\n print(\"Impossible\")\n test -= 1\n","repo_name":"git-shashwat/Competitive-Programming","sub_path":"codechef/July Challenge/CHFM.py","file_name":"CHFM.py","file_ext":"py","file_size_in_byte":406,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"3"} +{"seq_id":"70098998801","text":"from mesa.visualization.modules import CanvasGrid\nfrom mesa.visualization.ModularVisualization import ModularServer\nfrom mesa.visualization.modules import ChartModule\nfrom model import MarketModel\nfrom agent import Type\n\n\ndef agent_portrayal(agent):\n portrayal = {\"Shape\": \"circle\", \"Filled\": \"true\", \"Layer\": 1, \"r\": 0.5}\n\n if agent.type == Type.OPTIMIST:\n portrayal[\"Color\"] = \"red\"\n if agent.type == Type.PESSIMIST:\n portrayal[\"Color\"] = \"green\"\n if agent.type == Type.RANDOM:\n portrayal[\"Color\"] = \"grey\"\n\n return portrayal\n\n\nchart = ChartModule([{\"Label\": \"Price\", \"Color\": \"Black\"}], data_collector_name='data')\n\ngrid = CanvasGrid(agent_portrayal, 10, 10, 400, 400)\nmodel_params = {\"agents\": 100, \"price\": 50}\n\nserver = ModularServer(\n MarketModel,\n [grid, chart],\n \"Market Model\",\n model_params=model_params,\n)\n\nserver.port = 8521 # The default\nserver.launch()\n","repo_name":"jc-doyle/market-model","sub_path":"server.py","file_name":"server.py","file_ext":"py","file_size_in_byte":917,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"5979502111","text":"# random replies to questions\n# ask questions back\n# words\n# basic english grammar\n# read input\n\n# store input as data but continue the conversation\n\nimport random\n\nwords = {\n 'greeting': ['hi', 'hello'], \n 'perspron': ['i', 'you', ['he', 'she', 'it'], 'we', 'you', 'they'], \n '.?!': ['.', '?', '!'], \n 'qwords': ['what', 'why', 'how'], \n 'infowords': ['name', 'age', 'color']\n }\n\nbot_info = {'name': '',}\nuser_info = {'name': None, 'age': None}\n\n# function to create sentences\n# types: greeting, question\ndef sentence_generator(type):\n sentence = ''\n if type == 'greeting':\n if user_info['name'] == None:\n sentence = \"{}\".format(words['greeting'][random.randint(0, len(words['greeting'])-1)])\n if user_info['name'] != None:\n sentence = \"{} {}\".format(words['greeting'][random.randint(0, len(words['greeting']))], user_info['name'])\n if type == 'askname':\n sentence = 'What is your name?'\n \n return sentence\n\n'''\ngreet = bool(random.getrandbits(1))\nask_name = bool(random.getrandbits(1))\nif greet:\n print(sentence_generator('greeting'))\n\n if ask_name:\n print(sentence_generator('askname'))\n'''\n\n \n \nmessage = ''\ngreeted = False\nwhile message != 'quit':\n # new message\n newm = False\n # did the user prompt a question\n user_asked = False\n\n if not greeted:\n print(sentence_generator('greeting'))\n greeted = True\n if user_info['name'] == None:\n print(sentence_generator('askname'))\n message = input()\n user_info['name'] = message\n newm = True\n \n \n if not newm:\n message = input()\n \n \n \n\n","repo_name":"hjtomi/SimpleProjects","sub_path":"Scripts/Chatbot/chatbot.py","file_name":"chatbot.py","file_ext":"py","file_size_in_byte":1683,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"41180540756","text":"import frappe\nimport json\n@frappe.whitelist()\ndef add_member_details(row,doc):\n list = []\n row = json.loads(row)\n if frappe.db.exists(\"Customer\",doc):\n doc_ = frappe.get_doc(\"Customer\",doc)\n for j in doc_.family_members_details:\n for i in doc_.family_members_documents:\n if((row.get('member_row_id') != i.family_member_details_name) and (j.member_row_id == i.family_member_details_name)):\n list.append({'members_name':i.get('members_name'),'age':i.get('age'),'gender':i.get('gender'),'check_list_name':i.check_list_name,'family_member_details_name':i.get('family_member_details_name'),'check':i.get('check'),'receive_or_send':i.receive_or_send})\n table_doc = frappe.get_all(\"Check List\",{'gender':row.get('gender') or \"Both\",'age_limit_from':['<=', row.get('age')],'age_limit_to':['>=', row.get('age')],'disable':0,'check_list_for':\"Customer\"}) \n \n if not table_doc:table_doc = frappe.get_all(\"Check List\",{'gender':\"Both\",'age_limit_from':['<=', row.get('age')],'age_limit_to':['>=', row.get('age')],'disable':0,'check_list_for':\"Customer\"}) \n if not table_doc:frappe.throw(\"Check List Not Found for Gender \"+row.get('gender')+\" and age \"+str(row.get('age')))\n else:\n check_list_items = frappe.get_doc(\"Check List\",table_doc[0].name).check_list_items\n for i in check_list_items:\n list.append({'members_name':row.get('members_name'),'age':row.get('age'),'gender':row.get('gender'),'check_list_name':i.check_list_name,'family_member_details_name':row.get('member_row_id'),'check':0,'receive_or_send':i.receive_or_send})\n if frappe.db.exists(\"Customer\",doc):\n for i in list:\n for j in frappe.get_doc(\"Customer\",doc).family_members_documents:\n if ((i['members_name'] == j.members_name) and (str(i['age']) == str(j.age)) and (i['gender'] == j.gender) and (i['check_list_name'] == j.check_list_name) and (i['family_member_details_name'] == j.family_member_details_name)):\n i['check'] = j.check\n return(list)\n@frappe.whitelist()\ndef fetch_checklist(table,doc):\n if frappe.db.exists(\"Customer\",doc):\n doc_ = frappe.get_doc(\"Customer\",doc)\n table = json.loads(table)\n list = []\n for row in doc_.family_members_details:\n table_doc = frappe.get_all(\"Check List\",{'gender':row.get('gender') or \"Both\",'age_limit_from':['<=', row.get('age')],'age_limit_to':['>=', row.get('age')],'disable':0,'check_list_for':\"Customer\"}) \n if not table_doc:table_doc = frappe.get_all(\"Check List\",{'gender':\"Both\",'age_limit_from':['<=', row.get('age')],'age_limit_to':['>=', row.get('age')],'disable':0,'check_list_for':\"Customer\"}) \n if not table_doc:frappe.throw(\"Check List Not Found for Gender \"+row.get('gender')+\" and age \"+str(row.get('age')))\n else:\n check_list_items = frappe.get_doc(\"Check List\",table_doc[0].name).check_list_items\n for i in check_list_items:\n list.append({'members_name':row.get('members_name'),'age':row.get('age'),'gender':row.get('gender'),'check_list_name':i.check_list_name,'family_member_details_name':row.get('member_row_id'),'check':frappe.get_value(\"Family Members Documents\",{'members_name':row.get('members_name'),'age':row.get('age'),'gender':row.get('gender'),'check_list_name':i.check_list_name,'receive_or_send':i.receive_or_send},\"check\") or 0,'receive_or_send':i.receive_or_send})\n return(list)\n@frappe.whitelist()\ndef remove_list(row,name):\n row = json.loads(row)\n list=[]\n list1=[]\n doc = frappe.get_doc(\"Customer\",name)\n for i in doc.family_members_documents:\n if(row.get('member_row_id') != i.family_member_details_name):\n list.append({'members_name':i.get('members_name'),'age':i.get('age'),'gender':i.get('gender'),'check_list_name':i.check_list_name,'family_member_details_name':i.get('family_member_details_name'),'check':i.get('check'),'receive_or_send':i.receive_or_send})\n for i in doc.family_members_table:\n if(row.get('member_row_id') != i.family_members_documents_name):\n list1.append({'members_name':i.get('members_name'),'file_type':i.get('file_type'),'file':i.get('file'),'next_remainder_or_expiry_on':i.next_remainder_or_expiry_on,'family_members_documents_name':i.get('family_members_documents_name'),'description':i.get('description'),'attached_by':i.get('attached_by'),'receive_or_send':i.receive_or_send})\n return(list,list1)\n\ndef validate(doc,even):\n if(doc.family_members_details):\n doc.family_members_documents = check_members_alive(doc,doc.family_members_documents,'family_member_details_name')\n doc.family_members_table = check_members_alive(doc,doc.family_members_table,'family_members_documents_name')\n else:\n doc.family_members_documents = []\n doc.family_members_table = []\n re_list = []\n for i in doc.family_members_documents:\n if(i.check == 0):\n re_list.append({'check_list_name':i.check_list_name,'members_name':i.members_name})\n remove_idx= []\n for j in doc.check_list_remainder_table:\n dele = 0\n for i in re_list:\n if i[\"check_list_name\"] == j.check_list and i[\"members_name\"] == j.member_name:\n dele = 1\n if dele == 0:\n remove_idx.append(j.idx-1)\n\n for i in reversed(remove_idx):\n doc.check_list_remainder_table.pop(i)\n idx = 1\n for k in doc.check_list_remainder_table:\n k.update({'idx': idx})\n idx = idx+1\n for i in re_list:\n new = 0\n for j in doc.check_list_remainder_table:\n if i[\"check_list_name\"] == j.check_list and i[\"members_name\"] == j.member_name:\n new = 1\n if new == 0:\n doc.append('check_list_remainder_table',dict(\n check_list=i[\"check_list_name\"],\n member_name=i['members_name']\n ))\n\n\ndef check_members_alive(doc,field,id_field):\n table_field = field\n custom_list = []\n exiting_member = []\n missing_member =[]\n for i in doc.family_members_details:\n if i.get('member_row_id') not in exiting_member:custom_list.append(i.get('member_row_id'))\n for i in table_field:\n if i.get(id_field) not in exiting_member:exiting_member.append(i.get(id_field))\n\n for i in exiting_member:\n if i not in custom_list:\n missing_member.append(i)\n remove_idx= []\n if(missing_member):\n for i in range(0,len(table_field),1):\n if(table_field[i].get(id_field) in missing_member):\n remove_idx.append(i)\n\n for i in reversed(remove_idx):\n table_field.pop(i)\n return table_field\n\n@frappe.whitelist()\ndef exist_list(name,doctype,field_name,field):\n master_name=frappe.db.get_all(doctype, filters={field_name:[\"Like\", \"%\"+name+\"%\"]}, fields=field)\n return master_name","repo_name":"thirvusoft/juzgo","sub_path":"juzgo/juzgo/custom/py/customer.py","file_name":"customer.py","file_ext":"py","file_size_in_byte":6940,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"71877938643","text":"while True:\n\n # Taking the amount input from the user\n while True:\n try:\n usDollars = float(\n input(\"\\nPlease input the amount you want to convert (in USD): \")\n )\n break\n except:\n print(\"Not a valid amount!\")\n\n # Taking the exchange rate input from the user\n while True:\n try:\n # Setting the default exchangeRate value to 1.27\n exchangeRate = float(\n input(\"\\nPlease enter the current exchange rate from USD to CAD: \")\n or 1.27\n )\n break\n except:\n print(\"Not a valid exchange rate!\")\n\n # Calculating US Dollars to CA Dollars\n caDollars = usDollars * exchangeRate\n\n print(\"\\n%0.2f US$ is equal to %0.2f CA$\" % (usDollars, caDollars))\n\n # Prompting user to continue or end\n resume = input(\n \"\\nIf you would like to start over, please type 'yes'. Otherwise, type any key to exit. \"\n )\n if resume == \"yes\":\n continue\n else:\n break\n\nprint(\"\\nThe end. Bye now!\")\n\n\n# Yay success! :-)\n# Diana Jean\n","repo_name":"deetuquib/portfolio","sub_path":"cst8279/labs/lab04/Tuquib_041043852_lab4UStoCAN.py","file_name":"Tuquib_041043852_lab4UStoCAN.py","file_ext":"py","file_size_in_byte":1120,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"74133711762","text":"#-*-coding:utf-8-*-\n\"\"\"\n Argument parser (from file and terminal)\n @author Qianyue He\n @date 2022.12.16\n\"\"\"\n\nimport configargparse\n\ndef get_options(delayed_parse = False):\n # IO parameters\n parser = configargparse.ArgumentParser()\n parser.add_argument('--config', is_config_file=True, help='Config file path')\n parser.add_argument(\"--case_idx\", type = int, default = 1, help = \"Id of Experiment (1, 2, 3, 4)\")\n parser.add_argument(\"--img_idx\", type = int, default = 1, help = \"Id of image (1, 2, 4, 5)\")\n parser.add_argument(\"--em_steps\", type = int, default = 2, help = \"E-M step for iterative matching re-estimation\")\n parser.add_argument(\"--max_iter\", type = int, default = 8000, help = \"Max number of iteration (should not be big)\")\n\n parser.add_argument(\"--base_folder\", type = str, default = \"output\", help = \"Output base folder\")\n \n parser.add_argument(\"-v\", \"--verbose\", default = False, action = \"store_true\", help = \"Output some intermediate information\")\n parser.add_argument(\"-s\", \"--save_warpped\", default = False, action = \"store_true\", help = \"Save warpped images for visualization\")\n parser.add_argument(\"-m\", \"--save_hmat\", default = False, action = \"store_true\", help = \"Save Homography mat for matlab evaluation\")\n parser.add_argument(\"--lms\", default = False, action = \"store_true\", help = \"Use LMS solver for the model\")\n parser.add_argument(\"--only_diff\", default = False, action = \"store_true\", help = \"Visualize only matching differences between EM steps\")\n parser.add_argument(\"--baseline_hmat\", default = False, action = \"store_true\", help = \"Whether to save OpenCV baseline Homography result\")\n parser.add_argument(\"--viz_kpt\", default = 'none', choices=['save_quit', 'save', 'none'], help = \"Visualize keypoint distribution\")\n parser.add_argument(\"--viz\", default = 'ransac', choices=['ransac', 'spectral', 'weight_only'], help = \"Visualization mode\")\n\n # Prominent parameters that might affect training results\n parser.add_argument(\"--affinity_eps\", type = float, default = 30.0, help = \"Sigma distance of allowed spatial inconsistency\")\n parser.add_argument(\"--aff_thresh\", type = float, default = 0.5, help = \"Threshold for spectral score replacement\") # baseline 5.0\n parser.add_argument(\"--epi_weight\", type = float, default = 0.5, help = \"Weighting coeff for epipolar score\")\n parser.add_argument(\"--fluc\", type = float, default = 0.5, help = \"SDP fluctuation parameter for robust solution\")\n parser.add_argument(\"--em_radius\", type = float, default = 6.0, help = \"Point outside this radius after projection will not be considered\")\n parser.add_argument(\"--score_thresh\", type = float, default = 0.4, help = \"The matched features should have a similarity score above this threshold\")\n \n parser.add_argument(\"--huber_param\", type = float, default = -1.0, help = \"Huber Loss parameter. Value less than 0.01 means no Huber loss.\")\n\n if delayed_parse:\n return parser\n return parser.parse_args()\n\nif __name__ == \"__main__\":\n args = get_options()\n print(f\"Fluc: {args.fluc}\")\n","repo_name":"Enigmatisms/cvx_proj","sub_path":"pyviz/options.py","file_name":"options.py","file_ext":"py","file_size_in_byte":3214,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"3"} +{"seq_id":"25550677816","text":"class DAG:\n def __init__(self):\n self.aList = {}\n self.size = 0\n \n def isVertex(self, vertex):\n return vertex in self.aList\n\n def numVertices(self):\n return self.size\n\n def numEdges(self):\n return sum([len(self.aList[vertex]) for vertex in self.aList])\n\n def vertices(self):\n vertices = []\n for vertex in self.aList:\n vertices.append(vertex)\n return vertices\n \n def edges(self):\n edges = []\n for vertex in self.aList:\n for v in self.aList[vertex]:\n edges.append((vertex, v))\n return edges\n \n def sortAdjacencyList(self):\n # Sort keys\n self.aList = dict(sorted(self.aList.items()))\n # Sort values\n for vertex in self.aList:\n self.aList[vertex].sort()\n \n def insertVertex(self, vertex):\n if not self.isVertex(vertex):\n self.aList[vertex] = []\n self.size += 1\n else:\n print(\"Vertex already exists\")\n\n def insertEdge(self, edge):\n u, v = edge\n if not self.isVertex(u):\n self.insertVertex(u)\n if not self.isVertex(v):\n self.insertVertex(v)\n \n if v not in self.aList[u] and u not in self.aList[v]:\n self.aList[u].append(v)\n else:\n print(\"Invalid directed edge\")\n\n def removeVertex(self, vertex):\n if self.isVertex(vertex):\n for v in self.aList[vertex]:\n self.aList[v].remove(vertex)\n self.aList.pop(vertex)\n self.size -= 1\n else:\n print(\"Vertex does not exist\")\n \n def removeEdge(self, edge):\n u, v = edge\n if self.isVertex(u) and self.isVertex(v):\n if v in self.aList[u]:\n self.aList[u].remove(v)\n else:\n print(\"Invalid directed edge\")\n else:\n print(\"Invalid directed edge\")\n \n def inDegree(self, vertex):\n if self.isVertex(vertex):\n return sum([1 for v in self.aList if vertex in self.aList[v]])\n else:\n print(\"Vertex does not exist\")\n \n def outDegree(self, vertex):\n if self.isVertex(vertex):\n return len(self.aList[vertex])\n else:\n print(\"Vertex does not exist\")\n \n def degree(self, vertex):\n if self.isVertex(vertex):\n return self.inDegree(vertex) + self.outDegree(vertex)\n else:\n print(\"Vertex does not exist\")\n \n def neighbors(self, vertex):\n if self.isVertex(vertex):\n return self.aList[vertex]\n else:\n print(\"Vertex does not exist\")\n \n def adjacent(self, u, v):\n if self.isVertex(u) and self.isVertex(v):\n return v in self.aList[u]\n else:\n print(\"Invalid directed edge\")\n \n def DFS(self, start_vertex):\n visited = {}\n for v in self.aList:\n visited[v] = False\n \n dfs = []\n \n def DFS_visit(vertex):\n visited[vertex] = True\n dfs.append(vertex)\n for v in self.aList[vertex]:\n if not visited[v]:\n DFS_visit(v)\n \n DFS_visit(start_vertex)\n\n return dfs\n\n def BFS(self, start_vertex):\n visited = {}\n for v in self.aList:\n visited[v] = False\n \n bfs = []\n queue = [start_vertex]\n\n while queue:\n vertex = queue.pop(0)\n if not visited[vertex]:\n visited[vertex] = True\n bfs.append(vertex)\n for v in self.aList[vertex]:\n queue.append(v)\n\n return bfs\n \n def DFS_spanning_tree(self, start_vertex):\n visited = {}\n for vertex in self.vertices():\n visited[vertex] = False\n \n spanning_tree = {}\n\n def DFS_visit(vertex):\n visited[vertex] = True\n for v in self.aList[vertex]:\n if not visited[v]:\n spanning_tree[v] = vertex\n DFS_visit(v)\n \n DFS_visit(start_vertex)\n return spanning_tree\n \n def BFS_spanning_tree(self, start_vertex):\n visited = {}\n for vertex in self.vertices():\n visited[vertex] = False\n \n spanning_tree = {}\n queue = [start_vertex]\n\n while queue:\n vertex = queue.pop(0)\n if not visited[vertex]:\n visited[vertex] = True\n for v in self.aList[vertex]:\n if not visited[v]:\n spanning_tree[v] = vertex\n queue.append(v)\n\n return spanning_tree\n \n def topological_sort(self):\n \"\"\"\n 1. Compute the in-degree of each node in the graph.\n 2. Enqueue all nodes with in-degree 0 to a queue.\n 3. While the queue is not empty, dequeue a node from the front of the queue and add it to the sorted list.\n 4. For each of the dequeued node's neighbors, decrement their in-degree by 1.\n 5. If any of the dequeued node's neighbors now have in-degree 0, enqueue them to the queue.\n 6. Repeat steps 3-5 until the queue is empty.\n \"\"\"\n in_degrees = {}\n for vertex in self.vertices():\n in_degrees[vertex] = self.inDegree(vertex)\n \n topological_order = []\n queue = []\n\n for vertex in in_degrees:\n if in_degrees[vertex] == 0:\n queue.append(vertex)\n \n while queue:\n vertex = queue.pop(0)\n topological_order.append(vertex)\n for v in self.aList[vertex]:\n in_degrees[v] -= 1\n if in_degrees[v] == 0:\n queue.append(v)\n \n return topological_order\n \n def isDAG(self):\n spanning_tree = self.DFS_spanning_tree(self.vertices()[0])\n for vertex in spanning_tree:\n if spanning_tree[vertex] == vertex:\n return False\n return True\n \n def longestPath(self):\n in_degrees = {}\n longest_paths = {}\n for v in self.aList:\n in_degrees[v] = self.inDegree(v)\n longest_paths[v] = 0\n queue = []\n\n for v in in_degrees:\n if in_degrees[v] == 0:\n queue.append(v)\n \n while queue:\n vertex = queue.pop(0)\n for v in self.aList[vertex]:\n if longest_paths[v] < longest_paths[vertex] + 1:\n longest_paths[v] = longest_paths[vertex] + 1\n in_degrees[v] -= 1\n if in_degrees[v] == 0:\n queue.append(v)\n\n return longest_paths\n \n\ng = DAG()\n\nedgeList = [\n (1, 2), (1, 7),\n (2, 5),\n (0, 2), (0, 3), (0, 4),\n (3, 5), (3, 7),\n (6, 7),\n (5, 6),\n (4, 7)\n]\n\nfor edge in edgeList:\n g.insertEdge(edge)\n\ng.sortAdjacencyList()\nprint(\"\\n\")\nprint(\"Vertices:\", g.vertices())\nprint(\"Edges:\", g.edges())\nprint(\"Size:\", g.size)\nprint(\"Adjacency List:\", g.aList)\nprint(\"DFS:\", g.DFS(0))\nprint(\"BFS:\", g.BFS(0))\nprint(\"DFS Spanning Tree:\", g.DFS_spanning_tree(0))\nprint(\"BFS Spanning Tree:\", g.BFS_spanning_tree(0))\nprint(\"Is DAG:\", g.isDAG())\nprint(\"Topological Sort:\", g.topological_sort())\nprint(\"Longest Path:\", g.longestPath())\n","repo_name":"Ashrockzzz2003/Data_Structures_and_Algorithms","sub_path":"non_linear/graphs/python/DAG.py","file_name":"DAG.py","file_ext":"py","file_size_in_byte":7432,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"30905964708","text":"# (c) 2005 Ian Bicking and contributors; written for Paste (http://pythonpaste.org)\n# Licensed under the MIT license: http://www.opensource.org/licenses/mit-license.php\nimport inspect\nimport sys\n\ntry:\n import importlib.metadata as importlib_metadata # noqa F401\nexcept ImportError: # pragma: no cover\n # bw-compat shim for py37\n import importlib_metadata # noqa F401\n\n\ndef fix_type_error(exc_info, callable, varargs, kwargs):\n \"\"\"\n Given an exception, this will test if the exception was due to a\n signature error, and annotate the error with better information if\n so.\n\n Usage::\n\n try:\n val = callable(*args, **kw)\n except TypeError:\n exc_info = fix_type_error(None, callable, args, kw)\n raise exc_info[0], exc_info[1], exc_info[2]\n \"\"\"\n if exc_info is None:\n exc_info = sys.exc_info()\n if (\n exc_info[0] != TypeError\n or str(exc_info[1]).find('arguments') == -1\n or getattr(exc_info[1], '_type_error_fixed', False)\n ):\n return exc_info\n exc_info[1]._type_error_fixed = True\n argspec = inspect.formatargspec(*inspect.getargspec(callable))\n args = ', '.join(map(_short_repr, varargs))\n if kwargs and args:\n args += ', '\n if kwargs:\n kwargs = sorted(kwargs.items())\n args += ', '.join(['%s=...' % n for n, v in kwargs])\n gotspec = '(%s)' % args\n msg = f'{exc_info[1]}; got {gotspec}, wanted {argspec}'\n exc_info[1].args = (msg,)\n return exc_info\n\n\ndef _short_repr(v):\n v = repr(v)\n if len(v) > 12:\n v = v[:8] + '...' + v[-4:]\n return v\n\n\ndef fix_call(callable, *args, **kw):\n \"\"\"\n Call ``callable(*args, **kw)`` fixing any type errors that come out.\n \"\"\"\n try:\n val = callable(*args, **kw)\n except TypeError:\n exc_info = fix_type_error(None, callable, args, kw)\n raise exc_info[1] from None\n return val\n\n\ndef lookup_object(spec):\n \"\"\"\n Looks up a module or object from a some.module:func_name specification.\n To just look up a module, omit the colon and everything after it.\n \"\"\"\n parts, target = spec.split(':') if ':' in spec else (spec, None)\n module = __import__(parts)\n\n for part in parts.split('.')[1:] + ([target] if target else []):\n module = getattr(module, part)\n\n return module\n","repo_name":"Pylons/pastedeploy","sub_path":"src/paste/deploy/util.py","file_name":"util.py","file_ext":"py","file_size_in_byte":2333,"program_lang":"python","lang":"en","doc_type":"code","stars":23,"dataset":"github-code","pt":"3"} +{"seq_id":"41377521389","text":"from django.shortcuts import render\nfrom apps.product.form import ProductForm\nfrom django.http import HttpResponseRedirect,HttpResponse,HttpResponseForbidden,JsonResponse\nfrom django.urls import reverse\nfrom apps.product.models import Product\n# Create your views here.\ndef new_product_view(request):\n if request.user.is_authenticated:\n form = ProductForm(request.POST)\n if form.is_valid():\n product = form.save(commit=False)\n product.user = request.user\n product.save()\n return HttpResponseRedirect(reverse('index'))\n return HttpResponse('

product share error~~~

')\n else:\n return HttpResponseForbidden('

not login~~

')\n\ndef vote_product_view(request):\n pid = request.POST.get('pid',None)\n if pid is None:\n return JsonResponse({'errcode':400,'message':'parameter error'})\n if request.user is None or not request.user.is_authenticated:\n return JsonResponse({'errcode':401,'message':'not login'})\n\n\n\n try:\n product = Product.objects.get(pid = pid)\n product.vote(request.user)\n return JsonResponse({'errcode':200,'message':'success','data':{\n 'vote_count':product.vote_count\n }})\n except Product.DoesNotExist:\n return JsonResponse({'errcode':404 ,'message':'product not exist'})\n\n\n pass","repo_name":"xinyuwang1995/lab1","sub_path":"apps/product/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":1354,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"17996458337","text":"# -*- coding: utf-8 -*-\n\"\"\"\nSOAR Telescope - Goodman Pipeline.\n\nGoodman High Throughput Spectrograph Data Reduction Pipeline.\n\nSee:\nhttps://packaging.python.org/en/latest/distributing.html\nhttps://github.com/pypa/sampleproject\n\"\"\"\n\nimport os\nimport sys\n\n# Always prefer setuptools over distutils\nfrom setuptools import setup, find_packages\n\n# To use a consistent encoding\nfrom codecs import open\n\n\nhere = os.path.abspath(os.path.dirname(__file__))\n\n\ndef create_version_py(packagename, version, source_dir='.'):\n package_dir = os.path.join(source_dir, packagename)\n version_py = os.path.join(package_dir, 'version.py')\n\n version_str = \"# This is an automatic generated file please do not edit\\n\" \\\n \"__version__ = '{:s}'\".format(version)\n\n with open(version_py, 'w') as f:\n f.write(version_str)\n\n# Get configuration information from setup.cfg\ntry:\n from ConfigParser import ConfigParser\nexcept ImportError:\n from configparser import ConfigParser\nconf = ConfigParser()\n\n# conf.read([os.path.join(os.path.dirname(__file__), '..', 'setup.cfg')])\nconf.read([os.path.join(os.path.dirname(__file__), 'setup.cfg')])\nmetadata = dict(conf.items('metadata'))\n\nPACKAGENAME = metadata['package_name']\n\nVERSION = metadata['version']\n\nLICENSE = metadata['license']\n\nDESCRIPTION = metadata['description']\n\nLONG_DESCRIPTION = metadata['long_description']\n\nAUTHOR = metadata['author']\n\nAUTHOR_EMAIL = metadata['author_email']\n\nGITHUB_PROJECT = metadata['github_project']\n\n# freezes version information in version.py\ncreate_version_py(PACKAGENAME, VERSION)\n\n\n\n\nsetup(\n name=metadata['package_name'],\n\n # Versions should comply with PEP440. For a discussion on single-sourcing\n # the version across setup.py and the project code, see\n # https://packaging.python.org/en/latest/single_source_version.html\n version=VERSION,\n\n description=DESCRIPTION,\n\n long_description=LONG_DESCRIPTION,\n\n # The project's main homepage.\n url='https://github.com/{:s}0'.format(GITHUB_PROJECT),\n\n # Author details\n author=u'Simon Torres R.',\n\n author_email='storres@ctio.noao.edu, '\n 'cbriceno@ctio.noao.edu',\n\n # Choose your license\n license=LICENSE,\n\n # See https://pypi.python.org/pypi?%3Aaction=list_classifiers\n classifiers=[\n 'Development Status :: 4 - Beta',\n 'Environment :: Console',\n\n # Indicate who your project is intended for\n 'Intended Audience :: Developers',\n 'Intended Audience :: Education',\n 'Intended Audience :: Science/Research',\n\n 'License :: OSI Approved :: {:s}'.format(LICENSE),\n\n # Specify the Python versions you support here. In particular, ensure\n # that you indicate whether you support Python 2, Python 3 or both.\n 'Programming Language :: Python :: 3.5',\n 'Programming Language :: Python :: 3.6',\n\n 'Natural Language :: English',\n\n 'Operating System :: POSIX :: Linux',\n 'Operating System :: POSIX :: Other',\n 'Operating System :: MacOS :: MacOS X',\n\n 'Topic :: Scientific/Engineering :: Astronomy',\n 'Topic :: Scientific/Engineering :: Information Analysis',\n 'Topic :: Software Development :: Libraries :: Python Modules',\n\n ],\n\n # What does your project relate to?\n keywords='soar pipelines astronomy images spectroscopy data reference lamps wavelength',\n\n # You can just specify the packages manually here if your project is\n # simple. Or you can use find_packages().\n\n packages=['goodman_lamps',\n ],\n\n package_dir={'goodman_lamps': 'goodman_lamps'},\n\n package_data={'goodman_lamps': ['data/lamps/*.fits',\n 'data/nist/*.txt']},\n\n)\n\n\n","repo_name":"soar-telescope/goodman_lamps","sub_path":"setup.py","file_name":"setup.py","file_ext":"py","file_size_in_byte":3734,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"14195232950","text":"#I would like to go back through this and do the EDA after filtering for 'Girls' and 'Juniors'\n#Currently this includes all data\n\nimport json\nimport os\nfrom this import d\nfrom elosports.elo import Elo\nfrom collections import Counter\n\n# Read in path names into a list\ndirectory = os.fsencode(\n \"/Users/cameron/Documents/SMU_DS/Capstone/SMU_Capstone_Project/Raw Data/Match Data/\"\n)\nfile_path_holder = []\nfor file in os.listdir(directory):\n filename = os.fsdecode(file)\n if filename.endswith(\".json\"):\n file_path_holder.append(str(directory)[2:-1] + str(filename))\n\n# Extend contents of all files into a list\n# MUST SORT FILE PATHS OR ORDER COULD CHANGE\nfile_path_holder = sorted(file_path_holder)\nfull_vball_data = []\nfor path in file_path_holder:\n file = open(path)\n full_vball_data.extend(json.load(file))\n file.close()\n\n# Look at tournament info\nfull_vball_data[0].keys() # Tournament and type are unique to tournament\nfull_vball_data[0][\"divisions\"][0].keys()\n\n# Question: Are 'latitude', 'longitude', 'timeZoneName', 'googleLocation' the same within all tournaments\n# Answer: Only one division in one tournament doesn't follow this rule West Coast AAU Junior Olympic Games 2019 16 U Girls\n# Index: Tournament 21 and division 1\n\n# Loop to find any index that does not match\nfor i in range(len(full_vball_data)):\n for j in range(len(full_vball_data[i][\"divisions\"])):\n if (\n full_vball_data[i][\"divisions\"][j][\"latitude\"]\n != full_vball_data[i][\"divisions\"][0][\"latitude\"]\n or full_vball_data[i][\"divisions\"][j][\"longitude\"]\n != full_vball_data[i][\"divisions\"][0][\"longitude\"]\n or full_vball_data[i][\"divisions\"][j][\"timeZoneName\"]\n != full_vball_data[i][\"divisions\"][0][\"timeZoneName\"]\n or full_vball_data[i][\"divisions\"][j][\"googleLocation\"]\n != full_vball_data[i][\"divisions\"][0][\"googleLocation\"]\n ):\n print(\"error:\", i, j)\n\n# Details on unmatched data\nfull_vball_data[21][\"tournament\"]\nfull_vball_data[21][\"type\"]\nfull_vball_data[21][\"divisions\"][1].keys()\nkeys = [\"division\", \"gender\", \"ageType\", \"latitude\", \"longitude\", \"timeZoneName\"]\nfor i in range(len(full_vball_data[21][\"divisions\"])):\n for key in keys:\n full_vball_data[21][\"divisions\"][i].get(key)\n print(\"\\n\")\n\n# Look if the keys are consistent within each match\n# We find that the players can be listed under playerIds or playerProfileIds\n# There are fewer instances of playerProfileIds\nfull_vball_data[0][\"divisions\"][0][\"matches\"][0].keys()\n\nholder = []\nfor i in range(len(full_vball_data)):\n for j in range(len(full_vball_data[i][\"divisions\"])):\n for z in range(len(full_vball_data[i][\"divisions\"][j][\"matches\"])):\n temp = list(full_vball_data[i][\"divisions\"][j][\"matches\"][z].keys())\n holder.extend(temp)\n \nCounter(holder)\n\n\n\n# Look at number of games within each match. Consider bracket/pool play and isMatch = T/F\n\n# We find that there can be 1, 2, 3, 4, 5, and 7 games (most are 3 or less)\n# There are many more pool play matches and many more isMatch=F\n# isMatch=True is 3 games about 98% of the time (weirdly there are 60 1 game matches)\n# isMatch=True can apply to both bracket and pool play\n# isMatch=False is 1 or 2 games 99.7% of the time (mainly 1)\n# Pool games are mainly 1 but sometimes 2 and 3\n# Bracket games are mainly 1 but sometimes 3 (Rarely 2 like pool play)\nholder = [] # holder is all games\nismatch = []\ntrue_ismatch = []\nfalse_ismatch = []\nbracket_or_pool = []\npool_games = []\nbracket_games = []\nfor i in range(len(full_vball_data)):\n for j in range(len(full_vball_data[i][\"divisions\"])):\n for z in range(len(full_vball_data[i][\"divisions\"][j][\"matches\"])):\n temp = len(full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"games\"])\n holder.append(temp)\n bracket_or_pool.append(\n full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"type\"]\n )\n ismatch.append(full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"isMatch\"])\n if full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"isMatch\"] == True:\n true_ismatch.append(temp)\n if full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"isMatch\"] == False:\n false_ismatch.append(temp)\n if full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"type\"] == \"Bracket\":\n bracket_games.append(temp)\n if full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"type\"] == \"Pool\":\n pool_games.append(temp)\n\nCounter(holder)\nCounter(ismatch)\nCounter(true_ismatch)\nCounter(false_ismatch)\nCounter(bracket_or_pool)\nCounter(pool_games)\nCounter(bracket_games)\n\n# Check if match ID is unique\n# Confirmed it is not but no match ID is used more than twice\n# Used example of duplicate ID in this loop to verify that the matches were actually unique\nholder = []\nfor i in range(len(full_vball_data)):\n for j in range(len(full_vball_data[i][\"divisions\"])):\n for z in range(len(full_vball_data[i][\"divisions\"][j][\"matches\"])):\n temp = full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"id\"]\n holder.append(temp)\n if temp == 33654: # Example of match ID that shows up more than once\n print(full_vball_data[i][\"divisions\"][j][\"matches\"][z])\n\nid_count = Counter(holder)\nCounter(id_count.values())\n\n# Verify there are two players on every home and away team\n\n# Out of 111328 teams, 97905 have two players\n# Team Size: {2: 97905, 4: 9509, 5: 1415, 3: 823, 1: 613, 6: 564, 0: 282, 11: 80, 10: 66, 7: 28, 9: 18, 12: 15, 8: 6, 14: 4})\n\n# Out of 55664 matches 53812 have the same team size on both sides\n# Matching: {True: 53812, False: 1852}\n\n# Out of 53812 matches with same team size, 48838 were 2 vs. 2 matches\n# Matching by size: {2: 48838, 4: 4063, 3: 323, 1: 216, 6: 160, 5: 121, 0: 77, 11: 8, 10: 6}\n\nholder = [] # holder represents team size\nmatching = [] # does team size match within a game\nmatching_by_size = (\n []\n) # size of teams when they match (only show size of one team of match)\n\nfor i in range(len(full_vball_data)):\n for j in range(len(full_vball_data[i][\"divisions\"])):\n for z in range(len(full_vball_data[i][\"divisions\"][j][\"matches\"])):\n temp = full_vball_data[i][\"divisions\"][j][\"matches\"][z].get(\n \"playerIds\", \"skip\"\n )\n if temp == \"skip\":\n temp = full_vball_data[i][\"divisions\"][j][\"matches\"][z].get(\n \"playerProfileIds\"\n )\n holder.append(len(temp.get(\"home\")))\n holder.append(len(temp.get(\"away\")))\n matching.append(len(temp.get(\"home\")) == len(temp.get(\"away\")))\n if len(temp.get(\"home\")) == len(temp.get(\"away\")):\n matching_by_size.append(len(temp.get(\"home\")))\n # holder.append(sorted(temp.get('home')))\n # holder.append(sorted(temp.get('away')))\n # if len(temp.get('home'))==14 or len(temp.get('away'))==14: #Example of match ID that shows up more than once\n # print(full_vball_data[i]['divisions'][j]['matches'][z])\n if len(temp.get(\"home\")) != len(temp.get(\"away\")):\n print(full_vball_data[i][\"divisions\"][j][\"matches\"][z])\n\nCounter(holder)\nCounter(matching)\nCounter(matching_by_size)\n\n# Look at count of game result types\n# 92% of matches have a result (all 'no result' games have no home or away scores)\n# ~20% of matches with a result have the max home or away score not equal to the 'to' score for the game\n# 64% of the above have a max score lower than the 'to' score\n# 90% of the above have no scores\n# Weirdly 865 games have inputted scores and a result which don't reach the 'to' score\nholder = []\nholder2 = []\nholder3 = []\nfor i in range(len(full_vball_data)):\n for j in range(len(full_vball_data[i][\"divisions\"])):\n for z in range(len(full_vball_data[i][\"divisions\"][j][\"matches\"])):\n for g in range(\n len(full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"games\"])\n ):\n temp = full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"games\"][g][\n \"winner\"\n ]\n holder.append(temp)\n if (\n full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"games\"][g][\n \"winner\"\n ]\n == None\n ):\n holder2.append(\n full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"games\"][g]\n )\n\n game_path = full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"games\"][g]\n\n # Use comments to pick one of three if statements below\n if (\n max(game_path[\"away\"], game_path[\"home\"]) != game_path[\"to\"]\n and full_vball_data[i][\"divisions\"][j][\"matches\"][z][\"type\"] != None\n ):\n holder3.append(game_path)\n # if max(game_path['away'],game_path['home'])1 else \"\"\n fv.StartThreads(config=config_file)\n\n rate= TRateAdjuster(30)\n while not fv.IsShutdown():\n fv.DisplayImages()\n rate.Sleep()\n\n fv.StopThreads()\n","repo_name":"akihikoy/fingervision","sub_path":"fv_py/test1.py","file_name":"test1.py","file_ext":"py","file_size_in_byte":546,"program_lang":"python","lang":"en","doc_type":"code","stars":37,"dataset":"github-code","pt":"3"} +{"seq_id":"24606084240","text":"#!/usr/bin/env python3\n\"\"\"\nYOLO(You Only Look Once !!!)\n\"\"\"\nimport numpy as np\nimport tensorflow.keras as K\n\n\nclass Yolo:\n \"\"\"\n YOLO V3\n \"\"\"\n def __init__(self, model_path, classes_path, class_t, nms_t, anchors):\n \"\"\"\n Args:\n model_path: is the path to where a Darknet Keras model is stored\n classes_path: is the path to where the list of class names used for\n the Darknet model, listed in order of index, can be found\n class_t: representing the box score threshold for the initial\n filtering step\n nms_t: representing the IOU threshold for non-max suppression\n anchors:(outputs,anchor_boxes,2)containing all of the anchor boxs\n outputs: is the number of outputs (predictions)\n made by the Darknet model\n anchor_boxes: number of anchor boxes used for each predic\n 2 => [anchor_box_width, anchor_box_height]\n \"\"\"\n # Loading model with Keras\n self.model = K.models.load_model(model_path)\n # Character Meaning\n # 'r' open for reading (default)\n # 'w' open for writing, truncating the file first\n # 'x' open for exclusive creation, failing if the file already exists\n # 'a' open for writing, appending to the end of the file if it exists\n # 'b' binary mode\n # 't' text mode (default)\n # '+' open a disk file for updating (reading and writing)\n # '\n # U' universal newlines mode (deprecated)\n with open(classes_path, 'rt') as fd:\n self.class_names = fd.read().rstrip('\\n').split('\\n')\n self.class_t = class_t\n self.nms_t = nms_t\n self.anchors = anchors\n\n def sigmoid(self, number):\n \"\"\"\n Sigmoid activation function\n \"\"\"\n return 1 / (1 + np.exp(-number))\n\n def process_outputs(self, outputs, image_size):\n \"\"\"\n Args:\n outputs: numpy.ndarray - contains predictions from model\n for single image.\n image_size: numpy.ndarray - images original\n size (image_height, image_width)\n Return:\n tuple - (boxes, box_confidence, box_class_probs)\n boxes: numpy.ndarray - (grid_height, grid_width, anchorboxes, 4)\n 4 => (x1, y1, x2, y2)\n box_confidence: numpy.ndarray - shape\n (grid_height, grid_width, anchor_boxes, 1)\n box_class_probs: numpy.ndarray - shape\n (grid_height, grid_width, anchor_boxes, classes)\n contains class probabilities for each output\n \"\"\"\n IH, IW = image_size[0], image_size[1]\n boxes = [output[..., :4] for output in outputs]\n box_confidence, class_probs = [], []\n cornersX, cornersY = [], []\n\n for output in outputs:\n # Organize grid cells\n gridH, gridW, anchors = output.shape[:3]\n cx = np.arange(gridW).reshape(1, gridW)\n cx = np.repeat(cx, gridH, axis=0)\n cy = np.arange(gridW).reshape(1, gridW)\n cy = np.repeat(cy, gridH, axis=0).T\n\n cornersX.append(np.repeat(cx[..., np.newaxis], anchors, axis=2))\n cornersY.append(np.repeat(cy[..., np.newaxis], anchors, axis=2))\n # box confidence and class probability activations\n box_confidence.append(self.sigmoid(output[..., 4:5]))\n class_probs.append(self.sigmoid(output[..., 5:]))\n\n inputW = self.model.input.shape[1].value\n inputH = self.model.input.shape[2].value\n\n # Predicted boundary box\n for x, box in enumerate(boxes):\n bx = ((self.sigmoid(box[..., 0])+cornersX[x])/outputs[x].shape[1])\n by = ((self.sigmoid(box[..., 1])+cornersY[x])/outputs[x].shape[0])\n bw = ((np.exp(box[..., 2])*self.anchors[x, :, 0])/inputW)\n bh = ((np.exp(box[..., 3])*self.anchors[x, :, 1])/inputH)\n\n # x1\n box[..., 0] = (bx - (bw * 0.5))*IW\n # y1\n box[..., 1] = (by - (bh * 0.5))*IH\n # x2\n box[..., 2] = (bx + (bw * 0.5))*IW\n # y2\n box[..., 3] = (by + (bh * 0.5))*IH\n\n return (boxes, box_confidence, class_probs)\n","repo_name":"Luffy981/holbertonschool-machine_learning","sub_path":"supervised_learning/0x0A-object_detection/1-yolo.py","file_name":"1-yolo.py","file_ext":"py","file_size_in_byte":4335,"program_lang":"python","lang":"en","doc_type":"code","stars":3,"dataset":"github-code","pt":"3"} +{"seq_id":"28883781581","text":"import speech_recognition as sr\nimport pyttsx3 as ttx\nimport pywhatkit\nimport datetime\n\n\nlistener = sr.Recognizer()\nengine = ttx.init()\nvoice = engine.getProperty(\"voices\")\nengine.setProperty(\"voice\", \"french\")\n\n#definissons une fonction pour le parler\n\ndef parler(text):\n engine.say(text)\n engine.runAndWait()\n\n\n#definissons une fonction pour le Ecouter\n\ndef ecouter():\n try:\n with sr.Microphone() as source:\n print(\"Parler maintenant\")\n voix = listener.listen(source)\n command = listener.recognize_google(voix, language=\"fr-FR\")\n command.lower()\n\n except:\n pass\n return command\n\n\n#Definissons la fonction lancer assistant\n\n\ndef lancer_assistant():\n command = ecouter()\n print(command)\n\n\n #pour jouer la musique sur youtube\n if \"chanson\" in command:\n chanteur = command.replace(\"mets la chanson de\", \"\")\n print(chanteur)\n pywhatkit.playonyt(chanteur)\n parler(chanteur)\n #pour avoir l'heur een temps reel\n elif \"heure\" in command:\n heure = datetime.datetime.now().strftime(\"%H:%M\")\n parler(\"Il est\"+heure)\n\n elif \"Bonjour\" in command:\n parler(\"Bonjour comment allez vous ?\")\n\n elif \"concepteur\" in command:\n parler(\"J'ai été créer par le groupe 2, de la quatrième cohorte de orange digital academie \")\n\n #else:\n #parler(\"Bonjour, je suis Rufoce Bot. Votre assistant personnel. Je suis là pour vous faciliter la vie. Vous pouvez me commander d'effectuervdiverses tâches telles que: Vous informer sur l'actualité, sur la metéo, l'heure, la prise de rendez-vous chez votre medecin, commander des achats en ligne, émettre des appels et pleine de chose.\")\n\n\n#pour faire paser en bloucle mon programme\n\nwhile True:\n lancer_assistant()","repo_name":"RUFOS-od/VoiceBot","sub_path":"botTest/jouer_chanson.py","file_name":"jouer_chanson.py","file_ext":"py","file_size_in_byte":1805,"program_lang":"python","lang":"fr","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"12286134411","text":"# (C) Datadog, Inc. 2014-2017\n# (C) Cory Watson 2015-2016\n# All rights reserved\n# Licensed under Simplified BSD License (see LICENSE)\n\n# stdlib\nfrom collections import defaultdict\nfrom urlparse import urlparse\nimport re\n\n# 3rd party\nimport requests\n\n# project\nfrom checks import AgentCheck\n\nDEFAULT_MAX_METRICS = 350\nPATH = \"path\"\nALIAS = \"alias\"\nTYPE = \"type\"\nTAGS = \"tags\"\n\nGAUGE = \"gauge\"\nRATE = \"rate\"\nCOUNTER = \"counter\"\nDEFAULT_TYPE = GAUGE\n\n\nSUPPORTED_TYPES = {\n GAUGE: AgentCheck.gauge,\n RATE: AgentCheck.rate,\n COUNTER: AgentCheck.increment,\n}\n\nDEFAULT_METRIC_NAMESPACE = \"go_expvar\"\n\n\n# See http://golang.org/pkg/runtime/#MemStats\nDEFAULT_GAUGE_MEMSTAT_METRICS = [\n # General statistics\n \"Alloc\", \"TotalAlloc\",\n\n # Main allocation heap statistics\n \"HeapAlloc\", \"HeapSys\", \"HeapIdle\", \"HeapInuse\",\n \"HeapReleased\", \"HeapObjects\",\n\n]\n\nDEFAULT_RATE_MEMSTAT_METRICS = [\n # General statistics\n \"Lookups\", \"Mallocs\", \"Frees\",\n\n # Garbage collector statistics\n \"PauseTotalNs\", \"NumGC\",\n]\n\nDEFAULT_METRICS = [{PATH: \"memstats/%s\" % path, TYPE: GAUGE} for path in DEFAULT_GAUGE_MEMSTAT_METRICS] +\\\n [{PATH: \"memstats/%s\" % path, TYPE: RATE} for path in DEFAULT_RATE_MEMSTAT_METRICS]\n\nGO_EXPVAR_URL_PATH = \"/debug/vars\"\n\nclass GoExpvar(AgentCheck):\n\n def __init__(self, name, init_config, agentConfig, instances=None):\n AgentCheck.__init__(self, name, init_config, agentConfig, instances)\n self._last_gc_count = defaultdict(int)\n\n def _get_data(self, url, instance):\n ssl_params = {\n 'ssl': instance.get('ssl'),\n 'ssl_keyfile': instance.get('ssl_keyfile'),\n 'ssl_certfile': instance.get('ssl_certfile'),\n 'ssl_verify': instance.get('ssl_verify'),\n }\n for key, param in ssl_params.items():\n if param is None:\n del ssl_params[key]\n\n # Load SSL configuration, if available.\n # ssl_verify can be a bool or a string (http://docs.python-requests.org/en/latest/user/advanced/#ssl-cert-verification)\n if isinstance(ssl_params.get('ssl_verify'), bool) or isinstance(ssl_params.get('ssl_verify'), basestring):\n verify = ssl_params.get('ssl_verify')\n else:\n verify = None\n if ssl_params.get('ssl_certfile') and ssl_params.get('ssl_keyfile'):\n cert = (ssl_params.get('ssl_certfile'), ssl_params.get('ssl_keyfile'))\n elif ssl_params.get('ssl_certfile'):\n cert = ssl_params.get('ssl_certfile')\n else:\n cert = None\n\n resp = requests.get(\n url,\n timeout=10,\n verify=verify,\n cert=cert\n )\n resp.raise_for_status()\n return resp.json()\n\n def _load(self, instance):\n url = instance.get('expvar_url')\n if not url:\n raise Exception('GoExpvar instance missing \"expvar_url\" value.')\n\n parsed_url = urlparse(url)\n # if no path is specified we use the default one\n if not parsed_url.path:\n url = parsed_url._replace(path=GO_EXPVAR_URL_PATH).geturl()\n\n tags = instance.get('tags', [])\n tags.append(\"expvar_url:%s\" % url)\n data = self._get_data(url, instance)\n metrics = DEFAULT_METRICS + instance.get(\"metrics\", [])\n max_metrics = instance.get(\"max_returned_metrics\", DEFAULT_MAX_METRICS)\n namespace = instance.get('namespace', DEFAULT_METRIC_NAMESPACE)\n return data, tags, metrics, max_metrics, url, namespace\n\n def get_gc_collection_histogram(self, data, tags, url, namespace):\n num_gc = data.get(\"memstats\", {}).get(\"NumGC\")\n pause_hist = data.get(\"memstats\", {}).get(\"PauseNs\")\n last_gc_count = self._last_gc_count[url]\n if last_gc_count == num_gc:\n # No GC has run. Do nothing\n return\n start = last_gc_count % 256\n end = (num_gc + 255) % 256 + 1\n if start < end:\n values = pause_hist[start:end]\n else:\n values = pause_hist[start:] + pause_hist[:end]\n\n self._last_gc_count[url] = num_gc\n\n for value in values:\n self.histogram(\n self.normalize(\"memstats.PauseNs\", namespace, fix_case=True),\n value, tags=tags)\n\n def check(self, instance):\n data, tags, metrics, max_metrics, url, namespace = self._load(instance)\n self.get_gc_collection_histogram(data, tags, url, namespace)\n self.parse_expvar_data(data, tags, metrics, max_metrics, namespace)\n\n def parse_expvar_data(self, data, tags, metrics, max_metrics, namespace):\n '''\n Report all the metrics based on the configuration in instance\n If a metric is not well configured or is not present in the payload,\n continue processing metrics but log the information to the info page\n '''\n count = 0\n for metric in metrics:\n path = metric.get(PATH)\n metric_type = metric.get(TYPE, DEFAULT_TYPE)\n metric_tags = list(metric.get(TAGS, []))\n metric_tags += tags\n alias = metric.get(ALIAS)\n\n if not path:\n self.warning(\"Metric %s has no path\" % metric)\n continue\n\n if metric_type not in SUPPORTED_TYPES:\n self.warning(\"Metric type %s not supported for this check\" % metric_type)\n continue\n\n keys = path.split(\"/\")\n values = self.deep_get(data, keys)\n\n if len(values) == 0:\n self.warning(\"No results matching path %s\" % path)\n continue\n\n tag_by_path = alias is not None\n\n for traversed_path, value in values:\n actual_path = \".\".join(traversed_path)\n path_tag = [\"path:%s\" % actual_path] if tag_by_path else []\n\n metric_name = alias or self.normalize(actual_path, namespace, fix_case=True)\n\n try:\n float(value)\n except ValueError:\n self.log.warning(\"Unreportable value for path %s: %s\" % (path, value))\n continue\n\n if count >= max_metrics:\n self.warning(\"Reporting more metrics than the allowed maximum. \"\n \"Please contact hello@serverdensity.com for more information.\")\n return\n\n SUPPORTED_TYPES[metric_type](self, metric_name, value, metric_tags + path_tag)\n count += 1\n\n def deep_get(self, content, keys, traversed_path=None):\n '''\n Allow to retrieve content nested inside a several layers deep dict/list\n\n Examples: -content: {\n \"key1\": {\n \"key2\" : [\n {\n \"name\" : \"object1\",\n \"value\" : 42\n },\n {\n \"name\" : \"object2\",\n \"value\" : 72\n }\n ]\n }\n }\n -keys: [\"key1\", \"key2\", \"1\", \"value\"] would return [([\"key1\", \"key2\", \"1\", \"value\"], 72)]\n -keys: [\"key1\", \"key2\", \"1\", \"*\"] would return [([\"key1\", \"key2\", \"1\", \"value\"], 72), ([\"key1\", \"key2\", \"1\", \"name\"], \"object2\")]\n -keys: [\"key1\", \"key2\", \"*\", \"value\"] would return [([\"key1\", \"key2\", \"1\", \"value\"], 72), ([\"key1\", \"key2\", \"0\", \"value\"], 42)]\n '''\n\n if traversed_path is None:\n traversed_path = []\n\n if keys == []:\n return [(traversed_path, content)]\n\n key = keys[0]\n regex = \"\".join([\"^\", key, \"$\"])\n try:\n key_rex = re.compile(regex)\n except Exception:\n self.warning(\"Cannot compile regex: %s\" % regex)\n return []\n\n results = []\n for new_key, new_content in self.items(content):\n if key_rex.match(new_key):\n results.extend(self.deep_get(new_content, keys[1:], traversed_path + [str(new_key)]))\n return results\n\n def items(self, object):\n if isinstance(object, list):\n for new_key, new_content in enumerate(object):\n yield str(new_key), new_content\n elif isinstance(object, dict):\n for new_key, new_content in object.iteritems():\n yield str(new_key), new_content\n else:\n self.log.warning(\"Could not parse this object, check the json\"\n \"served by the expvar\")\n","repo_name":"serverdensity/sd-agent-core-plugins","sub_path":"go_expvar/check.py","file_name":"check.py","file_ext":"py","file_size_in_byte":8835,"program_lang":"python","lang":"en","doc_type":"code","stars":5,"dataset":"github-code","pt":"3"} +{"seq_id":"70724438163","text":"\n\n\n\nfrom pynput.mouse import Listener\n\ndef on_click(x, y, button, pressed):\n # 监听鼠标点击\n print('{0} at {1}'.format('Pressed' if pressed else 'Released', (x, y)))\n if not pressed:\n # Stop listener\n return False\nwhile True:\n try:\n listener.join()\n except KeyboardInterrupt:\n \n break\n","repo_name":"cjx1996/vscode_Pythoncode","sub_path":"Study python without teacher/get_the_location.py","file_name":"get_the_location.py","file_ext":"py","file_size_in_byte":342,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"35658637881","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Dec 21 07:16:39 2022\n\n@author: AJPfleger\n\nhttps://adventofcode.com/2022/day/21\n\"\"\"\n\n\nimport re\nimport operator\nimport math\n\n\ndef getMonkeys(filename):\n\n file = open(filename, \"r\")\n Lines = file.readlines()\n\n monkeys = {}\n for l in Lines:\n m = re.match(\"(\\w+): (.+)\", l.strip())\n k, v = m.groups()\n\n monkeys.update({k: v})\n\n return monkeys\n\n\ndef parseMonkeyValue(v):\n m = re.match(\"(\\w+) (\\D) (\\w+)\", v.strip())\n ma, op, mb = m.groups()\n return ma, op, mb\n\n\ndef monkeyOp(monkeys, monk):\n\n operators = {\n \"+\": operator.add,\n \"-\": operator.sub,\n \"*\": operator.mul,\n \"/\": operator.truediv,\n }\n\n v = monkeys[monk]\n if v.isnumeric():\n value = int(v)\n elif v == \"nan\":\n value = float(\"nan\")\n else:\n ma, op, mb = parseMonkeyValue(v)\n\n value = operators.get(op)(monkeyOp(monkeys, ma), monkeyOp(monkeys, mb))\n\n return value\n\n\ndef invMonkeyOp(monkeys, monk):\n\n ma, _, mb = parseMonkeyValue(monkeys[monk])\n\n va = monkeyOp(monkeys, ma)\n vb = monkeyOp(monkeys, mb)\n humn = va if math.isnan(vb) else vb\n monk = mb if math.isnan(vb) else ma\n\n hNotFound = True\n while hNotFound:\n ma, op, mb = parseMonkeyValue(monkeys[monk])\n\n va = monkeyOp(monkeys, ma)\n vb = monkeyOp(monkeys, mb)\n vOp = va if math.isnan(vb) else vb\n monk = mb if math.isnan(vb) else ma\n\n if op == \"+\":\n humn -= vOp\n elif op == \"-\":\n if math.isnan(va):\n humn += vOp\n else:\n humn -= vOp\n humn *= -1\n elif op == \"*\":\n humn /= vOp\n else:\n if math.isnan(va):\n humn *= vOp\n else:\n humn /= vOp\n humn = 1 / humn\n\n if monk == \"humn\":\n hNotFound = False\n\n return humn\n\n\nfilename = \"input.txt\"\nmonkeys = getMonkeys(filename)\n\n\nprint(\"*** Part 1 ***\")\nroot = int(monkeyOp(monkeys, \"root\"))\nprint(f\"root = {root}\")\n\n\nprint(\"\\n*** Part 2 ***\")\nmonkeys[\"humn\"] = \"nan\"\nhumn = int(invMonkeyOp(monkeys, \"root\"))\nprint(f\"humn = {humn}\")\n","repo_name":"AJPfleger/advent-of-code","sub_path":"2022/day21/day21.py","file_name":"day21.py","file_ext":"py","file_size_in_byte":2220,"program_lang":"python","lang":"en","doc_type":"code","stars":2,"dataset":"github-code","pt":"3"} +{"seq_id":"7743534266","text":"import pygame\n\n# Initialize Pygame\npygame.init()\n\n# Define the screen size and title\nscreen = pygame.display.set_mode((400, 300))\npygame.display.set_caption(\"Pygame Timer\")\n\n# Define the timer font\ntimer_font = pygame.font.Font(None, 36)\n\n# Define color themes\nthemes = {\n \"red\": (255, 0, 0),\n \"green\": (0, 255, 0),\n \"blue\": (0, 0, 255)\n}\n\n# Set the default theme\ntheme = \"red\"\n\n# Set the timer duration in seconds\nduration = 10\n\n# Set the start time\nstart_time = pygame.time.get_ticks()\n\n# Run the game loop\nrunning = True\nwhile running:\n # Handle events\n for event in pygame.event.get():\n if event.type == pygame.QUIT:\n running = False\n\n # Check for key events to switch themes\n if event.type == pygame.KEYDOWN:\n if event.unicode == \"r\":\n theme = \"red\"\n elif event.unicode == \"g\":\n theme = \"green\"\n elif event.unicode == \"b\":\n theme = \"blue\"\n\n # Clear the screen\n screen.fill((255, 255, 255))\n\n # Calculate the time remaining\n time_remaining = duration - (pygame.time.get_ticks() - start_time) / 1000\n\n # Render the timer text\n timer_text = timer_font.render(str(time_remaining), True, themes[theme])\n timer_rect = timer_text.get_rect()\n timer_rect.center = (200, 150)\n\n # Draw the timer\n screen.blit(timer_text, timer_rect)\n\n # Update the display\n pygame.display.update()\n\n # End the game loop when the timer is up\n if time_remaining <= 0:\n running = False\n\n# Quit Pygame\npygame.quit()\n","repo_name":"tlcDataScience/pygame-learning","sub_path":"Pygame build-up/L10/code_2.py","file_name":"code_2.py","file_ext":"py","file_size_in_byte":1563,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"32615470465","text":"import time\nimport json\nclass SaveLog:\n def __init__(self, _file_name, _now_time, _start_time, _end_time):\n self._file_name = _file_name \n self._now_time = _now_time\n self._start_time = _start_time\n self._end_time = _end_time\n\n\nclass LogFile(SaveLog):\n\n def __init__(self, _file_name, _now_time, _start_time, _end_time):\n super().__init__(_file_name, _now_time, _start_time, _end_time)\n\n def save_csv(self):\n with open(self._file_name+\".csv\", \"a\") as file:\n file.write(\"%s, %s, %s, %s \\n\" %(\n self._now_time.now,\n time.strftime('%Y-%m-%d %H:%M:%s', time.gmtime(self._start_time)),\n time.strftime('%Y-%m-%d %H:%M:%s', time.gmtime(self._end_time)),\n str(self._end_time - self._start_time)))\n\n\n def save_json(self): \n _json = {\n \"now\": str(self._now_time.now), \n \"start\": time.strftime(\"\"\"%Y-%m-%d %H:%M:%S\"\"\", time.gmtime(self._start_time)), \n \"end\": time.strftime(\"\"\"%Y-%m-%d %H:%M:%S\"\"\", time.gmtime(self._end_time)), \n \"time\": float(self._end_time - self._start_time)\n }\n with open(self._file_name+\".json\", \"a\") as file:\n json.dump(_json, file)\n","repo_name":"nanaones/psycopg-test","sub_path":"LogFIle.py","file_name":"LogFIle.py","file_ext":"py","file_size_in_byte":1385,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"71531345043","text":"\"\"\"empty message\n\nRevision ID: 5e1a86d9fa1d\nRevises: 7c9c44863173\nCreate Date: 2019-07-10 18:55:04.065504\n\n\"\"\"\nfrom alembic import op\nimport sqlalchemy as sa\n\n\n# revision identifiers, used by Alembic.\nrevision = '5e1a86d9fa1d'\ndown_revision = '7c9c44863173'\nbranch_labels = None\ndepends_on = None\n\n\ndef upgrade():\n # ### commands auto generated by Alembic - please adjust! ###\n op.add_column('nodegroup', sa.Column('cpu_total', sa.Integer(), nullable=True))\n op.add_column('nodegroup', sa.Column('memory_total', sa.Float(), nullable=True))\n # ### end Alembic commands ###\n\n\ndef downgrade():\n # ### commands auto generated by Alembic - please adjust! ###\n op.drop_column('nodegroup', 'memory_total')\n op.drop_column('nodegroup', 'cpu_total')\n # ### end Alembic commands ###\n","repo_name":"gnydick/orch","sub_path":"migrations/versions/5e1a86d9fa1d_.py","file_name":"5e1a86d9fa1d_.py","file_ext":"py","file_size_in_byte":797,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"69883027283","text":"from classes import Housing, Squads, Leaders, Children\nimport json\n\nCHILD1 = []\nCHILD = []\nSQUAD1 = []\nSQUAD = []\nLEADER = []\nHOUS = []\n\ndef ConvertFromDictToCLass(res):\n result = {}\n b = []\n key = res.keys()\n for i in key:\n for j in res[i]:\n a = []\n key_child = list(j.keys())\n for k in key_child:\n a.append(j[k])\n if a not in b:\n b.append(a)\n CHILD1.append(Children(a[0], a[1], a[2], a[3]))\n\n a = []\n count_squad = 0\n for i in CHILD1:\n key_squad = list(i.squad.keys())\n list_of_squad = [i.squad[key_squad[0]], i.squad[key_squad[1]], i.squad[key_squad[2]],\n i.squad[key_squad[3]], i.squad[key_squad[4]]]\n if list_of_squad not in a:\n a.append(list_of_squad)\n SQUAD1.append(Squads(a[count_squad][0], a[count_squad][1], a[count_squad][2],\n a[count_squad][3], a[count_squad][4]))\n count_squad += 1\n\n a = []\n b = []\n count_hous = 0\n count_lead = 0\n for i in SQUAD1:\n key_leader = list(i.leader.keys())\n key_housing = list(i.hausing.keys())\n list_of_lead = [i.leader[key_leader[0]], i.leader[key_leader[1]], i.leader[key_leader[2]]]\n if list_of_lead not in a:\n a.append(list_of_lead)\n LEADER.append(Leaders(a[count_lead][0], a[count_lead][1], a[count_lead][2]))\n count_lead+=1\n list_of_hous = [i.hausing[key_housing[0]], i.hausing[key_housing[1]], i.hausing[key_housing[2]]]\n if list_of_hous not in b:\n b.append(list_of_hous)\n HOUS.append(Housing(b[count_hous][0], b[count_hous][1], b[count_hous][2]))\n count_hous+=1\n result['LEADER'] = LEADER\n result['HOUS'] = HOUS\n\n for i in SQUAD1:\n for j in LEADER:\n if i.leader[list(i.leader.keys())[0]] == j.name:\n leader = j\n break\n for j in HOUS:\n if i.hausing[list(i.hausing.keys())[0]] == j.number:\n house = j\n break\n SQUAD.append(Squads(i.number, i.amount, i.age, leader.name, house.number))\n result['SQUAD'] = SQUAD\n\n for i in CHILD1:\n for j in SQUAD:\n if i.squad[list(i.squad.keys())[0]] == j.number:\n squad = j\n break\n CHILD.append(Children(i.name, i.age, squad.number, i.phone))\n result['CHILD'] = CHILD\n\n return result\n","repo_name":"DashaEvstratova/BaseDate","sub_path":"out.py","file_name":"out.py","file_ext":"py","file_size_in_byte":2492,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"17157259116","text":"# (c) Jordi Cortadella 2022\n# For the FRAME Project.\n# Licensed under the MIT License (see https://github.com/jordicf/FRAME/blob/master/LICENSE.txt).\n\n\"\"\"\nModule to represent netlists\n\"\"\"\n\nimport math\nfrom itertools import combinations\nfrom frame.netlist.module import Module\nfrom frame.netlist.netlist_types import HyperEdge\nfrom frame.netlist.yaml_read_netlist import parse_yaml_netlist\nfrom frame.netlist.yaml_write_netlist import dump_yaml_modules, dump_yaml_edges\nfrom frame.geometry.geometry import Rectangle, parse_yaml_rectangle\nfrom frame.utils.keywords import KW_MODULES, KW_NETS\nfrom frame.utils.utils import TextIO_String, write_yaml\n\n# Data structure to represent the rectangles associated to a module.\n# For each module, a list of rectangles is defined.\n# Each rectangle is a list of four values: [x, y, w, h].\n# Optionally, a fifth value (string representing the regions) can be added, e.g., [3, 5, 2, 8.5, \"dsp\"]\nModule2Rectangles = dict[str, list[list[float | str]]]\n\n\nclass Netlist:\n \"\"\"\n Class to represent a netlist\n \"\"\"\n\n _modules: list[Module] # List of modules\n _edges: list[HyperEdge] # List of edges, with references to modules\n _name2module: dict[str, Module] # Map from module names to modules\n _rectangles: list[Rectangle] | None # List of rectangles\n\n def __init__(self, stream: TextIO_String):\n \"\"\"\n Constructor of a netlist from a file or from a string of text\n :param stream: name of the YAML file (str) or handle to the file\n \"\"\"\n\n self._modules, _named_edges = parse_yaml_netlist(stream)\n self._name2module = {b.name: b for b in self._modules}\n self._create_rectangles()\n\n # Edges\n self._edges = []\n for e in _named_edges:\n modules: list[Module] = []\n for b in e.modules:\n assert b in self._name2module, f'Unknown module {b} in edge'\n modules.append(self._name2module[b])\n assert e.weight > 0, f'Incorrect edge weight {e.weight}'\n self._edges.append(HyperEdge(modules, e.weight))\n\n @property\n def num_modules(self) -> int:\n \"\"\"Number of modules of the netlist\"\"\"\n return len(self._modules)\n\n @property\n def modules(self) -> list[Module]:\n \"\"\"List of modules of the netlist\"\"\"\n return self._modules\n\n @property\n def num_edges(self) -> int:\n \"\"\"Number of hyperedges of the netlist\"\"\"\n return len(self._edges)\n\n @property\n def edges(self) -> list[HyperEdge]:\n \"\"\"List of hyperedges of the netlist\"\"\"\n return self._edges\n\n @property\n def wire_length(self) -> float:\n \"\"\"Total wire length to construct the netlist (sum of netlist hyperedges wire lengths)\"\"\"\n return sum([e.wire_length for e in self.edges])\n\n @property\n def num_rectangles(self) -> int:\n \"\"\"Number of rectangles of all modules of the netlist\"\"\"\n return len(self.rectangles)\n\n @property\n def rectangles(self) -> list[Rectangle]:\n \"\"\"Rectangles of all modules of the netlist\"\"\"\n if self._rectangles is None:\n self._create_rectangles()\n assert self._rectangles is not None\n return self._rectangles\n\n def get_module(self, name: str) -> Module:\n \"\"\"\n Returns the module with a certain name\n :param name: name mof the module\n :return: the module\n \"\"\"\n assert name in self._name2module, f'Module {name} does not exist'\n return self._name2module[name]\n\n def create_squares(self) -> list[Module]:\n \"\"\"\n Creates a default rectangle (square) for each module that has no rectangles\n :return: The list of modules for which a square has been created.\n \"\"\"\n modules = []\n for m in self.modules:\n if m.num_rectangles == 0:\n m.create_square()\n self._clean_rectangles()\n modules.append(m)\n return modules\n\n def create_stogs(self) -> None:\n \"\"\"\n Creates the Single-Trunk Orthogons (STOGs) for each module (if they can be identified as STOGs).\n The location of the rectangles of each module a labelled according to their role. If no STOG\n can be identified, the rectangles are labelled as NO_POLYGON\n \"\"\"\n for m in self.modules:\n m.create_stog()\n\n def all_soft_modules_have_stogs(self) -> bool:\n \"\"\"Indicates whether all soft modules have Single-Trunk Orthogons\"\"\"\n return all(m.is_hard or m.has_stog for m in self.modules)\n\n def assign_rectangles(self, m2r: Module2Rectangles) -> None:\n \"\"\"\n Defines the rectangles of the modules of the netlist\n :param m2r: The rectangles associated to every module\n \"\"\"\n for module_name, list_rect in m2r.items():\n m = self.get_module(module_name)\n m.clear_rectangles()\n for r in list_rect:\n m.add_rectangle(parse_yaml_rectangle(r, m.is_fixed, m.is_hard))\n self._clean_rectangles()\n\n def fixed_rectangles(self) -> list[Rectangle]:\n \"\"\"\n Returns the list of fixed rectangles\n :return: the list of fixed rectangles\n \"\"\"\n return [r for r in self.rectangles if r.fixed]\n\n def write_yaml(self, filename: str = None) -> None | str:\n \"\"\"\n Writes the netlist into a YAML file. If no file name is given, a string with the yaml contents\n is returned\n :param filename: name of the output file\n \"\"\"\n data = {\n KW_MODULES: dump_yaml_modules(self.modules),\n KW_NETS: dump_yaml_edges(self.edges)\n }\n return write_yaml(data, filename)\n\n def _clean_rectangles(self) -> None:\n \"\"\"\n Removes all the rectangles of the netlist\n \"\"\"\n self._rectangles = None\n\n def _create_rectangles(self) -> None:\n \"\"\"\n Creates the list of rectangles of the netlist. For hard nodes without rectangles,\n it creates a square. It also defines epsilon, in case it was not defined\n \"\"\"\n self._clean_rectangles()\n # Check that all fixed nodes have either a center or a rectangle\n smallest_distance = math.inf\n for m in self.modules:\n assert m.is_terminal or m.is_soft or m.center is not None or m.num_rectangles > 0, \\\n f'Module {m.name} is hard and has neither center nor rectangles'\n if m.is_hard and not m.is_terminal and m.num_rectangles == 0:\n m.create_square()\n if m.num_rectangles > 0:\n m.calculate_center_from_rectangles()\n self._rectangles = [r for b in self.modules for r in b.rectangles]\n\n if not Rectangle.epsilon_defined():\n for r in self.rectangles:\n smallest_distance = min(smallest_distance, r.shape.w, r.shape.h)\n for m in self.modules:\n a = m.area()\n if a > 0:\n smallest_distance = min(smallest_distance, math.sqrt(a))\n Rectangle.set_epsilon(smallest_distance * 1e-12)\n\n # Check that hard modules have non-overlapping rectangles.\n for m in self.modules:\n if m.is_hard and not m.is_terminal:\n for r1, r2 in combinations(m.rectangles, 2):\n assert not r1.overlap(r2), f\"Inconsistent hard module {m.name}: overlapping rectangles.\"\n\n # Create stogs\n for m in self.modules:\n if m.num_rectangles > 0:\n m.create_stog()\n\n assert all(not m.flip or m.has_stog for m in self.modules), \"Not all flip modules have a STOG\"\n","repo_name":"jordicf/FRAME","sub_path":"frame/netlist/netlist.py","file_name":"netlist.py","file_ext":"py","file_size_in_byte":7660,"program_lang":"python","lang":"en","doc_type":"code","stars":7,"dataset":"github-code","pt":"3"} +{"seq_id":"18412547702","text":"import matplotlib.pyplot as plt\nfrom mpl_toolkits.mplot3d import Axes3D\nimport numpy as np\n\ndef plot(mat,names):\n ax=plt.subplot(111,projection='3d')\n mat=np.array(mat)\n ax.scatter(mat[:,0],mat[:,1],mat[:,2])\n ax.set_xlabel(names[0])\n ax.set_ylabel(names[1])\n ax.set_zlabel(names[2])\n plt.show()","repo_name":"M0M01992/workspace","sub_path":"log_analysis/plot_mat.py","file_name":"plot_mat.py","file_ext":"py","file_size_in_byte":316,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"39496369422","text":"import telebot \n\n#bot=telebot.TeleBot(token)\n\n#@bot.message_handler(import telebot\n\nAPI_TOKEN = '5699136129:AAE_Cd0DlRUHlGExGFpJJ_pxhvcFpS5q_6Q'\n\nbot = telebot.TeleBot(API_TOKEN)\n@bot.message_handler(func=lambda message: True)\n\ndef echo_message(message):\n\n bot.reply_to(message, \"This bot has been changed to @buttonizebot. Please use that bot instead\")\n\nbot.infinity_polling()\n","repo_name":"musaib821/Master","sub_path":"main.py","file_name":"main.py","file_ext":"py","file_size_in_byte":381,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"14103711085","text":"# ZD_1\n#\n# class Fraction:\n# counter = 0\n#\n# def __init__(self, num: int = 0, den: int = 1):\n# self.num = num\n# self.den = den\n# Fraction.counter += 1\n#\n# def reset(self):\n# self.num = int(input('Введите новый числитель'))\n# self.den = int(input('Введите новый знаменатель'))\n#\n# def sum(self, another: 'Fraction'):\n# sh_den = self.den * another.den\n# sh_num = self.num * another.den + another.num * self.den\n# return Fraction(sh_num, sh_den)\n#\n# def min(self, another: 'Fraction'):\n# sh_den = self.den * another.den\n# sh_num = self.num * another.den - another.num * self.den\n# return Fraction(sh_num, sh_den)\n#\n# def umn(self, another: 'Fraction'):\n# sh_den = self.den * another.den\n# sh_num = self.num * another.num\n# return Fraction(sh_num, sh_den)\n#\n# def dell(self, another: 'Fraction'):\n# sh_den = self.den * another.num\n# sh_num = self.num * another.den\n# return Fraction(sh_num, sh_den)\n#\n# @staticmethod\n# def countter_obj():\n# return Fraction.counter\n#\n# pop = Fraction(3,4)\n# pip = Fraction(1,4)\n#\n# c = pop.sum(pip)\n# print(c.num, c.den)\n#\n# c1 = pop.min(pip)\n# print(c1.num, c1.den)\n#\n# c2 = pop.umn(pip)\n# print(c2.num, c2.den)\n#\n# c3 = pop.dell(pip)\n# print(c3.num, c3.den)\n#\n# print(f'{Fraction.countter_obj()}')\n\n\n# ZD_2\n\n# F = 9/5 * C + 32\n# C = (F - 32) * 5/9\n\n# class Convector:\n# counter_c = 0\n# counter_f = 0\n#\n# def __init__(self, cel, frg):\n# self.cel = cel\n# self.frg = frg\n#\n# @staticmethod\n# def frg_cel(frgg):\n# cell = (frgg - 32) * 5/9\n# Convector.counter_f += 1\n# return cell\n#\n# @staticmethod\n# def cel_frg(celll):\n# ffrg = (9/5) * celll + 32\n# Convector.counter_c += 1\n# return ffrg\n#\n# @staticmethod\n# def counters_opers():\n# return Convector.counter_c, Convector.counter_f\n#\n# m1 = Convector.cel_frg(10)\n# m2 = Convector.frg_cel(50)\n# m3 = Convector.cel_frg(30)\n# m4 = Convector.frg_cel(40)\n# m5 = Convector.cel_frg(70)\n#\n# print(m1, m2, m3, m4, m5)\n#\n# print(f'{Convector.counters_opers()}')\n\n# ZD_3\n\n# mil = m / 1609m\n# m = mil * 1609m\n# funt = gr/ 453gr\n# gr = funt * 453gr\n# akr = km^2 / 4046 km^2\n# km^2 = akr * 4046 km^2\n\nclass Eng_convector:\n counter_oper = 0\n\n @staticmethod\n def mil_m(m):\n Eng_convector.counter_oper += 1\n mil = m / 1609\n return mil\n\n @staticmethod\n def m_mil(mi):\n Eng_convector.counter_oper += 1\n met = mi * 1609\n return met\n\n @staticmethod\n def funt_gram(funt):\n Eng_convector.counter_oper += 1\n gram = funt * 453\n return gram\n\n @staticmethod\n def gram_funt(gra):\n Eng_convector.counter_oper += 1\n funt = gra / 453\n return funt\n\n @staticmethod\n def km_akr(kmm):\n Eng_convector.counter_oper += 1\n akr = kmm / 4046\n return akr\n\n @staticmethod\n def akr_km(akrr):\n Eng_convector.counter_oper += 1\n kkm = akrr * 4046\n return kkm\n\n @staticmethod\n def counter_operations():\n return Eng_convector.counter_oper\n\nprint(Eng_convector.mil_m(100))\nprint(Eng_convector.mil_m(1000))\nprint(Eng_convector.m_mil(10))\nprint(Eng_convector.m_mil(1))\nprint(Eng_convector.funt_gram(10))\nprint(Eng_convector.funt_gram(1))\nprint(Eng_convector.gram_funt(100))\nprint(Eng_convector.gram_funt(1000))\nprint(Eng_convector.km_akr(100))\nprint(Eng_convector.km_akr(10000))\nprint(Eng_convector.akr_km(1))\nprint(Eng_convector.akr_km(10))\nprint(Eng_convector.counter_operations())\n\n","repo_name":"SamuraiJack95/Kurs_DZ","sub_path":"DZ_18/DZ_18.py","file_name":"DZ_18.py","file_ext":"py","file_size_in_byte":3719,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"43023258084","text":"# 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 uuid\n\nimport pretend\nimport pytest\n\nfrom warehouse.admin.views import macaroons as views\nfrom warehouse.macaroons import caveats\n\nfrom ....common.db.accounts import UserFactory\n\n\n@pytest.fixture\ndef raw_token():\n \"\"\"\n A valid macaroon token string, without a database object.\n Intentionally split across lines to prevent false-positive detection by\n scanners, as it's only used for testing.\n \"\"\"\n return (\n \"py\"\n \"pi-AgEIcHlwaS5vcmcCJGQ0ZDhhNzA2LTUxYTEtNDg0NC1hNDlmLTEyZDRiYzNkYjZmOQAABi\"\n \"D6hJOpYl9jFI4jBPvA8gvV1mSu1Ic3xMHmxA4CSA2w_g\"\n )\n\n\nclass TestMacaroonDecodeToken:\n def test_get(self, db_request):\n db_request.method = \"GET\"\n result = views.macaroon_decode_token(db_request)\n\n assert result == {}\n\n def test_post_no_token(self, db_request):\n db_request.method = \"POST\"\n\n with pytest.raises(views.HTTPBadRequest) as excinfo:\n views.macaroon_decode_token(db_request)\n assert excinfo.value.message == \"No token provided.\"\n\n def test_post_invalid_token(self, db_request):\n db_request.method = \"POST\"\n db_request.POST = {\"token\": \"invalid\"}\n\n with pytest.raises(views.HTTPBadRequest) as excinfo:\n views.macaroon_decode_token(db_request)\n assert excinfo.value.message == \"The token cannot be deserialized\"\n\n def test_post_token_found(self, db_request, macaroon_service):\n user = UserFactory.create()\n db_request.user = user\n token, macaroon = macaroon_service.create_macaroon(\n location=\"fake location\",\n description=\"real description\",\n scopes=[caveats.RequestUser(user_id=str(user.id))],\n user_id=user.id,\n )\n db_request.method = \"POST\"\n db_request.POST = {\"token\": token}\n\n result = views.macaroon_decode_token(db_request)\n\n assert result[\"macaroon\"].location == \"fake location\"\n assert result[\"db_record\"].description == \"real description\"\n\n def test_post_token_not_found(self, db_request, macaroon_service, raw_token):\n db_request.method = \"POST\"\n db_request.POST = {\"token\": raw_token}\n\n result = views.macaroon_decode_token(db_request)\n\n # Can't compare the macaroon directly, because it will have a different\n # identifier. https://github.com/ecordell/pymacaroons/issues/62\n assert result[\"macaroon\"].location == \"pypi.org\"\n assert result[\"db_record\"] is None\n\n\nclass TestMacaroonDetail:\n def test_no_macaroon_raises_404(self, db_request):\n db_request.matchdict[\"macaroon_id\"] = uuid.uuid4()\n\n with pytest.raises(views.HTTPNotFound):\n views.macaroon_detail(db_request)\n\n def test_macaroon_exists(self, db_request, macaroon_service):\n user = UserFactory.create()\n _, macaroon = macaroon_service.create_macaroon(\n location=\"test\",\n description=\"test\",\n scopes=[caveats.RequestUser(user_id=str(user.id))],\n user_id=user.id,\n )\n db_request.matchdict[\"macaroon_id\"] = macaroon.id\n\n result = views.macaroon_detail(db_request)\n\n assert result[\"macaroon\"] == macaroon\n\n\nclass TestMacaroonDelete:\n def test_delete_succeeds_and_redirects(self, db_request, macaroon_service):\n user = UserFactory.create()\n db_request.user = user\n _, macaroon = macaroon_service.create_macaroon(\n location=\"test\",\n description=\"test\",\n scopes=[caveats.RequestUser(user_id=str(user.id))],\n user_id=user.id,\n )\n macaroon_id = str(macaroon.id)\n db_request.matchdict[\"macaroon_id\"] = macaroon_id\n db_request.route_url = pretend.call_recorder(\n lambda *a, **kw: \"/admin/macaroons/decode\"\n )\n\n result = views.macaroon_delete(db_request)\n\n assert result.status_code == views.HTTPSeeOther.code\n assert result.location == \"/admin/macaroons/decode\"\n assert macaroon_service.find_macaroon(macaroon_id) is None\n","repo_name":"pypi/warehouse","sub_path":"tests/unit/admin/views/test_macaroons.py","file_name":"test_macaroons.py","file_ext":"py","file_size_in_byte":4592,"program_lang":"python","lang":"en","doc_type":"code","stars":3382,"dataset":"github-code","pt":"3"} +{"seq_id":"38428608890","text":"#coding=utf-8\nfrom bs4 import BeautifulSoup\nimport requests\n\nurl=\"https://www.tripadvisor.cn/Attractions-g60763-Activities-New_York_City_New_York.html\"\n\nwebData=requests.get(url)\nSoup=BeautifulSoup(webData.text,'lxml')\ntitles=Soup.select('div.listing_title > a')\nimages=Soup.select('div.photo_booking.non_generic > a > img[width=\"180\"]')\nscores=Soup.select('div.rating > span.more > a')\nprint(images)\nfor title,image,score in zip(titles,images,scores):\n\n data={\n 'title':title.get_text(),\n 'image':image.get('src'),\n 'score':score.get_text(),\n }\n print(data)","repo_name":"13661892653/workspace","sub_path":"pyCode/crawDemo/New_York.py","file_name":"New_York.py","file_ext":"py","file_size_in_byte":588,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"29564066444","text":"from django.contrib.auth import logout, login\nfrom django.contrib.auth.views import LoginView\nfrom django.http import HttpResponse, HttpResponseNotFound, Http404\nfrom django.shortcuts import render, redirect, get_object_or_404\nfrom django.urls import reverse_lazy\nfrom django.views.generic import ListView, DetailView, CreateView, FormView, TemplateView\nfrom django.contrib.auth.mixins import LoginRequiredMixin\n\nfrom .forms import *\nfrom .utils import *\n\n\nclass WomenHome(DataMixin, ListView): # Важно первым ставить именно класс DataMixin\n \"\"\"\n Представление знаменитых женщин без разделения на категории\n \"\"\"\n model = Women # Модель, для которой в этом представлении будут отображаться данные\n template_name = 'women/index.html' # Ссылка на шаблон, использующий данные из модели model текущего класса\n context_object_name = 'posts' # Определяет имя переменной, для использования в данных из текущего класса в ->\n # -> html-шаблоне. По умолчанию называется object_list\n\n def get_context_data(self, *, object_list=None, **kwargs):\n \"\"\"Функция формирует статический (неизменяемые типы данных) и динамический (изменяемые типы данных) контекст для\n последующей п��редачи в html-шаблон\"\"\"\n context = super().get_context_data(**kwargs) # Приобщить к результату работы функции тот контекст, который ->\n # -> уже сформирован в классе. В нашем случае, например, context_object_name. Данные будут переданны в список ->\n # -> context в виде именованных параметров\n c_def = self.get_user_context(title=\"Главная страница\") # Получение стандартного контекста из DataMixin\n return dict(list(context.items()) + list(c_def.items())) # Соединение уникального контекста и контекста ->\n # -> полученного из класса DataMixin\n\n def get_queryset(self):\n return Women.objects.filter(is_published=True).select_related('cat') # .select_related('cat') - таким ->\n # -> образом мы подгружаем названия категорий из таблицы Category одним SQL-запросом (\"жадная\" загрузка ->\n # -> связанных данных)\n\n\n# def index(request):\n# posts = Women.objects.all()\n#\n# context = {\n# 'posts': posts,\n# 'menu': menu,\n# 'title': 'Главная страница',\n# 'cat_selected': 0,\n# }\n#\n# return render(request, 'women/index.html', context=context)\n\n\n# # @login_required # Декоратор, предоставляющий доступ к странице только авторизованным пользователям. Не забудь ->\n# # -> импортировать login_required, если хочешь использовать\n# def about(request):\n# return render(request, 'women/about.html', {'menu': menu, 'title': 'О сайте'})\n\n\nclass AboutPage(DataMixin, TemplateView):\n template_name = 'women/about.html'\n\n def get_context_data(self, *, object_list=None, **kwargs):\n \"\"\"Функция формирует статический (неизменяемые типы данных) и динамический (изменяемые типы данных) контекст для\n последующей передачи в html-шаблон\"\"\"\n context = super().get_context_data(**kwargs)\n c_def = self.get_user_context(title=\"О сайте\")\n return dict(list(context.items()) + list(c_def.items()))\n\n\nclass AddPage(LoginRequiredMixin, DataMixin, CreateView):\n \"\"\"\n Представление страницы добавления новых постов\n \"\"\"\n form_class = AddPostForm\n template_name = 'women/addpage.html'\n success_url = reverse_lazy('home') # URL-адрес для перенаправления ответа при успешной обработке формы. Если ->\n # -> не указать этот параметр, то при успешной обработке формы Django автоматически перенаправит пользователя ->\n # -> на страницу, указанную в классе Women.get_absolute_url(). В нашем случае, это страница вновь добавленного ->\n # -> поста.\n login_url = reverse_lazy('home') # Страница, куда перенаправляет пользователя, в случае, если он не авторизован\n raise_exception = True # В случае, если пользователь не авторизован - raise 403\n\n def get_context_data(self, **kwargs):\n context = super().get_context_data(**kwargs)\n c_def = self.get_user_context(title=\"Добавление статьи\")\n return dict(list(context.items()) + list(c_def.items()))\n\n\n# def addpage(request):\n# if request.method == 'POST':\n# form = AddPostForm(request.POST, request.FILES)\n# if form.is_valid():\n# form.save()\n# return redirect('home')\n# else:\n# form = AddPostForm()\n#\n# return render(request, 'women/addpage.html', {'form': form, 'menu': menu, 'title': 'Добавление статьи'})\n\n\n# def contact(request):\n# return HttpResponse(\"Обратная связь\")\n\n\nclass ContactFormView(DataMixin, FormView):\n \"\"\"\n Представление страницы отправки обратной связи\n \"\"\"\n form_class = ContactForm\n template_name = 'women/contact.html'\n success_url = reverse_lazy('home')\n\n def get_context_data(self, **kwargs):\n context = super().get_context_data(**kwargs)\n c_def = self.get_user_context(title=\"Обратная связь\")\n return dict(list(context.items()) + list(c_def.items()))\n\n # Функция, вызываемая в случае успешно заполненной формы поль��ователем\n def form_valid(self, form):\n print(form.cleaned_data)\n return redirect('home')\n\n\n# def login(request):\n# return HttpResponse(\"Авторизация\")\n\n\ndef page_not_found(request, exception):\n return HttpResponseNotFound(f'

Страница не найдена


{exception}')\n\n\nclass ShowPost(DataMixin, DetailView):\n \"\"\"\n Представление отдельной страницы поста\n \"\"\"\n model = Women\n template_name = 'women/post.html'\n slug_url_kwarg = 'post_slug' # Имя параметра, указанного в URL-адресе, содержащем заголовок. По умолчанию ->\n # -> slug_url_kwarg = 'slug'\n context_object_name = 'post'\n\n def get_context_data(self, **kwargs):\n context = super().get_context_data(**kwargs)\n c_def = self.get_user_context(title=context['post']) # Заголовок в данном случае формируется на основе ->\n # -> контекста, полученного ранее\n return dict(list(context.items()) + list(c_def.items()))\n\n\n# def show_post(request, post_slug):\n# post = get_object_or_404(Women, slug=post_slug)\n#\n# context = {\n# 'post': post,\n# 'menu': menu,\n# 'title': post.title,\n# 'cat_selected': post.cat_id,\n# }\n#\n# return render(request, 'women/post.html', context=context)\n\n\nclass WomenCategory(DataMixin, ListView):\n \"\"\"\n Представление знаменитых женщин по категориям\n \"\"\"\n model = Women\n template_name = 'women/index.html'\n context_object_name = 'posts'\n allow_empty = False\n\n def get_queryset(self):\n return Women.objects.filter(cat__slug=self.kwargs['cat_slug'], is_published=True).select_related('cat') # ->\n # -> Атрибут cat__slug - это атрибут slug из связанной модели Category. То есть мы из модели Women обратились ->\n # -> к атрибуту модели Category. Мы можем это делать через двойное подчеркивание потому что они связаны\n\n def get_context_data(self, *, object_list=None, **kwargs):\n context = super().get_context_data(**kwargs)\n c = Category.objects.get(slug=self.kwargs['cat_slug'])\n c_def = self.get_user_context(title='Категория - ' + str(c.name),\n cat_selected=c.pk)\n return dict(list(context.items()) + list(c_def.items()))\n\n\n# def show_category(request, cat_slug):\n# cats = Category.objects.all()\n# cat = get_object_or_404(Category, slug=cat_slug)\n# posts = Women.objects.all()\n#\n# if len(posts) == 0:\n# raise Http404()\n#\n# context = {\n# 'posts': posts,\n# 'menu': menu,\n# 'cats': cats,\n# 'title': 'Отображение по рубрикам',\n# 'cat_selected': cat.id,\n# }\n#\n# return render(request, 'women/index.html', context=context)\n\n\nclass RegisterUser(DataMixin, CreateView):\n \"\"\"\n Представление страницы регистрации пользователя\n \"\"\"\n form_class = RegisterUserForm\n template_name = 'women/register.html'\n success_url = reverse_lazy('login')\n\n def get_context_data(self, **kwargs):\n context = super().get_context_data(**kwargs)\n c_def = self.get_user_context(title=\"Регистрация\")\n return dict(list(context.items()) + list(c_def.items()))\n\n # Метод, который вызывается при успешной отправленной форме регистрации\n def form_valid(self, form):\n user = form.save() # Сохранение регистрационных данных пользователя в БД\n login(self.request, user) # Функция Django, которая авторизовывает пользователя\n return redirect('home') # Перенаправление пользователя домой после успешной авторизации\n\n\nclass LoginUser(DataMixin, LoginView):\n \"\"\"\n Представление страницы авторизации пользователя\n \"\"\"\n form_class = LoginUserForm\n template_name = 'women/login.html'\n\n def get_context_data(self, **kwargs):\n context = super().get_context_data(**kwargs)\n c_def = self.get_user_context(title=\"Авторизация\")\n return dict(list(context.items()) + list(c_def.items()))\n\n # Куда перенаправлять пользователя после успешной авторизации:\n def get_success_url(self):\n return reverse_lazy('home')\n\n\ndef logout_user(request):\n \"\"\"\n Функция представления logout\n \"\"\"\n logout(request)\n return redirect('login')\n","repo_name":"toptenov/famous-women","sub_path":"women/views.py","file_name":"views.py","file_ext":"py","file_size_in_byte":11568,"program_lang":"python","lang":"ru","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"31650971134","text":"'''\nA script which takes two files as parameters.A file containing tweet file and a dictionary containing sentiment scores for each term and compares them to produce a sentiment.\n'''\n\nimport sys\nimport json\nimport csv\nimport re\nimport operator \nfrom textblob import TextBlob\nfrom collections import Counter\nimport nltk\nfrom nltk.tokenize import word_tokenize\nfrom nltk.corpus import stopwords\nimport string\nimport matplotlib.pyplot as plt\nimport os, sys, codecs\nfrom nltk import bigrams\nfrom wordcloud import WordCloud, STOPWORDS, ImageColorGenerator\n#import classify\nfrom importlib import reload\nimport mainfile\nreload(mainfile)\nfrom mainfile import query, query_location, dictionary, tweet_file, sentiment_location, wc_location\n \ndic={}\n\nprint(\"Gathering Tweet Sentiment............\")\n\n'''Read Dictionary'''\ndef read_dictionary():\n x=0\n with open(dictionary) as f:\n lines=f.readline()\n while(lines!=''):\n lines=f.readline()\n line=lines.split('\\t')\n if(len(line) >= 2):\n scores=line[1]\n dic[line[0]]=int(scores)\n\n'''Plots a pic chart for the sentiment scores'''\ndef tweet_sentiment_plot(cou,pos,neg,neu):\n plt.figure()\n # The slices will be ordered and plotted counter-clockwise.\n labels = 'Positive', 'Negative', 'Neutral'\n values = [pos, neg, neu]\n sub_title=\"Gathered from a set of \", cou ,\"Tweets\"\n plt.pie(values, labels=labels, shadow=True, autopct='%.2f')\n plt.title(query.title() + ' Twitter Sentiment')\n plt.suptitle(sub_title, y=0.99, fontsize=12)\n plt.savefig(sentiment_location)\n\n'''Generate a WordCloud'''\n\ndef tweet_wordcloud():\n text = open(tweet_file).read()\n #text = \" \".join(tweets['text'].values.astype(str))\n no_urls_no_tags = \" \".join([word for word in text.split()\n if 'http' not in word\n and not word.startswith('@')\n and word != 'RT'\n ])\n wc = WordCloud(background_color=\"white\", max_font_size=40, random_state=42, relative_scaling=.5).generate(no_urls_no_tags)\n plt.figure()\n plt.imshow(wc)\n plt.axis(\"off\")\n plt.savefig(wc_location)\n \n'''Read the json time and outputs tweets'''\ndef tweet():\n count=0\n neu=0\n pos=0\n neg=0\n with open(query_location) as fp:\n for line in fp:\n tweet = json.loads(line)\n #print(tweet[\"text\"])\n try:\n with open(tweet_file, \"a\") as f:\n print(tweet[\"text\"],file=f)\n except KeyError:\n continue\n with open(tweet_file) as tweetfile:\n #line=tweetfile.readline()\n for line in tweetfile:\n try:\n #while(line!=''and line!='\\n'):\n scores=0\n tup=line.split(\" \")\n if(len(tup)>=1):\n for x in (tup):\n if x in dic:\n scores=scores + dic[x]\n #print (scores)\n count = count + 1 \n if scores > 1:\n pos = pos +1\n elif scores < 1:\n neg = neg + 1\n else:\n neu+=1\n except KeyError:\n continue\n tweet_sentiment(count, pos, neg , neu)\n\n'''Calculates Sentiment'''\ndef tweet_sentiment(c,p,n,ne):\n count=c\n positive=float(p/c)*100\n negative=float(n/c)*100\n neutral=float(ne/c)*100\n tweet_sentiment_plot(count,positive,negative,neutral)\n print (\"Total tweets\",c)\n #print (\"Positive \",float(p/c)*100,\"%\")\n #print (\"Negative \",float(n/c)*100,\"%\")\n #print (\"Neutral \",float(ne/c)*100,\"%\")\n \n#def tweet_cleaning():\n \n\ndef main():\n dic ={}\n open(tweet_file, \"w\")\n read_dictionary\n tweet()\n print(\"Tweet Sentiment pie chart generated at:\", sentiment_location)\n tweet_wordcloud()\n print(\"Tweet Word Cloud generated at:\", wc_location)\nif __name__ == '__main__':\n main()\n","repo_name":"aswinpai/TwitSenti","sub_path":"sentiment.py","file_name":"sentiment.py","file_ext":"py","file_size_in_byte":4173,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"21114493901","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nimport os\nimport sys\nimport re\n\nfrom dx_bge.StateWriter import *\n\nclass CommandMatch:\n STATE_COMMAND_REGEX = re.compile(r\"player_state:([a-zA-Z]):([a-zA-Z]):([a-zA-Z0-9])\")\n\n\ndef execute(args):\n command_name = args[0]\n\n if (command_name == \"create_player_state\"):\n name = args[1]\n StateWriting.create_player_state(name)\n else:\n cr = command_name.split(\":\")\n if(cr[0] == \"player_state\"):\n # add state\n if cr[1] == \"add\":\n # get etat\n etat = cr[2]\n # get etat fonctio\n etatFunction = cr[3]\n # add\n StateWriting.add_player_state(etat, etatFunction)\n\nif __name__ == \"__main__\":\n execute(sys.argv[1:])\n","repo_name":"Dynamique-Zak/Zelda_BlenderGame","sub_path":"manager.py","file_name":"manager.py","file_ext":"py","file_size_in_byte":798,"program_lang":"python","lang":"en","doc_type":"code","stars":26,"dataset":"github-code","pt":"3"} +{"seq_id":"29036035497","text":"import alice.tests.library.auth as auth\nimport alice.tests.library.directives as directives\nimport alice.tests.library.scenario as scenario\nimport alice.tests.library.surface as surface\nimport pytest\n\n\n@pytest.mark.oauth(auth.YandexPlus)\nclass TestStopVideo(object):\n\n owners = ('nkodosov',)\n\n @pytest.mark.parametrize('surface', [surface.station])\n def test_video_stop_station(self, alice):\n alice('найди видео с котиками')\n alice('включи номер 1')\n response = alice('хватит')\n assert response.scenario == scenario.Commands\n assert response.directive.name == directives.names.ClearQueueDirective\n assert not response.has_voice_response()\n\n @pytest.mark.parametrize('surface', [surface.smart_tv])\n @pytest.mark.device_state(video={'player_capabilities': ['pause']})\n def test_video_stop_tv(self, alice):\n response = alice('включи первый канал')\n assert response.scenario == scenario.TvChannels\n assert response.directive.name == directives.names.OpenUriDirective\n response = alice('хватит')\n assert response.scenario == scenario.Commands\n assert response.directive.name == directives.names.PlayerPauseDirective\n assert not response.has_voice_response()\n\n @pytest.mark.parametrize('surface', [surface.smart_tv])\n def test_video_stop_tv_unsupported(self, alice):\n response = alice('включи первый канал')\n assert response.scenario == scenario.TvChannels\n assert response.directive.name == directives.names.OpenUriDirective\n response = alice('хватит')\n assert response.scenario == scenario.Commands\n assert response.text == 'Извините, такая команда не поддерживается этим плеером.'\n","repo_name":"Alexander-Berg/2022-tests-examples","sub_path":"Voice Assistant tests/tests/integration_tests/video/stop_video.py","file_name":"stop_video.py","file_ext":"py","file_size_in_byte":1864,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"36677741852","text":"import json\nfrom difflib import get_close_matches\n\ndata=json.load(open(\"data.json\"))\n\ndef translate(w):\n\tw=w.lower()\n\tif word in data:\n\t\treturn data[w]\n\telif len(get_close_matches(word,data.keys()))>0:\n\t\tyn=input(\"Did you mean %s instead? press 'y' if YES, press 'n' if NO: \" %get_close_matches(word,data.keys())[0])\n\t\tif yn==\"y\":\n\t\t\treturn data[get_close_matches(word,data.keys())[0]]\n\t\telif yn=='n':\n\t\t\treturn \"word doesn't exist, please re-check it.\"\n\t\t\t\t\n\t\telse:\n\t\t\treturn \"sorry, we didn't understand your entry\"\n\t\t\t\n\telse:\n\t\treturn \"word doesn't exist, please re-check it.\"\nword=input(\"enter the word: \")\noutput=translate(word)\n\nif type(output)==list:\n\tfor i in output:\n\t\tprint(i)\nelse:\n\tprint(output)\n\n","repo_name":"btanaji/Interactive_Dictionary_CLI","sub_path":"idict.py","file_name":"idict.py","file_ext":"py","file_size_in_byte":709,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"26686801929","text":"#!/usr/bin/env python\n\n#----- import libraries and modules -----\n\n#import scapy.all as scapy\nimport scapy.all as scapy\nimport optparse\nimport os\n\n#-----define functions------\n\ndef get_args():\n '''\n Get command line arguments\n '''\n\n parser = optparse.OptionParser()\n parser.add_option(\"-t\", \"--target\", dest=\"ip\", help=\"Target IP or IP range. Form: xxx.xxx.xxx.xxx[/xx]\")\n #parser.add_option(\"-o\", \"--output\", dest=\"response_output\", help=\"Indicate if responses should be printed to screen\")\n\n (options, _) = parser.parse_args()\n\n if (not options.ip):\n parser.error(\"[-] Specify an IP (range) using '-t ' or use '--help' for more info\")\n quit()\n else:\n return options.ip\n\ndef scan(ip):\n '''\n Function taking an IP or IP range, sending an ARP request to all provided IPs via the network's broadcast channel\n and scanning all responding IPs for their MAC address. The function outputs all MAC addresses and returns\n a list of dicts containing a dict with 'ip' and 'mac'-keys for each response.\n\n :param ip:\n :return: client_list; list containing dict for ip and MAC for each response\n '''\n arp_request = scapy.ARP(pdst=ip)\n broadcast = scapy.Ether(dst=\"ff:ff:ff:ff:ff:ff\")\n arp_req_broadcast = broadcast/arp_request\n\n (response_list, no_response_list) = scapy.srp(arp_req_broadcast, timeout=2, verbose=False)\n\n clients_list = []\n for response in response_list: #response_list is a list of tuples with a tuple for each response received\n #print(response[1].summary()) ##each response is a tuple with the request at loc 1 and the response t loc 2; each of these is an ARP packet, which can be analyzed using .summary() or of which information can be extracted using .psrc or .hwsrc\n\n current_ip = response[1].psrc\n current_mac = response[1].hwsrc\n clients_dict = {\"ip\": current_ip, \"MAC\": current_mac}\n clients_list.append(clients_dict)\n\n return clients_list\n\ndef print_response(client_list):\n print(\"IP\\t\\t||\\tMAC address\")\n print(\"-----------------------------------------\")\n\n for response in client_list:\n try:\n print(f\"{response['ip']}\\t||\\t{response['MAC']}\")\n except SyntaxError:\n print(\"Use 'python3 net_scan.py -t '\")\n quit()\n\n#------call functions-----\nif __name__ == \"__main__\":\n print(\"\\n\\n\")\n ip = get_args()\n response_list = scan(ip)\n print_response(response_list)\n\n\n\n\n\n\n","repo_name":"lasupernova/ethical_hacking","sub_path":"network_scanner/net_scan.py","file_name":"net_scan.py","file_ext":"py","file_size_in_byte":2483,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"20405840232","text":"\r\ndef problem1():\r\n\twith open(\"Day8/input1.txt\") as f:\r\n\t lines = f.read().splitlines() \r\n\tlines = [x.strip(\"\") for x in lines] \r\n\r\n\tdigits = [x.split(\"|\")[0] for x in lines]\r\n\toutputs = [x.split(\"|\")[1] for x in lines]\r\n\r\n\toutputs = [output.split() for output in outputs]\r\n\r\n\tsum_of_1478 = 0\r\n\r\n\tfor output in outputs:\r\n\t\tfor digit in output:\r\n\t\t\tif len(digit) == 2 or len(digit) == 3 or len(digit) == 4 or len(digit) == 7:\r\n\t\t\t\tsum_of_1478 += 1\r\n\r\n\treturn sum_of_1478\r\n\t\r\nprint(problem1())","repo_name":"antoine1242/AdventOfCode","sub_path":"2021/Day8/problem1.py","file_name":"problem1.py","file_ext":"py","file_size_in_byte":494,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"18690206723","text":"n = int(input())\nn_arr = list(map(int, input().split()))\n\nm = int(input())\nm_arr = list(map(int, input().split()))\n\nn_arr.sort()\n\n# index 반환\ndef binary_search(arr, start, end, target):\n while start <= end:\n mid = (start + end) // 2\n\n if arr[mid] > target:\n end = mid - 1\n elif arr[mid] < target:\n start = mid + 1\n else:\n return True\n return False\n\nresult = [0 for _ in range(m)]\nfor i in range(m): # o(N)\n if binary_search(n_arr, 0, n-1, m_arr[i]): # o(logN)\n result[i] = 1\n# 총 O(NlogN) 500,000에 대해서 가능\nfor i in result:\n print(i, end=' ')","repo_name":"sanghyunEE/coding-test","sub_path":"binary_search/10815.py","file_name":"10815.py","file_ext":"py","file_size_in_byte":636,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"73778484242","text":"import paho.mqtt.client as mqtt\nfrom time import sleep\nfrom threading import Thread\nimport json\n\nclass RPIMQTTClient:\n def __init__(self, handleMessage):\n self.handleMessage = handleMessage\n\n def on_connect(self, client, userdata, flags, rc):\n print(\"on_connect(): {}\".format(mqtt.connack_string(rc)))\n\n def start(self, broker, port):\n self.client = mqtt.Client()\n self.client.on_message = self.on_message\n self.client.on_connect = self.on_connect\n print(\"Connecting to {}:{}\".format(broker, port))\n self.client.connect(broker, port)\n\n self.client.subscribe(\"g6/unit6/G6/update\")\n\n try:\n thread = Thread(target=self.client.loop_forever)\n thread.start()\n except KeyboardInterrupt:\n print(\"Interrupted\")\n self.client.disconnect()\n\n def on_message(self, client, userdata, msg):\n try:\n print(f\"Received `{msg.payload}` from `{msg.topic}` topic\")\n self.handleMessage(json.loads(msg.payload))\n except Exception as e:\n print(e)\n\n def send_status(self, unit, group, status):\n try:\n self.client.publish(\"g6/\" + unit + \"/\" + group, status)\n print(f\"Sent a message\")\n\n except Exception as e:\n print(e)\n\n","repo_name":"Jorrre/HelpMe","sub_path":"rpi/rpi_mqtt_client.py","file_name":"rpi_mqtt_client.py","file_ext":"py","file_size_in_byte":1315,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"26106090183","text":"from datetime import datetime\nimport pdb\n\nFORWARD_LOOKING_PERIOD = 6\n\n\nclass FuturesUtils(object):\n\n _date_today = datetime.today()\n _current_month = _date_today.month\n _current_year = _date_today.year\n\n _months_in_year = 12\n _futures_epxiration_data = []\n\n exp_months = {\n 1: 'F',\n 2: 'G',\n 3: 'H',\n 4: 'J',\n 5: 'K',\n 6: 'M',\n 7: 'N',\n 8: 'Q',\n 9: 'U',\n 10: 'V',\n 11: 'X',\n 12: 'Z'}\n\n def resolve_expiration_month_codes(self):\n\n expiration_dates = []\n expiration_months_codes = []\n expiration_months = []\n\n sum_months = self._current_month + (FORWARD_LOOKING_PERIOD - 1)\n if sum_months > self._months_in_year:\n diff_months = sum_months - self._months_in_year\n sub_one = {month: code\n + (self._current_year + 1).__str__()[-2:]\n for month, code in self.exp_months.items()\n if month <= diff_months}\n sub_two = {month: code\n + self._current_year.__str__()[-2:]\n for month, code in self.exp_months.items()\n if month >= self._current_month}\n futures_subset = sub_one.copy()\n futures_subset.update(sub_two)\n else:\n futures_subset = {month: code\n + self._current_year.__str__()[-2:]\n for month, code in self.exp_months.items()\n if self._current_month\n + FORWARD_LOOKING_PERIOD\n > month\n >= self._current_month}\n future_codes = futures_subset.values()\n future_code_string = None\n\n for fc in future_codes:\n year = '20' + fc[-2:]\n month_from_code = list(self.exp_months.keys())[\n list(self.exp_months.values()).index(fc[-3])]\n if month_from_code < 10:\n month_from_code = '0' + month_from_code.__str__()\n else:\n month_from_code = month_from_code.__str__()\n year_month_combo = year + month_from_code\n expiration_months_codes.append(fc)\n expiration_months.append(year_month_combo)\n\n expiration_dates.append(expiration_months_codes)\n expiration_dates.append(expiration_months)\n\n return expiration_dates\n","repo_name":"zwocram/TFS","sub_path":"tfs/utils/futures.py","file_name":"futures.py","file_ext":"py","file_size_in_byte":2472,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"16511911899","text":"from os import lstat\nimport pygame\nimport random\nfrom typing import Tuple\n\n# Globales\nSIZE = [800, 800]\nCUADRADO_ALTO = 40\nBLANCO = (255, 255, 255)\nNEGRO = (0, 0, 0)\nVERDE = (102, 204, 0)\nFONDO = (24, 25, 30)\nMATRIZ_OBSTACULOS = list()\nMATRIZ_MEMORIA = list()\nLISTA_MEMORIA = list() # Lista de posiciones visitadas\nCHECKPOINT = pygame.image.load(\"assets/checkPoint.jpg\")\nTHIEF = pygame.image.load(\"assets/ladron.png\")\nOBSTACULO = pygame.image.load(\"assets/obtaculo.jpg\")\n# Posición inicial de avatar\nX_1, Y_1 = 80, 40\n\n# crear matriz de obstáculos\nfor i in range(0, 20):\n MATRIZ_OBSTACULOS2 = list()\n for j in range(0, 20):\n MATRIZ_OBSTACULOS2.append(0)\n MATRIZ_OBSTACULOS.append(MATRIZ_OBSTACULOS2)\n\n# crear matriz de algoritmo para Dijksra\nfor i in range(0, 20):\n MATRIZ_MEMORIA2 = list()\n for j in range(0, 20):\n MATRIZ_MEMORIA2.append(0)\n MATRIZ_MEMORIA.append(MATRIZ_MEMORIA2)\n \n\ndef llenarFondo(screen:pygame.Surface, screen2:pygame.Surface):\n screen.fill(FONDO)\n color = 0\n k = 0\n m = 0\n\n for i in range(0, SIZE[0], CUADRADO_ALTO):\n k = int(i/40)\n for j in range(0, SIZE[1], CUADRADO_ALTO):\n m = int(j/40)\n # Avatar\n if MATRIZ_OBSTACULOS[k][m] == 88:\n thiefrect = THIEF.get_rect()\n thiefrect.move_ip(i, j)\n screen2.blit(THIEF, thiefrect)\n # Obstaculo\n elif MATRIZ_OBSTACULOS[k][m] == -1:\n obstaculorect = OBSTACULO.get_rect()\n obstaculorect.move_ip(i, j)\n screen.blit(OBSTACULO, obstaculorect)\n # checkPoint\n elif MATRIZ_OBSTACULOS[k][m] == 25:\n pygame.draw.rect(screen, VERDE, [i, j, CUADRADO_ALTO, CUADRADO_ALTO], 0, 2)\n else:\n # Fondo blanco y negro\n if color%2 == 0 and MATRIZ_OBSTACULOS[k][m] == 0:\n pygame.draw.rect(screen, NEGRO, [i, j, CUADRADO_ALTO, CUADRADO_ALTO], 0, 2)\n else:\n pygame.draw.rect(screen, BLANCO, [i, j, CUADRADO_ALTO, CUADRADO_ALTO], 0, 2)\n color += 1\n color += 1\n\n pygame.display.update()\n return screen\n\ndef guardarCheckPoint(x, y):\n x = int(x/40)\n y = int(y/40)\n for i in range(0, 20):\n for j in range(0, 20):\n # Borrar checkPoint si ya existe\n if MATRIZ_OBSTACULOS[i][j] == 25:\n MATRIZ_MEMORIA[x][y] = 0\n MATRIZ_OBSTACULOS[i][j] = 0\n elif (i,j) == (x, y): # 25, 88, -1\n # LIBRE\n if MATRIZ_OBSTACULOS[x][y] == 0 and MATRIZ_OBSTACULOS[x][y] != 25 and MATRIZ_OBSTACULOS[x][y] != 88: # 0\n MATRIZ_OBSTACULOS[x][y] = 25\n MATRIZ_MEMORIA[x][y] = 25\n algoritmo(0)\n # OCUPADO\n else:\n MATRIZ_MEMORIA[x][y] = MATRIZ_MEMORIA[x][y]\n MATRIZ_OBSTACULOS[x][y] = MATRIZ_OBSTACULOS[x][y]\n else:\n MATRIZ_OBSTACULOS[x][y] = MATRIZ_OBSTACULOS[x][y]\n MATRIZ_MEMORIA[x][y] = MATRIZ_MEMORIA[x][y]\n\ndef guardarObstaculo(x, y):\n x = int(x/40)\n y = int(y/40)\n\n for i in range(0, 20):\n for j in range(0, 20):\n if [i, j] == [x, y]:\n # Si se coloca encima del avatar\n if MATRIZ_OBSTACULOS[x][y] == 88 or MATRIZ_OBSTACULOS[i][j] == 25:\n MATRIZ_OBSTACULOS[x][y] = MATRIZ_OBSTACULOS[x][y]\n else:\n MATRIZ_OBSTACULOS[x][y] = -1\n\ndef eliminarObstaculo(x, y):\n x = int(x/40)\n y = int(y/40)\n # print(x, y)\n for i in range(0, 20):\n for j in range(0, 20):\n if [i, j] == [x, y] and MATRIZ_OBSTACULOS[x][y] == -1:\n MATRIZ_OBSTACULOS[x][y] = 0\n \ndef mover(opc):\n print(\"mover\")\n for i in range(0, 20):\n for j in range(0, 20):\n if MATRIZ_OBSTACULOS[i][j] == 88:\n avatar_x = i\n avatar_y = j\n LISTA_MEMORIA.append([i, j])\n\n if opc == 1: # Arriba\n # Obstaculo y borde\n if MATRIZ_OBSTACULOS[avatar_x][avatar_y-1] == -1 or avatar_y == 0:\n MATRIZ_OBSTACULOS[avatar_x][avatar_y] = MATRIZ_OBSTACULOS[avatar_x][avatar_y] \n # Meta\n # elif MATRIZ_OBSTACULOS[avatar_x][avatar_y-1] == 25:\n # run = False\n # print(\"You win!\")\n else:\n # Movimiento normal\n MATRIZ_OBSTACULOS[avatar_x][avatar_y] = 0\n MATRIZ_OBSTACULOS[avatar_x][int(avatar_y-1)] = 88\n \n if opc == 2: # Abajo\n if avatar_y == 19:\n MATRIZ_OBSTACULOS[avatar_x][avatar_y] = MATRIZ_OBSTACULOS[avatar_x][avatar_y] \n elif MATRIZ_OBSTACULOS[avatar_x][avatar_y+1] == -1:\n MATRIZ_OBSTACULOS[avatar_x][avatar_y] = MATRIZ_OBSTACULOS[avatar_x][avatar_y] \n else:\n MATRIZ_OBSTACULOS[avatar_x][avatar_y] = 0\n MATRIZ_OBSTACULOS[avatar_x][int(avatar_y+1)] = 88\n\n if opc == 3: # Izquierda\n if avatar_x == 0:\n MATRIZ_OBSTACULOS[avatar_x][avatar_y] = MATRIZ_OBSTACULOS[avatar_x][avatar_y] \n elif MATRIZ_OBSTACULOS[avatar_x-1][avatar_y] == -1:\n MATRIZ_OBSTACULOS[avatar_x][avatar_y] = MATRIZ_OBSTACULOS[avatar_x][avatar_y] \n else:\n MATRIZ_OBSTACULOS[avatar_x][avatar_y] = 0\n MATRIZ_OBSTACULOS[int(avatar_x-1)][avatar_y] = 88\n \n if opc == 4: # Derecha\n if avatar_x == 19:\n MATRIZ_OBSTACULOS[avatar_x][avatar_y] = MATRIZ_OBSTACULOS[avatar_x][avatar_y] \n elif MATRIZ_OBSTACULOS[avatar_x+1][avatar_y] == -1:\n MATRIZ_OBSTACULOS[avatar_x][avatar_y] = MATRIZ_OBSTACULOS[avatar_x][avatar_y] \n else:\n MATRIZ_OBSTACULOS[avatar_x][avatar_y] = 0\n MATRIZ_OBSTACULOS[int(avatar_x+1)][avatar_y] = 88\n \n # Imprimir\n # for i in range(0, 20): # Y\n # for j in range(0, 20): # X\n # print(\"[\",MATRIZ_OBSTACULOS[j][i], \"]\", end=\"\")\n # print(\"\\n\")\n # print(\"\\n\\n\")\n \n \ndef nuevo_objeto(clicks:Tuple):\n if clicks[0]:\n mouse = pygame.mouse.get_pos()\n key_checkPoint = pygame.key.get_pressed()\n x = (mouse[0]//40)*40\n y = (mouse[1]//40)*40\n \n if key_checkPoint[pygame.K_LSHIFT]:\n guardarCheckPoint(x, y)\n else:\n guardarObstaculo(x, y)\n\n if clicks[2]:\n mouse = pygame.mouse.get_pos()\n x = (mouse[0]//40)*40\n y = (mouse[1]//40)*40\n eliminarObstaculo(x, y)\n\ndef algoritmo(opc):\n # MAPA DE CALOR\n if opc == 0:\n # Posición de la meta\n for i in range(0,20):\n for j in range(0, 20):\n if MATRIZ_OBSTACULOS[i][j] == 25:\n MATRIZ_MEMORIA[i][j] = 25\n x_2 = i\n y_2 = j\n # Crear mapa a partir de la posición de la meta\n for i in range(0,20):\n for j in range(0, 20):\n if MATRIZ_MEMORIA[i][j] == 25:\n MATRIZ_MEMORIA[i][j] = 0\n elif MATRIZ_OBSTACULOS[i][j] == -1:\n MATRIZ_MEMORIA[i][j] = -1\n else:\n distancia_x = int(abs((i-x_2)))\n distancia_y = int(abs((j-y_2)))\n distancia_meta = int(pow(distancia_x,2)+pow(distancia_y,2))\n distancia_meta = int(distancia_meta**(.5))\n MATRIZ_MEMORIA[i][j] = distancia_meta\n # Imprimir mapa\n for i in range(0, 20):\n for j in range(0, 20):\n print(\"[\",MATRIZ_MEMORIA[j][i], \"]\", end=\"\")\n print(\"\\n\")\n print(\"\\n\\n\")\n\n # Saber hacia dónde moverse\n if opc == 1:\n for i in range(0, 20): \n for j in range(0, 20): \n if MATRIZ_OBSTACULOS[i][j] == 88:\n lista = list()\n lista.append({'costo':MATRIZ_MEMORIA[i][j-1], 'x':i, 'y':j-1})\n lista.append({'costo':MATRIZ_MEMORIA[i-1][j-1], 'x':i-1, 'y':j-1})\n lista.append({'costo':MATRIZ_MEMORIA[i-1][j], 'x':i-1, 'y':j})\n lista.append({'costo':MATRIZ_MEMORIA[i-1][j+1], 'x':i-1, 'y':j+1})\n lista.append({'costo':MATRIZ_MEMORIA[i][j+1], 'x':i, 'y':j+1})\n lista.append({'costo':MATRIZ_MEMORIA[i+1][j+1], 'x':i+1, 'y':j+1})\n lista.append({'costo':MATRIZ_MEMORIA[i+1][j], 'x':i+1, 'y':j})\n lista.append({'costo':MATRIZ_MEMORIA[i+1][j-1], 'x':i+1, 'y':j-1})\n # print(\"Lista: \", lista)\n for r in range(0, len(lista)):\n print(lista[r],\"\\n\")\n # if -1 in lista[r]: \n for l in lista:\n if l['costo'] == -1:\n lista.remove(l)\n # Eliminar si es un obstáculo y no comparar \n # for l in range(0, lista.length()):\n # print(\"Lista: \", l['costo'])\n # print(lista)\n # else: print(\"No removido: \", l['costo'])\n\n # return lista\n # print(lista)\n # El primero de la lista para compararlo\n menor_costo = lista[0]['costo']\n menor = lista[0]\n # Por cada objeto guardado\n for k in lista:\n # comparar costos\n if k['costo'] < menor_costo:\n menor_costo = k['costo'] # Costo menor actual va cambiando\n menor = k # Objeto completo menor costo\n # regresar el menor\n if menor['costo'] > 0:\n MATRIZ_OBSTACULOS[i][j] = 0\n MATRIZ_OBSTACULOS[menor['x']][menor['y']] = 88\n return menor\n\n\n \n\ndef main():\n # Inicializar pygame\n pygame.init()\n # Ventanas\n screen = pygame.display.set_mode(SIZE)\n screen2 = pygame.display.set_mode(SIZE)\n pygame.display.set_caption(\"Juego 1\")\n clock = pygame.time.Clock()\n # Crear objetos \n MATRIZ_OBSTACULOS[int(X_1/40)][int(Y_1/40)] = 88\n llenarFondo(screen, screen2)\n run = True\n pause = False\n\n while run:\n # start_key = True\n for event in pygame.event.get():\n if event.type == pygame.QUIT:\n run = False\n# Eventos\n clicks = pygame.mouse.get_pressed()\n if clicks:\n algoritmo(1)\n nuevo_objeto(clicks)\n llenarFondo(screen, screen2)\n# Eventos\n # pygame.time.delay(50) # Aumentar para avanzar más rápido\n # clock.tick(10) # Reducir para avanzar más lento\n pygame.time.delay(80)\n clock.tick(5)\n pygame.display.update()\n # Salir de pygame\n print(LISTA_MEMORIA)\n print(\"Total movimientos: \",LISTA_MEMORIA.__len__())\n pygame.quit()\n \nif __name__ == '__main__': main()\n\n\n","repo_name":"AdrianVvazquez/Perceptrones","sub_path":"Algoritmo Dijkstra/pyGame Dijkstra - v6.py","file_name":"pyGame Dijkstra - v6.py","file_ext":"py","file_size_in_byte":11137,"program_lang":"python","lang":"pt","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"16097404584","text":"import yaml\nimport os\nimport datetime\nimport sys\nimport json\nscript_path = os.path.abspath(__file__)\nscript_dir = os.path.dirname(script_path)\nchef_dir = os.path.join(script_dir, '../../../src')\nsys.path.append(chef_dir)\n\nfrom ChEF.evaluator import Evaluator, load_config, sample_dataset\nfrom ChEF.models import get_model\nfrom ChEF.scenario import dataset_dict\n\ndef find_res_json(directory, dataset_name):\n scienceqa_files = []\n if not os.path.isdir(directory):\n return directory\n\n for root, dirs, files in os.walk(directory):\n for file in files:\n if file.startswith(dataset_name) and file.endswith(\".json\"):\n file_path = os.path.join(root, file)\n scienceqa_files.append(file_path)\n return scienceqa_files[0]\n\ndef compute_MR(origin, target):\n mct, total = 0, 0\n res={}\n for o,t in zip(origin, target):\n main_idx = str(int(o['id']) % int(1e6))\n if main_idx in res:\n continue\n oid = o['options'].index(o['answer'])\n res[main_idx]=1\n total+=1\n assert o['id']==t['id']\n tid = t['options'].index(t['answer'])\n if oid==tid:\n mct+=1\n return mct/total*100\n\ndef main():\n model_cfg, recipe_cfg, save_dir, sample_len = load_config()\n\n # model\n model = get_model(model_cfg)\n \n # dataset\n scenario_cfg = recipe_cfg['scenario_cfg']\n settings = [('natural',0), ('natural',1), ('natural',2), ('neutral',0), ('neutral',1) ,('unnatural',0)]\n dataset_name = scenario_cfg['dataset_name']\n time = datetime.datetime.now().strftime(\"%Y%m%d%H%M%S\")\n base_save_dir = os.path.join(save_dir, model_cfg['model_name'],'Instruct_follow', dataset_name, time)\n # origin \n scenario_cfg['option_map'] = None\n dataset = dataset_dict[dataset_name](**scenario_cfg)\n dataset = sample_dataset(dataset, sample_len=sample_len, sample_seed=0)\n # save_cfg\n save_base_dir = os.path.join(base_save_dir, \"origin\")\n os.makedirs(save_base_dir, exist_ok=True)\n with open(os.path.join(save_base_dir, 'config.yaml'), 'w', encoding='utf-8') as f:\n yaml.dump(data=dict(model_cfg=model_cfg, recipe_cfg=recipe_cfg), stream=f, allow_unicode=True)\n print(f'Save origin results in {save_base_dir}!')\n # evaluate\n eval_cfg = recipe_cfg['eval_cfg']\n evaluater = Evaluator(dataset, save_base_dir, eval_cfg)\n evaluater.evaluate(model)\n origin_save_base_dir = save_base_dir\n for setting in settings:\n ins_dict={\n 'type':setting[0],\n 'ids' : setting[1]\n }\n scenario_cfg['option_map'] = ins_dict\n dataset = dataset_dict[dataset_name](**scenario_cfg)\n dataset = sample_dataset(dataset, sample_len=sample_len, sample_seed=0)\n # save_cfg\n save_base_dir = os.path.join(base_save_dir, f\"{setting[0]}_{setting[1]}\")\n os.makedirs(save_base_dir, exist_ok=True)\n\n with open(os.path.join(save_base_dir, 'config.yaml'), 'w', encoding='utf-8') as f:\n yaml.dump(data=dict(model_cfg=model_cfg, recipe_cfg=recipe_cfg), stream=f, allow_unicode=True)\n print(f'Save {setting[0]}_{setting[1]} results in {save_base_dir}!')\n\n # evaluate\n eval_cfg = recipe_cfg['eval_cfg']\n evaluater = Evaluator(dataset, save_base_dir, eval_cfg)\n evaluater.evaluate(model)\n\n #post processing\n with open(find_res_json(origin_save_base_dir, dataset_name),'r') as f:\n origin_res = json.load(f)\n\n types_dirs = {'natural':[],'neutral':[],'unnatural':[]}\n types_accs = {'natural':[],'neutral':[],'unnatural':[]}\n types_mrs = {'natural':[],'neutral':[],'unnatural':[]}\n for setting in settings:\n dir = os.path.join(base_save_dir, f\"{setting[0]}_{setting[1]}\")\n types_dirs[setting[0]].append(dir)\n acc_json_path = os.path.join(dir, 'results.json')\n with open(acc_json_path,'r') as f:\n acc_data = json.load(f)\n types_accs[setting[0]].append(acc_data['result'])\n result_json_path = find_res_json(dir, dataset_name)\n with open(result_json_path, 'r') as f:\n result_data = json.load(f)\n mr = compute_MR(origin_res, result_data)\n types_mrs[setting[0]].append(mr)\n print(f\"{setting[0]}_{setting[1]}: Acc: {acc_data['result']}, follow_MR: {mr}\")\n\n avg_acc, avg_mr = 0, 0\n for type,accs in types_accs.items():\n for acc in accs:\n avg_acc+=acc\n avg_acc/=len(settings)\n\n for type,mrs in types_mrs.items():\n for mr in mrs:\n avg_mr+=mr\n avg_mr/=len(settings)\n \n print(f'weighted_avg_MR: {avg_mr}, weighted_avg_Acc: {avg_acc}')\n final_res = {\n 'res_dirs': types_dirs,\n 'Accs': types_accs,\n 'MRs': types_mrs,\n 'weighted_avg_MR': avg_mr,\n 'weighted_avg_Acc':avg_acc,\n }\n with open(os.path.join(base_save_dir, 'Instruction_Follow_Results.json'), 'w', encoding='utf-8') as f:\n f.write(json.dumps(final_res, indent=4))\n\n \n\nif __name__ == '__main__':\n main()","repo_name":"OpenGVLab/LAMM","sub_path":"src/tools/ChEF/eval_insfollow.py","file_name":"eval_insfollow.py","file_ext":"py","file_size_in_byte":5044,"program_lang":"python","lang":"en","doc_type":"code","stars":122,"dataset":"github-code","pt":"3"} +{"seq_id":"18300492973","text":"from sqlalchemy import create_engine\nfrom sqlalchemy.ext.declarative import declarative_base\nfrom sqlalchemy.orm import sessionmaker\nimport psycopg2\n\n#SQLALCHAMY_DB_URL = 'sqlite:///database/data.db'\n#engine = create_engine(SQLALCHAMY_DB_URL, connect_args={'check_same_thread': False})\n\n#SQLALCHAMY_DB_URL = 'mysql+mysqlconnector://root:root@localhost:3306/qblocks'\n#engine = create_engine(SQLALCHAMY_DB_URL)\n\n# SQLALCHAMY_DB_URL = 'mysql+mysqlconnector://uvayh5ymlkx8ybfd:HJEYCKFKknzzlP7cvlKL@bjylablqdhnmt0gvpyai-mysql.services.clever-cloud.com:3306/bjylablqdhnmt0gvpyai'\n# engine = create_engine(SQLALCHAMY_DB_URL)\n\nSQLALCHEMY_DATABASE_URL = \"postgresql://wzfjmqrbdydvjw:0c18a705fa8cd156f0d47b77ffca8130d5b3941e224771f3ed9cbeab23e3abb0@ec2-3-223-213-207.compute-1.amazonaws.com:5432/derqlf1da4p838\"\nengine = create_engine(SQLALCHEMY_DATABASE_URL)\n\nSessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)\n\nBase = declarative_base()\n\ndef get_db():\n db = SessionLocal()\n try:\n yield db\n finally:\n db.close()\n","repo_name":"hansraj1999/qbassignment","sub_path":"database/database.py","file_name":"database.py","file_ext":"py","file_size_in_byte":1051,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"71514101842","text":"from QGL.ChannelLibraries import EdgeFactory, MeasFactory, QubitFactory\nfrom QGL import ChannelLibraries\nfrom QGL.Channels import Edge, Measurement\nfrom QGL.PulseSequencer import Pulse, CompositePulse\nfrom QGL.PatternUtils import flatten\nfrom QGL.PulsePrimitives import Id, X, MEAS\nfrom QGL.ControlFlow import qsync, qwait, ControlInstruction, Goto, Barrier\nfrom QGL.BlockLabel import BlockLabel\n#from QGL.Compiler import normalize\n\nfrom pyqgl2.test_cl import create_default_channelLibrary\n\nimport collections\nfrom math import pi\n\ndef channel_setup(doHW=False, new=True):\n # new indicates replace any existing library\n # Otherwise if there is an existing library, use it\n # FIXME: For now, supplying first arg false meaning do not create physical channel mappings\n if not new and ChannelLibraries.channelLib is not None and len(ChannelLibraries.channelLib.keys()) != 0:\n create_default_channelLibrary(doHW, False)\n # create_channel_library(ChannelLibraries.channelLib.channelDict)\n else:\n create_default_channelLibrary(doHW, True)\n # create_channel_library(new=True)\n\n# # OBE: Create a basic channel library\n# # Code stolen from QGL's test_Sequences\n# # It creates channels that are taken from test_Sequences APS2Helper\n# def create_channel_library(channels=dict(), new=False):\n# from QGL.Channels import LogicalMarkerChannel, PhysicalQuadratureChannel, PhysicalMarkerChannel\n\n# ChannelLibraries.ChannelLibrary(blank=True)\n\n# qubit_names = ['q1','q2','q3']\n# logical_names = ['digitizerTrig', 'slaveTrig']\n\n# for name in logical_names:\n# channels[name] = LogicalMarkerChannel(label=name)\n\n# for name in qubit_names:\n# mName = 'M-' + name\n# mgName = 'M-' + name + '-gate'\n# qgName = name + '-gate'\n\n# mg = LogicalMarkerChannel(label=mgName)\n# qg = LogicalMarkerChannel(label=qgName)\n\n# m = MeasFactory(label=mName, gate_chan = mg, trig_chan=channels['digitizerTrig'])\n\n# q = QubitFactory(label=name, gate_chan=qg)\n# q.pulse_params['length'] = 30e-9\n# q.pulse_params['phase'] = pi/2\n\n# channels[name] = q\n# channels[mName] = m\n# channels[mgName] = mg\n# channels[qgName] = qg\n\n# # this block depends on the existence of q1 and q2\n# channels['cr-gate'] = LogicalMarkerChannel(label='cr-gate')\n\n# q1, q2 = channels['q1'], channels['q2']\n# cr = None\n# try:\n# cr = EdgeFactory(q1, q2)\n# except:\n# cr = Edge(label=\"cr\", source = q1, target = q2, gate_chan = channels['cr-gate'] )\n# cr.pulse_params['length'] = 30e-9\n# cr.pulse_params['phase'] = pi/4\n# channels[\"cr\"] = cr\n\n# mq1q2g = LogicalMarkerChannel(label='M-q1q2-gate')\n# channels['M-q1q2-gate'] = mq1q2g\n# channels['M-q1q2'] = Measurement(label='M-q1q2', gate_chan = mq1q2g, trig_chan=channels['digitizerTrig'])\n\n# # Add a 2nd edge from q2 back to q1 to support edgeTest4 (which is weird)\n# channels['cr2-gate'] = LogicalMarkerChannel(label='cr2-gate')\n# cr2 = None\n# try:\n# cr2 = EdgeFactory(q2, q1)\n# except:\n# cr2 = Edge(label=\"cr2\", source = q2, target = q1, gate_chan = channels['cr2-gate'] )\n# cr2.pulse_params['length'] = 30e-9\n# cr2.pulse_params['phase'] = pi/4\n# channels[\"cr2\"] = cr2\n\n# mq2q1g = LogicalMarkerChannel(label='M-q2q1-gate')\n# channels['M-q2q1-gate'] = mq2q1g\n# channels['M-q2q1'] = Measurement(label='M-q2q1', gate_chan = mq2q1g, trig_chan=channels['digitizerTrig'])\n\n# # Now assign physical channels\n# for name in ['APS1', 'APS2', 'APS3', 'APS4', 'APS5', 'APS6',\n# 'APS7', 'APS8', 'APS9', 'APS10']:\n# channelName = name + '-12'\n# channel = PhysicalQuadratureChannel(label=channelName)\n# channel.sampling_rate = 1.2e9\n# channel.instrument = name\n# channel.translator = 'APS2Pattern'\n# channels[channelName] = channel\n\n# for m in range(1,5):\n# channelName = \"{0}-12m{1}\".format(name,m)\n# channel = PhysicalMarkerChannel(label=channelName)\n# channel.sampling_rate = 1.2e9\n# channel.instrument = name\n# channel.translator = 'APS2Pattern'\n# channels[channelName] = channel\n\n# mapping = {\t'digitizerTrig' : 'APS1-12m1',\n# 'slaveTrig' : 'APS1-12m2',\n# 'q1' : 'APS1-12',\n# 'q1-gate' : 'APS1-12m3',\n# 'M-q1' : 'APS2-12',\n# 'M-q1-gate' : 'APS2-12m1',\n# 'q2' : 'APS3-12',\n# 'q2-gate' : 'APS3-12m1',\n# 'M-q2' : 'APS4-12',\n# 'M-q2-gate' : 'APS4-12m1',\n# 'q3' : 'APS7-12',\n# 'q3-gate' : 'APS7-12m1',\n# 'M-q3' : 'APS8-12',\n# 'M-q3-gate' : 'APS8-12m1',\n# 'cr' : 'APS5-12',\n# 'cr-gate' : 'APS5-12m1',\n# 'M-q1q2' : 'APS6-12',\n# 'M-q1q2-gate' : 'APS6-12m1',\n# 'cr2' : 'APS9-12',\n# 'cr2-gate' : 'APS9-12m1',\n# 'M-q2q1' : 'APS10-12',\n# 'M-q2q1-gate' : 'APS10-12m1'}\n\n# finalize_map(mapping, channels, new)\n# return channels\n\n# # OBE: Store the given channels in the QGL ChannelLibraries\n# def finalize_map(mapping, channels, new=False):\n# for name,value in mapping.items():\n# channels[name].phys_chan = channels[value]\n\n# if new:\n# ChannelLibraries.channelLib = ChannelLibraries.ChannelLibrary(blank=True)\n# ChannelLibraries.channelLib.channelDict = channels\n# ChannelLibraries.channelLib.build_connectivity_graph()\n\n\n\ndef discard_zero_Ids(seqs):\n # assume seqs has a structure like [[entry0, entry1, ..., entryN]]\n for seq in seqs:\n ct = 0\n while ct < len(seq):\n entry = seq[ct]\n if isinstance(entry, Pulse) and entry.label == \"Id\" and entry.length == 0:\n del seq[ct]\n else:\n ct += 1\n\n# Things like echoCR create lists of pulses that need to be flattened\n# before calling compile_to_hardware\ndef flattenSeqs(seq):\n hasList = False\n for el in seq:\n if isinstance(el, collections.Iterable) and not isinstance(el, (str, Pulse, CompositePulse)) :\n hasList = True\n break\n if hasList:\n newS = []\n for el in flatten(seq):\n newS.append(el)\n return newS\n else:\n return seq\n\ndef testable_sequence(seqs):\n '''\n Transform a QGL2 result function output into something more easily testable\n by flattening pulse lists.\n '''\n seqs = flattenSeqs(seqs)\n# seqs = normalize(seqs, None)\n return seqs\n\ndef stripWaitBarrier(seqs):\n ''''\n QGL2 includes Waits and Barriers that are added after unit tests in QGL1, so strip them\n for comparison. Note however that Barrier;Pulse is how QGL2 does QGL1 PulseBlock(pulses).\n '''\n from QGL.ControlFlow import Barrier, Wait\n newS = []\n for el in seqs:\n if isinstance(el, Barrier) or isinstance(el, Wait):\n continue\n if isinstance(el, collections.Iterable) and not isinstance(el, (str, Pulse, CompositePulse)) :\n newel = stripWaitBarrier(el)\n newS.extend(newel)\n else:\n newS.append(el)\n return newS\n\n# See RB SimultaneousRB_AC test\ndef flattenPulseBlocks(seqs):\n '''Turn PulseBlocks into linear series of pulses.\n Used on QGL1 sequences to look more like QGL2 (which precedes these with a Barrier, so is equivalent)\n '''\n from QGL.PulseSequencer import PulseBlock\n newS = []\n for el in seqs:\n if isinstance(el, PulseBlock):\n for p in el.pulses.values():\n newS.append(p)\n else:\n newS.append(el)\n return newS\n\n# Adapted from unittest.case.py: assertSequenceEqual\n# Except use difflib.unified_diff instead of ndiff - much faster (less detail)\n# Note QGL2 uses Barriers to force concurrency where QGL1 might use PulseBlock; that will look different.\ndef assertPulseSequenceEqual(test, seq1, seq2, msg=None):\n \"\"\"An equality assertion for ordered sequences of pulses.\n\n For the purposes of this function, a valid ordered sequence type is one\n which can be indexed, has a length, and has an equality operator.\n\n Args:\n seq1: The first sequence to compare.\n seq2: The second sequence to compare.\n msg: Optional message to use on failure instead of a list of\n differences.\n \"\"\"\n import difflib\n import pprint\n from unittest.util import safe_repr, _common_shorten_repr\n seq_type = list\n if seq_type is not None:\n seq_type_name = seq_type.__name__\n if not isinstance(seq1, seq_type):\n raise test.failureException('First sequence is not a %s: %s'\n % (seq_type_name, safe_repr(seq1)))\n if not isinstance(seq2, seq_type):\n raise test.failureException('Second sequence is not a %s: %s'\n % (seq_type_name, safe_repr(seq2)))\n else:\n seq_type_name = \"sequence\"\n\n differing = None\n try:\n len1 = len(seq1)\n except (TypeError, NotImplementedError):\n differing = 'First %s has no length. Non-sequence?' % (\n seq_type_name)\n\n if differing is None:\n try:\n len2 = len(seq2)\n except (TypeError, NotImplementedError):\n differing = 'Second %s has no length. Non-sequence?' % (\n seq_type_name)\n\n if differing is None:\n if seq1 == seq2:\n return\n\n differing = '%ss differ: %s != %s\\n' % (\n (seq_type_name.capitalize(),) +\n _common_shorten_repr(seq1, seq2))\n\n for i in range(min(len1, len2)):\n try:\n item1 = seq1[i]\n except (TypeError, IndexError, NotImplementedError):\n differing += ('\\nUnable to index element %d of first %s\\n' %\n (i, seq_type_name))\n break\n\n try:\n item2 = seq2[i]\n except (TypeError, IndexError, NotImplementedError):\n differing += ('\\nUnable to index element %d of second %s\\n' %\n (i, seq_type_name))\n break\n\n if item1 != item2:\n differing += ('\\nFirst differing element %d:\\n%s\\n%s\\n' %\n (i, str(item1), str(item2)))\n break\n else:\n if (len1 == len2 and seq_type is None and\n type(seq1) != type(seq2)):\n # The sequences are the same, but have differing types.\n return\n\n\n if len1 > len2:\n differing += ('\\nFirst %s contains %d additional '\n 'elements.\\n' % (seq_type_name, len1 - len2))\n try:\n differing += ('First extra element %d:\\n%s\\n' %\n (len2, seq1[len2]))\n except (TypeError, IndexError, NotImplementedError):\n differing += ('Unable to index element %d '\n 'of first %s\\n' % (len2, seq_type_name))\n elif len1 < len2:\n differing += ('\\nSecond %s contains %d additional '\n 'elements.\\n' % (seq_type_name, len2 - len1))\n try:\n differing += ('First extra element %d:\\n%s\\n' %\n (len1, seq2[len1]))\n except (TypeError, IndexError, NotImplementedError):\n differing += ('Unable to index element %d '\n 'of second %s\\n' % (len1, seq_type_name))\n standardMsg = differing\n diffMsg = '\\n' + '\\n'.join(\n# difflib.ndiff(pprint.pformat(seq1).splitlines(),\n# FIXME: I wish I could get pprint.pformat to use str on pulses not repr\n difflib.unified_diff(pprint.pformat(seq1).splitlines(),\n pprint.pformat(seq2).splitlines()))\n\n standardMsg = test._truncateMessage(standardMsg, diffMsg)\n msg = test._formatMessage(msg, standardMsg)\n test.fail(msg)\n\ndef get_cal_seqs_1qubit(qubit, calRepeats=2):\n '''\n Note: return may include 0 length Id pulses.\n EG:\n qwait\n Id(q1)\n MEAS(q1),\n qwait\n Id(q1)\n MEAS(q1),\n qwait\n X(q1)\n MEAS(q1),\n qwait\n X(q1)\n MEAS(q1)\n '''\n calSeq = []\n for pulse in [Id, X]:\n for _ in range(calRepeats):\n calSeq += [\n qwait(channels=(qubit,)),\n pulse(qubit),\n Barrier(qubit),\n MEAS(qubit)\n ]\n return calSeq\n\ndef get_cal_seqs_2qubits(q1, q2, calRepeats=2):\n '''\n Prepare all computational 2-qubit basis states and measure them.\n '''\n\n calseq = []\n for pulseSet in [(Id, Id), (Id, X), (X, Id), (X, X)]:\n for _ in range(calRepeats):\n calseq += [\n qwait(channels=(q1, q2)),\n pulseSet[0](q1),\n pulseSet[1](q2),\n Barrier(q1, q2),\n MEAS(q1),\n MEAS(q2)\n ]\n\n return calseq\n\ndef match_labels(seq1, seq2):\n '''\n Returns a copy of seq1 which replaces BlockLabels in seq1 with\n corresponding BlockLabels in seq2\n '''\n new_seq = []\n label_map = {}\n for s1, s2 in zip(seq1, seq2):\n if (isinstance(s1, BlockLabel) and isinstance(s2, BlockLabel)):\n new_seq.append(s2)\n label_map[s1] = s2\n else:\n new_seq.append(s1)\n\n for entry in new_seq:\n if isinstance(entry, Goto) and entry.target:\n entry.target = label_map[entry.target]\n return new_seq\n","repo_name":"BBN-Q/pyqgl2","sub_path":"test/helpers.py","file_name":"helpers.py","file_ext":"py","file_size_in_byte":13950,"program_lang":"python","lang":"en","doc_type":"code","stars":9,"dataset":"github-code","pt":"3"} +{"seq_id":"39546634835","text":"from time import *\r\nimport random as r\r\n\r\ndef mistake(partest,usertest):\r\n error=0\r\n for i in range(len(partest)):\r\n try:\r\n if partest[i] != usertest[i]:\r\n error=error+1\r\n except:\r\n error=error+1\r\n return error\r\n\r\ndef speedTime(timeS,timeE,userinput):\r\n timeDelay=timeE-timeS \r\n timeR=round(timeDelay,2)\r\n speed=len(userinput)/timeR \r\n return round(speed)\r\n\r\ntest=[\"Update the salary of an employee using a stored procedure\",\r\n \"Before updating check whether the employee id exists or not\",\r\n \"If successfully updated, fire a trigger which enters the date\"]\r\ntest1=r.choice(test)\r\nprint(\"***** Typing Speed *****\")\r\nprint()\r\nprint(test1)\r\nprint()\r\nprint()\r\ntime_1=time()\r\ntestinput=input(\" Type Exactly same as above line : \")\r\ntime_2=time()\r\n\r\nprint('Speed: ',speedTime(time_1,time_2,testinput),\"w/sec\")\r\nprint('Eror: ',mistake(test1,testinput))","repo_name":"nilesh141/TypingSpeedCalculator","sub_path":"TypingSpeedCalculator.py","file_name":"TypingSpeedCalculator.py","file_ext":"py","file_size_in_byte":928,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"21215570745","text":"import re\n\nattacked_planet = []\ndestroyed_planet = []\n\nmessages_count = int(input())\nfor i in range(messages_count):\n message = input()\n decrypt = \"\"\n keys_count = int(len(re.findall(r\"[starSTAR]\", message)))\n for letter in message:\n new_letter = ord(letter) - keys_count\n decrypt += chr(new_letter)\n pattern = r\".*@([A-Z][a-z]+)[^\\@\\-\\!\\:\\>]*:(\\d+)[^\\@\\-\\!\\:\\>]*\\!(A|D)\\![^\\@\\-\\!\\:\\>]*\\->(\\d+).*\"\n matches = re.findall(pattern, decrypt)\n if matches:\n for match in matches:\n name = match[0]\n population = match[1]\n type = match[2]\n soldier = match[3]\n if type == \"A\":\n attacked_planet.append(name)\n elif type == \"D\":\n destroyed_planet.append(name)\n\nprint(f\"Attacked planets: {len(attacked_planet)}\")\nattacked_planet = sorted(attacked_planet)\nfor planet in attacked_planet:\n print(f\"-> {planet}\")\nprint(f\"Destroyed planets: {len(destroyed_planet)}\")\ndestroyed_planet = sorted(destroyed_planet)\nfor planet in destroyed_planet:\n print(f\"-> {planet}\")\n","repo_name":"Tsveti1103/Python-Fundamentals","sub_path":"regular_expressions_more_exercises/star_enigma.py","file_name":"star_enigma.py","file_ext":"py","file_size_in_byte":1092,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"30116449787","text":"from __future__ import annotations\n\nimport random\n\nfrom pygame import Surface, Vector2\nfrom typing import TYPE_CHECKING, List, Optional, Tuple, Union\n\nfrom .map import DMDungeonMap\nfrom utilities import *\n\nif TYPE_CHECKING:\n from .game import DMGame\n from ..objects.hero import DMHero\n from ..objects.monster import DMMonster\n from ..objects.room import DMRoom\n from ..objects.relic import DMRelic\n from ...rooms.special.Entrance import EntranceRoom\n################################################################################\n\n__all__ = (\"DMDungeon\",)\n\n################################################################################\nclass DMDungeon:\n\n __slots__ = (\n \"game\",\n \"heroes\",\n \"map\",\n \"spawned\"\n )\n\n################################################################################\n def __init__(self, game: DMGame):\n\n self.game: DMGame = game\n self.heroes: List[DMHero] = []\n self.map = DMDungeonMap(self)\n\n self.spawned = False\n\n################################################################################\n def __getitem__(self, index: int) -> List[Optional[DMRoom]]:\n\n return self.map[index]\n\n################################################################################\n def draw(self, screen: Surface) -> None:\n\n self.map.draw(screen)\n\n################################################################################\n def update(self, dt: float) -> None:\n\n self.map.update(dt)\n self.game.dark_lord.update(dt)\n\n###############################################################################\n def get_room_at(self, pos: Union[Vector2, Tuple[int, int]]) -> Optional[DMRoom]:\n\n print(pos)\n return self.map.get_room_at(Vector2(pos))\n\n################################################################################\n def all_rooms(self, entry: bool = False, boss: bool = False, empty: bool = False) -> List[DMRoom]:\n\n return self.map.all_rooms(entry, boss, empty)\n\n################################################################################\n def modify_hero_spawn_rate(self, amount: Union[int, float]) -> None:\n\n if not isinstance(amount, (int, float)):\n raise ArgumentTypeError(\n \"Invalid type passed to DMDungeon.modify_hero_spawn_rate()\",\n type(amount),\n type(int), type(float)\n )\n\n self.map.modify_hero_spawn_rate(amount)\n\n################################################################################\n @property\n def highlighting(self) -> bool:\n\n return self.map.highlighting\n\n################################################################################\n def reset_highlighting(self) -> None:\n\n self.map.reset_highlighting()\n\n################################################################################\n def toggle_highlighting(self, value: bool) -> None:\n\n self.map.toggle_highlighting(value)\n\n################################################################################\n def get_highlighted_room(self) -> Optional[DMRoom]:\n\n return self.map.get_highlighted_room()\n\n################################################################################\n def get_adjacent_rooms(\n self,\n pos: Vector2,\n *,\n show_west: bool = False,\n show_east: bool = False,\n show_north: bool = False,\n show_south: bool = False,\n all_rooms: bool = True,\n include_current: bool = False\n ) -> List[DMRoom]:\n\n return self.map.get_all_adjacent_rooms(\n pos, show_west, show_east, show_north,\n show_south, all_rooms, include_current\n )\n\n################################################################################\n def get_adjacent_monsters(\n self,\n pos: Vector2,\n *,\n include_west: bool = False,\n include_east: bool = False,\n include_north: bool = False,\n include_south: bool = False,\n all_rooms: bool = True,\n include_current: bool = False\n ) -> List[DMMonster]:\n \n rooms = self.get_adjacent_rooms(\n pos, show_west=include_west, show_east=include_east, show_north=include_north,\n show_south=include_south, all_rooms=all_rooms, include_current=include_current\n )\n \n monsters = []\n for room in rooms:\n try:\n monsters.extend(room.monsters) # type: ignore\n except AttributeError:\n pass\n \n return monsters\n \n################################################################################\n @property\n def deployed_monsters(self) -> List[DMMonster]:\n\n return self.game.inventory.deployed_monsters\n\n################################################################################\n def upgrade_random_monster(self, include_inventory: bool = False) -> DMMonster:\n\n choice = random.choice(self.game.inventory.monsters)\n choice.upgrade()\n\n return choice\n\n################################################################################\n def spawn_hero(self) -> DMHero:\n\n if not self.spawned:\n hero = self.game.spawn(\n spawn_type=SpawnType.Hero,\n end_rank=1\n )(self.game, self.game.dungeon.entrance)\n self.heroes.append(hero) # type: ignore\n self.spawned = True\n\n return hero # type: ignore\n\n################################################################################\n @property\n def entrance(self) -> EntranceRoom:\n\n return self.map[len(self.map) // 2][len(self.map[0]) - 1] # type: ignore\n\n################################################################################\n def get_heroes_by_room(self, pos: Vector2) -> List[DMHero]:\n\n return self.get_room_at(pos).heroes\n\n################################################################################\n def get_monsters_by_room(self, pos: Vector2) -> List[DMHero]:\n\n room = self.get_room_at(pos)\n if room.room_type is not RoomType.Battle:\n return []\n\n return room.monsters # type: ignore\n\n################################################################################\n def extend_map(self, relic: DMRelic) -> None:\n\n self.map.extend_grid(relic)\n\n################################################################################\n def replace_room(self, room: DMRoom, replacement: DMRoom) -> None:\n\n self.map.replace_room(room, replacement)\n\n################################################################################\n","repo_name":"AllegroVivo/DungeonDefense","sub_path":"dm/core/game/dungeon.py","file_name":"dungeon.py","file_ext":"py","file_size_in_byte":6724,"program_lang":"python","lang":"de","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"3966620845","text":"import subprocess\nimport shlex\nimport os\nimport zipfile\n#import pandas as pd\nfrom src.common.webtools import credentials as crd\n\n\nclass MTSN(object):\n\n def __init__(self, serial_number):\n self.serial = serial_number.upper()\n self.mtm = self.get_mtm()\n self.sn = self.get_sn()\n self.mtsn = self.get_mtsn()\n self.paths_l2_mtsn = self.get_available_mtsn_l2()\n # self.pathl3 = self.get_list_path_l3() # despues de una semana, se mueve al L3_BKUP\n\n def get_mtm(self):\n return self.serial[2:].split(\"J\")[0] # Remove 1S and get the 1st splitted str before 'J' (sn)\n\n def get_sn(self):\n return self.serial[2:].replace(self.mtm, '') # Remove 1S and MTM to get the sn\n\n def get_mtsn(self):\n mtsn_list = []\n if len(self.sn) > 7:\n mtsn_list.append('{}'.format(self.sn)) # MTSN - Purley\n else:\n mtsn_list.append('0{}'.format(self.sn))\n mtsn_list.append('{}{}.{}'.format(self.mtm[:4], self.sn[:4], self.sn[4:])) # MTSN - Legacy\n \"\"\"\n Quick fix to get a uniq mtsn... not a list of 2 mtsn\n \"\"\"\n for mtsn in mtsn_list:\n cmd = 'ssh 10.34.70.220 ls /dfcxact/mtsn/{}'.format(mtsn)\n args = shlex.split(cmd)\n r = subprocess.run(args=args, universal_newlines=False, stdout=subprocess.PIPE)\n if r.returncode != 0:\n mtsn_list.remove(mtsn)\n return mtsn_list[0]\n\n def get_available_mtsn_l2(self):\n return self.check_exists_mtsn(paths=self.path_l2(self.mtsn), server='10.34.70.220')\n\n\n def check_exists_mtsn(self, paths, server):\n \"\"\"\n This method check if a folder mtsn exists and return the list of mtsn available\n :param paths: This is a list of paths \"/dfcxact/.../\"\n :param server: L2 or BKUP\n :return: list of mtsn available\n \"\"\"\n mtsn_exists = []\n for path in paths:\n command = 'test -d ' + path + ' && echo True || echo False'\n remote_shell = 'ssh ' + server + ' ' + command\n args = shlex.split(remote_shell)\n shell_result = subprocess.run(args=args, universal_newlines=False, stdout=subprocess.PIPE)\n if shell_result.stdout.strip().decode('ascii') == 'True':\n mtsn_exists.append(path)\n return mtsn_exists\n\n def path_l2(self, mtsn):\n path_l2 = []\n path_l2.append('/dfcxact/mtsn/{}'.format(mtsn)) # Index 0\n path_l2.append('/dfcxact/old-mtsn/{}'.format(mtsn)) # Index 1\n path_l2.append('/dfcxact/work/old_mtsn/{}'.format(mtsn)) # Index 2\n return path_l2\n\n def path_bkup(self, mtsn):\n path = '/data/old-mtsn/*/{}'.format(mtsn)\n comm = 'ssh 10.34.70.223 ls -d ' + path\n args = shlex.split(comm)\n r = subprocess.run(args=args, universal_newlines=False, stderr=subprocess.PIPE)\n if r.stderr is not None:\n print('There is a mtsn in server-backup and it is: {}'.format())\n return r.stdout.decode('ascii').split() # List of the found mtsn-paths\n else:\n return None # There is no mtsn in backup-server\n # Example :\n # ['/data/old-mtsn/16-12-50/5465J103.G64',\n # '/data/old-mtsn/16-12-51/5465J103.G64',\n # '/data/old-mtsn/16-12-52/5465J103.G64']\n\n @staticmethod\n def copy_folder(mtsn, path, server):\n here = path.replace(mtsn, '')\n cmd = 'scp -r ' + server + ':' + path + ' ' + here\n args = shlex.split(cmd)\n r = subprocess.run(args=args, universal_newlines=False, stdout=subprocess.PIPE)\n return r.returncode # 0 means it ran successfully!\n\n @staticmethod\n def zip_mtsn(path, mtsn):\n \"\"\"\n :param path: /dfcxact/old-mtsn/J1003EMG/\n :param mtsn: J1003EMG\n :return: 0 if the .zip was created . . .\n \"\"\"\n cwdpath = os.getcwd() # save original path (*where you run this py file)\n zip_name = mtsn + '.zip'\n path_mtsn = path.replace(mtsn, '')\n absfolder = os.path.abspath(path_mtsn) # make sure folder is absolute\n os.chdir(absfolder)\n # Create Zipfile at absfolder ....could be: /dfcxact/mtsn\n zf = zipfile.ZipFile(zip_name, \"w\")\n for dirs, subdirs, files in os.walk('./' + mtsn):\n zf.write(dirs)\n for filename in files:\n zf.write(os.path.join(dirs, filename))\n zf.close()\n os.chdir(cwdpath)\n \"\"\"\n This is a very simple solution...\n Pending provide a clean up for mtsn and its .zip files\n \"\"\"\n cmd = 'ls ' + path_mtsn + mtsn + '.zip'\n args = shlex.split(cmd)\n r = subprocess.run(args=args, universal_newlines=False, stdout=subprocess.PIPE)\n return r.returncode # 0 means it ran successfully!\n","repo_name":"ObedEG/complex_web","sub_path":"src/common/webtools/mtsn.py","file_name":"mtsn.py","file_ext":"py","file_size_in_byte":4830,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"44449587471","text":"from collections import Iterable\nfrom typing import List\nfrom functools import partial\n\nfrom keras.preprocessing.sequence import pad_sequences\nfrom keras.preprocessing.text import Tokenizer, text_to_word_sequence\nfrom keras.preprocessing.image import img_to_array, load_img\nfrom keras.applications import inception_v3\nfrom PIL import Image\nimport numpy as np\n\nfrom .config import base_configuration\n\n\nclass ImagePreprocessor(object):\n IMAGE_SIZE = (299, 299) # Inceptionv3 input size\n\n def __init__(self):\n self.pad_images = base_configuration['params']['pad_images']\n self.image_cache = {}\n\n def preprocess_image(self, path):\n if self.pad_images:\n image = self.pad_image(load_img(path), self.IMAGE_SIZE)\n else:\n image = load_img(path, target_size=self.IMAGE_SIZE)\n image_array = img_to_array(image)\n image_array = inception_v3.preprocess_input(image_array)\n return image_array\n\n def preprocess_batch(self, image_list):\n return np.array(image_list)\n\n def preprocess_images(self, image_paths):\n # return [partial(self.preprocess_image)(path) for path in image_paths]\n return list(map(partial(self.preprocess_image), image_paths))\n\n def pad_image(self, img, padded_size):\n width, height = img.size\n if width > height:\n new_size = (padded_size[0], round(height * padded_size[0] / width))\n else:\n new_size = (round(width * padded_size[1] / height), padded_size[1])\n img = img.resize(new_size)\n\n padded_img = Image.new('RGB', self.IMAGE_SIZE)\n topleft = ((padded_size[0] - new_size[0]) // 2, (padded_size[1] - new_size[1]) // 2)\n padded_img.paste(img, topleft)\n return padded_img\n\n\nclass CaptionPreprocessor(object):\n # End of sentence token\n EOS_TOKEN = 'zeosz'\n\n def __init__(self):\n self.tokenizer = Tokenizer()\n self.word_dictionary = {}\n self.word_of = None\n\n @property\n def EOS_TOKEN_LABEL_ENCODED(self):\n return self.tokenizer.word_index[self.EOS_TOKEN]\n\n def eos_index(self):\n \"\"\"\n Returns id of the EOS token in the vocabulary\n :return: id of the EOS token in the vocabulary\n \"\"\"\n return self.tokenizer.word_index[self.EOS_TOKEN]\n\n def vocabs(self):\n \"\"\"\n Returns word index of vocabulary sorted by the ids\n :return: word index of vocabulary sorted by the ids\n \"\"\"\n word_index = self.tokenizer.word_index\n return sorted(word_index, key=word_index.get)\n\n @property\n def vocab_size(self):\n return len(self.tokenizer.word_index)\n\n def add_eos(self, captions: Iterable):\n # return (caption + ' ' + self.EOS_TOKEN for caption in captions)\n return map(lambda x: x + ' ' + self.EOS_TOKEN, captions)\n\n def preprocess_captions(self, captions: List[str]):\n # TODO: handle rare words\n captions = self.add_eos(captions)\n self.tokenizer.fit_on_texts(captions)\n self.word_dictionary = {index: word for word, index in self.tokenizer.word_index.items()}\n\n def encode_captions(self, captions: Iterable):\n captions = self.add_eos(captions)\n return self.tokenizer.texts_to_sequences(captions)\n\n def decode_captions(self, captions_prediction, expected_captions=None):\n \"\"\"\n Decodes predicted captions (in one-hot-encoding) into strings.\n :param captions_prediction: captions_prediction: numpy array of one-hot encoded captions\n :param expected_captions: the captions that should be predicted\n :return: list of captions decoded as strings\n \"\"\"\n captions = captions_prediction[:, :-1, :] # Discard the one-hot encoded EOS token\n decoded_labels = captions.argmax(axis=-1) # Returns indices of highest value in array (which is the number that was one-hot encoded)\n num_batches, num_words = decoded_labels.shape\n\n if expected_captions is not None:\n captions_length = self.captions_length(expected_captions)\n else:\n captions_length = [num_words] * num_batches # Placeholder with which we read all words\n\n decoded_captions = []\n for caption_index in range(0, num_batches):\n caption_string = []\n for word_index in range(0, captions_length[caption_index]):\n label = decoded_labels[caption_index, word_index]\n # print(decoded_labels)\n # print(\"WORDS\")\n # print(\"\\n\".join(self.word_dictionary))\n label += 1\n # caption_string.append(self.word_dictionary[label])\n caption_string.append(self.word_dictionary.get(label, \"BROKEN\"))\n decoded_captions.append(' '.join(caption_string))\n\n return decoded_captions\n\n def preprocess_batch(self, captions_label_encoded):\n captions = pad_sequences(captions_label_encoded, padding=\"post\") # pad with trailing zeros\n\n # The number of timesteps/words the model outputs is maxlen(captions) + 1 because the first \"word\" is an image\n captions_extended1 = pad_sequences(captions, maxlen=captions.shape[-1] + 1, padding=\"post\")\n # captions_one_hot = [self.tokenizer.sequences_to_matrix(seq) for seq in np.expand_dims(captions_extended1, -1)]\n captions_one_hot = list(map(self.tokenizer.sequences_to_matrix, np.expand_dims(captions_extended1, -1)))\n captions_one_hot = np.array(captions_one_hot, dtype=\"int\")\n\n # Left-shift one-hot encoding by one to set padding to 0 (so that error will be 0.0)\n # Decrease indices to adjust for change in one-hot encoding\n captions_decreased = captions.copy()\n captions_decreased[captions_decreased > 0] -= 1\n captions_one_hot_shifted = captions_one_hot[:, :, 1:]\n\n captions_input = captions_decreased\n captions_output = captions_one_hot_shifted\n return captions_input, captions_output\n\n def normalize_captions(self, captions: List[str]):\n # word_sequences = (text_to_word_sequence(elem) for elem in self.add_eos(captions))\n word_sequences = map(text_to_word_sequence, self.add_eos(captions))\n # return (' '.join(caption) for caption in word_sequences)\n return map(' '.join, word_sequences)\n\n def captions_length(self, captions):\n \"\"\"\n Calculates the lengths of the passed captions.\n :param captions: three-dimensional numpy array containing a batch of one-hot encoded captions\n :return: numpy array of the captions lengths (number of words in a caption)\n \"\"\"\n collapsed_one_hot_encodings = captions.sum(axis=2)\n zero_filtered_captions = collapsed_one_hot_encodings != 0\n caption_lengths = zero_filtered_captions.sum(axis=1)\n return caption_lengths\n\n def fit_on_captions(self, captions_txt):\n # captions_txt = self.handle_rare_words(captions_txt)\n captions_txt = self.add_eos(captions_txt)\n self.tokenizer.fit_on_texts(captions_txt)\n self.word_of = {i: w for w, i in self.tokenizer.word_index.items()}\n","repo_name":"janehmueller/DeepLearningChallenge","sub_path":"util/preprocessors.py","file_name":"preprocessors.py","file_ext":"py","file_size_in_byte":7124,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"8351035797","text":"class PartyAnimal:\n _x = 0\n _name = \"\"\n\n def __init__(self,name):\n _name = name\n\n def party(self):\n self._x = self._x + 1\n print(\"So far\", self._x)\n\n\nan = PartyAnimal(\"Sully\")\n\nan.party()\n\n\n\n\n# Type of the object\nprint(\"Type\", type(an))\n\n# It shows all the methods and attributes of a class\nprint(\"Dir\", dir(an))\n","repo_name":"Diegou2304/using-database-with-python","sub_path":"Week1/class_and_object.py","file_name":"class_and_object.py","file_ext":"py","file_size_in_byte":346,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"41424077385","text":"import random\nsecretNumber = random.randint(1, 20) #randomly selects a number for the game\nprint('I am thinking of a number between 1 and 20.')\n\nfor guesstaken in range(1, 7): #playger can take only six guesses\n print ('Guess a number:')\n number=int(input())\n \n if number > secretNumber: \n print ('Guess too high')\n elif number < secretNumber:\n print ('Guess too low')\n else:\n break\n \nif number==secretnumber:\n print('Good job! You guessed my number in ' + str(guessesTaken) + ' guesses!')\nelse:\n print('Nope. The number I was thinking of was ' + str(secretNumber))\n\n","repo_name":"muskankapoor/fall2017projects","sub_path":"Python/guessing game.py","file_name":"guessing game.py","file_ext":"py","file_size_in_byte":615,"program_lang":"python","lang":"en","doc_type":"code","stars":0,"dataset":"github-code","pt":"3"} +{"seq_id":"36403652374","text":"import pytest\nfrom u2s_sdk.client import ApiClient\nfrom u2s_sdk.handler import ResumableUploadHandler\n\n@pytest.fixture\ndef client(mocker):\n return ApiClient(base_url='https://test-api.com')\n\ndef test_start_upload_successful(client, mocker):\n # Mock the post method of the ApiClient to simulate a successful start_upload request\n mocker.patch.object(client, 'post', return_value=mocker.Mock(status_code=201, headers={'Location': '/upload?key=123'}))\n\n handler = ResumableUploadHandler(client)\n location_uri, upload_key = handler.start_upload('test.txt', 1024)\n\n assert location_uri == '/upload?key=123'\n assert upload_key == '123'\n\ndef test_start_upload_failed(client, mocker):\n # Mock the post method of the ApiClient to simulate a failed start_upload request\n mocker.patch.object(client, 'post', return_value=mocker.Mock(status_code=400))\n\n handler = ResumableUploadHandler(client)\n\n with pytest.raises(Exception, match=r'Failed to initiate resumable upload\\. Status code: 400'):\n handler.start_upload('test.txt', 1024)\n\ndef test_upload_chunk_successful(client, mocker):\n # Mock the put method of the ApiClient to simulate a successful upload_chunk request\n mocker.patch.object(client, 'put', return_value=mocker.Mock(status_code=201, headers={}))\n\n handler = ResumableUploadHandler(client)\n response_headers = handler.upload_chunk('/upload?key=123', 4, b'data', 0, 3)\n\n assert response_headers == {}\n\ndef test_upload_chunk_in_progress(client, mocker):\n # Mock the put method of the ApiClient to simulate an in-progress upload_chunk request\n mocker.patch.object(client, 'put', return_value=mocker.Mock(status_code=308))\n\n handler = ResumableUploadHandler(client)\n response_headers = handler.upload_chunk('/upload?key=123', 4, b'data', 0, 2)\n\n assert response_headers is False\n\ndef test_upload_chunk_failed(client, mocker):\n # Mock the put method of the ApiClient to simulate a failed upload_chunk request\n mocker.patch.object(client, 'put', return_value=mocker.Mock(status_code=400))\n\n handler = ResumableUploadHandler(client)\n\n with pytest.raises(Exception, match=r'Failed to upload chunk\\. Status code: 400'):\n handler.upload_chunk('/upload?key=123', 1024, b'data', 0, 3)\n\n# Add more test cases for the ResumableUploadHandler class as needed\n","repo_name":"up2share/python-sdk","sub_path":"tests/test_handler.py","file_name":"test_handler.py","file_ext":"py","file_size_in_byte":2334,"program_lang":"python","lang":"en","doc_type":"code","stars":1,"dataset":"github-code","pt":"3"} +{"seq_id":"10525946523","text":"import os\r\nimport inspect\r\n\r\n\r\nfrom OpenGL.GL import *\r\n\r\n\r\n_program = -1\r\n_fragment = (\"fragment.glsl\", GL_FRAGMENT_SHADER)\r\n_vertex = (\"vertex.glsl\", GL_VERTEX_SHADER)\r\n_shaders = (_fragment, _vertex)\r\n\r\n\r\ndef get_program():\r\n\tglobal _program\r\n\r\n\tif _program != -1:\r\n\t\treturn _program\r\n\r\n\t_program = glCreateProgram()\r\n\r\n\tfile = inspect.getfile(inspect.currentframe())\r\n\t_dir = os.path.dirname(os.path.abspath(file)) + '/'\r\n\tfor shader in _shaders:\r\n\t\twith open(_dir+shader[0]) as fin:\r\n\t\t\tsource = fin.read()\r\n\t\t\tobj = glCreateShader(shader[1])\r\n\t\t\tglShaderSource(obj, source)\r\n\t\t\tglCompileShader(obj)\r\n\t\t\tlog = glGetShaderInfoLog(obj).decode()\r\n\t\t\tif log:\r\n\t\t\t\tprint(log)\r\n\r\n\t\t\tglAttachShader(_program, obj)\r\n\r\n\tglLinkProgram(_program)\r\n\tlog = glGetProgramInfoLog(_program).decode()\r\n\tif log:\r\n\t\tprint(log)\r\n\r\n\treturn _program","repo_name":"Kupoman/conceptparticles","sub_path":"particles/shaders.py","file_name":"shaders.py","file_ext":"py","file_size_in_byte":830,"program_lang":"python","lang":"en","doc_type":"code","stars":5,"dataset":"github-code","pt":"3"} +{"seq_id":"7742353266","text":"# this is created explicitly by programmers.\nfrom django.http import HttpResponse\nfrom django.shortcuts import render\n\n\ndef index(request):\n # return HttpResponse('

hello raj