Best Python code snippet using playwright-python
World.py
Source: World.py
1#!/usr/bin/env python32# -*- coding: utf-8 -*-3"""4Created on Mon Jul 27 12:12:00 20205@author: andresmauriciotrianareina6"""7import numpy as np8import pandas as pd9import chart_studio.plotly as py10import plotly.graph_objs as go11import plotly.graph_objects as go12import cufflinks as cf13import seaborn as sns14import matplotlib.pyplot as plt15from matplotlib.pyplot import show16from pandas.plotting import register_matplotlib_converters17#%matplotlib inline18from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot19import plotly20import plotly.express as px21import time22from datetime import date, timedelta23from datetime import time24from datetime import datetime25import dash26import dash_core_components as dcc27import dash_html_components as html28from dash.dependencies import Input, Output29#####################################30#Data31df = pd.read_csv('https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/owid-covid-data.csv')32date_string = df['date']33#date_object = date_string.strptime('%Y,-%m')34#date_object = datetime.strptime(date_string, '%Y-%m')35df ['Year'] = df['date'].apply(lambda t: t.split('-')[0])36df ['Month'] = df['date'].apply(lambda t: t.split('-')[1])37df ['Year - Month'] = df ['Year'] + '-' + df ['Month']38#### Fecha39yesterday = date.today()-timedelta(days=1)40#yesterday = date.today()41fecha = yesterday.strftime("%Y-%m-%d")42#today = date.today()43#fecha = today.strftime("%Y-%m-%d")44otro = df['date'] == fecha45otro2 = df[otro]46with_world = otro2['location'] != 'World'47with_int1 = otro2[with_world]48with_int2 = with_int1['location'] != 'International'49actual = with_int1[with_int2]50### reemplazar valores nuos con 051#actual = actual.fillna(0)52df_order_total_cases = actual.sort_values('total_cases',ascending=False)53#df_order_total_cases.head()54df_order_total_death = actual.sort_values('total_deaths',ascending=False)55#df_order_total_death.head()56uno = (df['location'] != 'World') & (df['continent'] != 'International')57uno2 = df[uno]58uno3 = uno2['location'] != 'International'59uno4 = uno2[uno3]60sud = df['continent'] =='South America'61sudamerica = df[sud]62uno = (df['location'] != 'World') & (df['continent'] != 'International')63uno2 = df[uno]64uno3 = uno2['location'] != 'International'65uno4 = uno2[uno3]66uno5 = sudamerica['date'] == fecha67subamerica_hoy = sudamerica[uno5]68Wd = df['location'] == 'World'69World = df[Wd]70df_order_total_cases_per_mill = actual.sort_values('total_cases_per_million',ascending=False)71df_order_total_deaths_per_mill = actual.sort_values('total_deaths_per_million',ascending=False)72##### creación de graficas73def figures_to_html(figs, filename="20paisescontagios.html"):74 dashboard = open(filename, 'w')75 dashboard.write("<html><head></head><body>" + "\n")76 for fig in figs:77 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]78 dashboard.write(inner_html)79 dashboard.write("</body></html>" + "\n")80 81fig1 = px.bar(df_order_total_cases.head(20), x = 'location', y = 'total_cases', barmode='relative') 82 83figures_to_html([fig1])84def figures_to_html(figs, filename="20paisesmuertes.html"):85 dashboard = open(filename, 'w')86 dashboard.write("<html><head></head><body>" + "\n")87 for fig in figs:88 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]89 dashboard.write(inner_html)90 dashboard.write("</body></html>" + "\n")91 92fig1 = px.bar(df_order_total_death.head(20), x = 'location', y = 'total_deaths', barmode='relative')93figures_to_html([fig1])94def figures_to_html(figs, filename="Continente_contagios.html"):95 dashboard = open(filename, 'w')96 dashboard.write("<html><head></head><body>" + "\n")97 for fig in figs:98 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]99 dashboard.write(inner_html)100 dashboard.write("</body></html>" + "\n")101 102fig1 = px.pie(actual, values='total_cases', names='continent')103figures_to_html([fig1])104def figures_to_html(figs, filename="Continente_muertes.html"):105 dashboard = open(filename, 'w')106 dashboard.write("<html><head></head><body>" + "\n")107 for fig in figs:108 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]109 dashboard.write(inner_html)110 dashboard.write("</body></html>" + "\n")111 112fig1 = px.pie(actual, values='total_deaths', names='continent')113figures_to_html([fig1])114def figures_to_html(figs, filename="Contagiados_Fecha_Paises.html"):115 dashboard = open(filename, 'w')116 dashboard.write("<html><head></head><body>" + "\n")117 for fig in figs:118 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]119 dashboard.write(inner_html)120 dashboard.write("</body></html>" + "\n")121 122fig1 = px.line(df, x='date', y='total_cases', color='location')123figures_to_html([fig1])124def figures_to_html(figs, filename="fecha_Muertes_Paises.html"):125 dashboard = open(filename, 'w')126 dashboard.write("<html><head></head><body>" + "\n")127 for fig in figs:128 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]129 dashboard.write(inner_html)130 dashboard.write("</body></html>" + "\n")131 132fig1 = px.line(df, x='date', y='total_deaths', color='location')133figures_to_html([fig1])134def figures_to_html(figs, filename="Numero_contagios_fecha.html"):135 dashboard = open(filename, 'w')136 dashboard.write("<html><head></head><body>" + "\n")137 for fig in figs:138 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]139 dashboard.write(inner_html)140 dashboard.write("</body></html>" + "\n")141 142fig1 = px.line(World, x='date', y='total_cases')143figures_to_html([fig1])144def figures_to_html(figs, filename="Numero_muertes_fecha.html"):145 dashboard = open(filename, 'w')146 dashboard.write("<html><head></head><body>" + "\n")147 for fig in figs:148 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]149 dashboard.write(inner_html)150 dashboard.write("</body></html>" + "\n")151 152fig1 = px.line(World, x='date', y='total_deaths')153figures_to_html([fig1])154def figures_to_html(figs, filename="Mapa_Mundo_contagios.html"):155 dashboard = open(filename, 'w')156 dashboard.write("<html><head></head><body>" + "\n")157 for fig in figs:158 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]159 dashboard.write(inner_html)160 dashboard.write("</body></html>" + "\n")161 162data = dict (type = 'choropleth',163 locations = actual['iso_code'],164 z = actual['total_cases'],165 text = actual['location'],166 colorbar = {'title': 'Contagiados'})167layout = dict (geo = dict (showframe = False, projection = {'type':'mercator'}))168choromap = go.Figure(data = [data], layout =layout) 169figures_to_html([choromap])170def figures_to_html(figs, filename="Mapa_Mundo_muertes.html"):171 dashboard = open(filename, 'w')172 dashboard.write("<html><head></head><body>" + "\n")173 for fig in figs:174 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]175 dashboard.write(inner_html)176 dashboard.write("</body></html>" + "\n")177 178data2 = dict (type = 'choropleth',179 locations = actual['iso_code'],180 z = actual['total_deaths'],181 text = actual['location'],182 colorbar = {'title': 'Muertes'})183layout2 = dict (geo = dict (showframe = False, projection = {'type':'mercator'}))184choromap2 = go.Figure(data = [data2], layout =layout2)185figures_to_html([choromap2])186def figures_to_html(figs, filename="Tabla_contagiados_fallecidos.html"):187 dashboard = open(filename, 'w')188 dashboard.write("<html><head></head><body>" + "\n")189 for fig in figs:190 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]191 dashboard.write(inner_html)192 dashboard.write("</body></html>" + "\n")193 194 195#Today = date.today()196#fecha2 = Today.strftime("%Y-%m-%d")197yesterday = date.today()-timedelta(days=1)198fecha2 = yesterday.strftime("%Y-%m-%d")199otro = df['date'] == fecha2200otro2 = df[otro]201Only_world1 = otro2['location'] == 'World'202Only_world2 = otro2[Only_world1]203#Contagi = actual['total_cases'].sum()204Contagi = Only_world2['total_cases'].sum()205Total_deaths = Only_world2['total_deaths'].sum()206total_res_wor = pd.DataFrame({'Contagiados': [Contagi],'Fallecidos': [Total_deaths], 'Fecha':[fecha2]})207fig1 = go.Figure(data=[go.Table(208 header=dict(values=list(total_res_wor.columns),209 fill_color='rgba(15, 78, 64, 0.1)',210 align='center'),211 cells=dict(values=[total_res_wor.Contagiados, total_res_wor.Fallecidos, total_res_wor.Fecha ],212 fill_color='rgba(255, 255, 255, 0.1)',213 align='center',214 format = [",.0f", ",.0f",None]))215])216figures_to_html([fig1])217yesterday = date.today()-timedelta(days=1)218#yesterday = date.today()219fecha = yesterday.strftime("%Y-%m-%d")220otro = df['date'] == fecha221otro2 = df[otro]222with_world = otro2['location'] != 'World'223with_int1 = otro2[with_world]224with_int2 = with_int1['location'] != 'International'225actual = with_int1[with_int2]226def figures_to_html(figs, filename="Cases_per_millon.html"):227 dashboard = open(filename, 'w')228 dashboard.write("<html><head></head><body>" + "\n")229 for fig in figs:230 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]231 dashboard.write(inner_html)232 dashboard.write("</body></html>" + "\n")233 234 235fig1 = px.bar(df_order_total_cases_per_mill.head(20), x = 'location', y = 'total_cases_per_million')236figures_to_html([fig1])237def figures_to_html(figs, filename="deaths_per_millon.html"):238 dashboard = open(filename, 'w')239 dashboard.write("<html><head></head><body>" + "\n")240 for fig in figs:241 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]242 dashboard.write(inner_html)243 dashboard.write("</body></html>" + "\n")244 245 246fig1 = px.bar(df_order_total_deaths_per_mill.head(20), x = 'location', y = 'total_deaths_per_million')247figures_to_html([fig1])248def figures_to_html(figs, filename="deaths_extreme_poverty.html"):249 dashboard = open(filename, 'w')250 dashboard.write("<html><head></head><body>" + "\n")251 for fig in figs:252 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]253 dashboard.write(inner_html)254 dashboard.write("</body></html>" + "\n")255 256 257#fig1 = px.scatter(actual, x="extreme_poverty", y="total_deaths", color = "continent")258#figures_to_html([fig1])259def figures_to_html(figs, filename="cardiovasc_death_rate.html"):260 dashboard = open(filename, 'w')261 dashboard.write("<html><head></head><body>" + "\n")262 for fig in figs:263 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]264 dashboard.write(inner_html)265 dashboard.write("</body></html>" + "\n")266 267 268#fig1 = px.scatter(actual, x="cardiovasc_death_rate", y="total_deaths", color = "continent")269#figures_to_html([fig1])270def figures_to_html(figs, filename="diabetes_prevalence.html"):271 dashboard = open(filename, 'w')272 dashboard.write("<html><head></head><body>" + "\n")273 for fig in figs:274 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]275 dashboard.write(inner_html)276 dashboard.write("</body></html>" + "\n")277 278 279#fig1 = px.scatter(actual, x="diabetes_prevalence", y="total_deaths", color = "continent")280#figures_to_html([fig1])281def figures_to_html(figs, filename="New_cases_per_millon.html"):282 dashboard = open(filename, 'w')283 dashboard.write("<html><head></head><body>" + "\n")284 for fig in figs:285 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]286 dashboard.write(inner_html)287 dashboard.write("</body></html>" + "\n")288 289 290df_order_new_cases_per_mill = actual.sort_values('new_cases_per_million',ascending=False)291fig1 = px.bar(df_order_new_cases_per_mill.head(20), x = 'location', y = 'new_cases_per_million')292figures_to_html([fig1])293def figures_to_html(figs, filename="New_deaths_per_millon.html"):294 dashboard = open(filename, 'w')295 dashboard.write("<html><head></head><body>" + "\n")296 for fig in figs:297 inner_html = fig.to_html().split('<body>')[1].split('</body>')[0]298 dashboard.write(inner_html)299 dashboard.write("</body></html>" + "\n")300 301 302df_order_new_deaths_per_mill = actual.sort_values('new_deaths_per_million',ascending=False)303fig1 = px.bar(df_order_new_deaths_per_mill.head(20), x = 'location', y = 'new_deaths_per_million')...
builders.py
Source: builders.py
...9import components.stocks as stocks10import components.monitor as monitor11import components.logging as logging12from configuration import config13def build_header_now_playing_column_inner_html():14 template = '''15 <div id="now-playing-metadata" data-track-uri="{track_uri}" data-playlist-uri="{playlist_uri}">16 <div id="now-playing-playlist">{playlist_name}</div>17 <div id="now-playing-song">{track_name}</div>18 </div>19 <div id="now-playing-image-container">20 <div id="now-playing-image-overlay" onclick="spotifyPlaylistRemoveButtonClicked()">21 <img id="now-playing-image" data-destination="{destination}" src="/spotify/now_playing.jpeg" />22 </div>23 </div>24 '''25 tn, turi, pn, puri = None, None, None, None #spotify.now_playing_info()26 if tn == None:27 tn = '-'...
WebScrapingPartida.py
Source: WebScrapingPartida.py
...28 VermelhoQuatro = page.query_selector("#__next > div.css-1n276kj.eafu1dm0 > div.css-yspf3p.e1k2e1zv5 > table.css-18rus4b.e1snzzz71 > tbody > tr:nth-child(4) > td.summoner-name > a")29 VermelhoQuatroElo = page.query_selector("#__next > div.css-1n276kj.eafu1dm0 > div.css-yspf3p.e1k2e1zv5 > table.css-18rus4b.e1snzzz71 > tbody > tr:nth-child(4) > td.current-rank > div")30 VermelhoCinco = page.query_selector("#__next > div.css-1n276kj.eafu1dm0 > div.css-yspf3p.e1k2e1zv5 > table.css-18rus4b.e1snzzz71 > tbody > tr:nth-child(5) > td.summoner-name > a")31 VermelhoCincoElo = page.query_selector("#__next > div.css-1n276kj.eafu1dm0 > div.css-yspf3p.e1k2e1zv5 > table.css-18rus4b.e1snzzz71 > tbody > tr:nth-child(5) > td.current-rank > div")32 AzulUm_ = (AzulUm.inner_html()); AzulUmElo_ = (AzulUmElo.inner_html())33 AzulDois_ = (AzulDois.inner_html()); AzulDoisElo_ = (AzulDoisElo.inner_html())34 AzulTres_ = (AzulTres.inner_html()); AzulTresElo_ = (AzulTresElo.inner_html())35 AzulQuatro_ = (AzulQuatro.inner_html()); AzulQuatroElo_ = (AzulQuatroElo.inner_html())36 AzulCinco_ = (AzulCinco.inner_html()); AzulCincoElo_ = (AzulCincoElo.inner_html())37 VermelhoUm_ = (VermelhoUm.inner_html()); VermelhoUmElo_ = (VermelhoUmElo.inner_html())38 VermelhoDois_ = (VermelhoDois.inner_html()); VermelhoDoisElo_ = (VermelhoDoisElo.inner_html())39 VermelhoTres_ = (VermelhoTres.inner_html()); VermelhoTresElo_ = (VermelhoTresElo.inner_html())40 VermelhoQuatro_ = (VermelhoQuatro.inner_html()); VermelhoQuatroElo_ = (VermelhoQuatroElo.inner_html())41 VermelhoCinco_ = (VermelhoCinco.inner_html()); VermelhoCincoElo_ = (VermelhoCincoElo.inner_html())42 times = (f'Time Azul: \n \n {AzulUm_} - {AzulUmElo_} \n {AzulDois_} - {AzulDoisElo_}\n {AzulTres_} - {AzulTresElo_}\n {AzulQuatro_} - {AzulQuatroElo_}\n {AzulCinco_} - {AzulCincoElo_}\n\n Time Vermelho: \n \n {VermelhoUm_} - {VermelhoUmElo_} \n {VermelhoDois_} - {VermelhoDoisElo_} \n {VermelhoTres_} - {VermelhoTresElo_} \n {VermelhoQuatro_} - {VermelhoQuatroElo_} \n {VermelhoCinco_} - {VermelhoCincoElo_}')43 page.locator("div.css-yspf3p.e1k2e1zv5").screenshot(path="Game\WebScrapingPartida\AOVIVOPartida.png")...
details.py
Source: details.py
1from helper import inner_html, remove_tags2def hourly_forecast(soup):3 temp_map = {}4 for i in range(1, 6):5 time = inner_html(soup.select(6 f'.HourlyWeatherCard--TableWrapper--2kboH > ul:nth-child(1) > li:nth-child({i}) > a:nth-child(1) > h3:nth-child(1) > span:nth-child(1)'))7 temp = inner_html(soup.select(8 f'.HourlyWeatherCard--TableWrapper--2kboH > ul:nth-child(1) > li:nth-child({i}) > a:nth-child(1) > div:nth-child(2) > span:nth-child(1)'))9 precipitation = remove_tags(str(soup.select(10 f'.HourlyWeatherCard--TableWrapper--2kboH > ul:nth-child(1) > li:nth-child({i}) > a:nth-child(1) > div:nth-child(4)')[11 0]))12 temp_map[i] = {13 "time": time,14 "highest_temp": temp,15 "precipitation": precipitation16 }17 return temp_map18def daily_forecast(soup):19 temp_map = {}20 for i in range(1, 6):21 time = inner_html(soup.select(22 f".DailyWeatherCard--TableWrapper--12r1N > ul:nth-child(1) > li:nth-child({i}) > a:nth-child(1) > "23 f"h3:nth-child(1) > span:nth-child(1)"))24 highest_temp = inner_html(soup.select(25 f".DailyWeatherCard--TableWrapper--12r1N > ul:nth-child(1) > li:nth-child({i}) > a:nth-child(1) > "26 f"div:nth-child(2) > span:nth-child(1)"))27 lowest_temp = inner_html(soup.select(28 f".DailyWeatherCard--TableWrapper--12r1N > ul:nth-child(1) > li:nth-child({i}) > a:nth-child(1) > "29 f"div:nth-child(3) > span:nth-child(1)"))30 precipitation = remove_tags(str(soup.select(31 f".DailyWeatherCard--TableWrapper--12r1N > ul:nth-child(1) > li:nth-child({i}) > a:nth-child(1) > "32 f"div:nth-child(5)")[0]))33 temp_map[i] = {34 "time": time,35 "highest_temp": highest_temp,36 "lowest_temp": lowest_temp,37 "precipitation": precipitation38 }39 return temp_map40def today_forecast(soup):41 time = ["morning", "afternoon", "evening", "night"]42 temp_map = {}43 i = 144 for t in time:45 precip_selector = f'.WeatherTable--wide--YogM9 > li:nth-child({i}) > a:nth-child(1) > div:nth-child(4)'46 try:47 temp_map[t] = {48 "temperature": inner_html(soup.select(49 f'.WeatherTable--wide--YogM9 > li:nth-child({i}) > a:nth-child(1) > div:nth-child(2) > '50 f'span:nth-child(1)')),51 "precipitation": remove_tags(str(soup.select(precip_selector)[0])),52 }53 except IndexError:54 precip_selector = f'li.Column--active--FeXwd:nth-child({i}) > a:nth-child(1) > div:nth-child(4)'55 temp_map[t] = {56 "temperature": inner_html(soup.select(57 f'.WeatherTable--wide--YogM9 > li:nth-child({i}) > a:nth-child(1) > div:nth-child(2) > '58 f'span:nth-child(1)')),59 "precipitation": remove_tags(str(soup.select(precip_selector)[0]))60 }61 finally:62 i += 163 return temp_map64def today_weather_details(soup):65 weather_type = inner_html(soup.select('.CurrentConditions--phraseValue--2xXSr'))66 avg_temperature = inner_html(soup.select('.TodayDetailsCard--feelsLikeTempValue--2aogo'))67 today_max_temp = inner_html(68 soup.select('div.ListItem--listItem--1r7mf:nth-child(1) > div:nth-child(3) > span:nth-child(1)'))69 today_min_temp = inner_html(70 soup.select('div.ListItem--listItem--1r7mf:nth-child(1) > div:nth-child(3) > span:nth-child(2)'))71 wind_speed = remove_tags(inner_html(soup.select('.Wind--windWrapper--1Va1P')))72 humidity = inner_html(73 soup.select('div.ListItem--listItem--1r7mf:nth-child(3) > div:nth-child(3) > span:nth-child(1)'))74 pressure = remove_tags(inner_html(soup.select('.Pressure--pressureWrapper--3olKd')))75 uv_index = inner_html(76 soup.select('div.ListItem--listItem--1r7mf:nth-child(6) > div:nth-child(3) > span:nth-child(1)'))77 visibility = inner_html(78 soup.select('div.ListItem--listItem--1r7mf:nth-child(7) > div:nth-child(3) > span:nth-child(1)'))79 moon_phase = inner_html(soup.select('div.ListItem--listItem--1r7mf:nth-child(8) > div:nth-child(3)'))80 temp_map = {81 "weather_type": weather_type,82 "avg_temperature": avg_temperature,83 "today_max_temp": today_max_temp,84 "today_min_temp": today_min_temp,85 "wind_speed": wind_speed,86 "humidity": humidity,87 "pressure": pressure,88 "uv_index": uv_index,89 "visibility": visibility,90 "moon_phase": moon_phase,91 }...
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I solved my problem. In fact my docker container (frontend) is called "app" which is also domain name of fronend application. My application is running locally on http. Chromium and geko drivers force httpS connection for some domain names one of which is "app". So i have to change name for my docker container wich contains frontend application.
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