How to use inner_html method in Playwright Python

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World.py

Source:World.py Github

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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')...

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builders.py

Source:builders.py Github

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...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 = '-'...

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WebScrapingPartida.py

Source:WebScrapingPartida.py Github

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...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")...

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details.py

Source:details.py Github

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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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