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| import urllib.request as req | |
| from bs4 import BeautifulSoup as bs | |
| import re | |
| import pandas as pd | |
| import streamlit as st | |
| from io import BytesIO | |
| class BeautifulSoup_st: | |
| def __init__(self, width=600, height=400): | |
| self.iframe_width = width | |
| self.iframe_height = height | |
| def load_page(self, url): | |
| # Visualizar la pagina | |
| self.url = url.replace("watch?v=", "embed/") | |
| page = req.urlopen(self.url) | |
| soup = bs(page) | |
| html_code = st.checkbox('Codigo HTML') | |
| if html_code: st.code(str(soup.prettify())) | |
| def filter_content(self, data_type='p'): | |
| page = req.urlopen(self.url) | |
| soup = bs(page) | |
| # Buscamos todos los tipos de datos en la pagina | |
| page_content = str(soup.body) | |
| data_type_options = [i[1:] for i in set(re.findall('<\w+', page_content))] | |
| data_type = st.selectbox('Tipo de item', options=data_type_options) | |
| # filtramos aplicando el tipo de dato escogido | |
| content_filtered_1 = [str(i) for i in soup.body.findAll(data_type)] | |
| second_filter = st.checkbox('Filtrar por atributo') | |
| # filtramos aplicando el atributo escogido | |
| if second_filter: | |
| content_str_filter = '' | |
| for i in content_filtered_1: | |
| content_str_filter += f' {i}' | |
| atribute_options = [i[:-1] for i in set(re.findall('\w+=', content_str_filter))] | |
| data_atribute = st.selectbox('Atributo', options=atribute_options) | |
| content_filtered_2 = [str(re.findall(f'.*{data_atribute}="([^"]*)".*', i)) for i in content_filtered_1] | |
| df = pd.DataFrame(content_filtered_2) | |
| else: | |
| df = pd.DataFrame(content_filtered_1) | |
| transform_to_text = st.checkbox('Obtener texto contenido') | |
| if transform_to_text: | |
| if second_filter: | |
| content = soup.body.findAll(data_type) | |
| result = [] | |
| for item in content: | |
| h = str(item).split('>')[0] | |
| x = None | |
| if data_atribute in h: | |
| x = item[data_atribute] | |
| result.append(x) | |
| df = pd.DataFrame(result) | |
| else: | |
| content = soup.body.findAll(data_type) | |
| function_usage = [] | |
| for item in content: | |
| item = item.getText('#') | |
| item = item.replace('\n', '') | |
| function_usage.append(item) | |
| data = [i.split('#') for i in function_usage] | |
| df = pd.DataFrame(data) | |
| self.df = df | |
| st.table(df) | |
| def save(self): | |
| c1, c2, c3 = st.columns([7, 1, 1]) | |
| # Descargar csv | |
| c1.write(''' | |
| **Formato de descarga**''') | |
| csv = self.df.to_csv(header=False, index=False).encode('utf-8') | |
| c2.download_button( | |
| label="csv", | |
| data=csv, | |
| file_name='DB.csv') | |
| # Descargar excel | |
| output = BytesIO() | |
| excel_file = pd.ExcelWriter(output, engine='xlsxwriter') | |
| content_file = self.df.to_excel(excel_file, header=False, index=False) | |
| data = output.getvalue() | |
| c3.download_button( | |
| label="excel", | |
| data=data, | |
| file_name='DB.xlsx') | |
| #https://docs.python.org/3/library/random.html | |