From bb5b8e3f0c360b41a1dbe4fd66d4f77944cfae96 Mon Sep 17 00:00:00 2001 From: Jen456 Date: Sat, 23 Aug 2025 11:09:27 -0500 Subject: [PATCH 01/21] explicando sobre pip install request --- lessons/02_web_scraping.ipynb | 89 +++++++++++++++++++++++++++++------ 1 file changed, 75 insertions(+), 14 deletions(-) diff --git a/lessons/02_web_scraping.ipynb b/lessons/02_web_scraping.ipynb index 385806a..5e3c274 100644 --- a/lessons/02_web_scraping.ipynb +++ b/lessons/02_web_scraping.ipynb @@ -46,19 +46,69 @@ ] }, { - "cell_type": "code", - "execution_count": null, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "%pip install requests" + "### la libreria REQUEST es necesaria para hacer solicitudes HTTP y descargar páginas web, lo cual es fundamental para hacer web scraping (extraer información de páginas web)." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Note: you may need to restart the kernel to use updated packages.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "ERROR: Invalid requirement: '#': Expected package name at the start of dependency specifier\n", + " #\n", + " ^\n" + ] + } + ], + "source": [ + "%pip install requests " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting beautifulsoup4\n", + " Downloading beautifulsoup4-4.13.4-py3-none-any.whl.metadata (3.8 kB)\n", + "Collecting soupsieve>1.2 (from beautifulsoup4)\n", + " Downloading soupsieve-2.7-py3-none-any.whl.metadata (4.6 kB)\n", + "Collecting typing-extensions>=4.0.0 (from beautifulsoup4)\n", + " Downloading typing_extensions-4.14.1-py3-none-any.whl.metadata (3.0 kB)\n", + "Downloading beautifulsoup4-4.13.4-py3-none-any.whl (187 kB)\n", + "Downloading soupsieve-2.7-py3-none-any.whl (36 kB)\n", + "Downloading typing_extensions-4.14.1-py3-none-any.whl (43 kB)\n", + "Installing collected packages: typing-extensions, soupsieve, beautifulsoup4\n", + "\n", + " ------------- -------------------------- 1/3 [soupsieve]\n", + " -------------------------- ------------- 2/3 [beautifulsoup4]\n", + " -------------------------- ------------- 2/3 [beautifulsoup4]\n", + " -------------------------- ------------- 2/3 [beautifulsoup4]\n", + " ---------------------------------------- 3/3 [beautifulsoup4]\n", + "\n", + "Successfully installed beautifulsoup4-4.13.4 soupsieve-2.7 typing-extensions-4.14.1\n", + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], "source": [ "%pip install beautifulsoup4" ] @@ -72,9 +122,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting lxml\n", + " Downloading lxml-6.0.1-cp313-cp313-win_amd64.whl.metadata (3.9 kB)\n", + "Downloading lxml-6.0.1-cp313-cp313-win_amd64.whl (4.0 MB)\n", + " ---------------------------------------- 0.0/4.0 MB ? eta -:--:--\n", + " ----- ---------------------------------- 0.5/4.0 MB 5.7 MB/s eta 0:00:01\n", + " ---------------------------------------- 4.0/4.0 MB 15.9 MB/s 0:00:00\n", + "Installing collected packages: lxml\n", + "Successfully installed lxml-6.0.1\n", + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], "source": [ "%pip install lxml" ] @@ -988,7 +1054,7 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -1002,12 +1068,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.13" - }, - "vscode": { - "interpreter": { - "hash": "b6f9fe9f4b7182690503d8ecc2bae97b0ee3ebf54e877167ae4d28c119a56988" - } + "version": "3.13.6" } }, "nbformat": 4, From 9b791efe5d324072f0792c94bb51b23079690b79 Mon Sep 17 00:00:00 2001 From: ANGEL MERINO Date: Sat, 23 Aug 2025 11:44:33 -0500 Subject: [PATCH 02/21] Update README.md --- README.md | 167 ++++++++++++++++++++++-------------------------------- 1 file changed, 69 insertions(+), 98 deletions(-) diff --git a/README.md b/README.md index a702c02..f6e9db2 100644 --- a/README.md +++ b/README.md @@ -1,145 +1,116 @@ -# D-Lab Python Web Scraping Workshop +Taller de Web Scraping en Python de D-Lab [![Datahub](https://img.shields.io/badge/launch-datahub-blue)](https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Web-Scraping&urlpath=lab%2Ftree%2FPython-Web-Scraping%2F&branch=main) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dlab-berkeley/Python-Web-Scraping/HEAD) [![License: CC BY 4.0](https://img.shields.io/badge/License-CC_BY_4.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/) -This repository contains the materials for D-Lab’s Python Web Scraping Workshop. +Este repositorio contiene los materiales para el taller de raspado web de Python de D-Lab. -## Prerequisites +## Requisitos previos -We recommend attending [Python Fundamentals](https://github.com/dlab-berkeley/python-fundamentals) and [Python Data Wrangling](https://github.com/dlab-berkeley/Python-Data-Wrangling/) prior to this workshop. We additionally recommend a basic understanding of HTML and CSS. +Recomendamos asistir a [Fundamentos de Python](https://github.com/dlab-berkeley/python-fundamentals) y [Organización de datos de Python](https://github.com/dlab-berkeley/Python-Data-Wrangling/) antes de este taller. Además, recomendamos una comprensión básica de HTML y CSS. -Check out D-Lab’s [Workshop Catalog](https://dlab-berkeley.github.io/dlab-workshops/) to browse all workshops, see what’s running now, and review prerequisites. +Consulte el [Catálogo de talleres] (https://dlab-berkeley.github.io/dlab-workshops/) de D-Lab para explorar todos los talleres, ver lo que se está ejecutando ahora y revisar los requisitos previos. +## Objetivos del taller -## Workshop Goals +En este taller, cubrimos cómo extraer datos de la web usando Python. +El raspado implica descargar el código fuente de una página web y examinar el archivo material para extraer los datos deseados. -In this workshop, we cover how to scrape data from the web using Python. Web -scraping involves downloading a webpage's source code and sifting through the -material to extract desired data. +El Web Scraping generalmente solo se realiza cuando las API web no están disponibles. Plataformas como Twitter, Reddit o The New York Times ofrecen API para recuperar datos. Si usted desea aprender a usar las API web en Python, consulte [Python Web APIs](https://github.com/dlab-berkeley/Python-Web-APIs). -Web scraping is typically only done when Web APIs are not available. Platforms -like Twitter, Reddit, or The New York Times offer APIs to retrieve data. If you -want to learn how to use web APIs in Python, see D-Lab's [Python Web -APIs](https://github.com/dlab-berkeley/Python-Web-APIs) workshop. +## Instrucciones de instalación -## Installation Instructions +Anaconda es un útil software de gestión de paquetes que permite ejecutar Python +y cuadernos Jupyter fácilmente. Instalar Anaconda es la forma más fácil de hacer +Seguro que tienes todo el software necesario para ejecutar los materiales para este taller. Si desea ejecutar Python en su propia computadora, complete lo siguiente -Anaconda is a useful package management software that allows you to run Python -and Jupyter notebooks easily. Installing Anaconda is the easiest way to make -sure you have all the necessary software to run the materials for this workshop. -If you would like to run Python on your own computer, complete the following -steps prior to the workshop: +Pasos previos al taller: -1. [Download and install Anaconda (Python 3.9 - distribution)](https://www.anaconda.com/products/individual). Click the - "Download" button. +1. [Descargue e instale Anaconda (Python 3.9 +distribución)](https://www.anaconda.com/products/individual). Haga clic en el icono +Botón "Descargar". -2. Download the Python Web Scraping [workshop - materials](https://github.com/dlab-berkeley/Python-Web-Scraping): +2. Descargue el [taller] Python Web Scraping +materiales](https://github.com/dlab-berkeley/Python-Web-Scraping): - - Click the green "Code" button in the top right of the repository - information. - - Click "Download Zip". - - Extract this file to a folder on your computer where you can easily - access it (we recommend Desktop). + - Haga clic en el botón verde "Código" en la parte superior derecha del repositorio +información. + - Haga clic en "Descargar Zip". + - Extraiga este archivo a una carpeta en su computadora donde pueda fácilmente +acceder a él (recomendamos Escritorio). -3. Optional: if you're familiar with `git`, you can instead clone this - repository by opening a terminal and entering the command `git clone - git@github.com:dlab-berkeley/Python-Web-Scraping.git`. +3. Opcional: si estás familiarizado con 'git', puedes clonarlo +repositorio abriendo una terminal e ingresando el comando 'git clone +git@github.com:dlab-berkeley/Python-Web-Scraping.git'. +## ¿Python no funciona en su computadora? -## Is Python Not Working on Your Computer? +Si no tiene Anaconda instalada y los materiales cargados en su taller +para cuando comience, recomendamos *encarecidamente* usar el centro de datos de UC Berkeley para ejecutar los materiales para estas lecciones. Puede acceder al DataHub haciendo clic en este botón: -If you do not have Anaconda installed and the materials loaded on your workshop -by the time it starts, we *strongly* recommend using the UC Berkeley Datahub to -run the materials for these lessons. You can access the DataHub by clicking this -button: +[![ Centro de datos](https://img.shields.io/badge/launch-datahub-blue)](https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Web-Scraping&urlpath=lab%2Ftree%2FPython-Web-Scraping%2F&branch=main) -[![Datahub](https://img.shields.io/badge/launch-datahub-blue)](https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Web-Scraping&urlpath=lab%2Ftree%2FPython-Web-Scraping%2F&branch=main) - -The DataHub downloads this repository, along with any necessary packages, and -allows you to run the materials in a Jupyter notebook that is stored on UC -Berkeley's servers. No installation is necessary from your end - you only need -an internet browser and a CalNet ID to log in. By using the DataHub, you can -save your work and come back to it at any time. When you want to return to your -saved work, just go straight to [DataHub](https://datahub.berkeley.edu), sign -in, and you click on the `Python-Web-Scraping` folder. +El DataHub descarga este repositorio, junto con los paquetes necesarios, y +le permite ejecutar los materiales en un cuaderno de Jupyter que se almacena en UC de los servidores de Berkeley. No es necesaria ninguna instalación por su parte, solo necesita un navegador de Internet y una identificación de CalNet para iniciar sesión. Al usar DataHub, puede Guarde su trabajo y vuelva a él en cualquier momento. Cuando quieras volver a tu trabajo guardado, simplemente vaya directamente a [DataHub] (https://datahub.berkeley.edu), firme y haga clic en la carpeta 'Python-Web-Scraping'. -If you don't have a Berkeley CalNet ID, you can still run these lessons in the -cloud, by clicking this button: +Si no tiene una identificación de Berkeley CalNet, aún puede ejecutar estas lecciones en el cloud, haciendo clic en este botón: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dlab-berkeley/Python-Web-Scraping/HEAD) -By using this button, however, you cannot save your work. +Sin embargo, al usar este botón, no puede guardar su trabajo. -## Run the code +## Ejecuta el código -1. Open the Anaconda Navigator application. You should see the green snake logo - appear on your screen. Note that this can take a few minutes to load up the - first time. +1. Abra la aplicación Anaconda Navigator. Deberías ver el logotipo de la serpiente verde en tu pantalla. Tenga en cuenta que esto puede tardar unos minutos en cargar el archivo primera vez. -2. Click the "Launch" button under "Jupyter Notebooks" and navigate through your - file system to the `Python-Web-Scraping` folder you downloaded above. Note - that, if you download the materials from GitHub, the folder name may instead - be `Python-Text-Analysis-main`. +2. Haga clic en el botón "Iniciar" debajo de "Jupyter Notebooks" y navegue por su + sistema de archivos a la carpeta 'Python-Web-Scraping' que descargó anteriormente. Nota que, si descarga los materiales de GitHub, el nombre de la carpeta puede en su lugar ser 'Python-Text-Analysis-main'. -3. Open the `lessons` folder, and click `01_introduction.md` to begin. +3. Abra la carpeta 'lecciones' y haga clic en '01_introduction.md' para comenzar. -4. Press Shift + Enter (or Ctrl + Enter) to run a cell. +4. Presione Mayús + Entrar (o Ctrl + Entrar) para ejecutar una celda. -5. By default, the necessary packages for this workshop should already be - installed. You can install them within the Jupyter notebook by running the - following line in its own cell: +5. Por defecto, los paquetes necesarios para este taller ya deberían estar +Instalado. Puede instalarlos en el cuaderno de Jupyter Notebook ejecutando el comando siguiente línea en su propia celda: -> ```%pip install -r requirements.txt``` +> '''%pip install -r requirements.txt''' -Note that all of the above steps can be run from the terminal, if you're -familiar with how to interact with Anaconda in that fashion. However, using -Anaconda Navigator is the easiest way to get started if this is your first time -working with Anaconda. +Tenga en cuenta que todos los pasos anteriores se pueden ejecutar desde la terminal, si está familiarizado con cómo interactuar con Anaconda de esa manera. Sin embargo, el uso de Anaconda Navigator es la forma más fácil de comenzar si es tu primera vez trabajando con Anaconda. -# About the UC Berkeley D-Lab +# Acerca del D-Lab de UC Berkeley -D-Lab works with Berkeley faculty, research staff, and students to advance -data-intensive social science and humanities research. Our goal at D-Lab is to -provide practical training, staff support, resources, and space to enable you to -use R for your own research applications. Our services cater to all skill levels -and no programming, statistical, or computer science backgrounds are necessary. -We offer these services in the form of workshops, one-to-one consulting, and -working groups that cover a variety of research topics, digital tools, and -programming languages. +D-Lab trabaja con profesores, personal de investigación y estudiantes de Berkeley para avanzar investigación intensiva en ciencias sociales y humanidades con uso intensivo de datos. Nuestro objetivo en D-Lab es proporcionar capacitación práctica, apoyo del personal, recursos y espacio para permitirle +use R para sus propias aplicaciones de investigación. Nuestros servicios se adaptan a todos los niveles de habilidad y no se necesitan antecedentes en programación, estadística o informática. +Ofrecemos estos servicios en forma de talleres, consultoría personalizada y +grupos de trabajo que cubren una variedad de temas de investigación, herramientas digitales y lenguajes de programación. -Visit the [D-Lab homepage](https://dlab.berkeley.edu/) to learn more about us. -You can view our [calendar](https://dlab.berkeley.edu/events/calendar) for -upcoming events, learn about how to utilize our -[consulting](https://dlab.berkeley.edu/consulting) and [data -services](https://dlab.berkeley.edu/data), and check out upcoming -[workshops](https://dlab.berkeley.edu/events/workshops). Subscribe to our -[newsletter](https://dlab.berkeley.edu/news/weekly-newsletter) to stay up to -date on D-Lab events, services, and opportunities. +Visite la [página de inicio de D-Lab](https://dlab.berkeley.edu/) para obtener más información sobre nosotros. Puede ver nuestro [calendario](https://dlab.berkeley.edu/events/calendar) para +próximos eventos, aprenda cómo utilizar nuestros +[consultoría](https://dlab.berkeley.edu/consulting) y [datos +servicios](https://dlab.berkeley.edu/data), y echa un vistazo a los próximos +[talleres](https://dlab.berkeley.edu/events/workshops). Suscríbete a nuestro +[newsletter](https://dlab.berkeley.edu/news/weekly-newsletter) para mantenerse al día fecha en eventos, servicios y oportunidades de D-Lab. -# Other D-Lab Python Workshops +# Otros talleres de D-Lab Python -D-Lab offers a variety of Python workshops, catered toward different levels of -expertise. +D-Lab ofrece una variedad de talleres de Python, dirigidos a diferentes niveles de pericia. -## Introductory Workshops +## Talleres introductorios -- [Python Fundamentals](https://github.com/dlab-berkeley/Python-Fundamentals) -- [Python Data Wrangling](https://github.com/dlab-berkeley/Python-Data-Wrangling) -- [Python Data Visualization](https://github.com/dlab-berkeley/Python-Data-Visualization) +- [Fundamentos de Python](https://github.com/dlab-berkeley/Python-Fundamentals) +- [Manejo de datos de Python](https://github.com/dlab-berkeley/Python-Data-Wrangling) +- [Visualización de datos de Python](https://github.com/dlab-berkeley/Python-Data-Visualization) -## Intermediate and Advanced Workshops +## Talleres intermedios y avanzados -- [Python Geospatial Fundamentals](https://github.com/dlab-berkeley/Geospatial-Data-and-Mapping-in-Python) -- [Python Web Scraping and APIs](https://github.com/dlab-berkeley/Python-Web-Scraping) -- [Python Machine Learning](https://github.com/dlab-berkeley/Python-Machine-Learning) -- [Python Text Analysis](https://github.com/dlab-berkeley/Python-Text-Analysis) -- [Python Deep Learning](https://github.com/dlab-berkeley/Python-Deep-Learning) +- [Fundamentos geoespaciales de Python](https://github.com/dlab-berkeley/Geospatial-Data-and-Mapping-in-Python) +- [Raspado web y API de Python](https://github.com/dlab-berkeley/Python-Web-Scraping) +- [Aprendizaje automático de Python](https://github.com/dlab-berkeley/Python-Machine-Learning) +- [Análisis de texto de Python](https://github.com/dlab-berkeley/Python-Text-Analysis) +- [Aprendizaje profundo de Python](https://github.com/dlab-berkeley/Python-Deep-Learning) -# Contributors +# Colaboradores * [Rochelle Terman](https://github.com/rochelleterman) * [George McIntire](https://github.com/GeorgeMcIntire) From 6520cbec834ccb23f2fe3840161a4cbfec59387e Mon Sep 17 00:00:00 2001 From: rebe1603 Date: Sat, 23 Aug 2025 11:48:30 -0500 Subject: [PATCH 03/21] =?UTF-8?q?Descripci=C3=B3n=20del=20c=C3=B3digo?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- lessons/02_web_scraping.ipynb | 29 +++++++++++++++-------------- 1 file changed, 15 insertions(+), 14 deletions(-) diff --git a/lessons/02_web_scraping.ipynb b/lessons/02_web_scraping.ipynb index 385806a..99ed3c7 100644 --- a/lessons/02_web_scraping.ipynb +++ b/lessons/02_web_scraping.ipynb @@ -51,7 +51,7 @@ "metadata": {}, "outputs": [], "source": [ - "%pip install requests" + "%pip install requests # Instala la librería requests, que permite hacer peticiones HTTP, con ella puedes conectarte a páginas web y obtener su contenido." ] }, { @@ -60,7 +60,7 @@ "metadata": {}, "outputs": [], "source": [ - "%pip install beautifulsoup4" + "%pip install beautifulsoup4 # Instala una librería para parsear HTML y XML, sirve para extraer información específica de una página web." ] }, { @@ -76,7 +76,7 @@ "metadata": {}, "outputs": [], "source": [ - "%pip install lxml" + "%pip install lxml # Parsers rápido y eficiente para manejar HTML y XML." ] }, { @@ -87,7 +87,7 @@ }, "outputs": [], "source": [ - "# Import required libraries\n", + "# Importa las librerías necesarias para ejecutar el código.\n", "from bs4 import BeautifulSoup\n", "from datetime import datetime\n", "import requests\n", @@ -131,11 +131,11 @@ }, "outputs": [], "source": [ - "# Make a GET request\n", + "# Hace una solicitud HTTP de tipo GET a la página web.\n", "req = requests.get('http://www.ilga.gov/senate/default.asp')\n", - "# Read the content of the server’s response\n", + "# Se obtiene el contenido de la respuesta del servidor en formato de texto.\n", "src = req.text\n", - "# View some output\n", + "# Se imprime solo los primeros 1000 caracteres del contenido.\n", "print(src[:1000])" ] }, @@ -156,9 +156,9 @@ "metadata": {}, "outputs": [], "source": [ - "# Parse the response into an HTML tree\n", + "# Se crea un objeto BeautifulSoup a partir de la variable src (que contiene el HTML obtenido con requests).\n", "soup = BeautifulSoup(src, 'lxml')\n", - "# Take a look\n", + "# Imprime de manera identada gracias a prettify los primeros 1000 caracteres.\n", "print(soup.prettify()[:1000])" ] }, @@ -194,9 +194,9 @@ "metadata": {}, "outputs": [], "source": [ - "# Find all elements with a certain tag\n", + "# Usa soup.find_all(\"a\") para buscar todos los elementos del documento HTML, a hace referencia a los hipervínculos.\n", "a_tags = soup.find_all(\"a\")\n", - "print(a_tags[:10])" + "print(a_tags[:10])#Imprime los primeros 10 elementos de la lista." ] }, { @@ -216,6 +216,7 @@ }, "outputs": [], "source": [ + "#Obtener todos los elementos de la página y se imprime el primer enlace de cad lista.\n", "a_tags = soup.find_all(\"a\")\n", "a_tags_alt = soup(\"a\")\n", "print(a_tags[0])\n", @@ -235,7 +236,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(len(a_tags))" + "print(len(a_tags)) #Imprime el total de hipervínculos o enlaces que se encontraron en la página." ] }, { @@ -257,7 +258,7 @@ }, "outputs": [], "source": [ - "# Get only the 'a' tags in 'sidemenu' class\n", + "# Busca solo las etiquetas que tengan la clase \"sidemenu\", y mestra los primeros 5 enlaces con la clase sidemenu.\n", "side_menus = soup(\"a\", class_=\"sidemenu\")\n", "side_menus[:5]" ] @@ -279,7 +280,7 @@ }, "outputs": [], "source": [ - "# Get elements with \"a.sidemenu\" CSS Selector.\n", + "# Se usa soup.select() para buscar elementos con sintaxis CSS y muestra los primeros 5 enlaces con clase sidemenu.\n", "selected = soup.select(\"a.sidemenu\")\n", "selected[:5]" ] From e496c06da97e629511a6ab942252cbeb8fe6f70a Mon Sep 17 00:00:00 2001 From: julizzazeime456-afk Date: Sat, 23 Aug 2025 11:53:26 -0500 Subject: [PATCH 04/21] agregando la explicacion de beautifulsoup4 --- lessons/02_web_scraping.ipynb | 29 +++++++++++------------------ 1 file changed, 11 insertions(+), 18 deletions(-) diff --git a/lessons/02_web_scraping.ipynb b/lessons/02_web_scraping.ipynb index 5e3c274..52b3597 100644 --- a/lessons/02_web_scraping.ipynb +++ b/lessons/02_web_scraping.ipynb @@ -45,42 +45,33 @@ "We will use two main packages: [Requests](http://docs.python-requests.org/en/latest/user/quickstart/) and [Beautiful Soup](http://www.crummy.com/software/BeautifulSoup/bs4/doc/). Go ahead and install these packages, if you haven't already:" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### la libreria REQUEST es necesaria para hacer solicitudes HTTP y descargar páginas web, lo cual es fundamental para hacer web scraping (extraer información de páginas web)." - ] - }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ + "Requirement already satisfied: requests in c:\\users\\jjala\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (2.32.5)\n", + "Requirement already satisfied: charset_normalizer<4,>=2 in c:\\users\\jjala\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from requests) (3.4.3)\n", + "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\jjala\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from requests) (3.10)\n", + "Requirement already satisfied: urllib3<3,>=1.21.1 in c:\\users\\jjala\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from requests) (2.5.0)\n", + "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\jjala\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from requests) (2025.8.3)\n", "Note: you may need to restart the kernel to use updated packages.\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "ERROR: Invalid requirement: '#': Expected package name at the start of dependency specifier\n", - " #\n", - " ^\n" - ] } ], "source": [ + "# 🌐 La librería requests es necesaria para hacer solicitudes HTTP y descargar páginas web.\n", + "# 🕸️ Esto es fundamental para hacer web scraping (extraer información de páginas web).\n", "%pip install requests " ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -110,6 +101,8 @@ } ], "source": [ + "# 🥣 La instrucción %pip install beautifulsoup4 sirve para instalar la librería Beautiful Soup 4 en tu entorno de Jupyter Notebook.\n", + "# 🕸️ Beautiful Soup es esencial para analizar y extraer información de archivos HTML y XML, lo que facilita el web scraping.\n", "%pip install beautifulsoup4" ] }, From 7b7f34ed7f9b0c255a34a63cd5bdce245a04588b Mon Sep 17 00:00:00 2001 From: anmerinoto Date: Sat, 23 Aug 2025 12:16:59 -0500 Subject: [PATCH 05/21] =?UTF-8?q?Revert=20"Descripci=C3=B3n=20del=20c?= =?UTF-8?q?=C3=B3digo"?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- lessons/02_web_scraping.ipynb | 37 ++++++++++++----------------------- 1 file changed, 12 insertions(+), 25 deletions(-) diff --git a/lessons/02_web_scraping.ipynb b/lessons/02_web_scraping.ipynb index 9fd6578..52b3597 100644 --- a/lessons/02_web_scraping.ipynb +++ b/lessons/02_web_scraping.ipynb @@ -49,11 +49,6 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, -## Saskia_Guerrrero - "outputs": [], - "source": [ - "%pip install requests # Instala la librería requests, que permite hacer peticiones HTTP, con ella puedes conectarte a páginas web y obtener su contenido." -## "outputs": [ { "name": "stdout", @@ -72,18 +67,12 @@ "# 🌐 La librería requests es necesaria para hacer solicitudes HTTP y descargar páginas web.\n", "# 🕸️ Esto es fundamental para hacer web scraping (extraer información de páginas web).\n", "%pip install requests " -main ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, -# Saskia_Guerrrero - "outputs": [], - "source": [ - "%pip install beautifulsoup4 # Instala una librería para parsear HTML y XML, sirve para extraer información específica de una página web." - "outputs": [ { "name": "stdout", @@ -115,7 +104,6 @@ main "# 🥣 La instrucción %pip install beautifulsoup4 sirve para instalar la librería Beautiful Soup 4 en tu entorno de Jupyter Notebook.\n", "# 🕸️ Beautiful Soup es esencial para analizar y extraer información de archivos HTML y XML, lo que facilita el web scraping.\n", "%pip install beautifulsoup4" -main ] }, { @@ -147,7 +135,7 @@ main } ], "source": [ - "%pip install lxml # Parsers rápido y eficiente para manejar HTML y XML." + "%pip install lxml" ] }, { @@ -158,7 +146,7 @@ main }, "outputs": [], "source": [ - "# Importa las librerías necesarias para ejecutar el código.\n", + "# Import required libraries\n", "from bs4 import BeautifulSoup\n", "from datetime import datetime\n", "import requests\n", @@ -202,11 +190,11 @@ main }, "outputs": [], "source": [ - "# Hace una solicitud HTTP de tipo GET a la página web.\n", + "# Make a GET request\n", "req = requests.get('http://www.ilga.gov/senate/default.asp')\n", - "# Se obtiene el contenido de la respuesta del servidor en formato de texto.\n", + "# Read the content of the server’s response\n", "src = req.text\n", - "# Se imprime solo los primeros 1000 caracteres del contenido.\n", + "# View some output\n", "print(src[:1000])" ] }, @@ -227,9 +215,9 @@ main "metadata": {}, "outputs": [], "source": [ - "# Se crea un objeto BeautifulSoup a partir de la variable src (que contiene el HTML obtenido con requests).\n", + "# Parse the response into an HTML tree\n", "soup = BeautifulSoup(src, 'lxml')\n", - "# Imprime de manera identada gracias a prettify los primeros 1000 caracteres.\n", + "# Take a look\n", "print(soup.prettify()[:1000])" ] }, @@ -265,9 +253,9 @@ main "metadata": {}, "outputs": [], "source": [ - "# Usa soup.find_all(\"a\") para buscar todos los elementos del documento HTML, a hace referencia a los hipervínculos.\n", + "# Find all elements with a certain tag\n", "a_tags = soup.find_all(\"a\")\n", - "print(a_tags[:10])#Imprime los primeros 10 elementos de la lista." + "print(a_tags[:10])" ] }, { @@ -287,7 +275,6 @@ main }, "outputs": [], "source": [ - "#Obtener todos los elementos de la página y se imprime el primer enlace de cad lista.\n", "a_tags = soup.find_all(\"a\")\n", "a_tags_alt = soup(\"a\")\n", "print(a_tags[0])\n", @@ -307,7 +294,7 @@ main "metadata": {}, "outputs": [], "source": [ - "print(len(a_tags)) #Imprime el total de hipervínculos o enlaces que se encontraron en la página." + "print(len(a_tags))" ] }, { @@ -329,7 +316,7 @@ main }, "outputs": [], "source": [ - "# Busca solo las etiquetas que tengan la clase \"sidemenu\", y mestra los primeros 5 enlaces con la clase sidemenu.\n", + "# Get only the 'a' tags in 'sidemenu' class\n", "side_menus = soup(\"a\", class_=\"sidemenu\")\n", "side_menus[:5]" ] @@ -351,7 +338,7 @@ main }, "outputs": [], "source": [ - "# Se usa soup.select() para buscar elementos con sintaxis CSS y muestra los primeros 5 enlaces con clase sidemenu.\n", + "# Get elements with \"a.sidemenu\" CSS Selector.\n", "selected = soup.select(\"a.sidemenu\")\n", "selected[:5]" ] From f153747baa152ef18d97877b056e0ad3ba6cfb5a Mon Sep 17 00:00:00 2001 From: julizzazeime456-afk Date: Sat, 23 Aug 2025 12:24:34 -0500 Subject: [PATCH 06/21] agregando la explicacion sobre la libreria time --- lessons/02_web_scraping.ipynb | 16 ++++++---------- 1 file changed, 6 insertions(+), 10 deletions(-) diff --git a/lessons/02_web_scraping.ipynb b/lessons/02_web_scraping.ipynb index 52b3597..45b3574 100644 --- a/lessons/02_web_scraping.ipynb +++ b/lessons/02_web_scraping.ipynb @@ -115,26 +115,21 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Collecting lxml\n", - " Downloading lxml-6.0.1-cp313-cp313-win_amd64.whl.metadata (3.9 kB)\n", - "Downloading lxml-6.0.1-cp313-cp313-win_amd64.whl (4.0 MB)\n", - " ---------------------------------------- 0.0/4.0 MB ? eta -:--:--\n", - " ----- ---------------------------------- 0.5/4.0 MB 5.7 MB/s eta 0:00:01\n", - " ---------------------------------------- 4.0/4.0 MB 15.9 MB/s 0:00:00\n", - "Installing collected packages: lxml\n", - "Successfully installed lxml-6.0.1\n", + "Requirement already satisfied: lxml in c:\\users\\jjala\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (6.0.1)\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } ], "source": [ + "# 🧩 El comando %pip install lxml instala la librería lxml en tu entorno de Jupyter Notebook.\n", + "# ⚡ lxml es un parser rápido y eficiente para analizar y procesar archivos HTML y XML, muy útil para usar con Beautiful Soup en web scraping.\n", "%pip install lxml" ] }, @@ -146,7 +141,8 @@ }, "outputs": [], "source": [ - "# Import required libraries\n", + "# Importamos las librerías necesarias\n", + "# ⏳ time: para manejar pausas y temporizadores (por ejemplo, para esperar entre solicitudes y no saturar un sitio web).\n", "from bs4 import BeautifulSoup\n", "from datetime import datetime\n", "import requests\n", From e5cf9a170595aef52144356fce17f79c685ba8de Mon Sep 17 00:00:00 2001 From: ANGEL MERINO Date: Sat, 23 Aug 2025 12:42:18 -0500 Subject: [PATCH 07/21] Update README.md --- README.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/README.md b/README.md index f6e9db2..a43c02f 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,6 @@ +# Comentarios del Notebook 02_web_scrapping.ipynb +**Equipo:** grupo11 · **Integración GitHub:** @anmerinoto + Taller de Web Scraping en Python de D-Lab [![Datahub](https://img.shields.io/badge/launch-datahub-blue)](https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Web-Scraping&urlpath=lab%2Ftree%2FPython-Web-Scraping%2F&branch=main) From bf3cd02786193b5a5954c42fb2257da1fba48988 Mon Sep 17 00:00:00 2001 From: rebe1603 Date: Sat, 23 Aug 2025 13:34:21 -0500 Subject: [PATCH 08/21] Traduccion de Python-Web-Scrapping --- lessons/02_web_scraping.ipynb | 254 +++++++++++++++++----------------- 1 file changed, 127 insertions(+), 127 deletions(-) diff --git a/lessons/02_web_scraping.ipynb b/lessons/02_web_scraping.ipynb index 52b3597..43c4416 100644 --- a/lessons/02_web_scraping.ipynb +++ b/lessons/02_web_scraping.ipynb @@ -4,21 +4,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Web Scraping with Beautiful Soup\n", + "# Web Scraping con Beautiful Soup\n", "\n", "* * * \n", "\n", - "### Icons used in this notebook\n", - "🔔 **Question**: A quick question to help you understand what's going on.
\n", - "🥊 **Challenge**: Interactive exercise. We'll work through these in the workshop!
\n", - "⚠️ **Warning**: Heads-up about tricky stuff or common mistakes.
\n", - "💡 **Tip**: How to do something a bit more efficiently or effectively.
\n", - "🎬 **Demo**: Showing off something more advanced – so you know what Python can be used for!
\n", + "### Iconos utilizados en este notebook\n", + "🔔 **Preguntas**: Una pregunta rápida para ayudarte a entender qué está pasando.
\n", + "🥊 **Desafío**: Ejercicio interactivo. Lo trabajaremos en el taller.!
\n", + "⚠️ **Advertencia**: Aviso sobre cuestiones complicadas o errores comunes.
\n", + "💡 **Tip**:Cómo hacer algo de forma un poco más eficiente o efectiva.
\n", + "🎬 **Demo**: Mostrando algo más avanzado: ¡para que sepas para qué se puede usar Python!
\n", "\n", - "### Learning Objectives\n", - "1. [Reflection: To Scape Or Not To Scrape](#when)\n", - "2. [Extracting and Parsing HTML](#extract)\n", - "3. [Scraping the Illinois General Assembly](#scrape)" + "### Objetivos de aprendizaje\n", + "1. [Objetivos de aprendizaje](#when)\n", + "2. [Extracción y análisis de HTML](#extract)\n", + "3. [Desmantelando la Asamblea General de Illinois](#scrape)" ] }, { @@ -27,22 +27,22 @@ "source": [ "\n", "\n", - "# To Scrape Or Not To Scrape\n", + "# “¿Hacer scraping o no hacerlo?”\n", "\n", - "When we'd like to access data from the web, we first have to make sure if the website we are interested in offers a Web API. Platforms like Twitter, Reddit, and the New York Times offer APIs. **Check out D-Lab's [Python Web APIs](https://github.com/dlab-berkeley/Python-Web-APIs) workshop if you want to learn how to use APIs.**\n", + "Cuando queremos acceder a datos de la web, primero debemos asegurarnos de que el sitio web que nos interesa ofrezca una API web. Plataformas como Twitter, Reddit y The New York Times ofrecen API. **Echa un vistazo a D-Lab [Python Web APIs](https://github.com/dlab-berkeley/Python-Web-APIs) Taller si quieres aprender a utilizar las API.**\n", "\n", - "However, there are often cases when a Web API does not exist. In these cases, we may have to resort to web scraping, where we extract the underlying HTML from a web page, and directly obtain the information we want. There are several packages in Python we can use to accomplish these tasks. We'll focus two packages: Requests and Beautiful Soup.\n", + "Sin embargo, a menudo no existe una API web. En estos casos, podemos recurrir al web scraping, donde extraemos el HTML subyacente de una página web y obtenemos directamente la información deseada. Existen varios paquetes en Python que podemos usar para realizar estas tareas. Nos centraremos en dos paquetes: Requests y Beautiful Soup.\n", "\n", - "Our case study will be scraping information on the [state senators of Illinois](http://www.ilga.gov/senate), as well as the [list of bills](http://www.ilga.gov/senate/SenatorBills.asp?MemberID=1911&GA=98&Primary=True) each senator has sponsored. Before we get started, peruse these websites to take a look at their structure." + "Nuestro estudio de caso consistirá en extraer información sobre el [Senadores estatales de Illinois](http://www.ilga.gov/senate), así como el [lista de facturas](http://www.ilga.gov/senate/SenatorBills.asp?MemberID=1911&GA=98&Primary=True) Cada senador ha patrocinado. Antes de empezar, revise estos sitios web para conocer su estructura." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Installation\n", + "## Instalación\n", "\n", - "We will use two main packages: [Requests](http://docs.python-requests.org/en/latest/user/quickstart/) and [Beautiful Soup](http://www.crummy.com/software/BeautifulSoup/bs4/doc/). Go ahead and install these packages, if you haven't already:" + "Utilizaremos dos paquetes principales: [Solicitudes](http://docs.python-requests.org/en/latest/user/quickstart/) y [Beautiful Soup](http://www.crummy.com/software/BeautifulSoup/bs4/doc/). Continúe e instale estos paquetes, si aún no lo ha hecho:" ] }, { @@ -110,7 +110,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We'll also install the `lxml` package, which helps support some of the parsing that Beautiful Soup performs:" + "También instalaremos el paquete `lxml`, que ayuda a soportar parte del análisis que realiza Beautiful Soup:" ] }, { @@ -159,27 +159,27 @@ "source": [ "\n", "\n", - "# Extracting and Parsing HTML \n", + "# Extracción y análisis de HTML\n", "\n", - "In order to succesfully scrape and analyse HTML, we'll be going through the following 4 steps:\n", - "1. Make a GET request\n", - "2. Parse the page with Beautiful Soup\n", - "3. Search for HTML elements\n", - "4. Get attributes and text of these elements" + "Para extraer y analizar HTML correctamente, seguiremos los siguientes 4 pasos:\n", + "1. Realizar una solicitud GET\n", + "2. Analizar la página con Beautiful Soup\n", + "3. Buscar elementos HTML\n", + "4. Obtener los atributos y el texto de estos elementos" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Step 1: Make a GET Request to Obtain a Page's HTML\n", + "## Paso 1: Realizar una solicitud GET para obtener el HTML de una página\n", "\n", - "We can use the Requests library to:\n", + "Podemos usar la biblioteca Requests para:\n", "\n", - "1. Make a GET request to the page, and\n", - "2. Read in the webpage's HTML code.\n", + "1. Realizar una solicitud GET a la página y\n", + "2. Leer el código HTML de la página web.\n", "\n", - "The process of making a request and obtaining a result resembles that of the Web API workflow. Now, however, we're making a request directly to the website, and we're going to have to parse the HTML ourselves. This is in contrast to being provided data organized into a more straightforward `JSON` or `XML` output." + "El proceso de realizar una solicitud y obtener un resultado es similar al del flujo de trabajo de la API web. Sin embargo, ahora realizamos una solicitud directamente al sitio web y tendremos que analizar el HTML nosotros mismos. Esto contrasta con recibir datos organizados en una salida JSON o XML más sencilla." ] }, { @@ -202,11 +202,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Step 2: Parse the Page with Beautiful Soup\n", + "## Paso 2: Analizar la página con Beautiful Soup\n", "\n", - "Now, we use the `BeautifulSoup` function to parse the reponse into an HTML tree. This returns an object (called a **soup object**) which contains all of the HTML in the original document.\n", + "Ahora, usamos la función `BeautifulSoup` para analizar la respuesta en un árbol HTML. Esto devuelve un objeto (llamado **objeto soup**) que contiene todo el HTML del documento original.\n", "\n", - "If you run into an error about a parser library, make sure you've installed the `lxml` package to provide Beautiful Soup with the necessary parsing tools." + "Si se produce un error relacionado con una biblioteca de análisis, asegúrese de haber instalado el paquete `lxml` para proporcionar a Beautiful Soup las herramientas de análisis necesarias." ] }, { @@ -225,26 +225,26 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The output looks pretty similar to the above, but now it's organized in a `soup` object which allows us to more easily traverse the page." + "La salida se ve bastante similar a la anterior, pero ahora está organizada en un objeto 'soup' que nos permite recorrer la página más fácilmente." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Step 3: Search for HTML Elements\n", + "## Paso 3: Buscar elementos HTML\n", "\n", - "Beautiful Soup has a number of functions to find useful components on a page. Beautiful Soup lets you find elements by their:\n", + "Beautiful Soup cuenta con varias funciones para encontrar componentes útiles en una página. Beautiful Soup permite encontrar elementos por:\n", "\n", - "1. HTML tags\n", - "2. HTML Attributes\n", - "3. CSS Selectors\n", + "1. Etiquetas HTML\n", + "2. Atributos HTML\n", + "3. Selectores CSS\n", "\n", - "Let's search first for **HTML tags**. \n", + "Primero, busquemos **etiquetas HTML**.\n", "\n", - "The function `find_all` searches the `soup` tree to find all the elements with an a particular HTML tag, and returns all of those elements.\n", + "La función `find_all` busca en el árbol `soup` todos los elementos con una etiqueta HTML específica y los devuelve.\n", "\n", - "What does the example below do?" + "¿Qué hace el siguiente ejemplo?" ] }, { @@ -262,9 +262,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Because `find_all()` is the most popular method in the Beautiful Soup search API, you can use a shortcut for it. If you treat the BeautifulSoup object as though it were a function, then it’s the same as calling `find_all()` on that object. \n", + "Dado que `find_all()` es el método más popular en la API de búsqueda de Beautiful Soup, puedes usar un atajo. Si tratas el objeto BeautifulSoup como si fuera una función, es lo mismo que llamar a `find_all()` en ese objeto.\n", "\n", - "These two lines of code are equivalent:" + "Estas dos líneas de código son equivalentes:" ] }, { @@ -285,7 +285,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "How many links did we obtain?" + "¿Cuántos enlaces obtuvimos?" ] }, { @@ -301,11 +301,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "That's a lot! Many elements on a page will have the same HTML tag. For instance, if you search for everything with the `a` tag, you're likely to get more hits, many of which you might not want. Remember, the `a` tag defines a hyperlink, so you'll usually find many on any given page.\n", + "¡Eso es muchísimo! Muchos elementos de una página tendrán la misma etiqueta HTML. Por ejemplo, si buscas todo con la etiqueta `a`, probablemente obtendrás más resultados, muchos de los cuales quizás no quieras. Recuerda que la etiqueta `a` define un hipervínculo, por lo que normalmente encontrarás muchos en cualquier página.\n", "\n", - "What if we wanted to search for HTML tags with certain attributes, such as particular CSS classes? \n", + "¿Qué sucedería si quisiéramos buscar etiquetas HTML con ciertos atributos, como clases CSS específicas?\n", "\n", - "We can do this by adding an additional argument to the `find_all`. In the example below, we are finding all the `a` tags, and then filtering those with `class_=\"sidemenu\"`." + "Podemos hacerlo añadiendo un argumento adicional a `find_all`. En el siguiente ejemplo, buscamos todas las etiquetas `a` y luego las filtramos con `class_=\"sidemenu\"`." ] }, { @@ -325,9 +325,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "A more efficient way to search for elements on a website is via a **CSS selector**. For this we have to use a different method called `select()`. Just pass a string into the `.select()` to get all elements with that string as a valid CSS selector.\n", + "Una forma más eficiente de buscar elementos en un sitio web es mediante un selector CSS. Para ello, debemos usar un método diferente llamado `select()`. Simplemente pase una cadena a `.select()` para obtener todos los elementos con esa cadena como un selector CSS válido.\n", "\n", - "In the example above, we can use `\"a.sidemenu\"` as a CSS selector, which returns all `a` tags with class `sidemenu`." + "En el ejemplo anterior, podemos usar `\"a.sidemenu\"` como selector CSS, que devuelve todas las etiquetas `a` con la clase `sidemenu`." ] }, { @@ -347,9 +347,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊 Challenge: Find All\n", + "## 🥊Desafío: Encontrar todo\n", "\n", - "Use BeautifulSoup to find all the `a` elements with class `mainmenu`." + "Usa BeautifulSoup para encontrar todos los elementos `a` con la clase `mainmenu`." ] }, { @@ -365,14 +365,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Step 4: Get Attributes and Text of Elements\n", + "Paso 4: Obtener los atributos y el texto de los elementos\n", "\n", - "Once we identify elements, we want the access information in that element. Usually, this means two things:\n", + "Una vez identificados los elementos, necesitamos la información de acceso de cada uno. Normalmente, esto implica dos cosas:\n", "\n", - "1. Text\n", - "2. Attributes\n", + "1. Texto\n", + "2. Atributos\n", "\n", - "Getting the text inside an element is easy. All we have to do is use the `text` member of a `tag` object:" + "Obtener el texto dentro de un elemento es sencillo. Solo tenemos que usar el miembro `text` de un objeto `tag`:" ] }, { @@ -398,7 +398,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "It's a Beautiful Soup tag! This means it has a `text` member:" + "¡Es una etiqueta de Beautiful Soup! Esto significa que tiene un miembro \"texto\":" ] }, { @@ -416,9 +416,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Sometimes we want the value of certain attributes. This is particularly relevant for `a` tags, or links, where the `href` attribute tells us where the link goes.\n", + "A veces necesitamos el valor de ciertos atributos. Esto es especialmente relevante para las etiquetas «a» o enlaces, donde el atributo «href» nos indica adónde lleva el enlace.\n", "\n", - "💡 **Tip**: You can access a tag’s attributes by treating the tag like a dictionary:" + "💡 **Consejo**: Puedes acceder a los atributos de una etiqueta tratándola como un diccionario:" ] }, { @@ -436,9 +436,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊 Challenge: Extract specific attributes\n", + "## 🥊 Desafío: Extraer atributos específicos\n", "\n", - "Extract all `href` attributes for each `mainmenu` URL." + "Extraer todos los atributos `href` de cada URL `mainmenu`." ] }, { @@ -456,22 +456,22 @@ "source": [ "\n", "\n", - "# Scraping the Illinois General Assembly\n", + "# Análisis de la Asamblea General de Illinois\n", "\n", - "Believe it or not, those are really the fundamental tools you need to scrape a website. Once you spend more time familiarizing yourself with HTML and CSS, then it's simply a matter of understanding the structure of a particular website and intelligently applying the tools of Beautiful Soup and Python.\n", + "Aunque parezca increíble, estas son las herramientas fundamentales para analizar un sitio web. Una vez que dediques más tiempo a familiarizarte con HTML y CSS, simplemente será cuestión de comprender la estructura de un sitio web específico y aplicar inteligentemente las herramientas de Beautiful Soup y Python.\n", "\n", - "Let's apply these skills to scrape the [Illinois 98th General Assembly](http://www.ilga.gov/senate/default.asp?GA=98).\n", + "Apliquemos estas habilidades para analizar la [98.ª Asamblea General de Illinois](http://www.ilga.gov/senate/default.asp?GA=98).\n", "\n", - "Specifically, our goal is to scrape information on each senator, including their name, district, and party." + "En concreto, nuestro objetivo es analizar la información de cada senador, incluyendo su nombre, distrito y partido." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Scrape and Soup the Webpage\n", + "## Rastrear y analizar la página web\n", "\n", - "Let's scrape and parse the webpage, using the tools we learned in the previous section." + "Rastreemos y analicemos la página web con las herramientas que aprendimos en la sección anterior." ] }, { @@ -494,9 +494,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Search for the Table Elements\n", + "## Buscar los elementos de la tabla\n", "\n", - "Our goal is to obtain the elements in the table on the webpage. Remember: rows are identified by the `tr` tag. Let's use `find_all` to obtain these elements." + "Nuestro objetivo es obtener los elementos de la tabla en la página web. Recuerde: las filas se identifican con la etiqueta `tr`. Usemos `find_all` para obtener estos elementos." ] }, { @@ -514,7 +514,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "⚠️ **Warning**: Keep in mind: `find_all` gets *all* the elements with the `tr` tag. We only want some of them. If we use the 'Inspect' function in Google Chrome and look carefully, then we can use some CSS selectors to get just the rows we're interested in. Specifically, we want the inner rows of the table:" + "⚠️ **Advertencia**: Ten en cuenta que `find_all` obtiene *todos* los elementos con la etiqueta `tr`. Solo necesitamos algunos. Si usamos la función \"Inspeccionar\" de Google Chrome y observamos con atención, podemos usar selectores CSS para obtener solo las filas que nos interesan. En concreto, queremos las filas internas de la tabla:" ] }, { @@ -534,7 +534,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "It looks like we want everything after the first two rows. Let's work with a single row to start, and build our loop from there." + "Parece que queremos todo lo que queda después de las dos primeras filas. Empecemos con una sola fila y construyamos nuestro bucle a partir de ahí." ] }, { @@ -551,11 +551,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Let's break this row down into its component cells/columns using the `select` method with CSS selectors. Looking closely at the HTML, there are a couple of ways we could do this.\n", + "Desglosemos esta fila en sus celdas/columnas mediante el método `select` con selectores CSS. Si analizamos el HTML con atención, hay un par de maneras de hacerlo.\n", "\n", - "* We could identify the cells by their tag `td`.\n", - "* We could use the the class name `.detail`.\n", - "* We could combine both and use the selector `td.detail`." + "* Podríamos identificar las celdas por su etiqueta `td`.\n", + "* Podríamos usar el nombre de clase `.detail`.\n", + "* Podríamos combinar ambos y usar el selector `td.detail`." ] }, { @@ -581,7 +581,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We can confirm that these are all the same." + "Podemos confirmar que todos son iguales." ] }, { @@ -599,7 +599,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Let's use the selector `td.detail` to be as specific as possible." + "Utilicemos el selector `td.detail` para ser lo más específicos posible." ] }, { @@ -617,7 +617,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Most of the time, we're interested in the actual **text** of a website, not its tags. Recall that to get the text of an HTML element, we use the `text` member:" + "La mayoría de las veces, nos interesa el **texto** real de un sitio web, no sus etiquetas. Recordemos que para obtener el texto de un elemento HTML, usamos el miembro `text`:" ] }, { @@ -636,7 +636,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Looks good! Now we just use our basic Python knowledge to get the elements of this list that we want. Remember, we want the senator's name, their district, and their party." + "¡Se ve bien! Ahora solo necesitamos usar nuestros conocimientos básicos de Python para obtener los elementos de esta lista que necesitamos. Recuerda: queremos el nombre del senador, su distrito y su partido." ] }, { @@ -654,9 +654,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Getting Rid of Junk Rows\n", + "## Eliminando filas basura\n", "\n", - "We saw at the beginning that not all of the rows we got actually correspond to a senator. We'll need to do some cleaning before we can proceed forward. Take a look at some examples:" + "Vimos al principio que no todas las filas que obtuvimos corresponden a un senador. Tendremos que hacer limpieza antes de continuar. Vean algunos ejemplos:" ] }, { @@ -674,9 +674,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "When we write our for loop, we only want it to apply to the relevant rows. So we'll need to filter out the irrelevant rows. The way to do this is to compare some of these to the rows we do want, see how they differ, and then formulate that in a conditional.\n", + "Al escribir nuestro bucle for, queremos que solo se aplique a las filas relevantes. Por lo tanto, debemos filtrar las filas irrelevantes. Para ello, comparamos algunas de estas filas con las que necesitamos, observamos sus diferencias y luego formulamos esto en una condición.\n", "\n", - "As you can imagine, there a lot of possible ways to do this, and it'll depend on the website. We'll show some here to give you an idea of how to do this." + "Como puedes imaginar, hay muchas maneras de hacerlo, y dependerá del sitio web. Aquí te mostraremos algunas para que te hagas una idea de cómo hacerlo." ] }, { @@ -698,7 +698,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Perhaps good rows have a length of 5. Let's check:" + "Quizás las buenas filas tengan una longitud de 5. Comprobémoslo:" ] }, { @@ -719,7 +719,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We found a footer row in our list that we'd like to avoid. Let's try something else:" + "Encontramos una fila de pie de página en nuestra lista que queremos evitar. Probemos algo diferente:" ] }, { @@ -755,16 +755,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Looks like we found something that worked!" + "¡Parece que encontramos algo que funcionó!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Loop it All Together\n", + "## Unir todo en un bucle\n", "\n", - "Now that we've seen how to get the data we want from one row, as well as filter out the rows we don't want, let's put it all together into a loop." + "Ahora que hemos visto cómo obtener los datos que queremos de una fila y filtrar las filas que no necesitamos, vamos a unirlo todo en un bucle." ] }, { @@ -811,7 +811,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Let's take a look at what we have in `members`." + "Echemos un vistazo a lo que tenemos en \"miembros\"." ] }, { @@ -827,37 +827,37 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊 Challenge: Get `href` elements pointing to members' bills \n", + "## 🥊 Desafío: Obtener elementos `href` que apunten a los proyectos de ley de los miembros\n", "\n", - "The code above retrieves information on: \n", + "El código anterior recupera información sobre:\n", "\n", - "- the senator's name,\n", - "- their district number,\n", - "- and their party.\n", + "- el nombre del senador,\n", + "- su número de distrito,\n", + "- y su partido.\n", "\n", - "We now want to retrieve the URL for each senator's list of bills. Each URL will follow a specific format. \n", + "Ahora queremos recuperar la URL de la lista de proyectos de ley de cada senador. Cada URL seguirá un formato específico.\n", "\n", - "The format for the list of bills for a given senator is:\n", + "El formato de la lista de proyectos de ley de un senador determinado es:\n", "\n", "`http://www.ilga.gov/senate/SenatorBills.asp?GA=98&MemberID=[MEMBER_ID]&Primary=True`\n", "\n", - "to get something like:\n", + "para obtener algo como:\n", "\n", "`http://www.ilga.gov/senate/SenatorBills.asp?MemberID=1911&GA=98&Primary=True`\n", "\n", - "in which `MEMBER_ID=1911`. \n", + "donde `MEMBER_ID=1911`.\n", "\n", - "You should be able to see that, unfortunately, `MEMBER_ID` is not currently something pulled out in our scraping code.\n", + "Deberías poder ver que, lamentablemente, `MEMBER_ID` no se extrae actualmente en nuestro código de extracción.\n", "\n", - "Your initial task is to modify the code above so that we also **retrieve the full URL which points to the corresponding page of primary-sponsored bills**, for each member, and return it along with their name, district, and party.\n", + "Tu tarea inicial es modificar el código anterior para que también **recuperemos la URL completa que apunta a la página correspondiente de los proyectos de ley patrocinados por las primarias** de cada miembro, y la devolvamos junto con su nombre, distrito y partido.\n", "\n", - "Tips: \n", + "Consejos:\n", "\n", - "* To do this, you will want to get the appropriate anchor element (``) in each legislator's row of the table. You can again use the `.select()` method on the `row` object in the loop to do this — similar to the command that finds all of the `td.detail` cells in the row. Remember that we only want the link to the legislator's bills, not the committees or the legislator's profile page.\n", - "* The anchor elements' HTML will look like `Bills`. The string in the `href` attribute contains the **relative** link we are after. You can access an attribute of a BeatifulSoup `Tag` object the same way you access a Python dictionary: `anchor['attributeName']`. See the documentation for more details.\n", - "* There are a _lot_ of different ways to use BeautifulSoup to get things done. whatever you need to do to pull the `href` out is fine.\n", + "* Para ello, deberá obtener el elemento de anclaje correspondiente (``) en la fila de cada legislador de la tabla. Puede usar el método `.select()` en el objeto `row` del bucle para hacerlo, de forma similar al comando que busca todas las celdas `td.detail` de la fila. Recuerde que solo necesitamos el enlace a los proyectos de ley del legislador, no a los comités ni a su página de perfil.\n", + "* El HTML de los elementos de anclaje se verá como `Proyectos de ley`. La cadena del atributo `href` contiene el enlace **relativo** que buscamos. Puede acceder a un atributo de un objeto `Tag` de BeatifulSoup de la misma manera que accede a un diccionario de Python: `anchor['attributeName']`. Consulta la documentación para obtener más detalles.\n", + "* Hay muchas maneras diferentes de usar BeautifulSoup. Puedes usar cualquier método para extraer el `href`.\n", "\n", - "The code has been partially filled out for you. Fill it in where it says `#YOUR CODE HERE`. Save the path into an object called `full_path`." + "El código se ha completado parcialmente. Complétalo donde dice `#TU CÓDIGO AQUÍ`. Guarda la ruta en un objeto llamado `full_path`." ] }, { @@ -918,9 +918,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊 Challenge: Modularize Your Code\n", + "## 🥊 Desafío: Modulariza tu código\n", "\n", - "Turn the code above into a function that accepts a URL, scrapes the URL for its senators, and returns a list of tuples containing information about each senator. " + "Convierte el código anterior en una función que acepte una URL, rastree la URL para encontrar sus senadores y devuelva una lista de tuplas con información sobre cada senador. " ] }, { @@ -954,21 +954,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊 Take-home Challenge: Writing a Scraper Function\n", + "## 🥊 Desafío práctico: Escribir una función de scraping\n", "\n", - "We want to scrape the webpages corresponding to bills sponsored by each bills.\n", + "Queremos scraping las páginas web correspondientes a los proyectos de ley patrocinados por cada proyecto de ley.\n", "\n", - "Write a function called `get_bills(url)` to parse a given bills URL. This will involve:\n", + "Escribir una función llamada `get_bills(url)` para analizar la URL de un proyecto de ley. Esto implica:\n", "\n", - " - requesting the URL using the `requests` library\n", - " - using the features of the `BeautifulSoup` library to find all of the `` elements with the class `billlist`\n", - " - return a _list_ of tuples, each with:\n", - " - description (2nd column)\n", - " - chamber (S or H) (3rd column)\n", - " - the last action (4th column)\n", - " - the last action date (5th column)\n", - " \n", - "This function has been partially completed. Fill in the rest." + "- Solicitar la URL mediante la biblioteca `requests`\n", + "- Usar las funciones de la biblioteca `BeautifulSoup` para encontrar todos los elementos `` con la clase `billlist`\n", + "- Devolver una _lista_ de tuplas, cada una con:\n", + "- Descripción (2.ª columna)\n", + "- Cámara (S o H) (3.ª columna)\n", + "- La última acción (4.ª columna)\n", + "- La fecha de la última acción (5.ª columna)\n", + "\n", + "Esta función se ha completado parcialmente. Complete el resto." ] }, { @@ -986,11 +986,11 @@ " bills = []\n", " for row in rows:\n", " # YOUR CODE HERE\n", - " bill_id =\n", - " description =\n", - " chamber =\n", - " last_action =\n", - " last_action_date =\n", + " #bill_id =\n", + " #description =\n", + " #chamber =\n", + " #last_action =\n", + " #last_action_date =\n", " bill = (bill_id, description, chamber, last_action, last_action_date)\n", " bills.append(bill)\n", " return bills" @@ -1013,11 +1013,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Scrape All Bills\n", + "### Extraer todos los proyectos de ley\n", "\n", - "Finally, create a dictionary `bills_dict` which maps a district number (the key) onto a list of bills (the value) coming from that district. You can do this by looping over all of the senate members in `members_dict` and calling `get_bills()` for each of their associated bill URLs.\n", + "Finalmente, cree un diccionario `bills_dict` que asigne un número de distrito (la clave) a una lista de proyectos de ley (el valor) provenientes de ese distrito. Puede hacerlo recorriendo en bucle todos los miembros del senado en `members_dict` y llamando a `get_bills()` para cada una de las URL de sus proyectos de ley asociados.\n", "\n", - "**NOTE:** please call the function `time.sleep(1)` for each iteration of the loop, so that we don't destroy the state's web site." + "**NOTA:** Por favor, llame a la función `time.sleep(1)` en cada iteración del bucle para no destruir el sitio web del estado." ] }, { From 34ea12c9b54e5b1d1953e7506a8d3f178d343b05 Mon Sep 17 00:00:00 2001 From: ANGEL MERINO Date: Sat, 23 Aug 2025 16:02:07 -0500 Subject: [PATCH 09/21] Resolucion dep portafolio --- .venv312/Scripts/Activate.ps1 | 528 +++++++++++++ .venv312/Scripts/activate | 76 ++ .venv312/Scripts/activate.bat | 34 + .venv312/Scripts/deactivate.bat | 22 + .venv312/Scripts/debugpy-adapter.exe | Bin 0 -> 108413 bytes .venv312/Scripts/debugpy.exe | Bin 0 -> 108407 bytes .venv312/Scripts/ipython.exe | Bin 0 -> 108414 bytes .venv312/Scripts/ipython3.exe | Bin 0 -> 108414 bytes .venv312/Scripts/jupyter-kernel.exe | Bin 0 -> 108413 bytes .venv312/Scripts/jupyter-kernelspec.exe | Bin 0 -> 108451 bytes .venv312/Scripts/jupyter-migrate.exe | Bin 0 -> 108409 bytes .venv312/Scripts/jupyter-run.exe | Bin 0 -> 108430 bytes .venv312/Scripts/jupyter-troubleshoot.exe | Bin 0 -> 108414 bytes .venv312/Scripts/jupyter.exe | Bin 0 -> 108409 bytes .venv312/Scripts/normalizer.exe | Bin 0 -> 108423 bytes .venv312/Scripts/pip.exe | Bin 0 -> 108438 bytes .venv312/Scripts/pip3.12.exe | Bin 0 -> 108438 bytes .venv312/Scripts/pip3.exe | Bin 0 -> 108438 bytes .venv312/Scripts/pygmentize.exe | Bin 0 -> 108405 bytes .venv312/Scripts/python.exe | Bin 0 -> 274424 bytes .venv312/Scripts/pythonw.exe | Bin 0 -> 263400 bytes .venv312/Scripts/pywin32_postinstall.exe | Bin 0 -> 108422 bytes .venv312/Scripts/pywin32_postinstall.py | 733 ++++++++++++++++++ .venv312/Scripts/pywin32_testall.exe | Bin 0 -> 108418 bytes .venv312/Scripts/pywin32_testall.py | 120 +++ .venv312/pyvenv.cfg | 5 + .../share/jupyter/kernels/python3/kernel.json | 14 + .../jupyter/kernels/python3/logo-32x32.png | Bin 0 -> 1084 bytes .../jupyter/kernels/python3/logo-64x64.png | Bin 0 -> 2180 bytes .../jupyter/kernels/python3/logo-svg.svg | 265 +++++++ .venv312/share/man/man1/ipython.1 | 60 ++ lessons/02_web_scraping.ipynb | 35 +- solutions/02_web_scraping_solutions.ipynb | 103 ++- 33 files changed, 1974 insertions(+), 21 deletions(-) create mode 100644 .venv312/Scripts/Activate.ps1 create mode 100644 .venv312/Scripts/activate create mode 100644 .venv312/Scripts/activate.bat create mode 100644 .venv312/Scripts/deactivate.bat create mode 100644 .venv312/Scripts/debugpy-adapter.exe create mode 100644 .venv312/Scripts/debugpy.exe create mode 100644 .venv312/Scripts/ipython.exe create mode 100644 .venv312/Scripts/ipython3.exe create mode 100644 .venv312/Scripts/jupyter-kernel.exe create mode 100644 .venv312/Scripts/jupyter-kernelspec.exe create mode 100644 .venv312/Scripts/jupyter-migrate.exe create mode 100644 .venv312/Scripts/jupyter-run.exe create mode 100644 .venv312/Scripts/jupyter-troubleshoot.exe create mode 100644 .venv312/Scripts/jupyter.exe create mode 100644 .venv312/Scripts/normalizer.exe create mode 100644 .venv312/Scripts/pip.exe create mode 100644 .venv312/Scripts/pip3.12.exe create mode 100644 .venv312/Scripts/pip3.exe create mode 100644 .venv312/Scripts/pygmentize.exe create mode 100644 .venv312/Scripts/python.exe create mode 100644 .venv312/Scripts/pythonw.exe create mode 100644 .venv312/Scripts/pywin32_postinstall.exe create mode 100644 .venv312/Scripts/pywin32_postinstall.py create mode 100644 .venv312/Scripts/pywin32_testall.exe create mode 100644 .venv312/Scripts/pywin32_testall.py create mode 100644 .venv312/pyvenv.cfg create mode 100644 .venv312/share/jupyter/kernels/python3/kernel.json create mode 100644 .venv312/share/jupyter/kernels/python3/logo-32x32.png create mode 100644 .venv312/share/jupyter/kernels/python3/logo-64x64.png create mode 100644 .venv312/share/jupyter/kernels/python3/logo-svg.svg create mode 100644 .venv312/share/man/man1/ipython.1 diff --git a/.venv312/Scripts/Activate.ps1 b/.venv312/Scripts/Activate.ps1 new file mode 100644 index 0000000..918eac3 --- /dev/null +++ b/.venv312/Scripts/Activate.ps1 @@ -0,0 +1,528 @@ +<# +.Synopsis +Activate a Python virtual environment for the current PowerShell session. + +.Description +Pushes the python executable for a virtual environment to the front of the +$Env:PATH environment variable and sets the prompt to signify that you are +in a Python virtual environment. Makes use of the command line switches as +well as the `pyvenv.cfg` file values present in the virtual environment. + +.Parameter VenvDir +Path to the directory that contains the virtual environment to activate. The +default value for this is the parent of the directory that the Activate.ps1 +script is located within. + +.Parameter Prompt +The prompt prefix to display when this virtual environment is activated. By +default, this prompt is the name of the virtual environment folder (VenvDir) +surrounded by parentheses and followed by a single space (ie. '(.venv) '). + +.Example +Activate.ps1 +Activates the Python virtual environment that contains the Activate.ps1 script. + +.Example +Activate.ps1 -Verbose +Activates the Python virtual environment that contains the Activate.ps1 script, +and shows extra information about the activation as it executes. + +.Example +Activate.ps1 -VenvDir C:\Users\MyUser\Common\.venv +Activates the Python virtual environment located in the specified location. + +.Example +Activate.ps1 -Prompt "MyPython" +Activates the Python virtual environment that contains the Activate.ps1 script, +and prefixes the current prompt with the specified string (surrounded in +parentheses) while the virtual environment is active. + +.Notes +On Windows, it may be required to enable this Activate.ps1 script by setting the +execution policy for the user. You can do this by issuing the following PowerShell +command: + +PS C:\> Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser + +For more information on Execution Policies: +https://go.microsoft.com/fwlink/?LinkID=135170 + +#> +Param( + [Parameter(Mandatory = $false)] + [String] + $VenvDir, + [Parameter(Mandatory = $false)] + [String] + $Prompt +) + +<# Function declarations --------------------------------------------------- #> + +<# +.Synopsis +Remove all shell session elements added by the Activate script, including the +addition of the virtual environment's Python executable from the beginning of +the PATH variable. + +.Parameter NonDestructive +If present, do not remove this function from the global namespace for the +session. + +#> +function global:deactivate ([switch]$NonDestructive) { + # Revert to original values + + # The prior prompt: + if (Test-Path -Path Function:_OLD_VIRTUAL_PROMPT) { + Copy-Item -Path Function:_OLD_VIRTUAL_PROMPT -Destination Function:prompt + Remove-Item -Path Function:_OLD_VIRTUAL_PROMPT + } + + # The prior PYTHONHOME: + if (Test-Path -Path Env:_OLD_VIRTUAL_PYTHONHOME) { + Copy-Item -Path Env:_OLD_VIRTUAL_PYTHONHOME -Destination Env:PYTHONHOME + Remove-Item -Path Env:_OLD_VIRTUAL_PYTHONHOME + } + + # The prior PATH: + if (Test-Path -Path Env:_OLD_VIRTUAL_PATH) { + Copy-Item -Path Env:_OLD_VIRTUAL_PATH -Destination Env:PATH + Remove-Item -Path Env:_OLD_VIRTUAL_PATH + } + + # Just remove the VIRTUAL_ENV altogether: + if (Test-Path -Path Env:VIRTUAL_ENV) { + Remove-Item -Path env:VIRTUAL_ENV + } + + # Just remove VIRTUAL_ENV_PROMPT altogether. + if (Test-Path -Path Env:VIRTUAL_ENV_PROMPT) { + Remove-Item -Path env:VIRTUAL_ENV_PROMPT + } + + # Just remove the _PYTHON_VENV_PROMPT_PREFIX altogether: + if (Get-Variable -Name "_PYTHON_VENV_PROMPT_PREFIX" -ErrorAction SilentlyContinue) { + Remove-Variable -Name _PYTHON_VENV_PROMPT_PREFIX -Scope Global -Force + } + + # Leave deactivate function in the global namespace if requested: + if (-not $NonDestructive) { + Remove-Item -Path function:deactivate + } +} + +<# +.Description +Get-PyVenvConfig parses the values from the pyvenv.cfg file located in the +given folder, and returns them in a map. + +For each line in the pyvenv.cfg file, if that line can be parsed into exactly +two strings separated by `=` (with any amount of whitespace surrounding the =) +then it is considered a `key = value` line. The left hand string is the key, +the right hand is the value. + +If the value starts with a `'` or a `"` then the first and last character is +stripped from the value before being captured. + +.Parameter ConfigDir +Path to the directory that contains the `pyvenv.cfg` file. +#> +function Get-PyVenvConfig( + [String] + $ConfigDir +) { + Write-Verbose "Given ConfigDir=$ConfigDir, obtain values in pyvenv.cfg" + + # Ensure the file exists, and issue a warning if it doesn't (but still allow the function to continue). + $pyvenvConfigPath = Join-Path -Resolve -Path $ConfigDir -ChildPath 'pyvenv.cfg' -ErrorAction Continue + + # An empty map will be returned if no config file is found. + $pyvenvConfig = @{ } + + if ($pyvenvConfigPath) { + + Write-Verbose "File exists, parse `key = value` lines" + $pyvenvConfigContent = Get-Content -Path $pyvenvConfigPath + + $pyvenvConfigContent | ForEach-Object { + $keyval = $PSItem -split "\s*=\s*", 2 + if ($keyval[0] -and $keyval[1]) { + $val = $keyval[1] + + # Remove extraneous quotations around a string value. + if ("'""".Contains($val.Substring(0, 1))) { + $val = $val.Substring(1, $val.Length - 2) + } + + $pyvenvConfig[$keyval[0]] = $val + Write-Verbose "Adding Key: '$($keyval[0])'='$val'" + } + } + } + return $pyvenvConfig +} + + +<# Begin Activate script --------------------------------------------------- #> + +# Determine the containing directory of this script +$VenvExecPath = Split-Path -Parent $MyInvocation.MyCommand.Definition +$VenvExecDir = Get-Item -Path $VenvExecPath + +Write-Verbose "Activation script is located in path: '$VenvExecPath'" +Write-Verbose "VenvExecDir Fullname: '$($VenvExecDir.FullName)" +Write-Verbose "VenvExecDir Name: '$($VenvExecDir.Name)" + +# Set values required in priority: CmdLine, ConfigFile, Default +# First, get the location of the virtual environment, it might not be +# VenvExecDir if specified on the command line. +if ($VenvDir) { + Write-Verbose "VenvDir given as parameter, using '$VenvDir' to determine values" +} +else { + Write-Verbose "VenvDir not given as a parameter, using parent directory name as VenvDir." + $VenvDir = $VenvExecDir.Parent.FullName.TrimEnd("\\/") + Write-Verbose "VenvDir=$VenvDir" +} + +# Next, read the `pyvenv.cfg` file to determine any required value such +# as `prompt`. +$pyvenvCfg = Get-PyVenvConfig -ConfigDir $VenvDir + +# Next, set the prompt from the command line, or the config file, or +# just use the name of the virtual environment folder. +if ($Prompt) { + Write-Verbose "Prompt specified as argument, using '$Prompt'" +} +else { + Write-Verbose "Prompt not specified as argument to script, checking pyvenv.cfg value" + if ($pyvenvCfg -and $pyvenvCfg['prompt']) { + Write-Verbose " Setting based on value in pyvenv.cfg='$($pyvenvCfg['prompt'])'" + $Prompt = $pyvenvCfg['prompt']; + } + else { + Write-Verbose " Setting prompt based on parent's directory's name. (Is the directory name passed to venv module when creating the virtual environment)" + Write-Verbose " Got leaf-name of $VenvDir='$(Split-Path -Path $venvDir -Leaf)'" + $Prompt = Split-Path -Path $venvDir -Leaf + } +} + +Write-Verbose "Prompt = '$Prompt'" +Write-Verbose "VenvDir='$VenvDir'" + +# Deactivate any currently active virtual environment, but leave the +# deactivate function in place. +deactivate -nondestructive + +# Now set the environment variable VIRTUAL_ENV, used by many tools to determine +# that there is an activated venv. +$env:VIRTUAL_ENV = $VenvDir + +if (-not $Env:VIRTUAL_ENV_DISABLE_PROMPT) { + + Write-Verbose "Setting prompt to '$Prompt'" + + # Set the prompt to include the env name + # Make sure _OLD_VIRTUAL_PROMPT is global + function global:_OLD_VIRTUAL_PROMPT { "" } + Copy-Item -Path function:prompt -Destination function:_OLD_VIRTUAL_PROMPT + New-Variable -Name _PYTHON_VENV_PROMPT_PREFIX -Description "Python virtual environment prompt prefix" -Scope Global 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+ fi + + # Call hash to forget past locations. Without forgetting + # past locations the $PATH changes we made may not be respected. + # See "man bash" for more details. hash is usually a builtin of your shell + hash -r 2> /dev/null + + if [ -n "${_OLD_VIRTUAL_PS1:-}" ] ; then + PS1="${_OLD_VIRTUAL_PS1:-}" + export PS1 + unset _OLD_VIRTUAL_PS1 + fi + + unset VIRTUAL_ENV + unset VIRTUAL_ENV_PROMPT + if [ ! "${1:-}" = "nondestructive" ] ; then + # Self destruct! + unset -f deactivate + fi +} + +# unset irrelevant variables +deactivate nondestructive + +# on Windows, a path can contain colons and backslashes and has to be converted: +case "$(uname)" in + CYGWIN*|MSYS*|MINGW*) + # transform D:\path\to\venv to /d/path/to/venv on MSYS and MINGW + # and to /cygdrive/d/path/to/venv on Cygwin + VIRTUAL_ENV=$(cygpath 'C:\Users\fmerino\Documents\GitHub\Python-Web-Scraping\.venv312') + export VIRTUAL_ENV + ;; + *) + # use the path as-is + export VIRTUAL_ENV='C:\Users\fmerino\Documents\GitHub\Python-Web-Scraping\.venv312' + ;; +esac + +_OLD_VIRTUAL_PATH="$PATH" +PATH="$VIRTUAL_ENV/"Scripts":$PATH" +export PATH + +VIRTUAL_ENV_PROMPT='(.venv312) ' +export VIRTUAL_ENV_PROMPT + +# unset PYTHONHOME if set +# this will fail if PYTHONHOME is set to the empty string (which is bad anyway) +# could use `if (set -u; : $PYTHONHOME) ;` in bash +if [ -n "${PYTHONHOME:-}" ] ; then + _OLD_VIRTUAL_PYTHONHOME="${PYTHONHOME:-}" + unset PYTHONHOME +fi + +if [ -z "${VIRTUAL_ENV_DISABLE_PROMPT:-}" ] ; then + _OLD_VIRTUAL_PS1="${PS1:-}" + PS1="("'(.venv312) '") ${PS1:-}" + export PS1 +fi + +# Call hash to forget past commands. Without forgetting +# past commands the $PATH changes we made may not be respected +hash -r 2> /dev/null diff --git a/.venv312/Scripts/activate.bat b/.venv312/Scripts/activate.bat new file mode 100644 index 0000000..eb7fef6 --- /dev/null +++ b/.venv312/Scripts/activate.bat @@ -0,0 +1,34 @@ +@echo off + +rem This file is UTF-8 encoded, so we need to update the current code page while executing it +for /f "tokens=2 delims=:." %%a in ('"%SystemRoot%\System32\chcp.com"') do ( + set _OLD_CODEPAGE=%%a +) +if defined _OLD_CODEPAGE ( + "%SystemRoot%\System32\chcp.com" 65001 > nul +) + +set "VIRTUAL_ENV=C:\Users\fmerino\Documents\GitHub\Python-Web-Scraping\.venv312" + +if not defined PROMPT set PROMPT=$P$G + +if defined _OLD_VIRTUAL_PROMPT set PROMPT=%_OLD_VIRTUAL_PROMPT% +if defined _OLD_VIRTUAL_PYTHONHOME set PYTHONHOME=%_OLD_VIRTUAL_PYTHONHOME% + +set _OLD_VIRTUAL_PROMPT=%PROMPT% +set PROMPT=(.venv312) %PROMPT% + +if defined PYTHONHOME set _OLD_VIRTUAL_PYTHONHOME=%PYTHONHOME% +set PYTHONHOME= + +if defined _OLD_VIRTUAL_PATH set PATH=%_OLD_VIRTUAL_PATH% +if not defined _OLD_VIRTUAL_PATH set _OLD_VIRTUAL_PATH=%PATH% + +set "PATH=%VIRTUAL_ENV%\Scripts;%PATH%" +set "VIRTUAL_ENV_PROMPT=(.venv312) " + +:END +if defined _OLD_CODEPAGE ( + "%SystemRoot%\System32\chcp.com" %_OLD_CODEPAGE% > nul + set _OLD_CODEPAGE= +) diff --git a/.venv312/Scripts/deactivate.bat b/.venv312/Scripts/deactivate.bat new file mode 100644 index 0000000..62a39a7 --- /dev/null +++ b/.venv312/Scripts/deactivate.bat @@ -0,0 +1,22 @@ +@echo off + +if defined _OLD_VIRTUAL_PROMPT ( + set "PROMPT=%_OLD_VIRTUAL_PROMPT%" +) +set _OLD_VIRTUAL_PROMPT= + +if defined _OLD_VIRTUAL_PYTHONHOME ( + set "PYTHONHOME=%_OLD_VIRTUAL_PYTHONHOME%" + set _OLD_VIRTUAL_PYTHONHOME= +) + +if defined _OLD_VIRTUAL_PATH ( + set "PATH=%_OLD_VIRTUAL_PATH%" +) + +set _OLD_VIRTUAL_PATH= + +set VIRTUAL_ENV= +set VIRTUAL_ENV_PROMPT= + +:END diff --git a/.venv312/Scripts/debugpy-adapter.exe b/.venv312/Scripts/debugpy-adapter.exe new 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z?>1a9bDL_l#z)5`;00=lQ{&q%_wtl=-Ov01N zljA0g@@YmKn>BYdVndf!mH^kQp9=#>mH*`s csj0`GRPBQq%s^6<^Y>fmuXRR)Z* {root_key_name}\\{key_name}[{value_name}]={value!r}") + finally: + my_key.Close() + finally: + root_key.Close() + + +def UnsetPyKeyVal(key_name, value_name, delete_key=False): + root_hkey = get_root_hkey() + root_key = winreg.OpenKey(root_hkey, root_key_name) + try: + my_key = winreg.OpenKey(root_key, key_name, 0, winreg.KEY_SET_VALUE) + try: + winreg.DeleteValue(my_key, value_name) + if verbose: + print(f"-> DELETE {root_key_name}\\{key_name}[{value_name}]") + finally: + my_key.Close() + if delete_key: + winreg.DeleteKey(root_key, key_name) + if verbose: + print(f"-> DELETE {root_key_name}\\{key_name}") + except OSError as why: + winerror = getattr(why, "winerror", why.errno) + if winerror != 2: # file not found + raise + finally: + root_key.Close() + + +def RegisterCOMObjects(register=True): + import win32com.server.register + + if register: + func = win32com.server.register.RegisterClasses + else: + func = win32com.server.register.UnregisterClasses + flags = {} + if not verbose: + flags["quiet"] = 1 + for module, klass_name in com_modules: + __import__(module) + mod = sys.modules[module] + flags["finalize_register"] = getattr(mod, "DllRegisterServer", None) + flags["finalize_unregister"] = getattr(mod, "DllUnregisterServer", None) + klass = getattr(mod, klass_name) + func(klass, **flags) + + +def RegisterHelpFile(register=True, lib_dir=None): + if lib_dir is None: + lib_dir = sysconfig.get_paths()["platlib"] + if register: + # Register the .chm help file. + chm_file = os.path.join(lib_dir, "PyWin32.chm") + if os.path.isfile(chm_file): + # This isn't recursive, so if 'Help' doesn't exist, we croak + SetPyKeyVal("Help", None, None) + SetPyKeyVal("Help\\Pythonwin Reference", None, chm_file) + return chm_file + else: + print("NOTE: PyWin32.chm can not be located, so has not been registered") + else: + UnsetPyKeyVal("Help\\Pythonwin Reference", None, delete_key=True) + return None + + +def RegisterPythonwin(register=True, lib_dir=None): + """Add (or remove) Pythonwin to context menu for python scripts. + ??? Should probably also add Edit command for pys files also. + Also need to remove these keys on uninstall, but there's no function + to add registry entries to uninstall log ??? + """ + import os + + if lib_dir is None: + lib_dir = sysconfig.get_paths()["platlib"] + classes_root = get_root_hkey() + ## Installer executable doesn't seem to pass anything to postinstall script indicating if it's a debug build + pythonwin_exe = os.path.join(lib_dir, "Pythonwin", "Pythonwin.exe") + pythonwin_edit_command = pythonwin_exe + ' -edit "%1"' + + keys_vals = [ + ( + "Software\\Microsoft\\Windows\\CurrentVersion\\App Paths\\Pythonwin.exe", + "", + pythonwin_exe, + ), + ( + "Software\\Classes\\Python.File\\shell\\Edit with Pythonwin", + "command", + pythonwin_edit_command, + ), + ( + "Software\\Classes\\Python.NoConFile\\shell\\Edit with Pythonwin", + "command", + pythonwin_edit_command, + ), + ] + + try: + if register: + for key, sub_key, val in keys_vals: + ## Since winreg only uses the character Api functions, this can fail if Python + ## is installed to a path containing non-ascii characters + hkey = winreg.CreateKey(classes_root, key) + if sub_key: + hkey = winreg.CreateKey(hkey, sub_key) + winreg.SetValueEx(hkey, None, 0, winreg.REG_SZ, val) + hkey.Close() + else: + for key, sub_key, val in keys_vals: + try: + if sub_key: + hkey = winreg.OpenKey(classes_root, key) + winreg.DeleteKey(hkey, sub_key) + hkey.Close() + winreg.DeleteKey(classes_root, key) + except OSError as why: + winerror = getattr(why, "winerror", why.errno) + if winerror != 2: # file not found + raise + finally: + # tell windows about the change + from win32com.shell import shell, shellcon + + shell.SHChangeNotify( + shellcon.SHCNE_ASSOCCHANGED, shellcon.SHCNF_IDLIST, None, None + ) + + +def get_shortcuts_folder(): + if get_root_hkey() == winreg.HKEY_LOCAL_MACHINE: + try: + fldr = get_special_folder_path("CSIDL_COMMON_PROGRAMS") + except OSError: + # No CSIDL_COMMON_PROGRAMS on this platform + fldr = get_special_folder_path("CSIDL_PROGRAMS") + else: + # non-admin install - always goes in this user's start menu. + fldr = get_special_folder_path("CSIDL_PROGRAMS") + + try: + install_group = winreg.QueryValue( + get_root_hkey(), root_key_name + "\\InstallPath\\InstallGroup" + ) + except OSError: + install_group = "Python %d.%d" % ( + sys.version_info.major, + sys.version_info.minor, + ) + return os.path.join(fldr, install_group) + + +# Get the system directory, which may be the Wow64 directory if we are a 32bit +# python on a 64bit OS. +def get_system_dir(): + import win32api # we assume this exists. + + try: + import pythoncom + import win32process + from win32com.shell import shell, shellcon + + try: + if win32process.IsWow64Process(): + return shell.SHGetSpecialFolderPath(0, shellcon.CSIDL_SYSTEMX86) + return shell.SHGetSpecialFolderPath(0, shellcon.CSIDL_SYSTEM) + except (pythoncom.com_error, win32process.error): + return win32api.GetSystemDirectory() + except ImportError: + return win32api.GetSystemDirectory() + + +def fixup_dbi(): + # We used to have a dbi.pyd with our .pyd files, but now have a .py file. + # If the user didn't uninstall, they will find the .pyd which will cause + # problems - so handle that. + import win32api + import win32con + + pyd_name = os.path.join(os.path.dirname(win32api.__file__), "dbi.pyd") + pyd_d_name = os.path.join(os.path.dirname(win32api.__file__), "dbi_d.pyd") + py_name = os.path.join(os.path.dirname(win32con.__file__), "dbi.py") + for this_pyd in (pyd_name, pyd_d_name): + this_dest = this_pyd + ".old" + if os.path.isfile(this_pyd) and os.path.isfile(py_name): + try: + if os.path.isfile(this_dest): + print( + f"Old dbi '{this_dest}' already exists - deleting '{this_pyd}'" + ) + os.remove(this_pyd) + else: + os.rename(this_pyd, this_dest) + print(f"renamed '{this_pyd}'->'{this_pyd}.old'") + except OSError as exc: + print(f"FAILED to rename '{this_pyd}': {exc}") + + +def install(lib_dir): + import traceback + + # The .pth file is now installed as a regular file. + # Create the .pth file in the site-packages dir, and use only relative paths + # We used to write a .pth directly to sys.prefix - clobber it. + if os.path.isfile(os.path.join(sys.prefix, "pywin32.pth")): + os.unlink(os.path.join(sys.prefix, "pywin32.pth")) + # The .pth may be new and therefore not loaded in this session. + # Setup the paths just in case. + for name in "win32 win32\\lib Pythonwin".split(): + sys.path.append(os.path.join(lib_dir, name)) + # It is possible people with old versions installed with still have + # pywintypes and pythoncom registered. We no longer need this, and stale + # entries hurt us. + for name in "pythoncom pywintypes".split(): + keyname = "Software\\Python\\PythonCore\\" + sys.winver + "\\Modules\\" + name + for root in winreg.HKEY_LOCAL_MACHINE, winreg.HKEY_CURRENT_USER: + try: + winreg.DeleteKey(root, keyname + "\\Debug") + except OSError: + pass + try: + winreg.DeleteKey(root, keyname) + except OSError: + pass + LoadSystemModule(lib_dir, "pywintypes") + LoadSystemModule(lib_dir, "pythoncom") + import win32api + + # and now we can get the system directory: + files = glob.glob(os.path.join(lib_dir, "pywin32_system32\\*.*")) + if not files: + raise RuntimeError("No system files to copy!!") + # Try the system32 directory first - if that fails due to "access denied", + # it implies a non-admin user, and we use sys.prefix + for dest_dir in [get_system_dir(), sys.prefix]: + # and copy some files over there + worked = 0 + try: + for fname in files: + base = os.path.basename(fname) + dst = os.path.join(dest_dir, base) + CopyTo("installing %s" % base, fname, dst) + if verbose: + print(f"Copied {base} to {dst}") + worked = 1 + # Nuke any other versions that may exist - having + # duplicates causes major headaches. + bad_dest_dirs = [ + os.path.join(sys.prefix, "Library\\bin"), + os.path.join(sys.prefix, "Lib\\site-packages\\win32"), + ] + if dest_dir != sys.prefix: + bad_dest_dirs.append(sys.prefix) + for bad_dest_dir in bad_dest_dirs: + bad_fname = os.path.join(bad_dest_dir, base) + if os.path.exists(bad_fname): + # let exceptions go here - delete must succeed + os.unlink(bad_fname) + if worked: + break + except win32api.error as details: + if details.winerror == 5: + # access denied - user not admin - try sys.prefix dir, + # but first check that a version doesn't already exist + # in that place - otherwise that one will still get used! + if os.path.exists(dst): + msg = ( + "The file '%s' exists, but can not be replaced " + "due to insufficient permissions. You must " + "reinstall this software as an Administrator" % dst + ) + print(msg) + raise RuntimeError(msg) + continue + raise + else: + raise RuntimeError( + "You don't have enough permissions to install the system files" + ) + + # Register our demo COM objects. + try: + try: + RegisterCOMObjects() + except win32api.error as details: + if details.winerror != 5: # ERROR_ACCESS_DENIED + raise + print("You do not have the permissions to install COM objects.") + print("The sample COM objects were not registered.") + except Exception: + print("FAILED to register the Python COM objects") + traceback.print_exc() + + # There may be no main Python key in HKCU if, eg, an admin installed + # python itself. + winreg.CreateKey(get_root_hkey(), root_key_name) + + chm_file = None + try: + chm_file = RegisterHelpFile(True, lib_dir) + except Exception: + print("Failed to register help file") + traceback.print_exc() + else: + if verbose: + print("Registered help file") + + # misc other fixups. + fixup_dbi() + + # Register Pythonwin in context menu + try: + RegisterPythonwin(True, lib_dir) + except Exception: + print("Failed to register pythonwin as editor") + traceback.print_exc() + else: + if verbose: + print("Pythonwin has been registered in context menu") + + # Create the win32com\gen_py directory. + make_dir = os.path.join(lib_dir, "win32com", "gen_py") + if not os.path.isdir(make_dir): + if verbose: + print(f"Creating directory {make_dir}") + os.mkdir(make_dir) + + try: + # create shortcuts + # CSIDL_COMMON_PROGRAMS only available works on NT/2000/XP, and + # will fail there if the user has no admin rights. + fldr = get_shortcuts_folder() + # If the group doesn't exist, then we don't make shortcuts - its + # possible that this isn't a "normal" install. + if os.path.isdir(fldr): + dst = os.path.join(fldr, "PythonWin.lnk") + create_shortcut( + os.path.join(lib_dir, "Pythonwin\\Pythonwin.exe"), + "The Pythonwin IDE", + dst, + "", + sys.prefix, + ) + if verbose: + print("Shortcut for Pythonwin created") + # And the docs. + if chm_file: + dst = os.path.join(fldr, "Python for Windows Documentation.lnk") + doc = "Documentation for the PyWin32 extensions" + create_shortcut(chm_file, doc, dst) + if verbose: + print("Shortcut to documentation created") + else: + if verbose: + print(f"Can't install shortcuts - {fldr!r} is not a folder") + except Exception as details: + print(details) + + # importing win32com.client ensures the gen_py dir created - not strictly + # necessary to do now, but this makes the installation "complete" + try: + import win32com.client # noqa + except ImportError: + # Don't let this error sound fatal + pass + print("The pywin32 extensions were successfully installed.") + + +def uninstall(lib_dir): + # First ensure our system modules are loaded from pywin32_system, so + # we can remove the ones we copied... + LoadSystemModule(lib_dir, "pywintypes") + LoadSystemModule(lib_dir, "pythoncom") + + try: + RegisterCOMObjects(False) + except Exception as why: + print(f"Failed to unregister COM objects: {why}") + + try: + RegisterHelpFile(False, lib_dir) + except Exception as why: + print(f"Failed to unregister help file: {why}") + else: + if verbose: + print("Unregistered help file") + + try: + RegisterPythonwin(False, lib_dir) + except Exception as why: + print(f"Failed to unregister Pythonwin: {why}") + else: + if verbose: + print("Unregistered Pythonwin") + + try: + # remove gen_py directory. + gen_dir = os.path.join(lib_dir, "win32com", "gen_py") + if os.path.isdir(gen_dir): + shutil.rmtree(gen_dir) + if verbose: + print(f"Removed directory {gen_dir}") + + # Remove pythonwin compiled "config" files. + pywin_dir = os.path.join(lib_dir, "Pythonwin", "pywin") + for fname in glob.glob(os.path.join(pywin_dir, "*.cfc")): + os.remove(fname) + + # The dbi.pyd.old files we may have created. + try: + os.remove(os.path.join(lib_dir, "win32", "dbi.pyd.old")) + except OSError: + pass + try: + os.remove(os.path.join(lib_dir, "win32", "dbi_d.pyd.old")) + except OSError: + pass + + except Exception as why: + print(f"Failed to remove misc files: {why}") + + try: + fldr = get_shortcuts_folder() + for link in ("PythonWin.lnk", "Python for Windows Documentation.lnk"): + fqlink = os.path.join(fldr, link) + if os.path.isfile(fqlink): + os.remove(fqlink) + if verbose: + print(f"Removed {link}") + except Exception as why: + print(f"Failed to remove shortcuts: {why}") + # Now remove the system32 files. + files = glob.glob(os.path.join(lib_dir, "pywin32_system32\\*.*")) + # Try the system32 directory first - if that fails due to "access denied", + # it implies a non-admin user, and we use sys.prefix + try: + for dest_dir in [get_system_dir(), sys.prefix]: + # and copy some files over there + worked = 0 + for fname in files: + base = os.path.basename(fname) + dst = os.path.join(dest_dir, base) + if os.path.isfile(dst): + try: + os.remove(dst) + worked = 1 + if verbose: + print("Removed file %s" % (dst)) + except Exception: + print(f"FAILED to remove {dst}") + if worked: + break + except Exception as why: + print(f"FAILED to remove system files: {why}") + + +# NOTE: This used to be run from inside the bdist_wininst created binary un/installer. +# From inside the binary installer this script HAD to NOT +# call sys.exit() or raise SystemExit, otherwise the installer would also terminate! +# Out of principle, we're still not using system exits. + + +def verify_destination(location: str) -> str: + location = os.path.abspath(location) + if not os.path.isdir(location): + raise argparse.ArgumentTypeError( + f'Path "{location}" is not an existing directory!' + ) + return location + + +def main(): + parser = argparse.ArgumentParser( + formatter_class=argparse.RawDescriptionHelpFormatter, + description="""A post-install script for the pywin32 extensions. + + * Typical usage: + + > python -m pywin32_postinstall -install + + * or (shorter but you don't have control over which python environment is used) + + > pywin32_postinstall -install + + You need to execute this script, with a '-install' parameter, + to ensure the environment is setup correctly to install COM objects, services, etc. + """, + ) + parser.add_argument( + "-install", + default=False, + action="store_true", + help="Configure the Python environment correctly for pywin32.", + ) + parser.add_argument( + "-remove", + default=False, + action="store_true", + help="Try and remove everything that was installed or copied.", + ) + parser.add_argument( + "-wait", + type=int, + help="Wait for the specified process to terminate before starting.", + ) + parser.add_argument( + "-silent", + default=False, + action="store_true", + help='Don\'t display the "Abort/Retry/Ignore" dialog for files in use.', + ) + parser.add_argument( + "-quiet", + default=False, + action="store_true", + help="Don't display progress messages.", + ) + parser.add_argument( + "-destination", + default=sysconfig.get_paths()["platlib"], + type=verify_destination, + help="Location of the PyWin32 installation", + ) + + args = parser.parse_args() + + if not args.quiet: + print(f"Parsed arguments are: {args}") + + if not args.install ^ args.remove: + parser.error("You need to either choose to -install or -remove!") + + if args.wait is not None: + try: + os.waitpid(args.wait, 0) + except OSError: + # child already dead + pass + + silent = args.silent + verbose = not args.quiet + + if args.install: + install(args.destination) + + if args.remove: + uninstall(args.destination) + + +if __name__ == "__main__": + main() diff --git a/.venv312/Scripts/pywin32_testall.exe b/.venv312/Scripts/pywin32_testall.exe new file mode 100644 index 0000000000000000000000000000000000000000..bf37de606150a93cf130427ad79da79559e13ace GIT binary patch literal 108418 zcmeFadw5jU)%ZWjWXKQ_P7p@IO-Bic#!G0tBo5RJ%;*`JC{}2xf}+8Qib}(bU_}i* zNt@v~ed)#4zP;$%+PC)dzP-K@u*HN(5-vi(8(ykWyqs}B0W}HN^ZTrQW|Da6`@GNh z?;nrOIeVXdS$plZ*IsMwwRUQ*Tjz4ST&_I+w{4fJg{Suk 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2011" +.\" Please adjust this date whenever revising the manpage. +.\" +.\" Some roff macros, for reference: +.\" .nh disable hyphenation +.\" .hy enable hyphenation +.\" .ad l left justify +.\" .ad b justify to both left and right margins +.\" .nf disable filling +.\" .fi enable filling +.\" .br insert line break +.\" .sp insert n+1 empty lines +.\" for manpage-specific macros, see man(7) and groff_man(7) +.\" .SH section heading +.\" .SS secondary section heading +.\" +.\" +.\" To preview this page as plain text: nroff -man ipython.1 +.\" +.SH NAME +ipython \- Tools for Interactive Computing in Python. +.SH SYNOPSIS +.B ipython +.RI [ options ] " files" ... + +.B ipython subcommand +.RI [ options ] ... + +.SH DESCRIPTION +An interactive Python shell with automatic history (input and output), dynamic +object introspection, easier configuration, command completion, access to the +system shell, integration with numerical and scientific computing tools, +web notebook, Qt console, and more. + +For more information on how to use IPython, see 'ipython \-\-help', +or 'ipython \-\-help\-all' for all available command\(hyline options. + +.SH "ENVIRONMENT VARIABLES" +.sp +.PP +\fIIPYTHONDIR\fR +.RS 4 +This is the location where IPython stores all its configuration files. The default +is $HOME/.ipython if IPYTHONDIR is not defined. + +You can see the computed value of IPYTHONDIR with `ipython locate`. + +.SH FILES + +IPython uses various configuration files stored in profiles within IPYTHONDIR. +To generate the default configuration files and start configuring IPython, +do 'ipython profile create', and edit '*_config.py' files located in +IPYTHONDIR/profile_default. + +.SH AUTHORS +IPython is written by the IPython Development Team . diff --git a/lessons/02_web_scraping.ipynb b/lessons/02_web_scraping.ipynb index 52b3597..c8945b6 100644 --- a/lessons/02_web_scraping.ipynb +++ b/lessons/02_web_scraping.ipynb @@ -47,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -115,21 +115,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Collecting lxml\n", - " Downloading lxml-6.0.1-cp313-cp313-win_amd64.whl.metadata (3.9 kB)\n", - "Downloading lxml-6.0.1-cp313-cp313-win_amd64.whl (4.0 MB)\n", - " ---------------------------------------- 0.0/4.0 MB ? eta -:--:--\n", - " ----- ---------------------------------- 0.5/4.0 MB 5.7 MB/s eta 0:00:01\n", - " ---------------------------------------- 4.0/4.0 MB 15.9 MB/s 0:00:00\n", - "Installing collected packages: lxml\n", - "Successfully installed lxml-6.0.1\n", + "Requirement already satisfied: lxml in c:\\users\\fmerino\\documents\\github\\python-web-scraping\\.venv312\\lib\\site-packages (6.0.1)\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } @@ -140,7 +133,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": { "tags": [] }, @@ -184,11 +177,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'requests' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mNameError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;66;03m# Make a GET request\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m req = \u001b[43mrequests\u001b[49m.get(\u001b[33m'\u001b[39m\u001b[33mhttp://www.ilga.gov/senate/default.asp\u001b[39m\u001b[33m'\u001b[39m)\n\u001b[32m 3\u001b[39m \u001b[38;5;66;03m# Read the content of the server’s response\u001b[39;00m\n\u001b[32m 4\u001b[39m src = req.text\n", + "\u001b[31mNameError\u001b[39m: name 'requests' is not defined" + ] + } + ], "source": [ "# Make a GET request\n", "req = requests.get('http://www.ilga.gov/senate/default.asp')\n", @@ -1047,7 +1052,7 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python 3", + "display_name": ".venv312", "language": "python", "name": "python3" }, @@ -1061,7 +1066,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.6" + "version": "3.12.10" } }, "nbformat": 4, diff --git a/solutions/02_web_scraping_solutions.ipynb b/solutions/02_web_scraping_solutions.ipynb index a21532e..7d7124d 100644 --- a/solutions/02_web_scraping_solutions.ipynb +++ b/solutions/02_web_scraping_solutions.ipynb @@ -4,12 +4,13 @@ "cell_type": "markdown", "metadata": {}, "source": [ + "\n", "# Web Scraping with Beautiful Soup: Solutions" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -20,9 +21,35 @@ "import time" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Explicación de cada import**\n", + "\n", + "**from bs4 import BeautifulSoup**\n", + "- Trae la clase BeautifulSoup de la librería BeautifulSoup4.\n", + "- Sirve para parsear (analizar) el HTML o XML de páginas web y poder extraer información (textos, tablas, enlaces, etc.).\n", + "\n", + "**from datetime import datetime**\n", + "- Importa la clase datetime.\n", + "- Te permite manejar fechas y horas: obtener la fecha actual, dar formato, calcular diferencias de tiempo, etc.\n", + "\n", + "**import requests**\n", + "- Carga la librería requests, usada para hacer peticiones HTTP (GET, POST, etc.).\n", + "- Es lo que se usa para descargar contenido de páginas web o conectarse a APIs.\n", + "\n", + "**import time**\n", + "- Importa el módulo estándar time.\n", + "- Te permite trabajar con funciones relacionadas al tiempo:\n", + "\n", + " * time.sleep(segundos) para pausar la ejecución.\n", + " * time.time() para medir tiempos de ejecución." + ] + }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -34,6 +61,29 @@ "soup = BeautifulSoup(src, 'lxml')" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Explicacion**\n", + "\n", + "**req = requests.get('http://www.ilga.gov/senate/default.asp')**\n", + "\n", + "* Usa requests para hacer una petición HTTP GET a la página del Senado del Estado de Illinois (ilga.gov).\n", + "* El servidor responde con el código HTML de esa página.\n", + "* Ese resultado queda guardado en req.\n", + "* Puedes verificar si la petición fue exitosa con req.status_code (200 significa OK).\n", + "\n", + "**src = req.text**\n", + "* Extrae el contenido de la respuesta en forma de texto (string).\n", + "* Aquí estará el HTML crudo de la página web.\n", + "\n", + "**soup = BeautifulSoup(src, 'lxml')**\n", + "* Convierte el HTML en un árbol DOM navegable con la librería BeautifulSoup.\n", + "* Usa el parser lxml (más rápido y flexible que html.parser).\n", + "* Ahora puedes recorrer el HTML con métodos como .find(), .find_all(), .title, etc." + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -45,13 +95,33 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "soup.select(\"a.mainmenu\")" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Explicacion del codigo**\n", + "\n", + " Con soup.select(\"a.mainmenu\") obtendrás una lista de elementos <'a'> solo con clase mainmenu, es decir los dos primeros enlaces." + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -70,6 +140,15 @@ "[link['href'] for link in soup.select(\"a.mainmenu\")]" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Explicacion del codigo**\n", + "\n", + " Ese código lista para extraer solo los atributos href (los enlaces) de todas las etiquetas <'a'> con clase mainmenu." + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -150,6 +229,18 @@ " members.append(senator)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ese bloque de código es un scraper de la página del Senado de Illinois (98ª Asamblea General). Lo que hace es recorrer la tabla de senadores y extraer sus datos principales. Construye una lista de senadores de Illinois (98th GA) con:\n", + "\n", + "* Nombre\n", + "* Distrito\n", + "* Partido político\n", + "* Enlace a su perfil oficial" + ] + }, { "cell_type": "code", "execution_count": null, @@ -322,7 +413,7 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": ".venv312", "language": "python", "name": "python3" }, @@ -336,7 +427,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.13" + "version": "3.12.10" } }, "nbformat": 4, From edd0806ba9fec51f0c09e38deba0842cc228b1f9 Mon Sep 17 00:00:00 2001 From: anmerinoto Date: Sat, 23 Aug 2025 21:21:35 -0500 Subject: [PATCH 10/21] Actualizar README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index a43c02f..ac62820 100644 --- a/README.md +++ b/README.md @@ -7,7 +7,7 @@ Taller de Web Scraping en Python de D-Lab [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dlab-berkeley/Python-Web-Scraping/HEAD) [![License: CC BY 4.0](https://img.shields.io/badge/License-CC_BY_4.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/) -Este repositorio contiene los materiales para el taller de raspado web de Python de D-Lab. +Este repositorio contiene los materiales para el taller de Web Scraping de Python de D-Lab. ## Requisitos previos From 4434ccbd434aea320087dbc6f0526e1907dbc858 Mon Sep 17 00:00:00 2001 From: anmerinoto Date: Sat, 23 Aug 2025 21:23:25 -0500 Subject: [PATCH 11/21] Actualizar README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index ac62820..46547f7 100644 --- a/README.md +++ b/README.md @@ -18,7 +18,7 @@ Consulte el [Catálogo de talleres] (https://dlab-berkeley.github.io/dlab-worksh ## Objetivos del taller En este taller, cubrimos cómo extraer datos de la web usando Python. -El raspado implica descargar el código fuente de una página web y examinar el archivo material para extraer los datos deseados. +El Web Scraping implica descargar el código fuente de una página web y examinar el archivo material para extraer los datos deseados. El Web Scraping generalmente solo se realiza cuando las API web no están disponibles. Plataformas como Twitter, Reddit o The New York Times ofrecen API para recuperar datos. Si usted desea aprender a usar las API web en Python, consulte [Python Web APIs](https://github.com/dlab-berkeley/Python-Web-APIs). From 6db99c78123acf17401beac4d6a61d520f9a464e Mon Sep 17 00:00:00 2001 From: ANGEL MERINO Date: Sun, 24 Aug 2025 01:46:31 -0500 Subject: [PATCH 12/21] Upgrade Files --- .venv312/Scripts/f2py.exe | Bin 0 -> 108406 bytes .venv312/Scripts/numpy-config.exe | Bin 0 -> 108406 bytes README.md | 2 +- solutions/02_web_scraping_solutions.ipynb | 604 +++++++++- solutions/ILGA_Senate_Scraper.ipynb | 298 +++++ solutions/debug_ilga.html | 1215 +++++++++++++++++++++ solutions/debug_list.html | 1215 +++++++++++++++++++++ solutions/senado_ilga_moderno.csv | 61 ++ 8 files changed, 3352 insertions(+), 43 deletions(-) create mode 100644 .venv312/Scripts/f2py.exe create mode 100644 .venv312/Scripts/numpy-config.exe create mode 100644 solutions/ILGA_Senate_Scraper.ipynb create mode 100644 solutions/debug_ilga.html create mode 100644 solutions/debug_list.html create mode 100644 solutions/senado_ilga_moderno.csv diff --git a/.venv312/Scripts/f2py.exe b/.venv312/Scripts/f2py.exe new file mode 100644 index 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z+P!t1wyG<(OS>U=#CvFfyb6aq;--R8Ck}6Si9-G9z$OY;(YlWzXo*kQng#E#iBgkM zXEfd&7meO5YN$%qpIG^C_-dC;Mh< zk6-$_*8VWvZ?a3f?eL~`=C-;dzqvW=4jA%blCB?*7ALq+I0?&uj;J54`^0;(RTI=7 zfa@{3COMM`o{)+$pn4M8{QW%(oatbEvC@K3s64;AYTO1n+vdm-H#2s;a*RTG90TDJ z;7yl+OHhx4OQV5R<;RQ*AM&v*e0gqG#7k~&yFq%R(6hnvnuKu^p6J z&UU(P$AZ*zVsz4E^b-Ael^hm7 zC1HH@L~qOF*r3s)@iV&q-Z4=VlB2zQ_4F%kyDV^N`z|$p*LzRDGPw5iDJ^c(n zdqoCC28D!#4eUF7I6iQs_@(S)87J`jPDL5+nI4&unZq-c2i`G_`}ZHaBQZJjOGw#~N7w$FCZcFcCdR%}ytce{t(({8c**xTB>+5_$V?2-22 z_Q&jF?TPkj_Eh_P`(pbN`)d0-d#-((eV2Wo{hOZ_7TGU7YQi(=}&W&f=UUIjeKl<>cn<$^k8r)N;J)Bx71eYR3GG#TiR7 zR%fis$j#W6u`6R=#=(qZns3D!DwDkP%(P_sWVX%hn%PhD@v+RYnTeUxGE+0jnE$5# za^Qa#2bwev?mlv8GJY|7WK3K%esnuwWJtp3$#MAo_2iL#V<+{SJZfa*^hskA;#)ry zJ*xGP(G#QaYv*G|wwV$gKcz#v_9Jm8HW76bb)`1Z)1qre_ODX)9!+MyW%WiB=Nzh? zg)3$*Q?1sxsMvVCKrL~4Y+Pc(#7UOq>B%)?CMLvL;wQ%?PH$r!oe&=rJ7!Ws!UT)6 z1|e$3##pS@c>G+q)oStgx3n+~wdf8LZ?WJp8fp_YamSka}H#ozU6MEBMmAJuKKO7yhYNj~h@r)5i! y devuelve las URLs absolutas (evita dependencias del HTML antiguo).\n", + "* parse_profile(html): abre cada perfil individual y, con heurísticas (regex):\n", + " * extrae name (buscando h1, h2 o <'title'>),\n", + " * detecta district (varios patrones: “District 47”, “47 District”, etc.),\n", + " * detecta party (letra entre paréntesis (D|R|I) o palabras “Democrat/Republican/Independent”).\n", + "\n", + "**Flujo principal**\n", + "* Visita cada URL en LIST_URLS, junta y de-duplica todas las URLs de perfiles.\n", + "* Si no encuentra enlaces, guarda debug_list.html para inspeccionar el HTML real (útil si hay portal cautivo/antibot).\n", + "* Recorre cada perfil y arma members con tuplas (Nombre, Distrito, Partido, Perfil), poniendo una pausa de 0.5s por cortesía.\n", + "* (Opcional) Crea un DataFrame y exporta senado_ilga_moderno.csv.\n", + "\n", + "**Salida**\n", + "* Imprime cuántos **perfiles encontró** y **miembros parseados**, muestra los primeros, y guarda el CSV si pandas está instalado." ] }, { @@ -261,7 +464,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -295,7 +498,7 @@ " # Extract href\n", " href = row.select('a')[1]['href']\n", " # Create full path\n", - " full_path = \"http://www.ilga.gov/senate/\" + href + \"&Primary=True\"\n", + " full_path = \"https://www.ilga.gov/Senate/Members/List/\" + href + \"&Primary=True\"\n", "\n", " # Store in a tuple\n", " senator = (name, district, party, full_path)\n", @@ -304,16 +507,216 @@ " return(members)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Explicacion del Codigo**\n", + "\n", + "Ese código define una función get_members(url) que hace un web scraping sobre una página de la Asamblea Legislativa de Illinois. Hace lo siguiente:\n", + "\n", + "**Descarga la página web**\n", + "* Hace una petición HTTP a la URL.\n", + "* Obtiene el HTML como texto.\n", + "* Usa BeautifulSoup con el parser lxml para convertirlo en un árbol de etiquetas.\n", + "\n", + "**Inicializa una lista vacía**\n", + "* Aquí se guardarán los senadores extraídos.\n", + "\n", + "**Busca filas de tabla**\n", + "* Selecciona todas las filas <'tr'> anidadas tres niveles (muy específico).\n", + "* Filtra solo las que contienen celdas <'td class=\"detail\">, que son las filas con información útil.\n", + "\n", + "**Extrae los datos de cada fila**\n", + "* De cada fila toma solo las celdas con clase detail.\n", + "* Convierte su contenido a texto.\n", + "* Interpreta la primera celda como nombre, la cuarta como distrito (convertido a entero), y la quinta como partido político.\n", + "\n", + "**Obtiene el enlace al perfil**\n", + "* Busca los enlaces <'a> dentro de la fila.\n", + "* Toma el segundo enlace ([1]).\n", + "* Construye una URL completa concatenando con una ruta base y agregando &Primary=True.\n", + "\n", + "**Guarda la información en una tupla**\n", + "* Agrupa los datos en una tupla con la forma: (Nombre, Distrito, Partido, URL_perfil)\n", + "* Lo agrega a la lista members.\n", + "\n", + "**Devuelve el resultado**\n", + "* Retorna la lista completa de senadores encontrados en la página." + ] + }, { "cell_type": "code", - "execution_count": null, + "execution_count": 37, "metadata": {}, "outputs": [], "source": [ - "# Test your code!\n", - "url = 'http://www.ilga.gov/senate/default.asp?GA=98'\n", - "senate_members = get_members(url)\n", - "len(senate_members)" + "import re\n", + "from urllib.parse import urljoin\n", + "import requests\n", + "from bs4 import BeautifulSoup\n", + "\n", + "def get_members(url: str = \"https://www.ilga.gov/Senate/Members/List\"):\n", + " \"\"\"\n", + " Devuelve una lista de tuplas (Nombre, Distrito:int, Partido:str, Perfil:str)\n", + " extraídas desde la página moderna del Senado de Illinois.\n", + " \"\"\"\n", + " headers = {\"User-Agent\": \"Mozilla/5.0\"}\n", + " resp = requests.get(url, headers=headers, timeout=30)\n", + " resp.raise_for_status()\n", + "\n", + " soup = BeautifulSoup(resp.text, \"lxml\")\n", + " members = []\n", + "\n", + " # Enlaces a perfiles /Senate/Members/Details/\n", + " for a in soup.select('a[href*=\"/Senate/Members/Details/\"], a[href*=\"/senate/members/details/\"]'):\n", + " name = a.get_text(strip=True)\n", + " if not name:\n", + " continue\n", + "\n", + " # En el contenedor suele venir \"Nombre 47 R\" (número + partido)\n", + " full_text = a.parent.get_text(\" \", strip=True)\n", + " tail = full_text.replace(name, \"\").strip()\n", + "\n", + " # 1) patrón directo: \"47 R\"\n", + " m = re.search(r'(\\d+)\\s+([DRI])\\b', tail)\n", + " # 2) fallback: \"District 47 (R)\" u otras variantes\n", + " if not m:\n", + " m = re.search(r'(?:District\\s*)?(\\d+).*?([DRI])\\b', tail, re.I)\n", + " if not m:\n", + " # si no se detecta distrito/partido, igual guarda el nombre y el perfil\n", + " district, party = None, \"\"\n", + " else:\n", + " district = int(m.group(1))\n", + " party = m.group(2).upper()\n", + "\n", + " profile = urljoin(url, a.get(\"href\"))\n", + " members.append((name, district, party, profile))\n", + "\n", + " return members\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Explicación del Codigo**\n", + "\n", + "Ese código define una función get_members que hace web scraping sobre la página moderna del Senado de Illinois y devuelve información básica de cada senador. Hace lo siguiente:\n", + "\n", + "**Definicios de Imports**\n", + "* re: para usar expresiones regulares.\n", + "* urljoin: para construir URLs absolutas a partir de relativas.\n", + "* requests: para hacer la descarga de la página web.\n", + "* BeautifulSoup: para parsear el HTML.\n", + "\n", + "**Definición de la función**\n", + "* Toma como parámetro opcional la URL del listado de miembros del Senado.\n", + "* Si no le pasas nada, usa la lista oficial de senadores.\n", + "\n", + "**Descarga y parseo**\n", + "* Descarga la página con un User-Agent “realista”.\n", + "* raise_for_status() lanza error si la respuesta no fue 200 OK.\n", + "* Convierte el HTML a un árbol con BeautifulSoup.\n", + "\n", + "**Inicializa lista de resultados**\n", + "**Encuentra enlaces a perfiles individuales**\n", + "* Busca todos los <'a> cuyo href contenga /Senate/Members/Details/.\n", + "* Extrae el texto (nombre del senador).\n", + "\n", + "**Extrae distrito y partido del texto alrededor**\n", + "* El contenedor donde está el link suele tener “Nombre 47 R”.\n", + "* Usa regex para detectar el número de distrito y la letra del partido:\n", + " * D = Demócrata\n", + " * R = Republicano\n", + " * I = Independiente\n", + "* Si no encuentra nada, pone district = None y party = \"\".\n", + "\n", + "**Construye la URL del perfil**\n", + "* profile = urljoin(url, a.get(\"href\"))\n", + "\n", + "**Guarda la información**\n", + "* members.append((name, district, party, profile))\n", + "\n", + "**Devuelve el resultado**\n", + "* Entrega una lista de tuplas de la forma: (Nombre, Distrito, Partido, URL_perfil)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total miembros: 60\n", + "('Neil Anderson', None, '', 'https://www.ilga.gov/Senate/Members/Details/3312')\n", + "('Omar Aquino', None, '', 'https://www.ilga.gov/Senate/Members/Details/3316')\n", + "('Li Arellano, Jr.', None, '', 'https://www.ilga.gov/Senate/Members/Details/3383')\n", + "('Chris Balkema', None, '', 'https://www.ilga.gov/Senate/Members/Details/3413')\n", + "('Christopher Belt', None, '', 'https://www.ilga.gov/Senate/Members/Details/3337')\n" + ] + } + ], + "source": [ + "senate_members = get_members() # o get_members(\"https://www.ilga.gov/Senate/Members/List\")\n", + "print(\"Total miembros:\", len(senate_members))\n", + "for m in senate_members[:5]:\n", + " print(m)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "**Explicacion del Codigo**\n", + "\n", + "Este código ejecuta tu scraper, imprime el número total de senadores encontrados, y luego muestra en consola los primeros 5 registros (nombre, distrito, partido y link al perfil)." + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Nombre Distrito Partido \\\n", + "0 Neil Anderson None \n", + "1 Omar Aquino None \n", + "2 Li Arellano, Jr. None \n", + "3 Chris Balkema None \n", + "4 Christopher Belt None \n", + "\n", + " Perfil \n", + "0 https://www.ilga.gov/Senate/Members/Details/3312 \n", + "1 https://www.ilga.gov/Senate/Members/Details/3316 \n", + "2 https://www.ilga.gov/Senate/Members/Details/3383 \n", + "3 https://www.ilga.gov/Senate/Members/Details/3413 \n", + "4 https://www.ilga.gov/Senate/Members/Details/3337 \n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "df = pd.DataFrame(senate_members, columns=[\"Nombre\", \"Distrito\", \"Partido\", \"Perfil\"])\n", + "print(df.head())\n", + "# df.to_csv(\"senado_ilga_moderno.csv\", index=False, encoding=\"utf-8\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Explicacion del Codigo**\n", + "\n", + "* Este código convierte tu lista de senadores en una tabla con pandas y te muestra las primeras 5 filas." ] }, { @@ -339,42 +742,116 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 55, "metadata": {}, "outputs": [], "source": [ - "def get_bills(url):\n", - " src = requests.get(url).text\n", - " soup = BeautifulSoup(src)\n", - " rows = soup.select('tr tr tr')\n", - " bills = []\n", - " # Iterate over rows\n", - " for row in rows:\n", - " # Grab all bill list cells\n", - " cells = row.select('td.billlist')\n", - " # Keep in mind the name of the senator is not a billlist class!\n", - " if len(cells) == 5:\n", - " row_text = [cell.text for cell in cells]\n", - " # Extract info from row text\n", - " bill_id = row_text[0]\n", - " description = row_text[1]\n", - " chamber = row_text[2]\n", - " last_action = row_text[3]\n", - " last_action_date = row_text[4]\n", - " # Consolidate bill info\n", - " bill = (bill_id, description, chamber, last_action, last_action_date)\n", - " bills.append(bill)\n", - " return bills" + "import re, time\n", + "from urllib.parse import urljoin\n", + "import requests\n", + "from bs4 import BeautifulSoup\n", + "\n", + "HEADERS = {\"User-Agent\": \"Mozilla/5.0\"}\n", + "\n", + "def get_members():\n", + " url = \"https://www.ilga.gov/Senate/Members/List\"\n", + " s = requests.Session(); s.headers.update(HEADERS)\n", + " r = s.get(url, timeout=30); r.raise_for_status()\n", + " soup = BeautifulSoup(r.text, \"lxml\")\n", + " \n", + " \n", + "\n", + " # Encuentra todos los enlaces a perfiles\n", + " profile_links = []\n", + " for a in soup.select('a[href]'):\n", + " href = a.get(\"href\") or \"\"\n", + " if re.search(r\"/Senate/Members/Details/\\d+\", href, flags=re.I):\n", + " profile_links.append(urljoin(url, href))\n", + " profile_links = sorted(set(profile_links))\n", + "\n", + " members = []\n", + " # Si hay enlaces, visita cada perfil y extrae datos básicos\n", + " for purl in profile_links:\n", + " try:\n", + " pr = s.get(purl, timeout=30); pr.raise_for_status()\n", + " psoup = BeautifulSoup(pr.text, \"lxml\")\n", + " # Nombre\n", + " name = \"\"\n", + " if (h1 := psoup.select_one(\"h1\")): name = h1.get_text(strip=True)\n", + " elif (h2 := psoup.select_one(\"h2\")): name = h2.get_text(strip=True)\n", + " elif psoup.title: name = psoup.title.get_text(strip=True)\n", + "\n", + " text = psoup.get_text(\" \", strip=True)\n", + " # Distrito\n", + " m = re.search(r\"District\\s*(\\d+)\", text, re.I) or re.search(r\"Senate\\s+District\\s*(\\d+)\", text, re.I)\n", + " district = int(m.group(1)) if m else None\n", + " # Partido\n", + " party = \"\"\n", + " m = re.search(r\"\\((D|R|I)\\)\", text)\n", + " if m: party = m.group(1)\n", + " elif re.search(r\"\\bDemocrat(ic)?\\b\", text, re.I): party = \"D\"\n", + " elif re.search(r\"\\bRepublican\\b\", text, re.I): party = \"R\"\n", + " elif re.search(r\"\\bIndependent\\b\", text, re.I): party = \"I\"\n", + "\n", + " if name:\n", + " members.append((name, district, party, purl))\n", + " except Exception:\n", + " continue\n", + " time.sleep(0.2) # ser amable con el servidor\n", + " return members" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Explicacion del Codigo**\n", + "\n", + "* La función get_members() descarga el listado de senadores de Illinois, detecta los enlaces a cada perfil, entra en cada uno, y devuelve una lista con nombre, distrito, partido y URL de perfil de todos los miembros." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 56, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Perfil seleccionado: https://www.ilga.gov/Senate/Members/Details/3264\n", + "[]\n" + ] + } + ], "source": [ + "senate_members = get_members()\n", + "if not senate_members:\n", + " raise RuntimeError(\"No se obtuvieron senadores. Revisa debug_list.html y los selectores.\")\n", + "\n", + "# Ahora es seguro acceder al primero\n", "test_url = senate_members[0][3]\n", - "get_bills(test_url)[0:5]" + "print(\"Perfil seleccionado:\", test_url)\n", + "\n", + "# Solo llama get_bills si tienes una URL válida\n", + "bills = get_bills(test_url)\n", + "print(bills[:5])\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Explicacion del Codigo**\n", + "\n", + "Ese fragmento de código es un bloque de prueba que usa tu función get_members() (la que scrapea la web del Senado) y después llama a otra función get_bills() (seguramente hecha por ti para extraer proyectos de ley de un senador).\n", + "\n", + "Hace lo siguiente:\n", + "* Usa get_members() para obtener senadores.\n", + "* Se asegura de que haya resultados.\n", + "* Selecciona el perfil del primer senador.\n", + "* Llama a get_bills() sobre ese perfil.\n", + "* Imprime los primeros 5 proyectos de ley de ese senador." ] }, { @@ -390,11 +867,11 @@ }, { "cell_type": "code", - "execution_count": 134, + "execution_count": 60, "metadata": {}, "outputs": [], "source": [ - "bills_dict = {}\n", + "bills_dict = {} \n", "for member in senate_members[:5]:\n", " bills_dict[member[1]] = get_bills(member[3])\n", " time.sleep(1)" @@ -402,11 +879,54 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 61, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Clave encontrada: None\n", + "No hay datos para distrito 52.\n" + ] + } + ], + "source": [ + "# Verificar claves\n", + "for key in bills_dict.keys():\n", + " print(\"Clave encontrada:\", key)\n", + "\n", + "# Acceder de forma segura\n", + "if 52 in bills_dict:\n", + " print(\"Número de proyectos para distrito 52:\", len(bills_dict[52]))\n", + "else:\n", + " print(\"No hay datos para distrito 52.\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Claves disponibles en bills_dict: [None]\n", + "Total claves: 1\n", + "No hay datos para el distrito 52.\n" + ] + } + ], "source": [ - "len(bills_dict[52])" + "print(\"Claves disponibles en bills_dict:\", list(bills_dict.keys()))\n", + "print(\"Total claves:\", len(bills_dict))\n", + "\n", + "bills_52 = bills_dict.get(52) or bills_dict.get(\"52\")\n", + "if bills_52 is None:\n", + " print(\"No hay datos para el distrito 52.\")\n", + "else:\n", + " print(\"Número de proyectos:\", len(bills_52))\n" ] } ], diff --git a/solutions/ILGA_Senate_Scraper.ipynb b/solutions/ILGA_Senate_Scraper.ipynb new file mode 100644 index 0000000..d23cdab --- /dev/null +++ b/solutions/ILGA_Senate_Scraper.ipynb @@ -0,0 +1,298 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# ILGA Senate Members Scraper (Modern Page)\n", + "\n", + "Este notebook descarga el listado de senadores del Estado de Illinois desde la página moderna\n", + "`https://www.ilga.gov/Senate/Members/List`, lo parsea con **BeautifulSoup + lxml**, y genera\n", + "un **DataFrame** y un **CSV** (`senado_ilga_moderno.csv`).\n", + "\n", + "**Requisitos:** conexión a Internet desde tu entorno y las librerías `requests`, `beautifulsoup4`, `lxml`, `pandas`.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# (Opcional) Instalar dependencias desde el propio notebook\n", + "# Descomenta si lo necesitas en tu entorno actual:\n", + "# !pip install -q --upgrade pip\n", + "# !pip install -q requests beautifulsoup4 lxml pandas\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "5a2d0068", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[WARN] No se pudo leer https://www.ilga.gov/Senate/List: 404 Client Error: Not Found for url: https://www.ilga.gov/Senate/List\n", + "Perfiles encontrados en la lista: 60\n", + "Total miembros parseados: 60\n", + "('Member', 8505, 'D', 'https://www.ilga.gov/Senate/Members/Details/3264')\n", + "('Member', 5413, 'R', 'https://www.ilga.gov/Senate/Members/Details/3265')\n", + "('Member', 8176, 'D', 'https://www.ilga.gov/Senate/Members/Details/3268')\n", + "('Member', 5966, 'D', 'https://www.ilga.gov/Senate/Members/Details/3269')\n", + "('Member', 422, 'D', 'https://www.ilga.gov/Senate/Members/Details/3270')\n", + "('Member', 8250, 'D', 'https://www.ilga.gov/Senate/Members/Details/3271')\n", + "('Member', 9573, 'D', 'https://www.ilga.gov/Senate/Members/Details/3276')\n", + "('Member', 3840, 'R', 'https://www.ilga.gov/Senate/Members/Details/3281')\n", + "('Member', 5145, 'D', 'https://www.ilga.gov/Senate/Members/Details/3291')\n", + "('Member', 8066, 'D', 'https://www.ilga.gov/Senate/Members/Details/3292')\n", + "('Member', 9595, 'D', 'https://www.ilga.gov/Senate/Members/Details/3293')\n", + "('Member', 3650, 'D', 'https://www.ilga.gov/Senate/Members/Details/3294')\n", + "('Member', 1006, 'R', 'https://www.ilga.gov/Senate/Members/Details/3295')\n", + "('Member', 8022, 'D', 'https://www.ilga.gov/Senate/Members/Details/3296')\n", + "('Member', 5957, 'R', 'https://www.ilga.gov/Senate/Members/Details/3312')\n", + "('Member', 3875, 'D', 'https://www.ilga.gov/Senate/Members/Details/3313')\n", + "('Member', 8010, 'R', 'https://www.ilga.gov/Senate/Members/Details/3315')\n", + "('Member', 5652, 'D', 'https://www.ilga.gov/Senate/Members/Details/3316')\n", + "('Member', 7746, 'D', 'https://www.ilga.gov/Senate/Members/Details/3317')\n", + "('Member', 5509, 'R', 'https://www.ilga.gov/Senate/Members/Details/3318')\n", + "('Member', 2479, 'R', 'https://www.ilga.gov/Senate/Members/Details/3319')\n", + "('Member', 9407, 'R', 'https://www.ilga.gov/Senate/Members/Details/3329')\n", + "('Member', 3201, 'D', 'https://www.ilga.gov/Senate/Members/Details/3331')\n", + "('Member', 1977, 'R', 'https://www.ilga.gov/Senate/Members/Details/3334')\n", + "('Member', 4, 'R', 'https://www.ilga.gov/Senate/Members/Details/3336')\n", + "('Member', 187, 'D', 'https://www.ilga.gov/Senate/Members/Details/3337')\n", + "('Member', 2119, 'D', 'https://www.ilga.gov/Senate/Members/Details/3338')\n", + "('Member', 8192, 'D', 'https://www.ilga.gov/Senate/Members/Details/3339')\n", + "('Member', 8148, 'D', 'https://www.ilga.gov/Senate/Members/Details/3341')\n", + "('Member', 8206, 'R', 'https://www.ilga.gov/Senate/Members/Details/3342')\n", + "('Member', 5338, 'D', 'https://www.ilga.gov/Senate/Members/Details/3343')\n", + "('Member', 5755, 'R', 'https://www.ilga.gov/Senate/Members/Details/3344')\n", + "('Member', 5500, 'D', 'https://www.ilga.gov/Senate/Members/Details/3345')\n", + "('Member', 1035, 'D', 'https://www.ilga.gov/Senate/Members/Details/3369')\n", + "('Member', 7419, 'D', 'https://www.ilga.gov/Senate/Members/Details/3372')\n", + "('Member', 5304, 'D', 'https://www.ilga.gov/Senate/Members/Details/3375')\n", + "('Member', 523, 'D', 'https://www.ilga.gov/Senate/Members/Details/3376')\n", + "('Member', 8181, 'D', 'https://www.ilga.gov/Senate/Members/Details/3378')\n", + "('Member', 52, 'D', 'https://www.ilga.gov/Senate/Members/Details/3380')\n", + "('Member', 1942, 'R', 'https://www.ilga.gov/Senate/Members/Details/3383')\n", + "('Member', 33, 'D', 'https://www.ilga.gov/Senate/Members/Details/3385')\n", + "('Member', 8137, 'R', 'https://www.ilga.gov/Senate/Members/Details/3386')\n", + "('Member', 6216, 'R', 'https://www.ilga.gov/Senate/Members/Details/3397')\n", + "('Member', 8492, 'D', 'https://www.ilga.gov/Senate/Members/Details/3398')\n", + "('Member', 228, 'D', 'https://www.ilga.gov/Senate/Members/Details/3399')\n", + "('Member', 9415, 'D', 'https://www.ilga.gov/Senate/Members/Details/3403')\n", + "('Member', 54, 'D', 'https://www.ilga.gov/Senate/Members/Details/3404')\n", + "('Member', 1607, 'D', 'https://www.ilga.gov/Senate/Members/Details/3405')\n", + "('Member', 9463, 'R', 'https://www.ilga.gov/Senate/Members/Details/3406')\n", + "('Member', 7353, 'D', 'https://www.ilga.gov/Senate/Members/Details/3407')\n", + "('Member', 4307, 'D', 'https://www.ilga.gov/Senate/Members/Details/3408')\n", + "('Member', 8800, 'D', 'https://www.ilga.gov/Senate/Members/Details/3409')\n", + "('Member', 180, 'R', 'https://www.ilga.gov/Senate/Members/Details/3410')\n", + "('Member', 5247, 'R', 'https://www.ilga.gov/Senate/Members/Details/3411')\n", + "('Member', 2507, 'D', 'https://www.ilga.gov/Senate/Members/Details/3412')\n", + "('Member', 6597, 'R', 'https://www.ilga.gov/Senate/Members/Details/3413')\n", + "('Member', 8191, 'D', 'https://www.ilga.gov/Senate/Members/Details/3442')\n", + "('Member', 6252, 'D', 'https://www.ilga.gov/Senate/Members/Details/3443')\n", + "('Member', 4471, 'D', 'https://www.ilga.gov/Senate/Members/Details/3449')\n", + "('Member', 8010, 'R', 'https://www.ilga.gov/Senate/Members/Details/3460')\n", + "\n", + "Primeras 5 filas:\n", + " Nombre Distrito Partido Perfil\n", + "0 Member 8505 D https://www.ilga.gov/Senate/Members/Details/3264\n", + "1 Member 5413 R https://www.ilga.gov/Senate/Members/Details/3265\n", + "2 Member 8176 D https://www.ilga.gov/Senate/Members/Details/3268\n", + "3 Member 5966 D https://www.ilga.gov/Senate/Members/Details/3269\n", + "4 Member 422 D https://www.ilga.gov/Senate/Members/Details/3270\n", + "\n", + "CSV generado: senado_ilga_moderno.csv\n" + ] + } + ], + "source": [ + "import re, time\n", + "from urllib.parse import urljoin\n", + "import requests\n", + "from bs4 import BeautifulSoup\n", + "\n", + "LIST_URLS = [\n", + " \"https://www.ilga.gov/Senate/Members/List\",\n", + " \"https://www.ilga.gov/Senate/List\",\n", + "]\n", + "BASE = \"https://www.ilga.gov\"\n", + "\n", + "HEADERS = {\n", + " \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 \"\n", + " \"(KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36\",\n", + " \"Accept\": \"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\",\n", + " \"Accept-Language\": \"es-ES,es;q=0.9,en;q=0.8\",\n", + " \"Referer\": \"https://www.ilga.gov/\",\n", + " \"Connection\": \"keep-alive\",\n", + "}\n", + "\n", + "def fetch(url):\n", + " s = requests.Session()\n", + " s.headers.update(HEADERS)\n", + " r = s.get(url, timeout=30)\n", + " r.raise_for_status()\n", + " return r\n", + "\n", + "def find_profile_links(html, base=BASE):\n", + " soup = BeautifulSoup(html, \"lxml\")\n", + " # busca anchors a /Senate/Members/Details/... (insensible a mayúsculas)\n", + " links = set()\n", + " for a in soup.select('a[href]'):\n", + " href = a.get(\"href\") or \"\"\n", + " if re.search(r\"/Senate/Members/Details/\\d+\", href, flags=re.I):\n", + " links.add(urljoin(base, href))\n", + " return sorted(links)\n", + "\n", + "def parse_profile(html):\n", + " \"\"\"Devuelve (name, district:int|None, party:str|''), usando varias heurísticas.\"\"\"\n", + " soup = BeautifulSoup(html, \"lxml\")\n", + "\n", + " # Nombre: probar h1, h2, title, aria-labels…\n", + " name = \"\"\n", + " cand = []\n", + " cand += [h.get_text(strip=True) for h in soup.select(\"h1\")]\n", + " if not cand: cand += [h.get_text(strip=True) for h in soup.select(\"h2\")]\n", + " if not cand and soup.title: cand += [soup.title.get_text(strip=True)]\n", + " if cand: name = cand[0]\n", + "\n", + " # Texto visible para regex\n", + " text = soup.get_text(\" \", strip=True)\n", + "\n", + " # Distrito (varias variantes)\n", + " district = None\n", + " for pat in [\n", + " r\"District\\s*(\\d+)\",\n", + " r\"(\\d+)\\s+District\",\n", + " r\"Senate\\s+District\\s*(\\d+)\",\n", + " r\"(\\d+)\\s+\\(D\\)|(\\d+)\\s+\\(R\\)|(\\d+)\\s+\\(I\\)\"\n", + " ]:\n", + " m = re.search(pat, text, flags=re.I)\n", + " if m:\n", + " # toma el primer grupo no vacío\n", + " for g in m.groups():\n", + " if g and g.isdigit():\n", + " district = int(g)\n", + " break\n", + " if district is not None:\n", + " break\n", + "\n", + " # Partido (D/R/I o completo)\n", + " party = \"\"\n", + " # primero letra entre paréntesis\n", + " m = re.search(r\"\\((D|R|I)\\)\", text)\n", + " if m:\n", + " party = m.group(1)\n", + " else:\n", + " # palabras completas\n", + " if re.search(r\"\\bDemocrat(ic)?\\b\", text, flags=re.I):\n", + " party = \"D\"\n", + " elif re.search(r\"\\bRepublican\\b\", text, flags=re.I):\n", + " party = \"R\"\n", + " elif re.search(r\"\\bIndependent\\b\", text, flags=re.I):\n", + " party = \"I\"\n", + "\n", + " return name, district, party\n", + "\n", + "# === Flujo principal ===\n", + "try:\n", + " # 1) Prueba con las URLs de lista y junta todos los perfiles\n", + " all_profiles = []\n", + " for url in LIST_URLS:\n", + " try:\n", + " r = fetch(url)\n", + " profs = find_profile_links(r.text)\n", + " if profs:\n", + " all_profiles.extend(profs)\n", + " except Exception as e:\n", + " print(f\"[WARN] No se pudo leer {url}: {e}\")\n", + "\n", + " # de-duplicar\n", + " all_profiles = sorted(set(all_profiles))\n", + " print(\"Perfiles encontrados en la lista:\", len(all_profiles))\n", + "\n", + " # Diagnóstico si no hay enlaces\n", + " if not all_profiles:\n", + " print(\"No se hallaron enlaces a perfiles. Guardando debug_list.html…\")\n", + " try:\n", + " open(\"debug_list.html\", \"w\", encoding=\"utf-8\").write(r.text)\n", + " print(\"Revisa debug_list.html para ver el HTML real (¿portal cautivo/bloqueo?).\")\n", + " except Exception:\n", + " pass\n", + "\n", + " # 2) Visita cada perfil y extrae datos\n", + " members = []\n", + " for i, purl in enumerate(all_profiles, 1):\n", + " try:\n", + " pr = fetch(purl)\n", + " name, district, party = parse_profile(pr.text)\n", + " if name: # al menos nombre\n", + " members.append((name, district, party, purl))\n", + " except Exception as e:\n", + " print(f\"[WARN] Perfil con error ({purl}): {e}\")\n", + " time.sleep(0.5) # pausa cortita para ser amable\n", + "\n", + " print(\"Total miembros parseados:\", len(members))\n", + "\n", + " # 3) Mostrar algunas filas\n", + " for m in members[:60]:\n", + " print(m)\n", + "\n", + " # 4) (Opcional) DataFrame/CSV\n", + " try:\n", + " import pandas as pd\n", + " df = pd.DataFrame(members, columns=[\"Nombre\", \"Distrito\", \"Partido\", \"Perfil\"])\n", + " print(\"\\nPrimeras 5 filas:\")\n", + " print(df.head())\n", + " df.to_csv(\"senado_ilga_moderno.csv\", index=False, encoding=\"utf-8\")\n", + " print(\"\\nCSV generado: senado_ilga_moderno.csv\")\n", + " except ImportError:\n", + " print(\"Pandas no está instalado; omitiendo CSV. Instala con: pip install pandas openpyxl\")\n", + "\n", + "except Exception as e:\n", + " print(\"Error general:\", e)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Notas\n", + "- Si no se muestran miembros, guarda el HTML para depurar:\n", + "```python\n", + "import pathlib\n", + "html_path = pathlib.Path(\"debug_ilga.html\")\n", + "html_path.write_text(requests.get(\"https://www.ilga.gov/Senate/Members/List\", headers={\"User-Agent\":\"Mozilla/5.0\"}, timeout=20).text, encoding=\"utf-8\")\n", + "html_path\n", + "```\n", + "- Revisa el archivo `debug_ilga.html` para confirmar la estructura del HTML en tu red.\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv312", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/solutions/debug_ilga.html b/solutions/debug_ilga.html new file mode 100644 index 0000000..9e629da --- /dev/null +++ b/solutions/debug_ilga.html @@ -0,0 +1,1215 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Illinois General Assembly - Members + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

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Senate Members - 104th General Assembly

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+ Democrats: 40 + Republicans: 19 +
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Neil Anderson47R
Omar Aquino2D
Li Arellano, Jr.37R
Chris Balkema53R
Christopher Belt57D
Terri Bryant58R
Cristina Castro22D
Javier L. Cervantes1D
Andrew S. Chesney45R
Lakesia Collins5D
Bill Cunningham18D
John F. Curran41R
Donald P. DeWitte33R
Mary Edly-Allen31D
Laura Ellman21D
Paul Faraci52D
Sara Feigenholtz6D
Laura Fine9D
Dale Fowler59R
Suzy Glowiak Hilton23D
Graciela Guzmán20D
Michael W. Halpin36D
Don Harmon39D
Napoleon Harris, III15D
Erica Harriss56R
Michael E. Hastings19D
Darby A. Hills26R
Linda Holmes42D
Mattie Hunter3D
Adriane Johnson30D
Emil Jones, III14D
Patrick J. Joyce40D
David Koehler46D
Seth Lewis24R
Kimberly A. Lightford4D
Meg Loughran Cappel49D
Robert F. Martwick10D
Steve McClure54R
Julie A. Morrison29D
Laura M. Murphy28D
Robert Peters13D
Jason Plummer55R
Mike Porfirio11D
Willie Preston16D
Sue Rezin38R
Chapin Rose51R
Mike Simmons7D
Elgie R. Sims, Jr.17D
Steve Stadelman34D
Dave Syverson35R
Jil Tracy50R
Doris Turner48D
Sally J. Turner44R
Rachel Ventura43D
Karina Villa25D
Celina Villanueva12D
Ram Villivalam8D
Mark L. Walker27D
Craig Wilcox32R
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Dan McConchie26R
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Senate Members - 104th General Assembly

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+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ Senator + ↓↑ + + District + ↓↑ + + Party + ↓↑ +
Neil Anderson47R
Omar Aquino2D
Li Arellano, Jr.37R
Chris Balkema53R
Christopher Belt57D
Terri Bryant58R
Cristina Castro22D
Javier L. Cervantes1D
Andrew S. Chesney45R
Lakesia Collins5D
Bill Cunningham18D
John F. Curran41R
Donald P. DeWitte33R
Mary Edly-Allen31D
Laura Ellman21D
Paul Faraci52D
Sara Feigenholtz6D
Laura Fine9D
Dale Fowler59R
Suzy Glowiak Hilton23D
Graciela Guzmán20D
Michael W. Halpin36D
Don Harmon39D
Napoleon Harris, III15D
Erica Harriss56R
Michael E. Hastings19D
Darby A. Hills26R
Linda Holmes42D
Mattie Hunter3D
Adriane Johnson30D
Emil Jones, III14D
Patrick J. Joyce40D
David Koehler46D
Seth Lewis24R
Kimberly A. Lightford4D
Meg Loughran Cappel49D
Robert F. Martwick10D
Steve McClure54R
Julie A. Morrison29D
Laura M. Murphy28D
Robert Peters13D
Jason Plummer55R
Mike Porfirio11D
Willie Preston16D
Sue Rezin38R
Chapin Rose51R
Mike Simmons7D
Elgie R. Sims, Jr.17D
Steve Stadelman34D
Dave Syverson35R
Jil Tracy50R
Doris Turner48D
Sally J. Turner44R
Rachel Ventura43D
Karina Villa25D
Celina Villanueva12D
Ram Villivalam8D
Mark L. Walker27D
Craig Wilcox32R
+
+
+
+ +

Former Members

+
+ + + + + + + + + + + + + + + +
+ Senator + ↓↑ + + District + ↓↑ + + Party + ↓↑ +
Dan McConchie26R
+
+
+ + + +
+
+ + + +
+
+ +
+
+ +
+ +
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+ + +
+ + + + + + + + + + + + \ No newline at end of file diff --git a/solutions/senado_ilga_moderno.csv b/solutions/senado_ilga_moderno.csv new file mode 100644 index 0000000..50f0e43 --- /dev/null +++ b/solutions/senado_ilga_moderno.csv @@ -0,0 +1,61 @@ +Nombre,Distrito,Partido,Perfil +Member,8505,D,https://www.ilga.gov/Senate/Members/Details/3264 +Member,5413,R,https://www.ilga.gov/Senate/Members/Details/3265 +Member,8176,D,https://www.ilga.gov/Senate/Members/Details/3268 +Member,5966,D,https://www.ilga.gov/Senate/Members/Details/3269 +Member,422,D,https://www.ilga.gov/Senate/Members/Details/3270 +Member,8250,D,https://www.ilga.gov/Senate/Members/Details/3271 +Member,9573,D,https://www.ilga.gov/Senate/Members/Details/3276 +Member,3840,R,https://www.ilga.gov/Senate/Members/Details/3281 +Member,5145,D,https://www.ilga.gov/Senate/Members/Details/3291 +Member,8066,D,https://www.ilga.gov/Senate/Members/Details/3292 +Member,9595,D,https://www.ilga.gov/Senate/Members/Details/3293 +Member,3650,D,https://www.ilga.gov/Senate/Members/Details/3294 +Member,1006,R,https://www.ilga.gov/Senate/Members/Details/3295 +Member,8022,D,https://www.ilga.gov/Senate/Members/Details/3296 +Member,5957,R,https://www.ilga.gov/Senate/Members/Details/3312 +Member,3875,D,https://www.ilga.gov/Senate/Members/Details/3313 +Member,8010,R,https://www.ilga.gov/Senate/Members/Details/3315 +Member,5652,D,https://www.ilga.gov/Senate/Members/Details/3316 +Member,7746,D,https://www.ilga.gov/Senate/Members/Details/3317 +Member,5509,R,https://www.ilga.gov/Senate/Members/Details/3318 +Member,2479,R,https://www.ilga.gov/Senate/Members/Details/3319 +Member,9407,R,https://www.ilga.gov/Senate/Members/Details/3329 +Member,3201,D,https://www.ilga.gov/Senate/Members/Details/3331 +Member,1977,R,https://www.ilga.gov/Senate/Members/Details/3334 +Member,4,R,https://www.ilga.gov/Senate/Members/Details/3336 +Member,187,D,https://www.ilga.gov/Senate/Members/Details/3337 +Member,2119,D,https://www.ilga.gov/Senate/Members/Details/3338 +Member,8192,D,https://www.ilga.gov/Senate/Members/Details/3339 +Member,8148,D,https://www.ilga.gov/Senate/Members/Details/3341 +Member,8206,R,https://www.ilga.gov/Senate/Members/Details/3342 +Member,5338,D,https://www.ilga.gov/Senate/Members/Details/3343 +Member,5755,R,https://www.ilga.gov/Senate/Members/Details/3344 +Member,5500,D,https://www.ilga.gov/Senate/Members/Details/3345 +Member,1035,D,https://www.ilga.gov/Senate/Members/Details/3369 +Member,7419,D,https://www.ilga.gov/Senate/Members/Details/3372 +Member,5304,D,https://www.ilga.gov/Senate/Members/Details/3375 +Member,523,D,https://www.ilga.gov/Senate/Members/Details/3376 +Member,8181,D,https://www.ilga.gov/Senate/Members/Details/3378 +Member,52,D,https://www.ilga.gov/Senate/Members/Details/3380 +Member,1942,R,https://www.ilga.gov/Senate/Members/Details/3383 +Member,33,D,https://www.ilga.gov/Senate/Members/Details/3385 +Member,8137,R,https://www.ilga.gov/Senate/Members/Details/3386 +Member,6216,R,https://www.ilga.gov/Senate/Members/Details/3397 +Member,8492,D,https://www.ilga.gov/Senate/Members/Details/3398 +Member,228,D,https://www.ilga.gov/Senate/Members/Details/3399 +Member,9415,D,https://www.ilga.gov/Senate/Members/Details/3403 +Member,54,D,https://www.ilga.gov/Senate/Members/Details/3404 +Member,1607,D,https://www.ilga.gov/Senate/Members/Details/3405 +Member,9463,R,https://www.ilga.gov/Senate/Members/Details/3406 +Member,7353,D,https://www.ilga.gov/Senate/Members/Details/3407 +Member,4307,D,https://www.ilga.gov/Senate/Members/Details/3408 +Member,8800,D,https://www.ilga.gov/Senate/Members/Details/3409 +Member,180,R,https://www.ilga.gov/Senate/Members/Details/3410 +Member,5247,R,https://www.ilga.gov/Senate/Members/Details/3411 +Member,2507,D,https://www.ilga.gov/Senate/Members/Details/3412 +Member,6597,R,https://www.ilga.gov/Senate/Members/Details/3413 +Member,8191,D,https://www.ilga.gov/Senate/Members/Details/3442 +Member,6252,D,https://www.ilga.gov/Senate/Members/Details/3443 +Member,4471,D,https://www.ilga.gov/Senate/Members/Details/3449 +Member,8010,R,https://www.ilga.gov/Senate/Members/Details/3460 From 6647386c6916f932675d9aac819507e104034390 Mon Sep 17 00:00:00 2001 From: anmerinoto Date: Sun, 24 Aug 2025 01:48:01 -0500 Subject: [PATCH 13/21] Delete solutions/ILGA_Senate_Scraper.ipynb --- solutions/ILGA_Senate_Scraper.ipynb | 298 ---------------------------- 1 file changed, 298 deletions(-) delete mode 100644 solutions/ILGA_Senate_Scraper.ipynb diff --git a/solutions/ILGA_Senate_Scraper.ipynb b/solutions/ILGA_Senate_Scraper.ipynb deleted file mode 100644 index d23cdab..0000000 --- a/solutions/ILGA_Senate_Scraper.ipynb +++ /dev/null @@ -1,298 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# ILGA Senate Members Scraper (Modern Page)\n", - "\n", - "Este notebook descarga el listado de senadores del Estado de Illinois desde la página moderna\n", - "`https://www.ilga.gov/Senate/Members/List`, lo parsea con **BeautifulSoup + lxml**, y genera\n", - "un **DataFrame** y un **CSV** (`senado_ilga_moderno.csv`).\n", - "\n", - "**Requisitos:** conexión a Internet desde tu entorno y las librerías `requests`, `beautifulsoup4`, `lxml`, `pandas`.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "# (Opcional) Instalar dependencias desde el propio notebook\n", - "# Descomenta si lo necesitas en tu entorno actual:\n", - "# !pip install -q --upgrade pip\n", - "# !pip install -q requests beautifulsoup4 lxml pandas\n" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "5a2d0068", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[WARN] No se pudo leer https://www.ilga.gov/Senate/List: 404 Client Error: Not Found for url: https://www.ilga.gov/Senate/List\n", - "Perfiles encontrados en la lista: 60\n", - "Total miembros parseados: 60\n", - "('Member', 8505, 'D', 'https://www.ilga.gov/Senate/Members/Details/3264')\n", - "('Member', 5413, 'R', 'https://www.ilga.gov/Senate/Members/Details/3265')\n", - "('Member', 8176, 'D', 'https://www.ilga.gov/Senate/Members/Details/3268')\n", - "('Member', 5966, 'D', 'https://www.ilga.gov/Senate/Members/Details/3269')\n", - "('Member', 422, 'D', 'https://www.ilga.gov/Senate/Members/Details/3270')\n", - "('Member', 8250, 'D', 'https://www.ilga.gov/Senate/Members/Details/3271')\n", - "('Member', 9573, 'D', 'https://www.ilga.gov/Senate/Members/Details/3276')\n", - "('Member', 3840, 'R', 'https://www.ilga.gov/Senate/Members/Details/3281')\n", - "('Member', 5145, 'D', 'https://www.ilga.gov/Senate/Members/Details/3291')\n", - "('Member', 8066, 'D', 'https://www.ilga.gov/Senate/Members/Details/3292')\n", - "('Member', 9595, 'D', 'https://www.ilga.gov/Senate/Members/Details/3293')\n", - "('Member', 3650, 'D', 'https://www.ilga.gov/Senate/Members/Details/3294')\n", - "('Member', 1006, 'R', 'https://www.ilga.gov/Senate/Members/Details/3295')\n", - "('Member', 8022, 'D', 'https://www.ilga.gov/Senate/Members/Details/3296')\n", - "('Member', 5957, 'R', 'https://www.ilga.gov/Senate/Members/Details/3312')\n", - "('Member', 3875, 'D', 'https://www.ilga.gov/Senate/Members/Details/3313')\n", - "('Member', 8010, 'R', 'https://www.ilga.gov/Senate/Members/Details/3315')\n", - "('Member', 5652, 'D', 'https://www.ilga.gov/Senate/Members/Details/3316')\n", - "('Member', 7746, 'D', 'https://www.ilga.gov/Senate/Members/Details/3317')\n", - "('Member', 5509, 'R', 'https://www.ilga.gov/Senate/Members/Details/3318')\n", - "('Member', 2479, 'R', 'https://www.ilga.gov/Senate/Members/Details/3319')\n", - "('Member', 9407, 'R', 'https://www.ilga.gov/Senate/Members/Details/3329')\n", - "('Member', 3201, 'D', 'https://www.ilga.gov/Senate/Members/Details/3331')\n", - "('Member', 1977, 'R', 'https://www.ilga.gov/Senate/Members/Details/3334')\n", - "('Member', 4, 'R', 'https://www.ilga.gov/Senate/Members/Details/3336')\n", - "('Member', 187, 'D', 'https://www.ilga.gov/Senate/Members/Details/3337')\n", - "('Member', 2119, 'D', 'https://www.ilga.gov/Senate/Members/Details/3338')\n", - "('Member', 8192, 'D', 'https://www.ilga.gov/Senate/Members/Details/3339')\n", - "('Member', 8148, 'D', 'https://www.ilga.gov/Senate/Members/Details/3341')\n", - "('Member', 8206, 'R', 'https://www.ilga.gov/Senate/Members/Details/3342')\n", - "('Member', 5338, 'D', 'https://www.ilga.gov/Senate/Members/Details/3343')\n", - "('Member', 5755, 'R', 'https://www.ilga.gov/Senate/Members/Details/3344')\n", - "('Member', 5500, 'D', 'https://www.ilga.gov/Senate/Members/Details/3345')\n", - "('Member', 1035, 'D', 'https://www.ilga.gov/Senate/Members/Details/3369')\n", - "('Member', 7419, 'D', 'https://www.ilga.gov/Senate/Members/Details/3372')\n", - "('Member', 5304, 'D', 'https://www.ilga.gov/Senate/Members/Details/3375')\n", - "('Member', 523, 'D', 'https://www.ilga.gov/Senate/Members/Details/3376')\n", - "('Member', 8181, 'D', 'https://www.ilga.gov/Senate/Members/Details/3378')\n", - "('Member', 52, 'D', 'https://www.ilga.gov/Senate/Members/Details/3380')\n", - "('Member', 1942, 'R', 'https://www.ilga.gov/Senate/Members/Details/3383')\n", - "('Member', 33, 'D', 'https://www.ilga.gov/Senate/Members/Details/3385')\n", - "('Member', 8137, 'R', 'https://www.ilga.gov/Senate/Members/Details/3386')\n", - "('Member', 6216, 'R', 'https://www.ilga.gov/Senate/Members/Details/3397')\n", - "('Member', 8492, 'D', 'https://www.ilga.gov/Senate/Members/Details/3398')\n", - "('Member', 228, 'D', 'https://www.ilga.gov/Senate/Members/Details/3399')\n", - "('Member', 9415, 'D', 'https://www.ilga.gov/Senate/Members/Details/3403')\n", - "('Member', 54, 'D', 'https://www.ilga.gov/Senate/Members/Details/3404')\n", - "('Member', 1607, 'D', 'https://www.ilga.gov/Senate/Members/Details/3405')\n", - "('Member', 9463, 'R', 'https://www.ilga.gov/Senate/Members/Details/3406')\n", - "('Member', 7353, 'D', 'https://www.ilga.gov/Senate/Members/Details/3407')\n", - "('Member', 4307, 'D', 'https://www.ilga.gov/Senate/Members/Details/3408')\n", - "('Member', 8800, 'D', 'https://www.ilga.gov/Senate/Members/Details/3409')\n", - "('Member', 180, 'R', 'https://www.ilga.gov/Senate/Members/Details/3410')\n", - "('Member', 5247, 'R', 'https://www.ilga.gov/Senate/Members/Details/3411')\n", - "('Member', 2507, 'D', 'https://www.ilga.gov/Senate/Members/Details/3412')\n", - "('Member', 6597, 'R', 'https://www.ilga.gov/Senate/Members/Details/3413')\n", - "('Member', 8191, 'D', 'https://www.ilga.gov/Senate/Members/Details/3442')\n", - "('Member', 6252, 'D', 'https://www.ilga.gov/Senate/Members/Details/3443')\n", - "('Member', 4471, 'D', 'https://www.ilga.gov/Senate/Members/Details/3449')\n", - "('Member', 8010, 'R', 'https://www.ilga.gov/Senate/Members/Details/3460')\n", - "\n", - "Primeras 5 filas:\n", - " Nombre Distrito Partido Perfil\n", - "0 Member 8505 D https://www.ilga.gov/Senate/Members/Details/3264\n", - "1 Member 5413 R https://www.ilga.gov/Senate/Members/Details/3265\n", - "2 Member 8176 D https://www.ilga.gov/Senate/Members/Details/3268\n", - "3 Member 5966 D https://www.ilga.gov/Senate/Members/Details/3269\n", - "4 Member 422 D https://www.ilga.gov/Senate/Members/Details/3270\n", - "\n", - "CSV generado: senado_ilga_moderno.csv\n" - ] - } - ], - "source": [ - "import re, time\n", - "from urllib.parse import urljoin\n", - "import requests\n", - "from bs4 import BeautifulSoup\n", - "\n", - "LIST_URLS = [\n", - " \"https://www.ilga.gov/Senate/Members/List\",\n", - " \"https://www.ilga.gov/Senate/List\",\n", - "]\n", - "BASE = \"https://www.ilga.gov\"\n", - "\n", - "HEADERS = {\n", - " \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 \"\n", - " \"(KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36\",\n", - " \"Accept\": \"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\",\n", - " \"Accept-Language\": \"es-ES,es;q=0.9,en;q=0.8\",\n", - " \"Referer\": \"https://www.ilga.gov/\",\n", - " \"Connection\": \"keep-alive\",\n", - "}\n", - "\n", - "def fetch(url):\n", - " s = requests.Session()\n", - " s.headers.update(HEADERS)\n", - " r = s.get(url, timeout=30)\n", - " r.raise_for_status()\n", - " return r\n", - "\n", - "def find_profile_links(html, base=BASE):\n", - " soup = BeautifulSoup(html, \"lxml\")\n", - " # busca anchors a /Senate/Members/Details/... (insensible a mayúsculas)\n", - " links = set()\n", - " for a in soup.select('a[href]'):\n", - " href = a.get(\"href\") or \"\"\n", - " if re.search(r\"/Senate/Members/Details/\\d+\", href, flags=re.I):\n", - " links.add(urljoin(base, href))\n", - " return sorted(links)\n", - "\n", - "def parse_profile(html):\n", - " \"\"\"Devuelve (name, district:int|None, party:str|''), usando varias heurísticas.\"\"\"\n", - " soup = BeautifulSoup(html, \"lxml\")\n", - "\n", - " # Nombre: probar h1, h2, title, aria-labels…\n", - " name = \"\"\n", - " cand = []\n", - " cand += [h.get_text(strip=True) for h in soup.select(\"h1\")]\n", - " if not cand: cand += [h.get_text(strip=True) for h in soup.select(\"h2\")]\n", - " if not cand and soup.title: cand += [soup.title.get_text(strip=True)]\n", - " if cand: name = cand[0]\n", - "\n", - " # Texto visible para regex\n", - " text = soup.get_text(\" \", strip=True)\n", - "\n", - " # Distrito (varias variantes)\n", - " district = None\n", - " for pat in [\n", - " r\"District\\s*(\\d+)\",\n", - " r\"(\\d+)\\s+District\",\n", - " r\"Senate\\s+District\\s*(\\d+)\",\n", - " r\"(\\d+)\\s+\\(D\\)|(\\d+)\\s+\\(R\\)|(\\d+)\\s+\\(I\\)\"\n", - " ]:\n", - " m = re.search(pat, text, flags=re.I)\n", - " if m:\n", - " # toma el primer grupo no vacío\n", - " for g in m.groups():\n", - " if g and g.isdigit():\n", - " district = int(g)\n", - " break\n", - " if district is not None:\n", - " break\n", - "\n", - " # Partido (D/R/I o completo)\n", - " party = \"\"\n", - " # primero letra entre paréntesis\n", - " m = re.search(r\"\\((D|R|I)\\)\", text)\n", - " if m:\n", - " party = m.group(1)\n", - " else:\n", - " # palabras completas\n", - " if re.search(r\"\\bDemocrat(ic)?\\b\", text, flags=re.I):\n", - " party = \"D\"\n", - " elif re.search(r\"\\bRepublican\\b\", text, flags=re.I):\n", - " party = \"R\"\n", - " elif re.search(r\"\\bIndependent\\b\", text, flags=re.I):\n", - " party = \"I\"\n", - "\n", - " return name, district, party\n", - "\n", - "# === Flujo principal ===\n", - "try:\n", - " # 1) Prueba con las URLs de lista y junta todos los perfiles\n", - " all_profiles = []\n", - " for url in LIST_URLS:\n", - " try:\n", - " r = fetch(url)\n", - " profs = find_profile_links(r.text)\n", - " if profs:\n", - " all_profiles.extend(profs)\n", - " except Exception as e:\n", - " print(f\"[WARN] No se pudo leer {url}: {e}\")\n", - "\n", - " # de-duplicar\n", - " all_profiles = sorted(set(all_profiles))\n", - " print(\"Perfiles encontrados en la lista:\", len(all_profiles))\n", - "\n", - " # Diagnóstico si no hay enlaces\n", - " if not all_profiles:\n", - " print(\"No se hallaron enlaces a perfiles. Guardando debug_list.html…\")\n", - " try:\n", - " open(\"debug_list.html\", \"w\", encoding=\"utf-8\").write(r.text)\n", - " print(\"Revisa debug_list.html para ver el HTML real (¿portal cautivo/bloqueo?).\")\n", - " except Exception:\n", - " pass\n", - "\n", - " # 2) Visita cada perfil y extrae datos\n", - " members = []\n", - " for i, purl in enumerate(all_profiles, 1):\n", - " try:\n", - " pr = fetch(purl)\n", - " name, district, party = parse_profile(pr.text)\n", - " if name: # al menos nombre\n", - " members.append((name, district, party, purl))\n", - " except Exception as e:\n", - " print(f\"[WARN] Perfil con error ({purl}): {e}\")\n", - " time.sleep(0.5) # pausa cortita para ser amable\n", - "\n", - " print(\"Total miembros parseados:\", len(members))\n", - "\n", - " # 3) Mostrar algunas filas\n", - " for m in members[:60]:\n", - " print(m)\n", - "\n", - " # 4) (Opcional) DataFrame/CSV\n", - " try:\n", - " import pandas as pd\n", - " df = pd.DataFrame(members, columns=[\"Nombre\", \"Distrito\", \"Partido\", \"Perfil\"])\n", - " print(\"\\nPrimeras 5 filas:\")\n", - " print(df.head())\n", - " df.to_csv(\"senado_ilga_moderno.csv\", index=False, encoding=\"utf-8\")\n", - " print(\"\\nCSV generado: senado_ilga_moderno.csv\")\n", - " except ImportError:\n", - " print(\"Pandas no está instalado; omitiendo CSV. Instala con: pip install pandas openpyxl\")\n", - "\n", - "except Exception as e:\n", - " print(\"Error general:\", e)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Notas\n", - "- Si no se muestran miembros, guarda el HTML para depurar:\n", - "```python\n", - "import pathlib\n", - "html_path = pathlib.Path(\"debug_ilga.html\")\n", - "html_path.write_text(requests.get(\"https://www.ilga.gov/Senate/Members/List\", headers={\"User-Agent\":\"Mozilla/5.0\"}, timeout=20).text, encoding=\"utf-8\")\n", - "html_path\n", - "```\n", - "- Revisa el archivo `debug_ilga.html` para confirmar la estructura del HTML en tu red.\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv312", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.10" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From b43919c8656b7c62b47b41059cecc39e566ba9f1 Mon Sep 17 00:00:00 2001 From: anmerinoto Date: Sun, 24 Aug 2025 01:48:15 -0500 Subject: [PATCH 14/21] Delete solutions/debug_list.html --- solutions/debug_list.html | 1215 ------------------------------------- 1 file changed, 1215 deletions(-) delete mode 100644 solutions/debug_list.html diff --git a/solutions/debug_list.html b/solutions/debug_list.html deleted file mode 100644 index 3110ef6..0000000 --- a/solutions/debug_list.html +++ /dev/null @@ -1,1215 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Illinois General Assembly - Members - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Senate Members - 104th General Assembly

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- Democrats: 40 - Republicans: 19 -
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- Senator - ↓↑ - - District - ↓↑ - - Party - ↓↑ -
Neil Anderson47R
Omar Aquino2D
Li Arellano, Jr.37R
Chris Balkema53R
Christopher Belt57D
Terri Bryant58R
Cristina Castro22D
Javier L. Cervantes1D
Andrew S. Chesney45R
Lakesia Collins5D
Bill Cunningham18D
John F. Curran41R
Donald P. DeWitte33R
Mary Edly-Allen31D
Laura Ellman21D
Paul Faraci52D
Sara Feigenholtz6D
Laura Fine9D
Dale Fowler59R
Suzy Glowiak Hilton23D
Graciela Guzmán20D
Michael W. Halpin36D
Don Harmon39D
Napoleon Harris, III15D
Erica Harriss56R
Michael E. Hastings19D
Darby A. Hills26R
Linda Holmes42D
Mattie Hunter3D
Adriane Johnson30D
Emil Jones, III14D
Patrick J. Joyce40D
David Koehler46D
Seth Lewis24R
Kimberly A. Lightford4D
Meg Loughran Cappel49D
Robert F. Martwick10D
Steve McClure54R
Julie A. Morrison29D
Laura M. Murphy28D
Robert Peters13D
Jason Plummer55R
Mike Porfirio11D
Willie Preston16D
Sue Rezin38R
Chapin Rose51R
Mike Simmons7D
Elgie R. Sims, Jr.17D
Steve Stadelman34D
Dave Syverson35R
Jil Tracy50R
Doris Turner48D
Sally J. Turner44R
Rachel Ventura43D
Karina Villa25D
Celina Villanueva12D
Ram Villivalam8D
Mark L. Walker27D
Craig Wilcox32R
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Dan McConchie26R
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- - - - - - - - - - - - \ No newline at end of file From 9633f04625557d01cdc831e5967ef212bda210c4 Mon Sep 17 00:00:00 2001 From: ANGEL MERINO Date: Sun, 24 Aug 2025 02:00:52 -0500 Subject: [PATCH 15/21] Update 02_web_scraping.ipynb --- lessons/02_web_scraping.ipynb | 9 +-------- 1 file changed, 1 insertion(+), 8 deletions(-) diff --git a/lessons/02_web_scraping.ipynb b/lessons/02_web_scraping.ipynb index 844eea4..c8945b6 100644 --- a/lessons/02_web_scraping.ipynb +++ b/lessons/02_web_scraping.ipynb @@ -122,18 +122,12 @@ "name": "stdout", "output_type": "stream", "text": [ -<<<<<<< HEAD - "Requirement already satisfied: lxml in c:\\users\\jjala\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (6.0.1)\n", -======= "Requirement already satisfied: lxml in c:\\users\\fmerino\\documents\\github\\python-web-scraping\\.venv312\\lib\\site-packages (6.0.1)\n", ->>>>>>> 4434ccbd434aea320087dbc6f0526e1907dbc858 "Note: you may need to restart the kernel to use updated packages.\n" ] } ], "source": [ - "# 🧩 El comando %pip install lxml instala la librería lxml en tu entorno de Jupyter Notebook.\n", - "# ⚡ lxml es un parser rápido y eficiente para analizar y procesar archivos HTML y XML, muy útil para usar con Beautiful Soup en web scraping.\n", "%pip install lxml" ] }, @@ -145,8 +139,7 @@ }, "outputs": [], "source": [ - "# Importamos las librerías necesarias\n", - "# ⏳ time: para manejar pausas y temporizadores (por ejemplo, para esperar entre solicitudes y no saturar un sitio web).\n", + "# Import required libraries\n", "from bs4 import BeautifulSoup\n", "from datetime import datetime\n", "import requests\n", From 4d764f6de9a8f41e4cf78a74f37c2dac6700a1bc Mon Sep 17 00:00:00 2001 From: ANGEL MERINO Date: Sun, 24 Aug 2025 09:21:59 -0500 Subject: [PATCH 16/21] Upgrade rutina --- solutions/02_web_scraping_solutions.ipynb | 186 ++++++++++++++-------- solutions/senado_ilga_members.csv | 61 +++++++ solutions/senado_ilga_moderno.csv | 120 +++++++------- 3 files changed, 243 insertions(+), 124 deletions(-) create mode 100644 solutions/senado_ilga_members.csv diff --git a/solutions/02_web_scraping_solutions.ipynb b/solutions/02_web_scraping_solutions.ipynb index 68614c5..3d5eaa3 100644 --- a/solutions/02_web_scraping_solutions.ipynb +++ b/solutions/02_web_scraping_solutions.ipynb @@ -243,14 +243,13 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 84, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[WARN] No se pudo leer https://www.ilga.gov/Senate/List: 404 Client Error: Not Found for url: https://www.ilga.gov/Senate/List\n", "Perfiles encontrados en la lista: 60\n", "Total miembros parseados: 60\n", "('Member', 8505, 'D', 'https://www.ilga.gov/Senate/Members/Details/3264')\n", @@ -272,7 +271,7 @@ "3 Member 5966 D https://www.ilga.gov/Senate/Members/Details/3269\n", "4 Member 422 D https://www.ilga.gov/Senate/Members/Details/3270\n", "\n", - "CSV generado: senado_ilga_moderno.csv\n" + "CSV generado: senado_ilga_members.csv\n" ] } ], @@ -284,7 +283,7 @@ "\n", "LIST_URLS = [\n", " \"https://www.ilga.gov/Senate/Members/List\",\n", - " \"https://www.ilga.gov/Senate/List\",\n", + " \"https://www.ilga.gov/Senate/Members\",\n", "]\n", "BASE = \"https://www.ilga.gov\"\n", "\n", @@ -415,7 +414,7 @@ " print(\"\\nPrimeras 5 filas:\")\n", " print(df.head())\n", " df.to_csv(\"senado_ilga_moderno.csv\", index=False, encoding=\"utf-8\")\n", - " print(\"\\nCSV generado: senado_ilga_moderno.csv\")\n", + " print(\"\\nCSV generado: senado_ilga_members.csv\")\n", " except ImportError:\n", " print(\"Pandas no está instalado; omitiendo CSV. Instala con: pip install pandas openpyxl\")\n", "\n", @@ -547,53 +546,107 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 96, "metadata": {}, "outputs": [], "source": [ - "import re\n", + "import re, time\n", "from urllib.parse import urljoin\n", "import requests\n", "from bs4 import BeautifulSoup\n", "\n", - "def get_members(url: str = \"https://www.ilga.gov/Senate/Members/List\"):\n", + "HEADERS = {\"User-Agent\": \"Mozilla/5.0\"}\n", + "\n", + "# --- util: extraer distrito/partido desde texto plano ---\n", + "def _extract_district_party(text: str):\n", + " # 1) \"47 R\"\n", + " m = re.search(r'\\b(\\d+)\\s+([DRI])\\b', text)\n", + " if m:\n", + " return int(m.group(1)), m.group(2).upper()\n", + " # 2) \"District 47 (R)\" u otras variantes\n", + " m = re.search(r'(?:District\\s*)?(\\d+).*?\\b([DRI])\\b', text, flags=re.I)\n", + " if m:\n", + " return int(m.group(1)), m.group(2).upper()\n", + " # 3) Si solo viene el nombre del partido completo\n", + " party = \"\"\n", + " if re.search(r'\\bDemocrat(ic)?\\b', text, flags=re.I):\n", + " party = \"D\"\n", + " elif re.search(r'\\bRepublican\\b', text, flags=re.I):\n", + " party = \"R\"\n", + " elif re.search(r'\\bIndependent\\b', text, flags=re.I):\n", + " party = \"I\"\n", + " return None, party # distrito desconocido, partido si se detectó\n", + "\n", + "# --- leer distrito/partido desde el perfil individual ---\n", + "def _parse_profile(profile_url: str, session: requests.Session):\n", + " r = session.get(profile_url, timeout=30)\n", + " r.raise_for_status()\n", + " psoup = BeautifulSoup(r.text, \"lxml\")\n", + "\n", + " # nombre (por si quieres validar)\n", + " name = \"\"\n", + " h1 = psoup.select_one(\"h1\")\n", + " if h1:\n", + " name = h1.get_text(strip=True)\n", + " elif psoup.title:\n", + " name = psoup.title.get_text(strip=True)\n", + "\n", + " text = psoup.get_text(\" \", strip=True)\n", + " district, party = _extract_district_party(text)\n", + " return name, district, party\n", + "\n", + "def get_members(url: str = \"https://www.ilga.gov/Senate/Members\"):\n", " \"\"\"\n", - " Devuelve una lista de tuplas (Nombre, Distrito:int, Partido:str, Perfil:str)\n", - " extraídas desde la página moderna del Senado de Illinois.\n", + " Devuelve lista de tuplas (Nombre, Distrito:int|None, Partido:str, Perfil:str)\n", + " Tomando enlaces a /Senate/Members/Details/... desde /Senate/Members o /Senate/Members/List.\n", + " Si el distrito/partido no está cerca del enlace, se visita el perfil para extraerlos.\n", " \"\"\"\n", - " headers = {\"User-Agent\": \"Mozilla/5.0\"}\n", - " resp = requests.get(url, headers=headers, timeout=30)\n", - " resp.raise_for_status()\n", + " s = requests.Session()\n", + " s.headers.update(HEADERS)\n", + "\n", + " r = s.get(url, timeout=30)\n", + " r.raise_for_status()\n", + " soup = BeautifulSoup(r.text, \"lxml\")\n", "\n", - " soup = BeautifulSoup(resp.text, \"lxml\")\n", " members = []\n", + " seen = set()\n", "\n", - " # Enlaces a perfiles /Senate/Members/Details/\n", + " # Enlaces a perfiles\n", " for a in soup.select('a[href*=\"/Senate/Members/Details/\"], a[href*=\"/senate/members/details/\"]'):\n", " name = a.get_text(strip=True)\n", " if not name:\n", " continue\n", "\n", - " # En el contenedor suele venir \"Nombre 47 R\" (número + partido)\n", - " full_text = a.parent.get_text(\" \", strip=True)\n", - " tail = full_text.replace(name, \"\").strip()\n", - "\n", - " # 1) patrón directo: \"47 R\"\n", - " m = re.search(r'(\\d+)\\s+([DRI])\\b', tail)\n", - " # 2) fallback: \"District 47 (R)\" u otras variantes\n", - " if not m:\n", - " m = re.search(r'(?:District\\s*)?(\\d+).*?([DRI])\\b', tail, re.I)\n", - " if not m:\n", - " # si no se detecta distrito/partido, igual guarda el nombre y el perfil\n", - " district, party = None, \"\"\n", - " else:\n", - " district = int(m.group(1))\n", - " party = m.group(2).upper()\n", - "\n", - " profile = urljoin(url, a.get(\"href\"))\n", + " profile = urljoin(url, a.get(\"href\") or \"\")\n", + " if profile in seen:\n", + " continue\n", + " seen.add(profile)\n", + "\n", + " # 1) Intentar extraer distrito/partido del contenedor más cercano\n", + " container = a.parent\n", + " # sube hasta 3 niveles si es necesario (algunas páginas usan divs anidados)\n", + " hops = 0\n", + " while container and hops < 3 and len(container.get_text(strip=True)) < 10:\n", + " container = container.parent\n", + " hops += 1\n", + "\n", + " tail_text = \"\"\n", + " if container:\n", + " # texto del contenedor sin el nombre, para evitar falsos positivos\n", + " ctext = container.get_text(\" \", strip=True)\n", + " tail_text = ctext.replace(name, \"\").strip()\n", + "\n", + " district, party = _extract_district_party(tail_text)\n", + "\n", + " # 2) Si no encontramos, entramos al perfil\n", + " if district is None and not party:\n", + " _, district, party = _parse_profile(profile, s)\n", + " time.sleep(0.2) # cortesía con el servidor\n", + "\n", " members.append((name, district, party, profile))\n", "\n", - " return members\n" + " return members\n", + "\n" ] }, { @@ -644,7 +697,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 97, "metadata": {}, "outputs": [ { @@ -652,11 +705,11 @@ "output_type": "stream", "text": [ "Total miembros: 60\n", - "('Neil Anderson', None, '', 'https://www.ilga.gov/Senate/Members/Details/3312')\n", - "('Omar Aquino', None, '', 'https://www.ilga.gov/Senate/Members/Details/3316')\n", - "('Li Arellano, Jr.', None, '', 'https://www.ilga.gov/Senate/Members/Details/3383')\n", - "('Chris Balkema', None, '', 'https://www.ilga.gov/Senate/Members/Details/3413')\n", - "('Christopher Belt', None, '', 'https://www.ilga.gov/Senate/Members/Details/3337')\n" + "('Neil Anderson', 2006, 'R', 'https://www.ilga.gov/Senate/Members/Details/3312')\n", + "('Omar Aquino', 2016, 'D', 'https://www.ilga.gov/Senate/Members/Details/3316')\n", + "('Li Arellano, Jr.', 2025, 'D', 'https://www.ilga.gov/Senate/Members/Details/3383')\n", + "('Chris Balkema', 2025, 'R', 'https://www.ilga.gov/Senate/Members/Details/3413')\n", + "('Christopher Belt', 2019, 'R', 'https://www.ilga.gov/Senate/Members/Details/3337')\n" ] } ], @@ -664,7 +717,8 @@ "senate_members = get_members() # o get_members(\"https://www.ilga.gov/Senate/Members/List\")\n", "print(\"Total miembros:\", len(senate_members))\n", "for m in senate_members[:5]:\n", - " print(m)\n" + " print(m)\n", + "\n" ] }, { @@ -679,19 +733,19 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 98, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - " Nombre Distrito Partido \\\n", - "0 Neil Anderson None \n", - "1 Omar Aquino None \n", - "2 Li Arellano, Jr. None \n", - "3 Chris Balkema None \n", - "4 Christopher Belt None \n", + " Nombre Distrito Partido \\\n", + "0 Neil Anderson 2006.0 R \n", + "1 Omar Aquino 2016.0 D \n", + "2 Li Arellano, Jr. 2025.0 D \n", + "3 Chris Balkema 2025.0 R \n", + "4 Christopher Belt 2019.0 R \n", "\n", " Perfil \n", "0 https://www.ilga.gov/Senate/Members/Details/3312 \n", @@ -707,7 +761,8 @@ "\n", "df = pd.DataFrame(senate_members, columns=[\"Nombre\", \"Distrito\", \"Partido\", \"Perfil\"])\n", "print(df.head())\n", - "# df.to_csv(\"senado_ilga_moderno.csv\", index=False, encoding=\"utf-8\")\n" + "\n", + "df.to_csv(\"senado_ilga_moderno.csv\", index=False, encoding=\"utf-8\")\n" ] }, { @@ -742,7 +797,7 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 72, "metadata": {}, "outputs": [], "source": [ @@ -867,7 +922,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 101, "metadata": {}, "outputs": [], "source": [ @@ -879,15 +934,18 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 104, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Clave encontrada: None\n", - "No hay datos para distrito 52.\n" + "Clave encontrada: 2006\n", + "Clave encontrada: 2016\n", + "Clave encontrada: 2025\n", + "Clave encontrada: 2019\n", + "Número de proyectos para distrito 2006: 0\n" ] } ], @@ -897,24 +955,24 @@ " print(\"Clave encontrada:\", key)\n", "\n", "# Acceder de forma segura\n", - "if 52 in bills_dict:\n", - " print(\"Número de proyectos para distrito 52:\", len(bills_dict[52]))\n", + "if 2006 in bills_dict:\n", + " print(\"Número de proyectos para distrito 2006:\", len(bills_dict[2006]))\n", "else:\n", - " print(\"No hay datos para distrito 52.\")\n" + " print(\"No hay datos para distrito 2006.\")\n" ] }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 107, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Claves disponibles en bills_dict: [None]\n", - "Total claves: 1\n", - "No hay datos para el distrito 52.\n" + "Claves disponibles en bills_dict: [2006, 2016, 2025, 2019]\n", + "Total claves: 4\n", + "No hay datos para el distrito 2019.\n" ] } ], @@ -922,11 +980,11 @@ "print(\"Claves disponibles en bills_dict:\", list(bills_dict.keys()))\n", "print(\"Total claves:\", len(bills_dict))\n", "\n", - "bills_52 = bills_dict.get(52) or bills_dict.get(\"52\")\n", - "if bills_52 is None:\n", - " print(\"No hay datos para el distrito 52.\")\n", + "bills_2019 = bills_dict.get(2019) or bills_dict.get(\"2019\")\n", + "if bills_2019 is None:\n", + " print(\"No hay datos para el distrito 2019.\")\n", "else:\n", - " print(\"Número de proyectos:\", len(bills_52))\n" + " print(\"Número de proyectos:\", len(bills_2019))\n" ] } ], diff --git a/solutions/senado_ilga_members.csv b/solutions/senado_ilga_members.csv new file mode 100644 index 0000000..c1a799c --- /dev/null +++ b/solutions/senado_ilga_members.csv @@ -0,0 +1,61 @@ +Nombre,Distrito,Partido,Perfil +Craig Wilcox,4,R,https://www.ilga.gov/Senate/Members/Details/3336 +Karina Villa,33,D,https://www.ilga.gov/Senate/Members/Details/3385 +Meg Loughran Cappel,52,D,https://www.ilga.gov/Senate/Members/Details/3380 +Mike Porfirio,54,D,https://www.ilga.gov/Senate/Members/Details/3404 +Andrew S. Chesney,180,R,https://www.ilga.gov/Senate/Members/Details/3410 +Christopher Belt,187,D,https://www.ilga.gov/Senate/Members/Details/3337 +Doris Turner,228,D,https://www.ilga.gov/Senate/Members/Details/3399 +Linda Holmes,422,D,https://www.ilga.gov/Senate/Members/Details/3270 +Sara Feigenholtz,523,D,https://www.ilga.gov/Senate/Members/Details/3376 +Chapin Rose,1006,R,https://www.ilga.gov/Senate/Members/Details/3295 +Robert F. Martwick,1035,D,https://www.ilga.gov/Senate/Members/Details/3369 +Willie Preston,1607,D,https://www.ilga.gov/Senate/Members/Details/3405 +"Li Arellano, Jr.",1942,R,https://www.ilga.gov/Senate/Members/Details/3383 +Donald P. DeWitte,1977,R,https://www.ilga.gov/Senate/Members/Details/3334 +Laura Fine,2119,D,https://www.ilga.gov/Senate/Members/Details/3338 +Jil Tracy,2479,R,https://www.ilga.gov/Senate/Members/Details/3319 +Paul Faraci,2507,D,https://www.ilga.gov/Senate/Members/Details/3412 +"Elgie R. Sims, Jr.",3201,D,https://www.ilga.gov/Senate/Members/Details/3331 +Julie A. Morrison,3650,D,https://www.ilga.gov/Senate/Members/Details/3294 +Sue Rezin,3840,R,https://www.ilga.gov/Senate/Members/Details/3281 +Laura M. Murphy,3875,D,https://www.ilga.gov/Senate/Members/Details/3313 +Michael W. Halpin,4307,D,https://www.ilga.gov/Senate/Members/Details/3408 +Mark L. Walker,4471,D,https://www.ilga.gov/Senate/Members/Details/3449 +Bill Cunningham,5145,D,https://www.ilga.gov/Senate/Members/Details/3291 +Erica Harriss,5247,R,https://www.ilga.gov/Senate/Members/Details/3411 +Celina Villanueva,5304,D,https://www.ilga.gov/Senate/Members/Details/3375 +Robert Peters,5338,D,https://www.ilga.gov/Senate/Members/Details/3343 +Dave Syverson,5413,R,https://www.ilga.gov/Senate/Members/Details/3265 +Ram Villivalam,5500,D,https://www.ilga.gov/Senate/Members/Details/3345 +Dale Fowler,5509,R,https://www.ilga.gov/Senate/Members/Details/3318 +Omar Aquino,5652,D,https://www.ilga.gov/Senate/Members/Details/3316 +Jason Plummer,5755,R,https://www.ilga.gov/Senate/Members/Details/3344 +Neil Anderson,5957,R,https://www.ilga.gov/Senate/Members/Details/3312 +Mattie Hunter,5966,D,https://www.ilga.gov/Senate/Members/Details/3269 +Sally J. Turner,6216,R,https://www.ilga.gov/Senate/Members/Details/3397 +Lakesia Collins,6252,D,https://www.ilga.gov/Senate/Members/Details/3443 +Chris Balkema,6597,R,https://www.ilga.gov/Senate/Members/Details/3413 +Mary Edly-Allen,7353,D,https://www.ilga.gov/Senate/Members/Details/3407 +Patrick J. Joyce,7419,D,https://www.ilga.gov/Senate/Members/Details/3372 +Cristina Castro,7746,D,https://www.ilga.gov/Senate/Members/Details/3317 +Dan McConchie,8010,R,https://www.ilga.gov/Senate/Members/Details/3315 +Darby A. Hills,8010,R,https://www.ilga.gov/Senate/Members/Details/3460 +Steve Stadelman,8022,D,https://www.ilga.gov/Senate/Members/Details/3296 +"Napoleon Harris, III",8066,D,https://www.ilga.gov/Senate/Members/Details/3292 +Terri Bryant,8137,R,https://www.ilga.gov/Senate/Members/Details/3386 +Suzy Glowiak Hilton,8148,D,https://www.ilga.gov/Senate/Members/Details/3341 +Don Harmon,8176,D,https://www.ilga.gov/Senate/Members/Details/3268 +Adriane Johnson,8181,D,https://www.ilga.gov/Senate/Members/Details/3378 +Graciela Guzmn,8191,D,https://www.ilga.gov/Senate/Members/Details/3442 +Laura Ellman,8192,D,https://www.ilga.gov/Senate/Members/Details/3339 +Steve McClure,8206,R,https://www.ilga.gov/Senate/Members/Details/3342 +David Koehler,8250,D,https://www.ilga.gov/Senate/Members/Details/3271 +Mike Simmons,8492,D,https://www.ilga.gov/Senate/Members/Details/3398 +Kimberly A. Lightford,8505,D,https://www.ilga.gov/Senate/Members/Details/3264 +Rachel Ventura,8800,D,https://www.ilga.gov/Senate/Members/Details/3409 +John F. Curran,9407,R,https://www.ilga.gov/Senate/Members/Details/3329 +Javier L. Cervantes,9415,D,https://www.ilga.gov/Senate/Members/Details/3403 +Seth Lewis,9463,R,https://www.ilga.gov/Senate/Members/Details/3406 +"Emil Jones, III",9573,D,https://www.ilga.gov/Senate/Members/Details/3276 +Michael E. Hastings,9595,D,https://www.ilga.gov/Senate/Members/Details/3293 diff --git a/solutions/senado_ilga_moderno.csv b/solutions/senado_ilga_moderno.csv index 50f0e43..35c72aa 100644 --- a/solutions/senado_ilga_moderno.csv +++ b/solutions/senado_ilga_moderno.csv @@ -1,61 +1,61 @@ Nombre,Distrito,Partido,Perfil -Member,8505,D,https://www.ilga.gov/Senate/Members/Details/3264 -Member,5413,R,https://www.ilga.gov/Senate/Members/Details/3265 -Member,8176,D,https://www.ilga.gov/Senate/Members/Details/3268 -Member,5966,D,https://www.ilga.gov/Senate/Members/Details/3269 -Member,422,D,https://www.ilga.gov/Senate/Members/Details/3270 -Member,8250,D,https://www.ilga.gov/Senate/Members/Details/3271 -Member,9573,D,https://www.ilga.gov/Senate/Members/Details/3276 -Member,3840,R,https://www.ilga.gov/Senate/Members/Details/3281 -Member,5145,D,https://www.ilga.gov/Senate/Members/Details/3291 -Member,8066,D,https://www.ilga.gov/Senate/Members/Details/3292 -Member,9595,D,https://www.ilga.gov/Senate/Members/Details/3293 -Member,3650,D,https://www.ilga.gov/Senate/Members/Details/3294 -Member,1006,R,https://www.ilga.gov/Senate/Members/Details/3295 -Member,8022,D,https://www.ilga.gov/Senate/Members/Details/3296 -Member,5957,R,https://www.ilga.gov/Senate/Members/Details/3312 -Member,3875,D,https://www.ilga.gov/Senate/Members/Details/3313 -Member,8010,R,https://www.ilga.gov/Senate/Members/Details/3315 -Member,5652,D,https://www.ilga.gov/Senate/Members/Details/3316 -Member,7746,D,https://www.ilga.gov/Senate/Members/Details/3317 -Member,5509,R,https://www.ilga.gov/Senate/Members/Details/3318 -Member,2479,R,https://www.ilga.gov/Senate/Members/Details/3319 -Member,9407,R,https://www.ilga.gov/Senate/Members/Details/3329 -Member,3201,D,https://www.ilga.gov/Senate/Members/Details/3331 -Member,1977,R,https://www.ilga.gov/Senate/Members/Details/3334 -Member,4,R,https://www.ilga.gov/Senate/Members/Details/3336 -Member,187,D,https://www.ilga.gov/Senate/Members/Details/3337 -Member,2119,D,https://www.ilga.gov/Senate/Members/Details/3338 -Member,8192,D,https://www.ilga.gov/Senate/Members/Details/3339 -Member,8148,D,https://www.ilga.gov/Senate/Members/Details/3341 -Member,8206,R,https://www.ilga.gov/Senate/Members/Details/3342 -Member,5338,D,https://www.ilga.gov/Senate/Members/Details/3343 -Member,5755,R,https://www.ilga.gov/Senate/Members/Details/3344 -Member,5500,D,https://www.ilga.gov/Senate/Members/Details/3345 -Member,1035,D,https://www.ilga.gov/Senate/Members/Details/3369 -Member,7419,D,https://www.ilga.gov/Senate/Members/Details/3372 -Member,5304,D,https://www.ilga.gov/Senate/Members/Details/3375 -Member,523,D,https://www.ilga.gov/Senate/Members/Details/3376 -Member,8181,D,https://www.ilga.gov/Senate/Members/Details/3378 -Member,52,D,https://www.ilga.gov/Senate/Members/Details/3380 -Member,1942,R,https://www.ilga.gov/Senate/Members/Details/3383 -Member,33,D,https://www.ilga.gov/Senate/Members/Details/3385 -Member,8137,R,https://www.ilga.gov/Senate/Members/Details/3386 -Member,6216,R,https://www.ilga.gov/Senate/Members/Details/3397 -Member,8492,D,https://www.ilga.gov/Senate/Members/Details/3398 -Member,228,D,https://www.ilga.gov/Senate/Members/Details/3399 -Member,9415,D,https://www.ilga.gov/Senate/Members/Details/3403 -Member,54,D,https://www.ilga.gov/Senate/Members/Details/3404 -Member,1607,D,https://www.ilga.gov/Senate/Members/Details/3405 -Member,9463,R,https://www.ilga.gov/Senate/Members/Details/3406 -Member,7353,D,https://www.ilga.gov/Senate/Members/Details/3407 -Member,4307,D,https://www.ilga.gov/Senate/Members/Details/3408 -Member,8800,D,https://www.ilga.gov/Senate/Members/Details/3409 -Member,180,R,https://www.ilga.gov/Senate/Members/Details/3410 -Member,5247,R,https://www.ilga.gov/Senate/Members/Details/3411 -Member,2507,D,https://www.ilga.gov/Senate/Members/Details/3412 -Member,6597,R,https://www.ilga.gov/Senate/Members/Details/3413 -Member,8191,D,https://www.ilga.gov/Senate/Members/Details/3442 -Member,6252,D,https://www.ilga.gov/Senate/Members/Details/3443 -Member,4471,D,https://www.ilga.gov/Senate/Members/Details/3449 -Member,8010,R,https://www.ilga.gov/Senate/Members/Details/3460 +Neil Anderson,2006.0,R,https://www.ilga.gov/Senate/Members/Details/3312 +Omar Aquino,2016.0,D,https://www.ilga.gov/Senate/Members/Details/3316 +"Li Arellano, Jr.",2025.0,D,https://www.ilga.gov/Senate/Members/Details/3383 +Chris Balkema,2025.0,R,https://www.ilga.gov/Senate/Members/Details/3413 +Christopher Belt,2019.0,R,https://www.ilga.gov/Senate/Members/Details/3337 +Terri Bryant,2015.0,D,https://www.ilga.gov/Senate/Members/Details/3386 +Cristina Castro,2017.0,D,https://www.ilga.gov/Senate/Members/Details/3317 +Javier L. Cervantes,2022.0,R,https://www.ilga.gov/Senate/Members/Details/3403 +Andrew S. Chesney,2018.0,D,https://www.ilga.gov/Senate/Members/Details/3410 +Lakesia Collins,2020.0,R,https://www.ilga.gov/Senate/Members/Details/3443 +Bill Cunningham,2011.0,R,https://www.ilga.gov/Senate/Members/Details/3291 +John F. Curran,110.0,D,https://www.ilga.gov/Senate/Members/Details/3329 +Donald P. DeWitte,2018.0,R,https://www.ilga.gov/Senate/Members/Details/3334 +Mary Edly-Allen,2023.0,D,https://www.ilga.gov/Senate/Members/Details/3407 +Laura Ellman,2019.0,D,https://www.ilga.gov/Senate/Members/Details/3339 +Paul Faraci,2023.0,R,https://www.ilga.gov/Senate/Members/Details/3412 +Sara Feigenholtz,1995.0,R,https://www.ilga.gov/Senate/Members/Details/3376 +Laura Fine,2013.0,R,https://www.ilga.gov/Senate/Members/Details/3338 +Dale Fowler,2016.0,D,https://www.ilga.gov/Senate/Members/Details/3318 +Suzy Glowiak Hilton,2019.0,D,https://www.ilga.gov/Senate/Members/Details/3341 +Graciela Guzmán,2.0,R,https://www.ilga.gov/Senate/Members/Details/3442 +Michael W. Halpin,2023.0,D,https://www.ilga.gov/Senate/Members/Details/3408 +Don Harmon,2003.0,D,https://www.ilga.gov/Senate/Members/Details/3268 +"Napoleon Harris, III",2013.0,R,https://www.ilga.gov/Senate/Members/Details/3292 +Erica Harriss,24.0,D,https://www.ilga.gov/Senate/Members/Details/3411 +Michael E. Hastings,121.0,D,https://www.ilga.gov/Senate/Members/Details/3293 +Darby A. Hills,2025.0,D,https://www.ilga.gov/Senate/Members/Details/3460 +Linda Holmes,309.0,I,https://www.ilga.gov/Senate/Members/Details/3270 +Mattie Hunter,2003.0,R,https://www.ilga.gov/Senate/Members/Details/3269 +Adriane Johnson,2020.0,R,https://www.ilga.gov/Senate/Members/Details/3378 +"Emil Jones, III",2009.0,R,https://www.ilga.gov/Senate/Members/Details/3276 +Patrick J. Joyce,2019.0,D,https://www.ilga.gov/Senate/Members/Details/3372 +David Koehler,2006.0,R,https://www.ilga.gov/Senate/Members/Details/3271 +Seth Lewis,24.0,D,https://www.ilga.gov/Senate/Members/Details/3406 +Kimberly A. Lightford,1998.0,R,https://www.ilga.gov/Senate/Members/Details/3264 +Meg Loughran Cappel,2020.0,D,https://www.ilga.gov/Senate/Members/Details/3380 +Robert F. Martwick,2013.0,D,https://www.ilga.gov/Senate/Members/Details/3369 +Steve McClure,2019.0,I,https://www.ilga.gov/Senate/Members/Details/3342 +Julie A. Morrison,2013.0,D,https://www.ilga.gov/Senate/Members/Details/3294 +Laura M. Murphy,2015.0,R,https://www.ilga.gov/Senate/Members/Details/3313 +Robert Peters,2019.0,I,https://www.ilga.gov/Senate/Members/Details/3343 +Jason Plummer,2019.0,R,https://www.ilga.gov/Senate/Members/Details/3344 +Mike Porfirio,2023.0,I,https://www.ilga.gov/Senate/Members/Details/3404 +Willie Preston,2023.0,R,https://www.ilga.gov/Senate/Members/Details/3405 +Sue Rezin,24.0,D,https://www.ilga.gov/Senate/Members/Details/3281 +Chapin Rose,2003.0,D,https://www.ilga.gov/Senate/Members/Details/3295 +Mike Simmons,2021.0,R,https://www.ilga.gov/Senate/Members/Details/3398 +"Elgie R. Sims, Jr.",2012.0,D,https://www.ilga.gov/Senate/Members/Details/3331 +Steve Stadelman,2013.0,D,https://www.ilga.gov/Senate/Members/Details/3296 +Dave Syverson,1993.0,D,https://www.ilga.gov/Senate/Members/Details/3265 +Jil Tracy,23.0,D,https://www.ilga.gov/Senate/Members/Details/3319 +Doris Turner,2021.0,I,https://www.ilga.gov/Senate/Members/Details/3399 +Sally J. Turner,2021.0,D,https://www.ilga.gov/Senate/Members/Details/3397 +Rachel Ventura,2.0,R,https://www.ilga.gov/Senate/Members/Details/3409 +Karina Villa,2019.0,R,https://www.ilga.gov/Senate/Members/Details/3385 +Celina Villanueva,2019.0,R,https://www.ilga.gov/Senate/Members/Details/3375 +Ram Villivalam,2019.0,R,https://www.ilga.gov/Senate/Members/Details/3345 +Mark L. Walker,2009.0,D,https://www.ilga.gov/Senate/Members/Details/3449 +Craig Wilcox,2018.0,D,https://www.ilga.gov/Senate/Members/Details/3336 +Dan McConchie,,R,https://www.ilga.gov/Senate/Members/Details/3315 From 4af992262bd0853e0b09cb5df704bed636381043 Mon Sep 17 00:00:00 2001 From: julizzazeime456-afk Date: Sun, 24 Aug 2025 17:16:50 -0500 Subject: [PATCH 17/21] agrego traduccionn del paso 1 --- lessons/02_web_scraping.ipynb | 202 +++++++++++++++++++++++++++------- 1 file changed, 164 insertions(+), 38 deletions(-) diff --git a/lessons/02_web_scraping.ipynb b/lessons/02_web_scraping.ipynb index c8945b6..acd5906 100644 --- a/lessons/02_web_scraping.ipynb +++ b/lessons/02_web_scraping.ipynb @@ -115,7 +115,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -128,18 +128,20 @@ } ], "source": [ + "# 🧩 El comando %pip install lxml instala la librería lxml en tu entorno de Jupyter Notebook.\n", + "# ⚡ lxml es un parser rápido y eficiente para analizar y procesar archivos HTML y XML, muy útil para usar con Beautiful Soup en web scraping.\n", "%pip install lxml" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 23, "metadata": { "tags": [] }, "outputs": [], "source": [ - "# Import required libraries\n", + "# importamos las librerías necesarias\n", "from bs4 import BeautifulSoup\n", "from datetime import datetime\n", "import requests\n", @@ -152,45 +154,60 @@ "source": [ "\n", "\n", - "# Extracting and Parsing HTML \n", + "# Extracción y análisis de HTML\n", "\n", - "In order to succesfully scrape and analyse HTML, we'll be going through the following 4 steps:\n", - "1. Make a GET request\n", - "2. Parse the page with Beautiful Soup\n", - "3. Search for HTML elements\n", - "4. Get attributes and text of these elements" + "Para extraer y analizar correctamente HTML, seguiremos los siguientes 4 pasos:\n", + "1. Realizar una solicitud GET\n", + "2. Analizar la página con Beautiful Soup\n", + "3. Buscar elementos HTML\n", + "4. Obtener atributos y texto de estos elementos" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Step 1: Make a GET Request to Obtain a Page's HTML\n", + "## Paso 1: Realiza una solicitud GET para obtener el HTML de una página\n", + "\n", + "Podemos usar la librería Requests para:\n", "\n", - "We can use the Requests library to:\n", + "1. Realizar una solicitud GET a la página, y\n", "\n", - "1. Make a GET request to the page, and\n", - "2. Read in the webpage's HTML code.\n", + "2. Leer el código HTML de la página web.\n", "\n", - "The process of making a request and obtaining a result resembles that of the Web API workflow. Now, however, we're making a request directly to the website, and we're going to have to parse the HTML ourselves. This is in contrast to being provided data organized into a more straightforward `JSON` or `XML` output." + "El proceso de realizar una solicitud y obtener un resultado se asemeja al flujo de trabajo de una API web. Sin embargo, en este caso estamos haciendo la solicitud directamente al sitio web y tendremos que analizar el HTML por nuestra cuenta. Esto es diferente a cuando se nos proporciona la información ya organizada en un formato más sencillo como JSON o XML." ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 24, "metadata": { "tags": [] }, "outputs": [ { - "ename": "NameError", - "evalue": "name 'requests' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mNameError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;66;03m# Make a GET request\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m req = \u001b[43mrequests\u001b[49m.get(\u001b[33m'\u001b[39m\u001b[33mhttp://www.ilga.gov/senate/default.asp\u001b[39m\u001b[33m'\u001b[39m)\n\u001b[32m 3\u001b[39m \u001b[38;5;66;03m# Read the content of the server’s response\u001b[39;00m\n\u001b[32m 4\u001b[39m src = req.text\n", - "\u001b[31mNameError\u001b[39m: name 'requests' is not defined" + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " English\n", + " , \n", + " Afrikaans\n", + " , \n", + " Albanian\n", + " , \n", + " Arabic\n", + " , \n", + " Armenian\n", + " , \n", + " Azerbaijani\n", + " , \n", + " Basque\n", + " , \n", + " Bengali\n", + " , \n", + " Bosnian\n", + " , \n", + " Catalan\n", + " ]\n" + ] + } + ], "source": [ "# Find all elements with a certain tag\n", "a_tags = soup.find_all(\"a\")\n", @@ -274,11 +345,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " English\n", + " \n", + "\n", + " English\n", + " \n" + ] + } + ], "source": [ "a_tags = soup.find_all(\"a\")\n", "a_tags_alt = soup(\"a\")\n", @@ -295,9 +379,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "270\n" + ] + } + ], "source": [ "print(len(a_tags))" ] @@ -315,11 +407,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Get only the 'a' tags in 'sidemenu' class\n", "side_menus = soup(\"a\", class_=\"sidemenu\")\n", @@ -337,11 +440,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Get elements with \"a.sidemenu\" CSS Selector.\n", "selected = soup.select(\"a.sidemenu\")\n", @@ -359,7 +473,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "metadata": {}, "outputs": [], "source": [ @@ -382,11 +496,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "ename": "IndexError", + "evalue": "list index out of range", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mIndexError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[32]\u001b[39m\u001b[32m, line 5\u001b[39m\n\u001b[32m 2\u001b[39m side_menu_links = soup.select(\u001b[33m\"\u001b[39m\u001b[33ma.sidemenu\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 4\u001b[39m \u001b[38;5;66;03m# Examine the first link\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m5\u001b[39m first_link = \u001b[43mside_menu_links\u001b[49m\u001b[43m[\u001b[49m\u001b[32;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[32m 6\u001b[39m \u001b[38;5;28mprint\u001b[39m(first_link)\n\u001b[32m 8\u001b[39m \u001b[38;5;66;03m# What class is this variable?\u001b[39;00m\n", + "\u001b[31mIndexError\u001b[39m: list index out of range" + ] + } + ], "source": [ "# Get all sidemenu links as a list\n", "side_menu_links = soup.select(\"a.sidemenu\")\n", From b3f45a96bf74a452d8a3ebbb409e881d25055634 Mon Sep 17 00:00:00 2001 From: rebe1603 Date: Tue, 26 Aug 2025 10:24:44 -0500 Subject: [PATCH 18/21] =?UTF-8?q?Traduccion=20en=20espa=C3=B1ol=20web=5Fsc?= =?UTF-8?q?rapping?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- lessons/02_web_scraping.ipynb | 234 +++++++++++++++++----------------- 1 file changed, 117 insertions(+), 117 deletions(-) diff --git a/lessons/02_web_scraping.ipynb b/lessons/02_web_scraping.ipynb index acd5906..696e0b0 100644 --- a/lessons/02_web_scraping.ipynb +++ b/lessons/02_web_scraping.ipynb @@ -4,21 +4,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Web Scraping with Beautiful Soup\n", + "# Web Scraping con Beautiful Soup\n", "\n", - "* * * \n", + "* * *\n", "\n", - "### Icons used in this notebook\n", - "🔔 **Question**: A quick question to help you understand what's going on.
\n", - "🥊 **Challenge**: Interactive exercise. We'll work through these in the workshop!
\n", - "⚠️ **Warning**: Heads-up about tricky stuff or common mistakes.
\n", - "💡 **Tip**: How to do something a bit more efficiently or effectively.
\n", - "🎬 **Demo**: Showing off something more advanced – so you know what Python can be used for!
\n", + "### Íconos usados ​​en este cuaderno\n", + "🔔 **Pregunta**: Una pregunta rápida para ayudarte a entender qué está pasando.
\n", + "🥊 **Desafío**: Ejercicio interactivo. ¡Lo resolveremos en el taller!
\n", + "⚠️ **Advertencia**: Atención sobre aspectos complicados o errores comunes.
\n", + "💡 **Consejo**: Cómo hacer algo de forma más eficiente o efectiva.
\n", + "🎬 **Demostración**: ¡Mostrando algo más avanzado para que sepas para qué se puede usar Python!
\n", "\n", - "### Learning Objectives\n", - "1. [Reflection: To Scape Or Not To Scrape](#when)\n", - "2. [Extracting and Parsing HTML](#extract)\n", - "3. [Scraping the Illinois General Assembly](#scrape)" + "### Objetivos de aprendizaje\n", + "1. [Reflexión: Escapar o no raspar](#when)\n", + "2. [Extracción y análisis de HTML](#extract)\n", + "3. [Desmantelando la Asamblea General de Illinois](#scrape)" ] }, { @@ -27,22 +27,22 @@ "source": [ "\n", "\n", - "# To Scrape Or Not To Scrape\n", + "# Scraping o no scraping\n", "\n", - "When we'd like to access data from the web, we first have to make sure if the website we are interested in offers a Web API. Platforms like Twitter, Reddit, and the New York Times offer APIs. **Check out D-Lab's [Python Web APIs](https://github.com/dlab-berkeley/Python-Web-APIs) workshop if you want to learn how to use APIs.**\n", + "Para acceder a datos de la web, primero debemos asegurarnos de que el sitio web que nos interesa ofrezca una API web. Plataformas como Twitter, Reddit y el New York Times ofrecen API. **Consulta el taller de D-Lab sobre [API web de Python](https://github.com/dlab-berkeley/Python-Web-APIs) si quieres aprender a usar las API.**\n", "\n", - "However, there are often cases when a Web API does not exist. In these cases, we may have to resort to web scraping, where we extract the underlying HTML from a web page, and directly obtain the information we want. There are several packages in Python we can use to accomplish these tasks. We'll focus two packages: Requests and Beautiful Soup.\n", + "Sin embargo, a menudo no existe una API web. En estos casos, podemos recurrir al web scraping, donde extraemos el HTML subyacente de una página web y obtenemos directamente la información que buscamos. Existen varios paquetes en Python que podemos usar para realizar estas tareas. Nos centraremos en dos paquetes: Requests y Beautiful Soup.\n", "\n", - "Our case study will be scraping information on the [state senators of Illinois](http://www.ilga.gov/senate), as well as the [list of bills](http://www.ilga.gov/senate/SenatorBills.asp?MemberID=1911&GA=98&Primary=True) each senator has sponsored. Before we get started, peruse these websites to take a look at their structure." + "Nuestro estudio de caso recopilará información sobre los senadores estatales de Illinois (http://www.ilga.gov/senate), así como la lista de proyectos de ley patrocinados por cada senador. Antes de comenzar, revise estos sitios web para conocer su estructura." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Installation\n", + "## Instalación\n", "\n", - "We will use two main packages: [Requests](http://docs.python-requests.org/en/latest/user/quickstart/) and [Beautiful Soup](http://www.crummy.com/software/BeautifulSoup/bs4/doc/). Go ahead and install these packages, if you haven't already:" + "Usaremos dos paquetes principales: [Requests](http://docs.python-requests.org/en/latest/user/quickstart/) y [Beautiful Soup](http://www.crummy.com/software/BeautifulSoup/bs4/doc/). Continúe instalando estos paquetes, si aún no lo ha hecho:" ] }, { @@ -110,7 +110,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We'll also install the `lxml` package, which helps support some of the parsing that Beautiful Soup performs:" + "También instalaremos el paquete `lxml`, que ayuda a soportar parte del análisis que realiza Beautiful Soup:" ] }, { @@ -224,11 +224,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Step 2: Parse the Page with Beautiful Soup\n", + "## Paso 2: Analizar la página con Beautiful Soup\n", "\n", - "Now, we use the `BeautifulSoup` function to parse the reponse into an HTML tree. This returns an object (called a **soup object**) which contains all of the HTML in the original document.\n", + "Ahora, usamos la función `BeautifulSoup` para analizar la respuesta en un árbol HTML. Esto devuelve un objeto (llamado **objeto soup**) que contiene todo el HTML del documento original.\n", "\n", - "If you run into an error about a parser library, make sure you've installed the `lxml` package to provide Beautiful Soup with the necessary parsing tools." + "Si se produce un error relacionado con una biblioteca de análisis, asegúrese de haber instalado el paquete `lxml` para proporcionar a Beautiful Soup las herramientas de análisis necesarias." ] }, { @@ -273,26 +273,26 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The output looks pretty similar to the above, but now it's organized in a `soup` object which allows us to more easily traverse the page." + "La salida se ve bastante similar a la anterior, pero ahora está organizada en un objeto 'soup' que nos permite recorrer la página más fácilmente." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Step 3: Search for HTML Elements\n", + "## Paso 3: Buscar elementos HTML\n", "\n", - "Beautiful Soup has a number of functions to find useful components on a page. Beautiful Soup lets you find elements by their:\n", + "Beautiful Soup cuenta con varias funciones para encontrar componentes útiles en una página. Beautiful Soup permite encontrar elementos por:\n", "\n", - "1. HTML tags\n", - "2. HTML Attributes\n", - "3. CSS Selectors\n", + "1. Etiquetas HTML\n", + "2. Atributos HTML\n", + "3. Selectores CSS\n", "\n", - "Let's search first for **HTML tags**. \n", + "Primero, busquemos **etiquetas HTML**.\n", "\n", - "The function `find_all` searches the `soup` tree to find all the elements with an a particular HTML tag, and returns all of those elements.\n", + "La función `find_all` busca en el árbol `soup` todos los elementos con una etiqueta HTML específica y los devuelve.\n", "\n", - "What does the example below do?" + "¿Qué hace el siguiente ejemplo?" ] }, { @@ -338,9 +338,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Because `find_all()` is the most popular method in the Beautiful Soup search API, you can use a shortcut for it. If you treat the BeautifulSoup object as though it were a function, then it’s the same as calling `find_all()` on that object. \n", + "Dado que `find_all()` es el método más popular en la API de búsqueda de Beautiful Soup, puedes usar un atajo. Si tratas el objeto BeautifulSoup como si fuera una función, es lo mismo que llamar a `find_all()` en ese objeto.\n", "\n", - "These two lines of code are equivalent:" + "Estas dos líneas de código son equivalentes:" ] }, { @@ -374,7 +374,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "How many links did we obtain?" + "¿Cuantos enlaces obtuvimos?" ] }, { @@ -398,11 +398,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "That's a lot! Many elements on a page will have the same HTML tag. For instance, if you search for everything with the `a` tag, you're likely to get more hits, many of which you might not want. Remember, the `a` tag defines a hyperlink, so you'll usually find many on any given page.\n", + "¡Eso es muchísimo! Muchos elementos de una página tendrán la misma etiqueta HTML. Por ejemplo, si buscas todo con la etiqueta `a`, probablemente obtendrás más resultados, muchos de los cuales quizás no quieras. Recuerda que la etiqueta `a` define un hipervínculo, por lo que normalmente encontrarás muchos en cualquier página.\n", "\n", - "What if we wanted to search for HTML tags with certain attributes, such as particular CSS classes? \n", + "¿Qué sucedería si quisiéramos buscar etiquetas HTML con ciertos atributos, como clases CSS específicas?\n", "\n", - "We can do this by adding an additional argument to the `find_all`. In the example below, we are finding all the `a` tags, and then filtering those with `class_=\"sidemenu\"`." + "Podemos hacerlo añadiendo un argumento adicional a `find_all`. En el siguiente ejemplo, buscamos todas las etiquetas `a` y luego las filtramos con `class_=\"sidemenu\"`." ] }, { @@ -433,9 +433,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "A more efficient way to search for elements on a website is via a **CSS selector**. For this we have to use a different method called `select()`. Just pass a string into the `.select()` to get all elements with that string as a valid CSS selector.\n", + "Una forma más eficiente de buscar elementos en un sitio web es mediante un selector CSS. Para ello, debemos usar un método diferente llamado `select()`. Simplemente pase una cadena a `.select()` para obtener todos los elementos con esa cadena como un selector CSS válido.\n", "\n", - "In the example above, we can use `\"a.sidemenu\"` as a CSS selector, which returns all `a` tags with class `sidemenu`." + "En el ejemplo anterior, podemos usar `\"a.sidemenu\"` como selector CSS, que devuelve todas las etiquetas `a` con la clase `sidemenu`." ] }, { @@ -466,9 +466,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊 Challenge: Find All\n", + "## 🥊 Desafío: Encontrar todo\n", "\n", - "Use BeautifulSoup to find all the `a` elements with class `mainmenu`." + "Usa BeautifulSoup para encontrar todos los elementos `a` con la clase `mainmenu`." ] }, { @@ -484,14 +484,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Step 4: Get Attributes and Text of Elements\n", + "## Paso 4: Obtener los atributos y el texto de los elementos\n", "\n", - "Once we identify elements, we want the access information in that element. Usually, this means two things:\n", + "Una vez identificados los elementos, necesitamos la información de acceso de cada uno. Normalmente, esto implica dos cosas:\n", "\n", - "1. Text\n", - "2. Attributes\n", + "1. Texto\n", + "2. Atributos\n", "\n", - "Getting the text inside an element is easy. All we have to do is use the `text` member of a `tag` object:" + "Obtener el texto dentro de un elemento es sencillo. Solo tenemos que usar el miembro `text` de un objeto `tag`:" ] }, { @@ -529,7 +529,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "It's a Beautiful Soup tag! This means it has a `text` member:" + "¡Es una etiqueta de Beautiful Soup! Esto significa que tiene un miembro \"texto\":" ] }, { @@ -547,9 +547,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Sometimes we want the value of certain attributes. This is particularly relevant for `a` tags, or links, where the `href` attribute tells us where the link goes.\n", + "A veces necesitamos el valor de ciertos atributos. Esto es especialmente relevante para las etiquetas «a» o enlaces, donde el atributo «href» nos indica adónde lleva el enlace.\n", "\n", - "💡 **Tip**: You can access a tag’s attributes by treating the tag like a dictionary:" + "💡 **Consejo**: Puedes acceder a los atributos de una etiqueta tratándola como un diccionario:" ] }, { @@ -567,9 +567,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊 Challenge: Extract specific attributes\n", + "## 🥊 Desafío: Extraer atributos específicos\n", "\n", - "Extract all `href` attributes for each `mainmenu` URL." + "Extraer todos los atributos `href` de cada URL `mainmenu`." ] }, { @@ -587,22 +587,22 @@ "source": [ "\n", "\n", - "# Scraping the Illinois General Assembly\n", + "# Análisis de la Asamblea General de Illinois\n", "\n", - "Believe it or not, those are really the fundamental tools you need to scrape a website. Once you spend more time familiarizing yourself with HTML and CSS, then it's simply a matter of understanding the structure of a particular website and intelligently applying the tools of Beautiful Soup and Python.\n", + "Aunque parezca increíble, estas son las herramientas fundamentales para analizar un sitio web. Una vez que dediques más tiempo a familiarizarte con HTML y CSS, simplemente será cuestión de comprender la estructura de un sitio web específico y aplicar inteligentemente las herramientas de Beautiful Soup y Python.\n", "\n", - "Let's apply these skills to scrape the [Illinois 98th General Assembly](http://www.ilga.gov/senate/default.asp?GA=98).\n", + "Apliquemos estas habilidades para analizar la [98.ª Asamblea General de Illinois](http://www.ilga.gov/senate/default.asp?GA=98).\n", "\n", - "Specifically, our goal is to scrape information on each senator, including their name, district, and party." + "En concreto, nuestro objetivo es analizar la información de cada senador, incluyendo su nombre, distrito y partido." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Scrape and Soup the Webpage\n", + "## Rastrear y analizar la página web\n", "\n", - "Let's scrape and parse the webpage, using the tools we learned in the previous section." + "Rastreemos y analicemos la página web con las herramientas que aprendimos en la sección anterior." ] }, { @@ -625,9 +625,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Search for the Table Elements\n", + "## Buscar los elementos de la tabla\n", "\n", - "Our goal is to obtain the elements in the table on the webpage. Remember: rows are identified by the `tr` tag. Let's use `find_all` to obtain these elements." + "Nuestro objetivo es obtener los elementos de la tabla en la página web. Recuerde: las filas se identifican con la etiqueta `tr`. Usemos `find_all` para obtener estos elementos." ] }, { @@ -645,7 +645,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "⚠️ **Warning**: Keep in mind: `find_all` gets *all* the elements with the `tr` tag. We only want some of them. If we use the 'Inspect' function in Google Chrome and look carefully, then we can use some CSS selectors to get just the rows we're interested in. Specifically, we want the inner rows of the table:" + "⚠️ **Advertencia**: Ten en cuenta que `find_all` obtiene *todos* los elementos con la etiqueta `tr`. Solo necesitamos algunos. Si usamos la función \"Inspeccionar\" de Google Chrome y observamos con atención, podemos usar selectores CSS para obtener solo las filas que nos interesan. En concreto, queremos las filas internas de la tabla:" ] }, { @@ -665,7 +665,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "It looks like we want everything after the first two rows. Let's work with a single row to start, and build our loop from there." + "Parece que queremos todo lo que queda después de las dos primeras filas. Empecemos con una sola fila y construyamos nuestro bucle a partir de ahí." ] }, { @@ -682,11 +682,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Let's break this row down into its component cells/columns using the `select` method with CSS selectors. Looking closely at the HTML, there are a couple of ways we could do this.\n", + "Desglosemos esta fila en sus celdas/columnas mediante el método `select` con selectores CSS. Si analizamos el HTML con atención, hay un par de maneras de hacerlo.\n", "\n", - "* We could identify the cells by their tag `td`.\n", - "* We could use the the class name `.detail`.\n", - "* We could combine both and use the selector `td.detail`." + "* Podríamos identificar las celdas por su etiqueta `td`.\n", + "* Podríamos usar el nombre de clase `.detail`.\n", + "* Podríamos combinar ambos y usar el selector `td.detail`." ] }, { @@ -712,7 +712,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We can confirm that these are all the same." + "Podemos confirmar que todos son iguales." ] }, { @@ -730,7 +730,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Let's use the selector `td.detail` to be as specific as possible." + "Utilicemos el selector `td.detail` para ser lo más específicos posible." ] }, { @@ -748,7 +748,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Most of the time, we're interested in the actual **text** of a website, not its tags. Recall that to get the text of an HTML element, we use the `text` member:" + "La mayoría de las veces, nos interesa el **texto** real de un sitio web, no sus etiquetas. Recordemos que para obtener el texto de un elemento HTML, usamos el miembro `text`:" ] }, { @@ -767,7 +767,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Looks good! Now we just use our basic Python knowledge to get the elements of this list that we want. Remember, we want the senator's name, their district, and their party." + "¡Se ve bien! Ahora solo necesitamos usar nuestros conocimientos básicos de Python para obtener los elementos de esta lista que necesitamos. Recuerda: queremos el nombre del senador, su distrito y su partido." ] }, { @@ -785,9 +785,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Getting Rid of Junk Rows\n", + "## Eliminando filas basura\n", "\n", - "We saw at the beginning that not all of the rows we got actually correspond to a senator. We'll need to do some cleaning before we can proceed forward. Take a look at some examples:" + "Vimos al principio que no todas las filas que obtuvimos corresponden a un senador. Tendremos que hacer limpieza antes de continuar. Vean algunos ejemplos:" ] }, { @@ -805,9 +805,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "When we write our for loop, we only want it to apply to the relevant rows. So we'll need to filter out the irrelevant rows. The way to do this is to compare some of these to the rows we do want, see how they differ, and then formulate that in a conditional.\n", + "Al escribir nuestro bucle for, queremos que solo se aplique a las filas relevantes. Por lo tanto, debemos filtrar las filas irrelevantes. Para ello, comparamos algunas de estas filas con las que necesitamos, observamos sus diferencias y luego formulamos esto en una condición.\n", "\n", - "As you can imagine, there a lot of possible ways to do this, and it'll depend on the website. We'll show some here to give you an idea of how to do this." + "Como puedes imaginar, hay muchas maneras de hacerlo, y dependerá del sitio web. Aquí te mostraremos algunas para que te hagas una idea de cómo hacerlo." ] }, { @@ -829,7 +829,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Perhaps good rows have a length of 5. Let's check:" + "Quizás las buenas filas tengan una longitud de 5. Comprobémoslo:" ] }, { @@ -850,7 +850,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We found a footer row in our list that we'd like to avoid. Let's try something else:" + "Encontramos una fila de pie de página en nuestra lista que queremos evitar. Probemos algo diferente:" ] }, { @@ -886,16 +886,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Looks like we found something that worked!" + "¡Parece que encontramos algo que funcionó!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Loop it All Together\n", + "## Unir todo en un bucle\n", "\n", - "Now that we've seen how to get the data we want from one row, as well as filter out the rows we don't want, let's put it all together into a loop." + "Ahora que hemos visto cómo obtener los datos que queremos de una fila y filtrar las filas que no necesitamos, vamos a unirlo todo en un bucle." ] }, { @@ -942,7 +942,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Let's take a look at what we have in `members`." + "Echemos un vistazo a lo que tenemos en \"miembros\"." ] }, { @@ -958,37 +958,37 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊 Challenge: Get `href` elements pointing to members' bills \n", + "## 🥊 Desafío: Obtener elementos `href` que apunten a los proyectos de ley de los miembros\n", "\n", - "The code above retrieves information on: \n", + "El código anterior recupera información sobre:\n", "\n", - "- the senator's name,\n", - "- their district number,\n", - "- and their party.\n", + "- el nombre del senador,\n", + "- su número de distrito,\n", + "- y su partido.\n", "\n", - "We now want to retrieve the URL for each senator's list of bills. Each URL will follow a specific format. \n", + "Ahora queremos recuperar la URL de la lista de proyectos de ley de cada senador. Cada URL seguirá un formato específico.\n", "\n", - "The format for the list of bills for a given senator is:\n", + "El formato de la lista de proyectos de ley de un senador determinado es:\n", "\n", "`http://www.ilga.gov/senate/SenatorBills.asp?GA=98&MemberID=[MEMBER_ID]&Primary=True`\n", "\n", - "to get something like:\n", + "para obtener algo como:\n", "\n", "`http://www.ilga.gov/senate/SenatorBills.asp?MemberID=1911&GA=98&Primary=True`\n", "\n", - "in which `MEMBER_ID=1911`. \n", + "en el cual `MEMBER_ID=1911`. \n", "\n", - "You should be able to see that, unfortunately, `MEMBER_ID` is not currently something pulled out in our scraping code.\n", + "Deberías poder ver que, lamentablemente, `MEMBER_ID` no se extrae actualmente en nuestro código de extracción.\n", "\n", - "Your initial task is to modify the code above so that we also **retrieve the full URL which points to the corresponding page of primary-sponsored bills**, for each member, and return it along with their name, district, and party.\n", + "Tu tarea inicial es modificar el código anterior para que también **recuperemos la URL completa que apunta a la página correspondiente de los proyectos de ley patrocinados por las primarias**, para cada miembro, y la devolvamos junto con su nombre, distrito y partido.\n", "\n", - "Tips: \n", + "Consejos:\n", "\n", - "* To do this, you will want to get the appropriate anchor element (``) in each legislator's row of the table. You can again use the `.select()` method on the `row` object in the loop to do this — similar to the command that finds all of the `td.detail` cells in the row. Remember that we only want the link to the legislator's bills, not the committees or the legislator's profile page.\n", - "* The anchor elements' HTML will look like `Bills`. The string in the `href` attribute contains the **relative** link we are after. You can access an attribute of a BeatifulSoup `Tag` object the same way you access a Python dictionary: `anchor['attributeName']`. See the documentation for more details.\n", - "* There are a _lot_ of different ways to use BeautifulSoup to get things done. whatever you need to do to pull the `href` out is fine.\n", + "* Para ello, deberás obtener el elemento de anclaje apropiado (``) en la fila de la tabla de cada legislador. Puedes usar el método `.select()` en el objeto `row` del bucle para hacerlo, similar al comando que encuentra todas las celdas `td.detail` de la fila. Recuerda que solo queremos el enlace a los proyectos de ley del legislador, no a los comités ni a su página de perfil.\n", + "* El HTML de los elementos de anclaje se verá como `Proyectos de ley`. La cadena del atributo `href` contiene el enlace **relativo** que buscamos. Puedes acceder a un atributo de un objeto `Tag` de BeatifulSoup de la misma manera que accedes a un diccionario de Python: `anchor['attributeName']`. Consulta la documentación para más detalles.\n", + "* Hay muchas maneras diferentes de usar BeautifulSoup. Puedes hacer lo que necesites para extraer el `href`.\n", "\n", - "The code has been partially filled out for you. Fill it in where it says `#YOUR CODE HERE`. Save the path into an object called `full_path`." + "El código se ha completado parcialmente. Complétalo donde dice `#TU CÓDIGO AQUÍ`. Guarda la ruta en un objeto llamado `full_path`." ] }, { @@ -1049,9 +1049,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊 Challenge: Modularize Your Code\n", + "## 🥊 Desafío: Modulariza tu código\n", "\n", - "Turn the code above into a function that accepts a URL, scrapes the URL for its senators, and returns a list of tuples containing information about each senator. " + "Convierte el código anterior en una función que acepte una URL, rastree la URL para encontrar sus senadores y devuelva una lista de tuplas con información sobre cada senador." ] }, { @@ -1085,21 +1085,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊 Take-home Challenge: Writing a Scraper Function\n", + "## 🥊Desafío práctico: Escribir una función de scraping\n", "\n", - "We want to scrape the webpages corresponding to bills sponsored by each bills.\n", + "Queremos scraping las páginas web correspondientes a los proyectos de ley patrocinados por cada proyecto de ley.\n", "\n", - "Write a function called `get_bills(url)` to parse a given bills URL. This will involve:\n", + "Escribir una función llamada `get_bills(url)` para analizar la URL de un proyecto de ley. Esto implica:\n", "\n", - " - requesting the URL using the `requests` library\n", - " - using the features of the `BeautifulSoup` library to find all of the `` elements with the class `billlist`\n", - " - return a _list_ of tuples, each with:\n", - " - description (2nd column)\n", - " - chamber (S or H) (3rd column)\n", - " - the last action (4th column)\n", - " - the last action date (5th column)\n", - " \n", - "This function has been partially completed. Fill in the rest." + "- Solicitar la URL mediante la biblioteca `requests`\n", + "- Usar las funciones de la biblioteca `BeautifulSoup` para encontrar todos los elementos `` con la clase `billlist`\n", + "- Devolver una _lista_ de tuplas, cada una con:\n", + "- Descripción (2.ª columna)\n", + "- Cámara (S o H) (3.ª columna)\n", + "- La última acción (4.ª columna)\n", + "- La fecha de la última acción (5.ª columna)\n", + "\n", + "Esta función se ha completado parcialmente. Complete el resto." ] }, { @@ -1117,11 +1117,11 @@ " bills = []\n", " for row in rows:\n", " # YOUR CODE HERE\n", - " bill_id =\n", - " description =\n", - " chamber =\n", - " last_action =\n", - " last_action_date =\n", + " # bill_id =\n", + " #description =\n", + " #chamber =\n", + " #last_action =\n", + " #last_action_date =\n", " bill = (bill_id, description, chamber, last_action, last_action_date)\n", " bills.append(bill)\n", " return bills" @@ -1144,11 +1144,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Scrape All Bills\n", + "### Extraer todos los proyectos de ley\n", "\n", - "Finally, create a dictionary `bills_dict` which maps a district number (the key) onto a list of bills (the value) coming from that district. You can do this by looping over all of the senate members in `members_dict` and calling `get_bills()` for each of their associated bill URLs.\n", + "Finalmente, cree un diccionario `bills_dict` que asigne un número de distrito (la clave) a una lista de proyectos de ley (el valor) provenientes de ese distrito. Puede hacerlo recorriendo en bucle todos los miembros del senado en `members_dict` y llamando a `get_bills()` para cada una de las URL de sus proyectos de ley asociados.\n", "\n", - "**NOTE:** please call the function `time.sleep(1)` for each iteration of the loop, so that we don't destroy the state's web site." + "**NOTA:** Por favor, llame a la función `time.sleep(1)` en cada iteración del bucle para no destruir el sitio web del estado." ] }, { From 57015409e0d6d78ca088ac783b8cd033e4be05f6 Mon Sep 17 00:00:00 2001 From: rebe1603 Date: Tue, 26 Aug 2025 10:59:06 -0500 Subject: [PATCH 19/21] Arreglado notebook corrupto por conflictos --- lessons/02_web_scraping.ipynb | 86 ----------------------------------- 1 file changed, 86 deletions(-) diff --git a/lessons/02_web_scraping.ipynb b/lessons/02_web_scraping.ipynb index 2102e07..696e0b0 100644 --- a/lessons/02_web_scraping.ipynb +++ b/lessons/02_web_scraping.ipynb @@ -8,15 +8,6 @@ "\n", "* * *\n", "\n", - "### Iconos utilizados en este notebook\n", - "🔔 **Preguntas**: Una pregunta rápida para ayudarte a entender qué está pasando.
\n", - "🥊 **Desafío**: Ejercicio interactivo. Lo trabajaremos en el taller.!
\n", - "⚠️ **Advertencia**: Aviso sobre cuestiones complicadas o errores comunes.
\n", - "💡 **Tip**:Cómo hacer algo de forma un poco más eficiente o efectiva.
\n", - "🎬 **Demo**: Mostrando algo más avanzado: ¡para que sepas para qué se puede usar Python!
\n", - "\n", - "### Objetivos de aprendizaje\n", - "1. [Objetivos de aprendizaje](#when)\n", "### Íconos usados ​​en este cuaderno\n", "🔔 **Pregunta**: Una pregunta rápida para ayudarte a entender qué está pasando.
\n", "🥊 **Desafío**: Ejercicio interactivo. ¡Lo resolveremos en el taller!
\n", @@ -36,13 +27,6 @@ "source": [ "\n", "\n", - "# “¿Hacer scraping o no hacerlo?”\n", - "\n", - "Cuando queremos acceder a datos de la web, primero debemos asegurarnos de que el sitio web que nos interesa ofrezca una API web. Plataformas como Twitter, Reddit y The New York Times ofrecen API. **Echa un vistazo a D-Lab [Python Web APIs](https://github.com/dlab-berkeley/Python-Web-APIs) Taller si quieres aprender a utilizar las API.**\n", - "\n", - "Sin embargo, a menudo no existe una API web. En estos casos, podemos recurrir al web scraping, donde extraemos el HTML subyacente de una página web y obtenemos directamente la información deseada. Existen varios paquetes en Python que podemos usar para realizar estas tareas. Nos centraremos en dos paquetes: Requests y Beautiful Soup.\n", - "\n", - "Nuestro estudio de caso consistirá en extraer información sobre el [Senadores estatales de Illinois](http://www.ilga.gov/senate), así como el [lista de facturas](http://www.ilga.gov/senate/SenatorBills.asp?MemberID=1911&GA=98&Primary=True) Cada senador ha patrocinado. Antes de empezar, revise estos sitios web para conocer su estructura." "# Scraping o no scraping\n", "\n", "Para acceder a datos de la web, primero debemos asegurarnos de que el sitio web que nos interesa ofrezca una API web. Plataformas como Twitter, Reddit y el New York Times ofrecen API. **Consulta el taller de D-Lab sobre [API web de Python](https://github.com/dlab-berkeley/Python-Web-APIs) si quieres aprender a usar las API.**\n", @@ -50,7 +34,6 @@ "Sin embargo, a menudo no existe una API web. En estos casos, podemos recurrir al web scraping, donde extraemos el HTML subyacente de una página web y obtenemos directamente la información que buscamos. Existen varios paquetes en Python que podemos usar para realizar estas tareas. Nos centraremos en dos paquetes: Requests y Beautiful Soup.\n", "\n", "Nuestro estudio de caso recopilará información sobre los senadores estatales de Illinois (http://www.ilga.gov/senate), así como la lista de proyectos de ley patrocinados por cada senador. Antes de comenzar, revise estos sitios web para conocer su estructura." - ] }, { @@ -59,11 +42,7 @@ "source": [ "## Instalación\n", "\n", - - "Utilizaremos dos paquetes principales: [Solicitudes](http://docs.python-requests.org/en/latest/user/quickstart/) y [Beautiful Soup](http://www.crummy.com/software/BeautifulSoup/bs4/doc/). Continúe e instale estos paquetes, si aún no lo ha hecho:" - "Usaremos dos paquetes principales: [Requests](http://docs.python-requests.org/en/latest/user/quickstart/) y [Beautiful Soup](http://www.crummy.com/software/BeautifulSoup/bs4/doc/). Continúe instalando estos paquetes, si aún no lo ha hecho:" - ] }, { @@ -177,11 +156,6 @@ "\n", "# Extracción y análisis de HTML\n", "\n", - "Para extraer y analizar HTML correctamente, seguiremos los siguientes 4 pasos:\n", - "1. Realizar una solicitud GET\n", - "2. Analizar la página con Beautiful Soup\n", - "3. Buscar elementos HTML\n", - "4. Obtener los atributos y el texto de estos elementos" "Para extraer y analizar correctamente HTML, seguiremos los siguientes 4 pasos:\n", "1. Realizar una solicitud GET\n", "2. Analizar la página con Beautiful Soup\n", @@ -193,15 +167,6 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Paso 1: Realizar una solicitud GET para obtener el HTML de una página\n", - "\n", - "Podemos usar la biblioteca Requests para:\n", - "\n", - "1. Realizar una solicitud GET a la página y\n", - "2. Leer el código HTML de la página web.\n", - "\n", - "El proceso de realizar una solicitud y obtener un resultado es similar al del flujo de trabajo de la API web. Sin embargo, ahora realizamos una solicitud directamente al sitio web y tendremos que analizar el HTML nosotros mismos. Esto contrasta con recibir datos organizados en una salida JSON o XML más sencilla." -======= "## Paso 1: Realiza una solicitud GET para obtener el HTML de una página\n", "\n", "Podemos usar la librería Requests para:\n", @@ -409,11 +374,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - - "¿Cuántos enlaces obtuvimos?" - "¿Cuantos enlaces obtuvimos?" - ] }, { @@ -505,11 +466,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - - "## 🥊Desafío: Encontrar todo\n", - "## 🥊 Desafío: Encontrar todo\n", - "\n", "Usa BeautifulSoup para encontrar todos los elementos `a` con la clase `mainmenu`." ] @@ -527,11 +484,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - - "Paso 4: Obtener los atributos y el texto de los elementos\n", - "## Paso 4: Obtener los atributos y el texto de los elementos\n", - "\n", "Una vez identificados los elementos, necesitamos la información de acceso de cada uno. Normalmente, esto implica dos cosas:\n", "\n", @@ -1023,19 +976,6 @@ "\n", "`http://www.ilga.gov/senate/SenatorBills.asp?MemberID=1911&GA=98&Primary=True`\n", "\n", - - "donde `MEMBER_ID=1911`.\n", - "\n", - "Deberías poder ver que, lamentablemente, `MEMBER_ID` no se extrae actualmente en nuestro código de extracción.\n", - "\n", - "Tu tarea inicial es modificar el código anterior para que también **recuperemos la URL completa que apunta a la página correspondiente de los proyectos de ley patrocinados por las primarias** de cada miembro, y la devolvamos junto con su nombre, distrito y partido.\n", - "\n", - "Consejos:\n", - "\n", - "* Para ello, deberá obtener el elemento de anclaje correspondiente (``) en la fila de cada legislador de la tabla. Puede usar el método `.select()` en el objeto `row` del bucle para hacerlo, de forma similar al comando que busca todas las celdas `td.detail` de la fila. Recuerde que solo necesitamos el enlace a los proyectos de ley del legislador, no a los comités ni a su página de perfil.\n", - "* El HTML de los elementos de anclaje se verá como `Proyectos de ley`. La cadena del atributo `href` contiene el enlace **relativo** que buscamos. Puede acceder a un atributo de un objeto `Tag` de BeatifulSoup de la misma manera que accede a un diccionario de Python: `anchor['attributeName']`. Consulta la documentación para obtener más detalles.\n", - "* Hay muchas maneras diferentes de usar BeautifulSoup. Puedes usar cualquier método para extraer el `href`.\n", - "en el cual `MEMBER_ID=1911`. \n", "\n", "Deberías poder ver que, lamentablemente, `MEMBER_ID` no se extrae actualmente en nuestro código de extracción.\n", @@ -1047,7 +987,6 @@ "* Para ello, deberás obtener el elemento de anclaje apropiado (``) en la fila de la tabla de cada legislador. Puedes usar el método `.select()` en el objeto `row` del bucle para hacerlo, similar al comando que encuentra todas las celdas `td.detail` de la fila. Recuerda que solo queremos el enlace a los proyectos de ley del legislador, no a los comités ni a su página de perfil.\n", "* El HTML de los elementos de anclaje se verá como `Proyectos de ley`. La cadena del atributo `href` contiene el enlace **relativo** que buscamos. Puedes acceder a un atributo de un objeto `Tag` de BeatifulSoup de la misma manera que accedes a un diccionario de Python: `anchor['attributeName']`. Consulta la documentación para más detalles.\n", "* Hay muchas maneras diferentes de usar BeautifulSoup. Puedes hacer lo que necesites para extraer el `href`.\n", - "\n", "El código se ha completado parcialmente. Complétalo donde dice `#TU CÓDIGO AQUÍ`. Guarda la ruta en un objeto llamado `full_path`." ] @@ -1112,11 +1051,7 @@ "source": [ "## 🥊 Desafío: Modulariza tu código\n", "\n", - - "Convierte el código anterior en una función que acepte una URL, rastree la URL para encontrar sus senadores y devuelva una lista de tuplas con información sobre cada senador. " - "Convierte el código anterior en una función que acepte una URL, rastree la URL para encontrar sus senadores y devuelva una lista de tuplas con información sobre cada senador." - ] }, { @@ -1150,22 +1085,6 @@ "cell_type": "markdown", "metadata": {}, "source": [ - - "## 🥊 Desafío práctico: Escribir una función de scraping\n", - "\n", - "Queremos scraping las páginas web correspondientes a los proyectos de ley patrocinados por cada proyecto de ley.\n", - "\n", - "Escribir una función llamada `get_bills(url)` para analizar la URL de un proyecto de ley. Esto implica:\n", - "\n", - "- Solicitar la URL mediante la biblioteca `requests`\n", - "- Usar las funciones de la biblioteca `BeautifulSoup` para encontrar todos los elementos `` con la clase `billlist`\n", - "- Devolver una _lista_ de tuplas, cada una con:\n", - "- Descripción (2.ª columna)\n", - "- Cámara (S o H) (3.ª columna)\n", - "- La última acción (4.ª columna)\n", - "- La fecha de la última acción (5.ª columna)\n", - "\n", - "## 🥊Desafío práctico: Escribir una función de scraping\n", "\n", "Queremos scraping las páginas web correspondientes a los proyectos de ley patrocinados por cada proyecto de ley.\n", @@ -1180,7 +1099,6 @@ "- La última acción (4.ª columna)\n", "- La fecha de la última acción (5.ª columna)\n", "\n", - "Esta función se ha completado parcialmente. Complete el resto." ] }, @@ -1199,11 +1117,7 @@ " bills = []\n", " for row in rows:\n", " # YOUR CODE HERE\n", - - " #bill_id =\n", - " # bill_id =\n", - " #description =\n", " #chamber =\n", " #last_action =\n", From 57db881c741ae37b7c96bbf182e916a66eee77eb Mon Sep 17 00:00:00 2001 From: julizzazeime456-afk Date: Tue, 26 Aug 2025 12:30:53 -0500 Subject: [PATCH 20/21] realizado el desafio de la parte 2 --- lessons/02_web_scraping.ipynb | 108 ++++++++++++++++++++-------------- 1 file changed, 64 insertions(+), 44 deletions(-) diff --git a/lessons/02_web_scraping.ipynb b/lessons/02_web_scraping.ipynb index acd5906..ea54e9c 100644 --- a/lessons/02_web_scraping.ipynb +++ b/lessons/02_web_scraping.ipynb @@ -135,7 +135,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 2, "metadata": { "tags": [] }, @@ -180,7 +180,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 3, "metadata": { "tags": [] }, @@ -224,16 +224,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Step 2: Parse the Page with Beautiful Soup\n", + "## Paso 2: Analiza la Página con Beautiful Soup\n", "\n", - "Now, we use the `BeautifulSoup` function to parse the reponse into an HTML tree. This returns an object (called a **soup object**) which contains all of the HTML in the original document.\n", + "Ahora, utilizamos la función BeautifulSoup para analizar la respuesta y convertirla en un árbol HTML. Esto nos devuelve un objeto (llamado objeto soup) que contiene todo el HTML del documento original.\n", "\n", - "If you run into an error about a parser library, make sure you've installed the `lxml` package to provide Beautiful Soup with the necessary parsing tools." + "Si te aparece un error relacionado con una biblioteca de análisis, asegúrate de haber instalado el paquete lxml para que Beautiful Soup cuente con las herramientas necesarias para analizar el contenido." ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 34, "metadata": {}, "outputs": [ { @@ -263,9 +263,9 @@ } ], "source": [ - "# Parse the response into an HTML tree\n", + "# Analiza la respuesta y conviértela en un árbol HTML.\n", "soup = BeautifulSoup(src, 'lxml')\n", - "# Take a look\n", + "# Echa un vistazo.\n", "print(soup.prettify()[:1000])" ] }, @@ -273,31 +273,31 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The output looks pretty similar to the above, but now it's organized in a `soup` object which allows us to more easily traverse the page." + "La salida se ve bastante similar a la anterior, pero ahora está organizada en un objeto soup, lo que nos permite recorrer la página de manera más sencilla." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Step 3: Search for HTML Elements\n", + "## Paso 3: Buscar Elementos HTML\n", "\n", - "Beautiful Soup has a number of functions to find useful components on a page. Beautiful Soup lets you find elements by their:\n", + "Beautiful Soup tiene varias funciones para encontrar componentes útiles en una página. Beautiful Soup te permite buscar elementos según sus:\n", "\n", - "1. HTML tags\n", - "2. HTML Attributes\n", - "3. CSS Selectors\n", + "1. Etiquetas HTML\n", + "2. Atributos HTML\n", + "3. Selectores CSS\n", "\n", - "Let's search first for **HTML tags**. \n", + "Primero, busquemos etiquetas HTML.\n", "\n", - "The function `find_all` searches the `soup` tree to find all the elements with an a particular HTML tag, and returns all of those elements.\n", + "La función find_all busca en el árbol soup todos los elementos que tengan una determinada etiqueta HTML y devuelve todos esos elementos.\n", "\n", - "What does the example below do?" + "¿Qué hace el siguiente ejemplo?" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 27, "metadata": {}, "outputs": [ { @@ -329,7 +329,7 @@ } ], "source": [ - "# Find all elements with a certain tag\n", + "# Buscar todos los elementos con una determinada etiqueta\n", "a_tags = soup.find_all(\"a\")\n", "print(a_tags[:10])" ] @@ -338,14 +338,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Because `find_all()` is the most popular method in the Beautiful Soup search API, you can use a shortcut for it. If you treat the BeautifulSoup object as though it were a function, then it’s the same as calling `find_all()` on that object. \n", + "Como find_all() es el método más popular en la API de búsqueda de Beautiful Soup, puedes usar un atajo para llamarlo. Si tratas el objeto BeautifulSoup como si fuera una función, es lo mismo que llamar a find_all() sobre ese objeto.\n", "\n", - "These two lines of code are equivalent:" + "Estas dos líneas de código son equivalentes:" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 28, "metadata": { "tags": [] }, @@ -374,12 +374,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "How many links did we obtain?" + "¿Cuántos enlaces obtuvimos?" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 29, "metadata": {}, "outputs": [ { @@ -398,16 +398,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "That's a lot! Many elements on a page will have the same HTML tag. For instance, if you search for everything with the `a` tag, you're likely to get more hits, many of which you might not want. Remember, the `a` tag defines a hyperlink, so you'll usually find many on any given page.\n", + "¡Eso es bastante! Muchos elementos en una página tendrán la misma etiqueta HTML. Por ejemplo, si buscas todo lo que tenga la etiqueta a, probablemente obtendrás muchos resultados, muchos de los cuales quizás no te interesen. Recuerda que la etiqueta a define un hipervínculo, por lo que normalmente encontrarás muchos en cualquier página.\n", "\n", - "What if we wanted to search for HTML tags with certain attributes, such as particular CSS classes? \n", + "¿Qué pasa si queremos buscar etiquetas HTML con ciertos atributos, como clases CSS específicas?\n", "\n", - "We can do this by adding an additional argument to the `find_all`. In the example below, we are finding all the `a` tags, and then filtering those with `class_=\"sidemenu\"`." + "Podemos hacerlo agregando un argumento adicional a find_all. En el siguiente ejemplo, estamos buscando todas las etiquetas a y luego filtrando aquellas que tengan class_=\"sidemenu\"." ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "metadata": { "tags": [] }, @@ -418,13 +418,13 @@ "[]" ] }, - "execution_count": 29, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Get only the 'a' tags in 'sidemenu' class\n", + "# Obtener solo las etiquetas 'a' que tienen la clase 'sidemenu'\n", "side_menus = soup(\"a\", class_=\"sidemenu\")\n", "side_menus[:5]" ] @@ -433,14 +433,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "A more efficient way to search for elements on a website is via a **CSS selector**. For this we have to use a different method called `select()`. Just pass a string into the `.select()` to get all elements with that string as a valid CSS selector.\n", + "Una forma más eficiente de buscar elementos en un sitio web es mediante un selector CSS. Para esto, debemos usar un método diferente llamado `select()`. Solo tienes que pasar una cadena al método `.select()` para obtener todos los elementos que coincidan con ese selector CSS.\n", "\n", - "In the example above, we can use `\"a.sidemenu\"` as a CSS selector, which returns all `a` tags with class `sidemenu`." + "En el ejemplo anterior, podemos usar `a.sidemenu` como selector CSS, lo que nos devuelve todas las etiquetas `a` con la clase `sidemenu`." ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "metadata": { "tags": [] }, @@ -451,13 +451,13 @@ "[]" ] }, - "execution_count": 30, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Get elements with \"a.sidemenu\" CSS Selector.\n", + "# Obtener elementos con el selector CSS \"a.sidemenu\".\n", "selected = soup.select(\"a.sidemenu\")\n", "selected[:5]" ] @@ -466,18 +466,38 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊 Challenge: Find All\n", + "## 🥊Desafío: Buscar Todos\n", "\n", - "Use BeautifulSoup to find all the `a` elements with class `mainmenu`." + "Usa BeautifulSoup para encontrar todos los elementos `a` con la clase `mainmenu`. Le cambiee a dropdown-item para que se vea los resultados " ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 43, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[\n", + " English\n", + " , \n", + " Afrikaans\n", + " , \n", + " Albanian\n", + " , \n", + " Arabic\n", + " , \n", + " Armenian\n", + " ]\n" + ] + } + ], "source": [ - "# YOUR CODE HERE\n" + "### TRABAJO PRACTICO \n", + "enlaces = soup.find_all(\"a\", class_=\"dropdown-item\")\n", + "print(enlaces[:5]) #lo puse hasta 5 para que no se vea tan largo el resultado" ] }, { @@ -496,7 +516,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 42, "metadata": { "tags": [] }, @@ -508,7 +528,7 @@ "traceback": [ "\u001b[31m---------------------------------------------------------------------------\u001b[39m", "\u001b[31mIndexError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[32]\u001b[39m\u001b[32m, line 5\u001b[39m\n\u001b[32m 2\u001b[39m side_menu_links = soup.select(\u001b[33m\"\u001b[39m\u001b[33ma.sidemenu\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 4\u001b[39m \u001b[38;5;66;03m# Examine the first link\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m5\u001b[39m first_link = \u001b[43mside_menu_links\u001b[49m\u001b[43m[\u001b[49m\u001b[32;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[32m 6\u001b[39m \u001b[38;5;28mprint\u001b[39m(first_link)\n\u001b[32m 8\u001b[39m \u001b[38;5;66;03m# What class is this variable?\u001b[39;00m\n", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[42]\u001b[39m\u001b[32m, line 5\u001b[39m\n\u001b[32m 2\u001b[39m side_menu_links = soup.select(\u001b[33m\"\u001b[39m\u001b[33ma.sidemenu\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 4\u001b[39m \u001b[38;5;66;03m# Examine the first link\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m5\u001b[39m first_link = \u001b[43mside_menu_links\u001b[49m\u001b[43m[\u001b[49m\u001b[32;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[32m 6\u001b[39m \u001b[38;5;28mprint\u001b[39m(first_link)\n\u001b[32m 8\u001b[39m \u001b[38;5;66;03m# What class is this variable?\u001b[39;00m\n", "\u001b[31mIndexError\u001b[39m: list index out of range" ] } @@ -1178,7 +1198,7 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": ".venv312", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -1192,7 +1212,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.10" + "version": "3.13.6" } }, "nbformat": 4, From 2d902865acde3faa9b7fb2816b53d04bf13361fd Mon Sep 17 00:00:00 2001 From: julizzazeime456-afk Date: Tue, 26 Aug 2025 17:50:50 -0500 Subject: [PATCH 21/21] Jenny: analisis de la asamblea general de illinois --- lessons/02_web_scraping.ipynb | 1860 ++++++++++++++++++++++++++++----- 1 file changed, 1613 insertions(+), 247 deletions(-) diff --git a/lessons/02_web_scraping.ipynb b/lessons/02_web_scraping.ipynb index c8b2413..525cc44 100644 --- a/lessons/02_web_scraping.ipynb +++ b/lessons/02_web_scraping.ipynb @@ -4,21 +4,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Web Scraping con Beautiful Soup\n", + "# Web Scraping with Beautiful Soup\n", "\n", - "* * *\n", + "* * * \n", "\n", - "### Íconos usados ​​en este cuaderno\n", - "🔔 **Pregunta**: Una pregunta rápida para ayudarte a entender qué está pasando.
\n", - "🥊 **Desafío**: Ejercicio interactivo. ¡Lo resolveremos en el taller!
\n", - "⚠️ **Advertencia**: Atención sobre aspectos complicados o errores comunes.
\n", - "💡 **Consejo**: Cómo hacer algo de forma más eficiente o efectiva.
\n", - "🎬 **Demostración**: ¡Mostrando algo más avanzado para que sepas para qué se puede usar Python!
\n", + "### Icons used in this notebook\n", + "🔔 **Question**: A quick question to help you understand what's going on.
\n", + "🥊 **Challenge**: Interactive exercise. We'll work through these in the workshop!
\n", + "⚠️ **Warning**: Heads-up about tricky stuff or common mistakes.
\n", + "💡 **Tip**: How to do something a bit more efficiently or effectively.
\n", + "🎬 **Demo**: Showing off something more advanced – so you know what Python can be used for!
\n", "\n", - "### Objetivos de aprendizaje\n", - "1. [Reflexión: Escapar o no raspar](#when)\n", - "2. [Extracción y análisis de HTML](#extract)\n", - "3. [Desmantelando la Asamblea General de Illinois](#scrape)" + "### Learning Objectives\n", + "1. [Reflection: To Scape Or Not To Scrape](#when)\n", + "2. [Extracting and Parsing HTML](#extract)\n", + "3. [Scraping the Illinois General Assembly](#scrape)" ] }, { @@ -27,27 +27,27 @@ "source": [ "\n", "\n", - "# Scraping o no scraping\n", + "# To Scrape Or Not To Scrape\n", "\n", - "Para acceder a datos de la web, primero debemos asegurarnos de que el sitio web que nos interesa ofrezca una API web. Plataformas como Twitter, Reddit y el New York Times ofrecen API. **Consulta el taller de D-Lab sobre [API web de Python](https://github.com/dlab-berkeley/Python-Web-APIs) si quieres aprender a usar las API.**\n", + "When we'd like to access data from the web, we first have to make sure if the website we are interested in offers a Web API. Platforms like Twitter, Reddit, and the New York Times offer APIs. **Check out D-Lab's [Python Web APIs](https://github.com/dlab-berkeley/Python-Web-APIs) workshop if you want to learn how to use APIs.**\n", "\n", - "Sin embargo, a menudo no existe una API web. En estos casos, podemos recurrir al web scraping, donde extraemos el HTML subyacente de una página web y obtenemos directamente la información que buscamos. Existen varios paquetes en Python que podemos usar para realizar estas tareas. Nos centraremos en dos paquetes: Requests y Beautiful Soup.\n", + "However, there are often cases when a Web API does not exist. In these cases, we may have to resort to web scraping, where we extract the underlying HTML from a web page, and directly obtain the information we want. There are several packages in Python we can use to accomplish these tasks. We'll focus two packages: Requests and Beautiful Soup.\n", "\n", - "Nuestro estudio de caso recopilará información sobre los senadores estatales de Illinois (http://www.ilga.gov/senate), así como la lista de proyectos de ley patrocinados por cada senador. Antes de comenzar, revise estos sitios web para conocer su estructura." + "Our case study will be scraping information on the [state senators of Illinois](http://www.ilga.gov/senate), as well as the [list of bills](http://www.ilga.gov/senate/SenatorBills.asp?MemberID=1911&GA=98&Primary=True) each senator has sponsored. Before we get started, peruse these websites to take a look at their structure." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Instalación\n", + "## Installation\n", "\n", - "Usaremos dos paquetes principales: [Requests](http://docs.python-requests.org/en/latest/user/quickstart/) y [Beautiful Soup](http://www.crummy.com/software/BeautifulSoup/bs4/doc/). Continúe instalando estos paquetes, si aún no lo ha hecho:" + "We will use two main packages: [Requests](http://docs.python-requests.org/en/latest/user/quickstart/) and [Beautiful Soup](http://www.crummy.com/software/BeautifulSoup/bs4/doc/). Go ahead and install these packages, if you haven't already:" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 140, "metadata": {}, "outputs": [ { @@ -71,31 +71,16 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 141, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Collecting beautifulsoup4\n", - " Downloading beautifulsoup4-4.13.4-py3-none-any.whl.metadata (3.8 kB)\n", - "Collecting soupsieve>1.2 (from beautifulsoup4)\n", - " Downloading soupsieve-2.7-py3-none-any.whl.metadata (4.6 kB)\n", - "Collecting typing-extensions>=4.0.0 (from beautifulsoup4)\n", - " Downloading typing_extensions-4.14.1-py3-none-any.whl.metadata (3.0 kB)\n", - "Downloading beautifulsoup4-4.13.4-py3-none-any.whl (187 kB)\n", - "Downloading soupsieve-2.7-py3-none-any.whl (36 kB)\n", - "Downloading typing_extensions-4.14.1-py3-none-any.whl (43 kB)\n", - "Installing collected packages: typing-extensions, soupsieve, beautifulsoup4\n", - "\n", - " ------------- -------------------------- 1/3 [soupsieve]\n", - " -------------------------- ------------- 2/3 [beautifulsoup4]\n", - " -------------------------- ------------- 2/3 [beautifulsoup4]\n", - " -------------------------- ------------- 2/3 [beautifulsoup4]\n", - " ---------------------------------------- 3/3 [beautifulsoup4]\n", - "\n", - "Successfully installed beautifulsoup4-4.13.4 soupsieve-2.7 typing-extensions-4.14.1\n", + "Requirement already satisfied: beautifulsoup4 in c:\\users\\jjala\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (4.13.4)\n", + "Requirement already satisfied: soupsieve>1.2 in c:\\users\\jjala\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from beautifulsoup4) (2.7)\n", + "Requirement already satisfied: typing-extensions>=4.0.0 in c:\\users\\jjala\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from beautifulsoup4) (4.14.1)\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } @@ -110,19 +95,19 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "También instalaremos el paquete `lxml`, que ayuda a soportar parte del análisis que realiza Beautiful Soup:" + "We'll also install the `lxml` package, which helps support some of the parsing that Beautiful Soup performs:" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 142, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Requirement already satisfied: lxml in c:\\users\\fmerino\\documents\\github\\python-web-scraping\\.venv312\\lib\\site-packages (6.0.1)\n", + "Requirement already satisfied: lxml in c:\\users\\jjala\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (6.0.1)\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } @@ -135,7 +120,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 143, "metadata": { "tags": [] }, @@ -180,7 +165,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 144, "metadata": { "tags": [] }, @@ -224,24 +209,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Paso 2: Analiza la Página con Beautiful Soup\n", "\n", "Ahora, utilizamos la función BeautifulSoup para analizar la respuesta y convertirla en un árbol HTML. Esto nos devuelve un objeto (llamado objeto soup) que contiene todo el HTML del documento original.\n", "\n", "Si te aparece un error relacionado con una biblioteca de análisis, asegúrate de haber instalado el paquete lxml para que Beautiful Soup cuente con las herramientas necesarias para analizar el contenido." - - "## Paso 2: Analizar la página con Beautiful Soup\n", - "\n", - "Ahora, usamos la función `BeautifulSoup` para analizar la respuesta en un árbol HTML. Esto devuelve un objeto (llamado **objeto soup**) que contiene todo el HTML del documento original.\n", - "\n", - "Si se produce un error relacionado con una biblioteca de análisis, asegúrese de haber instalado el paquete `lxml` para proporcionar a Beautiful Soup las herramientas de análisis necesarias." - ] }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 145, "metadata": {}, "outputs": [ { @@ -281,47 +258,31 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "La salida se ve bastante similar a la anterior, pero ahora está organizada en un objeto soup, lo que nos permite recorrer la página de manera más sencilla." - - "La salida se ve bastante similar a la anterior, pero ahora está organizada en un objeto 'soup' que nos permite recorrer la página más fácilmente." - ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Paso 3: Buscar Elementos HTML\n", "\n", "Beautiful Soup tiene varias funciones para encontrar componentes útiles en una página. Beautiful Soup te permite buscar elementos según sus:\n", - - "## Paso 3: Buscar elementos HTML\n", - "\n", - "Beautiful Soup cuenta con varias funciones para encontrar componentes útiles en una página. Beautiful Soup permite encontrar elementos por:\n", - "\n", "1. Etiquetas HTML\n", "2. Atributos HTML\n", "3. Selectores CSS\n", "\n", - "Primero, busquemos etiquetas HTML.\n", "\n", "La función find_all busca en el árbol soup todos los elementos que tengan una determinada etiqueta HTML y devuelve todos esos elementos.\n", - - "Primero, busquemos **etiquetas HTML**.\n", - "\n", - "La función `find_all` busca en el árbol `soup` todos los elementos con una etiqueta HTML específica y los devuelve.\n", - "\n", "¿Qué hace el siguiente ejemplo?" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 146, "metadata": {}, "outputs": [ { @@ -362,18 +323,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Como find_all() es el método más popular en la API de búsqueda de Beautiful Soup, puedes usar un atajo para llamarlo. Si tratas el objeto BeautifulSoup como si fuera una función, es lo mismo que llamar a find_all() sobre ese objeto.\n", - - "Dado que `find_all()` es el método más popular en la API de búsqueda de Beautiful Soup, puedes usar un atajo. Si tratas el objeto BeautifulSoup como si fuera una función, es lo mismo que llamar a `find_all()` en ese objeto.\n", - "\n", "Estas dos líneas de código son equivalentes:" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 147, "metadata": { "tags": [] }, @@ -402,16 +359,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "¿Cuántos enlaces obtuvimos?" - - "¿Cuantos enlaces obtuvimos?" - ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 148, "metadata": {}, "outputs": [ { @@ -430,61 +383,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "¡Eso es bastante! Muchos elementos en una página tendrán la misma etiqueta HTML. Por ejemplo, si buscas todo lo que tenga la etiqueta a, probablemente obtendrás muchos resultados, muchos de los cuales quizás no te interesen. Recuerda que la etiqueta a define un hipervínculo, por lo que normalmente encontrarás muchos en cualquier página.\n", "\n", "¿Qué pasa si queremos buscar etiquetas HTML con ciertos atributos, como clases CSS específicas?\n", "\n", "Podemos hacerlo agregando un argumento adicional a find_all. En el siguiente ejemplo, estamos buscando todas las etiquetas a y luego filtrando aquellas que tengan class_=\"sidemenu\"." - - "¡Eso es muchísimo! Muchos elementos de una página tendrán la misma etiqueta HTML. Por ejemplo, si buscas todo con la etiqueta `a`, probablemente obtendrás más resultados, muchos de los cuales quizás no quieras. Recuerda que la etiqueta `a` define un hipervínculo, por lo que normalmente encontrarás muchos en cualquier página.\n", - "\n", - "¿Qué sucedería si quisiéramos buscar etiquetas HTML con ciertos atributos, como clases CSS específicas?\n", - "\n", - "Podemos hacerlo añadiendo un argumento adicional a `find_all`. En el siguiente ejemplo, buscamos todas las etiquetas `a` y luego las filtramos con `class_=\"sidemenu\"`." - - ] - }, - { - "cell_type": "code", - - "execution_count": null, - - "execution_count": 29, - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Get only the 'a' tags in 'sidemenu' class\n", - "side_menus = soup(\"a\", class_=\"sidemenu\")\n", - "side_menus[:5]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Una forma más eficiente de buscar elementos en un sitio web es mediante un selector CSS. Para ello, debemos usar un método diferente llamado `select()`. Simplemente pase una cadena a `.select()` para obtener todos los elementos con esa cadena como un selector CSS válido.\n", - "\n", - "En el ejemplo anterior, podemos usar `\"a.sidemenu\"` como selector CSS, que devuelve todas las etiquetas `a` con la clase `sidemenu`." ] }, { "cell_type": "code", - "execution_count": 30, - + "execution_count": 149, "metadata": { "tags": [] }, @@ -495,7 +403,7 @@ "[]" ] }, - "execution_count": 30, + "execution_count": 149, "metadata": {}, "output_type": "execute_result" } @@ -517,7 +425,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 150, "metadata": { "tags": [] }, @@ -528,7 +436,7 @@ "[]" ] }, - "execution_count": 32, + "execution_count": 150, "metadata": {}, "output_type": "execute_result" } @@ -543,20 +451,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊Desafío: Buscar Todos\n", "\n", "Usa BeautifulSoup para encontrar todos los elementos `a` con la clase `mainmenu`. Le cambiee a dropdown-item para que se vea los resultados " - - "## 🥊 Desafío: Encontrar todo\n", - "\n", - "Usa BeautifulSoup para encontrar todos los elementos `a` con la clase `mainmenu`." - ] }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 151, "metadata": {}, "outputs": [ { @@ -587,61 +489,1379 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Paso 4: Obtener los atributos y el texto de los elementos\n", + "## Paso 4: Obtener atributos y texto de los elementos\n", "\n", - "Una vez identificados los elementos, necesitamos la información de acceso de cada uno. Normalmente, esto implica dos cosas:\n", + "Una vez que identificamos elementos, queremos acceder a la información en ese elemento. Usualmente, esto significa dos cosas:\n", "\n", "1. Texto\n", "2. Atributos\n", "\n", - "Obtener el texto dentro de un elemento es sencillo. Solo tenemos que usar el miembro `text` de un objeto `tag`:" + "Obtener el texto dentro de un elemento es fácil. Todo lo que tenemos que hacer es usar el miembro `text` de un objeto `tag`:" ] }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 152, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Texto: \n", + " English\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Afrikaans\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Albanian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Arabic\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Armenian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Azerbaijani\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Basque\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Bengali\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Bosnian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Catalan\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Croatian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Czech\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Danish\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Dutch\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Esperanto\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Estonian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Filipino\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Finnish\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " French\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Galician\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Georgian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " German\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Greek\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Gujarati\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Haitian Creole\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Hausa\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Hawaiian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Hebrew\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Hindi\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Hungarian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Icelandic\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Indonesian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Interlingua\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Interlingue\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Inuktitut\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Irish\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Italian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Japanese\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Javanese\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Kannada\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Khmer\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Korean\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Latin\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Latvian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Lithuanian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Luxembourgish\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Macedonian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Malagasy\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Malayalam\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Maltese\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Maori\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Marathi\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Myanmar\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Nepali\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Norwegian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Odia\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Pashto\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Punjabi\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Romanian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Russian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Samoan\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Sango\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Sanskrit\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Sardinian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Sindhi\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Sinhala\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Slovak\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Slovenian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Somali\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Southern Sotho\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Spanish\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Sundanese\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Swahili\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Swedish\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Tamil\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Telugu\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Thai\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Tigrinya\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Tonga\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Turkish\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Ukrainian\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Urdu\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Vietnamese\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Welsh\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Xhosa\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Yiddish\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Yoruba\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: \n", + " Zulu\n", + " \n", + "href: #\n", + "clases: ['dropdown-item']\n", + "------\n", + "Texto: Translate\n", + "href: https://translate.google.com\n", + "clases: ['goog-logo-link']\n", + "------\n", + "Texto: ILGA.GOV\n", + "href: /\n", + "clases: None\n", + "------\n", + "Texto: \n", + "LEGISLATION & LAWS \n", + "\n", + "href: /Legislation\n", + "clases: None\n", + "------\n", + "Texto: Bills & Resolutions\n", + "href: /Legislation\n", + "clases: None\n", + "------\n", + "Texto: Public Acts\n", + "href: /Legislation/PublicActs\n", + "clases: None\n", + "------\n", + "Texto: Illinois Compiled Statutes\n", + "href: /Legislation/ILCS/Chapters\n", + "clases: None\n", + "------\n", + "Texto: Illinois Constitution\n", + "href: /documents/commission/lrb/conmain.htm\n", + "clases: None\n", + "------\n", + "Texto: Search Legislation\n", + "href: /Search?q=&base=Legis\n", + "clases: None\n", + "------\n", + "Texto: Glossary\n", + "href: /Legislation/Glossary\n", + "clases: None\n", + "------\n", + "Texto: Guide\n", + "href: /Guide\n", + "clases: None\n", + "------\n", + "Texto: \n", + "Reports & Inquiry \n", + "\n", + "href: /Reports\n", + "clases: None\n", + "------\n", + "Texto: Legislative Reports\n", + "href: /Reports\n", + "clases: None\n", + "------\n", + "Texto: Special Reports\n", + "href: /Reports/SpecialReports\n", + "clases: None\n", + "------\n", + "Texto: FTP Site\n", + "href: /ftp/\n", + "clases: None\n", + "------\n", + "Texto: Legislator Lookup\n", + "href: /members/FindMyLegislator\n", + "clases: None\n", + "------\n", + "Texto: Capitol Complex Phone Numbers\n", + "href: /directory\n", + "clases: None\n", + "------\n", + "Texto: \n", + "Rules & Regulations \n", + "\n", + "href: #\n", + "clases: None\n", + "------\n", + "Texto: Illinois Register\n", + "href: http://www.cyberdriveillinois.com/departments/index/register/home.html\n", + "clases: None\n", + "------\n", + "Texto: Administrative Rules\n", + "href: /agencies/JCAR/AdminCode\n", + "clases: None\n", + "------\n", + "Texto: \n", + "Senate \n", + "\n", + "href: /Senate/Members\n", + "clases: None\n", + "------\n", + "Texto: Members\n", + "href: /Senate/Members\n", + "clases: None\n", + "------\n", + "Texto: Schedules\n", + "href: /Senate/Schedules\n", + "clases: None\n", + "------\n", + "Texto: Committees\n", + "href: /Senate/Committees\n", + "clases: None\n", + "------\n", + "Texto:  Request for Remote Testimony\n", + "href: /Uploads/Testimony/Senate/Remote Legislative Hearing Process 104th GA.pdf\n", + "clases: None\n", + "------\n", + "Texto: Journals\n", + "href: /Senate/Journals\n", + "clases: None\n", + "------\n", + "Texto: Transcripts\n", + "href: /Senate/Transcripts\n", + "clases: None\n", + "------\n", + "Texto: Rules\n", + "href: /Senate/Rules\n", + "clases: None\n", + "------\n", + "Texto: Audio/Video\n", + "href: /Senate/AudioVideo\n", + "clases: None\n", + "------\n", + "Texto: FOIA Information\n", + "href: /Documents/senate/FOIA.pdf\n", + "clases: None\n", + "------\n", + "Texto: Senate Employment Opportunities\n", + "href: /EmploymentOpportunities\n", + "clases: None\n", + "------\n", + "Texto: Media Guidelines\n", + "href: /Documents/senate/SenateMediaGuidelines.pdf\n", + "clases: None\n", + "------\n", + "Texto: \n", + "House \n", + "\n", + "href: /House/Members\n", + "clases: None\n", + "------\n", + "Texto: Members\n", + "href: /House/Members\n", + "clases: None\n", + "------\n", + "Texto: Schedules\n", + "href: /House/Schedules\n", + "clases: None\n", + "------\n", + "Texto: Committees\n", + "href: /House/Committees\n", + "clases: None\n", + "------\n", + "Texto:  Submit testimony for House Committees\n", + "href: /Uploads/Testimony/House/Remote_Committee_Hearing_Process_March2023.pdf\n", + "clases: None\n", + "------\n", + "Texto: Journals\n", + "href: /House/Journals\n", + "clases: None\n", + "------\n", + "Texto: Transcripts\n", + "href: /House/Transcripts\n", + "clases: None\n", + "------\n", + "Texto: Rules\n", + "href: /House/Rules\n", + "clases: None\n", + "------\n", + "Texto: Audio/Video\n", + "href: /House/AudioVideo\n", + "clases: None\n", + "------\n", + "Texto: FOIA Information\n", + "href: /Documents/house/FOIA.pdf\n", + "clases: None\n", + "------\n", + "Texto: House Employment Opportunities\n", + "href: /EmploymentOpportunities\n", + "clases: None\n", + "------\n", + "Texto:  Log In\n", + "href: /Account/Login\n", + "clases: ['nav-link']\n", + "------\n", + "Texto: Home\n", + "href: /\n", + "clases: ['active']\n", + "------\n", + "Texto: View List\n", + "href: /Senate/Members/List\n", + "clases: ['btn', 'btn-primary']\n", + "------\n", + "Texto: Officers\n", + "href: /Documents/Senate/104th_Senate_Officers.pdf\n", + "clases: ['btn', 'btn-primary', 'm-1']\n", + "------\n", + "Texto: Leadership\n", + "href: /Documents/Senate/104th_Senate_Leadership.pdf\n", + "clases: ['btn', 'btn-primary', 'm-1']\n", + "------\n", + "Texto: Seating Chart\n", + "href: https://www.ilga.gov/Documents/Senate/104th_Senate_Seating_Chart.pdf\n", + "clases: ['btn', 'btn-primary', 'm-1']\n", + "------\n", + "Texto: Report List\n", + "href: Members/rptMemberList\n", + "clases: ['btn', 'btn-primary', 'm-1']\n", + "------\n", + "Texto: Neil Anderson\n", + "href: /Senate/Members/Details/3312\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Neil Anderson\n", + "href: /Senate/Members/Details/3312\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Omar Aquino\n", + "href: /Senate/Members/Details/3316\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Omar Aquino\n", + "href: /Senate/Members/Details/3316\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Li Arellano, Jr.\n", + "href: /Senate/Members/Details/3383\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Li Arellano, Jr.\n", + "href: /Senate/Members/Details/3383\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Chris Balkema\n", + "href: /Senate/Members/Details/3413\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Chris Balkema\n", + "href: /Senate/Members/Details/3413\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Christopher Belt\n", + "href: /Senate/Members/Details/3337\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Christopher Belt\n", + "href: /Senate/Members/Details/3337\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Terri Bryant\n", + "href: /Senate/Members/Details/3386\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Terri Bryant\n", + "href: /Senate/Members/Details/3386\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Cristina Castro\n", + "href: /Senate/Members/Details/3317\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Cristina Castro\n", + "href: /Senate/Members/Details/3317\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Javier L. Cervantes\n", + "href: /Senate/Members/Details/3403\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Javier L. Cervantes\n", + "href: /Senate/Members/Details/3403\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Andrew S. Chesney\n", + "href: /Senate/Members/Details/3410\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Andrew S. Chesney\n", + "href: /Senate/Members/Details/3410\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Lakesia Collins\n", + "href: /Senate/Members/Details/3443\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Lakesia Collins\n", + "href: /Senate/Members/Details/3443\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Bill Cunningham\n", + "href: /Senate/Members/Details/3291\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Bill Cunningham\n", + "href: /Senate/Members/Details/3291\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: John F. Curran\n", + "href: /Senate/Members/Details/3329\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: John F. Curran\n", + "href: /Senate/Members/Details/3329\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Donald P. DeWitte\n", + "href: /Senate/Members/Details/3334\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Donald P. DeWitte\n", + "href: /Senate/Members/Details/3334\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Mary Edly-Allen\n", + "href: /Senate/Members/Details/3407\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Mary Edly-Allen\n", + "href: /Senate/Members/Details/3407\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Laura Ellman\n", + "href: /Senate/Members/Details/3339\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Laura Ellman\n", + "href: /Senate/Members/Details/3339\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Paul Faraci\n", + "href: /Senate/Members/Details/3412\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Paul Faraci\n", + "href: /Senate/Members/Details/3412\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Sara Feigenholtz\n", + "href: /Senate/Members/Details/3376\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Sara Feigenholtz\n", + "href: /Senate/Members/Details/3376\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Laura Fine\n", + "href: /Senate/Members/Details/3338\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Laura Fine\n", + "href: /Senate/Members/Details/3338\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Dale Fowler\n", + "href: /Senate/Members/Details/3318\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Dale Fowler\n", + "href: /Senate/Members/Details/3318\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Suzy Glowiak Hilton\n", + "href: /Senate/Members/Details/3341\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Suzy Glowiak Hilton\n", + "href: /Senate/Members/Details/3341\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Graciela Guzmán\n", + "href: /Senate/Members/Details/3442\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Graciela Guzmán\n", + "href: /Senate/Members/Details/3442\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Michael W. Halpin\n", + "href: /Senate/Members/Details/3408\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Michael W. Halpin\n", + "href: /Senate/Members/Details/3408\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Don Harmon\n", + "href: /Senate/Members/Details/3268\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Don Harmon\n", + "href: /Senate/Members/Details/3268\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Napoleon Harris, III\n", + "href: /Senate/Members/Details/3292\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Napoleon Harris, III\n", + "href: /Senate/Members/Details/3292\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Erica Harriss\n", + "href: /Senate/Members/Details/3411\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Erica Harriss\n", + "href: /Senate/Members/Details/3411\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Michael E. Hastings\n", + "href: /Senate/Members/Details/3293\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Michael E. Hastings\n", + "href: /Senate/Members/Details/3293\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Darby A. Hills\n", + "href: /Senate/Members/Details/3460\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Darby A. Hills\n", + "href: /Senate/Members/Details/3460\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Linda Holmes\n", + "href: /Senate/Members/Details/3270\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Linda Holmes\n", + "href: /Senate/Members/Details/3270\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Mattie Hunter\n", + "href: /Senate/Members/Details/3269\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Mattie Hunter\n", + "href: /Senate/Members/Details/3269\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Adriane Johnson\n", + "href: /Senate/Members/Details/3378\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Adriane Johnson\n", + "href: /Senate/Members/Details/3378\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Emil Jones, III\n", + "href: /Senate/Members/Details/3276\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Emil Jones, III\n", + "href: /Senate/Members/Details/3276\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Patrick J. Joyce\n", + "href: /Senate/Members/Details/3372\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Patrick J. Joyce\n", + "href: /Senate/Members/Details/3372\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: David Koehler\n", + "href: /Senate/Members/Details/3271\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: David Koehler\n", + "href: /Senate/Members/Details/3271\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Seth Lewis\n", + "href: /Senate/Members/Details/3406\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Seth Lewis\n", + "href: /Senate/Members/Details/3406\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Kimberly A. Lightford\n", + "href: /Senate/Members/Details/3264\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Kimberly A. Lightford\n", + "href: /Senate/Members/Details/3264\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Meg Loughran Cappel\n", + "href: /Senate/Members/Details/3380\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Meg Loughran Cappel\n", + "href: /Senate/Members/Details/3380\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Robert F. Martwick\n", + "href: /Senate/Members/Details/3369\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Robert F. Martwick\n", + "href: /Senate/Members/Details/3369\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Steve McClure\n", + "href: /Senate/Members/Details/3342\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Steve McClure\n", + "href: /Senate/Members/Details/3342\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Julie A. Morrison\n", + "href: /Senate/Members/Details/3294\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Julie A. Morrison\n", + "href: /Senate/Members/Details/3294\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Laura M. Murphy\n", + "href: /Senate/Members/Details/3313\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Laura M. Murphy\n", + "href: /Senate/Members/Details/3313\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Robert Peters\n", + "href: /Senate/Members/Details/3343\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Robert Peters\n", + "href: /Senate/Members/Details/3343\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Jason Plummer\n", + "href: /Senate/Members/Details/3344\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Jason Plummer\n", + "href: /Senate/Members/Details/3344\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Mike Porfirio\n", + "href: /Senate/Members/Details/3404\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Mike Porfirio\n", + "href: /Senate/Members/Details/3404\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Willie Preston\n", + "href: /Senate/Members/Details/3405\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Willie Preston\n", + "href: /Senate/Members/Details/3405\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Sue Rezin\n", + "href: /Senate/Members/Details/3281\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Sue Rezin\n", + "href: /Senate/Members/Details/3281\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Chapin Rose\n", + "href: /Senate/Members/Details/3295\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Chapin Rose\n", + "href: /Senate/Members/Details/3295\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Mike Simmons\n", + "href: /Senate/Members/Details/3398\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Mike Simmons\n", + "href: /Senate/Members/Details/3398\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Elgie R. Sims, Jr.\n", + "href: /Senate/Members/Details/3331\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Elgie R. Sims, Jr.\n", + "href: /Senate/Members/Details/3331\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Steve Stadelman\n", + "href: /Senate/Members/Details/3296\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Steve Stadelman\n", + "href: /Senate/Members/Details/3296\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Dave Syverson\n", + "href: /Senate/Members/Details/3265\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Dave Syverson\n", + "href: /Senate/Members/Details/3265\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Jil Tracy\n", + "href: /Senate/Members/Details/3319\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Jil Tracy\n", + "href: /Senate/Members/Details/3319\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Doris Turner\n", + "href: /Senate/Members/Details/3399\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Doris Turner\n", + "href: /Senate/Members/Details/3399\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Sally J. Turner\n", + "href: /Senate/Members/Details/3397\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Sally J. Turner\n", + "href: /Senate/Members/Details/3397\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Rachel Ventura\n", + "href: /Senate/Members/Details/3409\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Rachel Ventura\n", + "href: /Senate/Members/Details/3409\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Karina Villa\n", + "href: /Senate/Members/Details/3385\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Karina Villa\n", + "href: /Senate/Members/Details/3385\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Celina Villanueva\n", + "href: /Senate/Members/Details/3375\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Celina Villanueva\n", + "href: /Senate/Members/Details/3375\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Ram Villivalam\n", + "href: /Senate/Members/Details/3345\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Ram Villivalam\n", + "href: /Senate/Members/Details/3345\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Mark L. Walker\n", + "href: /Senate/Members/Details/3449\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Mark L. Walker\n", + "href: /Senate/Members/Details/3449\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Craig Wilcox\n", + "href: /Senate/Members/Details/3336\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Craig Wilcox\n", + "href: /Senate/Members/Details/3336\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Dan McConchie\n", + "href: /Senate/Members/Details/3315\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: Dan McConchie\n", + "href: /Senate/Members/Details/3315\n", + "clases: ['notranslate']\n", + "------\n", + "Texto: \n", + " Contact ILGA Webmaster\n", + " \n", + "href: mailto:webmaster@ilga.gov?subject=Email from ILGA Web\n", + "clases: None\n", + "------\n", + "Texto: \n", + "\n", + "\n", + "href: http://www.amberillinois.com\n", + "clases: None\n", + "------\n", + "Texto: \n", + "\n", + "\n", + "href: https://www.missingkids.org\n", + "clases: None\n", + "------\n", + "Texto: ILGA.GOV\n", + "href: /\n", + "clases: None\n", + "------\n", + "Texto: Disclaimers\n", + "href: /Disclaimers\n", + "clases: None\n", + "------\n", + "Texto: \n", + " ADA\n", + " \n", + "href: /Accessibility\n", + "clases: None\n", + "------\n", + "Texto: \n", + " Contact ILGA Webmaster\n", + " \n", + "href: mailto:webmaster@ilga.gov?subject=Email from ILGA Web\n", + "clases: None\n", + "------\n", + "Texto: \n", + "\n", + "\n", + "href: http://www.amberillinois.com\n", + "clases: None\n", + "------\n", + "Texto: \n", + "\n", + "\n", + "href: https://www.missingkids.org\n", + "clases: None\n", + "------\n", + "Texto: ILGA.GOV\n", + "href: /\n", + "clases: None\n", + "------\n", + "Texto: Disclaimers\n", + "href: /Disclaimers\n", + "clases: None\n", + "------\n", + "Texto: \n", + " ADA\n", + " \n", + "href: /Accessibility\n", + "clases: None\n", + "------\n", + "Texto: \n", + "href: #\n", + "clases: ['back-to-top', 'd-flex', 'align-items-center', 'justify-content-center']\n", + "------\n" + ] + } + ], + "source": [ + "# Encuentra todos los enlaces del HTML\n", + "links = soup.find_all(\"a\")\n", + "\n", + "# Imprime el texto y el href de cada enlace\n", + "for link in links:\n", + " print(\"Texto:\", link.text)\n", + " print(\"href:\", link.get('href'))\n", + " print(\"clases:\", link.get('class'))\n", + " print(\"------\")\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 153, "metadata": { "tags": [] }, "outputs": [ { - "ename": "IndexError", - "evalue": "list index out of range", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mIndexError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[42]\u001b[39m\u001b[32m, line 5\u001b[39m\n\u001b[32m 2\u001b[39m side_menu_links = soup.select(\u001b[33m\"\u001b[39m\u001b[33ma.sidemenu\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 4\u001b[39m \u001b[38;5;66;03m# Examine the first link\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m5\u001b[39m first_link = \u001b[43mside_menu_links\u001b[49m\u001b[43m[\u001b[49m\u001b[32;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[32m 6\u001b[39m \u001b[38;5;28mprint\u001b[39m(first_link)\n\u001b[32m 8\u001b[39m \u001b[38;5;66;03m# What class is this variable?\u001b[39;00m\n", - "\u001b[31mIndexError\u001b[39m: list index out of range" + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " English\n", + " \n", + "Class: \n" ] } ], "source": [ - "# Get all sidemenu links as a list\n", - "side_menu_links = soup.select(\"a.sidemenu\")\n", + "# obtener elementos con el selector CSS \"a.dropdown-item\"\n", + "side_menu_links = soup.select(\"a.dropdown-item\")\n", "\n", - "# Examine the first link\n", + "# examinar el primer elemento\n", "first_link = side_menu_links[0]\n", - "print(first_link)\n", "\n", - "# What class is this variable?\n", - "print('Class: ', type(first_link))" + "# obtener el texto del enlace\n", + "print(first_link.text)\n", + "\n", + "# cuál clase de objeto es?\n", + "print('Class: ', type(first_link))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "¡Es una etiqueta de Beautiful Soup! Esto significa que tiene un miembro \"texto\":" + "It's a Beautiful Soup tag! This means it has a `text` member:" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 154, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " English\n", + " \n" + ] + } + ], "source": [ "print(first_link.text)" ] @@ -650,18 +1870,26 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "A veces necesitamos el valor de ciertos atributos. Esto es especialmente relevante para las etiquetas «a» o enlaces, donde el atributo «href» nos indica adónde lleva el enlace.\n", + "Sometimes we want the value of certain attributes. This is particularly relevant for `a` tags, or links, where the `href` attribute tells us where the link goes.\n", "\n", - "💡 **Consejo**: Puedes acceder a los atributos de una etiqueta tratándola como un diccionario:" + "💡 **Tip**: You can access a tag’s attributes by treating the tag like a dictionary:" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 155, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "#\n" + ] + } + ], "source": [ "print(first_link['href'])" ] @@ -672,16 +1900,21 @@ "source": [ "## 🥊 Desafío: Extraer atributos específicos\n", "\n", - "Extraer todos los atributos `href` de cada URL `mainmenu`." + "Extrae todos los atributos `href` de cada URL `mainmenu`." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 156, "metadata": {}, "outputs": [], "source": [ - "# YOUR CODE HERE\n" + "# YOUR CODE HERE\n", + "# Extraer todos los atributos href de cada enlace con la clase 'mainmenu'\n", + "mainmenu_links = soup.select(\"a.mainmenu\")\n", + "\n", + "for link in mainmenu_links:\n", + " print(link.get('href'))\n" ] }, { @@ -692,7 +1925,7 @@ "\n", "# Análisis de la Asamblea General de Illinois\n", "\n", - "Aunque parezca increíble, estas son las herramientas fundamentales para analizar un sitio web. Una vez que dediques más tiempo a familiarizarte con HTML y CSS, simplemente será cuestión de comprender la estructura de un sitio web específico y aplicar inteligentemente las herramientas de Beautiful Soup y Python.\n", + "Aunque parezca increíble, estas son las herramientas fundamentales para analizar un sitio web. Una vez que dediques más tiempo a familiarizarte con HTML y CSS, solo tendrás que comprender la estructura de un sitio web específico y aplicar con inteligencia las herramientas de Beautiful Soup y Python.\n", "\n", "Apliquemos estas habilidades para analizar la [98.ª Asamblea General de Illinois](http://www.ilga.gov/senate/default.asp?GA=98).\n", "\n", @@ -703,24 +1936,24 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Rastrear y analizar la página web\n", + "## Analizar la página web\n", "\n", - "Rastreemos y analicemos la página web con las herramientas que aprendimos en la sección anterior." + "Analicemos la página web usando las herramientas que aprendimos en la sección anterior." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 157, "metadata": { "tags": [] }, "outputs": [], "source": [ - "# Make a GET request\n", - "req = requests.get('http://www.ilga.gov/senate/default.asp?GA=98')\n", - "# Read the content of the server’s response\n", + "# Hacemos una nueva solicitud a otra página\n", + "req = requests.get('https://www.ilga.gov/Senate/Members/rptMemberList')\n", + "# leer el contenido de la respuesta del servidor\n", "src = req.text\n", - "# Soup it\n", + "# analiza la respuesta y conviértela en un árbol HTML.\n", "soup = BeautifulSoup(src, \"lxml\")" ] }, @@ -735,11 +1968,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 158, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "60" + ] + }, + "execution_count": 158, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Get all table row elements\n", + "# obtener todas las filas de la tabla\n", "rows = soup.find_all(\"tr\")\n", "len(rows)" ] @@ -753,15 +1997,15 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 159, "metadata": {}, "outputs": [], "source": [ - "# Returns every ‘tr tr tr’ css selector in the page\n", - "rows = soup.select('tr tr tr')\n", + "# retornar solo las filas que están dentro de otra fila\n", + "rows = soup.select('a.dropdown-item')\n", "\n", - "for row in rows[:5]:\n", - " print(row, '\\n')" + "for row in rows[:20]:\n", + " print(row, '\\n')\n" ] }, { @@ -773,12 +2017,42 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 160, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0\n", + "[]\n" + ] + } + ], "source": [ - "example_row = rows[2]\n", - "print(example_row.prettify())" + "print(len(rows))\n", + "print(rows)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 161, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "No rows found.\n" + ] + } + ], + "source": [ + "if rows:\n", + "\texample_row = rows[0]\n", + "\tprint(example_row.prettify())\n", + "else:\n", + "\tprint(\"No rows found.\")" ] }, { @@ -794,21 +2068,93 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 162, "metadata": {}, "outputs": [], "source": [ - "for cell in example_row.select('td'):\n", - " print(cell)\n", - "print()\n", + "# Parse the HTML to get the rows\n", + "soup = BeautifulSoup(src, \"lxml\")\n", + "rows = soup.select(\"tbody tr\")\n", "\n", - "for cell in example_row.select('.detail'):\n", - " print(cell)\n", - "print()\n", + "if rows:\n", + "\texample_row = rows[0]\n", + "else:\n", + "\texample_row = None\n", + "\tprint(\"No rows found.\")\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 163, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " \n", + " \n", + " Neil Anderson\n", + " \n", + " (R)\n", + "
\n", + " 47th District\n", + " \n", + " \n", + " 208 A Capitol Building\n", + "
\n", + "
\n", + " Springfield, IL 62706\n", + "
\n", + " (217) 782-5957\n", + " \n", + " \n", + " 103 North College Avenue\n", + "
\n", + " #201\n", + "
\n", + " Aledo IL 61231\n", + "
\n", + " (309) 230-7584\n", + " \n", + "\n", + "\n", + "\n", + "Neil Anderson (R)\n", + "
\n", + " 47th District\n", + " \n", + "\n", + " 208 A Capitol Building
\n", + "
\n", + " Springfield, IL 62706
\n", + " (217) 782-5957\n", + " \n", + " \n", + "103 North College Avenue
\n", + " #201
\n", + " Aledo IL 61231
\n", + " (309) 230-7584\n", + " \n" + ] + } + ], + "source": [ + "if rows:\n", + " example_row = rows[0]\n", + " print(example_row.prettify())\n", "\n", - "for cell in example_row.select('td.detail'):\n", - " print(cell)\n", - "print()" + " # Aquí procesa example_row solo si existe\n", + " for cell in example_row.select('td'):\n", + " print(cell)\n", + " for cell in example_row.select('.detail'):\n", + " print(cell)\n", + " for cell in example_row.select('td.detail'):\n", + " print(cell)\n", + "else:\n", + " print(\"No rows found.\")\n" ] }, { @@ -820,20 +2166,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 167, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tds: 3\n", + "details: 0\n", + "td.details: 0\n" + ] + } + ], "source": [ - "assert example_row.select('td') == example_row.select('.detail') == example_row.select('td.detail')" + "# revisamos cuántos elementos encuentra cada método\n", + "tds = example_row.select('td')\n", + "details = example_row.select('.detail')\n", + "td_details = example_row.select('td.detail')\n", + "\n", + "print(\"tds:\", len(tds))\n", + "print(\"details:\", len(details))\n", + "print(\"td.details:\", len(td_details))\n", + "\n", + "# solo para verificar que todos los .detail están en \n", + "assert td_details == details # estos deben de ser iguales" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Utilicemos el selector `td.detail` para ser lo más específicos posible." + "Let's use the selector `td.detail` to be as specific as possible." ] }, { @@ -851,7 +2217,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "La mayoría de las veces, nos interesa el **texto** real de un sitio web, no sus etiquetas. Recordemos que para obtener el texto de un elemento HTML, usamos el miembro `text`:" + "Most of the time, we're interested in the actual **text** of a website, not its tags. Recall that to get the text of an HTML element, we use the `text` member:" ] }, { @@ -870,7 +2236,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "¡Se ve bien! Ahora solo necesitamos usar nuestros conocimientos básicos de Python para obtener los elementos de esta lista que necesitamos. Recuerda: queremos el nombre del senador, su distrito y su partido." + "Looks good! Now we just use our basic Python knowledge to get the elements of this list that we want. Remember, we want the senator's name, their district, and their party." ] }, { @@ -888,9 +2254,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Eliminando filas basura\n", + "## Getting Rid of Junk Rows\n", "\n", - "Vimos al principio que no todas las filas que obtuvimos corresponden a un senador. Tendremos que hacer limpieza antes de continuar. Vean algunos ejemplos:" + "We saw at the beginning that not all of the rows we got actually correspond to a senator. We'll need to do some cleaning before we can proceed forward. Take a look at some examples:" ] }, { @@ -908,9 +2274,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Al escribir nuestro bucle for, queremos que solo se aplique a las filas relevantes. Por lo tanto, debemos filtrar las filas irrelevantes. Para ello, comparamos algunas de estas filas con las que necesitamos, observamos sus diferencias y luego formulamos esto en una condición.\n", + "When we write our for loop, we only want it to apply to the relevant rows. So we'll need to filter out the irrelevant rows. The way to do this is to compare some of these to the rows we do want, see how they differ, and then formulate that in a conditional.\n", "\n", - "Como puedes imaginar, hay muchas maneras de hacerlo, y dependerá del sitio web. Aquí te mostraremos algunas para que te hagas una idea de cómo hacerlo." + "As you can imagine, there a lot of possible ways to do this, and it'll depend on the website. We'll show some here to give you an idea of how to do this." ] }, { @@ -932,7 +2298,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Quizás las buenas filas tengan una longitud de 5. Comprobémoslo:" + "Perhaps good rows have a length of 5. Let's check:" ] }, { @@ -953,7 +2319,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Encontramos una fila de pie de página en nuestra lista que queremos evitar. Probemos algo diferente:" + "We found a footer row in our list that we'd like to avoid. Let's try something else:" ] }, { @@ -989,16 +2355,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "¡Parece que encontramos algo que funcionó!" + "Looks like we found something that worked!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Unir todo en un bucle\n", + "## Loop it All Together\n", "\n", - "Ahora que hemos visto cómo obtener los datos que queremos de una fila y filtrar las filas que no necesitamos, vamos a unirlo todo en un bucle." + "Now that we've seen how to get the data we want from one row, as well as filter out the rows we don't want, let's put it all together into a loop." ] }, { @@ -1045,7 +2411,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Echemos un vistazo a lo que tenemos en \"miembros\"." + "Let's take a look at what we have in `members`." ] }, { @@ -1061,37 +2427,37 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊 Desafío: Obtener elementos `href` que apunten a los proyectos de ley de los miembros\n", + "## 🥊 Challenge: Get `href` elements pointing to members' bills \n", "\n", - "El código anterior recupera información sobre:\n", + "The code above retrieves information on: \n", "\n", - "- el nombre del senador,\n", - "- su número de distrito,\n", - "- y su partido.\n", + "- the senator's name,\n", + "- their district number,\n", + "- and their party.\n", "\n", - "Ahora queremos recuperar la URL de la lista de proyectos de ley de cada senador. Cada URL seguirá un formato específico.\n", + "We now want to retrieve the URL for each senator's list of bills. Each URL will follow a specific format. \n", "\n", - "El formato de la lista de proyectos de ley de un senador determinado es:\n", + "The format for the list of bills for a given senator is:\n", "\n", "`http://www.ilga.gov/senate/SenatorBills.asp?GA=98&MemberID=[MEMBER_ID]&Primary=True`\n", "\n", - "para obtener algo como:\n", + "to get something like:\n", "\n", "`http://www.ilga.gov/senate/SenatorBills.asp?MemberID=1911&GA=98&Primary=True`\n", "\n", - "en el cual `MEMBER_ID=1911`. \n", + "in which `MEMBER_ID=1911`. \n", "\n", - "Deberías poder ver que, lamentablemente, `MEMBER_ID` no se extrae actualmente en nuestro código de extracción.\n", + "You should be able to see that, unfortunately, `MEMBER_ID` is not currently something pulled out in our scraping code.\n", "\n", - "Tu tarea inicial es modificar el código anterior para que también **recuperemos la URL completa que apunta a la página correspondiente de los proyectos de ley patrocinados por las primarias**, para cada miembro, y la devolvamos junto con su nombre, distrito y partido.\n", + "Your initial task is to modify the code above so that we also **retrieve the full URL which points to the corresponding page of primary-sponsored bills**, for each member, and return it along with their name, district, and party.\n", "\n", - "Consejos:\n", + "Tips: \n", "\n", - "* Para ello, deberás obtener el elemento de anclaje apropiado (``) en la fila de la tabla de cada legislador. Puedes usar el método `.select()` en el objeto `row` del bucle para hacerlo, similar al comando que encuentra todas las celdas `td.detail` de la fila. Recuerda que solo queremos el enlace a los proyectos de ley del legislador, no a los comités ni a su página de perfil.\n", - "* El HTML de los elementos de anclaje se verá como `Proyectos de ley`. La cadena del atributo `href` contiene el enlace **relativo** que buscamos. Puedes acceder a un atributo de un objeto `Tag` de BeatifulSoup de la misma manera que accedes a un diccionario de Python: `anchor['attributeName']`. Consulta la documentación para más detalles.\n", - "* Hay muchas maneras diferentes de usar BeautifulSoup. Puedes hacer lo que necesites para extraer el `href`.\n", + "* To do this, you will want to get the appropriate anchor element (``) in each legislator's row of the table. You can again use the `.select()` method on the `row` object in the loop to do this — similar to the command that finds all of the `td.detail` cells in the row. Remember that we only want the link to the legislator's bills, not the committees or the legislator's profile page.\n", + "* The anchor elements' HTML will look like `Bills`. The string in the `href` attribute contains the **relative** link we are after. You can access an attribute of a BeatifulSoup `Tag` object the same way you access a Python dictionary: `anchor['attributeName']`. See the documentation for more details.\n", + "* There are a _lot_ of different ways to use BeautifulSoup to get things done. whatever you need to do to pull the `href` out is fine.\n", "\n", - "El código se ha completado parcialmente. Complétalo donde dice `#TU CÓDIGO AQUÍ`. Guarda la ruta en un objeto llamado `full_path`." + "The code has been partially filled out for you. Fill it in where it says `#YOUR CODE HERE`. Save the path into an object called `full_path`." ] }, { @@ -1152,9 +2518,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊 Desafío: Modulariza tu código\n", + "## 🥊 Challenge: Modularize Your Code\n", "\n", - "Convierte el código anterior en una función que acepte una URL, rastree la URL para encontrar sus senadores y devuelva una lista de tuplas con información sobre cada senador." + "Turn the code above into a function that accepts a URL, scrapes the URL for its senators, and returns a list of tuples containing information about each senator. " ] }, { @@ -1188,21 +2554,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 🥊Desafío práctico: Escribir una función de scraping\n", - "\n", - "Queremos scraping las páginas web correspondientes a los proyectos de ley patrocinados por cada proyecto de ley.\n", + "## 🥊 Take-home Challenge: Writing a Scraper Function\n", "\n", - "Escribir una función llamada `get_bills(url)` para analizar la URL de un proyecto de ley. Esto implica:\n", + "We want to scrape the webpages corresponding to bills sponsored by each bills.\n", "\n", - "- Solicitar la URL mediante la biblioteca `requests`\n", - "- Usar las funciones de la biblioteca `BeautifulSoup` para encontrar todos los elementos `` con la clase `billlist`\n", - "- Devolver una _lista_ de tuplas, cada una con:\n", - "- Descripción (2.ª columna)\n", - "- Cámara (S o H) (3.ª columna)\n", - "- La última acción (4.ª columna)\n", - "- La fecha de la última acción (5.ª columna)\n", + "Write a function called `get_bills(url)` to parse a given bills URL. This will involve:\n", "\n", - "Esta función se ha completado parcialmente. Complete el resto." + " - requesting the URL using the `requests` library\n", + " - using the features of the `BeautifulSoup` library to find all of the `` elements with the class `billlist`\n", + " - return a _list_ of tuples, each with:\n", + " - description (2nd column)\n", + " - chamber (S or H) (3rd column)\n", + " - the last action (4th column)\n", + " - the last action date (5th column)\n", + " \n", + "This function has been partially completed. Fill in the rest." ] }, { @@ -1220,11 +2586,11 @@ " bills = []\n", " for row in rows:\n", " # YOUR CODE HERE\n", - " # bill_id =\n", - " #description =\n", - " #chamber =\n", - " #last_action =\n", - " #last_action_date =\n", + " bill_id =\n", + " description =\n", + " chamber =\n", + " last_action =\n", + " last_action_date =\n", " bill = (bill_id, description, chamber, last_action, last_action_date)\n", " bills.append(bill)\n", " return bills" @@ -1247,11 +2613,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Extraer todos los proyectos de ley\n", + "### Scrape All Bills\n", "\n", - "Finalmente, cree un diccionario `bills_dict` que asigne un número de distrito (la clave) a una lista de proyectos de ley (el valor) provenientes de ese distrito. Puede hacerlo recorriendo en bucle todos los miembros del senado en `members_dict` y llamando a `get_bills()` para cada una de las URL de sus proyectos de ley asociados.\n", + "Finally, create a dictionary `bills_dict` which maps a district number (the key) onto a list of bills (the value) coming from that district. You can do this by looping over all of the senate members in `members_dict` and calling `get_bills()` for each of their associated bill URLs.\n", "\n", - "**NOTA:** Por favor, llame a la función `time.sleep(1)` en cada iteración del bucle para no destruir el sitio web del estado." + "**NOTE:** please call the function `time.sleep(1)` for each iteration of the loop, so that we don't destroy the state's web site." ] }, {

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