From 644fa3c5a3fe70d3ad7e508f4c30270f7dce11b9 Mon Sep 17 00:00:00 2001 From: imb Date: Fri, 18 Oct 2024 11:17:58 +0200 Subject: [PATCH] Updated webscraping --- s-307/API.ipynb | 281 +++++ s-307/WebScraping.ipynb | 1713 ++++++++++++++++++++++++++ s-307/WebScrapping.ipynb | 1215 ------------------ s-307/files/cavalls-de-valltorta.jpg | Bin 0 -> 47530 bytes s-307/files/logo2.png | Bin 0 -> 10614 bytes 5 files changed, 1994 insertions(+), 1215 deletions(-) create mode 100644 s-307/API.ipynb create mode 100644 s-307/WebScraping.ipynb delete mode 100644 s-307/WebScrapping.ipynb create mode 100644 s-307/files/cavalls-de-valltorta.jpg create mode 100644 s-307/files/logo2.png diff --git a/s-307/API.ipynb b/s-307/API.ipynb new file mode 100644 index 0000000..106bc1b --- /dev/null +++ b/s-307/API.ipynb @@ -0,0 +1,281 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + " \n", + "\n", + "

\"Data Hunting and Gathering\"

\n", + "\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

Introduction to API

" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## APIS (Aplication Programing Interface)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Definitions\n", + "\n", + "#### URLs\n", + "\n", + "**U**niform **R**esource **L**ocator\n", + "\n", + "Contains the information about a resource we (the CLIENT) are requesting from a SERVER\n", + "\n", + "http://www.google.com/search?q=puppies\n", + "\n", + "http://127.0.0.1:306/invocations\n", + "\n", + "- Protocol: http\n", + "- Top Level Domain: com\n", + "- Domain: google\n", + "- Subdomain: www\n", + "- IP: 127.0.0.1\n", + "- Port: 306\n", + "- Route/Folder/Path: search/invocations\n", + "- Query Parameters: q=puppies\n", + "\n", + "#### HTTP\n", + "**H**yper **T**ext **T**transfer **P**rotocol (**S**ecure) \n", + "\n", + "HTTP(S) is a protocol that provides a structure for request between a client and a server.\n", + "For example, the web browser of a user (the client) uses HTTP to request information from a server that hoist a website\n", + "\n", + "#### Response\n", + "The response is usually dependent on the functionality you are looking for:\n", + " * a JSON \n", + " * an image\n", + " * a video\n", + " * an HTML\n", + " * ...\n", + "\n", + "#### Request\n", + "**Requests** are the questions we (clients) ask of a server to get some information (the **response**). \n", + "Types of request (verbs):\n", + " * GET: read info from a resource and do not change it in any way. This is the standard request that in most sites gets the HTML+CSS of the page as a response.\n", + " * POST: send data that creates/updates a resource, or triggers some process.\n", + " * PUT\n", + " * DELETE\n", + " * PATCH\n", + " * ...\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "TFL = requests.get('https://api.tfl.gov.uk/AirQuality')\n", + "\n", + "TFL.headers\n", + "TFL.content\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Content is typically in a JSON format - What does a json look like?\n", + "TFL.json()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![json](https://www.convertsimple.com/wp-content/uploads/2022/05/json-example.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Onboarding API data into Pandas\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "\n", + "weather_data = pd.DataFrame.from_dict(TFL.json())\n", + "weather_data.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Not ideal, part of the request is still in json. This is a nested json...\n", + "weather_data['currentForecast'][1]\n", + "\n", + "# There is a function in pandas to un-nest jsons, but it makes some assumptions and sometimes we have to unpack hierarchical structures ourselves\n", + "# beware this usually involves a lot of for loops and apply functions\n", + "pd.json_normalize(weather_data['currentForecast'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Parameters" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "r = requests.get('https://v2.jokeapi.dev/joke/programming')\n", + "r.json()\n", + "\n", + "\n", + "# Sometimes we want to pass parameters to the endpoint, just like we pass arguments to functions in python \n", + "# We pass parameters via the url as `?param1=value1¶m2=value2...` at the end of the url\n", + "r = requests.get('https://v2.jokeapi.dev/joke/programming?contains=python&amount=3')\n", + "r.json()\n", + "\n", + "params_dict = {\"contains\":\"python\",\"amount\":\"3\"}\n", + "r = requests.get('https://v2.jokeapi.dev/joke/programming',params=params_dict)\n", + "r.json()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Business Challange API" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Example: Fetching Weather Data Using OpenWeatherMap API in Python\n", + "\n", + "This example demonstrates how to use the OpenWeatherMap API to fetch current weather data for a specific city using Python.\n", + "\n", + "#### Prerequisites\n", + "- An API key from OpenWeatherMap.\n", + "- Python's `requests` library installed. (Install via `pip install requests` if needed.)\n", + "\n", + "#### Steps to Follow\n", + "1. **Sign Up for OpenWeatherMap API**:\n", + " - Register for an account at [OpenWeatherMap](https://openweathermap.org/api).\n", + " - Obtain your free API key (note that there might be an activation delay).\n", + "\n", + "2. **Python Script for Weather Data Retrieval**:\n", + " - The script uses the `requests` library to make an API call.\n", + " - Replace `'YOUR_API_KEY'` with your actual OpenWeatherMap API key.\n", + " - Replace `'CITY_NAME'` with your desired city name." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Business Challenge II - Optional\n", + "\n", + "#### Challenge: Analyzing Instagram Hashtag Trends with Instaloader\n", + "\n", + "## Objective\n", + "Leverage `Instaloader`, a Python library, to download posts associated with a specific hashtag on Instagram. Analyze the collected data to identify trends, popular content, and user engagement.\n", + "\n", + "## Steps\n", + "\n", + "### 1. Install Instaloader\n", + "- Ensure Python is installed on your system.\n", + "- Install `Instaloader` using pip: `pip install instaloader`\n", + "\n", + "\n", + "### 2. Data Collection\n", + "- Choose a hashtag relevant to a topic of interest (e.g., #nature, #travel, #food).\n", + "- Use `Instaloader` to download posts tagged with the chosen hashtag. Consider limitations like the number of posts to avoid overwhelming the API.\n", + "\n", + "```python\n", + "import instaloader\n", + "\n", + "L = instaloader.Instaloader()\n", + "posts = instaloader.Hashtag.from_name(L.context, 'YOUR_HASHTAG').get_posts()\n", + "\n", + "for post in posts:\n", + " # Add code to process and store post details\n", + "```\n", + "### 3. Data Analysis\n", + "Analyze the downloaded data for:\n", + "- Popular trends in the hashtag.\n", + "- Common themes or subjects in images or captions.\n", + "- Levels of user engagement (likes, comments).\n", + "\n", + "### 4. Reporting\n", + "- Compile your findings into a report.\n", + "- Include visual representations (graphs, word clouds) to illustrate key trends.\n", + "\n", + "### Important Notes\n", + "- Respect Instagram's terms of service and ethical guidelines in data scraping.\n", + "- Be mindful of privacy and consent, especially with user-generated content.\n", + "- The scope of data collection should be limited for educational purposes.\n", + "\n", + "### Expected Outcome\n", + "This challenge aims to provide practical experience with Instaloader, develop data analysis skills, and offer insights into social media trends and user behavior." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import requests\n", + "\n", + "def get_weather(api_key, city):\n", + " base_url = \"http://api.openweathermap.org/data/2.5/weather?\"\n", + " city_name = city\n", + " complete_url = f\"{base_url}appid={api_key}&q={city_name}\"\n", + " response = requests.get(complete_url)\n", + " return response.json()\n", + "\n", + "# Replace 'YOUR_API_KEY' with your actual API key and 'CITY_NAME' with your city\n", + "api_key = 'YOUR_API_KEY'\n", + "city_name = 'CITY_NAME'\n", + "weather_data = get_weather(api_key, city_name)\n", + "\n", + "print(f\"Weather in {city_name}:\")\n", + "print(weather_data)" + ] + } + ], + "metadata": { + "language_info": { + "name": "python" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/s-307/WebScraping.ipynb b/s-307/WebScraping.ipynb new file mode 100644 index 0000000..7e3c40c --- /dev/null +++ b/s-307/WebScraping.ipynb @@ -0,0 +1,1713 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + " \n", + "\n", + "

Web Scraping: Mining the Web for Data

\n", + "\n", + "

\"Data Hunting and Gathering\"

\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "* 1. [HTML](#HTML)\n", + "* 2. [CSS Selectors](#CSS)\n", + "* 3. [JavaScript](#JavaScript)\n", + "* 4. [Summary](#Summary)\n", + "\n", + "\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "____________" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Welcome to the first part of our journey into the world of web scraping. Web scraping, also known as web harvesting or web data extraction, is a technique used for extracting data from websites. This process involves fetching the web page and then extracting data from it.\n", + "\n", + "In this lesson, we'll use the `requests` library to fetch web pages and `Beautiful Soup` from the `bs4` package to parse these pages and extract information." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

By the end of this lesson, you'll:

\n", + "\n", + "- Understand **the value of web scraping**.\n", + "- Extract data from basic **HTML** and **CSS** structures.\n", + "- Learn to use **BeautifulSoup** and the **requests** library.\n", + "- Dive deeper into **web scraping ethics**.\n", + "- Explore advanced techniques for **handling JavaScript-based content**." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

Web Scraping?

" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![legtsgo](https://i.giphy.com/media/v1.Y2lkPTc5MGI3NjExbzQ4eDdobnZlenhtN3c5MndmcDZpMW4wdXZzZTcxaDl1Zmo2YWt3dSZlcD12MV9pbnRlcm5hbF9naWZfYnlfaWQmY3Q9Zw/SpopD7IQN2gK3qN4jS/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Understanding how to scrape data from the web is a valuable skill for any data professional. In the digital era, **data is the new gold**, and web scraping is the mining equipment that helps you extract it. Web scraping allows you to automatically collect and analyze data from websites, providing insights that can be a game-changer in competitive fields.\n", + "\n", + "#### Why Learn Web Scraping?\n", + "- **Data Availability**: The internet is a vast, dynamic source of data that can be used for all kinds of analyses, from understanding market trends to conducting academic research.\n", + "- **Automation**: Manual data collection can be tedious and time-consuming. Web scraping automates the process, saving time and ensuring a consistent data pipeline.\n", + "- **Competitive Advantage**: In fields like marketing, finance, and e-commerce, having timely and relevant data is crucial. Web scraping provides a competitive edge by allowing you to access real-time information.\n", + "\n", + "#### How Does Web Scraping Work?\n", + "- **Fetching Web Pages**: Web scraping starts with making a request to a webpage to fetch its content.\n", + "- **Parsing the Data**: Once the content is fetched, it is parsed using tools like BeautifulSoup or Scrapy to extract relevant information. This is especially useful when the data isn't available through public APIs.\n", + "- **Data Usage**: After extracting data, it can be cleaned, analyzed, and stored for further data analytics tasks, enabling deeper insights and more informed decision-making.\n", + "\n", + "#### Real-World Applications\n", + "- **Market Research**: Gather insights about competitors, identify customer sentiments, or track market trends by scraping review sites and social media.\n", + "- **Price Comparison**: Aggregate pricing data from different e-commerce platforms to create comparison tools.\n", + "- **Social Media Analysis**: Collect data from social networks for sentiment analysis, trend spotting, or brand monitoring.\n", + "\n", + "> **Note**: While web scraping is a powerful tool, always ensure compliance with website terms of service and legal regulations regarding data usage.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

Web structure

" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The fundamental web technologies that form the structure of the websites we aim to scrape are:\n", + "\n", + "- **HTML**: Standing as the backbone of almost all websites, HTML, the core markup language, is instrumental in creating web pages. It houses all the content available on a webpage.\n", + " \n", + "- **CSS**: This stylesheet language works alongside HTML, taking charge of the presentation aspect of the webpages. It controls how HTML elements are displayed, setting the stage for a visually pleasing and organized web interface.\n", + "\n", + "- **JavaScript**: Adding a dynamic touch to the websites, JavaScript comes into play to create interactive and animated content. This programming language has the power to alter webpage content even after it has loaded, bringing a dynamic and responsive element to web designs.\n", + "\n", + "In this lesson, we will work with the **HTML** and **CSS** from the websites using **BeautifulSoup** and **requests** libraries and **Selenium** to handle **JavaScript** content." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# HTML" + ] + }, + { + "attachments": { + "image.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![image.png](attachment:image.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The most fundamental web pages are constructed using HTML and CSS. These technologies serve two primary purposes: **HTML (Hypertext Markup Language)** structures and stores the content, making it the primary target for web scraping, while **CSS (Cascading Style Sheets)** formats and styles the content, highlighting visual elements like fonts, colors, borders, and layout.\n", + "\n", + "HTML is a markup language typically rendered by web browsers. It uses 'tags' to define elements on a web page. A typical tag format includes a tag name, attributes (if any), and the content between opening and closing tags.\n", + "\n", + "#### Key Components of an HTML File\n", + "\n", + "- **HTML Structure**:\n", + " - **Hierarchical**: HTML documents are structured hierarchically, meaning elements are nested within other elements, forming a tree-like structure.\n", + " - **Tags**: These are the building blocks of HTML, defining elements that hold different types of content.\n", + " - **Attributes**: HTML tags can have attributes, which define properties of an element and are used to set various characteristics such as class, ID, and style.\n", + "\n", + "- **DOCTYPE Declaration**: \n", + " - Begins with ``, indicating the use of HTML5.\n", + " - Earlier HTML versions had different DOCTYPEs.\n", + "\n", + "- **HTML Tag**: \n", + " - The `html` tag (and its closing `/html` tag) encloses the entire web page content.\n", + "\n", + "- **Head and Body**: \n", + " - The `head` section often includes the `title` tag, defining the webpage's name, links to CSS stylesheets, and JavaScript files for dynamic behavior.\n", + " - The `body` contains the visible webpage content.\n", + "\n", + "- **Common HTML Elements**:\n", + " - **Headings and Paragraphs**: Use `h#` (where # is a number) for headings and `p` for paragraphs.\n", + " - **Hyperlinks**: Defined with the `href` attribute in `a` (anchor) tags.\n", + " - **Images**: Embedded using `img` tags with the `src` attribute. Note: `img` is self-closing." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%html\n", + "\n", + "\n", + "\n", + " \n", + " \n", + " Basic knowledge for web scraping.\n", + " \t\n", + "\n", + "\n", + "\n", + " \n", + "

About HTML\n", + "

\n", + "\n", + " \n", + "

\n", + "\n", + "

\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%html\n", + "\n", + "\n", + "\n", + " \n", + " \n", + " Basic knowledge for web scraping.\n", + " \t\n", + "\n", + "\n", + "\n", + " \n", + "

About HTML\n", + "

\n", + " \n", + "

Html (Hypertext markdown language) is the basic language to provide contents in the web. It is a tagged language. You can check more about it in World Wide Web Consortium.

\n", + " \n", + " \n", + "

One of the following rubberduckies is clickable\n", + "

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\n", + " \n", + " \n", + " \n", + " \n", + "

\n", + "" + ] + }, + { + "attachments": { + "image.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![image.png](attachment:image.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

Use Case: Three Sisters doc from Alice in Wonderland

" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "html_doc = \"\"\"\n", + "\n", + "The Dormouse's story\n", + "\n", + "

The Dormouse's story

\n", + "\n", + "

Once upon a time there were three little sisters; and their names were\n", + "Elsie,\n", + "Lacie and\n", + "Tillie;\n", + "and they lived at the bottom of a well.

\n", + "\n", + "

...

\n", + "\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "html_doc" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

Creating the Soup

" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# pip install bs4" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "from bs4 import BeautifulSoup" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![Cool GIF](https://i.pinimg.com/originals/e2/9e/f7/e29ef7444d2b503da0720e67ffee4002.gif)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# parse the element\n", + "soup = BeautifulSoup(html_doc, 'html.parser') # standard\n", + "soup" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "type(soup)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### `.prettify()`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Makes things pretty!!!\n", + "print(soup.prettify())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### `.title`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "soup.title\n", + "soup.title.string" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "title = soup.title.string\n", + "title" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "soup.title.parent\n", + "soup.title.name" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### `.p`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "soup.p" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "soup.p[\"class\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### `.a`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "soup.a" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "soup.find_all(\"a\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### `.find()`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "soup.find(id=\"link1\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### `.body`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "soup.body.parent.name" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "soup.find(\"p\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### `.find_all()`" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`find` and `findAll` (or its equivalent `find_all`) are methods used to search the soup tree for tags that match a certain criterion.\n", + "\n", + "1. **find**:\n", + " - Returns only the **first** tag that matches a given set of criteria.\n", + " - Useful when you know there's only one tag of interest or you only want the first occurrence.\n", + " - Example: If you have multiple `

` tags on a page and you use `soup.find('p')`, you'll get only the first `

` tag.\n", + "\n", + "2. **findAll (or find_all)**:\n", + " - Returns a **list** of tags that match the given criteria.\n", + " - Useful when you want to capture all occurrences of a particular tag or set of tags.\n", + " - Example: Using `soup.find_all('p')` will give you a list containing all `

` tags on the page.\n", + "\n", + "Here's a simple illustration:\n", + "\n", + "```html\n", + "\n", + " \n", + "

First paragraph.

\n", + "

Second paragraph.

\n", + "
Some div.
\n", + " \n", + "\n", + "```\n", + "\n", + "Using `find('p')` would return the \"First paragraph.\" while `find_all('p')` would return a list containing both \"First paragraph.\" and \"Second paragraph.\".\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A common web scraping task is to extract all urls from a website:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To get all content text from a website:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "p_tags = soup.find_all(\"p\")\n", + "len(p_tags)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "p_tags" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A common web scraping task is to extract all urls from a website:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### `.get()`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "soup.find_all(\"a\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for link in soup.find_all(\"a\"):\n", + " print(link.get(\"href\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### `.get_text()`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for link in soup.find_all(\"a\"):\n", + " print(link.get_text())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Access the attribute**: Once you have the element, use the `.get()` method to access the attribute value.\n", + "\n", + " ```python\n", + " link_url = link_element.get('href')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To search for HTML elements by class in a webpage using BeautifulSoup, you can also use the `find` and `find_all` methods.\n", + "\n", + "1. **Using `find` method to get the first matching element**:\n", + " \n", + " ```python\n", + " result = soup.find(class_='your-class-name')\n", + " ```\n", + "\n", + "2. **Using `find_all` method to get a list of all matching elements**:\n", + "\n", + " ```python\n", + " results = soup.find_all(class_='your-class-name')\n", + " ```\n", + " \n", + "Note that we are using the `class_` parameter because `class` is a reserved keyword in Python." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 💡 **Activity**: Your turn:\n", + "\n", + "Write code to print the following contents (not including the html tags, only human-readable text):\n", + "\n", + "1. All the \"fun facts\".\n", + "\n", + "2. The names of all the places.\n", + "\n", + "3. The content (name and fact) of all the cities (only cities, not countries!)\n", + "\n", + "4. The names (not facts!) of all the cities (not countries!)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "geography = \"\"\"\n", + "\n", + "\n", + " Geography\n", + "\n", + "\n", + "
\n", + "

London

\n", + "

London is the most popular tourist destination in the world.

\n", + "
\n", + "\n", + "
\n", + "

Paris

\n", + "

Paris was originally a Roman City called Lutetia.

\n", + "
\n", + "\n", + "
\n", + "

Spain

\n", + "

Spain produces 43,8% of all the world's Olive Oil.

\n", + "
\n", + "\n", + "\n", + "\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "soup = BeautifulSoup(geography, 'html.parser')\n", + "# print(soup.prettify())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# hint: all the fun facts\n", + "soup.find_all(\"p\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# CSS" + ] + }, + { + "attachments": { + "image.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![image.png](attachment:image.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**CSS selectors** are patterns used to select and manipulate one or more elements in an HTML or XML document. When web scraping with Python, CSS selectors can be used to target specific elements of interest within the page's content." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `select` method in BeautifulSoup allows you to pass a CSS selector and returns a list of elements matching that selector." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "1. **Tag Selector**: Targets elements by their tag name.\n", + " - `p`: selects all `

` elements.\n", + " - `soup.select(\"p\")` will retrieve all `

` elements\n", + "\n", + "2. **Class Selector**: Targets elements by their class attribute.\n", + " - `.classname`: selects all elements with `class=\"classname\"`.\n", + " - If class name has spaces, they must be changed by `.`\n", + " - `soup.select(\".classname\")`\n", + " - To combine both, we can have `soup.select(\"tagname.classname\")`\n", + "\n", + "3. **Descendant Selector**: Targets an element that is a descendant of another element.\n", + " - `div p`: selects all `

` elements inside a `

` element.\n", + " - `.class1 .class2`: selects all elements with class2 that is a descendant of an element with class1.\n", + " \n", + "4. **Attribute Selector**: Targets elements based on their attributes and values.\n", + " - `a[href]`: selects all `` elements with an `href` attribute.\n", + " - `a[href=\"https://www.example.com\"]`: selects all `` elements with an `href` value of \"https://www.example.com\"." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 💡 **Activity**: Using CSS selectors\n", + "\n", + "One. Step. At the time:\n", + "\n", + "- Let's learn first the syntax of css selectors playing this game: https://flukeout.github.io/\n", + "\n", + "**Everyone should reach level 6!**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 💡 **Activity**: Using HTML selectors" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "More exercises with solutions to practise: https://www.w3resource.com/python-exercises/BeautifulSoup/index.php" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from bs4 import BeautifulSoup\n", + "html_doc = \"\"\"\n", + "\n", + "\n", + "\n", + "An example of HTML page\n", + "\n", + "\n", + "

This is an example HTML page

\n", + "

\n", + "Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nunc at nisi velit,\n", + "aliquet iaculis est. Curabitur porttitor nisi vel lacus euismod egestas. In hac\n", + "habitasse platea dictumst. In sagittis magna eu odio interdum mollis. Phasellus\n", + "sagittis pulvinar facilisis. Donec vel odio volutpat tortor volutpat commodo.\n", + "Donec vehicula vulputate sem, vel iaculis urna molestie eget. Sed pellentesque\n", + "adipiscing tortor, at condimentum elit elementum sed. Mauris dignissim\n", + "elementum nunc, non elementum felis condimentum eu. In in turpis quis erat\n", + "imperdiet vulputate. Pellentesque mauris turpis, dignissim sed iaculis eu,\n", + "euismod eget ipsum. Vivamus mollis adipiscing viverra. Morbi at sem eget nisl\n", + "euismod porta.

\n", + "

Learn HTML from\n", + "w3resource.com

\n", + "

Learn CSS from\n", + "w3resource.com

\n", + "\n", + "\n", + "\"\"\"" + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "Main functions:\n", + " find\n", + " find_all\n", + " text\n", + " get_text\n", + " get\n", + " select" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "### Write a Python program to find the title tags from a given html document.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "### Write a Python program to retrieve all the paragraph tags from a given html document\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "### Write a Python program to get the number of paragraph tags of a given html document.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "### Write a Python program to extract the text in the first paragraph tag of a given html document.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "### Write a Python program to find the length of the text of the first

tag of a given html document.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "### Write a Python program to find the href of the first tag of a given html document.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "### Write a Python program to extract all the text from a given web page.\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![legtsgo](https://i.giphy.com/media/v1.Y2lkPTc5MGI3NjExZDhsYmRqMXh5M2t3Njh2dmQ2NW5zaTI4emw3azZpcGZqYzYxZ255cCZlcD12MV9pbnRlcm5hbF9naWZfYnlfaWQmY3Q9Zw/IwTWTsUzmIicM/giphy.gif)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

00 | Use case 1

" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# pip install requests" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# 📚 Basic libraries\n", + "import pandas as pd\n", + "\n", + "#❗New Libraries !\n", + "from bs4 import BeautifulSoup\n", + "import requests\n", + "\n", + "# ⚙️ Settings\n", + "pd.set_option('display.max_columns', None) # display all columns\n", + "import warnings\n", + "warnings.filterwarnings('ignore') # ignore warnings" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

01 | Data Extraction

" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's go to https://books.toscrape.com/, where we'll see a collection of books\n", + "Notice how each movie has the following elements:\n", + "\n", + "- Title\n", + "\n", + "- Price\n", + "\n", + "Our objective is going to be to scrape this information and store it in a pandas dataframe.\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Exploring Web Page Structures\n", + "\n", + "To inspect the underlying HTML of a web page, right-click anywhere on the page. \n", + "- Choose \"View Page Source\" in browsers like Chrome or Firefox.\n", + "- For Internet Explorer, choose \"View Source,\" and for Safari, select \"Show Page Source.\"\n", + "- (In Safari, if this option isn't visible, navigate to Safari Preferences, click on the Advanced tab, and enable \"Show Develop menu in menu bar.\")\n", + "\n", + "To embark on your web scraping journey, you just need to grasp **three foundational aspects** of HTML:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Fact 1: HTML is Built on Tags\n", + "\n", + "At its core, HTML is composed of content enveloped in ``. Tags come in various types:\n", + " * **Headings**: `

`, `

`, `

`, `

`...\n", + " * **Phrasing**: ``, ``, ``, ``, ``...\n", + " * **Embedded Content**: `