What are the Requirements for Web Scraping using Python?

What is Web Scraping

Web scraping is a data extraction technique where automated scripts or tools retrieve and parse the HTML or other markup language of web pages to extract specific information. This process involves sending HTTP requests to target websites, retrieving the page content, and utilizing parsing techniques to isolate and collect relevant data elements such as text, images, or links. Web scraping is employed for various purposes, including data analysis, research, or aggregating information from multiple sources. However, it should be conducted ethically and in accordance with the terms of service of the targeted websites to avoid legal and ethical concerns.

In a nutshell, the meaning of web scraping is extracting data from a website.

How Python can be Used for Web Scraping

Python is widely used for web scraping due to its simplicity, rich libraries, and powerful tools. Developers often leverage libraries such as BeautifulSoup and lxml to parse HTML content easily, while the requests library is employed for making HTTP requests to websites. Additionally, frameworks like Scrapy provide a more structured approach for building web scrapers. The combination of these tools allows developers to send requests to web pages, retrieve HTML content, and extract desired data efficiently. Python's readability and ease of use make it a popular choice for web scraping projects, enabling developers to create effective scripts for data extraction, analysis, and automation. However, it's essential to be mindful of ethical considerations and comply with the terms of service of the targeted websites to ensure responsible and legal use of web scraping with Python.

Tools and Libraries Available for Web Scraping

The most useful libraries and frameworks available in Python for web scraping are:

requests:
BeautifulSoup:
lxml:
Scrapy:
Selenium:
Requests-HTML:
MechanicalSoup:
PyQuery:
Urllib:

How Web Scraping Works

Web scraping works by sending an HTTP request to a targeted website, retrieving the HTML content of the webpage, parsing the HTML to identify and extract specific data elements, and then storing or using the extracted information. Tools and libraries like requests, BeautifulSoup, and lxml in Python are commonly employed for automating this process. Ethical considerations and adherence to a website's terms of service are crucial to ensure responsible and legal web scraping.

What are the requirements for web scraping using Python?

Install Python Web Scraping Libraries

To install Python web scraping libraries, open a terminal or command prompt and use pip, the Python package installer. Execute the following commands to install commonly used web scraping libraries: pip install requests for making HTTP requests, pip install beautifulsoup4 for HTML parsing with BeautifulSoup, pip install lxml for high-performance XML and HTML processing, pip install scrapy for a comprehensive web scraping framework, and pip install selenium for browser automation. Ensure Python and pip are installed on your system, and if you're working within a virtual environment, activate it before running these commands to keep your project dependencies isolated.

Python Web Scraping with Requests

To perform web scraping in Python, use an HTTP request library (e.g. requests) along with a parser library (e.g. BeautifulSoup) or use a browser-based library (e.g. Selenium).

I have a video tutorial to teach you how to do web scraping with the Python requests library (an alternative is the requests-HTML library).

Essentially all you need is to:

Install python

Install the requests library

1	$ pip install requests

Run this code to fetch a web page.

# import the request library

import requests

# Define your URL

url = 'https://crawler-test.com/'

# Fetch the page

response = requests.get(url)

# Show the Response

response.text

The output is the HTML of the web page in unicode (text) format.

Python Web Scraping with BeautifulSoup

To parse the HTML of the page using BeautifulSoup in Python, install the library, fetch the HTML with an HTTP request library and parse the HTML using the BeautifulSoup() class on the HTML.

First, Install the BeautifulSoup library.

1	$ pip3 install beautifulsoup4

After, import bs4, parse the page with it and use the BeautifulSoup methods to get various HTML tags from the page.

# Fetch the HTML

import requests

url = 'https://crawler-test.com/'

response = requests.get(url)

# Import BeautifulSoup

from bs4 import BeautifulSoup

# Parse the HTML

soup = BeautifulSoup(response.text, 'html.parser')

# Extract any HTML tag

soup.find('title')

Python Web Scraping with lxml

In Python, the lxml library is a parsing library that can be used to extract information from HTML or XML. The lxml library can be used as an alternative to the BeautifulSoup library.

To use the lxml library in Python, fetch the page with the requests library and parse the HTML with the html.fromstring() method.

Install the lxml library with pip.

$ pip install lxml

Parse the textual representation of HTML with the fromstring() method.

import requests

from lxml import html

r = requests.get()

tree = html.fromstring(r.text)

The advantage of lxml over BeautifulSoup is that it is possible to use XPath expressions to extract data.

1 2	# Parse with XPath in lxml html.xpath('//*[@class="panel-header"]')

Python Web Scraping with Requests-HTML

The requests-HTML library is an HTML parser that lets you use CSS Selectors and XPath expressions to extract the information that you want from a web page. It also offers the capacity to perform JavaScript Rendering.

To scrape a web page in Python with the requests-HTML library, first install the required Python libraries and then use the HTMLSession() class initialize the session object. Then, perform a GET request using the .get() method.

Install libraries

pip install requests requests-HTML urlparse4

Scrape the website using HTMLSession() in Python.

# Scrape website with Requests-HTML

from requests_html import HTMLSession

session = HTMLSession()

r = session.get('https://crawler-test.com/')

r.html.find('title')[0].text

You may get the following error if you are using a Jupyter Notebook, in that case use the AsyncHTMLSession.

RuntimeError: Cannot use HTMLSession within an existing event loop.

Python Web Scraping with Selenium

To use the Selenium web browser application to perform Web Scraping in Python, install the required library and the web driver, instantiate the webdriver module and use the get() method to open the web browser to the web page that you want to extract information from.

Selenium works by opening a browser and loads a web page, just like you would do when you browse the web. This way, it renders the page so that you can scrape anything on it. Selenium is incredible to automate any browser activities.

To use Selenium in Python Web Scraping, you need to install:

1	$ pip3 install webdriver-manager Selenium

And then run this code to show the H1 of the page for example.

from selenium import webdriver

from selenium.webdriver.chrome.service import Service

from webdriver_manager.chrome import ChromeDriverManager

from selenium.webdriver.common.by import By

# Install Webdriver

driver = webdriver.Chrome(service=Service(ChromeDriverManager().install()))

# Fetch page

driver.get('https://crawler-test.com/')

try:

# Get the span element

elem = driver.find_element(By.TAG_NAME, 'h1')

# Show scraped content

print(elem.text)

except Exception as e:

print('There was an error', e)

# Quit browser when done

driver.quit()

Python Web Scraping with Scrapy

To scrape web pages with Scrapy in Python, create your own custom web crawler in Python. You will need to install the required library and use either the scrapy shell or the Selector() object.

First, install the required Python libraries.