Getting started with web scraping is quite simple, but you need to secure the right programs to make the process as efficient as possible. Python is always an excellent choice, as it equips you with all the necessary tools for building a useful web scraper.
As one of the simplest programming languages, Python is easy to understand and use. Unlike other languages, it’s object-oriented, meaning it’s much more practical and understandable.
In this article, you’ll learn why and how to use Python for web scraping purposes. Additionally, we’ll touch upon some of the most widely used libraries. Make sure to keep reading to find out more.
The term web scraping
Web scraping is a term used for collecting, structuring, and storing large amounts of data in one place. Namely, the public data is available to anyone on the internet. The web scraping programs automatically visit certain niche pages and collect their unstructured data. Next, the program also orders the data in a well-organized way and stores it in one place.
As a result, you gain access to large amounts of data that you can use for various purposes. Some of the most common web scraping uses include:
- Price collection – monitoring prices and tracking price changes of your competitors.
- Weather data observation – analyzing information and using it for research and development.
- Real estate listings collection – tracking available real estate offers and their price alterations.
- Contact gathering – gathering contact information, such as email addresses, to promote products.
- Much more – tracking news and current trends, automating business, job listings and recruitment, brand monitoring, and so on.
How Python fits in with scraping
As already mentioned, Python is one of the easiest and most efficient programming languages, so it’s no wonder it’s widely used for web scraping purposes. Because of its simplicity, you don’t have to be an advanced programmer to understand how web scraping works, which is why non-programmers often go for Python.
Besides the fact that Python is easy to learn and master, you can use this programming language for multiple web scraping tasks simultaneously and quickly. Also, you don’t need to learn complex and sophisticated coding.
So, you can collect large amounts of data for a very short time, and the creation of the program doesn’t require advanced programming skills. Additionally, Python can access the websites with both simple and dynamic web pages.
These properties make Python the ideal tool for web crawling and web scraping, which explains its popularity and wide use.
Benefits of using Python for scraping
While Python is used mainly for all types of web scraping, it offers plenty of benefits compared to some other programming languages. Here’s a list of the essential reasons why Python is widely used in web scraping:
- Python is easy to use – Other codes require much more complex orders and coding, where Python needs a much simpler version. For example, you don’t need semicolons or curly-braces, which already make it much easier to create and use a code.
- Python’s syntax is easily understandable – It’s much easier to go through Python’s syntax because it’s almost like reading plain English. It’s direct and easy to comprehend, which saves a lot of time. Also, you’ll make fewer mistakes, and even if you do, they’ll be more obvious and easy to spot.
- Python is made to save time – The whole point of web scraping is to obtain as much information as possible for less time. However, if you spend a lot of time making the code, you’re not saving that much time. With Python, you don’t have these troubles because the code requires minimal time input.
- Python has a large selection of libraries – With an extensive collection of libraries, you can do almost anything with Python. Use different libraries to crawl, gather, and manipulate collected data, all with one program. For example, you can check a Puppeteer tutorial for a smooth web scraping process.
Best Python libraries to use
Closely connected to the final point of Python’s benefits, let’s take a closer look at the best Python libraries used for web scraping.
- Python Requests Library – As a standard for making an HTTP request in Python, the Python requests library is a great way to further save time on complex codes and make them much simpler.
- BeautifulSoup – The BeautifulSoup library is excellent for parsing any HTML or XML files and extracting data easily.
- Pandas – If you want to manipulate the data and store it in the desired format, then the Pandas library is the right choice.
- Selenium – To provide automation for browser activities, use the Selenium library.
All in all, Python is a great way to complete various kinds of web scraping tasks. With numerous libraries and options, you can customize the code to best fit your scraping needs with minimal effort. Using different libraries, such as Python requests library, BeautifulSoup, Pandas, or Selenium, you can use one programming language for all activities and take advantage of Python’s core benefits. Don’t forget to check the Puppeteer tutorial to ensure a smooth web scraping process.