Today, web scraping is one of the best, most effective data harvesting methods. It allows you to quickly browse the web, target top content across multiple web pages, and extract data to save in a preferable format.
Businesses of all sizes rely on web scraping to gather valuable data to beat their competitors, adjust their pricing, and expand operations into new markets. Since technology is constantly advancing, web scraping tools are evolving with it.
The internet offers several programming languages for developing the most advanced web scraping tools. You can use them to accomplish any scraping goal and extract any type of data.
Even if a target website is in a restricted area, you can combine your scraping tools with various proxies, such as proxy Mexico (find more info), to bypass geo-restrictions and access the data you need. Python is one of the best languages for web scraping. Today, we’ll discuss what Python is and how it can help with web scraping.
What is Python?
Python is one of the most popular programming languages on the web. It’s a high-level, general-purpose coding language that you can apply to a range of operations online, such as:
- Data scraping
- Web browsing
- Web page targeting
- Content crawling
- Data harvesting
Python excels at streamlining web scraping operations at any scale. It makes scraping bots virtually undetectable and can bypass any restriction and anti-scraping measures. Because of that, Python is the most popular choice for launching large-scale automated data scraping operations, especially when combined with other tactics, like in our proxy Mexico example.
What makes Python so unique and valuable is access to framework libraries such as Scrapy and Beautiful Soup. These top-grade libraries can execute almost any web scraping and data extraction process quickly and efficiently.
Python web scraping
Python is perfect for web scraping and data extraction because it offers increased flexibility and more effective database management. Since it provides unprecedented levels of scraping and crawling efficiency, you can use it to avoid detecting and blocking mechanisms while extracting data from the web.
Although it comes with a relatively easy learning curve, most coders use Python to upgrade their coding skills. Python allows for automating complex web scraping processes related to crawling the web, targeting web pages, filtering content, and replicating data.
It allows you to develop different types of scraping bots to perform various digitized operations. However, the true strength of Python in web scraping is in extracting data from HTML pages. It does so by targeting and copying HTML code from the web pages.
However, many businesses choose Python for web scraping due to the option to store the extracted data in a preferred database format. Since it can replicate website content, Python allows you to scrape the needed data across several locations on the web.
That’s why companies prefer Python for web scraping, as it allows them to conduct thorough market research, auto-fetch the information they need, and monitor competitors.
Advantages of data scraping with Python
Let’s review some of the advantages of using Python in web scraping.
Diverse libraries
Python provides access to extremely powerful libraries such as Scrapy, Beautiful Soup, LXML, and Selenium. Since you need coding scripts to extract data from the web, Selenium automates repetitive script processes such as scrolling, clicking, browsing, and targeting content on web pages.
LXML does almost the same thing as Selenium with one difference – it automates processes related to scraping HTML and XML files. On the other hand, Beautiful Soup is an excellent option for XML and HTML parsing. It accesses XML and HTML files and parses them to make the extraction process easy and more time-efficient.
Easy to use
Since Python has an easy learning curve, it makes coding easy. Compared to C++ or PHP, Python code doesn’t need curly brackets or semicolons to work. More importantly, it’s much easier to navigate Python syntax and locate different blocks in the code.
Saves time
Python simplifies the web scraping process by automating most of the repetitive tasks. It helps you save time on harvesting vast amounts of data.
Large Python community
One of the best things about Python is its large and active online community. You can talk to other developers, get the latest updates, learn new scraping techniques, and receive valuable insights on the best code writing practices.
Conclusion
Python makes web scraping as simple as possible. It provides top features and framework libraries for automating web scraping processes. While you can use it for virtually every web scraping process, Python excels at extracting data in the desired format from HTML and XML pages.
You can use it to create your database, replicate website content across multiple locations on the web, gather data from several sources, and more. Its easy learning curve makes it simple to write in, clear to read, and easy to navigate.
