Data is the statistical and factual point of reference for business leaders to evaluate progress and make strategic decisions. With good data, companies can establish goals, baselines, and benchmarks. In amassing data to guide business decision-making, you might have to extract volumes of information from various sources on the web. But how do you penetrate websites and pull data without getting noticed and blocked? Python web scrapers are an excellent solution.
What Are the Benefits of Using Python for Web Scrapers?
Python is a developer’s favorite programming language, known for its simple code and syntax readability, enabling the expression of concepts in just a few lines of code. Python web scrapers are automated data extraction bots that pull considerable amounts of unstructured data from websites and store it in a well-thought-out format.
Business owners continually use web scrapers to collect and compare product information from e-commerce websites. Python web scraping bots can also intelligently penetrate online resources to gather email addresses for sending bulk emails. Other pertinent applications of Python web scraping include gathering opinions from social media posts, evaluating job listings, and researching news affecting stock prices. Python is the ideal programming language for developing web scrapers for the following reasons.
User-Friendly Design
Python is the most straightforward language for coding. You don’t need to be tech-savvy or have expert-level programming knowledge to write code for a web scraper. When coding with Python, there is no need for curly brackets and semicolons.
Additionally, Python syntax is easily readable, expressible, and quick to understand. Reading Python code is less messy, and identifying blocks is easy. In fact, when you dedicate time to coding with Python, you can develop a Python web scraper in days, even when you have no prior programming knowledge.
Extensive Web Scraping Library
Python has a large library to facilitate developing web scraping scripts. BeautifulSoup is one of the key libraries for parsing XML and HTML documents into tree structures to find and gather data. It has automatic encoding conversions and a Pythonic interface that supports working with web-extracted data. Selenium is an open-source web driver and a top Python library perfect for automatic logins, data deletion/adding, submissions, and alert handling.
The MechanicalSoup library for Python facilitates automated web scraping. You can use it to send cookies, submit forms, follow redirects, and follow links automatically. Lastly, LXML is a user-friendly and feature-rich library Python developers use to parse HTML and XML. It combines the user-friendliness of Python with superb element trees and high parsing speed.
Flexibility
One of the reasons developers continually stick to Python for web scrapers is its flexibility. You can easily write a script that does more than gather data. With the right resources, your scraper will be able to parse, import, and visualize data.
Budget-Friendly Setup
Aside from being a free, open-source language, Python applications also take less time to develop. Therefore, it’s a very budget-friendly option for startups and bootstrappers. The quicker your scraper can start gathering data, the faster you’ll reap the profits.
Proxy Compatibility
Many website owners are against the trend of content creators and businesses scraping their data. Although the intelligent counter-bot measures they have in place won’t block your scraping script if you only scrape websites once in a while, they will raise alarms when your bot sends hundreds of requests within seconds. Even the most reliable and robust Python web scraper will be flagged if you send thousands of requests daily for an extended period. When your bot is flagged, it’ll trigger CAPTCHAs and bans, which are hard to bypass. Collecting massive amounts of data from several web pages requires masking your computer’s identity to avoid getting flagged.
Luckily, proxies are easily programmable into Python apps. Using Python for web scraping with the aid of proxies creates an illusion that the requests come from different people in different locations, meaning the server won’t have any reason to flag your scraping bot.
Conclusion
Python is the programming language for data science experts and businesses that want to harvest large chunks of data with optimal simplicity. Today’s post intensifies your knowledge of Python and the many benefits it brings to web scraping scripts. Before writing your web scraper, research the best libraries and practices. That will promise a smooth journey.
