The Anti-bot Solution to Scrape Everything? Get Your Free API Key! 😎

Scrapy vs. Requests: Which One Should You Choose?

February 28, 2024 · 3 min read

Are you just starting with web scraping and want to know the best scraping tool between Scrapy and Requests? Each has specific scenarios where it excels.

In this article, you'll see how Scrapy compares with the Requests library so you can decide what library to choose in various cases.

Scrapy vs Requests: Which Is Best?

Scrapy is a dedicated web scraping and crawling framework in Python. It features all the tools and middleware for making requests, organizing and storing the extracted data. Scrapy is suitable for large-scale content extraction. 

The Requests library is a Python HTTP client for sending requests to websites and APIs, and it only works with parser libraries like BeautifulSoup. Its job in web scraping is to retrieve a website's HTML content and make it available to HTML parsing libraries like BeautifulSoup for data extraction.

Use Scrapy for web scraping if your project is large-scale and involves complex tasks like crawling. The Requests library works best for simple data extraction and is one of the best HTTP clients to pair with HTML parsers like BeautifulSoup.

Consideration Requests Scrapy
HTTP requests Yes Yes
Best for Simple web scraping Simple to complex web scraping
Ease of use Very easy to use Steeper learning curve
Speed Good Good
Crawl management Not built-in and technical to implement Built-in
Parsing No. Requires parsing libraries like BeautifulSoup Yes
Popularity Good Good
Avoid getting blocked Request header customization, proxy Request header customization, proxy middleware
Frustrated that your web scrapers are blocked once and again?
ZenRows API handles rotating proxies and headless browsers for you.
Try for FREE

Let's dive into more detailed comparisons in the next sections.

Scrapy Outshines Requests in Large-Scale Web Scraping

Scrapy's built-in ability to send requests, parse HTML, and scrape multiple pages concurrently makes it superior to the Requests library for large-scale web scraping.

Python's Requests is only suitable for simple web scraping tasks, and it relies on external libraries like BeautifulSoup for HTML parsing.

Requests Simplifies Basic Web Scraping

The Requests library lets you retrieve HTML content from web pages with a few code lines, making them available to parsing libraries like BeautifulSoup for light web scraping.

You can also use Scrapy for basic web scraping. However, its complex development requirements can complicate simple data extraction.

Scrapy is Better to Automate Repetitive Tasks

Scrapy has data processing pipelines and supports concurrency and request prioritization. It also integrates with external tools like Scrapyd for crawl scheduling. All these make it a perfect tool for automating repetitive scraping tasks.

The Requests library is limited to sending HTTP requests and lacks the requirements to automate content extraction.

Requests Is Much Easier to Learn

Python's Requests is straightforward and only requires a few code lines to send requests and obtain responses. This makes learning Requests relatively easy. 

Scrapy's extra setup requirements and complex code architecture give it a steeper learning curve than the Requests library.

Requests Is Faster Than Scrapy

Scrapy inherently handles every scraping step, including sending requests, obtaining responses, and parsing HTML. This introduces extra overhead into its workflow and slows it down. 

The Requests library is faster than Scrapy since it only accounts for sending requests and getting responses.

We performed a 100-iteration benchmark to compare the speed of Scrapy and Requests for sending a basic request to the same website. The Requests library was faster at 1.55 seconds, while Scrapy came behind at 2.84 seconds.

See the graphical representation of the benchmark below (from the fastest to the slowest):

Best Choice to Avoid Getting Blocked While Scraping

Many websites will use anti-bots to detect and block your scraper, and you need to bypass them to get the data you want.

Scrapy and Requests have ways of avoiding anti-bot detection. Both tools allow you to customize the Request headers and add proxies to your requests. You can even use middleware to enable JavaScript support in Scrapy and mimic human behavior.

However, you need more than these methods to bypass advanced anti-bots. The best way to scrape without getting blocked is to use web scraping APIs like ZenRows. 

The Requests library lets you retrieve a page's HTML through the ZenRows API, helping you to bypass anti-bot detection and scrape any website without getting blocked. ZenRows also integrates perfectly with Scrapy.

Conclusion

This article shows that Scrapy is superior to Requests in functionality, specifically in its ability to automate tasks and perform complex scraping operations. The Requests library excels for its easy learning curve and speed at obtaining a page's HTML content.

With that said, most websites will still block your scraper regardless of the tool you use. Bypass all anti-bot detection with ZenRows and scrape any website without getting blocked. Try ZenRows for free!

Did you find the content helpful? Spread the word and share it on Twitter, or LinkedIn.

Frustrated that your web scrapers are blocked once and again? ZenRows API handles rotating proxies and headless browsers for you.
Try for FREE

The easiest way to do Web Scraping

From Rotating Proxies and Headless Browsers to CAPTCHAs, a single API call to ZenRows handles all anti-bot bypass for you.