Scrapy vs Requests: Which is Better?

Scrapy and Requests are two popular Python libraries for web scraping, but they serve different purposes. Let’s compare them to help you decide which one to use.

1. Overview of Scrapy and Requests

What is Scrapy?

Scrapy is a powerful web scraping framework that allows users to extract data efficiently. It comes with built-in tools for handling crawling, data extraction, and storage.

Key Features of Scrapy:

✅ Asynchronous scraping (handles multiple requests in parallel).
✅ Built-in support for pagination, retries, and error handling.
✅ Allows exporting data to JSON, CSV, and databases.
✅ Supports middleware and pipeline processing.

What is Requests?

Requests is a lightweight HTTP library used for sending HTTP requests. It is simple and best suited for fetching data from static web pages.

Key Features of Requests:

✅ Easy to use (simple syntax for sending GET and POST requests).
✅ Can handle cookies, headers, and authentication.
✅ Works well for API requests and fetching static HTML pages.
✅ Supports session management.

2. Key Differences Between Scrapy and Requests

Feature	Scrapy	Requests
Type	Web scraping framework	HTTP request library
Speed	Faster (handles multiple requests asynchronously)	Slower (sends one request at a time)
Crawling	Handles multi-page crawling easily	Requires manual handling of pagination
Data Handling	Extracts and processes structured data	Returns raw HTML content
Ease of Use	Requires setting up spiders	Simple and beginner-friendly
JavaScript Handling	Needs integration with Selenium for JavaScript	Cannot handle JavaScript
Best for	Large-scale web scraping projects	Small-scale scraping and API requests

3. When to Use Scrapy vs. Requests?

Use Scrapy if:

✔️ You need to scrape multiple pages with structured data.
✔️ You want to process and store data efficiently.
✔️ The project requires handling pagination, retries, and middleware.
✔️ You are working on large-scale web scraping.

Use Requests if:

✔️ You only need to fetch HTML content or API responses.
✔️ The target website does not require crawling.
✔️ You are performing one-time data extraction.
✔️ You want a lightweight and easy-to-use solution.

4. Can You Use Both Together?

Yes! You can use Requests to fetch data and Scrapy to process and structure it. However, Scrapy already has a built-in request system, so in most cases, Scrapy alone is sufficient.

Example: Using Requests to Fetch HTML Content

pythonCopy codeimport requests
from bs4 import BeautifulSoup

url = "https://example.com"
response = requests.get(url)
soup = BeautifulSoup(response.text, "html.parser")

print(soup.title.text)  # Extracts the page title

Example: Using Scrapy for Web Crawling

pythonCopy codeimport scrapy

class MySpider(scrapy.Spider):
    name = "my_spider"
    start_urls = ["https://example.com"]

    def parse(self, response):
        title = response.css("title::text").get()
        print("Page Title:", title)

5. Conclusion: Which is Better?

🔹 Scrapy is better for complex and large-scale scraping, where speed and efficiency matter.
🔹 Requests is better for simple tasks, such as fetching HTML or making API calls.

👉 If you need advanced crawling, Scrapy is the way to go. If you just need to fetch a webpage, Requests is enough. 🚀

ApexDelight