Scrapy vs Pyspider: Which Should You Use?

In this article, I’ll walk you through the differences between Scrapy and Pyspider in a simple way. So, let’s dive in and explore what makes these two web scraping frameworks unique and how they can help with your scraping goals.

No-Code Alternatives

I want to introduce some of the best no-code solutions for web scraping. Those will be perfect for you if you are not interested in writing your own code at all.

Bright Data — Enterprise-grade, scalable, structured data delivery.
Octoparse — Multi-tool for unstructured data extraction.
ParseHub — Beginner-friendly, interactive scraping workflows.
Apify — Pre-made templates, cloud-based scraping.
Web Scraper — Free browser extension with scheduling.
Import.io — Point-and-click, cloud-only premium scraping.
Simplescraper — Affordable, easy, unlimited concurrent scraping.

I am not affiliated with any of the scrapers mentioned above.

What Are Scrapy and Pyspider?

Scrapy

Scrapy is a Python-based web scraping framework designed for extracting structured data from websites. Whether you’re working on small-scale projects or enterprise-level tasks, Scrapy delivers efficiency, speed, and extensibility.

Key Features of Scrapy:

Powerful selectors using XPath and CSS.
Built-in pipelines for cleaning and organizing data.
Middleware support for proxies and headers to avoid detection.
Extensible architecture for third-party integrations like Scrapy-Splash (for JavaScript rendering).

Pyspider

Pyspider takes a task-based approach to web scraping and offers a web-based user interface for managing and monitoring scraping tasks. It also includes built-in JavaScript rendering through PhantomJS, though this dependency is now outdated.

Key Features of Pyspider:

User-friendly web interface for task management.
Built-in scheduler for automating tasks.
Real-time data monitoring.
Support for concurrency.

Key Differences Between Scrapy and Pyspider

To help you choose, let’s compare these tools across essential factors:

1. Ease of Use

Scrapy: Best suited for developers familiar with Python and command-line tools. While its learning curve is gentle for Python users, it lacks a graphical interface for managing tasks.
Pyspider: Offers a visual web interface, making it appealing to users who prefer managing tasks without heavy coding. However, its setup process can be complex.

2. Community and Maintenance

Scrapy: Backed by an active and large community, with regular updates to tackle modern scraping challenges.
Pyspider: Has not been actively maintained since 2018, making troubleshooting harder due to an inactive community.

3. JavaScript Support

Scrapy: Requires third-party tools like Scrapy-Splash or Selenium for handling JavaScript-heavy websites.
Pyspider: Provides built-in JavaScript rendering via PhantomJS, but reliance on deprecated software limits its viability.

4. Scalability

Scrapy: Designed for scalability, with features like request queuing, concurrency, and middleware support for enterprise projects.
Pyspider: While it supports concurrency and scheduling, its outdated technology makes it less reliable for scaling.

5. Anti-Bot Measures

Both tools help mitigate anti-bot detection with proxy rotation and header customization, but Scrapy has an edge thanks to its integration with advanced anti-bot solutions.

6. Popularity and Support

Scrapy: Boasts a large user base with extensive tutorials, plugins, and documentation.
Pyspider: Has a smaller user base and limited resources, which can be a barrier for new users.

In-Depth Comparison: Scrapy vs. Pyspider

When to Choose Scrapy

Advantages:

Actively maintained with frequent updates.
Beginner-friendly documentation and examples.
Flexible integration with external libraries.
Proven scalability for large projects.

Disadvantages:

Requires external tools for JavaScript rendering.
Limited to CLI for task management.

Best For: Developers seeking a scalable and robust framework for web scraping.

When to Choose Pyspider

Advantages:

User-friendly web interface.
Built-in support for JavaScript rendering.
Ideal for real-time monitoring and task-based scraping.

Disadvantages:

Outdated dependencies like PhantomJS.
Inactive community and no ongoing maintenance.
More complex setup compared to Scrapy.

Best For: Users prioritizing a graphical interface for task management, despite outdated technology.