Yuliia Barabash - Data Harvest: Unlocking Insights with Python Web Scraping | PyData Global 2023

Scrapy is a powerful Python framework for web scraping that uses asynchronous architecture, allowing concurrent processing of requests without waiting for responses

Key Scrapy features include:

• Built-in export to JSON, XML, CSV
• Pipeline system for processing/cleaning data
• Middleware for custom request/response handling
• Integration with cloud storage (S3, Google Cloud)
• Support for proxies and user-agent customization

Two main selector types are available in Scrapy:

• CSS selectors (similar to CSS styling syntax)
• XPath selectors (for traversing HTML elements)

Project structure includes:

• Spiders folder for crawler definitions
• Pipeline files for data processing
• Settings for configuration
• Middleware for request/response handling

Best practices for web scraping:

• Respect website policies and rate limits
• Consider timing of scraping (off-peak hours)
• Use proper user agents and headers
• Handle failed requests and errors
• Implement concurrent processing carefully

Data processing capabilities:

• Clean and validate extracted data
• Transform data structure
• Store in databases
• Export to multiple formats
• Pipeline for sequential processing

Can be extended with plugins for:

• JavaScript rendering (Selenium, Playwright)
• Authentication handling
• Custom middleware
• Database integration
• Cloud deployment