Python Web Scraper
Generates Python-based web scraping workflows with selectors and data fields for developers and researchers.
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About This Tool
Conceptual operation: The generated script fetches pages with requests, parses HTML with BeautifulSoup or lxml, applies the provided selectors to extract values, and performs type conversions before streaming records to JSON or CSV. It includes pagination handling, basic error handling, and optional retry logic. Advanced options allow login, proxy support, rate limiting, and selection of a headless browser for dynamic content when needed.
Who benefits: developers, data engineers, and researchers needing repeatable data collection across sites. Unique differentiators include domain-aware defaults, automated selector validation, and a ready-to-run scaffold that enforces a stable data shape. Typical use cases include product catalog extraction, price monitoring, and market research; outputs integrate with existing data pipelines and analytics workflows.
How to Use
- Provide inputs: seed_url, data_fields, selectors, and output format.
- Choose library and options (Requests + BeautifulSoup by default, or Scrapy/Playwright for dynamic pages).
- Generate a scraper skeleton and configuration.
- Run locally against a test page to verify selectors and data types.
- Export data to JSON or CSV and integrate into your workflow.
Frequently Asked Questions
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What libraries does the generated script use?
Can it handle dynamic pages?
How are selectors defined and validated?
What outputs are produced?
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