Web Scraper Python

This tool provides a Python-based scraping workflow that accepts a target URL, a map of fields to selectors, and export settings to produce a structured dataset. It supports static pages via HTTP requests and can render JavaScript-driven pages when the optional headless browser is enabled. Typical uses include collecting product catalogs, pricing data, and publication metadata across multiple pages for analysis.
During execution, the tool normalizes URLs, applies CSS or XPath selectors to extract field values, and aggregates results across pages. It produces a list of records with consistent field keys and supports deduplication by a chosen key. Relative URLs are resolved to absolute URLs to ensure portability in downstream systems; outputs can be JSON, CSV, or newline-delimited JSON.
Who benefits: researchers, market researchers, data engineers, and product teams performing competitive intelligence, cataloging, or data enrichment. Its Python-based foundation enables straightforward integration with existing pipelines and cloud storage, while optional rendering expands coverage beyond static HTML. The tool emphasizes reproducibility, with consistent field mappings and export formats across runs.
Unique value includes robust URL handling, clear field mappings, and structured exports designed for automation. It enforces basic politeness controls and can respect robots.txt when enabled. It is not a full browser, cannot bypass paywalls or login walls, and requires appropriate permissions for target sites.