Scrapy is an open source Python framework built specifically for web scraping by Zyte co-founders Pablo Hoffman and Shane Evans. Out of the box, Scrapy spiders are designed to download webpage data (HTML, JSON, XML…), parse and process the data and save it in any structured data format (e.g. CSV, JSON, XML).

Scrapy boasts a wide range of built-in extensions and middlewares designed for handling cookies and sessions as well as HTTP features like compression, authentication, caching, user-agents, robots.txt and crawl depth restriction. It is also very easy to extend through the development of custom middlewares or pipelines to your web scraping projects which can give you the specific functionality you require.

Scrapy is our open source web crawling framework written in Python. Scrapy is one of the most widely used and highly regarded frameworks of its kind; very powerful yet easy to use.
Spidermon is our battle-tested open source spider monitoring library for Scrapy.
DateParser is our library for parsing human-readable dates and times. Supports 18 languages.
A library for debugging machine learning classifiers and explaining their predictions.
Formasaurus figures out the type of an HTML form using machine learning. Is it a login, search, sign up, password recovery, contact form, etc.
W3lib provides a number of useful web-related functions for your web scraping projects.
ScrapyRT let’s you reuse your spider’s logic to extract data from web pages through a single HTTP request.
Queuelib lets you create disk-based queues in Python.
Parsel lets you extract data from XML/HTML documents using XPath or CSS selectors
CSS Selectors for Python
Library to populate items using XPath and CSS with a convenient API
Common interface for data container classes
A pure-Python robots.txt parser with support for modern conventions.
Extract price amount and currency symbol from a raw text string
Parse numbers written in natural language







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Standard and bespoke web data extraction projects