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Memorious

The solitary and lucid spectator of a multiform, instantaneous and almost intolerably precise world.

-- `Funes the Memorious <http://users.clas.ufl.edu/burt/spaceshotsairheads/borges-funes.pdf>`_,
Jorge Luis Borges

… image:: https://github.com/alephdata/memorious/workflows/memorious/badge.svg

memorious is a light-weight web scraping toolkit. It supports scrapers that
collect structured or un-structured data. This includes the following use cases:

• Make crawlers modular and simple tasks re-usable
• Provide utility functions to do common tasks such as data storage, HTTP session management
• Integrate crawlers with the Aleph and FollowTheMoney ecosystem
• Get out of your way as much as possible

Design

When writing a scraper, you often need to paginate through through an index
page, then download an HTML page for each result and finally parse that page
and insert or update a record in a database.

memorious handles this by managing a set of crawlers, each of which
can be composed of multiple stages. Each stage is implemented using a
Python function, which can be re-used across different crawlers.

The basic steps of writing a Memorious crawler:

1. Make YAML crawler configuration file
2. Add different stages
3. Write code for stage operations (optional)
4. Test, rinse, repeat

Documentation

The documentation for Memorious is available at
alephdata.github.io/memorious <https://alephdata.github.io/memorious/>_.
Feel free to edit the source files in the docs folder and send pull requests for improvements.

To build the documentation, inside the docs folder run make html

You’ll find the resulting HTML files in /docs/_build/html.