Memorious

February 2, 2026 · View on GitHub

Docs memorious4 on pypi PyPI Downloads PyPI - Python Version Python test and package pre-commit Coverage Status AGPLv3+ License Pydantic v2

Memorious

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

-- Funes the Memorious, Jorge Luis Borges

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 reusable
  • 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

memorious is part of the OpenAleph suite but can be used standalone as well.

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 reused 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 docs.investigraph.dev/lib/memorious. Feel free to edit the source files in the docs folder and send pull requests for improvements.

To serve the documentation locally, run mkdocs serve

memorious, (C) -2024 Organized Crime and Corruption Reporting Project

memorious, (C) 2025 Data and Research Center – DARC

memorious4, (C) 2026 Data and Research Center – DARC

memorious4 is licensed under the AGPLv3 or later license.

Prior to version 4.0.0, memorious was released under the MIT license.

see NOTICE and LICENSE