Skip to main content

A minimalistic, recursive web crawling library for Python.

Project description

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

Funes the Memorious, Jorge Luis Borges

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. 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.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

memorious-2.6.5.tar.gz (41.0 kB view details)

Uploaded Source

Built Distribution

memorious-2.6.5-py2.py3-none-any.whl (52.4 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file memorious-2.6.5.tar.gz.

File metadata

  • Download URL: memorious-2.6.5.tar.gz
  • Upload date:
  • Size: 41.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.7

File hashes

Hashes for memorious-2.6.5.tar.gz
Algorithm Hash digest
SHA256 5690d32309cc7a269190bd157df7b6a4c9f9f9e896367ea1ba02d483c211e76d
MD5 69beecfbb546ca35eff82b47771f8ef6
BLAKE2b-256 508597ec7c1f8bdd90f73347b3972a5b6c663f5995e7a49e4cd3f73c46af8510

See more details on using hashes here.

Provenance

File details

Details for the file memorious-2.6.5-py2.py3-none-any.whl.

File metadata

  • Download URL: memorious-2.6.5-py2.py3-none-any.whl
  • Upload date:
  • Size: 52.4 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.7

File hashes

Hashes for memorious-2.6.5-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 5997259e0e5e3e92012bd87d506dfd947f8900c53e8c5717696169a523c48780
MD5 3c64862426bff79ca7744238b1057dcd
BLAKE2b-256 70dcf8543dbc42b92a041bfa59a5aa57e61e9a8906cd8bde1bcbe6fcca51dbe1

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page