Skip to main content

Data standard, storage and retrieval for structured and unstructured FollowTheMoney data

Project description

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

ftm-lakehouse

ftm-lakehouse provides a data standard and archive storage for leaked data, private and public document collections. The concepts and implementations are originally inspired by mmmeta and Aleph's servicelayer archive.

ftm-lakehouse acts as a multi-tenant storage and retrieval mechanism for structured entity data, documents and their metadata. It provides a high-level interface for generating and sharing document collections and importing them into various search and analysis platforms, such as OpenALeph, ICIJ Datashare or Liquid Investigations

Installation

Requires python 3.11 or later.

pip install ftm-lakehouse

Documentation

openaleph.org/docs/lib/ftm-lakehouse

Development

This package is using poetry for packaging and dependencies management, so first install it.

Clone this repository to a local destination.

Within the repo directory, run

poetry install --with dev

This installs a few development dependencies, including pre-commit which needs to be registered:

poetry run pre-commit install

Before creating a commit, this checks for correct code formatting (isort, black) and some other useful stuff (see: .pre-commit-config.yaml)

Testing

ftm-lakehouse uses pytest as the testing framework.

make test

License and Copyright

ftm-lakehouse, (c) 2024 investigativedata.io

ftm-lakehouse, (c) 2025 Data and Research Center – DARC

ftm-lakehouse is licensed under the AGPLv3 or later license.

Project details


Download files

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

Source Distribution

ftm_lakehouse-0.4.0.tar.gz (91.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ftm_lakehouse-0.4.0-py3-none-any.whl (124.4 kB view details)

Uploaded Python 3

File details

Details for the file ftm_lakehouse-0.4.0.tar.gz.

File metadata

  • Download URL: ftm_lakehouse-0.4.0.tar.gz
  • Upload date:
  • Size: 91.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.4.1 CPython/3.13.5 Linux/6.12.74+deb13+1-amd64

File hashes

Hashes for ftm_lakehouse-0.4.0.tar.gz
Algorithm Hash digest
SHA256 f7d278f3e0e04e1a1d40f1fad69a13d33f0a61d849296534d60aa477936fd83f
MD5 d0f84e7b844e88220f7d534f2e2840f3
BLAKE2b-256 6249c76ad4d2e3a6d5f4f8cd4c3d8d16e5b60693926793299140866260dae2d8

See more details on using hashes here.

File details

Details for the file ftm_lakehouse-0.4.0-py3-none-any.whl.

File metadata

  • Download URL: ftm_lakehouse-0.4.0-py3-none-any.whl
  • Upload date:
  • Size: 124.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.4.1 CPython/3.13.5 Linux/6.12.74+deb13+1-amd64

File hashes

Hashes for ftm_lakehouse-0.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 dd938e7c5c65dd3dc3cccd6b3cb13805c310b50725241337875be8c337648ab9
MD5 94176d06354806e33941fcf026ee2cb3
BLAKE2b-256 ed5ce2c9332a26809ca8077a4785f1cc34e4704ff4b4109e6a6bd009169e5d2b

See more details on using hashes here.

Supported by

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