A relational data pipeline framework.
Project description
Welcome to DataJoint for Python!
DataJoint for Python is a framework for scientific workflow management based on relational principles. DataJoint is built on the foundation of the relational data model and prescribes a consistent method for organizing, populating, computing, and querying data.
DataJoint was initially developed in 2009 by Dimitri Yatsenko in Andreas Tolias' Lab at Baylor College of Medicine for the distributed processing and management of large volumes of data streaming from regular experiments. Starting in 2011, DataJoint has been available as an open-source project adopted by other labs and improved through contributions from several developers. Presently, the primary developer of DataJoint open-source software is the company DataJoint (https://datajoint.com).
Data Pipeline Example
Getting Started
-
Install with Conda
conda install -c conda-forge datajoint
-
Install with pip
pip install datajoint
-
Interactive Tutorials on GitHub Codespaces
-
DataJoint Elements - Catalog of example pipelines for neuroscience experiments
-
Contribute
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
Built Distribution
Hashes for datajoint-0.14.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 87773eb365a920b61df7c60dd154d0f28f11fb8944b0950218abe8c9878a789a |
|
MD5 | f0bd460951128a61006350e8a51f6e1b |
|
BLAKE2b-256 | fa44bd41ce34c7546556fe5814b0b9c2a7d232227c5dd5a341818133068ab48c |