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.

Data Pipeline Example

Yatsenko et al., bioRxiv 2021

Getting Started

• Install with Conda

  conda install -c conda-forge datajoint
  

• Install with pip

  pip install datajoint
  

• Quick Start Guide

• Interactive Tutorials on GitHub Codespaces

• DataJoint Elements - Catalog of example pipelines for neuroscience experiments

• Contribute

  • Development Environment
  • Guidelines