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@datajoint

DataJoint

Open-source tools for computational data pipelines.

Welcome to DataJoint!

DataJoint is a Python framework for scientific data pipelines built on the Relational Workflow Model—a paradigm where your database schema is an executable specification of your workflow.

In this GitHub Organization, you will find the source code for DataJoint, as well as tutorials and example pipelines.

Data Pipeline Example

pipeline

Yatsenko et al., arXiv 2023

Getting Started

  • Install with pip

    pip install datajoint
  • Install with Conda

    conda install -c conda-forge datajoint
  • Documentation - Tutorials, how-to guides, explanations, and API reference

  • Migration Guide - Upgrading to DataJoint 2.0

  • DataJoint Elements - Reusable pipeline modules for neurophysiology experiments

DataJoint 2.0

DataJoint 2.0 is a major release with significant improvements. Existing pipelines require migration—see the Migration Guide for upgrade instructions.

Pinned Loading

  1. datajoint-python datajoint-python Public

    Relational data pipelines for the science lab

    Python 187 93

  2. datajoint-tutorials datajoint-tutorials Public

    Getting started materials for DataJoint - with Calcium Imaging, Electrophysiology, Machine Learning examples

    Jupyter Notebook 14 158

  3. element-array-ephys element-array-ephys Public

    DataJoint Element for Neuropixels analysis with Kilosort

    Jupyter Notebook 8 40

  4. element-calcium-imaging element-calcium-imaging Public

    DataJoint Element for multi-photon calcium imaging analysis with CaImAn, Suite2p, and EXTRACT

    Jupyter Notebook 15 47

Repositories

Showing 10 of 93 repositories