DataJoint for Python
DataJoint is a framework for scientific data pipelines based on the Relational Workflow Model — a paradigm where your database schema is an executable specification of your workflow.
- Tables represent workflow steps — Each table is a step in your pipeline
- Foreign keys encode dependencies — Parent tables must be populated before child tables
- Computations are declarative — Define what to compute; DataJoint handles when
- Results are immutable — Full lineage and reproducibility
Documentation: https://docs.datajoint.com
📘 Upgrading from legacy DataJoint (pre-2.0)? See the Migration Guide for a step-by-step upgrade path.
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Installation
pip install datajoint
or with Conda:
conda install -c conda-forge datajoint
Example Pipeline
Cite DataJoint: Yatsenko et al., 2026 — RRID: SCR_014543
Resources
- Documentation — Complete guides and reference
- Tutorials — Learn by example
- How-To Guides — Task-oriented guides
- API Reference — Complete API documentation
- Migration Guide — Upgrade from legacy versions
- DataJoint Elements — Example pipelines for neuroscience
- GitHub Discussions — Community support
Contributing
See CONTRIBUTING.md for development setup and guidelines.
Release files for datajoint 2.3.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| datajoint-2.3.3.tar.gz | 524.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| datajoint-2.3.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 787.5 kB
Release files / datajoint-2.3.3.tar.gz
| Download URL | datajoint-2.3.3.tar.gz |
|---|---|
| Size | 524.8 kB |
| Tags | Source |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
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twine/7.0.0 CPython/3.10.21
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Release files / datajoint-2.3.3-py3-none-any.whl
| Download URL | datajoint-2.3.3-py3-none-any.whl |
|---|---|
| Size | 262.7 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.21
|