BioCypher
| License |  |
Python |  |
| Package |    |
Build status |   |
| Tests |  |
Docker |   |
| Development |     |
Contributions |    |
❓ Description
Knowledge graphs (KGs) are an approach to knowledge representation that uses graph structure to facilitate exploration and analysis of complex data, often leveraging semantic information. They are popular in many research areas, including the life sciences, due to their versatile use, for instance in data storage, integration, reasoning, and more recently in artificial intelligence. The creation of KGs is a complex task; BioCypher helps you in creating and maintaining your own KG. For more overview, usage notes, and a tutorial, read the docs here.
📖 Documentation
Tutorial and developer docs at https://biocypher.org. For a quickstart into your own pipeline, you can refer to our project template, and for an overview of existing and planned adapters for resources and outputs, as well as other features, visit our GitHub Project Board.
⚙️ Installation / Usage
Install the package from PyPI using pip install biocypher. For Neo4j online mode
support, install with pip install biocypher[neo4j]. More comprehensive
installation and configuration instructions can be found
here.
Exemplary usage of BioCypher to build a graph database is shown in our tutorial and the various pipelines we have created. You can find these on the Components Project Board.
🤝 Getting involved
We are very happy about contributions from the community, large and small! If you would like to contribute to BioCypher development, please refer to our contribution guidelines. :)
If you want to ask informal questions, talk about dev things, or just chat, please join our community at https://biocypher.zulipchat.com!
Imposter syndrome disclaimer: We want your help. No, really. There may be a little voice inside your head that is telling you that you're not ready, that you aren't skilled enough to contribute. We assure you that the little voice in your head is wrong. Most importantly, there are many valuable ways to contribute besides writing code.
This disclaimer was adapted from the Pooch project.
✍️ Citation
The BioCypher paper has been peer-reviewed in Nature Biotechnology. It is available as a self-archived version on Zenodo, online version here. Before, it was available as a preprint at https://arxiv.org/abs/2212.13543.
Acknowledgements
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 965193 for DECIDER and No 116030 for TransQST.
Metadata
Release files for biocypher 0.17.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| biocypher-0.17.0.tar.gz | 5.1 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| biocypher-0.17.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 5.3 MB
Release files / biocypher-0.17.0.tar.gz
| Download URL | biocypher-0.17.0.tar.gz |
|---|---|
| Size | 5.1 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
53a77bc3c1ab06560c329bc263bca246884966031a05ec097b12921d60f96053
|
|
BLAKE2b-256 checksum How to use checksums |
281382af4192463f3b14aaca0aae4182f937ab3289efc2fc95f41d3b9e66a731
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Aug 18, 2026.
Transparency logRelease files / biocypher-0.17.0-py3-none-any.whl
| Download URL | biocypher-0.17.0-py3-none-any.whl |
|---|---|
| Size | 137.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
1064b2e7419c313624533c3eea17c6f10bdce2eea7603ae1e3908c7c7b476a13
|
|
BLAKE2b-256 checksum How to use checksums |
8a91a38c67e3dfdc74c56e5845a8aaa7d16d11968ca7d3d013f1e87d7e3e3039
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Aug 18, 2026.
Transparency log
