graspologic
graspologic is a package for graph statistical algorithms.
- Overview
- Documentation
- System Requirements
- Installation Guide
- Contributing
- License
- Issues
- Citing
graspologic
Overview
A graph, or network, provides a mathematically intuitive representation of data with some sort of relationship between items. For example, a social network can be represented as a graph by considering all participants in the social network as nodes, with connections representing whether each pair of individuals in the network are friends with one another. Naively, one might apply traditional statistical techniques to a graph, which neglects the spatial arrangement of nodes within the network and is not utilizing all of the information present in the graph. In this package, we provide utilities and algorithms designed for the processing and analysis of graphs with specialized graph statistical algorithms.
Documentation
The official documentation with usage is at https://graspologic-org.github.io/graspologic/latest
Please visit the tutorial section in the official website for more in depth usage.
System Requirements
Hardware requirements
graspologic package requires only a standard computer with enough RAM to support the in-memory operations.
Software requirements
OS Requirements
graspologic is tested on the following OSes:
- Linux x64
- macOS x64
- Windows 10 x64
And across the following x86_64 versions of Python:
- 3.9
- 3.10
- 3.11
- 3.12
If you try to use graspologic for a different platform than the ones listed and notice any unexpected behavior,
please feel free to raise an issue. It's better for ourselves and our users
if we have concrete examples of things not working!
Installation Guide
Install from pip
pip install graspologic
Install from Github
git clone https://github.com/graspologic-org/graspologic
cd graspologic
python3 -m venv venv
source venv/bin/activate
pip install .
Contributing
We welcome contributions from anyone. Please see our contribution guidelines before making a pull request. Our issues page is full of places we could use help! If you have an idea for an improvement not listed there, please make an issue first so you can discuss with the developers.
License
This project is covered under the MIT License.
Issues
We appreciate detailed bug reports and feature requests (though we appreciate pull requests even more!). Please visit our issues page if you have questions or ideas.
Citing graspologic
If you find graspologic useful in your work, please cite the package via the GraSPy paper
Chung, J., Pedigo, B. D., Bridgeford, E. W., Varjavand, B. K., Helm, H. S., & Vogelstein, J. T. (2019). GraSPy: Graph Statistics in Python. Journal of Machine Learning Research, 20(158), 1-7.
3 maintainers
Release files for graspologic 3.4.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| graspologic-3.4.4.tar.gz | 5.1 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| graspologic-3.4.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.3 MB
Release files / graspologic-3.4.4.tar.gz
| Download URL | graspologic-3.4.4.tar.gz |
|---|---|
| Size | 5.1 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
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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 Sep 8, 2025.
Transparency logRelease files / graspologic-3.4.4-py3-none-any.whl
| Download URL | graspologic-3.4.4-py3-none-any.whl |
|---|---|
| Size | 5.2 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
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 Sep 8, 2025.
Transparency log
