# graphing
This Python library provides several graphing-related utilities that can be used to apply graph theory concepts and graph algorithms to a variety of problems.
## Getting Started This library is available for use on PyPI here: [https://pypi.org/project/graphing/](https://pypi.org/project/graphing/)
For local development, do the following. - Clone this repository. - Set up and activate a Python3 virtual environment using conda. More info here: [https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-with-commands](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-with-commands) - Navigate to the graphing repo. - Run the command: python3 setup.py install to install the package in the conda virtual environment. - As development progresses, run the above command to update the build in the conda virtual environment.
## Sample Code
Try to run the following sample code:
> from graphing.special_graphs.neural_trigraph.path_cover import min_cover_trigraph > > from graphing.special_graphs.neural_trigraph.rand_graph import * > ## Generate a random neural trigraph. Here, it is two sets of edges between layers 1 and 2 (edges1) and layers 2 and 3 (edges2) > edges1, edges2 = neur_trig_edges(7, 3, 7, shuffle_p=.05) > ## Find the full-path cover for this neural trigraph. > paths1 = min_cover_trigraph(edges1, edges2) > > print(paths1)
Metadata
Release files for graphing 0.0.26
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| graphing-0.0.26.tar.gz | 38.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| graphing-0.0.26-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 88.1 kB
Release files / graphing-0.0.26.tar.gz
| Download URL | graphing-0.0.26.tar.gz |
|---|---|
| Size | 38.3 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/4.0.2 CPython/3.11.9
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Release files / graphing-0.0.26-py3-none-any.whl
| Download URL | graphing-0.0.26-py3-none-any.whl |
|---|---|
| Size | 49.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.9
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