Metadata-Version: 2.1
Name: graphworks
Version: 0.2.0
Summary: Graph theoretic classes and helper functions.
Home-page: https://github.com/nathan-gilbert/graphworks
Author: Nathan Gilbert
Author-email: me@nathangilbert.com
License: Copyright (c) 2020 Nathan Gilbert
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to  use, copy, modify, merge, or distribute copies of the Software, and to
        permit persons to whom the Software is furnished to do so, subject to the
        following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS  FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY,  WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Mathematics
Description-Content-Type: text/markdown
License-File: LICENSE

# Graphworks

[![Python package](https://github.com/nathan-gilbert/graphworks/actions/workflows/python-package-ci.yml/badge.svg)](https://github.com/nathan-gilbert/graphworks/actions/workflows/python-package-ci.yml)

## A Python module for efficient graph theoretic programming

**NOTE** This is a very old project I created for my undergrad capstone project.
It's not in a working state at the moment, but I'm bringing it back to life.

## Usage

TODO

## Development

### Requirements

- Python 3.8+
- virtualenv
- numpy
- graphviz

### Install the required packages

```sh
pip install virtualenv
virtualenv env
```

### Start the virtualenv

```sh
source ./env/bin/activate
```

### You can deactivate the virtualenv with

```sh
deactivate
```

### Lastly, install the required libraries

```sh
pip install -r requirements.txt
```

### Building the package

- Update the version number in `setup.py`
- Run `python setup.py sdist bdist_wheel`
- Run `twine check dist/*`
- Upload to test PyPi: `twine upload --repository-url https://test.pypi.org/legacy/ dist/*`
- Upload to PyPi main: `twine upload --skip-existing dist/*`
- To autopublish, tag commit with `git tag -a vX.Y.Z -m 'release message`
- Then `git push --tags`

### Diagnostics

- Run the unit tests: `python -m unittest discover tests '*_tests.py'`
- Run unit test coverage: `coverage run --source=graphworks/ -m unittest discover tests '*_tests.py'`
- Generate test coverage reports (either works):
  - `coverage report --omit="*/test*,*/venv/*"`
  - `coverage html --omit="*/test*,*/venv/*"`

## TODO

- Searching/Sorting
  - Topological sort
  - <https://towardsdatascience.com/4-types-of-tree-traversal-algorithms-d56328450846>
- <https://www.python-course.eu/graphs_python.php>
- Build out directed graphs algorithms
  - Hierholzer’s Algorithm
  - <https://algs4.cs.princeton.edu/42digraph/>
- Allow for weighted graph algorithms
  - Jarnik's algorithm
  - Dijkstra's algorithm
- C++ binaries for speeding up graph computations


