pyphene 1.0.10

A multithreaded graph runner

Pyphene

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Table of Contents

1. About The Project
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Roadmap
5. Contributing
6. License
7. Contact
8. Acknowledgments

About The Project

Pyphene is an open-source Python library that allows for the execution of Direct Acyclic Graph (DAG) workloads in-memory and multithreaded. The name "pyphene" is a combination of the words "Python" and "Graphene", reflecting the library's focus on providing an easy-to-use and efficient solution for working with DAGs in Python.

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Getting Started

You can install Pyphene with pip:

pip install pyphene

Prerequisites

The only prerequisite is to be running Python 3.6 or higher.

Installation

You can install Pyphene with pip:

pip install pyphene

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Usage

Pyphene is really simple to use. You can instantiate the graph either from a JSON (not super supported) or declaratively with code:

import time
from pyphene import graph

# Create a new DAG
pyph = graph.Graph()

def do_work(dep_input, states, event):
    print("Starting to work")
    time.sleep(2)
    print("Done!")

# Add tasks to the DAG
pyph.add_node("node_name1", [], do_work)
pyph.add_node("node_name2", ["node_name1"], do_work)

# Execute the DAG
pyph.run()

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Roadmap

• Add Changelog
• Add back to top links
• Add Additional Templates w/ Examples
• Add "components" document to easily copy & paste sections of the readme
• Multi-language Support
  • Chinese
  • Spanish

See the open issues for a full list of proposed features (and known issues).

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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License

Distributed under the MIT License. See LICENSE.txt for more information.

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Contact

Your Name - @your_twitter - [e-mail]

Project Link: https://github.com/your_username/repo_name

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Acknowledgments

Use this space to list resources you find helpful and would like to give credit to. I've included a few of my favorites to kick things off!

• Choose an Open Source License
• GitHub Emoji Cheat Sheet
• Malven's Flexbox Cheatsheet
• Malven's Grid Cheatsheet
• Img Shields
• GitHub Pages
• Font Awesome
• React Icons

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MIT License

Copyright (c) 2023 MOVING LAKE SAPI DE CV

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, publish, distribute, sublicense, and/or sell 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.