discovery-capability

Project Hadron

Overview

Project Hadron is an open-source application framework for in-memory preprocessing, where data analysis, machine learning, and other data-intensive tasks require efficiency and speed. With :Apache Arrow as its canonical, and a more directed use of pandas, Project Hadron offers effective data management, extensive interoperability, improved memory management and hardware optimization.

At its concept, Project Hadron was conceived with a desire to improve the availability of objective relevant data, increase the transparency and traceability of data lineage and facilitate knowledge transfer, retrieval and reuse.

At its core Project Hadron is a selection of capabilities that represent an encapsulated set of actions that act upon a given set of features or dataset. An example of this would be FeatureSelection, a capability class, encapsulating cleaning data by removing uninformative columns.

For the complete documentation read-the-docs

Installation

Python version

We recommend using the latest version of Python. Project Hadron supports Python 3.8 and newer.

Package installation

The best way to install the component packages is directly from the Python Package Index using pip.

The component package is discovery-capability and pip installed with:

pip install discovery-capability

if you want to upgrade your current version then using pip install upgrade with:

pip install -U discovery-capability

This will also install or update dependent third party packages. The dependencies are limited to Python, PyArrow and related Data manipulation tooling such as Pandas, Numpy, scipy, scikit-learn and visual packages matplotlib and seaborn, and thus have a limited footprint and non-disruptive installation in a data processing environment.

Next Steps

For next steps read-the-docs

License

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

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!

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