geneweaver-core 0.6.1a0

The core of the Jax-Geneweaver Python library

Geneweaver Core

The Geneweaver Core Python library provides shared foundational functionality for the Geneweaver project. It is a dependency of all other Geneweaver Python libraries, and is not intended to be used directly.

Installation

The Geneweaver Core library is available on PyPI and can be installed with pip:

pip install geneweaver-core

If you are using Poetry, you can add the Geneweaver Core library to your project with:

poetry add geneweaver-core

Overview

This package is structured so as to share an import path with other geneweaver packages. This allows you to install the package and import it without having to worry about the package name. For example, if you install the geneweaver-core package, as well as the geneweaver-db package, you can import the geneweaver package and access both libraries:

from geneweaver import core, db

The Geneweaver Core library provides the following functionality:

• geneweaver.core.schema: Pydantic schema definitions

• geneweaver.core.enum: Enumerations

• geneweaver.core.config: Configuration management

  • GeneweaverBaseSettings: Base Settings class to inherit from for your own package's configuration classes
  • GeneweaverCoreSettings: Configuration class for Geneweaver Core settings

• geneweaver.core.exc: Geneweaver shared exceptions

  • GeneweaverException: Base exception class for Geneweaver
  • GeneweaverError: Base error class for Geneweaver
  • GeneweaverWarning: Base warning class for Geneweaver

• geneweaver.core.pase: Geneweaver file parsing functionality

  • batch: Functions for parsing a batch file
  • score: Functions for parsing a score
  • csv: Functions for parsing a CSV file
  • xlsx: Functions for parsing an Excel file
  • enum: Enumerations for file parsing
  • exceptions: Exceptions for file parsing
  • utils: Utility functions for file parsing

Planned Functionality

• geneweaver.core.logging: Shared logging management
• geneweaver.core.utils: Shared utility functions

Acknowledgements

This project was developed by the Computational Systems and Synthetic Biology Center at the Jackson Laboratory in conjunction with the Baylor University Computational Biology and Bioinformatics Program.