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0.0.6

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affectlog-widgets

Interactive visualizations to assess fairness, explain models, generate counterfactual examples, analyze causal effects and analyze errors in Machine Learning models.

Published12 Oct 2024
Direct dependencies10
Transitive dependenciesNot calculated

README

Version 0.0.6 documentation

AffectLog Widgets

This repository contains the affectlog_widgets library, which is used for creating interactive, visual Trustworthy AI tools. This project provides a set of widgets for model assessment, fairness analysis, error detection, and more, built on top of machine learning frameworks.

Requirements for Development

To contribute to affectlog_widgets, make sure to install the following dependencies.

Testing Dependencies

For running tests with code coverage and mocking, use the following:

pytest==7.0.1
pytest-cov
pytest-mock==3.6.1

Parser Dependencies

For parsing requirements, use:

requirements-parser==0.2.0

Package Building

Ensure you have the necessary tools for building the package:

wheel

Machine Learning & Fairness Libraries

Install the following libraries to enable machine learning and fairness evaluation tools:

fairlearn==0.7.0
ml-wrappers>=0.4.0
sktime
pmdarima

Note: For Windows users running Python 3.7, add the following fix for joblib compatibility:

joblib<1.3.0; python_version <= '3.7' and sys_platform == 'win32'

Notebook Testing

To test notebooks and perform notebook validation, install:

nbformat
papermill
scrapbook
jupyter
nbval

Documentation Dependencies

For generating documentation, install the following:

docutils<=0.19
sphinx==5.0.2
sphinx-gallery==0.10.0
pydata-sphinx-theme==0.7.2

Setting up the Development Environment

Follow these steps to set up your local development environment:

  1. Clone the repository:

    git clone <repository_url>
    cd affectlog_widgets
    
  2. Install Dependencies: You can install all dependencies via pip:

    pip install -r requirements.txt
    
  3. Run Tests: To ensure everything is working, run the tests:

    pytest
    

Local Installation

For local development, ensure that trustworthyai is available in your project. You can use the relative path for local development:

../trustworthyai/.

Add this path when running your local environment so the necessary modules can be accessed.

Contributing

If you're interested in contributing, please create a feature branch from main, make your changes, and open a pull request. Ensure that all tests pass and documentation is updated where necessary.

License

This project is licensed under the MIT License. See the LICENSE file for details.

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Declared dependencies 10

Native requirements
10 direct targetsNot calculated transitive count
Package / targetRequirementRelationship
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Distribution files

2 collected
affectlog_widgets-0.0.6-py3-none-any.whl

bdist_wheel · 34.82 KB · Python py3

Source file
affectlog_widgets-0.0.6.tar.gz

sdist · 29.91 KB · Python source

Source file

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affectlog/trustworthy-ai-toolbox

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package_version:7b55377ffff16b75dbe33bebada3c2bf6a8844ba5b91c7e905077ddfcaa36e8c

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