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0.4.4

PyPI

affectlog-utils

Common basic utilities used across various TAI tools

Published12 Oct 2024

Direct dependencies5

Transitive dependenciesNot calculated

README

Version 0.4.4 documentation

Trustworthy AI Utilities for Python

This package has been tested with Python 3.7, 3.8, 3.9, 3.10 and 3.11

The Trustworthy AI Utilities package contains common functions shared across various TAI tools, including fairlearn, interpret-community, trustworthyai, affectlog_widgets and other packages, as well as notebook examples.

Please see the main documentation website: https://trustworthyaitoolbox.ai/

The open source code can be found here: https://github.com/affectlog/trustworthy-ai-widgets

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Declared dependencies 5

Native requirements

5 direct targetsNot calculated transitive count

Package / target	Requirement	Relationship
numpy Environment { "extras": "", "marker": null, "requires_python": ">=3.7", "evaluation": "NOT_EVALUATED" }	`numpy`	runtime
pandas Environment { "extras": "", "marker": null, "requires_python": ">=3.7", "evaluation": "NOT_EVALUATED" }	`pandas`	runtime
requests Environment { "extras": "", "marker": null, "requires_python": ">=3.7", "evaluation": "NOT_EVALUATED" }	`requests`	runtime
scikit-learn Environment { "extras": "", "marker": null, "requires_python": ">=3.7", "evaluation": "NOT_EVALUATED" }	`scikit-learn`	runtime
scipy Environment { "extras": "", "marker": null, "requires_python": ">=3.7", "evaluation": "NOT_EVALUATED" }	`scipy`	runtime