Metadata-Version: 2.1
Name: mllint
Version: 0.1.3
Summary: Linter for Machine Learning projects
Home-page: https://gitlab.com/bvobart/mllint
Author: Bart van Oort
Author-email: bart@vanoort.is
License: MIT
Project-URL: Bug Tracker, https://gitlab.com/bvobart/mllint/-/issues
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: BSD :: FreeBSD
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development :: Build Tools
Classifier: Topic :: Software Development :: Pre-processors
Classifier: Topic :: Software Development :: Quality Assurance
Classifier: Topic :: Software Development :: Version Control :: Git
Requires-Python: >=3.6
Description-Content-Type: text/markdown

# `mllint` — Linter for Machine Learning projects

`mllint` is a command-line utility to evaluate the quality of Machine Learning (ML) projects by means of static analysis of the project's repository. It measures the project's adherence to ML best practices, as collected and deduced from se4ml.github.io and Google's [Rules for ML](https://developers.google.com/machine-learning/guides/rules-of-ml).

TODO: write overview of linting rules

TODO: find a way to publish this to Pip or something so that users can just pip install it.

## Getting Started (development)

Clone this repository and run `go run .` in the root of this repository.


