pyproject.toml

[tool.poetry]
name = "metriculous"
version = "0.3.0"
description = "Very unstable library containing utilities to measure and visualize statistical properties of machine learning models."
authors = ["Marlon", "Luminovo GmbH <pypi@luminovo.ai>"]
maintainers = ["Marlon"]
license = "MIT"
readme = "README.md"
repository = "https://github.com/metriculous-ml/metriculous"
keywords = [
    "metriculous", "machine", "learning", "metrics", "statistics", "data science", "evaluation",
    "regression", "classification", "residual plot", "ROC curve", "PR curve", "confusion matrix",
    "statistical performance", "ML", "deep learning", "scikit-learn", "bokeh", "forecasting"
    ]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Developers",
    "Intended Audience :: Science/Research",
    "Topic :: Software Development",
    "Topic :: Software Development :: Libraries :: Python Modules",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
    "Topic :: Scientific/Engineering :: Bio-Informatics",
    "Topic :: Scientific/Engineering :: Information Analysis",
    "Topic :: Scientific/Engineering :: Visualization",
    "Topic :: Software Development :: Quality Assurance",
    "Programming Language :: Python :: 3.7",
    "Programming Language :: Python :: 3.8",
    ]
include = ["LICENSE"]


[tool.poetry.dependencies]
python = "^3.10"
numpy = ">=1.16"
scikit-learn = ">=0.21.2"
assertpy = ">=0.14.0"
pandas = ">=1.4.0"
bokeh = "^3.5.2"
jupyter = "^1.0"

[tool.poetry.dev-dependencies]
pytest = "8.3.3"
jupytext = "^1.0"
mypy = "1.11.2"
isort = "^5.0.9"
black = "24.8.0"
flake8 = "^3.8.3"
numpy-stubs = {git = "https://github.com/numpy/numpy-stubs.git"}
jupyterlab = "^2.2.2"

[build-system]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"