content: [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"