content: [tool.poetry]
  name = "bayesian-event-detector"
  version = "0.1.0"
  description = "Lambda³ Analytics for Bayes & CausalJunction - A framework for detecting structural changes and causal relationships in time series using Bayesian methods"
  authors = ["Masamichi Iizumi <m.iizumi@miosync.email>"]
  license = "MIT"
  readme = "README.md"
  homepage = "https://github.com/miosync-masa/bayesian-event-detector"
  repository = "https://github.com/miosync-masa/bayesian-event-detector"
  keywords = ["lambda3", "bayesian", "time-series", "event-detection", "causal-analysis"]
  classifiers = [
      "Development Status :: 3 - Alpha",
      "Intended Audience :: Science/Research",
      "Topic :: Scientific/Engineering :: Information Analysis",
      "License :: OSI Approved :: MIT License",
      "Programming Language :: Python :: 3.8",
      "Programming Language :: Python :: 3.9",
      "Programming Language :: Python :: 3.10",
      "Programming Language :: Python :: 3.11",
  ]
  
  [tool.poetry.dependencies]
  python = "^3.8"
  pymc = "^5.0"
  numpy = "^1.21"
  arviz = "^0.15"
  seaborn = "^0.12"
  matplotlib = "^3.5"
  scikit-learn = "^1.0"
  networkx = "^3.0"
  numba = "^0.56"
  pandas = "^1.3"
  yfinance = "^0.2"
  
  [tool.poetry.group.dev.dependencies]
  pytest = "^7.0"
  black = "^23.0"
  isort = "^5.0"
  flake8 = "^6.0"
  
  [build-system]
  requires = ["poetry-core"]
  build-backend = "poetry.core.masonry.api"
  
  [tool.black]
  line-length = 120
  target-version = ['py38']
  
  [tool.isort]
  profile = "black"
  line_length = 120
  