pyproject.toml

[tool.poetry]
name = "torchts"
version = "0.1.1"
description = "Time series forecasting with PyTorch"
authors = [
    "TorchTS Team <torchts@googlegroups.com>"
]
license = "MIT"
readme = "README.md"
homepage = "https://rose-stl-lab.github.io/torchTS"
repository = "https://github.com/Rose-STL-Lab/torchTS"
documentation = "https://rose-stl-lab.github.io/torchTS/docs"
keywords = ["deep-learning", "machine-learning", "time-series", "pytorch"]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Developers",
    "Intended Audience :: Science/Research",
    "Topic :: Scientific/Engineering",
    "Topic :: Software Development :: Libraries :: Python Modules"
]

[tool.poetry.dependencies]
python = ">=3.8,<3.10"
torch = "^1.4"
pytorch-lightning = "^1.2"
scipy = "^1.7.1"

[tool.poetry.group.test.dependencies]
pytest = "^7.0.1"
pytest-cov = "^3.0.0"
pytest-mock = "^3.7.0"
pre-commit = "^2.17.0"

[tool.poetry.group.docs.dependencies]
sphinx = "^4.4.0"
asteroid-sphinx-theme = "^0.0.3"

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

[tool.black]
line-length = 88

[tool.isort]
profile = "black"

[tool.flakeheaven]
exclude = ["*.ipynb"]
format = "grouped"
max_complexity = 10
max_line_length = 88
show_source = true

[tool.flakeheaven.plugins]
pycodestyle = ["+*", "-E203", "-E741"]
pyflakes = ["+*"]
mccabe = ["+*"]
flake8-bugbear = ["+*"]
flake8-comprehensions = ["+*"]