pyproject.toml

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[project]
name = "tsfm-bench"
dynamic = [
  "version",
]
dependencies = [
  "pandas>=2.2,<2.3",
  "gluonts>=0.16,<0.17",
  "numpy>=1.26,<2",
  "python-dotenv>=1.1,<2",
  "scipy>=1.11,<1.12",
  "pyyaml>=6,<7",
  "httpx>=0.27,<0.29",
  "requests>=2.32,<3",
  "huggingface_hub>=0.23,<0.35.3",
  "statsmodels>=0.14,<0.15",
]
requires-python = ">=3.10,<3.13"
authors = [
  {name = "Taha Aksu", email = "iaksu@salesforce.com"},
  {name = "Gerald Woo", email = "gwoo@salesforce.com"},
  {name = "Chenghao Liu", email = "chenghao.liu@salesforce.com"},
  {name = "Juncheng Liu", email = "juncheng.liu@salesforce.com"},
  {name = "Xu Liu", email = "xu.liu@salesforce.com"},
  {name = "Caiming Xiong"},
  {name = "Silvio Savarese"},
  {name = "Doyen Sahoo"},
]
maintainers = [
  {name = "Thinkcat-Lab"},
]

description = "LiveHouse-TS: a live benchmark for time series foundation models"
#readme = "README.md"
#license = {file = "LICENSE.txt"}
keywords = ["Time Series Forecasting", "Transformer", "Deep Learning", "PyTorch"]
classifiers = [
  "Development Status :: 3 - Alpha",
  "Programming Language :: Python",
  "Topic :: Scientific/Engineering :: Artificial Intelligence",
]

[project.optional-dependencies]
leaderboard = ["gradio==4.44.0", "pydantic>=2.7,<2.11", "plotly>=5,<6", "matplotlib>=3.9,<3.10"]
dev = ["pytest>=8,<9", "fastapi==0.112.4", "uvicorn==0.30.6"]
gift = ["datasets~=2.17.1", "einops==0.7.*", "hydra-core==1.3", "orjson", "matplotlib~=3.9.2", "tsfeatures", "ray"]
tabpfn-ts = [
  "tabpfn-time-series>=1.1.0; python_version >= '3.10'",
]
baseline = [
  "torch>=2.1",
  "statsforecast",
  "tensorboard",
  "torch>=2.1",
  "lightning>=2.0",
]

[tool.hatch.version]
path = "src/gift_eval/__about__.py"

[tool.hatch.build]
packages = ["src/gift_eval", "src/tsfm_bench"]

[tool.isort]
profile = "black"

[tool.black]
line-length = 88
target-version = ['py310']

[tool.pytest.ini_options]
pythonpath = [
  ".", "src",
]