[DEFAULT]
host = github
lib_name = statsforecast
user = Nixtla
description = Time series forecasting suite using statistical models
keywords = time-series forecasting arima ets 
author = Nixtla
author_email = business@nixtla.io
copyright = Nixtla Inc.
branch = main
version = 1.5.0
min_python = 3.7
audience = Developers
language = English
custom_sidebar = True
license = apache2
status = 2
requirements = matplotlib numba>=0.55.0 numpy>=1.21.6 pandas>=1.3.5 plotly polars scipy>=1.7.3 statsmodels>=0.13.2 tqdm plotly-resampler fugue>=0.8.1
ray_requirements = fugue[ray]>=0.8.1 protobuf>=3.15.3,<4.0.0
dask_requirements = fugue[dask]>=0.8.1
spark_requirements = fugue[spark]>=0.8.1
dev_requirements = nbdev black mypy flake8 ray protobuf>=3.15.3,<4.0.0 matplotlib pmdarima prophet scikit-learn fugue[dask,ray,spark]>=0.8.1 datasetsforecast supersmoother
nbs_path = nbs
doc_path = _docs
recursive = True
doc_host =  https://%(user)s.github.io
doc_baseurl = /%(lib_name)s/
git_url = https://github.com/%(user)s/statsforecast/
lib_path = %(lib_name)s
title = %(lib_name)s
black_formatting = True
jupyter_hooks = True
clean_ids = True
readme_nb = index.ipynb
