settings.ini

[DEFAULT]
host = github
lib_name = mlforecast
user = Nixtla
description = Scalable machine learning based time series forecasting
keywords = python forecast forecasting machine-learning dask
author = José Morales
author_email = jmoralz92@gmail.com
copyright = Nixtla
branch = main
version = 0.10.0
min_python = 3.8
audience = Developers
language = English
custom_sidebar = True
license = apache2
status = 3
requirements = numba packaging pandas scikit-learn utilsforecast>=0.0.10 window-ops
dask = fugue dask[complete] lightgbm xgboost
ray = fugue[ray] lightgbm_ray xgboost_ray
spark = fugue pyspark lightgbm xgboost
dev_requirements = black dask[complete] datasetsforecast fugue[ray] lightgbm lightgbm_ray matplotlib mypy nbdev polars pyarrow pyspark ruff utilsforecast xgboost xgboost_ray
nbs_path = nbs
doc_path = _docs
recursive = True
doc_host = https://Nixtla.github.io
doc_baseurl = /
git_url = https://github.com/Nixtla/mlforecast
lib_path = mlforecast
title = mlforecast
tst_flags = polars
black_formatting = True
readme_nb = index.ipynb
allowed_metadata_keys = 
allowed_cell_metadata_keys = 
jupyter_hooks = True
clean_ids = True
clear_all = False
put_version_in_init = True