settings.ini

[DEFAULT]
repo = utilsforecast
lib_name = utilsforecast
version = 0.2.10
min_python = 3.8
license = apache2
black_formatting = True
doc_path = _docs
lib_path = utilsforecast
nbs_path = nbs
recursive = True
tst_flags = datasets distributed matplotlib polars pyarrow scipy
put_version_in_init = True
branch = main
custom_sidebar = True
doc_host = https://Nixtla.github.io
doc_baseurl = /utilsforecast
git_url = https://github.com/Nixtla/utilsforecast
title = utilsforecast
audience = Developers
author = Nixtla
author_email = business@nixtla.io
copyright = Nixtla Inc.
description = Forecasting utilities
keywords = time-series analysis forecasting
language = English
status = 3
user = Nixtla
requirements = numpy packaging pandas>=1.1.1
plotting_requirements = pandas[plot] plotly plotly-resampler
polars_requirements = polars[numpy]
dev_requirements = black datasetsforecast==0.0.8 nbdev<2.3.26 numba>=0.58.0 pyarrow scipy
readme_nb = index.ipynb
allowed_metadata_keys = 
allowed_cell_metadata_keys = 
jupyter_hooks = True
clean_ids = True
clear_all = False
cell_number = True