Factual package intelligence from PyPI

skforecast 0.23.0 package intelligence

Skforecast is a Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models. It works with any estimator compatible with the scikit-lear

pip install skforecast

Current version
0.23.0
Python requirement
>=3.10
License
BSD-3-Clause
Distribution type
Pure Python wheel
Release files
2 (1 wheels, 1 source)
Download size
951.1 KiB
Release history
33 releases with files
Median release cadence
48 days

skforecast dependencies

PyPI declares 41 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. numpy >=1.26
  2. pandas <3.0,>=2.1
  3. tqdm >=4.66
  4. scikit-learn >=1.4
  5. scipy >=1.12
  6. optuna >=4.0
  7. joblib >=1.3
  8. numba >=0.59
  9. rich >=13.9

The compact report shows 12 of 41 declarations. The interactive dependency graph loads the complete metadata.

Compatibility and release files

skforecast publishes 1 wheel and 1 source archive for version 0.23.0. Wheel platform tags: any.

Declared Python classifiers: 3.10, 3.11, 3.12, 3.13, 3.14.

Security snapshot for skforecast 0.23.0

An OSV query completed on and found 0 known vulnerabilities affecting this version. 0 advisories are classified as critical. 0 advisories appear in the CISA Known Exploited Vulnerabilities catalog.

Release activity and sources

PyPI lists 33 releases with files. The first dated release is ; 9 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .