Factual package intelligence from PyPI

mlpforecast 0.1.2 package intelligence

Multilayer Perceptron Learning Models for Time Series Forecasting

pip install mlpforecast

Current version
0.1.2
Python requirement
<3.12,>=3.11
License
Not declared
Distribution type
Pure Python wheel
Release files
2 (1 wheels, 1 source)
Download size
80.9 KiB
Release history
3 releases with files
Median release cadence
7 days

mlpforecast dependencies

PyPI declares 26 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. numpy <2.0.0,>=1.24.3
  2. torch <3.0.0,>=2.0.1
  3. lightning <3.0.0,>=2.0.8
  4. optuna <4.0.0,>=3.2.0
  5. optuna-integration <4.0.0,>=3.6.0
  6. scikit-learn ==1.5.1
  7. pandas ==1.5.3
  8. pyarrow <14.0.0,>=13.0.0
  9. pytimetk <0.5.0,>=0.4.0
  10. matplotlib <4.0.0,>=3.8.4
  11. ppscore <2.0.0,>=1.3.0
  12. torchmetrics <2.0.0,>=1.4.0
  13. wandb <0.18.0,>=0.17.4
  14. tqdm <5.0.0,>=4.66.4
  15. tensorboard <3.0.0,>=2.1.5
  16. rich <14.0.0,>=13.7.1
  17. arviz <0.19.0,>=0.18.0
  18. astral <4.0,>=3.2
  19. altair >=5.3.0
  20. vl-convert-python >1.4.0
  21. matplotlib_inline >=0.1.6
  22. seaborn >=0.13.2
  23. statsmodels >=0.14.0
  24. coreforecast <0.0.7,>=0.0.6
  25. utilsforecast <0.0.26,>=0.0.25

The compact report shows 25 of 26 declarations. The interactive dependency graph loads the complete metadata.

Compatibility and release files

mlpforecast publishes 1 wheel and 1 source archive for version 0.1.2. Wheel platform tags: any.

Declared Python classifiers: 3.11.

Metadata completeness

PyPI does not currently declare: license, project URL. PyDeps marks these fields as unknown instead of guessing values.

Release activity and sources

PyPI lists 3 releases with files. The first dated release is ; 3 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .

The project does not publish external project URLs in its PyPI metadata.