windML
Wind data sources can be accessed from Python with windML, a framework built on NumPy, SciPy, scikit-learn, and Matplotlib.
About windML
windML is a Python framework that provides easy access to wind data sources, built on NumPy, SciPy, scikit-learn, and Matplotlib. It is designed for use cases including renewable wind energy analysis, forecasting, and prediction. The package is no longer actively maintained, with a deprecated master branch available for reference.
Key features
- Python interface for accessing wind data sources
- Built on NumPy, SciPy, scikit-learn, and Matplotlib
- Supports renewable wind energy analysis workflows
- Includes tools for wind forecasting and prediction
Best for: Python developers and researchers working on wind energy, forecasting, and prediction projects.
Good for
- Provides easy-to-use access to wind data sources for Python users
- Built on widely adopted Python scientific computing libraries
Watch out for
- Package is no longer actively maintained
windML at a glance
- Website
- github.com/cigroup-ol/windml
- Category
- Development › Developer Tools
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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windML FAQ
Is windML still actively maintained?
No, the package is currently not maintained, with only a deprecated master branch available for reference.
What Python libraries does windML build on?
It is built on NumPy, SciPy, scikit-learn, and Matplotlib.
What use cases is windML designed for?
It is intended for renewable wind energy analysis, forecasting, and prediction.
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