windML
Python Framework for Wind Energy Analysis and Prediction
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is windML?
WindML is a Python framework designed to facilitate wind energy analysis and prediction. It provides tools and models that help researchers and developers understand and forecast wind patterns, contributing significantly to renewable energy research.
Key differentiator
“WindML stands out as an open-source Python framework specifically tailored for wind energy analysis and prediction, offering specialized tools not commonly found in general-purpose machine learning libraries.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Documentation lacks examples for integrating with popular wind energy datasets or simulation software
GitHub repository has fewer than 50 stars and less than 10 contributors
Fit analysis
Who is it for?
✓ Best for
Teams conducting detailed analysis on wind energy patterns and predictions
Academic researchers working on renewable energy projects
Companies looking to optimize their wind energy production strategies
✕ Not a fit for
Projects requiring real-time data processing for immediate decision-making
Applications that need a cloud-based solution without local setup
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Works well with
Next step
Get Started with windML
Step-by-step setup guide with code examples and common gotchas.