Our verdict
We have not reviewed Flower yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About Flower
Flower is an open-source Python framework for federated learning. It enables training machine learning models across decentralized data sources without centralizing raw data. The framework is designed to be friendly and accessible for developers.
Best for
Researchers and developers building privacy-preserving distributed machine learning systems
Use cases
- Training models on sensitive client data in healthcare or finance
- Collaborating across organizations without sharing private data
- Simulating and prototyping federated learning experiments
Notes
6,922 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.
Pros
- Large open-source community with over 6900 GitHub stars
- Python-native framework that integrates easily with existing ML tooling
- Simple, developer-friendly API for federated learning
Cons
- Focused solely on federated learning, not a general observability tool
- Requires setting up and managing a federated infrastructure
- Less mature than some centralized ML frameworks
Key facts
What we have checked
- Latest version
- framework-1.42.0 (released 22 Oct 2026)
- GitHub stars
- 7,148
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Stars and usage
How Flower is growing
6,922 to 7,148
Sources
Where this comes from
- GitHubOfficial
- github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
Released framework-1.42.0
Released framework-1.41.0
Released framework-1.40.0
Released framework-1.39.0
Released framework-1.38.0
Released framework-1.37.0
Released framework-1.36.0
Released framework-1.35.0
Released framework-1.34.0
Released framework-1.33.0
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
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PyTorch
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Tensors and Dynamic neural networks in Python with strong GPU acceleration
scikit-learn
Community
scikit-learn: machine learning in Python
TensorFlow
Community
An Open Source Machine Learning Framework for Everyone
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