Pre-release
This release is a pre-release and may not be stable for production use.
SecretFlow is a unified framework for privacy-preserving data intelligence and machine learning. To achieve this goal, it provides:
- An abstract device layer consists of plain devices and secret devices which encapsulate various cryptographic protocols.
- A device flow layer modeling higher algorithms as device object flow and DAG.
- An algorithm layer to do data analysis and machine learning with horizontal or vertical partitioned data.
- A workflow layer that seamlessly integrates data processing, model training, and hyperparameter tuning.
Documentation
SecretFlow Related Projects
- Kuscia: A K8s-based privacy computing task orchestration framework.
- SCQL: A system that allows multiple distrusting parties to run joint analysis without revealing their private data.
- SPU: A provable, measurable secure computation device, which provides computation ability while keeping your private data protected.
- HEU: A high-performance homomorphic encryption algorithm library.
- YACL: A C++ library that contains cryptography, network and io modules which other SecretFlow code depends on.
Install
Please check INSTALLATION.md
Deployment
Please check DEPLOYMENT.md
Learn PETs
We also provide a curated list of papers and SecretFlow's tutorials on Privacy-Enhancing Technologies (PETs).
Please check AWESOME-PETS.md
Contributing
Please check CONTRIBUTING.md
Disclaimer
Non-release versions of SecretFlow are prohibited from using in any production environment due to possible bugs, glitches, lack of functionality, security issues or other problems.
1 maintainer
Metadata
1 maintainer
Release files for secretflow-lite 1.1.0.dev20230822
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| secretflow_lite-1.1.0.dev20230822-cp38-cp38-manylinux2014_x86_64.whl | CPython 3.8 | CPython 3.8 | Linux glibc 2.17+ x86-64 | Details |
| secretflow_lite-1.1.0.dev20230822-cp38-cp38-macosx_11_0_arm64.whl | CPython 3.8 | CPython 3.8 | macOS 11.0+ ARM64 | Details |
| secretflow_lite-1.1.0.dev20230822-cp38-cp38-macosx_10_16_x86_64.whl | CPython 3.8 | CPython 3.8 | macOS 10.16+ x86-64 | Details |
Total release size: 4.9 MB
Release files / secretflow_lite-1.1.0.dev20230822-cp38-cp38-manylinux2014_x86_64.whl
| Download URL | secretflow_lite-1.1.0.dev20230822-cp38-cp38-manylinux2014_x86_64.whl |
|---|---|
| Size | 1.4 MB |
| Tags | CPython 3.8 Linux glibc 2.17+ x86-64 |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.17
|
Release files / secretflow_lite-1.1.0.dev20230822-cp38-cp38-macosx_11_0_arm64.whl
| Download URL | secretflow_lite-1.1.0.dev20230822-cp38-cp38-macosx_11_0_arm64.whl |
|---|---|
| Size | 1.7 MB |
| Tags | CPython 3.8 macOS 11.0+ ARM64 |
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No |
| Uploaded via |
twine/4.0.2 CPython/3.8.17
|
Release files / secretflow_lite-1.1.0.dev20230822-cp38-cp38-macosx_10_16_x86_64.whl
| Download URL | secretflow_lite-1.1.0.dev20230822-cp38-cp38-macosx_10_16_x86_64.whl |
|---|---|
| Size | 1.8 MB |
| Tags | CPython 3.8 macOS 10.16+ x86-64 |
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SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/4.0.2 CPython/3.8.17
|
