System requirements
Before installing Syft-Flwr, ensure your system meets these requirements:- Python: 3.12 or higher (< 3.14)
- Operating System: Linux, macOS, or Windows
- Package Manager: pip or uv (recommended)
For Google Colab, all dependencies are pre-installed. You only need to install Syft-Flwr.
Installation methods
- PyPI (recommended)
- From source (latest)
- Development setup
- Google Colab
Install the latest stable release from PyPI:Or using uv (faster):Verify the installation:
Dependencies
Syft-Flwr automatically installs these core dependencies:Federated learning framework
Federated learning framework
flwr[simulation]==1.25.0- Flower federated learning frameworkflwr-datasets[vision]>=0.5.0- Federated datasets
Syft ecosystem
Syft ecosystem
syft-rds>=0.5.0- Remote data science runtimesyft-client>=0.1.94- Syft client for data governancesyft-dataset>=0.1.5- Dataset managementsyft-job>=0.1.23- Job orchestration
Utilities
Utilities
loguru>=0.7.3- Loggingsafetensors>=0.7.0- Model serializationhuggingface-hub>=0.26.0- Dataset downloadstomli>=2.3.0- TOML parsingtyping-extensions>=4.13.0- Type hints
Optional dependencies
For ML model training, you’ll need additional packages:Verify installation
Run this Python script to verify everything is installed correctly:Environment setup
For local development
If running locally with SyftBox:Install SyftBox
Follow the SyftBox installation guide to set up the local sync daemon.
For Google Colab
No additional setup required! Syft-Flwr auto-detects Colab and uses P2P transport (Google Drive) instead of SyftBox.For development
Install additional development tools:Platform-specific notes
macOS
macOS
Apple Silicon (M1/M2/M3)PyTorch automatically detects Metal Performance Shaders (MPS) for GPU acceleration:Intel-based MacsUse CPU or install with CUDA if you have an eGPU.
Windows
Windows
Activate virtual environmentPath issuesUse raw strings for paths:Long pathsEnable long path support:
Computer Configuration > Administrative Templates > System > Filesystem > Enable Win32 long pathsLinux
Linux
GPU supportFor CUDA-enabled GPUs:File permissionsEnsure your user has read/write access to the SyftBox folder:
Troubleshooting
Import errors
Import errors
Error:
ModuleNotFoundError: No module named 'syft_flwr'Solution:Version conflicts
Version conflicts
Error:
ERROR: pip's dependency resolver does not currently take into account...Solution:Python version mismatch
Python version mismatch
Error:
Requires-Python >=3.12,<3.14Solution:Flower simulation errors
Flower simulation errors
Error:
AttributeError: module 'flwr' has no attribute 'simulation'Solution:Upgrading
To upgrade to the latest version:Uninstalling
To completely remove Syft-Flwr:Next steps
Quickstart
Train your first federated model in 5 minutes
Development guide
Set up your development environment
API reference
Explore the complete API
Examples
Learn from real-world examples
Get help
If you encounter issues:- Check existing GitHub issues
- Ask in Slack - #support-syftbox channel
- Create a new issue with your error details