| og:description: | Learn how to install Flower, the Python-based federated learning framework, using PyPI, conda, or Docker in this easy-to-follow guide. |
|---|
Flower requires at least Python 3.10.
Stable releases are available on PyPI:
python -m pip install flwr
For simulations that use the Simulation Runtime, flwr should be installed with the
simulation extra:
python -m pip install "flwr[simulation]"
Flower can also be installed from the conda-forge channel.
If you have not added conda-forge to your channels, you will first need to run the
following:
conda config --add channels conda-forge conda config --set channel_priority strict
Once the conda-forge channel has been enabled, flwr can be installed with
conda:
conda install flwr
or with mamba:
mamba install flwr
The following command can be used to verify if Flower was successfully installed. If everything worked, it should print the version of Flower to the command line:
$ flwr --version
Flower version: |stable_flwr_version|Note
If you're on Windows and see unexpected terminal output (e.g.: � □[32m□[1m),
check :ref:`this FAQ entry <faq-windows-unexpected-output>`.
:doc:`Run Flower using Docker <docker/index>`
New (possibly unstable) versions of Flower are sometimes available as pre-release versions (alpha, beta, release candidate) before the stable release happens:
python -m pip install -U --pre flwr
For simulations that use the Simulation Runtime, flwr pre-releases should be
installed with the simulation extra:
python -m pip install -U --pre 'flwr[simulation]'
The latest (potentially unstable) changes in Flower are available as nightly releases:
python -m pip install -U flwr-nightly
For simulations that use the Simulation Runtime, flwr-nightly should be installed
with the simulation extra:
python -m pip install -U flwr-nightly[simulation]