Installing FedFred#

FedFred is available on both PyPI and Conda-Forge. This page covers multiple ways to install FedFred for production or development use.

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Installation Methods#

Install the latest stable release from PyPI:

pip install fedfred

Installs core dependencies needed for Pandas-based DataFrame outputs.

Install via Conda-Forge:

conda install -c conda-forge fedfred

We recommend creating a new environment:

conda create -n myenv
conda activate myenv
conda install -c conda-forge fedfred

Clone and install for local development:

git clone https://github.com/nikhilxsunder/fedfred.git
cd fedfred
poetry install

See Contributing to FedFred for developer guidelines.

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Optional Enhancements#

Install Type Stubs for Static Typing

Boost development experience with type hints (e.g., mypy, pyright):

pip install fedfred[types]

Includes stubs for pandas, geopandas, cachetools, and others.

Install Additional DataFrame Backends

FedFred supports optional high-performance DataFrame libraries:

pip install fedfred[polars]
pip install fedfred[dask]

  • Polars: Lightning-fast DataFrames for large datasets.

  • Dask: Parallel, out-of-core DataFrame computation.

See FedFred API Overview for details.

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Developer Quick Setup#

Development Setup (Poetry)

Clone the repository and install with all development dependencies:

git clone https://github.com/nikhilxsunder/fedfred.git
cd fedfred
poetry install
View Source on GitHub
Alternative Setup (conda + pip)

Create a dedicated environment manually:

git clone https://github.com/nikhilxsunder/fedfred.git
cd fedfred

conda create -n fedfred-dev python=3.9
conda activate fedfred-dev

pip install -e ".[dev,types]"

pre-commit install
View Source on GitHub

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