FAL Framework

Federated Adversarial Learning framework for running federated learning experiments with clean, adversarial, and mixed training modes.

Install

pip install fal-framework

Use

from sklearn.linear_model import LogisticRegression
from fal import FAL

fal = FAL(
    dataset="wine",
    model=LogisticRegression(max_iter=1000),
    trainer_type="clean",
    metrics=["accuracy", "f1"],
    num_clients=3,
    num_rounds=3,
    fl_algorithm="fedavg",
)

result = fal.run()

Metadata

Release files for fal-framework 0.2.0

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Source distribution for fal-framework 0.2.0
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Built distribution (wheel)

Table of built distributions (wheels) for fal-framework 0.2.0
File	Interpreter	ABI	Platform	Reset
fal_framework-0.2.0-py3-none-any.whl 68.2 kB Oct 16, 2026 Without provenance	Python 3	none	any	Details

Total release size: 120.8 kB

Release files / fal_framework-0.2.0.tar.gz

Download URL	fal_framework-0.2.0.tar.gz
Size	52.6 kB
Tags	Source
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Uploaded via	`twine/6.2.0 CPython/3.11.9`

Release files / fal_framework-0.2.0-py3-none-any.whl

Download URL	fal_framework-0.2.0-py3-none-any.whl
Size	68.2 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`9aff2c6c3bd3853f5ef81280579ff5390af28adaf4ca9b7dc6702e3a4b2b4de8`
BLAKE2b-256 checksum How to use checksums	`b3efc8bb54df0550875e227a4aafc04e385d3b0a9487edd1644cc4e2022ef995`
Upload date	Oct 16, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.11.9`

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