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aimclub/FEDOT

Automated modeling and machine learning framework FEDOT

Python ◇ automated-machine-learning BSD-3-Clause
★712STARS
⑂98FORKS
!81ISSUES
🏆#7,019GLOBAL RANK
🔥9DAYS TRENDING
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Momentum

+18

STARS · LAST 30 DAYS

1

PER DAY

#950

MOST-STARRED Python

Window7 days30 days90 days
Stars gained+0+18+90
Per day111
Forks gained+0+3+10

FEDOT gained 18 stars in the last 30 days, about 1 a day, and now has 712. It is about 7 years old and has averaged roughly 102 stars a year. It ranks #950 among Python repositories and #7,019 across all languages on GitHubRepo.

Trending Record

FEDOT has maintained a continuous presence across global trending indexes, peaking at #6555. Below is the 30-day activity profile:

💡 Overview

FEDOT is an open-source project written in Python: Automated modeling and machine learning framework FEDOT.

Engineered for speed, consistency, and developer ease, it solves common hurdles in automated-machine-learning, automation, automl. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Python for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ pip install FEDOT

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Python >= 3.9, pip, virtualenv

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

FEDOT coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Production System Integration

Embed FEDOT into Python backend services to handle core application logic.

CI/CD Automated Pipelines

Run automated validation, builds, and integration suites during deployments.

Developer Tooling & Workflows

Accelerate developer onboarding with pre-configured project utilities.

Open Source Extension

Fork and customize internal modules under the repository's open BSD-3-Clause license.

🚀 Getting Started

1

Install FEDOT using your package manager: `pip install FEDOT`

2

Initialize your project workspace or configuration file for FEDOT.

3

Import FEDOT into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `FEDOT --help` to verify successful setup.

👍 Strengths

Active community backing with 712 GitHub stars and verified adoption.
Permissive open-source distribution under the BSD-3-Clause license.
Built in Python for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Python and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

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👥 Who Should Use This

Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

aimclub/FEDOT is currently ranked #7,019 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#7,009 pegainfer-project/pegainfer Rust ★ 714 Compare ↗
#7,015 codevise/pageflow JavaScript ★ 713 Compare ↗
#7,015 enginmanap/limonEngine C++ ★ 713 Compare ↗
#7,015 chapar-rest/chapar Go ★ 713 Compare ↗
#7,015 rushiranpise/Shizuku-Next Kotlin ★ 713 Compare ↗
#7,019 aimclub/FEDOT This Project Python ★ 712
#7,019 maxlapshin/mysql2postgres Ruby ★ 712 Compare ↗
#7,019 FreeCol/freecol Java ★ 712 Compare ↗
#7,019 10up/classifai PHP ★ 712 Compare ↗
#7,023 voku/anti-xss PHP ★ 711 Compare ↗
#7,023 phpstan/phpstan-strict-rules PHP ★ 711 Compare ↗
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Frequently Asked Questions

What does FEDOT do? +

Automated modeling and machine learning framework FEDOT

What language is FEDOT written in? +

The primary language is Python. Topics include: automated-machine-learning, automation, automl, evolutionary-algorithms, fedot.

Is FEDOT actively maintained? +

Yes, the last recorded push was on Oct 7, 2026 with 81 open issues being tracked.

How many stars does FEDOT have? +

FEDOT has 712 stars and 98 forks on GitHub.

How does FEDOT rank among GitHub repositories? +

With 712 stars, aimclub/FEDOT is ranked #7,019 globally across all repositories tracked on GitHubRepo and #950 among Python projects.

What license is FEDOT distributed under? +

The repository reports a BSD-3-Clause license. Always verify the repository LICENSE file for legal terms.

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