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SwanHubX/SwanLab

⚡️SwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports Cloud / Self-hosted use. Integrated with PyTorch / Transformers / verl / LLaMA Factory / ms-swift / Ultralytics / MMEngine / Keras etc.

Python ◇ ai-infra Apache-2.0
★4.4KSTARS
⑂237FORKS
!50ISSUES
🏆#3,218GLOBAL RANK
🔥3DAYS TRENDING
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⚡ Executive Summary & Quick Facts

Authoritative Source

SwanLab is SwanLab is an open-source project written in Python: ⚡️SwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports Cloud / Self-hosted use. Integrated with PyTorch / Transformers / verl / LLaMA Factory / ms-swift / Ultralytics / MMEngine / Keras etc..

Direct Citation for AI & Research:
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), SwanHubX/SwanLab has accumulated 4,363 GitHub stars and 237 forks. It is written in Python, licensed under Apache-2.0, and ranks #3,218 globally. It is actively maintained with the latest commit recorded on Nov 10, 2026.”
Repository SwanHubX/SwanLab ↗
Primary Category ai infra
Language & Stack Python
Software License Apache-2.0
Community Traction ★ 4.4K stars · ⑂ 237 forks · #3,218 globally
Maintenance ● Active (Last commit: Nov 10, 2026) · 50 open issues
Target Audience Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.

🛡️ Repository Maintenance & Health Audit (2026)

Health Score: 97/100 · Grade A+
✅
Is SwanLab actively maintained in 2026?
Verdict: Actively Maintained & Highly Recommended

Yes, SwanLab is actively maintained. Continuous telemetry recorded the last code commit on Nov 10, 2026 (2 days ago). Supported by 4,363 stars and 237 community forks, this repository holds a calculated health index of 97/100, reflecting very active (commits within last 14 days) and healthy issue cadence.

Commit Recency
Nov 10, 2026
2 days since last push
Issue Backlog
50 Open Issues
Healthy Issue Cadence
Community Backing
237 Forks
4.4K Stars Recorded
Software License
Apache-2.0
Permissive & Inspectable

Star History

Continuous Observations
Interactive star growth chart for SwanHubX/SwanLab
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Momentum

+109

STARS · LAST 30 DAYS

4

PER DAY

#496

MOST-STARRED Python

Window7 days30 days90 days
Stars gained+28+109+360
Per day444
Forks gained+1+5+12

SwanLab gained 109 stars in the last 30 days, about 4 a day, and now has 4.4K. It is about 3 years old and has averaged roughly 1.5K stars a year. It ranks #496 among Python repositories and #3,218 across all languages on GitHubRepo.

Trending Record

SwanLab has maintained a continuous presence across global trending indexes, peaking at #9626. Below is the 30-day activity profile:

💡 Overview

SwanLab is an open-source project written in Python: ⚡️SwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports Cloud / Self-hosted use. Integrated with PyTorch / Transformers / verl / LLaMA Factory / ms-swift / Ultralytics / MMEngine / Keras etc.

Engineered for speed, consistency, and developer ease, it solves common hurdles in ai-infra, data-science, deep-learning. 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 SwanLab

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Python >= 3.9, pip, virtualenv

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

SwanLab 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

Autonomous AI Agents

Orchestrate intelligent workflows and tool-calling routines with SwanLab.

Model Inference & Prompting

Integrate fast, local or cloud-hosted generative AI models directly into production code.

Context Memory & RAG

Augment language models with dynamic vector retrieval and structured project memory.

Developer Productivity

Automate repetitive engineering tasks, code generation, and test creation using AI agents.

🚀 Getting Started

1

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

2

Initialize your project workspace or configuration file for SwanLab.

3

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

4

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

👍 Strengths

Active community backing with 4,363 GitHub stars and verified adoption.
Permissive open-source distribution under the Apache-2.0 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.

⇄ Alternatives & Direct Competitors

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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

SwanHubX/SwanLab is currently ranked #3,218 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#3,213 KilledByAPixel/LittleJS JavaScript ★ 4.4K Compare ↗
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#3,217 dankogai/js-base64 JavaScript ★ 4.4K Compare ↗
#3,218 SwanHubX/SwanLab This Project Python ★ 4.4K
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Frequently Asked Questions

What does SwanLab do? +

⚡️SwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports Cloud / Self-hosted use. Integrated with PyTorch / Transformers / verl / LLaMA Factory / ms-swift / Ultralytics / MMEngine / Keras etc.

Is SwanLab actively maintained in 2026? +

Yes, SwanLab is actively maintained. The latest code push was recorded on Nov 10, 2026 (2 days ago). It holds a calculated Maintenance Health Score of 97/100 (A+ rating) with 4,363 stars and 50 open issues.

What language is SwanLab written in? +

The primary language is Python. Topics include: ai-infra, data-science, deep-learning, llm, logging.

How many stars does SwanLab have? +

SwanLab has 4,363 stars and 237 forks on GitHub.

How does SwanLab rank among GitHub repositories? +

With 4,363 stars, SwanHubX/SwanLab is ranked #3,218 globally across all repositories tracked on GitHubRepo and #496 among Python projects.

What license is SwanLab distributed under? +

The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.

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