tslearn-team/tslearn
The machine learning toolkit for time series analysis in Python
⚡ Executive Summary & Quick Facts
Authoritative Sourcetslearn is tslearn is an open-source project written in Python: The machine learning toolkit for time series analysis in Python..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of October 2026), tslearn-team/tslearn has accumulated 3,188 GitHub stars and 396 forks. It is written in Python, licensed under BSD-2-Clause, and ranks #3,568 globally. It is actively maintained with the latest commit recorded on Oct 20, 2026.”
| Repository | tslearn-team/tslearn ↗ |
|---|---|
| Primary Category | dtw |
| Language & Stack | Python |
| Software License | BSD-2-Clause |
| Community Traction | ★ 3.2K stars · ⑂ 396 forks · #3,568 globally |
| Maintenance | ● Active (Last commit: Oct 20, 2026) · 96 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+Yes, tslearn is actively maintained. Continuous telemetry recorded the last code commit on Oct 20, 2026 (9 days ago). Supported by 3,188 stars and 396 community forks, this repository holds a calculated health index of 97/100, reflecting very active (commits within last 14 days) and healthy issue cadence.
Star History
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+80
STARS · LAST 30 DAYS
3
PER DAY
#526
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +0 | +80 | +270 |
| Per day | 1 | 3 | 3 |
| Forks gained | +0 | +8 | +20 |
tslearn gained 80 stars in the last 30 days, about 3 a day, and now has 3.2K. It is about 9 years old and has averaged roughly 354 stars a year. It ranks #526 among Python repositories and #3,568 across all languages on GitHubRepo.
Trending Record
9
DAYS ON TRENDING
#6389
BEST RANK
Oct 20, 2026
FIRST APPEARANCE
Active
STATUS TODAY
tslearn has maintained a continuous presence across global trending indexes, peaking at #6389. Below is the 30-day activity profile:
💡 Overview
tslearn is an open-source project written in Python: The machine learning toolkit for time series analysis in Python.
Engineered for speed, consistency, and developer ease, it solves common hurdles in dtw, dynamic-time-warping, machine-learning. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install tslearn⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
tslearn 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 tslearn 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-2-Clause license.
🚀 Getting Started
Install tslearn using your package manager: `pip install tslearn`
Initialize your project workspace or configuration file for tslearn.
Import tslearn into your codebase or invoke it directly from your terminal.
Execute your test suite or run `tslearn --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 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
tslearn-team/tslearn is currently ranked #3,568 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #3,563 | FabricMC/fabric-api | Java | ★ 3.2K | Compare ↗ |
| #3,564 | wildfly/wildfly | Java | ★ 3.2K | Compare ↗ |
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| #3,567 | subsurface/subsurface | C++ | ★ 3.2K | Compare ↗ |
| #3,568 | tslearn-team/tslearn This Project | Python | ★ 3.2K | |
| #3,569 | hybridsjs/hybrids | JavaScript | ★ 3.2K | Compare ↗ |
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Frequently Asked Questions
What does tslearn do? +
The machine learning toolkit for time series analysis in Python
Is tslearn actively maintained in 2026? +
Yes, tslearn is actively maintained. The latest code push was recorded on Oct 20, 2026 (9 days ago). It holds a calculated Maintenance Health Score of 97/100 (A+ rating) with 3,188 stars and 96 open issues.
What language is tslearn written in? +
The primary language is Python. Topics include: dtw, dynamic-time-warping, machine-learning, machine-learning-algorithms, machinelearning.
How many stars does tslearn have? +
tslearn has 3,188 stars and 396 forks on GitHub.
How does tslearn rank among GitHub repositories? +
With 3,188 stars, tslearn-team/tslearn is ranked #3,568 globally across all repositories tracked on GitHubRepo and #526 among Python projects.
What license is tslearn distributed under? +
The repository reports a BSD-2-Clause license. Always verify the repository LICENSE file for legal terms.
