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lab-cosmo/upet

Universal machine-learning models for advanced atomistic simulations

Python ◇ machine-learned-interatomic-potentials BSD-3-Clause

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★235STARS

⑂24FORKS

!3ISSUES

🏆#4,909GLOBAL RANK

🔥5DAYS TRENDING

🚀

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Star History

Continuous Observations

Interactive star growth chart for lab-cosmo/upet

Momentum

+10

STARS · LAST 30 DAYS

PER DAY

#576

MOST-STARRED Python

Window	7 days	30 days	90 days
Stars gained	+7	+10	+90
Per day	1	1	1
Forks gained	+1	+3	+10

upet gained 10 stars in the last 30 days, about 1 a day, and now has 235. It is about 2 years old and has averaged roughly 118 stars a year. It ranks #576 among Python repositories and #4,909 across all languages on GitHubRepo.

Trending Record

upet has maintained a continuous presence across global trending indexes, peaking at #1912. Below is the 30-day activity profile:

💡 Overview

upet is an open-source project written in Python: Universal machine-learning models for advanced atomistic simulations.

Engineered for speed, consistency, and developer ease, it solves common hurdles in machine-learned-interatomic-potentials, machine-learning, molecular-dynamics. 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

terminal

$ pip install upet

$ pip install upet # or: brew install upet

> pip install upet

⚙ System Requirements

Platforms

• macOS
• Linux
• Windows

Runtime & Dependencies

Python >= 3.9, pip, virtualenv

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

upet 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 upet 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

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

Initialize your project workspace or configuration file for upet.

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

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

👍 Strengths

Active community backing with 235 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.

⇄ Alternatives & Direct Competitors

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The agent that grows with you

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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

lab-cosmo/upet is currently ranked #4,909 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

Rank	Repository	Language	Stars	Action
#4,897	jsinger67/parol	Rust	★ 236	Compare ↗
#4,897	nvidia-holoscan/holohub	C++	★ 236	Compare ↗
#4,897	guaardvark/guaardvark	Python	★ 236	Compare ↗
#4,897	owenselles/CloudNow	Swift	★ 236	Compare ↗
#4,897	uwuclxdy/clauth	Rust	★ 236	Compare ↗
#4,909	lab-cosmo/upet This Project	Python	★ 235
#4,909	xaviershay/tufte-graph	JavaScript	★ 235	Compare ↗
#4,909	delano/rye	Ruby	★ 235	Compare ↗
#4,909	Universite-Gustave-Eiffel/NoiseModelling	Java	★ 235	Compare ↗
#4,909	cpburnz/python-pathspec	Python	★ 235	Compare ↗
#4,909	Hack23/cia	Java	★ 235	Compare ↗

Frequently Asked Questions

What does upet do? +

Universal machine-learning models for advanced atomistic simulations

What language is upet written in? +

The primary language is Python. Topics include: machine-learned-interatomic-potentials, machine-learning, molecular-dynamics, universal-potential.

Is upet actively maintained? +

Yes, the last recorded push was on Sep 25, 2026 with 3 open issues being tracked.

How many stars does upet have? +

upet has 235 stars and 24 forks on GitHub.

How does upet rank among GitHub repositories? +

With 235 stars, lab-cosmo/upet is ranked #4,909 globally across all repositories tracked on GitHubRepo and #576 among Python projects.

What license is upet distributed under? +

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

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LinkedIn

Why upet is replacing paid subscriptions for engineering teams

Stop paying $50+/month for locked SaaS tools.

Over 235 developers have starred lab-cosmo/upet, an impressive Python open-source project designed to Universal machine-learning models for advanced atomistic simulations.

Key Engineering Advantages:
• 100% Local-First: Complete data privacy with zero tracking or telemetry.
• Zero Subscription Costs: No paywalls, per-seat fees, or API markups.
• Complete Customization: Native open-source architecture you can fork, inspect, and deploy anywhere.
• Proven Adoption: 235 GitHub stars and 24 forks.

If you're looking to streamline your engineering workflows without ballooning software expenses, this is worth checking out.

👉 Full star velocity and architectural report: https://githubrepo.cloud/repo/lab-cosmo/upet
⭐ GitHub Repository: https://github.com/lab-cosmo/upet

#OpenSource #SoftwareEngineering #DeveloperTools #Tech #Programming #Python

🤖

Reddit (r/opensource, r/webdev, r/selfhosted)

Show r/opensource: upet – A free, self-hosted tool that lets you Universal machine-learning models for advanced atomistic simulations

Hey everyone,

I wanted to share an interesting open-source project called **upet** (https://github.com/lab-cosmo/upet) that has been picking up heavy momentum lately (235 stars).

### What problem does it solve?
Many existing tools in this domain require expensive cloud plans or store your data on third-party servers. upet was built with a local-first philosophy, allowing developers to Universal machine-learning models for advanced atomistic simulations without recurring subscription costs or privacy compromises.

### Tech Stack & Details:
- **Language:** Python
- **License:** BSD-3-Clause
- **GitHub:** [lab-cosmo/upet](https://github.com/lab-cosmo/upet)
- **Live Star Momentum Tracker:** [https://githubrepo.cloud/repo/lab-cosmo/upet](https://githubrepo.cloud/repo/lab-cosmo/upet)

Has anyone here tested this in production or integrated it into existing pipelines? Would love to hear your experience and feedback!

🟧

Hacker News (Show HN)

Show HN: upet – Universal machine-learning models for advanced atomistic simulations

Hi HN,

upet is an open-source Python project designed to Universal machine-learning models for advanced atomistic simulations.

Rather than relying on closed cloud endpoints, it executes locally on your own machine, providing predictable latency, total privacy, and full control.

Repository: https://github.com/lab-cosmo/upet
Documentation & Metrics: https://githubrepo.cloud/repo/lab-cosmo/upet

Feedback and PRs are welcome.

✍️

Dev.to / Hashnode Tags: opensource, python, devtools, webdev

This GitHub repo replaces a $50 a month tool! Stop paying expensive software subscriptions. Meet upet (235 GitHub Stars)

---
title: This GitHub repo replaces a $50 a month tool! Stop paying expensive software subscriptions. Meet upet
published: true
tags: opensource, python, devtools, programming
---

## Stop Paying Software Subscriptions For This

Finding high-quality, production-ready open source alternatives to expensive proprietary software can save engineering teams thousands of dollars every year.

Today, we're looking at **[lab-cosmo/upet](https://github.com/lab-cosmo/upet)**, a rapidly rising repository with **235 GitHub stars** and **24 forks**.

### What is upet?

> Universal machine-learning models for advanced atomistic simulations

Written in **Python**, upet runs directly on your local workstation or private server, keeping your data secure and eliminating recurring license fees.

### Key Highlights
- **High Performance:** Lightweight, reliable, and built in Python.
- **Privacy & Security:** Complete ownership of your environment and data.
- **Growing Momentum:** Ranked **#4,909** globally across tracked repositories on [GitHubRepo](https://githubrepo.cloud/repo/lab-cosmo/upet).

### Quick Start
To get started locally:

```bash
git clone https://github.com/lab-cosmo/upet.git
cd upet
```

Check out the full repository and star history analytics here:
- **GitHub:** [lab-cosmo/upet](https://github.com/lab-cosmo/upet)
- **Star Velocity Tracker:** [upet on GitHubRepo.cloud](https://githubrepo.cloud/repo/lab-cosmo/upet)

𝕏

X / Twitter Communities

Thread / Community Post for upet

Developers are sleeping on this GitHub repo 👇

lab-cosmo/upet (235 ⭐) replaces expensive monthly software subscriptions with 100% free open source code.

⚡ What it does: Universal machine-learning models for advanced atomistic simulations
💻 Built with: Python
🔒 100% local execution & privacy

Check live star velocity and benchmarks:
https://githubrepo.cloud/repo/lab-cosmo/upet

#opensource #developer #coding #tech #programming

🧵

Threads Topics

Topic Discussion: Open Source & Developer Tools

This GitHub repo replaces a $50/month tool! 🚀

If you want to save hours of manual work and stop paying subscriptions, check out lab-cosmo/upet.

It already has over 235 stars and lets you Universal machine-learning models for advanced atomistic simulations.

Drop a comment if you've tried it, or check the full star momentum report:
https://githubrepo.cloud/repo/lab-cosmo/upet

From our network

lab-cosmo/upet

Star History

Momentum

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💡 Overview

⚡ Key Features

📥 Installation

⚙ System Requirements

Platforms

Runtime & Dependencies

Architecture

🧠 How It Works

🎯 Production Use Cases

Production System Integration

CI/CD Automated Pipelines

Developer Tooling & Workflows

Open Source Extension

🚀 Getting Started

👍 Strengths

⚠️ Considerations

⇄ Alternatives & Direct Competitors

👥 Who Should Use This

🏆 Nearby in the Rankings

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