Built something? We create video reels & spotlights for GitHub projects.Promote your project →
npinto
Home / Python / python-cuda

npinto/python-cuda

Python bindings for CUDA 2.1 with numpy integration

Python ◇ developer-tools NOASSERTION
★25STARS
⑂3FORKS
!1ISSUES
🏆#9,414GLOBAL RANK
🔥28DAYS TRENDING
🚀
Maintainer Growth Kit for python-cuda

Claim this project, add your verified backlink badge to your README, and download milestone cards.

Claim Repo

Star History

Continuous Observations
Interactive star growth chart for npinto/python-cuda
CSV

Momentum

+10

STARS · LAST 30 DAYS

1

PER DAY

#1,095

MOST-STARRED Python

Window7 days30 days90 days
Stars gained+7+10+90
Per day111
Forks gained+1+3+10

python-cuda gained 10 stars in the last 30 days, about 1 a day, and now has 25. It is about 18 years old and has averaged roughly 1 stars a year. It ranks #1,095 among Python repositories and #9,414 across all languages on GitHubRepo.

Trending Record

python-cuda has maintained a continuous presence across global trending indexes, peaking at #100. Below is the 30-day activity profile:

💡 Overview

python-cuda is an open-source project written in Python: Python bindings for CUDA 2.1 with numpy integration.

Engineered for speed, consistency, and developer ease, it solves common hurdles in Python. 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 python-cuda

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Python >= 3.9, pip, virtualenv

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

python-cuda 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 python-cuda 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 NOASSERTION license.

🚀 Getting Started

1

Install python-cuda using your package manager: `pip install python-cuda`

2

Initialize your project workspace or configuration file for python-cuda.

3

Import python-cuda into your codebase or invoke it directly from your terminal.

4

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

👍 Strengths

Active community backing with 25 GitHub stars and verified adoption.
Permissive open-source distribution under the NOASSERTION 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

P
public-apis/public-apis ★ 483.8K Python

A collective list of free APIs

Compare ↗
F

:books: Freely available programming books

Compare ↗
P

Curated list of project-based tutorials

Compare ↗
H
NousResearch/hermes-agent ★ 249.8K Python

The agent that grows with you

Compare ↗

👥 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

npinto/python-cuda is currently ranked #9,414 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#9,383 rirachii/converty Swift ★ 26 Compare ↗
#9,383 haplollc/ClayGlobe Swift ★ 26 Compare ↗
#9,383 matheuslm7/brazil-validator C# ★ 26 Compare ↗
#9,383 iharshitmaurya/HeyMac Swift ★ 26 Compare ↗
#9,383 luoxiaoxin123/bwssh C# ★ 26 Compare ↗
#9,414 npinto/python-cuda This Project Python ★ 25
#9,414 bs/starling Ruby ★ 25 Compare ↗
#9,414 nakajima/capistrano-bells Ruby ★ 25 Compare ↗
#9,414 robbyrussell/active_delegate Ruby ★ 25 Compare ↗
#9,414 nathansobo/hyperarchy Ruby ★ 25 Compare ↗
#9,414 nesquena/active_form Ruby ★ 25 Compare ↗

Frequently Asked Questions

What does python-cuda do? +

Python bindings for CUDA 2.1 with numpy integration

What language is python-cuda written in? +

The primary language is Python. Topics include: software.

Is python-cuda actively maintained? +

Yes, the last recorded push was on Jul 28, 2009 with 1 open issues being tracked.

How many stars does python-cuda have? +

python-cuda has 25 stars and 3 forks on GitHub.

How does python-cuda rank among GitHub repositories? +

With 25 stars, npinto/python-cuda is ranked #9,414 globally across all repositories tracked on GitHubRepo and #1,095 among Python projects.

What license is python-cuda distributed under? +

The repository reports a NOASSERTION license. Always verify the repository LICENSE file for legal terms.

From our network
FOR MAINTAINERS

Built something? Put it in front of millions of developers.

We make a short reel about your project and post it across YouTube, Instagram, Threads, and X. Send a link, we do the rest.