{"categories":[{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/2"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering"},{"label":"Education","url":"https://skillfed.io/packages/category/education"}],"enrichment":{"capability":"cuda-python is a metapackage providing Pythonic access to NVIDIA's CUDA platform, bundling low-level bindings, runtime abstractions, and utilities for GPU-accelerated computing from Python.","skillfed_tags":["gpu-computing","cuda","nvidia"],"use_cases":["Write GPU kernels in Python using numba.cuda or cuda.tile DSLs and compile them to CUDA without leaving Python.","Access CUDA Driver and Runtime APIs directly from Python for fine-grained GPU memory and kernel control.","Build GPU-accelerated libraries that expose CUDA functionality through idiomatic Python interfaces.","Profile and debug CUDA Python applications using Nsight Python or CUPTI Python profiling tools.","Perform distributed GPU computing with nvshmem4py's PGAS programming model across multiple GPUs."],"what_it_does":"cuda-python is NVIDIA's official Python interface to the CUDA platform, restructured as a metapackage that bundles multiple subcomponents. It provides both high-level, Pythonic abstractions (cuda.core for CUDA Runtime) and low-level C API bindings (cuda.bindings for CUDA Driver, NVRTC, NVML, and related libraries), plus utilities like cuda.pathfinder for locating CUDA installations. The package aims to enable end-to-end GPU development in Python without leaving the language.\n\nThe metapackage approach allows developers to install only the components they need\u2014whether that's just the runtime bindings, low-level driver access, or specialized modules like numba.cuda for kernel JIT compilation or nvmath-python for math library access. It targets developers, researchers, and end users on Windows and Linux, supporting Python 3.10 through 3.14.","worth_installing":"Yes, if you are developing GPU-accelerated Python applications and have an NVIDIA GPU with compatible drivers. The package is actively maintained, has low install friction, and provides both high-level and low-level access to CUDA. However, verify that the proprietary NVIDIA license aligns with your project's requirements before committing to it in production or redistributed code."},"id":"cuda-python","links":{"html":"https://skillfed.io/packages/cuda-python","md":"https://skillfed.io/packages/cuda-python.md","pypi":"https://pypi.org/project/cuda-python/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-05-29","license_spdx":"LicenseRef-NVIDIA-SOFTWARE-LICENSE","license_treatment":"unclear","name":"cuda-python","python_support":"supports_current","summary":"CUDA Python: Performance meets Productivity"},"popularity":{"monthly_downloads":10132165,"position":1478,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"13.3.1"}