py3nvml
Python 3 Bindings for the NVIDIA Management Library
Decision gist · record as of 2026-08-14
No—the package is abandoned (last release 2021-11-22, last commit 2022-04-14) and will not track NVIDIA driver or CUDA API changes. For new projects, use actively maintained alternatives. If you have legacy code already using py3nvml, it may still work on older systems, but do not adopt it for new development.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires NVIDIA GPU hardware and NVIDIA drivers installed; NVIDIA Management Library (libnvidia-ml.so or equivalent) must be accessible on the system.
- Low install friction with a single lightweight dependency (xmltodict).
- However, the package is abandoned—last release was 2021-11-22 and last commit 2022-04-14, with no active maintenance or security updates.
License · maintenance · safety
BSD (permissive) — BSD license is permissive and imposes minimal restrictions; you can use, modify, and distribute the package freely with attribution.
last release 2021-11-22 (1726 days) · last repo commit 2022-04-14 · 250 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 192,517 downloads/mo, #9,861 on PyPI
Alternatives
Verify before relying
pip install py3nvml
from py3nvml.py3nvml import *
nvmlInit()
print("Driver Version: {}".format(nvmlSystemGetDriverVersion()))
deviceCount = nvmlDeviceGetCount()
nvmlShutdown()- Compatibility with NVIDIA driver versions and CUDA toolkits released after 2022-04-14.
- Whether xmltodict dependency is actually used at runtime or only for optional nvidia_smi module functionality.
- Support status for Python versions beyond 3.5 (classifiers list only 3.5 explicitly).
What it is and what it does
py3nvml is a Python 3 port of NVIDIA's official python bindings to the NVIDIA Management Library (NVML), allowing you to query GPU state, driver info, memory usage, and running processes programmatically. It wraps the C NVML library and raises Python exceptions instead of returning error codes, making it more Pythonic than the original C interface.
Beyond basic NVML queries, the package includes utility functions for shared GPU server scenarios: grab_gpus() automatically sets CUDA_VISIBLE_DEVICES to allocate a specified number of free GPUs based on memory thresholds, get_free_gpus() detects which GPUs have no running processes, and a py3smi command-line tool provides formatted GPU status output. These utilities address the practical problem of preventing greedy frameworks from monopolizing all available GPUs.
Use it for
- Automatically allocate N free GPUs to a job on a shared multi-GPU server without manual CUDA_VISIBLE_DEVICES configuration.
- Monitor GPU memory usage and process counts programmatically to implement custom GPU scheduling or load-balancing logic.
- Query driver version, GPU model names, and memory capacity at runtime to validate hardware requirements before launching compute jobs.
- Implement a health-check or monitoring script that detects hung GPU processes or memory leaks across a cluster of machines.
- Build a web dashboard or CLI tool that displays formatted GPU status with custom metrics or filtering.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
No—the package is abandoned (last release 2021-11-22, last commit 2022-04-14) and will not track NVIDIA driver or CUDA API changes.
For new projects, use actively maintained alternatives. If you have legacy code already using py3nvml, it may still work on older systems, but do not adopt it for new development.
Install
py3nvml on PyPI
Before you install
Low install friction with a single lightweight dependency (xmltodict). However, the package is abandoned—last release was 2021-11-22 and last commit 2022-04-14, with no active maintenance or security updates.
Requires NVIDIA GPU hardware and NVIDIA drivers installed; NVIDIA Management Library (libnvidia-ml.so or equivalent) must be accessible on the system.
License in practice
BSD license is permissive and imposes minimal restrictions; you can use, modify, and distribute the package freely with attribution.
Quickstart
pip install py3nvml
from py3nvml.py3nvml import *
nvmlInit()
print("Driver Version: {}".format(nvmlSystemGetDriverVersion()))
deviceCount = nvmlDeviceGetCount()
nvmlShutdown()Verify before relying
- Compatibility with NVIDIA driver versions and CUDA toolkits released after 2022-04-14.
- Whether xmltodict dependency is actually used at runtime or only for optional nvidia_smi module functionality.
- Support status for Python versions beyond 3.5 (classifiers list only 3.5 explicitly).
Package facts
| License | BSD permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagexmltodict |
| Maintenance | Abandoned 1,726 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 192,517 / month, #9,861 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaIntended Audience :: DevelopersIntended Audience :: System AdministratorsLicense :: OSI Approved :: BSD LicenseOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: PythonProgramming Language :: Python :: 3.5Topic :: Software Development :: Libraries :: Python ModulesTopic :: System :: HardwareTopic :: System :: Systems Administration |
Evidence: py3nvml-0.2.7-py3-none-any.whl
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See also nvidia-ml-py3 · pynvml · nvidia-ml-py · GPUtil · nvgpu · nvitop · gpustat · pyrsmi · egl-probe · cuequivariance-ops-cu12