nvidia-nvtx
NVIDIA Tools Extension
Install
nvidia-nvtx on PyPI
pip
pip install nvidia-nvtxuv
uv add nvidia-nvtxpoetry
poetry add nvidia-nvtxPackage facts
| License | not declared (unclear) |
| Python support | supports the current Python release (>=3) |
| Install friction | medium — platform-specific wheel |
| Runtime dependencies | none |
| Maintenance | actively maintained — 79 days since the last release |
| First released | |
| Popularity | one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-13) |
Evidence: nvidia_nvtx-13.3.29-py3-none-manylinux1_x86_64.manylinux_2_5_x86_64.whl; nvidia_nvtx-13.3.29-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; nvidia_nvtx-13.3.29-py3-none-win_amd64.whl
Keywords: cuda, nvidia, runtime, machine learning, deep learning
About nvidia-nvtx
from the package's own PyPI description — quoted content, verbatim
A C-based API for annotating events, code ranges, and resources in your applications. Applications which integrate NVTX can use the Visual Profiler to capture and visualize these events and ranges.
AI interpretation — verify before relying
AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page
Provides a C-based API for annotating events and code ranges in applications to enable performance profiling and visualization with NVIDIA's Visual Profiler.
Medium install friction due to platform-specific wheels (manylinux1_x86_64, manylinux2014_aarch64, win_amd64); actively maintained with a release 79 days ago and no runtime dependencies to complicate setup.
License status is unclear—no SPDX identifier or raw license text is available in the package metadata, so users should verify licensing terms directly with NVIDIA before adoption.
Usage
pip install nvidia-nvtx==13.3.29
import nvidia_nvtx as nvtx
with nvtx.annotate('operation_name'):
pass # your code here
Requires Python >=3; platform-specific wheels mean installation may fail on unsupported architectures.
Verdict: A specialized profiling tool from NVIDIA in the top 1000 PyPI packages with active maintenance and no known vulnerabilities. Medium install friction and unclear licensing are the main considerations; otherwise suitable for CUDA-based ML and scientific workloads that need performance instrumentation.
Needs verification
- Exact license terms and any restrictions on commercial use or redistribution
- Whether the package works on all listed Python versions (3.5–3.11) or only a subset
- Compatibility with non-NVIDIA GPU frameworks or CPU-only environments
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