NVIDIA Nsight Compute Profiler Report Python Interface
The ncu-report package provides a Python interface to work with NVIDIA Nsight Compute profiler reports. It allows users to parse, analyze, and manipulate profiling data programmatically using Python.
Installation
You can install the ncu-report package using pip:
pip install ncu-report
Usage
After installing the package, you can import it in your Python scripts:
import ncu_report
More details about usage can be found in NVIDIA Nsight Compute’s online documentation.
Metadata
Release files for ncu-report 2026.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Actions Reset | |||
|---|---|---|---|---|
| ncu_report-2026.3.1-cp37-abi3-win_arm64.whl | CPython 3.7 | abi3 | Windows ARM64 | Details for ncu_report-2026.3.1-cp37-abi3-win_arm64.whl |
| ncu_report-2026.3.1-cp37-abi3-win_amd64.whl | CPython 3.7 | abi3 | Windows x86-64 | Details for ncu_report-2026.3.1-cp37-abi3-win_amd64.whl |
| ncu_report-2026.3.1-cp37-abi3-manylinux_2_25_x86_64.whl | CPython 3.7 | abi3 | Linux glibc 2.25+ x86-64 | Details for ncu_report-2026.3.1-cp37-abi3-manylinux_2_25_x86_64.whl |
| ncu_report-2026.3.1-cp37-abi3-manylinux_2_25_aarch64.whl | CPython 3.7 | abi3 | Linux glibc 2.25+ ARM64 | Details for ncu_report-2026.3.1-cp37-abi3-manylinux_2_25_aarch64.whl |
| ncu_report-2026.3.1-cp37-abi3-macosx_13_0_x86_64.whl | CPython 3.7 | abi3 | macOS 13.0+ x86-64 | Details for ncu_report-2026.3.1-cp37-abi3-macosx_13_0_x86_64.whl |
| ncu_report-2026.3.1-cp37-abi3-macosx_13_0_arm64.whl | CPython 3.7 | abi3 | macOS 13.0+ ARM64 | Details for ncu_report-2026.3.1-cp37-abi3-macosx_13_0_arm64.whl |
Total release size: 91.3 MB
Release files / ncu_report-2026.3.1-cp37-abi3-win_arm64.whl
| Download URL | ncu_report-2026.3.1-cp37-abi3-win_arm64.whl |
|---|---|
| Size | 13.3 MB |
| Tags | CPython 3.7 Windows ARM64 abi3 |
|
SHA-256 checksum How to use checksums |
cd7ad7fe6d06949959bf299df7eedd075a7aab115d54a50650edd2579f84e19a
|
|
BLAKE2b-256 checksum How to use checksums |
3eab778776e13d0d98f97468e3fc499513169c41882c96e1d80b2aee3d8f52fb
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.3
|
Release files / ncu_report-2026.3.1-cp37-abi3-win_amd64.whl
| Download URL | ncu_report-2026.3.1-cp37-abi3-win_amd64.whl |
|---|---|
| Size | 13.7 MB |
| Tags | CPython 3.7 Windows x86-64 abi3 |
|
SHA-256 checksum How to use checksums |
d1914271a3bbb0b0d47385033cca7de8320b9ba2fb8bcf8ea7b208d71a8f8855
|
|
BLAKE2b-256 checksum How to use checksums |
f24603b0c7623da5072b6be54c9077e9a6ee8d47344c2b1dcca0de79632b60b7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.3
|
Release files / ncu_report-2026.3.1-cp37-abi3-manylinux_2_25_x86_64.whl
| Download URL | ncu_report-2026.3.1-cp37-abi3-manylinux_2_25_x86_64.whl |
|---|---|
| Size | 17.3 MB |
| Tags | CPython 3.7 Linux glibc 2.25+ x86-64 abi3 |
|
SHA-256 checksum How to use checksums |
45684dc191727e51eb7ce5aa46e4a6c3742eb071b105fdc2ca40dc5c85925191
|
|
BLAKE2b-256 checksum How to use checksums |
166f520e4b24537aad7bf8de781ef6cd61aa6649b5c163675082e8748fe77e53
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.3
|
Release files / ncu_report-2026.3.1-cp37-abi3-manylinux_2_25_aarch64.whl
| Download URL | ncu_report-2026.3.1-cp37-abi3-manylinux_2_25_aarch64.whl |
|---|---|
| Size | 16.9 MB |
| Tags | CPython 3.7 Linux glibc 2.25+ ARM64 abi3 |
|
SHA-256 checksum How to use checksums |
a78f02d9e92d6733e8b3921ac7717b324464fe9f61a8a26fae4fd84914c8bca8
|
|
BLAKE2b-256 checksum How to use checksums |
10b346bf5b7317193c5897d68e9e8d9bfbfd94fb7a5583a10e5c9755d2054f9d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.3
|
Release files / ncu_report-2026.3.1-cp37-abi3-macosx_13_0_x86_64.whl
| Download URL | ncu_report-2026.3.1-cp37-abi3-macosx_13_0_x86_64.whl |
|---|---|
| Size | 15.3 MB |
| Tags | CPython 3.7 abi3 macOS 13.0+ x86-64 |
|
SHA-256 checksum How to use checksums |
4df4d6a63e49a6ecd5e41cd5f993816ef82e4e6c2ffe0d720c3939e9d3570dfe
|
|
BLAKE2b-256 checksum How to use checksums |
cdfe8c00b7eb92b92cc564a4c584d85061f2f622c803d5f7025f32ae7f7b246b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.3
|
Release files / ncu_report-2026.3.1-cp37-abi3-macosx_13_0_arm64.whl
| Download URL | ncu_report-2026.3.1-cp37-abi3-macosx_13_0_arm64.whl |
|---|---|
| Size | 14.7 MB |
| Tags | CPython 3.7 abi3 macOS 13.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
4e11f012146d707a66abd5dfb323d5e7cd305389bcd570f904c006963ff6db23
|
|
BLAKE2b-256 checksum How to use checksums |
fefe40bdda4cb1f4742ddf47f6112a7b7c7e8fd2fcea54d043d147a1e003dbd1
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.3
|
Security for ncu-report 2026.3.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.