Skip to main content

Nvidia Data Science Workbench

Project description

Data Science Workbench

Build process

Clone the repo, build the docker image for the build environment, e.g. cd nvdss && sh build-docker.sh. Now you can launch your build docker container, e.g. sh run-docker.sh

To run the build:

sh build.sh none
# if you want to push to the pip test or prod
# sh build.sh test
# sh build.sh prod

The build creates a .whl file, e.g. dist/nvdsw-0.0.382-py3-none-any.whl

Now, you can reinstall nvdsw, e.g. do this outside of docker

pip3 install --force-reinstall dist/nvdsw-0.0.382-py3-none-any.whl

Now you can launch nvdsw:

nvdsw

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

nvdsw-0.0.389-py3-none-any.whl (170.7 kB view details)

Uploaded Python 3

File details

Details for the file nvdsw-0.0.389-py3-none-any.whl.

File metadata

  • Download URL: nvdsw-0.0.389-py3-none-any.whl
  • Upload date:
  • Size: 170.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

File hashes

Hashes for nvdsw-0.0.389-py3-none-any.whl
Algorithm Hash digest
SHA256 fe20041134b86fe6da6bba447b97ebb5595b91db46ea4e0726f728914d60eef0
MD5 d3ae5d8a835815619b7385f03de59cee
BLAKE2b-256 444f7050af2b1cb65b45e23253f2d7ac9ee7427095b6ae466919ee587ac82bc7

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page