A command line interface (CLI) application for managing machine learning workflows using Docker
Project description
Docker Jobber
Docker Jobber (jobber) is a command line interface (CLI) application for managing machine learning workflows using Docker.
Please see the homepage for documentation and examples
Installation
You'll need Docker of course, then install the jobber command using pip (Docker Jobber requires Python3):
pip install docker-jobber
Version History
0.3.9 (2019-04-09)
- Credentials
- Merge all config files on directory path
- Fixed: successful build pushes to defined registries
- Default registry configuration name changed to 'default-registry'
0.3.8 (2019-04-09)
- Really fix PyYAML security hole
0.3.7 (2019-04-09)
- Fix PyYAML security hole
0.3.6 (2019-04-09)
- Initial release
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
docker-jobber-0.3.9.tar.gz
(19.0 kB
view details)
File details
Details for the file docker-jobber-0.3.9.tar.gz.
File metadata
- Download URL: docker-jobber-0.3.9.tar.gz
- Upload date:
- Size: 19.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.18.4 setuptools/40.0.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | bed920c8a0c749a34b0bb6c3e7b8eee98b7f996fc1ba49a4459ad03afc1247a6 |
|
| MD5 | af888ab30490358fc2e6ad09e00e9030 |
|
| BLAKE2b-256 | 0b09571b99cb91acb61603aefebea37db54651ce3abec7b5ba55b1076abf8014 |
