https://github.com/valohai/minihai

An open-source application for running notebooks server-side
https://github.com/valohai/minihai

data-science jupyter jupyter-notebook machine-learning notebook

Last synced: 11 months ago
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An open-source application for running notebooks server-side

• Host: GitHub
• URL: https://github.com/valohai/minihai
• Owner: valohai
• License: agpl-3.0
• Created: 2020-05-14T14:16:29.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2022-12-26T22:00:01.000Z (over 3 years ago)
• Last Synced: 2023-08-11T11:31:55.519Z (almost 3 years ago)
• Topics: data-science, jupyter, jupyter-notebook, machine-learning, notebook
• Language: Python
• Homepage: https://valohai.com/minihai/
• Size: 52.7 KB
• Stars: 6
• Watchers: 10
• Forks: 2
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
Minihai

=======

Installation instructions (dev)

-------------------------------

* Create a new Python 3.6+ virtualenv and activate it

* Run `pip install -e .`

* Run `minihai start`

* Point your Jupyhai-enabled Jupyter Notebook to use Minihai for execution:  

  `env VALOHAI_HOST=http://127.0.0.1:8000/ jupyter notebook`

 

Configuration

-------------

You can configure Minihai with environment variables or a YAML-based configuration file.

Most configuration settings will be more conveniently set in a file. Set the `MINIHAI_CONFIG`

environment variable, or start Minihai with the `-c` option to specify the path to the configuration file.

### Authentication

By default, Minihai operates without any access control at all. This is undesirable when the server

is accessible by the world at large. For the time being, the only authentication scheme

is a very simple mapping of usernames to *unencrypted* passwords, e.g.

```yaml

auth:

  arthur: teatime

  bob: almighty

  ford: towel

```