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Tool for managing machine learning model and service projects and other fast paced python projects.

Project description

Unit tests

Bouillon contains; a) a project structure, b) a Command Line Interface (CLI) for building, testing, etc., that are easy to adapt and, c) a module that provides helper functionality when writing your cli.

The idea is that you together with your project ship a program that assist the developers to setup a development environment, run tests, release the project, and other tedious tasks, helping you to;

  • Reduce time spent on repetetive tasks.
  • Guareentee a well defined development environement, reducing human error.
  • Simplify setup of CI/CD, as the same commands locally and remotely.

Features

The cli provides various useful functionality using various projects, e.g.:

  • Pep8 syntax enforcement.
  • Static Code Analysis.
  • Verification of installed dependencies against requirements.
  • Verification of licenses in included modules.
  • Execution of unit tests.
  • Coverage of unit tests.
  • API documentation.
  • Updating of dependencies.

Getting Started

git clone git@github.com:janusheide/bouillon.git
cd bouillon

python boil --help

Will pip install packages, a venv is recommended:

python boil setup
python boil test

Start A New Project

You can use this repository as a template, use repository as a template guide.

Alternatively a more manual approach could be something like the following, where new_project is a empty git repository.

Clone the repository and remove the history:

git clone git@github.com:janusheide/bouillon.git
cd bouillon
rm -rf .git

Copy the project structure into your existing (empty) git repository:

cp -r * ../new_project
cd ../new_project/
git add .
git commit -m 'Initial commit'
git push

You should now have a project with the following structure, and should modify as indicated below:

├── boil -> cicd/boil.py
├── cicd (modify)
│   ├── boil.py
│   ├── licenses.ini
│   ├── mypy.ini
│   └── requirements.txt
├── LICENSE.txt (replace)
├── NEWS.rst (replace)
├── README.rst (replace)
├── setup.py (modify)
├── src (replace)
│   ├── bouillon
│   │   ├── bouillon.py
│   │   ├── __init__.py
│   │   └── requirements.txt
└── test (replace)
    ├── cicd
    │   └── test_boil_cli.py
    ├── requirements.txt
    └── src
        ├── test_bouillon.py
        └── test___init__.py

At some point it might be convenient to fork this repository, make any changes you need and use that as your template repository.

Ways of Inclusion

You can include the bouillon module in a number of ways in your script, below are some options prioritized options.

Pip Install During Setup Step

Install the module using Pip. This requires that the initial setup step can be executed without importing the module.

Pip Install Prior to Executing Script

Install the module prior to running any script commands, this adds an extra step and consequently the script setup step only partly setup the environment.

Copy Module File

Copy the module implementation (bouillon.py) into your project and import it from the local file in your script. Consequently you will have to manually update the module or implement a way to push a new module version into your repository.

Copy Module Source Into CLI file

Copy the module implementation or the functionality you need into your cli file. While it is simple but even more inconvenient to keep the module functionality up to date.

Logging

Supports standard log levels; DEBUG, INFO, WARING, ERROR, CRITICAL, and writing log to a file.

Set the log level to debug:

python boil --log-level=DEBUG test

Set the log level to debug and redirect output from executed commands to bar.log:

python boil --log-level=DEBUG test >> bar.log

Set the log level to debug and redirect output from executed commands to bar.log and log information to foo.log:

python boil --log-level=DEBUG --log-file=foo.log test >> bar.log

Set the log level to debug and redirect output from executed commands and log information to foo.log:

python boil --log-level=DEBUG --log-file=foo.log test >> foo.log

Goals

The primary use is intended for, but not limited to, projects with frequently releases, e.g. ML models and services. The goal is to make it quick and easy to set up a new project with the basic testing and releasing functionality.

User Friendliness

  • Make the life of the user easier.
  • Use plain Python and modules that many are familiar with.
  • Quick and easy to setup and run repetitive tasks.
  • All tasks should be equally easy to rin locally as in a CI/CD environement.

Reproducibility

  • Results and builds should be easy to reproduce.
  • All dependencies must be hard (versioned).
  • The master should always be green.

Simplicity

  • Simplicity over features.
  • Components should be easy to replace.

Automation

  • Reduce maintenance, repetitive tasks, and human errors.
  • Easy to upgrade dependencies.
  • Use merge policies and triggered and scheduled events.

Project details


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