Template for Python projects

This project contains a template for Python apps that implement training and inference of Machine Learning models.

With this template, you will be able to:

• Use Python with the usual libraries for data science
• Write tests for your app using the provided examples

This README.md is full of details for an easier reuse of this template. But beware, erase its contents and include yours before publishing your project.

Dependencies

The only strong requirement is that you this template is written for Python 3. You can adapt it to Python 2 with minimal changes (most likely, changing the print statements through the code)

Utilities and common libraries

This template imports tensorflow. The provided scripts will install these dependencies if they are missing in your system.

If you need to include additional dependencies, please add new lines to the file requirements.txt, with the package name.

You can include any package available in the PyPi.

Directories structure

In the top dir, you will find the following two files:

• README.md: This file will be shown as the default page in the Overview of your project in Bitbucket or Stash. Use it as an example of a README for your project.
• setup.py: The main setuptoolsscript for your project. You should edit it to change the common properties of your project. If you want to change the version of your project, edit src/__init__.py instead.
• requirements.txt: Dependencies that must be installed for your project to work. Include one package name per line. The packages should be available in the official PyPi repository

There is also a hidden file:

• .gitignore: Excludes many temporary and generated files from Git.

The template has the following folders:

• trainer: Directory for the sources. This directory is a Python package, with the following contents:
  • __init__.py: Edit this file to update the version the version of your project, and for any other tasks common to your package
  • task.py: A simple Python script with a main function, and some small functions (intended to showcase how to write a test).
• tests: This directory contains the tests included in this template as examples. Use the files included here as templates to write your own tests.

A note on testing

This template is using PyTest for the tests, with some additional plugins for coverage calculations.

To launch the tests, PyTest offers different options. The recommended way to trigger the unit tests is by running the following command:

$ python setup.py test

You can also use the following options:

• The pytest script
• Calling it as a module in the top dir of your project (this is equivalent to running python setup.py test)

We discourage the use of the pytest script for testing. If you use this script, the top dir of your project is not included in the path, and you need to explicitly add it to your test. Only after that you are able to import your own modules for the tests.

For instance, if your module is called src, and you are using the pytest script, you will need to do something like the following:

import os
import sys
sys.path.insert(0, os.path.pardir)
from trainer import ...

This is a violation of the Python PEP8 style guide, because you should always group all the import statements together. But this is impossible for your src module unless you add it to the path.

This problem does not exist if you use PyTest as a module. This is the approach used in this template. In that case, the module src is simply available in the path, you don't need to tweak any system path. When using python -m pytest, the previous code would become:

from trainer import ...

So for testing your project in local, please do python -m pytest rather than using pytest. In the CI jobs, the default pipeline scripts are using python -m pytest.