build-harness 0.0.0

CI build harness embodying best practices for Python projects.

A command line CI pipeline build harness utility for Python 3 projects based on known best practices.

There are lots of accessories that are useful for establishing a high quality Python pipeline and copy-pasting all the bits and pieces to initialize a new project is tedious and error prone. This utility aims to streamline the creation of a project with all the necessary development and pipeline dependencies and a ready to run pipeline.

Why not just use CookieCutter?

build_harness complements the use of CookieCutter nicely - you can use build_harness to establish and maintain your Python project pipeline with minimal effort and then focus on using CookieCutter to implement your business specific customization of build, test and analysis options.

build_harness also lends itself to being easily applied across multiple use cases, from the pipeline itself, to pre-commit hooks, to developers manually running specific components of the pipeline for test and debug.

Contents

• 1 Installation

• 2 Getting started

• 3 Concepts

  • 3.1 Release Management

    • 3.1.1 VERSION file workflow

1 Installation

The package is available from PyPI. Installing into a virtual environment is recommended.

# A first time installation creating a virtual environment inside the project
# directory
cd my_project_repo
python3 -m venv .venv; .venv/bin/pip install build_harness

Note that Ubuntu, for example, separates pip and venv installations from the main Python installation and they are not installed by default, so if you are working with a fresh Ubuntu install you will need something like this to acquire them.

sudo apt update && sudo apt install -y python3-pip python3-venv

2 Getting started

Installation makes a command line utility build-harness available in the virtual environment. There are currently five groups of sub-commands available.

acceptance

Run and manage Gherkin features and step files using the behave package.

formatting

Format source code to PEP-8 standard using the isort and black packages.

install

Install and manage project dependencies in the virtual environment. The install command will look for a virtual environment .venv in the project root directory and create it if needed. Then it installs and manages all the project dependencies there.

package

Build wheel and sdist packages of the project.

publish

Publish project artifacts to publication repositories such as PyPI and readthedocs.

static-analysis

Run static analysis on source code; pydocstyle, flake8 and mypy packages.

unit-test

Run unit tests of the project using pytest.

Further options for these commands can be explored using the --help argument.

build-harness --help
build-harness install --help

A quick summary of using each of the sub-commands.

# Install project dependencies into the virtual environment.
build-harness install
# Check if project dependencies are up to date in the virtual environment.
build-harness install --check

# Format code to PEP-8 standards using isort, black.
build-harness formatting
# Fail (exit non-zero) if formatting needs to be applied.
build-harness formatting --check

# Run pydocstyle, flake8 and mypy analysis on the project.
build-harness static-analysis

# Run pytest on unit tests in the project.
build-harness unit-test
# Test that coverage passes the specified threshold.
build-harness unit-test --check <int>

# Run Python behave on Gherkin based features.
build-harness acceptance tests
# Generate step file snippets for unimplemented features.
build-harness acceptance snippets
# Report where tags are used in feature files.
build-harness acceptance tags

3 Concepts

For now, the sub-commands are limited to a specific set of tools (the ones I have found to be most useful).

Fine tuning configuration of the underlying tools is generally possible using configuration files such as sections added to pyproject.toml or setup.cfg or tool specific files in some cases.

3.1 Release Management

Python has myriad ways of defining the release id of a project for publication and almost all of them require some custom workflow from the user to make it work for automation so it’s really difficult to support all of them. For this reason the default packaging option does nothing relating to the release id and assumes that the user has done whatever is necessary for their workflow to correctly define the release id for packaging.

There’s a fairly useful survey of Python release control in the answers to this StackOverflow question. The setuptools_scm package also has some useful notes on different ways to control release id insertion to a package.

Having said that, the goal of this project is to have useful out-of-the-box functionality as much as possible so described here are workflows that have been integrated into the build_harness project.

3.1.1 VERSION file workflow

This is the workflow used by the build_harness project itself, so you can refer to the source code for an example of how to implement this workflow.

• Install a simple text file named VERSION in the top-level Python package of your project.

• The file should be committed to source control with an acceptable “benign” release id that is readily identifiable as not a real release.

• The package reads the content of the VERSION file and applies it to the __version__ variable in the package.

• Use the snippets below to set the Python __version__ variable for the project from the content of the VERSION file.

Some Internet discussions on this topic recommend that the VERSION is not committed to source control. The problem I have historically experienced is that this complicates the local build because the developer must remember to create a useful “benign” VERSION file for themselves otherwise their build will fail; if it’s created locally and every developer needs it, then why not just commit it to source control and avoid the “toil”? If the pipeline somehow fails to update the VERSION file correctly, then at least an invalid package is created with the benign release id that can be readily identified as an error to fix.

The committed file should contain a default value that is readily recognisable as having not been built by a pipeline. eg. If a developer builds the package locally it should be clear that the package they built is not an official release (which should only have been built by a pipeline).

A default value I have historically used is “0.0.0”. Within the limitations defined by PEP-440 another option could be “0.0.0+local”.

For manual release definition you have to ensure that the content of the VERSION file reflects the release id you are releasing. Doing this manually is error prone and easily acquires a number of deficiencies with respect to how organizations often want to organize their releases.

For automation the pipeline just needs to be able to update the content of the file with the release id defined for a release; this is easily achieved by defining semantic version tags on the repo (or some similar such rule that can be incorporated into the pipeline code) as a formal release and having the pipeline update the VERSION file with the tag text.

# top-level __init__.py
"""flit requires top-level docstring summary of project"""

from ._version import acquire_version

__version__ = acquire_version()

# _version.py
import pathlib

def acquire_version() -> str:
    """
    Acquire PEP-440 compliant version from VERSION file.

    Returns:
        Acquired version text.
    Raises:
        RuntimeError: If version is not valid.
    """
    here = pathlib.Path(__file__).parent
    version_file_path = (here / "VERSION").absolute()

    with open(version_file_path) as version_file:
        # Note that the release id is expected to be simple text;
        # no quotes, no comments, nothing in the file except the PEP-440 release id.
        version = version_file.read().strip()

    if not version:
        raise RuntimeError("Unable to acquire version")

    return version