This repository is the counterpart to the Jenkins Shared Library repository and contains various templates that can be used by Azure Pipelines.
This job is based on setuptools and does the following:
- builds the Python module
- validates the module (eg. linter, tests)
- deploys the module to a PyPI index
- deploys the module as a Docker image to a Docker registry
Before using the pipeline please create a new variable group
with the name GitHub
. This group contains variables required during the release/deploy
process.
Add the following variables to the group:
-
GH_TOKEN
The personal access token is used when pushing the version bump commits to the master branch during a release (see details below in Variables -> release). Change the variable type to secret.
-
GH_USER_MAIL
The email of the user assigned to the personal access token (GH_TOKEN).
Example:
[email protected]
-
GH_USER_NAME
The name of the user assigned to the personal access token.
Example:
my-ci-user
The Python pipeline allows only on-demand releases. By default the project is only built and validated. If a new release of the Python module and Docker image should be released a new build has to be queued.
In order to initiate a new release the variable release: true
needs to be defined during the queuing. This will result in bumping the
version (snapshot->release) and result in a deployed PyPI package, a Docker image and two version commits.
By default Docker images are built only during the release process. In case a snapshot image is needed one can queue a new build and set the variable
dockerSnapshot: true
. This will result in building a Docker image with a snapshot version.
Flag to enable/disable building and publishing a Docker image with the Python module.
Default: true
Filename of the Dockerfile used for defining the content of the image to be pushed to the Docker registry.
Default: Dockerfile
Azure DevOps service connector that defines the Docker registry where the Docker image should be pushed to.
Default: tomtom-docker-registry-bintray
Name of the repository an image should be pushed to. Also called a namespace in Docker terminology.
A Docker image with a Python module will be called <dockerRepo>/<name-of-module>
.
Default: python
Azure DevOps service connector that defines the PyPI index (eg. pypi.org) where PyPi modules should be deployed to.
Default: testpypi-tomtom-dev
The Python version used for creating the source distribution package deployed to the specified PyPI index.
Default: 3.6
Specify the Python versions to be used in all jobs other than deploy (which uses just pythonDeployVersion).
Default:
- name: Python35
version: "3.5"
- name: Python36
version: "3.6"
- name: Python37
version: "3.7"
Specify the job names and VM images. By default this runs on all three of the supported platforms, Linux, macOS and Windows.
Default:
- name: Linux
vmImage: ubuntu-16.04
- name: macOS
vmImage: macos-10.13
- name: Windows
vmImage: vs2017-win2016
This step-by-step guide shows how to make use of Azure Pipelines and these templates in your own project. It shows you how to create a Python project and use the Python template job from this repository.
The following steps will create a Python project generated with the tomtom-international/cookiecutter-python
template.
-
Create a project using cookiecutter
The cookiecutter will ask you at some point for a project name (
project_name
). For this tutorial we will use the nameexample-project
.cookiecutter gh:tomtom-international/cookiecutter-python
-
Push the generated project to GitHub
# Enter the previously generated project cd example-project # Initialize project for Git git init # Configure the remote to the newly create Github project git remote add origin https://github.com/tomtom-international/example-project.git git add -A git commit -am "Initial commit" git push -u origin master
-
Go to your Azure DevOps account (eg. https://dev.azure.com/your_organization/your_project/_build)
-
Create a new build pipeline for the newly created repository
-
Scroll down to the bottom of the list and click on the connection link (Search for 'You may also select a connection'):
-
Select the service connection for your GitHub account/organization (A detailed description on how to create service connections can be found in the official Azure Devops documentation)
-
Click on Run or Save and run.. to trigger the first build and wait until the build finishes to see the results: