Enabling Azure Pipelines for Python: A Step-by-Step Guide

Introduction:
Azure Pipelines is a powerful continuous integration and delivery (CI/CD) platform provided by Microsoft. It allows developers to automate the build, test, and deployment processes of their applications. In this blog post, we will explore how to enable Azure Pipelines for Python projects, providing a complete example with code snippets.
Prerequisites:
Before we begin, make sure you have the following prerequisites in place:
- An Azure DevOps account (you can sign up for free at https://dev.azure.com)
- 2. A Python project hosted in a version control system (e.g., GitHub, Azure Repos)
Step 1: Create an Azure Pipeline
- Log in to your Azure DevOps account and navigate to your project.
- 2. Go to Pipelines > Pipelines and click on “New Pipeline”.
- 3. Select your version control system and choose the repository where your Python project is hosted.
- 4. Azure Pipelines will automatically detect the project’s configuration file. If it doesn’t, you can manually select it.
- 5. Click on “Run” to start the pipeline.
Step 2: Define the Pipeline Configuration
- In your project’s repository, create a new file named `azure-pipelines.yml`.
- 2. Add the following code to define the pipeline configuration:
trigger:
branches:
include:
main
pool:
vmImage: ‘ubuntu-latest’
steps:
task: UsePythonVersion@0
inputs:
versionSpec: ‘3.x’
addToPath: true
-script:
python -m pip install — upgrade pip
pip install -r requirements.txt
displayName: ‘Install dependencies’
— script: |
python -m unittest discover -s tests -p ‘*_test.py’
displayName: ‘Run tests’
In this configuration, we define the trigger to run the pipeline whenever changes are pushed to the `main` branch. We specify the virtual machine image to use, which in this case is `ubuntu-latest`. The steps include setting up the Python version, installing project dependencies, and running tests.
Step 3: Commit and Push the Configuration
- Save the `azure-pipelines.yml` file and commit it to your repository.
- 2. Push the changes to trigger the pipeline.
Step 4: Monitor the Pipeline Execution
- Go back to your Azure DevOps account and navigate to Pipelines > Pipelines.
- 2. Click on your pipeline to view its execution details.
- 3. You can monitor the progress, check the logs, and see the test results.
Conclusion:
In this blog post, we explored how to enable Azure Pipelines for Python projects. We walked through the steps of creating an Azure Pipeline, defining the pipeline configuration using YAML, and monitoring the pipeline execution. By leveraging Azure Pipelines, you can automate the build, test, and deployment processes of your Python applications, ensuring faster and more reliable software delivery.
Remember, this is just a basic example to get you started. Azure Pipelines offers a wide range of features and customization options to suit your specific project requirements. Feel free to explore the Azure Pipelines documentation for more advanced configurations and integrations.
Happy coding and happy automating with Azure Pipelines!