Python test and build
Create a Flow pipeline that automates Python code checkout, build, unit testing, and test reporting. Detailed logs help you identify and resolve issues quickly.
Step 1: Create a test build pipeline
Log on to the Flow console. In the upper-right corner, click Create Pipeline.
-
In the Choose a Template dialog box, select Python · Test, build , and then click Create .
Step 2: Configure the pipeline source
-
In the Pipeline Source stage, click Add Pipeline Source.
-
Select Sample Code Source. Set Code Type to Python and click Add.
Step 3: Configure the test stage
In the Test stage, configure tasks for different build clusters and build environments.
Configure the basic parameters.
Parameter
Description
Job Name
You can specify a custom job name or use the default name.
Build Cluster
The following build clusters are supported:
Build Environment
The following build environments are supported:
Specify Container Environment (Alibaba Cloud DevOps default build cluster): Flow starts a specified container on the build machine and performs the build in that container. You can select from the provided Flow System Images or specify your own custom image as the runtime environment.
Default VM Environment (supported only for self-hosted build clusters): You must select a build node from the Specify Build Nodes list. Flow installs the required environment and runs the job directly on the build machine. To speed up the build process, we recommend that you install the necessary SDKs and environment dependencies on the machine beforehand.
Default Environment (Alibaba Cloud DevOps default build cluster/self-hosted build cluster): (Deprecated) Flow uses a default container image based on the job type. The image comes pre-installed with the required SDKs and environment, and cannot be changed.
NoteDuring job execution, the build environment is exclusively allocated to you. You have full control over the environment and can customize the execution scripts.
Download Pipeline Source
When enabled, the configured source files are downloaded to the working directory. The following options are available:
Download All Pipeline Sources
Do Not Download Pipeline Sources
Download Selected Pipeline Sources
-
Configure the Python Unit Test task.
Configure the test task based on your selected build environment.
Specified container environment and Default VM environment
-
Add an Install Python step. Set the Step Name to Install Python and select a Python version for your project, such as 3.7.
-
Add an Execute Test Command step. In the Execute Command field, enter
pip install pytest pytest-html -i https://mirrors.aliyun.com/pypi/simpleto install test dependencies, thenpytest --ignore=Python --html=report/index.html || trueto run tests and generate an HTML report. -
In the Unit Test Report step, configure the following parameters.
Parameter
Description
Test report file path
Path to the test report file, such as report/index.html. The containing directory is uploaded.
testing tool
Testing tool or framework, such as Python-Pytest.
Fail on Error
If enabled, the pipeline stops when a unit test fails. This option is enabled by default.
Default environment
NotePipelines created from templates use the specified container environment by default. If you switch to the Default environment, existing task steps become invalid. Clear the original configuration and add the following steps.
Go to and configure the parameters.
Parameter
Description
Step name
A custom name for the step.
Python version
Select a Python version based on your project requirements.
Test command
Custom command to run tests and generate reports. Runs from the code repository root and supports pytest-html reports.
Test report directory
Directory containing the generated test report, such as
report. Automatically uploaded for display.Test report entry file
Entry file for the report, such as index.html.
Redline information
Define the success and failure conditions for the task.
The default test command is
pytest --html=report/index.html. In Redline Information, select metrics such as Test Pass Rate and set a comparison condition and threshold (for example, greater than100). -
Step 4: Configure the build stage
In the Python build stage, you can configure build tasks for different build environments.
Specified container environment and Default VM environment
-
In the Install Python step, select an appropriate Python version based on your build requirements.
-
Add an Execute Python build command step. The default command is
make build. In the Execute Command field, enterpython --versionto verify the Python version. -
In the Artifact upload task, configure the Upload method and related parameters.
Select an upload method and configure its parameters.
Upload to Packages
Parameters:
Parameter
Description
Add Service Connection
Click Add Service Connection and follow the on-screen instructions to create a service connection from Flow to Packages. For more information, see Manage service connections.
Repository
After the service connection is created, select a Generic repository in Packages as the destination repository.
NoteFor more information about Generic repositories, see Manage generic artifacts.
Artifact Name
This name distinguishes the output from different builds and is used by deployment jobs. We recommend using dynamic variables. The default name is
Artifacts_${PIPELINE_ID}. You can specify a custom name, such astarget1.Artifact Version
The version uniquely identifies your artifact file. You cannot push an artifact with a duplicate version to the same repository. We recommend using a dynamic variable, such as
${DATETIME}.Package Path
The path to the files or directories to package, relative to your project's root folder. For example,
target/. You can specify multiple paths.Include package path in artifact
If selected, the generated archive includes the full directory structure specified in Package Path. If cleared, the archive contains only the files. This option is automatically set to
trueif you specify multiple package paths.Archive to public storage
Parameters:
Parameter
Description
Artifact Name
This name distinguishes the output from different builds and is used by deployment jobs. We recommend using dynamic variables. The default name is
Artifacts_${PIPELINE_ID}. You can specify a custom name, such astarget1.Package Path
The path to the files or directories to package, relative to your project's root folder. For example,
target/. You can specify multiple paths.Include package path in artifact
If selected, the generated archive includes the full directory structure specified in Package Path. If cleared, the archive contains only the files. This option is automatically set to
trueif you specify multiple package paths.
Default environment
Pipelines created from templates use the specified container environment by default. If you switch to the Default environment, existing task steps become invalid. Clear the original configuration and add the following steps.
-
Go to and configure the build commands.
Parameter
Description
Step name
A custom name for the step.
Python version
Select a Python version based on your project requirements.
Execute build command
The default command for Python is
python --version.In Advanced Settings, Build Environment Specification defaults to DEFAULT and Timeout to 240 minutes.
-
Go to and configure the artifact parameters.
Select an upload method and configure its parameters.
Upload to Packages
Parameters:
Parameter
Description
Add Service Connection
Click Add Service Connection and follow the on-screen instructions to create a service connection from Flow to Packages. For more information, see Manage service connections.
Repository
After the service connection is created, select a Generic repository in Packages as the destination repository.
NoteFor more information about Generic repositories, see Manage generic artifacts.
Artifact Name
This name distinguishes the output from different builds and is used by deployment jobs. We recommend using dynamic variables. The default name is
Artifacts_${PIPELINE_ID}. You can specify a custom name, such astarget1.Artifact Version
The version uniquely identifies your artifact file. You cannot push an artifact with a duplicate version to the same repository. We recommend using a dynamic variable, such as
${DATETIME}.Package Path
The path to the files or directories to package, relative to your project's root folder. For example,
target/. You can specify multiple paths.Include package path in artifact
If selected, the generated archive includes the full directory structure specified in Package Path. If cleared, the archive contains only the files. This option is automatically set to
trueif you specify multiple package paths.Archive to public storage
Parameters:
Parameter
Description
Artifact Name
This name distinguishes the output from different builds and is used by deployment jobs. We recommend using dynamic variables. The default name is
Artifacts_${PIPELINE_ID}. You can specify a custom name, such astarget1.Package Path
The path to the files or directories to package, relative to your project's root folder. For example,
target/. You can specify multiple paths.Include package path in artifact
If selected, the generated archive includes the full directory structure specified in Package Path. If cleared, the archive contains only the files. This option is automatically set to
trueif you specify multiple package paths.
Step 5: Run the pipeline and check the results
-
After the pipeline completes, the results page shows #2 Succeeded . The visualization displays the Pipeline Source (master branch), Test stage (Python unit test, 21s), and Build stage (Python build, 47s) with the output artifact.
-
Click Logs on a task node to view its execution log. A green checkmark indicates success. For example, the artifact upload log confirms the artifact was uploaded.
-
If you used the Organization-private generic artifact repository, find the artifact in Artifact Repository Packages. Generic artifact management.