Gitlab Runner Python

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Pytest is used to run unit tests in the Analytics project. The tests are executed from the root directory of the project with the pythonpytest CI pipeline job. The job produces a JUnit report of test results which is then processed by GitLab and displayed on merge requests. Writing New Tests.

Pure python gitlab-runner

1. GitLab Runner can also run inside a Docker container or be deployed into a Kubernetes cluster. View some best practices for how to use and administer GitLab Runner. GitLab Runner versions. For compatibility reasons, the GitLab Runner major.minor version should stay in sync with the GitLab major and minor version. Older runners may still work.
2. Python development guidelines SCSS style guide Shell scripting standards and style guidelines Sidekiq debugging Sidekiq style guide. GitLab Runner officially supported binaries are available for the following architectures: x86, AMD64, ARM64, ARM, s390x, ppc64le.

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14.3.0

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Gitlab Runner Source Code

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Unofficial implementation of the GitLab runner client for making customised CI runners

Project description

Python Gitlab Module

An unofficial Python implementation of the API for creating customised GitLab CI runners.

This package provides the basic functionality for registering a Runner.This object can then be used to request a Job and communicate the log, status and artifacts back to GitLab.No functionality is provided to execute the payloads defined in the .gitlab-ci.yml.

This package was originally developed to support LHCb’s Analysis Productions by providing a CI runner that could submit jobs to LHCbDIRAC.More details can be found in TODO.

Registering a Runner

Python Gitlab Example

The simplest way to register a new Runner is with the included command line tool:

For example

where arguments can be found by navigating to the “CI/CD” page of the desired repository’s settings.

Getting jobs

After a runner has been registered it can be loaded from the .json file and used to request jobs:

Executing jobs

Gitlab Runner Python Interview

A minimal CI executor might run as follows:

See the reference Job documentation for the full list of available properties.

Persisting jobs

For long running jobs it may be desirable to persist the job object between calls.This can be done using a similar interface to the pickle module in the Python standard library:

Note: The job log is included in the persisted data therefore the Job object cannot be persisted once and loaded multiple times without loosing the log messages.

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Gitlab Runner Python Example