How to simulate GitLab CI stages in Python

Build a lightweight Python mock of GitLab CI pipeline stages to test job sequencing and output locally.

Easy Python 3.9+ Aug 9, 2026 Production deployment patterns 14 views 0 copies

gitlab ci simulation stages

Python code

32 lines

Python 3.9+

def mock_gitlab_ci_stages():
    stages = ["build", "test", "deploy"]
    stage_status = {}

    for stage in stages:
        jobs = []

        if stage == "build":
            jobs = ["compile", "package"]
        elif stage == "test":
            jobs = ["unit", "integration", "e2e"]
        elif stage == "deploy":
            jobs = ["staging", "production"]

        stage_status[stage] = {
            "jobs": jobs,
            "status": None
        }

    for stage, info in stage_status.items():
        for job in info["jobs"]:
            print(f"{stage}:{job}:running")

    print("mock pipeline executed")

    return stage_status


if __name__ == "__main__":
    result = mock_gitlab_ci_stages()
    for stage, config in result.items():
        print(f"Stage {stage} has {len(config['jobs'])} jobs")

Output

stdout

build:compile:running
build:package:running
test:unit:running
test:integration:running
test:e2e:running
deploy:staging:running
deploy:production:running
mock pipeline executed
Stage build has 2 jobs
Stage test has 3 jobs
Stage deploy has 2 jobs

How it works

This mock represents a GitLab CI pipeline as a dictionary mapping stage names to job lists and statuses. The loop assigns jobs per stage, then iterates all stages and jobs to simulate execution order. Statuses are set to None as placeholders for real results. The script prints each job as it runs, then saves the full structure for further assertions. Using nested dicts makes it easy to extend with statuses like 'success' or 'failed'.

Common mistakes

Forgetting to set status per job, leaving None in final reports
Hardcoding stage order instead of reading from .gitlab-ci.yml
Using list of tuples instead of dicts, making updates clunky
Not checking that all stages run in correct sequence

Variations

Use dataclasses to model Stage and Job objects for type safety
Read stage definitions from a YAML file using PyYAML for closer simulation

Real-world use cases

Testing CI pipeline logic locally before pushing to GitLab, speeding up feedback loops.
Simulating deployment steps in development environments to validate job order without running containers.
Training new team members on CI stages with a safe, interactive demo.

How to simulate GitLab CI stages in Python

Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

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Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

More from Production deployment patterns

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Tutorials

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