That’s where the GitLab API comes in—and using it with Python makes integration both powerful and easy.
In this guide, we’ll walk through everything you need to know to get started with the GitLab API in Python—from setting up access tokens to making real API requests.
What is the GitLab API?
The GitLab API is a RESTful and GraphQL interface that lets you automate nearly every aspect of GitLab—from managing repositories and issues to controlling pipelines, users, and groups.
With it, you can:
- Create and manage projects
- Trigger pipelines
- Assign issues
- Fetch repository data
- And much more
The GitLab API is especially useful for scripting repetitive tasks, integrating with other services, or building internal tools.
Why Use Python with GitLab API?
Python is one of the most popular programming languages for automation, scripting, and backend development. Thanks to its simplicity and readability, it’s a great choice for working with REST APIs.
Some benefits of using Python with the GitLab API:
- Simple HTTP request handling with libraries like requests
- Mature SDKs like python-gitlab
- Excellent community support and documentation
- Easy integration with CI/CD scripts
Getting Started: Prerequisites
To start using the GitLab API with Python, you’ll need:
- A GitLab account (self-hosted or GitLab.com)
- A Personal Access Token (PAT) with the necessary API scopes
- Python 3 installed on your system
- The python-gitlab package or the requests library
Step 1: Install the python-gitlab Library
While you can use Python’s built-in requests library to make direct API calls, GitLab provides an official SDK called python-gitlab that simplifies this process.
Install it using pip:
pip install python-gitlab
Step 2: Authenticate with GitLab
Create a personal access token by going to:
GitLab > Settings > Access Tokens
Make sure you include the correct scopes like api, read_repository, or write_repository.
Once you have your token:
import gitlab
# Replace with your GitLab URL and token
gl = gitlab.Gitlab('https://gitlab.com', private_token='YOUR_ACCESS_TOKEN')
# Test the connection
user = gl.user
print(f"Logged in as: {user.username}")
Step 3: Interact with Projects
Let’s fetch your GitLab projects:
projects = gl.projects.list(owned=True)
for project in projects:
print(f"{project.name} - {project.web_url}")
To create a new project:
project = gl.projects.create({'name': 'demo-project'})
print(f"Created project: {project.name}")
Step 4: Work with Issues
You can automate issue creation and management using the API:
project = gl.projects.get('namespace/demo-project')
issue = project.issues.create({'title': 'Bug in login flow', 'description': 'Steps to reproduce...'})
print(f"Issue created: {issue.web_url}")
To list issues:
for issue in project.issues.list():
print(f"{issue.title} - Status: {issue.state}")
Step 5: Trigger a CI/CD Pipeline
To trigger a pipeline for a project:
project = gl.projects.get('namespace/demo-project')
pipeline = project.pipelines.create({'ref': 'main'})
print(f"Pipeline triggered: ID {pipeline.id}")
You can also monitor the pipeline status:
pipeline = project.pipelines.get(pipeline.id)
print(f"Pipeline status: {pipeline.status}")
Making Raw API Requests (Optional)
If you prefer not to use python-gitlab, you can use the requests library:
import requests
headers = {'PRIVATE-TOKEN': 'YOUR_ACCESS_TOKEN'}
response = requests.get('https://gitlab.com/api/v4/projects', headers=headers)
projects = response.json()
for project in projects:
print(project['name'])
Real-World Use Cases
Here are some ways developers and DevOps engineers use the GitLab API with Python:
- Automating repository setup for new team members
- Auto-assigning issues based on labels
- Bulk-closing outdated issues
- Monitoring pipeline health across multiple projects
- Generating custom dashboards from GitLab data
Conclusion
Integrating the GitLab API with Python empowers you to build custom tools, automate processes, and supercharge your DevOps workflow. Whether you're managing CI pipelines, repositories, or team collaboration, Python's versatility combined with GitLab’s robust API makes it a powerful combo.
Start simple, build iteratively, and unlock the full potential of automation in your GitLab environment.
Want to test your GitLab APIs automatically?
Try Keploy — an open-source tool that auto-generates test cases and mocks from real API traffic. Perfect for developers using GitLab CI pipelines!
Read more on https://keploy.io/blog/community/introduction-to-gitlab-python-api