Getting started with the API

python-gitlab only supports GitLab APIs v4.

gitlab.Gitlab class

To connect to a GitLab server, create a gitlab.Gitlab object:

import gitlab

# private token or personal token authentication
gl = gitlab.Gitlab('', private_token='JVNSESs8EwWRx5yDxM5q')

# oauth token authentication
gl = gitlab.Gitlab('', oauth_token='my_long_token_here')

# job token authentication (to be used in CI)
import os
gl = gitlab.Gitlab('', job_token=os.environ['CI_JOB_TOKEN'])

# anonymous gitlab instance, read-only for public resources
gl = gitlab.Gitlab('')

# make an API request to create the gl.user object. This is mandatory if you
# use the username/password authentication.

You can also use configuration files to create gitlab.Gitlab objects:

gl = gitlab.Gitlab.from_config('somewhere', ['/tmp/gl.cfg'])

See the Configuration section for more information about configuration files.


If the GitLab server you are using redirects requests from http to https, make sure to use the https:// protocol in the URL definition.

Note on password authentication

The /session API endpoint used for username/password authentication has been removed from GitLab in version 10.2, and is not available on anymore. Personal token authentication is the preferred authentication method.

If you need username/password authentication, you can use cookie-based authentication. You can use the web UI form to authenticate, retrieve cookies, and then use a custom requests.Session object to connect to the GitLab API. The following code snippet demonstrates how to automate this:

See issue 380 for a detailed discussion.


The gitlab.Gitlab class provides managers to access the GitLab resources. Each manager provides a set of methods to act on the resources. The available methods depend on the resource type.


# list all the projects
projects = gl.projects.list()
for project in projects:

# get the group with id == 2
group = gl.groups.get(2)
for project in group.projects.list():

# create a new user
user_data = {'email': '', 'username': 'jen', 'name': 'Jen'}
user = gl.users.create(user_data)

You can list the mandatory and optional attributes for object creation and update with the manager’s get_create_attrs() and get_update_attrs() methods. They return 2 tuples, the first one is the list of mandatory attributes, the second one is the list of optional attribute:

# v4 only
(('name',), ('path', 'namespace_id', ...))

The attributes of objects are defined upon object creation, and depend on the GitLab API itself. To list the available information associated with an object use the attributes attribute:

project = gl.projects.get(1)

Some objects also provide managers to access related GitLab resources:

# list the issues for a project
project = gl.projects.get(1)
issues = project.issues.list()

python-gitlab allows to send any data to the GitLab server when making queries. In case of invalid or missing arguments python-gitlab will raise an exception with the GitLab server error message:

>>> gl.projects.list(sort='invalid value')
GitlabListError: 400: sort does not have a valid value

You can use the query_parameters argument to send arguments that would conflict with python or python-gitlab when using them as kwargs:

gl.user_activities.list(from='2019-01-01')  ## invalid

gl.user_activities.list(query_parameters={'from': '2019-01-01'})  # OK

Gitlab Objects

You can update or delete a remote object when it exists locally:

# update the attributes of a resource
project = gl.projects.get(1)
project.wall_enabled = False
# don't forget to apply your changes on the server:

# delete the resource

Some classes provide additional methods, allowing more actions on the GitLab resources. For example:

# star a git repository
project = gl.projects.get(1)

Base types

The gitlab package provides some base types.

  • gitlab.Gitlab is the primary class, handling the HTTP requests. It holds the GitLab URL and authentication information.
  • gitlab.base.RESTObject is the base class for all the GitLab v4 objects. These objects provide an abstraction for GitLab resources (projects, groups, and so on).
  • gitlab.base.RESTManager is the base class for v4 objects managers, providing the API to manipulate the resources and their attributes.

Lazy objects

To avoid useless API calls to the server you can create lazy objects. These objects are created locally using a known ID, and give access to other managers and methods.

The following example will only make one API call to the GitLab server to star a project (the previous example used 2 API calls):

# star a git repository
project = gl.projects.get(1, lazy=True)  # no API call  # API call


If you have the administrator status, you can use sudo to act as another user. For example:

p = gl.projects.create({'name': 'awesome_project'}, sudo='user1')

Advanced HTTP configuration

python-gitlab relies on requests Session objects to perform all the HTTP requests to the Gitlab servers.

You can provide your own Session object with custom configuration when you create a Gitlab object.

Context manager

You can use Gitlab objects as context managers. This makes sure that the requests.Session object associated with a Gitlab instance is always properly closed when you exit a with block:

with gitlab.Gitlab(host, token) as gl:


The context manager will also close the custom Session object you might have used to build the Gitlab instance.

Proxy configuration

The following sample illustrates how to define a proxy configuration when using python-gitlab:

import gitlab
import requests

session = requests.Session()
session.proxies = {
    'https': os.environ.get('https_proxy'),
    'http': os.environ.get('http_proxy'),
gl = gitlab.gitlab(url, token, api_version=4, session=session)


SSL certificate verification

python-gitlab relies on the CA certificate bundle in the certifi package that comes with the requests library.

If you need python-gitlab to use your system CA store instead, you can provide the path to the CA bundle in the REQUESTS_CA_BUNDLE environment variable.


Client side certificate

The following sample illustrates how to use a client-side certificate:

import gitlab
import requests

session = requests.Session()
session.cert = ('/path/to/client.cert', '/path/to/client.key')
gl = gitlab.gitlab(url, token, api_version=4, session=session)


Rate limits

python-gitlab obeys the rate limit of the GitLab server by default. On receiving a 429 response (Too Many Requests), python-gitlab sleeps for the amount of time in the Retry-After header that GitLab sends back. If GitLab does not return a response with the Retry-After header, python-gitlab will perform an exponential backoff.

If you don’t want to wait, you can disable the rate-limiting feature, by supplying the obey_rate_limit argument.

import gitlab
import requests

gl = gitlab.gitlab(url, token, api_version=4)
gl.projects.list(all=True, obey_rate_limit=False)

If you do not disable the rate-limiting feature, you can supply a custom value for max_retries; by default, this is set to 10. To retry without bound when throttled, you can set this parameter to -1. This parameter is ignored if obey_rate_limit is set to False.

import gitlab
import requests

gl = gitlab.gitlab(url, token, api_version=4)
gl.projects.list(all=True, max_retries=12)


You will get an Exception, if you then go over the rate limit of your GitLab instance.

Transient errors

GitLab server can sometimes return a transient HTTP error. python-gitlab can automatically retry in such case, when retry_transient_errors argument is set to True. When enabled, HTTP error codes 500 (Internal Server Error), 502 (502 Bad Gateway), 503 (Service Unavailable), and 504 (Gateway Timeout) are retried. By default an exception is raised for these errors.

import gitlab
import requests

gl = gitlab.gitlab(url, token, api_version=4)
gl.projects.list(all=True, retry_transient_errors=True)


python-gitlab will by default use the timeout option from it’s configuration for all requests. This is passed downwards to the requests module at the time of making the HTTP request. However if you would like to override the global timeout parameter for a particular call, you can provide the timeout parameter to that API invocation:

import gitlab

gl = gitlab.gitlab(url, token, api_version=4)
gl.projects.import_github(ACCESS_TOKEN, 123456, "root", timeout=120.0)