Jubilant is a Python library that wraps the Juju CLI, primarily for use in charm integration tests. It provides methods that map 1:1 to Juju CLI commands, but with a type-annotated, Pythonic interface.
You should consider switching to Jubilant if your integration tests currently use pytest-operator (and they probably do). Jubilant has an API you'll pick up quickly, and it avoids some of the pain points of python-libjuju, such as websocket failures and having to use async. Read our design goals.
Jubilant 1.0.0 was released in April 2025. We'll avoid making breaking changes to the API after this point.
Jubilant is published to PyPI, so you can install and use it with your favorite Python package manager:
$ pip install jubilant
# or
$ uv add jubilant
Because Jubilant calls the Juju CLI, you'll also need to install Juju.
To use Jubilant in Python code:
import jubilant
juju = jubilant.Juju()
juju.deploy('snappass-test')
juju.wait(jubilant.all_active)
# Or only wait for specific applications:
juju.wait(lambda status: jubilant.all_active(status, 'snappass-test', 'another-app'))Below is an example of a charm integration test. First we define a module-scoped pytest fixture named juju which creates a temporary model and runs the test with a Juju instance pointing at that model. Jubilant'stemp_model context manager creates the model during test setup and destroys it during teardown:
# conftest.py
@pytest.fixture(scope='module')
def juju():
with jubilant.temp_model() as juju:
yield juju
# test_deploy.py
def test_deploy(juju: jubilant.Juju): # Use the "juju" fixture
juju.deploy('snappass-test') # Deploy the charm
status = juju.wait(jubilant.all_active) # Wait till the app and unit are 'active'
# Hit the Snappass HTTP endpoint to ensure it's up and running.
address = status.apps['snappass-test'].units['snappass-test/0'].address
response = requests.get(f'http://{address}:5000/', timeout=10)
response.raise_for_status()
assert 'snappass' in response.text.lower()You don't have to use pytest with Jubilant, but it's what we recommend. Pytest's assert-based approach is a straight-forward way to write tests, and its fixtures are helpful for structuring setup and teardown.