Testing plugins

We recommend using pytest to write automated tests for your plugins.

If you use the template described in Starting an installable plugin using cookiecutter your plugin will start with a single test in your tests/ directory that looks like this:

from datasette.app import Datasette
import pytest


@pytest.mark.asyncio
async def test_plugin_is_installed():
    datasette = Datasette([], memory=True)
    response = await datasette.client.get("/-/plugins.json")
    assert response.status_code == 200
    installed_plugins = {p["name"] for p in response.json()}
    assert (
        "datasette-plugin-template-demo"
        in installed_plugins
    )

This test uses the datasette.client object to exercise a test instance of Datasette. datasette.client is a wrapper around the HTTPX Python library which can imitate HTTP requests using ASGI. This is the recommended way to write tests against a Datasette instance.

This test also uses the pytest-asyncio package to add support for async def test functions running under pytest.

You can install these packages like so:

pip install pytest pytest-asyncio

If you are building an installable package you can add them as test dependencies to your setup.py module like this:

setup(
    name="datasette-my-plugin",
    # ...
    extras_require={"test": ["pytest", "pytest-asyncio"]},
    tests_require=["datasette-my-plugin[test]"],
)

You can then install the test dependencies like so:

pip install -e '.[test]'

Then run the tests using pytest like so:

pytest

Using pdb for errors thrown inside Datasette

If an exception occurs within Datasette itself during a test, the response returned to your plugin will have a response.status_code value of 500.

You can add pdb=True to the Datasette constructor to drop into a Python debugger session inside your test run instead of getting back a 500 response code. This is equivalent to running the datasette command-line tool with the --pdb option.

Here's what that looks like in a test function:

def test_that_opens_the_debugger_or_errors():
    ds = Datasette([db_path], pdb=True)
    response = await ds.client.get("/")

If you use this pattern you will need to run pytest with the -s option to avoid capturing stdin/stdout in order to interact with the debugger prompt.

Using pytest fixtures

Pytest fixtures can be used to create initial testable objects which can then be used by multiple tests.

A common pattern for Datasette plugins is to create a fixture which sets up a temporary test database and wraps it in a Datasette instance.

Here's an example that uses the sqlite-utils library to populate a temporary test database. It also sets the title of that table using a simulated metadata.json configuration:

from datasette.app import Datasette
import pytest
import sqlite_utils


@pytest.fixture(scope="session")
def datasette(tmp_path_factory):
    db_directory = tmp_path_factory.mktemp("dbs")
    db_path = db_directory / "test.db"
    db = sqlite_utils.Database(db_path)
    db["dogs"].insert_all(
        [
            {"id": 1, "name": "Cleo", "age": 5},
            {"id": 2, "name": "Pancakes", "age": 4},
        ],
        pk="id",
    )
    datasette = Datasette(
        [db_path],
        metadata={
            "databases": {
                "test": {
                    "tables": {
                        "dogs": {"title": "Some dogs"}
                    }
                }
            }
        },
    )
    return datasette


@pytest.mark.asyncio
async def test_example_table_json(datasette):
    response = await datasette.client.get(
        "/test/dogs.json?_shape=array"
    )
    assert response.status_code == 200
    assert response.json() == [
        {"id": 1, "name": "Cleo", "age": 5},
        {"id": 2, "name": "Pancakes", "age": 4},
    ]


@pytest.mark.asyncio
async def test_example_table_html(datasette):
    response = await datasette.client.get("/test/dogs")
    assert ">Some dogs</h1>" in response.text

Here the datasette() function defines the fixture, which is than automatically passed to the two test functions based on pytest automatically matching their datasette function parameters.

The @pytest.fixture(scope="session") line here ensures the fixture is reused for the full pytest execution session. This means that the temporary database file will be created once and reused for each test.

If you want to create that test database repeatedly for every individual test function, write the fixture function like this instead. You may want to do this if your plugin modifies the database contents in some way:

@pytest.fixture
def datasette(tmp_path_factory):
    # This fixture will be executed repeatedly for every test
    ...

Testing outbound HTTP calls with pytest-httpx

If your plugin makes outbound HTTP calls - for example datasette-auth-github or datasette-import-table - you may need to mock those HTTP requests in your tests.

The pytest-httpx package is a useful library for mocking calls. It can be tricky to use with Datasette though since it mocks all HTTPX requests, and Datasette's own testing mechanism uses HTTPX internally.

To avoid breaking your tests, you can return ["localhost"] from the non_mocked_hosts() fixture.

As an example, here's a very simple plugin which executes an HTTP response and returns the resulting content:

from datasette import hookimpl
from datasette.utils.asgi import Response
import httpx


@hookimpl
def register_routes():
    return [
        (r"^/-/fetch-url$", fetch_url),
    ]


async def fetch_url(datasette, request):
    if request.method == "GET":
        return Response.html(
            """
            <form action="/-/fetch-url" method="post">
            <input type="hidden" name="csrftoken" value="{}">
            <input name="url"><input type="submit">
        </form>""".format(
                request.scope["csrftoken"]()
            )
        )
    vars = await request.post_vars()
    url = vars["url"]
    return Response.text(httpx.get(url).text)

Here's a test for that plugin that mocks the HTTPX outbound request:

from datasette.app import Datasette
import pytest


@pytest.fixture
def non_mocked_hosts():
    # This ensures httpx-mock will not affect Datasette's own
    # httpx calls made in the tests by datasette.client:
    return ["localhost"]


async def test_outbound_http_call(httpx_mock):
    httpx_mock.add_response(
        url="https://www.example.com/",
        text="Hello world",
    )
    datasette = Datasette([], memory=True)
    response = await datasette.client.post(
        "/-/fetch-url",
        data={"url": "https://www.example.com/"},
    )
    assert response.text == "Hello world"

    outbound_request = httpx_mock.get_request()
    assert (
        outbound_request.url == "https://www.example.com/"
    )