Testing¶
You can test Quart-Schema validated routes the same way you’d test
normal Quart routes (everything works the same). In addition
Quart-Schema allows Pydantic models, or dataclasses to be sent via the
test client as json or form data, for example,
@dataclass
class DCDetails:
name: str
age: Optional[int] = None
@pytest.mark.asyncio
async def test_send_dataclass() -> None:
...
test_client = app.test_client()
response = await test_client.post("/", json=DCDetails(name="bob", age=2))
# Or
response = await test_client.post("/", form=DCDetails(name="bob", age=2))
Hypothesis testing¶
It can be difficult to write test cases for complex structures that cover all the edge cases (data state space). Hypothesis is a library that can generate data for you that covers the edge cases. As Hypothesis can infer how to construct type-annotated classes and Pydantic ships a Hypothesis plugin for specific types it is possible to test Quart-Schema routes with Hypothesis generated data, for example,
from hypothesis import given, strategies as st
from dataclasses import dataclass
# Other imports not shown
@dataclass
class DCDetails:
name: str
age: Optional[int] = None
@given(st.builds(DCDetails))
@pytest.mark.asyncio
async def test_index(data: DCDetails) -> None:
app = Quart(__name__)
QuartSchema(app)
@app.route("/", methods=["POST"])
@validate_request(DCDetails)
async def index(data: DCDetails) -> Any:
return data
test_client = app.test_client()
response = await test_client.post("/", json=data)
assert response.status_code == 200
Note
Hypothesis must be installed seperately.