Add app scaffold and workflows
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2025-12-03 08:58:34 +01:00
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"""Test suite for backend."""

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from fastapi.testclient import TestClient
from hypothesis import given, settings
from hypothesis import strategies as st
# Import the main FastAPI application instance from your source code
from main import app
# Initialize the TestClient to make requests against your FastAPI app instance
client = TestClient(app)
def test_liveness_ok():
"""
Test the basic liveness endpoint.
A liveness probe checks if the container is running and responsive.
It should always return a 200 OK status and the text 'live'.
"""
response = client.get("/health/live")
assert response.status_code == 200
assert response.text == "live"
@given(st.text(min_size=0, max_size=16))
@settings(max_examples=10)
def test_liveness_resilience_to_query_noise(noise: str):
"""
Use Hypothesis for property-based testing.
This test ensures that the liveness endpoint is robust and remains functional
even when unexpected or garbage query parameters ("noise") are provided in the URL.
The `given` decorator generates various string inputs for the 'noise' parameter.
"""
# Pass arbitrary query parameters to the endpoint
response = client.get("/health/live", params={"noise": noise})
assert response.status_code == 200
assert response.text == "live"
def test_readiness_ok():
"""
Test the basic readiness endpoint.
A readiness probe checks if the container is ready to accept traffic (e.g., database connection established).
It should return a 200 OK status and the text 'ready' when healthy.
"""
response = client.get("/health/ready")
assert response.status_code == 200
assert response.text == "ready"
@given(st.text(min_size=0, max_size=16))
@settings(max_examples=10)
def test_readiness_resilience_to_query_noise(noise: str):
"""
Use Hypothesis for property-based testing.
This test ensures that the readiness endpoint is robust and remains functional
even when unexpected or garbage query parameters ("noise") are provided in the URL.
The `given` decorator generates various string inputs for the 'noise' parameter.
"""
# Pass arbitrary query parameters to the endpoint
response = client.get("/health/ready", params={"noise": noise})
assert response.status_code == 200
assert response.text == "ready"
def test_detailed_health_pass():
"""
Test the detailed health check endpoint, often conforming to the
[IETF health check standard](datatracker.ietf.org).
It should return a 200 OK status, and the JSON body should have a
"status" of "pass" and a dictionary of individual "checks".
"""
response = client.get("/health")
assert response.status_code == 200
body = response.json()
assert body["status"] == "pass"
assert isinstance(body["checks"], dict)
@given(st.text(min_size=0, max_size=16))
@settings(max_examples=10)
def test_health_resilience_to_query_noise(noise: str):
"""
Use Hypothesis for property-based testing.
This test ensures that the health endpoint is robust and remains functional
even when unexpected or garbage query parameters ("noise") are provided in the URL.
The `given` decorator generates various string inputs for the 'noise' parameter.
"""
# Pass arbitrary query parameters to the endpoint
response = client.get("/health", params={"noise": noise})
assert response.status_code == 200
body = response.json()
assert body["status"] == "pass"
assert isinstance(body["checks"], dict)