backend/tests/test_api.py

"""Smoke tests for the FastAPI app."""

from __future__ import annotations

import json
from pathlib import Path

import pytest
from fastapi.testclient import TestClient

from app.main import create_app

SAMPLES_DIR = Path(__file__).resolve().parents[1] / "app" / "data_sources" / "samples"


@pytest.fixture(scope="module")
def client() -> TestClient:
    return TestClient(create_app())


def test_health(client: TestClient):
    r = client.get("/api/health")
    assert r.status_code == 200
    body = r.json()
    assert body["status"] == "ok"
    assert body["service"] == "bayesscenparams-backend"


def test_list_samples(client: TestClient):
    r = client.get("/api/data/samples")
    assert r.status_code == 200
    body = r.json()
    ids = {s["id"] for s in body}
    assert ids == {"gdp", "climate", "population"}
    for s in body:
        assert s["n"] > 0
        assert s["icon"]


def test_get_sample(client: TestClient):
    r = client.get("/api/data/samples/gdp")
    assert r.status_code == 200
    body = r.json()
    assert body["id"] == "gdp"
    assert len(body["values"]) > 100
    assert isinstance(body["values"][0], float)


def test_bayesian_compute(client: TestClient):
    gdp = json.loads((SAMPLES_DIR / "sample-gdp.json").read_text())
    payload = {
        "data": gdp["values"],
        "judgments": [0, 1, 2, 3, 4],
        "R": 10.0,
    }
    r = client.post("/api/bayesian/compute", json=payload)
    assert r.status_code == 200
    body = r.json()
    assert "prior" in body and "likelihood" in body and "posterior" in body
    assert len(body["posterior"]["weights"]) == 5
    assert abs(sum(body["posterior"]["weights"]) - 1.0) < 1e-9
    # likelihood for level 4 is R^2 = 100
    assert body["likelihood"]["weights"][4] == pytest.approx(100.0)


def test_bayesian_compute_validates_R():
    client = TestClient(create_app())
    gdp = json.loads((SAMPLES_DIR / "sample-gdp.json").read_text())
    r = client.post(
        "/api/bayesian/compute",
        json={"data": gdp["values"], "judgments": [0, 1, 2, 3, 4], "R": 0.5},
    )
    assert r.status_code == 422


def test_sensitivity(client: TestClient):
    gdp = json.loads((SAMPLES_DIR / "sample-gdp.json").read_text())
    r = client.post(
        "/api/bayesian/sensitivity",
        json={"data": gdp["values"], "judgments": [0, 1, 2, 3, 4]},
    )
    assert r.status_code == 200
    body = r.json()
    assert len(body["points"]) == 5
    # Each point's posterior sums to 1
    for p in body["points"]:
        s = sum(p["result"]["posterior"]["weights"])
        assert abs(s - 1.0) < 1e-9