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Smoke coverage for the read-only /v1/analysis/* endpoints (analysis_api.py).
These need at least one aggregatable sweep under SPOOKY_BENCHMARKS_DIR
(default <repo>/results/sweeps). That tree isn't committed, so every test
skips cleanly when it's absent rather than failing on a fresh checkout / CI.
"""
import pytest
from fastapi.testclient import TestClient
from api import app
from analysis_api import _sweep_dir_map
def _first_sweep_id():
ids = list(_sweep_dir_map().keys())
if not ids:
pytest.skip("no sweeps under SPOOKY_BENCHMARKS_DIR")
# newest-first, matching the /sweeps ordering
with TestClient(app) as client:
return client.get("/v1/analysis/sweeps").json()["sweeps"][0]["sweep_id"]
def test_list_sweeps_shape():
with TestClient(app) as client:
body = client.get("/v1/analysis/sweeps").json()
assert "sweeps" in body and body["sweep_count"] == len(body["sweeps"])
for entry in body["sweeps"]:
assert entry["sweep_id"]
assert set(entry) >= {"solvers", "grid_sizes", "n_completed", "git_commit"}
def test_summary_and_recommend_agree_on_solvers():
sweep_id = _first_sweep_id()
with TestClient(app) as client:
summary = client.get(f"/v1/analysis/sweeps/{sweep_id}/summary")
assert summary.status_code == 200, summary.text
assert isinstance(summary.json()["statistical_tests"], list)
rec = client.get(f"/v1/analysis/sweeps/{sweep_id}/recommend")
assert rec.status_code == 200, rec.text
body = rec.json()
assert body["solvers"], "recommend returned no solvers for the whole sweep"
# sorted best-first: success rate descending
rates = [s["success_rate"] for s in body["solvers"]]
assert rates == sorted(rates, reverse=True)
assert body["verdict"]
def test_plots_return_plotly_json():
sweep_id = _first_sweep_id()
with TestClient(app) as client:
for name in ("scaling", "success_rate", "variable_reduction"):
res = client.get(f"/v1/analysis/sweeps/{sweep_id}/plots/{name}")
assert res.status_code == 200, (name, res.text)
assert "data" in res.json()
assert (
client.get(f"/v1/analysis/sweeps/{sweep_id}/plots/bogus").status_code == 404
)
def test_by_instance_and_filtered_plot():
sweep_id = _first_sweep_id()
with TestClient(app) as client:
grids = client.get("/v1/analysis/sweeps").json()["sweeps"][0]["grid_sizes"]
assert grids, "sweep has no grid sizes"
grid = grids[0]
rows = client.get(
f"/v1/analysis/sweeps/{sweep_id}/by-instance?grid_size={grid}"
)
assert rows.status_code == 200, rows.text
body = rows.json()
assert body["row_count"] == len(body["rows"]) > 0
for row in body["rows"]:
assert row["grid_size"] == grid
assert 0.0 <= row["success_rate"] <= 1.0
assert isinstance(row["failure_causes"], dict)
# a filterable plot honours grid_size; scaling ignores it (still 200)
assert (
client.get(
f"/v1/analysis/sweeps/{sweep_id}/plots/success_rate?grid_size={grid}"
).status_code
== 200
)
assert (
client.get(
f"/v1/analysis/sweeps/{sweep_id}/plots/scaling?grid_size={grid}"
).status_code
== 200
)
assert (
client.get(
f"/v1/analysis/sweeps/{sweep_id}/by-instance?grid_size=999x999"
).status_code
== 404
)
def test_unknown_sweep_404():
with TestClient(app) as client:
assert (
client.get("/v1/analysis/sweeps/does_not_exist/summary").status_code == 404
)
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