You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
motief/tests/test_explorer_quiz.py

158 lines
5.4 KiB

"""Tests for build_mp_quiz_tab and related quiz DB integration.
Task 2.1 + Task 3.1: smoke test that the builder is exported and callable,
plus an end-to-end simulation of the quiz matching logic via real temp DuckDB.
"""
import importlib
from pathlib import Path
import duckdb
from database import MotionDatabase
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _create_motion(db: MotionDatabase, url: str, title: str, controversy: float = 0.5):
md = {
"title": title,
"description": title,
"date": "2023-01-01",
"policy_area": "test",
"voting_results": {},
"winning_margin": controversy,
"layman_explanation": f"Uitleg over {title}",
"url": url,
}
ok = db.insert_motion(md)
assert ok, f"insert_motion failed for {url}"
conn = duckdb.connect(db.db_path)
row = conn.execute("SELECT id FROM motions WHERE url = ?", (url,)).fetchone()
conn.close()
assert row is not None
return int(row[0])
# ---------------------------------------------------------------------------
# Task 2.1 — smoke test: builder exported and callable
# ---------------------------------------------------------------------------
def test_builder_exists():
"""build_mp_quiz_tab must be importable from explorer and callable."""
mod = importlib.import_module("explorer")
assert hasattr(mod, "build_mp_quiz_tab"), "build_mp_quiz_tab not found in explorer"
assert callable(mod.build_mp_quiz_tab)
# ---------------------------------------------------------------------------
# Task 3.1 — end-to-end quiz matching simulation
# ---------------------------------------------------------------------------
def test_quiz_unique_match(tmp_path: Path):
"""Full quiz flow: 6 motions, 4 MPs — pre-filled votes produce a unique match."""
db_path = str(tmp_path / "quiz_e2e.db")
db = MotionDatabase(db_path)
# 6 motions
mids = [_create_motion(db, f"http://qe{i}", f"Motion {i}") for i in range(6)]
# 4 MPs with distinct voting patterns
mpA = "Alpha, A."
mpB = "Beta, B."
mpC = "Gamma, G."
mpD = "Delta, D."
patterns = {
mpA: ["voor", "voor", "voor", "voor", "voor", "voor"], # all voor
mpB: ["tegen", "tegen", "voor", "voor", "voor", "voor"], # 2 tegen then 4 voor
mpC: ["voor", "tegen", "voor", "tegen", "voor", "tegen"], # alternating
mpD: ["tegen", "tegen", "tegen", "tegen", "tegen", "voor"], # mostly tegen
}
for idx, mid in enumerate(mids):
for mp, votes in patterns.items():
db.insert_mp_vote(mid, mp, votes[idx], "2023-01-01")
# User votes matching mpA exactly (all Voor)
user_votes = {mid: "Voor" for mid in mids}
results = db.match_mps_for_votes(user_votes, limit=50)
assert results, "Expected ranked results"
top = results[0]
assert top["mp_name"] == mpA
assert top["agreement_pct"] == 100.0
# Unique match: only mpA should be at 100%
top_matches = [r for r in results if r["agreement_pct"] == top["agreement_pct"]]
assert len(top_matches) == 1, f"Expected unique top match, got {top_matches}"
def test_quiz_indistinguishable_mps(tmp_path: Path):
"""When two MPs vote identically, both appear at the top with same agreement_pct."""
db_path = str(tmp_path / "quiz_indist.db")
db = MotionDatabase(db_path)
mids = [
_create_motion(db, f"http://ind{i}", f"Indist Motion {i}") for i in range(3)
]
mpA = "Alice, A."
mpB = "Bob, B."
# Both vote identically
for mid in mids:
db.insert_mp_vote(mid, mpA, "voor", "2023-01-01")
db.insert_mp_vote(mid, mpB, "voor", "2023-01-01")
user_votes = {mid: "Voor" for mid in mids}
results = db.match_mps_for_votes(user_votes, limit=50)
assert len(results) == 2, "Both identical MPs should appear"
assert results[0]["agreement_pct"] == results[1]["agreement_pct"] == 100.0
def test_quiz_discriminating_reduces_candidates(tmp_path: Path):
"""After one discriminating question, candidate set should shrink."""
db_path = str(tmp_path / "quiz_disc.db")
db = MotionDatabase(db_path)
# 4 motions: motion0 splits mpA from mpB/mpC
mids = [_create_motion(db, f"http://disc{i}", f"Disc Motion {i}") for i in range(4)]
mpA = "Alpha, A."
mpB = "Beta, B."
mpC = "Gamma, G."
# motion0 splits; motions 1-3 they all agree
db.insert_mp_vote(mids[0], mpA, "voor", "2023-01-01")
db.insert_mp_vote(mids[0], mpB, "tegen", "2023-01-01")
db.insert_mp_vote(mids[0], mpC, "tegen", "2023-01-01")
for i in range(1, 4):
for mp in (mpA, mpB, mpC):
db.insert_mp_vote(mids[i], mp, "voor", "2023-01-01")
# All three agree on motions 1-3; choose_discriminating_motions should pick motion0
all_mps = [mpA, mpB, mpC]
chosen = db.choose_discriminating_motions(all_mps, excluded_motion_ids=[], k=1)
assert chosen[0] == mids[0], (
f"Expected motion {mids[0]} as discriminating, got {chosen}"
)
# After user answers Voor on motion0, only mpA should rank at 100%
user_votes = {mids[0]: "Voor"}
results = db.match_mps_for_votes(user_votes, limit=50)
top = results[0]
assert top["mp_name"] == mpA
assert top["agreement_pct"] == 100.0
# mpB and mpC should be at 0%
for r in results:
if r["mp_name"] in (mpB, mpC):
assert r["agreement_pct"] == 0.0