Spaces:
Configuration error
Configuration error
File size: 11,537 Bytes
e23172f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 | """Unit tests for the trifecta predictor. All tests run without live API access.
Run: python -m unittest discover -s tests
"""
from __future__ import annotations
import os
import sys
import unittest
from pathlib import Path
# Make package importable
ROOT = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(ROOT))
from trifecta_bro.config import settings # noqa: E402
from trifecta_bro.data.normalizer import normalise_race, normalise_meeting # noqa: E402
from trifecta_bro.model.feature_engine import ( # noqa: E402
parse_form_positions, form_quality_score, spell_count, is_fresh_after_spell)
from trifecta_bro.model.pace_analysis import classify_pace, pace_adjustment # noqa: E402
from trifecta_bro.model.scoring import score_runner, load_weights # noqa: E402
from trifecta_bro.model.probability import ( # noqa: E402
generate_trifecta, compute_confidence, softmax_probabilities)
from trifecta_bro.model.analyse_race import analyse_race # noqa: E402
from trifecta_bro.data.storage import Storage # noqa: E402
from trifecta_bro.evaluation.backtester import Backtester, _parse_actual # noqa: E402
from tests.mock_formfav import ( # noqa: E402
meetings_payload, race_form_full, race_form_with_scratch_and_missing,
race_form_abandoned)
DB_PATH = ROOT / "data" / "test_trincta_bro.db"
def fresh_storage() -> Storage:
if DB_PATH.exists():
DB_PATH.unlink()
return Storage(db_path=DB_PATH)
class TestDateLogic(unittest.TestCase):
def test_tomorrow_australia(self):
from trifecta_bro.jobs.daily_prediction import tomorrow_australia
# deterministic check: a known now -> next day
result = tomorrow_australia()
self.assertEqual(len(result), 10)
self.assertRegex(result, r"^\d{4}-\d{2}-\d{2}$")
class TestFormParsing(unittest.TestCase):
def test_positions_basic(self):
self.assertEqual(parse_form_positions("12345"), [1, 2, 3, 4, 5])
def test_x_is_spell_not_position(self):
pos = parse_form_positions("1x231")
self.assertEqual(pos, [1, None, 2, 3, 1])
def test_zero_is_tenth_or_worse(self):
pos = parse_form_positions("10")
self.assertEqual(pos, [1, 0])
def test_spell_count_and_fresh(self):
self.assertEqual(spell_count("1x23x"), 2)
self.assertTrue(is_fresh_after_spell("123x"))
self.assertFalse(is_fresh_after_spell("x123"))
class TestFormQuality(unittest.TestCase):
def test_strong_recent_form_scores_high(self):
score, diag = form_quality_score("11122")
self.assertGreater(score, 70)
self.assertGreater(diag["consistency"], 0.8)
def test_poor_form_scores_low(self):
score, _ = form_quality_score("88880")
self.assertLess(score, 40)
def test_spell_does_not_count_as_position(self):
score_with_spell, _ = form_quality_score("1x231")
score_no_spell, _ = form_quality_score("12231")
# spell slightly lowers availability but shouldn't be treated as a 10th
self.assertLess(score_with_spell, score_no_spell + 1)
def test_empty_form(self):
score, diag = form_quality_score("")
self.assertEqual(score, 0.0)
self.assertIn("no form data", diag["reason"])
class TestPace(unittest.TestCase):
def test_classify_and_roles(self):
race = normalise_race(race_form_full())
pace = classify_pace(race, race.active_runners)
self.assertIn(pace["label"], {"SLOW", "MODERATE", "FAST", "VERY FAST"})
self.assertIn(1, pace["roles"])
def test_leader_advantaged_in_slow(self):
from trifecta_bro.data.models import RaceModel, RunnerModel
r = RunnerModel(number=1, barrier=1, win_percent=20.0)
slow = {"label": "SLOW", "roles": {1: "leader/on-speed"}}
self.assertGreater(pace_adjustment(r, slow), 0)
def test_leader_penalised_in_fast(self):
from trifecta_bro.data.models import RunnerModel
r = RunnerModel(number=1, barrier=1, win_percent=20.0)
fast = {"label": "FAST", "roles": {1: "leader/on-speed"}}
self.assertLess(pace_adjustment(r, fast), 0)
class TestScoring(unittest.TestCase):
def test_weights_load_and_sums(self):
w = load_weights()
self.assertAlmostEqual(sum(w.values()), 1.0, places=2)
def test_score_runner_runs(self):
race = normalise_race(race_form_full())
pace = classify_pace(race, race.active_runners)
w = load_weights()
res = score_runner(race.active_runners[0], race, pace, w)
self.assertIn("score", res)
self.assertGreaterEqual(res["score"], 0)
self.assertLessEqual(res["score"], 100)
def test_missing_fields_graceful(self):
race = normalise_race(race_form_with_scratch_and_missing())
pace = classify_pace(race, race.active_runners)
w = load_weights()
# Ghost runner has almost no data; should not crash and returns a score
ghost = [r for r in race.active_runners if r.name == "Ghost"][0]
res = score_runner(ghost, race, pace, w)
self.assertIsInstance(res["score"], float)
class TestScratchedAbandoned(unittest.TestCase):
def test_scratched_excluded(self):
race = normalise_race(race_form_with_scratch_and_missing())
numbers = [r.number for r in race.active_runners]
self.assertNotIn(4, numbers) # scratched
self.assertIn(8, numbers)
def test_abandoned_flag(self):
race = normalise_race(race_form_abandoned())
self.assertTrue(race.abandoned)
def test_missing_form_falls_back(self):
race = normalise_race(race_form_with_scratch_and_missing())
only = [r for r in race.active_runners if r.name == "OnlyOne"][0]
self.assertTrue(only.form) # derived from last20Starts
class TestTrifectaGen(unittest.TestCase):
def test_generate_trifecta(self):
race = normalise_race(race_form_full())
a = analyse_race(race)
self.assertEqual(len(a["trifecta"]), 3)
self.assertCountEqual(a["top3"], a["trifecta"])
self.assertIsInstance(a["alternatives"], list)
def test_probabilities_sum_to_one(self):
probs = softmax_probabilities([50, 60, 70], temperature=12.0)
self.assertAlmostEqual(sum(probs), 1.0, places=3)
def test_insufficient_runners_skips(self):
# build a 2-runner race
payload = race_form_full()
payload["runners"] = payload["runners"][:2]
race = normalise_race(payload)
a = analyse_race(race)
self.assertTrue(a.get("skippable"))
class TestConfidence(unittest.TestCase):
def test_confidence_categories(self):
race = normalise_race(race_form_full())
a = analyse_race(race)
self.assertIn(a["confidence"]["category"], {"HIGH", "MEDIUM", "LOW", "AVOID"})
def test_avoid_on_weak_leader(self):
from trifecta_bro.model.probability import compute_confidence
# fake ranking with weak leader
ranked = [{"number": 1, "score": 12.0}, {"number": 2, "score": 11.0}]
conf = compute_confidence(ranked, 0.9, {"label": "SLOW"}, {})
self.assertEqual(conf["category"], "AVOID")
class TestValidation(unittest.TestCase):
def test_meetings_validation_flags_error(self):
from trifecta_bro.api.validator import validate_meetings
issues = validate_meetings({"foo": 1})
self.assertTrue(any(i.level == "error" for i in issues))
def test_race_form_validation(self):
from trifecta_bro.api.validator import validate_race_form
issues = validate_race_form(race_form_full())
self.assertFalse(any(i.level == "error" for i in issues))
class TestStorage(unittest.TestCase):
def setUp(self):
self.store = fresh_storage()
def tearDown(self):
self.store.close()
if DB_PATH.exists():
DB_PATH.unlink()
def test_upsert_and_read(self):
race = normalise_race(race_form_full())
rid = self.store.upsert_race(race)
self.assertGreater(rid, 0)
# save a prediction
self.store.save_prediction({
"date": race.date, "track": race.track, "track_slug": race.track_slug,
"race_number": race.race_number, "model_version": "1.0.0",
"generated_at": "2026-08-11T00:00:00Z", "top3": [3, 1, 2],
"trifecta": [3, 1, 2], "alternatives": [[1, 3, 2]],
"confidence": "MEDIUM", "confidence_score": 55,
"ranked_runners": [{"no": 3, "name": "x", "score": 70}],
"data_completeness": 0.9,
})
preds = self.store.get_predictions(race.date)
self.assertEqual(len(preds), 1)
self.assertEqual(preds[0]["trifecta"], [3, 1, 2])
def test_save_result(self):
race = normalise_race(race_form_full())
self.store.upsert_race(race)
self.store.save_result(race.date, race.track, race.track_slug, race.race_number, [3, 1, 2])
# re-saving is idempotent
self.store.save_result(race.date, race.track, race.track_slug, race.race_number, [3, 1, 2])
class TestBacktester(unittest.TestCase):
def test_parse_actual_variants(self):
self.assertEqual(_parse_actual("1,7,9"), [1, 7, 9])
self.assertEqual(_parse_actual([4, 5, 6]), [4, 5, 6])
self.assertIsNone(_parse_actual(""))
self.assertIsNone(_parse_actual(None))
def test_backtest_no_leakage(self):
race = normalise_race(race_form_full())
# analyse WITHOUT actuals first
a = analyse_race(race)
pred = a["trifecta"]
# now compute metrics against actual — actual never fed to model
bt = Backtester()
result = bt.evaluate([race], {("dubbo", 1): [3, 1, 2]})
rec = result["records"][0]
self.assertTrue(rec["scored"])
# exact hit only if prediction matched the provided actual
self.assertEqual(rec["exact_hit"], (pred == [3, 1, 2]))
# metrics present
self.assertIn("exact_trifecta_hit_rate", result)
self.assertIn("top1_accuracy", result)
def test_backtest_partial_coverage(self):
race = normalise_race(race_form_full())
bt = Backtester()
result = bt.evaluate([race], {("dubbo", 1): [9, 9, 9]}) # none match
rec = result["records"][0]
self.assertEqual(rec["partial3"], 0)
class TestEndToEndMocked(unittest.TestCase):
def test_full_pipeline_with_fake_client(self):
from trifecta_bro.api.formfav_client import FormFavClient
class FakeClient(FormFavClient):
def get_meetings(self, date, country=None, race_code=None):
return meetings_payload(date)["meetings"]
def get_race_form(self, date, track, race, country=None, race_code=None, timezone=None):
if track == "dubbo" and race == 1:
return race_form_full(date, track, race)
if track == "dubbo" and race == 2:
return race_form_abandoned(date, track, race)
if track == "randwick" and race == 7:
return race_form_with_scratch_and_missing(date, track, race)
raise FileNotFoundError("no mock")
# exercise analyse_race for each race form directly
for fn in (race_form_full, race_form_with_scratch_and_missing, race_form_abandoned):
race = normalise_race(fn())
a = analyse_race(race)
self.assertIn("confidence", a)
if __name__ == "__main__":
unittest.main(verbosity=2)
|