Files
ai-exchange/tests/unit/test_runtime_script_json.py
2026-04-30 00:29:18 +08:00

174 lines
7.1 KiB
Python

import contextlib
import io
import json
import os
import unittest
from unittest.mock import patch
from sqlalchemy.exc import OperationalError
os.environ.setdefault("DATABASE_URL", "postgresql+psycopg://user:pass@localhost:5432/ai_ict_test")
from scripts import (
apply_migrations,
check_db,
check_db_connection,
run_api_server,
run_dev,
run_displacement,
run_fvg,
run_liquidity,
run_mss,
run_ranges,
run_session_generator,
run_sweeps,
run_swings,
run_training_cases,
show_models,
)
class _FakeTrainingCaseGenerator:
def __init__(self) -> None:
self.calls = []
def generate_cases(self, instrument_id, timeframe, case_types=None, limit_per_type=10):
self.calls.append(
{
"instrument_id": instrument_id,
"timeframe": timeframe,
"case_types": list(case_types),
"limit_per_type": limit_per_type,
}
)
return run_training_cases.CaseGenerationResult(
generated=2,
by_type={"sweep": 1, "range": 1},
case_ids=[101, 202],
)
class RuntimeScriptJsonTests(unittest.TestCase):
def test_structure_scripts_report_database_unavailable_json(self) -> None:
cases = [
(run_session_generator, "SESSION_GENERATOR_OUTPUT_JSON", "scripts.run_session_generator.SessionGenerator.generate_for_date"),
(run_swings, "SWINGS_OUTPUT_JSON", "scripts.run_swings.SwingService.detect_swings"),
(run_ranges, "RANGES_OUTPUT_JSON", "scripts.run_ranges.DealingRangeService.build_active_range"),
(run_liquidity, "LIQUIDITY_OUTPUT_JSON", "scripts.run_liquidity.LiquidityPoolService.build_candidates"),
(run_sweeps, "SWEEPS_OUTPUT_JSON", "scripts.run_sweeps.SweepService.detect_sweeps"),
(run_displacement, "DISPLACEMENT_OUTPUT_JSON", "scripts.run_displacement.DisplacementService.detect_displacement"),
(run_mss, "MSS_OUTPUT_JSON", "scripts.run_mss.MSSService.detect_mss"),
(run_fvg, "FVG_OUTPUT_JSON", "scripts.run_fvg.FVGService.detect_fvg"),
]
for module, env_key, patch_target in cases:
with self.subTest(script=module.__name__):
output = io.StringIO()
with patch(patch_target, side_effect=OperationalError("stmt", {}, Exception())), contextlib.redirect_stdout(output):
exit_code = module.main(env={env_key: "1"})
payload = json.loads(output.getvalue())
self.assertEqual(exit_code, 2)
self.assertFalse(payload["passed"])
self.assertEqual(payload["error_type"], "OperationalError")
self.assertEqual(payload["instrument_id"], 1)
self.assertEqual(payload["timeframe"], "1m")
def test_database_check_scripts_report_unavailable_json(self) -> None:
cases = [
(check_db, "CHECK_DB_OUTPUT_JSON", "scripts.check_db.engine.connect"),
(check_db_connection, "CHECK_DB_CONNECTION_OUTPUT_JSON", "scripts.check_db_connection.engine.connect"),
]
for module, env_key, patch_target in cases:
with self.subTest(script=module.__name__):
output = io.StringIO()
with patch(patch_target, side_effect=OperationalError("stmt", {}, Exception())), contextlib.redirect_stdout(output):
exit_code = module.main(env={env_key: "1"})
payload = json.loads(output.getvalue())
self.assertEqual(exit_code, 2)
self.assertFalse(payload["passed"])
self.assertFalse(payload["available"])
self.assertEqual(payload["error_type"], "OperationalError")
def test_training_cases_report_database_unavailable_json(self) -> None:
output = io.StringIO()
with patch(
"scripts.run_training_cases.TrainingCaseGenerator.generate_cases",
side_effect=OperationalError("stmt", {}, Exception()),
), contextlib.redirect_stdout(output):
exit_code = run_training_cases.main(env={"TRAINING_CASES_OUTPUT_JSON": "1"})
payload = json.loads(output.getvalue())
self.assertEqual(exit_code, 2)
self.assertFalse(payload["passed"])
self.assertEqual(payload["error_type"], "OperationalError")
self.assertEqual(payload["instrument_id"], 1)
self.assertEqual(payload["timeframe"], "1m")
self.assertEqual(payload["case_types"], ["sweep", "fvg", "range", "mss_displacement"])
self.assertEqual(payload["generated"], 0)
def test_training_cases_outputs_generation_json(self) -> None:
output = io.StringIO()
generator = _FakeTrainingCaseGenerator()
with contextlib.redirect_stdout(output):
exit_code = run_training_cases.run_training_generation(
generator=generator,
instrument_id=7,
timeframe="5m",
case_types=["sweep", "range"],
limit_per_type=3,
output_json=True,
)
payload = json.loads(output.getvalue())
self.assertEqual(exit_code, 0)
self.assertTrue(payload["passed"])
self.assertEqual(payload["instrument_id"], 7)
self.assertEqual(payload["timeframe"], "5m")
self.assertEqual(payload["limit_per_type"], 3)
self.assertEqual(payload["case_types"], ["sweep", "range"])
self.assertEqual(payload["generated"], 2)
self.assertEqual(payload["by_type"], {"range": 1, "sweep": 1})
self.assertEqual(payload["case_ids"], [101, 202])
self.assertEqual(generator.calls[0]["case_types"], ["sweep", "range"])
def test_show_models_outputs_json(self) -> None:
output = io.StringIO()
with contextlib.redirect_stdout(output):
exit_code = show_models.main(env={"SHOW_MODELS_OUTPUT_JSON": "1"})
payload = json.loads(output.getvalue())
self.assertEqual(exit_code, 0)
self.assertTrue(payload["passed"])
self.assertGreater(payload["model_count"], 0)
self.assertIn("candle", payload["models"])
def test_apply_migrations_delegates_to_safe_runner(self) -> None:
with patch("scripts.apply_migrations.run_migrations_main", return_value=2) as run_migrations:
exit_code = apply_migrations.main(env={"MIGRATIONS_OUTPUT_JSON": "1"})
self.assertEqual(exit_code, 2)
run_migrations.assert_called_once_with(env={"MIGRATIONS_OUTPUT_JSON": "1"})
def test_run_dev_preserves_zero_exit_code(self) -> None:
with patch("scripts.run_dev.app_main") as app_main:
exit_code = run_dev.main()
self.assertEqual(exit_code, 0)
app_main.assert_called_once_with()
def test_run_api_server_uses_env_and_returns_when_server_stops(self) -> None:
with patch("scripts.run_api_server.serve_api") as serve_api:
exit_code = run_api_server.main(env={"AI_ICT_API_HOST": "127.0.0.1", "AI_ICT_API_PORT": "8123"})
self.assertEqual(exit_code, 0)
serve_api.assert_called_once_with(host="127.0.0.1", port=8123)
if __name__ == "__main__":
unittest.main()