2569718930@qq.com
d1d9f80f0f
Fast evidence mode should not say DEB and models support the center when the latest METAR has already exceeded that center or the model upper edge. The fallback now treats the live observation as a lower bound for the daily high and explains the upward revision pressure. Constraint: Fallback output must remain useful before the full AI bulletin read returns Rejected: Keep the original DEB center until AI completes | it can be lower than an already-observed temperature Confidence: high Scope-risk: narrow Tested: pytest tests/test_web_observability.py::test_city_ai_fallback_revises_up_when_latest_metar_breaks_above_models tests/test_web_observability.py::test_city_ai_fallback_reasoning_identifies_fast_evidence_mode tests/test_web_observability.py::test_city_ai_stream_request_only_asks_provider_for_observation_read -q Tested: npm run build
618 lines
22 KiB
Python
618 lines
22 KiB
Python
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from fastapi.testclient import TestClient
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from web.app import app
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import web.routes as routes
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import web.scan_terminal_service as scan_terminal_service
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from web.scan_terminal_service import _scan_terminal_cache_key
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from src.database.db_manager import DBManager
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from src.database.runtime_state import TruthRecordRepository, TrainingFeatureRecordRepository
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client = TestClient(app)
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def test_healthz_returns_ok_shape():
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response = client.get('/healthz')
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assert response.status_code == 200
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payload = response.json()
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assert payload['status'] in {'ok', 'degraded'}
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assert 'db' in payload
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assert 'state_storage_mode' in payload
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assert 'cities_count' in payload
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def test_system_status_returns_summary_shape():
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response = client.get('/api/system/status')
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assert response.status_code == 200
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payload = response.json()
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assert 'db' in payload
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assert 'state_storage_mode' in payload
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assert 'features' in payload
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assert 'integrations' in payload
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assert 'cache' in payload
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assert 'analysis' in payload['cache']
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assert 'probability' in payload
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assert 'rollout' in payload['probability']
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assert payload['probability']['rollout']['decision']['decision'] in {'hold', 'observe', 'promote'}
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assert 'training_data' in payload
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assert 'station_networks' in payload
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assert 'prewarm' in payload
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assert 'truth_records' in payload['training_data']
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assert 'training_features' in payload['training_data']
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assert 'city_coverage' in payload['training_data']
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assert 'model_city_coverage' in payload['training_data']
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assert 'artifacts' in payload['training_data']
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assert 'metar_entries' in payload['cache']
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assert 'nmc_entries' in payload['cache']
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assert 'runtime' in payload['prewarm']
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assert 'last_summary_ok' in payload['prewarm']['runtime']
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assert 'cities_count' in payload
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def test_system_status_reads_shared_prewarm_runtime(monkeypatch):
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monkeypatch.setenv("POLYWEATHER_DASHBOARD_PREWARM_ENABLED", "true")
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monkeypatch.setenv("POLYWEATHER_PREWARM_INTERVAL_SEC", "300")
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monkeypatch.setenv("POLYWEATHER_PREWARM_JITTER_SEC", "20")
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DBManager().set_payment_runtime_state(
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"dashboard_prewarm",
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{
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"cycle_count": 3,
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"success_count": 3,
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"failure_count": 0,
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"last_started_at": "2026-04-08T12:00:00",
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"last_finished_at": "2026-04-08T12:00:05",
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"last_duration_sec": 5.0,
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"last_success": True,
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"last_http_status": 200,
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"last_error": None,
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"last_requested_cities": ["shanghai", "beijing"],
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"last_requested_city_count": 2,
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"last_include_detail": True,
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"last_include_market": True,
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"last_force_refresh": False,
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"last_warmed_count": 2,
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"last_summary_ok": 2,
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"last_detail_ok": 2,
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"last_market_ok": 2,
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"last_failed_count": 0,
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"last_heartbeat_ts": __import__("time").time(),
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"writer_mode": "standalone_process",
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"writer_pid": 12345,
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"writer_thread_name": "MainThread",
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},
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)
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response = client.get('/api/system/status')
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assert response.status_code == 200
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payload = response.json()
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assert payload["prewarm"]["enabled"] is True
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assert payload["prewarm"]["thread_alive"] is True
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assert payload["prewarm"]["runtime"]["cycle_count"] >= 3
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assert payload["prewarm"]["runtime"]["last_summary_ok"] == 2
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def test_metrics_endpoint_returns_prometheus_payload():
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response = client.get('/metrics')
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assert response.status_code == 200
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assert 'polyweather_http_requests_total' in response.text
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def test_city_ai_fallback_reasoning_identifies_fast_evidence_mode():
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payload = scan_terminal_service._build_city_ai_fallback(
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{
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"city_display_name": "Tokyo",
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"temp_symbol": "°C",
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"deb": {"prediction": 17.8},
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"model_cluster": {
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"sources": [
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{"value": 17.0},
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{"value": 17.8},
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{"value": 20.6},
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]
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},
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"observation_anchor": {
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"is_airport_metar": True,
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"station_code": "RJTT",
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},
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"airport_current": {
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"station_code": "RJTT",
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"temp": 16.0,
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"report_time": "21:30Z",
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"raw_metar": "RJTT 262130Z AUTO 00000KT 9999 FEW030 16/10 Q1015",
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},
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},
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locale="zh-CN",
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reason="preview",
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)
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assert "当前为快速证据模式" in payload["reasoning_zh"]
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assert "完整 AI 机场报文解读返回后再合并" in payload["reasoning_zh"]
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assert "AI 机场报文解读正常" not in payload["reasoning_zh"]
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assert "后补" not in payload["reasoning_zh"]
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assert "AI 增强可作为后续补充" not in payload["reasoning_zh"]
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def test_city_ai_fallback_revises_up_when_latest_metar_breaks_above_models():
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payload = scan_terminal_service._build_city_ai_fallback(
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{
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"city_display_name": "Manila",
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"temp_symbol": "°C",
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"deb": {"prediction": 34.0},
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"model_cluster": {
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"sources": [
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{"value": 32.5},
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{"value": 33.8},
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{"value": 34.0},
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{"value": 34.7},
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]
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},
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"observation_anchor": {
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"is_airport_metar": True,
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"station_code": "RPLL",
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},
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"airport_current": {
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"station_code": "RPLL",
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"temp": 35.0,
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"report_time": "03:00Z / 当地 11:00",
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"raw_metar": "RPLL 270300Z 34004KT CAVOK 35/24 Q1009",
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},
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},
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locale="zh-CN",
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reason="stream preview",
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)
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assert payload["predicted_max"] == 35.0
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assert payload["range_high"] == 35.0
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assert "高于原先 34.0°C 中枢" in payload["final_judgment_zh"]
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assert "上修到至少 35.0°C" in payload["final_judgment_zh"]
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assert "共同支撑本轮最高温中枢" not in payload["reasoning_zh"]
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assert "超过模型上沿 34.7°C" in payload["reasoning_zh"]
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assert "继续上修最高温中枢" in payload["risks_zh"][0]
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def test_city_ai_stream_request_only_asks_provider_for_observation_read():
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request_payload = scan_terminal_service._build_city_ai_stream_request(
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{
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"city": "Tokyo",
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"city_display_name": "Tokyo",
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"temp_symbol": "°C",
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"deb": {"prediction": 17.8},
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"model_cluster": {"sources": [{"value": 17.0}, {"value": 17.8}]},
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"observation_anchor": {
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"is_airport_metar": True,
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"read_label_zh": "机场报文解读",
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},
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"airport_current": {
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"station_code": "RJTT",
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"temp": 16.0,
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"report_time": "21:30Z",
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"raw_metar": "RJTT 262130Z AUTO 00000KT 9999 FEW030 16/10 Q1015",
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},
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},
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locale="zh-CN",
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)
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user_payload = request_payload["messages"][1]["content"]
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assert request_payload["stream"] is True
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assert request_payload["max_tokens"] <= 650
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assert request_payload["max_tokens"] < scan_terminal_service.SCAN_AI_MAX_TOKENS
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assert '"required_json_keys": ["metar_read_zh", "metar_read_en", "reasoning_zh", "reasoning_en"]' in user_payload
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assert "Do not return final_judgment" in user_payload
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def test_city_ai_partial_json_trims_dangling_taf_clause():
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payload = scan_terminal_service._build_city_ai_fallback(
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{
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"city_display_name": "London",
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"temp_symbol": "°C",
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"deb": {"prediction": 24.3},
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"model_cluster": {
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"sources": [
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{"value": 22.3},
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{"value": 23.1},
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{"value": 24.3},
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{"value": 26.3},
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]
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},
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"observation_anchor": {
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"is_airport_metar": True,
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"station_code": "EGLL",
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},
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"airport_current": {
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"station_code": "EGLL",
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"temp": 21.0,
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"report_time": "09:00Z",
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"raw_metar": "EGLL 270900Z 34004KT CAVOK 21/09 Q1016",
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},
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},
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locale="zh-CN",
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reason="AI content is not a JSON object",
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raw_content=(
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'{"metar_read_zh":"最新METAR报文09:00观测温度21°C，西北风4节（340°），'
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'CAVOK（能见度良好，无重要云）。当前西北风弱，趋向增温但影响有限；'
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'TAF预示10-11点转南风（18012KT），南风可能带来凉爽海风抑制升温。",'
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'"reasoning_zh":"DEB预测24.3°C，多数模型集中在23-26°C，'
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'当前09时实测21°C处于快速升温路径，但TAF显示'
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),
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)
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assert "但TAF显示" not in payload["reasoning_zh"]
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assert payload["reasoning_zh"].endswith("。")
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assert "当前09时实测21°C处于快速升温路径" in payload["reasoning_zh"]
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def test_city_ai_schema_completion_trims_dangling_taf_clause():
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payload = scan_terminal_service._complete_city_ai_payload(
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{
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"predicted_max": 24.3,
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"range_low": 22.3,
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"range_high": 26.3,
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"unit": "°C",
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"confidence": "medium",
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"final_judgment_zh": "London 最高温中枢暂看24°C附近。",
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"final_judgment_en": "London high is centered near 24°C.",
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"metar_read_zh": "最新METAR报文09:00观测温度21°C，西北风4节，CAVOK。",
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"metar_read_en": "The latest METAR shows 21°C at 09:00 with northwesterly wind and CAVOK.",
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"reasoning_zh": "当前09时实测21°C处于快速升温路径，但TAF显示",
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"reasoning_en": "The 09:00 observation is on a fast warming path, but TAF shows",
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"risks_zh": ["后续METAR若升温放缓，需要下修。"],
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"risks_en": ["If later METAR warming slows, revise lower."],
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"model_cluster_note_zh": "4/4 个模型落在 DEB ±2°C 内。",
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"model_cluster_note_en": "4/4 models sit within 2°C of DEB.",
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},
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{
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"city_display_name": "London",
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"temp_symbol": "°C",
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"deb": {"prediction": 24.3},
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"model_cluster": {"sources": [{"value": 22.3}, {"value": 26.3}]},
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"observation_anchor": {"is_airport_metar": True, "station_code": "EGLL"},
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"airport_current": {
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"station_code": "EGLL",
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"temp": 21.0,
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"report_time": "09:00Z",
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"raw_metar": "EGLL 270900Z 34004KT CAVOK 21/09 Q1016",
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},
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},
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locale="zh-CN",
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)
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assert payload["reasoning_zh"] == "当前09时实测21°C处于快速升温路径。"
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assert payload["reasoning_en"] == "The 09:00 observation is on a fast warming path."
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assert payload["_polyweather_meta"]["trimmed_incomplete_fields"] == [
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"reasoning_en",
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"reasoning_zh",
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]
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def test_cities_endpoint_uses_denver_display_name_for_aurora_market():
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response = client.get("/api/cities")
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assert response.status_code == 200
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payload = response.json()
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aurora = next(item for item in payload["cities"] if item["name"] == "aurora")
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assert aurora["display_name"] == "Denver"
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assert aurora["network_provider"] == "global_metar"
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assert aurora["deb_recent_tier"] in {"high", "medium", "low", "other"}
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assert "deb_recent_sample_count" in aurora
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def test_cities_endpoint_includes_new_wunderground_cities():
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response = client.get("/api/cities")
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assert response.status_code == 200
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payload = response.json()
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names = {item["name"] for item in payload["cities"]}
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assert {
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"busan",
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"panama city",
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"kuala lumpur",
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"jakarta",
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"helsinki",
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"amsterdam",
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}.issubset(names)
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def test_payment_runtime_endpoint_returns_shape():
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response = client.get('/api/payments/runtime')
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assert response.status_code == 200
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payload = response.json()
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assert 'checkout' in payload
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assert 'rpc' in payload
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assert 'event_loop_state' in payload
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assert 'recent_audit_events' in payload
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def test_auth_me_does_not_reconcile_on_status_probe(monkeypatch):
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monkeypatch.setattr(routes, "_assert_entitlement", lambda request: None)
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def _bind_identity(request):
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request.state.auth_user_id = "user-1"
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request.state.auth_email = "user@example.com"
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monkeypatch.setattr(routes, "_bind_optional_supabase_identity", _bind_identity)
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monkeypatch.setattr(routes, "_resolve_auth_points", lambda request: 0)
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monkeypatch.setattr(routes, "_resolve_weekly_profile", lambda request: {"weekly_points": 0, "weekly_rank": None})
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monkeypatch.setattr(routes.SUPABASE_ENTITLEMENT, "enabled", True)
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calls = {"count": 0}
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reconcile_calls = {"count": 0}
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def _latest_subscription(user_id, respect_requirement=False):
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calls["count"] += 1
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return {
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"plan_code": "pro_monthly",
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"starts_at": "2026-03-22T00:00:00+00:00",
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"expires_at": "2026-04-21T00:00:00+00:00",
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}
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monkeypatch.setattr(
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routes.SUPABASE_ENTITLEMENT,
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"get_latest_active_subscription",
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_latest_subscription,
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)
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monkeypatch.setattr(routes.PAYMENT_CHECKOUT, "enabled", True)
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def _reconcile_latest_intent(user_id):
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reconcile_calls["count"] += 1
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return {"ok": True, "action": "reconciled_confirmed_intent"}
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monkeypatch.setattr(
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routes.PAYMENT_CHECKOUT,
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"reconcile_latest_intent",
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_reconcile_latest_intent,
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)
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response = client.get("/api/auth/me")
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assert response.status_code == 200
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payload = response.json()
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assert payload["subscription_active"] is True
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assert payload["subscription_plan_code"] == "pro_monthly"
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assert reconcile_calls["count"] == 0
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def test_ops_memberships_prefers_supabase_auth_email(monkeypatch):
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monkeypatch.setattr(routes, "_assert_entitlement", lambda request: None)
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monkeypatch.setattr(routes, "_require_ops_admin", lambda request: None)
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monkeypatch.setattr(routes.PAYMENT_CHECKOUT, "enabled", False)
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class _FakeDB:
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@staticmethod
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def get_users_by_supabase_user_ids(user_ids):
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return {
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"user-1": {
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"supabase_email": "stale@example.com",
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"username": "tester",
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"telegram_id": 1,
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"created_at": "2026-03-01T00:00:00+00:00",
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}
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}
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import src.database.db_manager as db_module
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monkeypatch.setattr(db_module, "DBManager", lambda: _FakeDB())
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monkeypatch.setattr(
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routes.SUPABASE_ENTITLEMENT,
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"list_active_subscriptions",
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lambda limit=200: [
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{
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"user_id": "user-1",
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"plan_code": "pro_monthly",
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"starts_at": "2026-03-22T00:00:00+00:00",
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"expires_at": "2026-04-21T00:00:00+00:00",
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}
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],
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)
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monkeypatch.setattr(
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routes.SUPABASE_ENTITLEMENT,
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"get_auth_users",
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lambda user_ids: {
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"user-1": {
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"email": "fresh@example.com",
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"created_at": "2026-03-02T00:00:00+00:00",
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}
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},
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)
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response = client.get("/api/ops/memberships")
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assert response.status_code == 200
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payload = response.json()
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assert payload["memberships"][0]["email"] == "fresh@example.com"
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def test_ops_truth_history_returns_filtered_rows(monkeypatch):
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monkeypatch.setattr(routes, "_assert_entitlement", lambda request: None)
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monkeypatch.setattr(routes, "_require_ops_admin", lambda request: None)
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repo = TruthRecordRepository()
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repo.upsert_truth(
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city="taipei",
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target_date="2026-04-02",
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actual_high=26.0,
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settlement_source="wunderground",
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settlement_station_code="RCSS",
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settlement_station_label="Taipei Songshan Airport Station",
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truth_version="v1",
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updated_by="test",
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source_payload={"sample": True},
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is_final=True,
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)
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||
|
||
response = client.get("/api/ops/truth-history?city=taipei&date_from=2026-04-01&date_to=2026-04-03&limit=10")
|
||
|
||
assert response.status_code == 200
|
||
payload = response.json()
|
||
assert "items" in payload
|
||
assert payload["filters"]["city"] == "taipei"
|
||
assert payload["items"][0]["city"] == "taipei"
|
||
|
||
|
||
def test_scan_terminal_service_returns_stale_payload_after_failed_refresh(monkeypatch):
|
||
filters = {"scan_mode": "tradable", "limit": 5}
|
||
normalized_filters = scan_terminal_service._normalize_scan_terminal_filters(filters)
|
||
scan_terminal_service._SCAN_TERMINAL_CACHE.clear()
|
||
|
||
monkeypatch.setattr(
|
||
scan_terminal_service,
|
||
"_scan_city_terminal_rows",
|
||
lambda *_args, **_kwargs: {
|
||
"city": "taipei",
|
||
"rows": [
|
||
{
|
||
"id": "row-1",
|
||
"market_key": "market-1",
|
||
"edge_percent": 12.4,
|
||
"final_score": 83.0,
|
||
"volume": 2000,
|
||
}
|
||
],
|
||
"candidate_total": 1,
|
||
"primary_scores": [83.0],
|
||
},
|
||
)
|
||
|
||
ready = scan_terminal_service.build_scan_terminal_payload(filters, force_refresh=True)
|
||
assert ready["status"] == "ready"
|
||
assert ready["rows"][0]["id"] == "row-1"
|
||
|
||
def _explode(*_args, **_kwargs):
|
||
raise RuntimeError("upstream 504")
|
||
|
||
monkeypatch.setattr(scan_terminal_service, "_scan_city_terminal_rows", _explode)
|
||
|
||
stale = scan_terminal_service.build_scan_terminal_payload(filters, force_refresh=True)
|
||
|
||
assert stale["status"] == "stale"
|
||
assert stale["stale"] is True
|
||
assert stale["rows"][0]["id"] == "row-1"
|
||
assert stale["filters"] == normalized_filters
|
||
assert stale["stale_reason"] == "upstream 504"
|
||
|
||
|
||
def test_scan_terminal_service_returns_failed_without_success_snapshot(monkeypatch):
|
||
filters = {"scan_mode": "tradable", "limit": 5}
|
||
scan_terminal_service._SCAN_TERMINAL_CACHE.clear()
|
||
|
||
def _explode(*_args, **_kwargs):
|
||
raise RuntimeError("network down")
|
||
|
||
monkeypatch.setattr(scan_terminal_service, "_scan_city_terminal_rows", _explode)
|
||
|
||
failed = scan_terminal_service.build_scan_terminal_payload(filters, force_refresh=True)
|
||
|
||
assert failed["status"] == "failed"
|
||
assert failed["stale"] is False
|
||
assert failed["rows"] == []
|
||
assert failed["summary"]["candidate_total"] == 0
|
||
assert failed["stale_reason"] == "network down"
|
||
|
||
|
||
def test_scan_terminal_endpoint_forwards_filters(monkeypatch):
|
||
monkeypatch.setattr(routes, "_assert_entitlement", lambda request: None)
|
||
|
||
captured = {}
|
||
|
||
def _fake_build_scan_terminal_payload(filters, *, force_refresh=False):
|
||
captured["filters"] = dict(filters)
|
||
captured["force_refresh"] = force_refresh
|
||
return {
|
||
"generated_at": "2026-04-23T00:00:00Z",
|
||
"filters": filters,
|
||
"summary": {
|
||
"recommended_count": 1,
|
||
"visible_count": 1,
|
||
"candidate_total": 3,
|
||
"avg_edge_percent": 4.2,
|
||
"avg_primary_confidence": 88.0,
|
||
"tradable_market_count": 1,
|
||
"total_volume": 1500,
|
||
"resolved_market_type": "maxtemp",
|
||
},
|
||
"top_signal": None,
|
||
"rows": [],
|
||
}
|
||
|
||
monkeypatch.setattr(routes, "build_scan_terminal_payload", _fake_build_scan_terminal_payload)
|
||
|
||
response = client.get(
|
||
"/api/scan/terminal?scan_mode=trend&min_price=0.1&max_price=0.8&min_edge_pct=3"
|
||
"&min_liquidity=700&high_liquidity_only=true&market_type=all&time_range=week&limit=12&force_refresh=true"
|
||
)
|
||
|
||
assert response.status_code == 200
|
||
payload = response.json()
|
||
assert payload["summary"]["recommended_count"] == 1
|
||
assert captured["force_refresh"] is True
|
||
assert captured["filters"]["scan_mode"] == "trend"
|
||
assert captured["filters"]["market_type"] == "all"
|
||
assert captured["filters"]["time_range"] == "week"
|
||
assert captured["filters"]["limit"] == 12
|
||
|
||
|
||
def test_scan_terminal_cache_key_includes_filter_dimensions():
|
||
first = _scan_terminal_cache_key(
|
||
{
|
||
"scan_mode": "tradable",
|
||
"time_range": "today",
|
||
"limit": 25,
|
||
}
|
||
)
|
||
second = _scan_terminal_cache_key(
|
||
{
|
||
"scan_mode": "trend",
|
||
"time_range": "week",
|
||
"limit": 10,
|
||
}
|
||
)
|
||
|
||
assert first != second
|
||
assert "trend" in second
|
||
assert "week" in second
|
||
|
||
|
||
def test_city_history_is_read_only_and_uses_sqlite_truth_and_features(monkeypatch):
|
||
monkeypatch.setattr(routes, "_assert_entitlement", lambda request: None)
|
||
|
||
def _fail_bootstrap(*args, **kwargs):
|
||
raise AssertionError("bootstrap should not be called by /api/history")
|
||
|
||
monkeypatch.setattr(routes, "bootstrap_recent_daily_history_if_missing", _fail_bootstrap, raising=False)
|
||
|
||
truth_repo = TruthRecordRepository()
|
||
truth_repo.upsert_truth(
|
||
city="ankara",
|
||
target_date="2026-04-02",
|
||
actual_high=16.0,
|
||
settlement_source="metar",
|
||
settlement_station_code="LTAC",
|
||
settlement_station_label="Ankara Esenboga Airport",
|
||
truth_version="v1",
|
||
updated_by="test",
|
||
source_payload={"sample": True},
|
||
is_final=True,
|
||
)
|
||
feature_repo = TrainingFeatureRecordRepository()
|
||
feature_repo.upsert_record(
|
||
"ankara",
|
||
"2026-04-02",
|
||
{
|
||
"deb_prediction": 16.4,
|
||
"mu": 16.2,
|
||
"forecasts": {"Open-Meteo": 15.8, "ECMWF": 16.1},
|
||
},
|
||
)
|
||
|
||
response = client.get("/api/history/ankara")
|
||
|
||
assert response.status_code == 200
|
||
payload = response.json()
|
||
assert payload["history"]
|
||
row = next(item for item in payload["history"] if item["date"] == "2026-04-02")
|
||
assert row["actual"] == 16.0
|
||
assert row["deb"] == 16.4
|
||
assert row["mu"] == 16.2
|
||
assert row["forecasts"]["Open-Meteo"] == 15.8
|
||
assert row["settlement_station_code"] == "LTAC"
|
||
assert row["truth_version"] == "v1"
|