from fastapi.testclient import TestClient from web.app import app import web.routes as routes import web.scan_terminal_cache as scan_terminal_cache import web.scan_terminal_service as scan_terminal_service from web.scan_terminal_cache import scan_terminal_cache_key from src.database.runtime_state import TruthRecordRepository client = TestClient(app) def test_healthz_returns_ok_shape(): response = client.get('/healthz') assert response.status_code == 200 payload = response.json() assert payload['status'] in {'ok', 'degraded'} assert 'db' in payload assert 'state_storage_mode' in payload assert 'cities_count' in payload def test_system_status_returns_summary_shape(): response = client.get('/api/system/status') assert response.status_code == 200 payload = response.json() assert 'db' in payload assert 'state_storage_mode' in payload assert 'features' in payload assert 'integrations' in payload assert 'cache' in payload assert 'analysis' in payload['cache'] assert 'probability' in payload assert payload['probability']['engine_mode'] == 'legacy' assert 'training_data' in payload assert 'station_networks' in payload assert 'truth_records' in payload['training_data'] assert 'training_features' in payload['training_data'] assert 'city_coverage' in payload['training_data'] assert 'model_city_coverage' in payload['training_data'] assert 'metar_entries' in payload['cache'] assert 'nmc_entries' in payload['cache'] assert 'cities_count' in payload def test_metrics_endpoint_returns_prometheus_payload(): response = client.get('/metrics') assert response.status_code == 200 assert 'polyweather_http_requests_total' in response.text def test_city_ai_fallback_reasoning_identifies_fast_evidence_mode(): payload = scan_terminal_service._build_city_ai_fallback( { "city_display_name": "Tokyo", "temp_symbol": "°C", "deb": {"prediction": 17.8}, "model_cluster": { "sources": [ {"value": 17.0}, {"value": 17.8}, {"value": 20.6}, ] }, "observation_anchor": { "is_airport_metar": True, "station_code": "RJTT", }, "airport_current": { "station_code": "RJTT", "temp": 16.0, "report_time": "21:30Z", "raw_metar": "RJTT 262130Z AUTO 00000KT 9999 FEW030 16/10 Q1015", }, }, locale="zh-CN", reason="preview", ) assert "当前为快速证据模式" in payload["reasoning_zh"] assert "完整 AI 机场报文解读返回后再合并" in payload["reasoning_zh"] assert "AI 机场报文解读正常" not in payload["reasoning_zh"] assert "后补" not in payload["reasoning_zh"] assert "AI 增强可作为后续补充" not in payload["reasoning_zh"] def test_city_ai_fallback_revises_up_when_latest_metar_breaks_above_models(): payload = scan_terminal_service._build_city_ai_fallback( { "city_display_name": "Manila", "temp_symbol": "°C", "deb": {"prediction": 34.0}, "model_cluster": { "sources": [ {"value": 32.5}, {"value": 33.8}, {"value": 34.0}, {"value": 34.7}, ] }, "observation_anchor": { "is_airport_metar": True, "station_code": "RPLL", }, "airport_current": { "station_code": "RPLL", "temp": 35.0, "report_time": "03:00Z / 当地 11:00", "raw_metar": "RPLL 270300Z 34004KT CAVOK 35/24 Q1009", }, }, locale="zh-CN", reason="stream preview", ) assert payload["predicted_max"] == 35.0 assert payload["range_high"] == 35.0 assert "高于原先 34.0°C 中枢" in payload["final_judgment_zh"] assert "上修到至少 35.0°C" in payload["final_judgment_zh"] assert "共同支撑本轮最高温中枢" not in payload["reasoning_zh"] assert "超过模型上沿 34.7°C" in payload["reasoning_zh"] assert "继续上修最高温中枢" in payload["risks_zh"][0] def test_city_ai_fallback_revises_down_after_peak_when_observed_high_lags(): payload = scan_terminal_service._build_city_ai_fallback( { "city_display_name": "London", "temp_symbol": "°C", "deb": {"prediction": 30.0}, "model_cluster": { "sources": [ {"value": 29.2}, {"value": 30.0}, {"value": 31.1}, ] }, "window_phase": "post_peak", "peak_window_label": "14:00-16:59", "observation_anchor": { "is_airport_metar": True, "station_code": "EGLL", }, "airport_current": { "station_code": "EGLL", "temp": 27.0, "max_so_far": 27.5, "report_time": "16:30Z", "raw_metar": "EGLL 271630Z 22008KT 9999 SCT030 27/15 Q1012", }, }, locale="zh-CN", reason="stream preview", ) assert payload["predicted_max"] == 27.5 assert "峰值窗口（14:00-16:59）已过或接近结束" in payload["final_judgment_zh"] assert "最高温中枢需先下修到 27.5°C" in payload["final_judgment_zh"] assert "共同支撑本轮最高温中枢" not in payload["reasoning_zh"] assert "下修压力" in payload["reasoning_zh"] assert "继续下修最高温中枢" in payload["risks_zh"][0] def test_city_ai_fallback_does_not_downrevise_before_peak_window(): payload = scan_terminal_service._build_city_ai_fallback( { "city_display_name": "Dubai", "temp_symbol": "°C", "deb": {"prediction": 41.0}, "model_cluster": { "sources": [ {"value": 40.5}, {"value": 41.0}, {"value": 41.6}, ] }, "window_phase": "early_today", "minutes_until_peak_start": 240, "peak_window_label": "14:00-16:59", "observation_anchor": { "is_airport_metar": True, "station_code": "OMDB", }, "airport_current": { "station_code": "OMDB", "temp": 35.0, "report_time": "08:00Z", "raw_metar": "OMDB 270800Z 29007KT CAVOK 35/20 Q1008", }, }, locale="zh-CN", reason="stream preview", ) assert payload["predicted_max"] == 41.0 assert "暂不直接下修" in payload["reasoning_zh"] assert "峰值窗口尚未到来" in payload["reasoning_zh"] assert "若峰值窗口前继续偏低，需要下修最高温中枢" in payload["risks_zh"][0] def test_city_ai_fallback_marks_peak_window_passed_without_waiting_for_warming(): payload = scan_terminal_service._build_city_ai_fallback( { "city_display_name": "Paris", "temp_symbol": "°C", "deb": {"prediction": 28.0}, "model_cluster": { "sources": [ {"value": 27.6}, {"value": 28.0}, {"value": 28.5}, ] }, "window_phase": "post_peak", "peak_window_label": "13:00-15:59", "observation_anchor": { "is_airport_metar": True, "station_code": "LFPG", }, "airport_current": { "station_code": "LFPG", "temp": 27.0, "max_so_far": 27.2, "report_time": "17:00Z", "raw_metar": "LFPG 271700Z 25006KT 9999 FEW035 27/13 Q1014", }, }, locale="zh-CN", reason="stream preview", ) assert "峰值窗口（13:00-15:59）已过" in payload["final_judgment_zh"] assert "不是继续按待升温路径解读" in payload["reasoning_zh"] assert "避免继续上调最高温中枢" in payload["risks_zh"][0] def test_city_ai_fallback_treats_stale_metar_as_background_not_anchor(): payload = scan_terminal_service._build_city_ai_fallback( { "city_display_name": "Manila", "temp_symbol": "°C", "deb": {"prediction": 34.0}, "model_cluster": { "sources": [ {"value": 33.5}, {"value": 34.0}, {"value": 34.4}, ] }, "metar_context": { "stale_for_today": True, "last_observation_time": "00:00Z", }, "observation_anchor": { "is_airport_metar": True, "station_code": "RPLL", }, "airport_current": { "station_code": "RPLL", "temp": 36.0, "report_time": "00:00Z", "raw_metar": "RPLL 270000Z 34004KT CAVOK 36/24 Q1009", }, }, locale="zh-CN", reason="stream preview", ) assert payload["predicted_max"] == 34.0 assert "过旧" in payload["metar_read_zh"] assert "不能作为强实况锚点" in payload["metar_read_zh"] assert "先以 DEB 和多模型路径为主" in payload["final_judgment_zh"] assert "不能作为强实况锚点" in payload["reasoning_zh"] assert "上修到至少 36.0°C" not in payload["final_judgment_zh"] def test_city_ai_cache_key_changes_when_observation_fingerprint_changes(): """METAR 原文不变 → 缓存 key 不变（命中）；METAR 原文变了 → key 变化（miss）。""" base_input = { "city": "Manila", "local_date": "2026-04-28", "observation_anchor": { "source": "METAR", "is_airport_metar": True, "station_code": "RPLL", }, "airport_current": { "obs_time": "03:00Z", "raw_metar": "RPLL 280300Z 34004KT CAVOK 34/24 Q1009", }, "metar_context": { "stale_for_today": False, "last_observation_time": "03:00Z", }, } changed_input = { **base_input, "airport_current": { **base_input["airport_current"], "raw_metar": "RPLL 280330Z 36006KT 9999 FEW020 33/25 Q1010", "obs_time": "03:30Z", }, } assert scan_terminal_service._scan_city_ai_cache_key(base_input) != scan_terminal_service._scan_city_ai_cache_key(changed_input) def test_city_ai_stream_request_only_asks_provider_for_observation_read(): request_payload = scan_terminal_service._build_city_ai_stream_request( { "city": "Tokyo", "city_display_name": "Tokyo", "temp_symbol": "°C", "deb": {"prediction": 17.8}, "model_cluster": {"sources": [{"value": 17.0}, {"value": 17.8}]}, "observation_anchor": { "is_airport_metar": True, "read_label_zh": "机场报文解读", }, "airport_current": { "station_code": "RJTT", "temp": 16.0, "report_time": "21:30Z", "raw_metar": "RJTT 262130Z AUTO 00000KT 9999 FEW030 16/10 Q1015", }, }, locale="zh-CN", ) user_payload = request_payload["messages"][1]["content"] assert request_payload["stream"] is True assert request_payload["max_tokens"] <= 1200 assert request_payload["max_tokens"] < scan_terminal_service.SCAN_AI_MAX_TOKENS assert "taf_read_zh" in user_payload assert "probability_read_zh" in user_payload assert "predicted_max" in user_payload assert "final_judgment" in user_payload def test_city_ai_partial_json_trims_dangling_taf_clause(): payload = scan_terminal_service._build_city_ai_fallback( { "city_display_name": "London", "temp_symbol": "°C", "deb": {"prediction": 24.3}, "model_cluster": { "sources": [ {"value": 22.3}, {"value": 23.1}, {"value": 24.3}, {"value": 26.3}, ] }, "observation_anchor": { "is_airport_metar": True, "station_code": "EGLL", }, "airport_current": { "station_code": "EGLL", "temp": 21.0, "report_time": "09:00Z", "raw_metar": "EGLL 270900Z 34004KT CAVOK 21/09 Q1016", }, }, locale="zh-CN", reason="AI content is not a JSON object", raw_content=( '{"metar_read_zh":"最新METAR报文09:00观测温度21°C，西北风4节（340°），' '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；' 'TAF预示10-11点转南风（18012KT），南风可能带来凉爽海风抑制升温。",' '"reasoning_zh":"DEB预测24.3°C，多数模型集中在23-26°C，' '当前09时实测21°C处于快速升温路径，但TAF显示' ), ) assert "但TAF显示" not in payload["reasoning_zh"] assert payload["reasoning_zh"].endswith("。") assert "当前09时实测21°C处于快速升温路径" in payload["reasoning_zh"] def test_city_ai_schema_completion_trims_dangling_taf_clause(): payload = scan_terminal_service._complete_city_ai_payload( { "predicted_max": 24.3, "range_low": 22.3, "range_high": 26.3, "unit": "°C", "confidence": "medium", "final_judgment_zh": "London 最高温中枢暂看24°C附近。", "final_judgment_en": "London high is centered near 24°C.", "metar_read_zh": "最新METAR报文09:00观测温度21°C，西北风4节，CAVOK。", "metar_read_en": "The latest METAR shows 21°C at 09:00 with northwesterly wind and CAVOK.", "reasoning_zh": "当前09时实测21°C处于快速升温路径，但TAF显示", "reasoning_en": "The 09:00 observation is on a fast warming path, but TAF shows", "risks_zh": ["后续METAR若升温放缓，需要下修。"], "risks_en": ["If later METAR warming slows, revise lower."], "model_cluster_note_zh": "4/4 个模型落在 DEB ±2°C 内。", "model_cluster_note_en": "4/4 models sit within 2°C of DEB.", }, { "city_display_name": "London", "temp_symbol": "°C", "deb": {"prediction": 24.3}, "model_cluster": {"sources": [{"value": 22.3}, {"value": 26.3}]}, "observation_anchor": {"is_airport_metar": True, "station_code": "EGLL"}, "airport_current": { "station_code": "EGLL", "temp": 21.0, "report_time": "09:00Z", "raw_metar": "EGLL 270900Z 34004KT CAVOK 21/09 Q1016", }, }, locale="zh-CN", ) assert payload["reasoning_zh"] == "当前09时实测21°C处于快速升温路径。" assert payload["reasoning_en"] == "The 09:00 observation is on a fast warming path." assert payload["_polyweather_meta"]["trimmed_incomplete_fields"] == [ "reasoning_en", "reasoning_zh", ] def test_city_ai_schema_completion_guards_stale_observation_text(): payload = scan_terminal_service._complete_city_ai_payload( { "predicted_max": 36.0, "range_low": 35.0, "range_high": 37.0, "unit": "°C", "confidence": "medium", "final_judgment_zh": "Manila 最新 METAR 已经支撑 36°C 高温中枢。", "final_judgment_en": "Manila latest METAR supports a 36°C high center.", "metar_read_zh": "RPLL 最新 METAR 显示 36°C，当前作为强实况锚点。", "metar_read_en": "RPLL latest METAR shows 36°C and is a strong live anchor.", "reasoning_zh": "最新 METAR 与模型共同支撑上修。", "reasoning_en": "Latest METAR and models jointly support an upward revision.", "risks_zh": ["若继续升温，需要上修。"], "risks_en": ["If it keeps warming, revise upward."], "model_cluster_note_zh": "3/3 个模型集中。", "model_cluster_note_en": "3/3 models are clustered.", }, { "city_display_name": "Manila", "temp_symbol": "°C", "deb": {"prediction": 34.0}, "model_cluster": { "sources": [{"value": 33.5}, {"value": 34.0}, {"value": 34.4}] }, "metar_context": { "stale_for_today": True, "last_observation_time": "00:00Z", }, "observation_anchor": {"is_airport_metar": True, "station_code": "RPLL"}, "airport_current": { "station_code": "RPLL", "temp": 36.0, "report_time": "00:00Z", "raw_metar": "RPLL 270000Z 34004KT CAVOK 36/24 Q1009", }, }, locale="zh-CN", ) assert payload["predicted_max"] == 34.0 assert "过旧" in payload["metar_read_zh"] assert "不能作为强实况锚点" in payload["metar_read_zh"] assert "先以 DEB 和多模型路径为主" in payload["final_judgment_zh"] assert "共同支撑上修" not in payload["reasoning_zh"] assert "deterministic_guard_fields" in payload["_polyweather_meta"] def test_city_ai_schema_completion_guards_observed_high_break_numbers(): payload = scan_terminal_service._complete_city_ai_payload( { "predicted_max": 34.0, "range_low": 32.5, "range_high": 34.7, "unit": "°C", "confidence": "medium", "final_judgment_zh": "Manila 最高温仍以 34.0°C 为中枢。", "final_judgment_en": "Manila high remains centered near 34.0°C.", "metar_read_zh": "RPLL 最新 METAR 显示 35°C，CAVOK。", "metar_read_en": "RPLL latest METAR shows 35°C and CAVOK.", "reasoning_zh": "模型区间仍覆盖当前路径，无需上修。", "reasoning_en": "The model range still covers the path, so no upward revision is needed.", "risks_zh": ["后续报文偏离再修正。"], "risks_en": ["Revise if later reports diverge."], "model_cluster_note_zh": "4/4 个模型集中。", "model_cluster_note_en": "4/4 models are clustered.", }, { "city_display_name": "Manila", "temp_symbol": "°C", "deb": {"prediction": 34.0}, "model_cluster": { "sources": [ {"value": 32.5}, {"value": 33.8}, {"value": 34.0}, {"value": 34.7}, ] }, "observation_anchor": {"is_airport_metar": True, "station_code": "RPLL"}, "airport_current": { "station_code": "RPLL", "temp": 35.0, "report_time": "03:00Z / 当地 11:00", "raw_metar": "RPLL 270300Z 34004KT CAVOK 35/24 Q1009", }, }, locale="zh-CN", ) assert payload["predicted_max"] == 35.0 assert payload["range_high"] == 35.0 assert "上修到至少 35.0°C" in payload["final_judgment_zh"] assert "无需上修" not in payload["reasoning_zh"] assert "deterministic_guard_fields" in payload["_polyweather_meta"] def test_cities_endpoint_uses_denver_display_name_for_aurora_market(): response = client.get("/api/cities") assert response.status_code == 200 payload = response.json() denver = next(item for item in payload["cities"] if item["name"] == "denver") assert denver["display_name"] == "Denver" assert denver["network_provider"] == "global_metar" assert denver["deb_recent_tier"] in {"high", "medium", "low", "other"} assert "deb_recent_sample_count" in denver def test_cities_endpoint_includes_new_wunderground_cities(): response = client.get("/api/cities") assert response.status_code == 200 payload = response.json() names = {item["name"] for item in payload["cities"]} assert { "busan", "qingdao", "panama city", "kuala lumpur", "jakarta", "helsinki", "amsterdam", }.issubset(names) def test_payment_runtime_endpoint_returns_shape(): response = client.get('/api/payments/runtime') assert response.status_code == 200 payload = response.json() assert 'checkout' in payload assert 'rpc' in payload assert 'event_loop_state' in payload assert 'recent_audit_events' in payload def test_auth_me_does_not_reconcile_on_status_probe(monkeypatch): monkeypatch.setattr(routes, "_assert_entitlement", lambda request: None) def _bind_identity(request): request.state.auth_user_id = "user-1" request.state.auth_email = "user@example.com" monkeypatch.setattr(routes, "_bind_optional_supabase_identity", _bind_identity) monkeypatch.setattr(routes, "_resolve_auth_points", lambda request: 0) monkeypatch.setattr(routes, "_resolve_weekly_profile", lambda request: {"weekly_points": 0, "weekly_rank": None}) monkeypatch.setattr(routes.SUPABASE_ENTITLEMENT, "enabled", True) calls = {"count": 0} reconcile_calls = {"count": 0} def _latest_subscription(user_id, respect_requirement=False): calls["count"] += 1 return { "plan_code": "pro_monthly", "starts_at": "2026-03-22T00:00:00+00:00", "expires_at": "2026-04-21T00:00:00+00:00", } monkeypatch.setattr( routes.SUPABASE_ENTITLEMENT, "get_latest_active_subscription", _latest_subscription, ) monkeypatch.setattr(routes.PAYMENT_CHECKOUT, "enabled", True) def _reconcile_latest_intent(user_id): reconcile_calls["count"] += 1 return {"ok": True, "action": "reconciled_confirmed_intent"} monkeypatch.setattr( routes.PAYMENT_CHECKOUT, "reconcile_latest_intent", _reconcile_latest_intent, ) response = client.get("/api/auth/me") assert response.status_code == 200 payload = response.json() assert payload["subscription_active"] is True assert payload["subscription_plan_code"] == "pro_monthly" assert reconcile_calls["count"] == 0 def test_ops_memberships_prefers_supabase_auth_email(monkeypatch): monkeypatch.setattr(routes, "_assert_entitlement", lambda request: None) monkeypatch.setattr(routes, "_require_ops_admin", lambda request: None) monkeypatch.setattr(routes.PAYMENT_CHECKOUT, "enabled", False) class _FakeDB: @staticmethod def get_users_by_supabase_user_ids(user_ids): return { "user-1": { "supabase_email": "stale@example.com", "username": "tester", "telegram_id": 1, "created_at": "2026-03-01T00:00:00+00:00", } } import src.database.db_manager as db_module monkeypatch.setattr(db_module, "DBManager", lambda: _FakeDB()) monkeypatch.setattr( routes.SUPABASE_ENTITLEMENT, "list_active_subscriptions", lambda limit=200: [ { "user_id": "user-1", "plan_code": "pro_monthly", "starts_at": "2026-03-22T00:00:00+00:00", "expires_at": "2026-04-21T00:00:00+00:00", } ], ) monkeypatch.setattr( routes.SUPABASE_ENTITLEMENT, "get_auth_users", lambda user_ids: { "user-1": { "email": "fresh@example.com", "created_at": "2026-03-02T00:00:00+00:00", } }, ) response = client.get("/api/ops/memberships") assert response.status_code == 200 payload = response.json() assert payload["memberships"][0]["email"] == "fresh@example.com" def test_ops_truth_history_returns_filtered_rows(monkeypatch): monkeypatch.setattr(routes, "_assert_entitlement", lambda request: None) monkeypatch.setattr(routes, "_require_ops_admin", lambda request: None) repo = TruthRecordRepository() repo.upsert_truth( city="taipei", target_date="2026-04-02", actual_high=26.0, settlement_source="wunderground", settlement_station_code="RCSS", settlement_station_label="Taipei Songshan Airport Station", truth_version="v1", updated_by="test", source_payload={"sample": True}, is_final=True, ) 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_cache._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_cache._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