2569718930@qq.com
343 lines
11 KiB
Python
343 lines
11 KiB
Python
from web.scan_terminal_filters import normalize_scan_terminal_filters
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from web import scan_terminal_cache
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from web.scan_terminal_metar_gate import _apply_metar_gate_to_row
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from web.scan_terminal_payloads import (
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build_failed_scan_terminal_payload,
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build_scan_terminal_snapshot_id,
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build_stale_scan_terminal_payload,
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compact_ranked_scan_rows_for_payload,
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SCAN_PAYLOAD_DEFERRED_RUNWAY_POINTS,
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SCAN_PAYLOAD_FULL_RUNWAY_HISTORY_ROWS,
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)
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from web.scan_terminal_ranker import build_ranked_scan_terminal_result
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from web import scan_terminal_city_row
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from web.scan_terminal_city_row import _build_quick_row
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from web.routers.scan import router as scan_router
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from web.scan_terminal_service import _scan_terminal_prewarm_filters
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class _FakeRedis:
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def __init__(self):
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self.data = {}
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def get(self, key):
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return self.data.get(key)
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def setex(self, key, _ttl, value):
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self.data[key] = value
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def test_scan_terminal_cache_hydrates_success_payload_from_redis(monkeypatch):
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fake_redis = _FakeRedis()
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monkeypatch.setenv("POLYWEATHER_SCAN_TERMINAL_REDIS_CACHE_ENABLED", "true")
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monkeypatch.setattr(scan_terminal_cache, "_get_redis_client", lambda: fake_redis)
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scan_terminal_cache._SCAN_TERMINAL_CACHE.clear()
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filters = {"scan_mode": "tradable", "limit": 9}
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payload = {
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"generated_at": "2026-06-01T00:00:00Z",
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"rows": [{"id": "row-1"}],
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"summary": {"candidate_total": 1},
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}
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scan_terminal_cache.set_cached_scan_terminal_payload(filters, payload)
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scan_terminal_cache._SCAN_TERMINAL_CACHE.clear()
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entry = scan_terminal_cache.get_scan_terminal_cache_entry(filters)
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cached = scan_terminal_cache.get_cached_scan_terminal_payload(filters, ttl_sec=3600)
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assert entry["success_payload"]["rows"] == [{"id": "row-1"}]
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assert cached["summary"]["candidate_total"] == 1
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def test_scan_terminal_failure_state_preserves_redis_success_payload(monkeypatch):
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fake_redis = _FakeRedis()
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monkeypatch.setenv("POLYWEATHER_SCAN_TERMINAL_REDIS_CACHE_ENABLED", "true")
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monkeypatch.setattr(scan_terminal_cache, "_get_redis_client", lambda: fake_redis)
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scan_terminal_cache._SCAN_TERMINAL_CACHE.clear()
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filters = {"scan_mode": "tradable", "limit": 9}
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scan_terminal_cache.set_cached_scan_terminal_payload(
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filters,
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{
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"generated_at": "2026-06-01T00:00:00Z",
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"rows": [{"id": "row-1"}],
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},
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)
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scan_terminal_cache._SCAN_TERMINAL_CACHE.clear()
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scan_terminal_cache.set_scan_terminal_failure_state(filters, error_message="timeout")
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scan_terminal_cache._SCAN_TERMINAL_CACHE.clear()
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entry = scan_terminal_cache.get_scan_terminal_cache_entry(filters)
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assert entry["success_payload"]["rows"] == [{"id": "row-1"}]
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assert entry["last_error"] == "timeout"
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def test_scan_terminal_prewarm_covers_default_api_limit():
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limits = {filters["limit"] for filters in _scan_terminal_prewarm_filters()}
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assert 25 in limits
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assert 180 in limits
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def test_scan_city_terminal_rows_reuses_persisted_panel_cache(monkeypatch):
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payload = {
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"display_name": "Paris",
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"local_date": "2026-06-10",
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"local_time": "12:00",
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"current": {"temp": 18.0},
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"risk": {},
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"deb": {"prediction": 20.0},
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"probabilities": {},
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"multi_model": {},
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}
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class _Cache:
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@staticmethod
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def get_city_cache(kind, city):
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assert (kind, city) == ("panel", "paris")
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return {"payload": payload}
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monkeypatch.setattr(scan_terminal_city_row, "_PANEL_CACHE_DB", _Cache())
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monkeypatch.setattr(
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scan_terminal_city_row,
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"_analyze",
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lambda *_args, **_kwargs: (_ for _ in ()).throw(
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AssertionError("non-force scan must not fetch external sources")
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),
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)
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result = scan_terminal_city_row._scan_city_terminal_rows(
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"paris",
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{"market_type": "maxtemp"},
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force_refresh=False,
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)
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assert result["city"] == "paris"
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assert result["rows"][0]["current_temp"] == 18.0
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def test_scan_router_does_not_expose_terminal_ai_endpoint():
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routes = {
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getattr(route, "path", None): getattr(route, "methods", set())
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for route in scan_router.routes
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}
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assert "/api/scan/terminal/ai" not in routes
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def test_normalize_scan_terminal_filters_clamps_and_swaps_bounds():
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filters = normalize_scan_terminal_filters(
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{
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"min_price": 1.2,
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"max_price": -0.2,
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"limit": 999,
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"high_liquidity_only": True,
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"min_liquidity": 100,
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"timezone_offset_seconds": "28800",
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}
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)
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assert filters["min_price"] == 0.0
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assert filters["max_price"] == 1.0
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assert filters["limit"] == 200
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assert filters["min_liquidity"] == 5000.0
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assert filters["timezone_offset_seconds"] == 28800
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def test_ranked_scan_terminal_result_sorts_and_summarizes_unique_markets():
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result = build_ranked_scan_terminal_result(
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city_results=[
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{
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"candidate_total": 2,
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"primary_scores": [80.0],
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"rows": [
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{
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"id": "low",
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"market_key": "m1",
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"final_score": 70.0,
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"edge_percent": 4.0,
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"volume": 100,
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},
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{
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"id": "high",
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"market_key": "m1",
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"final_score": 90.0,
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"edge_percent": 2.0,
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"volume": 250,
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},
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],
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},
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{
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"candidate_total": 1,
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"primary_scores": [60.0],
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"rows": [
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{
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"id": "tie-break",
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"market_key": "m2",
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"final_score": 90.0,
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"edge_percent": 5.0,
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"volume": 300,
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}
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],
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},
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],
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filters={"limit": 2},
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total_city_count=3,
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failed_city_count=1,
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)
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assert [row["id"] for row in result["ranked_rows"]] == ["tie-break", "high"]
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assert [row["rank"] for row in result["ranked_rows"]] == [1, 2]
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assert result["top_signal"]["id"] == "tie-break"
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assert result["summary"]["candidate_total"] == 3
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assert result["summary"]["visible_count"] == 2
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assert result["summary"]["tradable_market_count"] == 2
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assert result["summary"]["total_volume"] == 550
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assert result["summary"]["failed_city_count"] == 1
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def test_scan_terminal_payload_helpers_preserve_stale_and_failed_shape():
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success_payload = {
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"generated_at": "2026-04-28T00:00:00Z",
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"snapshot_id": "scan-old",
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"filters": {"scan_mode": "tradable"},
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"rows": [{"id": "row-1"}],
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}
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stale = build_stale_scan_terminal_payload(
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filters={"scan_mode": "trend"},
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success_payload=success_payload,
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error_message="refresh failed",
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failed_at="2026-04-28T00:01:00Z",
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)
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failed = build_failed_scan_terminal_payload(
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filters={"scan_mode": "trend"},
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error_message="network down",
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failed_at="2026-04-28T00:02:00Z",
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)
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assert stale["status"] == "stale"
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assert stale["stale"] is True
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assert stale["rows"] == [{"id": "row-1"}]
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assert stale["filters"] == {"scan_mode": "trend"}
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assert stale["last_success_at"] == "2026-04-28T00:00:00Z"
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assert failed["status"] == "failed"
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assert failed["summary"]["candidate_total"] == 0
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assert failed["rows"] == []
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def test_scan_terminal_snapshot_id_is_stable_for_same_ranked_inputs():
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summary = {
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"candidate_total": 2,
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"tradable_market_count": 2,
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"avg_edge_percent": 3.5,
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}
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rows = [
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{"id": "a", "edge_percent": 4.0, "final_score": 90.0},
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{"id": "b", "edge_percent": 3.0, "final_score": 80.0},
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]
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first = build_scan_terminal_snapshot_id({"limit": 2}, rows, summary, rows[0])
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second = build_scan_terminal_snapshot_id({"limit": 2}, rows, summary, rows[0])
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assert first == second
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assert first.startswith("scan-")
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def test_scan_terminal_payload_slims_deferred_runway_history_rows():
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runway_points = [
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{"time": f"2026-05-31T{hour:02d}:00:00+00:00", "temp": 20 + hour}
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for hour in range(24)
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]
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rows = [
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{
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"id": f"row-{index}",
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"runway_plate_history": {"35R": list(runway_points)},
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}
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for index in range(SCAN_PAYLOAD_FULL_RUNWAY_HISTORY_ROWS + 2)
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]
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compacted = compact_ranked_scan_rows_for_payload(rows)
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assert len(compacted[0]["runway_plate_history"]["35R"]) == len(runway_points)
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assert (
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len(
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compacted[SCAN_PAYLOAD_FULL_RUNWAY_HISTORY_ROWS - 1][
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"runway_plate_history"
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]["35R"]
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)
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== len(runway_points)
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)
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assert (
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len(
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compacted[SCAN_PAYLOAD_FULL_RUNWAY_HISTORY_ROWS][
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"runway_plate_history"
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]["35R"]
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)
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== SCAN_PAYLOAD_DEFERRED_RUNWAY_POINTS
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)
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assert len(rows[SCAN_PAYLOAD_FULL_RUNWAY_HISTORY_ROWS]["runway_plate_history"]["35R"]) == len(
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runway_points
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)
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def test_scan_terminal_quick_row_compacts_runway_history_for_list_payload():
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raw_history = {
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"35R": [
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{"time": "2026-05-31T00:00:00+00:00", "temp": 22.11},
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{"time": "2026-05-31T00:01:00+00:00", "temp": 22.22},
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{"time": "2026-05-31T00:02:00+00:00", "temp": 22.33},
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{"time": "2026-05-31T00:10:00+00:00", "temp": 23.44},
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{"time": "2026-05-31T00:11:00+00:00", "temp": 23.55},
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]
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}
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row = _build_quick_row(
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city="shanghai",
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data={
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"display_name": "Shanghai",
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"local_date": "2026-05-31",
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"local_time": "2026-05-31T08:11:00+08:00",
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"temp_symbol": "°C",
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"current": {"temp": 22.3, "max_so_far": 23.0},
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"risk": {"airport": "Shanghai Pudong", "level": "medium"},
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"deb": {"prediction": 24.0},
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"probabilities": {"distribution": []},
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"multi_model": {},
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"runway_plate_history": raw_history,
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},
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)
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compact_history = row["runway_plate_history"]["35R"]
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assert len(compact_history) == 2
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assert compact_history[0]["temp"] == 22.3
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assert compact_history[1]["temp"] == 23.6
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assert len(str(row["runway_plate_history"])) < len(str(raw_history))
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def test_metar_gate_vetoes_yes_when_observed_breaks_above_bucket():
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row = {
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"id": "yes-row",
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"side": "yes",
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"target_lower": 32.0,
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"target_upper": 34.0,
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"target_unit": "°C",
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"metar_context": {
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"obs_count": 6,
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"max_temp": 35.0,
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"last_temp": 35.0,
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"trend_delta": 1.0,
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"stale_for_today": False,
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},
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}
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_apply_metar_gate_to_row(row)
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assert row["v4_metar_decision"] == "veto"
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assert row["ai_decision"] == "veto"
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assert "越过目标桶上沿" in row["ai_reason_zh"]
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