test(filter): add failing tests for OHLCV cache helper methods

tests/test_filter_ohlcv_cache.py

@@ -0,0 +1,135 @@
+"""Tests for OHLCV-cache-backed filter enrichment."""
+import pandas as pd
+import pytest
+from unittest.mock import MagicMock, patch
+
+
+def _make_ohlcv(closes: list[float]) -> pd.DataFrame:
+    """Build a minimal OHLCV DataFrame from a list of closing prices."""
+    dates = pd.date_range("2026-01-01", periods=len(closes), freq="B")
+    return pd.DataFrame(
+        {
+            "Open": closes,
+            "High": closes,
+            "Low": closes,
+            "Close": closes,
+            "Volume": [1_000_000] * len(closes),
+        },
+        index=dates,
+    )
+
+
+def _make_filter(config_overrides=None):
+    """Instantiate a CandidateFilter with minimal config."""
+    from tradingagents.dataflows.discovery.filter import CandidateFilter
+
+    config = {
+        "discovery": {
+            "ohlcv_cache_dir": "data/ohlcv_cache",
+            "filters": {
+                "min_average_volume": 0,
+                "volume_lookback_days": 10,
+                "filter_same_day_movers": True,
+                "intraday_movement_threshold": 10.0,
+                "filter_recent_movers": True,
+                "recent_movement_lookback_days": 7,
+                "recent_movement_threshold": 10.0,
+                "recent_mover_action": "filter",
+                "volume_cache_key": "default",
+                "min_market_cap": 0,
+                "compression_atr_pct_max": 2.0,
+                "compression_bb_width_max": 6.0,
+                "compression_min_volume_ratio": 1.3,
+                "filter_fundamental_risk": False,
+                "min_z_score": None,
+                "min_f_score": None,
+            },
+            "enrichment": {
+                "batch_news_vendor": "google",
+                "batch_news_batch_size": 150,
+                "news_lookback_days": 0.5,
+                "context_max_snippets": 2,
+                "context_snippet_max_chars": 140,
+            },
+            "max_candidates_to_analyze": 200,
+            "analyze_all_candidates": False,
+            "final_recommendations": 15,
+            "truncate_ranking_context": False,
+            "max_news_chars": 500,
+            "max_insider_chars": 300,
+            "max_recommendations_chars": 300,
+            "log_tool_calls": False,
+            "log_tool_calls_console": False,
+            "log_prompts_console": False,
+            "tool_log_max_chars": 10_000,
+            "tool_log_exclude": [],
+        }
+    }
+    if config_overrides:
+        config["discovery"]["filters"].update(config_overrides)
+
+    # Create a mock tool executor
+    mock_tool_executor = MagicMock()
+
+    return CandidateFilter(config, mock_tool_executor)
+
+
+def test_current_price_comes_from_ohlcv_cache():
+    """current_price on the candidate should be the last close from the OHLCV cache."""
+    closes = [100.0] * 210 + [123.45]  # last close = 123.45
+    ohlcv_data = {"AAPL": _make_ohlcv(closes)}
+
+    f = _make_filter()
+    price = f._price_from_cache("AAPL", ohlcv_data)
+    assert price == pytest.approx(123.45)
+
+
+def test_intraday_check_from_cache_not_moved():
+    """intraday check: <10% day-over-day change → already_moved=False."""
+    closes = [100.0] * 210 + [105.0]  # +5% last day — under threshold
+    ohlcv_data = {"AAPL": _make_ohlcv(closes)}
+
+    f = _make_filter()
+    result = f._intraday_from_cache("AAPL", ohlcv_data, threshold=10.0)
+    assert result["already_moved"] is False
+    assert result["intraday_change_pct"] == pytest.approx(5.0)
+
+
+def test_intraday_check_from_cache_moved():
+    """intraday check: >10% day-over-day change → already_moved=True."""
+    closes = [100.0] * 210 + [115.0]  # +15% last day — over threshold
+    ohlcv_data = {"AAPL": _make_ohlcv(closes)}
+
+    f = _make_filter()
+    result = f._intraday_from_cache("AAPL", ohlcv_data, threshold=10.0)
+    assert result["already_moved"] is True
+    assert result["intraday_change_pct"] == pytest.approx(15.0)
+
+
+def test_recent_move_check_from_cache_leading():
+    """recent-move check: <10% change over 7 days → status=leading."""
+    closes = [100.0] * 205 + [103.0] * 7  # flat last 7 days
+    ohlcv_data = {"AAPL": _make_ohlcv(closes)}
+
+    f = _make_filter()
+    result = f._recent_move_from_cache("AAPL", ohlcv_data, lookback_days=7, threshold=10.0)
+    assert result["status"] == "leading"
+    assert abs(result["price_change_pct"]) < 10.0
+
+
+def test_recent_move_check_from_cache_lagging():
+    """recent-move check: >10% change over 7 days → status=lagging."""
+    closes = [100.0] * 205 + [100.0] * 6 + [115.0]  # +15% in last day within window
+    ohlcv_data = {"AAPL": _make_ohlcv(closes)}
+
+    f = _make_filter()
+    result = f._recent_move_from_cache("AAPL", ohlcv_data, lookback_days=7, threshold=10.0)
+    assert result["status"] == "lagging"
+
+
+def test_cache_miss_returns_none():
+    """If ticker is not in ohlcv_data, helper returns None."""
+    f = _make_filter()
+    assert f._price_from_cache("MISSING", {}) is None
+    assert f._intraday_from_cache("MISSING", {}, threshold=10.0) is None
+    assert f._recent_move_from_cache("MISSING", {}, lookback_days=7, threshold=10.0) is None