feat: implement ML filter with LightGBM for trading signal validation

- Added MLFilter class to load and evaluate LightGBM model for trading signals.
- Introduced retraining mechanism to update the model daily based on new data.
- Created feature engineering and label building utilities for model training.
- Updated bot logic to incorporate ML filter for signal validation.
- Added scripts for data fetching and model training.

Made-with: Cursor

tests/test_label_builder.py

@@ -0,0 +1,73 @@
+import pandas as pd
+import numpy as np
+import pytest
+from src.label_builder import build_labels
+
+
+def make_signal_df():
+    """
+    신호 발생 시점 이후 가격이 TP에 도달하는 시나리오
+    entry=100, TP=103, SL=98.5
+    """
+    future_closes = [100.5, 101.0, 101.8, 102.5, 103.1, 103.5]
+    future_highs  = [c + 0.3 for c in future_closes]
+    future_lows   = [c - 0.3 for c in future_closes]
+    return future_closes, future_highs, future_lows
+
+
+def test_label_tp_reached():
+    closes, highs, lows = make_signal_df()
+    label = build_labels(
+        future_closes=closes,
+        future_highs=highs,
+        future_lows=lows,
+        take_profit=103.0,
+        stop_loss=98.5,
+        side="LONG",
+    )
+    assert label == 1, "TP 먼저 도달해야 레이블 1"
+
+
+def test_label_sl_reached():
+    future_closes = [99.5, 99.0, 98.8, 98.4, 98.0]
+    future_highs  = [c + 0.3 for c in future_closes]
+    future_lows   = [c - 0.3 for c in future_closes]
+    label = build_labels(
+        future_closes=future_closes,
+        future_highs=future_highs,
+        future_lows=future_lows,
+        take_profit=103.0,
+        stop_loss=98.5,
+        side="LONG",
+    )
+    assert label == 0, "SL 먼저 도달해야 레이블 0"
+
+
+def test_label_neither_reached_returns_none():
+    future_closes = [100.1, 100.2, 100.3]
+    future_highs  = [c + 0.1 for c in future_closes]
+    future_lows   = [c - 0.1 for c in future_closes]
+    label = build_labels(
+        future_closes=future_closes,
+        future_highs=future_highs,
+        future_lows=future_lows,
+        take_profit=103.0,
+        stop_loss=98.5,
+        side="LONG",
+    )
+    assert label is None, "미결 시 None 반환"
+
+
+def test_label_short_tp():
+    future_closes = [99.5, 99.0, 98.0, 97.0]
+    future_highs  = [c + 0.3 for c in future_closes]
+    future_lows   = [c - 0.3 for c in future_closes]
+    label = build_labels(
+        future_closes=future_closes,
+        future_highs=future_highs,
+        future_lows=future_lows,
+        take_profit=97.0,
+        stop_loss=101.5,
+        side="SHORT",
+    )
+    assert label == 1