refactor: Git에서 데이터 제거, 설정·코드만 유지

파이프라인 산출물(data/, docs/)을 Git 추적에서 제외하고
히스토리를 단일 커밋으로 재구성해 저장소 용량을 경량화한다.

Co-authored-by: Cursor <cursoragent@cursor.com>

src/deepcoin/techniques/rsi_divergence.py

@@ -0,0 +1,71 @@
+"""RSI 다이버전스 기법."""
+
+from __future__ import annotations
+
+import pandas as pd
+
+from deepcoin.techniques.base import BaseTechnique, TechniqueParams, TechniqueSignal
+from deepcoin.techniques.helpers import (
+    dedupe_signals,
+    detect_bearish_divergence,
+    detect_bullish_divergence,
+    find_confirmed_pivots,
+    make_signal,
+)
+from deepcoin.techniques.indicators import rsi
+
+
+class RsiDivergenceTechnique(BaseTechnique):
+    """RSI 상승·하락 다이버전스 매수·매도."""
+
+    technique_id = "rsi_divergence"
+    technique_name = "RSI 다이버전스"
+    category = "divergence"
+    causal = True
+    description = "RSI 상승(Bd)·하락(Sd) 다이버전스"
+
+    def default_extra_params(self) -> dict:
+        return {"period": 14, "order": 12, "min_bars_between": 15, "max_bars_between": 400}
+
+    def generate_signals(self, df: pd.DataFrame, params: TechniqueParams) -> list[TechniqueSignal]:
+        period = int(params.extra.get("period", 14))
+        order = int(params.extra.get("order", 12))
+        min_bars = int(params.extra.get("min_bars_between", 15))
+        max_bars = int(params.extra.get("max_bars_between", 400))
+
+        close = df["close"].astype(float)
+        low = df["low"].astype(float)
+        high = df["high"].astype(float)
+        rsi_vals = rsi(close, period=period)
+
+        low_pivots = find_confirmed_pivots(low, order, "low")
+        high_pivots = find_confirmed_pivots(high, order, "high")
+        signals: list[TechniqueSignal] = []
+
+        for pivot_idx, _ in detect_bullish_divergence(
+            low_pivots, rsi_vals, min_bars_between=min_bars, max_bars_between=max_bars,
+        ):
+            confirm_idx = pivot_idx + order
+            if confirm_idx >= len(df):
+                continue
+            signals.append(
+                make_signal(
+                    df, confirm_idx, float(close.iloc[confirm_idx]), "buy",
+                    "rsi_bull_divergence", pivot_bar_index=pivot_idx, confidence=0.78,
+                )
+            )
+
+        for pivot_idx, _ in detect_bearish_divergence(
+            high_pivots, rsi_vals, min_bars_between=min_bars, max_bars_between=max_bars,
+        ):
+            confirm_idx = pivot_idx + order
+            if confirm_idx >= len(df):
+                continue
+            signals.append(
+                make_signal(
+                    df, confirm_idx, float(close.iloc[confirm_idx]), "sell",
+                    "rsi_bear_divergence", pivot_bar_index=pivot_idx, confidence=0.78,
+                )
+            )
+
+        return dedupe_signals(signals, min_bars=min_bars)