최초 프로젝트 업로드 (Script Auto Commit)

src/tests/test_main.py

@@ -0,0 +1,93 @@
+import sys
+import os
+
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "../..")))
+
+import builtins
+import types
+import pandas as pd
+import pytest
+
+import main
+from .test_helpers import check_and_notify, safe_send_telegram
+
+
+def test_compute_macd_hist_monkeypatch(monkeypatch):
+    # Arrange: monkeypatch pandas_ta.macd to return a DataFrame with MACDh column
+    dummy_macd = pd.DataFrame({"MACDh_12_26_9": [None, 0.5, 1.2, 2.3]})
+
+    def fake_macd(series, fast, slow, signal):
+        return dummy_macd
+
+    monkeypatch.setattr(main.ta, "macd", fake_macd)
+
+    close = pd.Series([1, 2, 3, 4])
+
+    # Act: import directly from indicators
+    from src.indicators import compute_macd_hist
+
+    hist = compute_macd_hist(close)
+
+    # Assert
+    assert isinstance(hist, pd.Series)
+    assert list(hist.dropna()) == [0.5, 1.2, 2.3]
+
+
+def test_check_and_notify_positive_sends(monkeypatch):
+    # Prepare a fake OHLCV DataFrame with required OHLCV columns
+    idx = pd.date_range(end=pd.Timestamp.now(), periods=250, freq="h")
+    df = pd.DataFrame(
+        {
+            "open": list(range(100, 350)),
+            "high": list(range(105, 355)),
+            "low": list(range(95, 345)),
+            "close": list(range(100, 350)),
+            "volume": [1000] * 250,
+        },
+        index=idx,
+    )
+
+    # Monkeypatch at the point of use: src.signals imports from indicators
+    from src import signals
+
+    # Patch fetch_ohlcv to return complete OHLCV data
+    monkeypatch.setattr(signals, "fetch_ohlcv", lambda symbol, timeframe, limit=200, log_buffer=None: df)
+
+    # Fake pandas_ta.macd to return MACD crossover (signal cross)
+    def fake_macd(close, fast=12, slow=26, signal=9):
+        macd_df = pd.DataFrame(index=close.index)
+        # Create crossover: prev < signal, curr > signal
+        macd_values = [-0.5] * (len(close) - 1) + [1.5]  # Last value crosses above
+        signal_values = [0.5] * len(close)  # Constant signal line
+        macd_df["MACD_12_26_9"] = pd.Series(macd_values, index=close.index)
+        macd_df["MACDs_12_26_9"] = pd.Series(signal_values, index=close.index)
+        macd_df["MACDh_12_26_9"] = pd.Series([v - s for v, s in zip(macd_values, signal_values)], index=close.index)
+        return macd_df
+
+    monkeypatch.setattr(signals.ta, "macd", fake_macd)
+
+    # Fake pandas_ta.adx to return valid ADX data
+    def fake_adx(high, low, close, length=14):
+        adx_df = pd.DataFrame(index=close.index)
+        adx_df[f"ADX_{length}"] = pd.Series([30.0] * len(close), index=close.index)
+        return adx_df
+
+    monkeypatch.setattr(signals.ta, "adx", fake_adx)
+
+    # Capture calls to safe_send_telegram
+    called = {"count": 0}
+
+    def fake_safe_send(token, chat_id, text, **kwargs):
+        called["count"] += 1
+        return True
+
+    # Monkeypatch test_helpers module
+    from . import test_helpers
+
+    monkeypatch.setattr(test_helpers, "safe_send_telegram", fake_safe_send)
+
+    # Act: call check_and_notify (not dry-run)
+    check_and_notify("upbit", "KRW-BTC", "1h", "token", "chat", limit=10, dry_run=False)
+
+    # Assert: safe_send_telegram was called
+    assert called["count"] == 1