feat: add technical indicator calculation (30 indicators via MyTT), bump to 1.4.0

Integrate MyTT library to provide 30 technical indicators (MACD, KDJ, RSI,
BOLL, DMI, ATR, etc.) accessible via API and CLI with automatic EMA warm-up.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

tests/unit/test_indicator.py

@@ -0,0 +1,158 @@
+"""indicator.py 离线单元测试。"""
+
+from __future__ import annotations
+
+import warnings
+
+import numpy as np
+import pandas as pd
+import pytest
+
+from easy_tdx.indicator import compute_indicators, list_indicators, _REGISTRY
+
+
+def _make_ohlcv(n: int = 200, seed: int = 42) -> pd.DataFrame:
+    rng = np.random.default_rng(seed)
+    close = 100 + np.cumsum(rng.standard_normal(n) * 0.5)
+    high = close + np.abs(rng.standard_normal(n))
+    low = close - np.abs(rng.standard_normal(n))
+    open_ = low + (high - low) * rng.random(n)
+    vol = (rng.random(n) * 1e6).astype(float)
+    return pd.DataFrame({
+        "datetime": pd.date_range("2024-01-01", periods=n, freq="D"),
+        "open": open_,
+        "high": high,
+        "low": low,
+        "close": close,
+        "vol": vol,
+        "amount": vol * close,
+    })
+
+
+class TestRegistry:
+    def test_all_indicators_registered(self):
+        assert len(_REGISTRY) >= 22
+
+    def test_list_indicators_returns_metadata(self):
+        info = list_indicators()
+        assert len(info) >= 22
+        for entry in info:
+            assert "name" in entry
+            assert "inputs" in entry
+            assert "outputs" in entry
+            assert "description" in entry
+
+
+class TestComputeIndicators:
+    def test_single_indicator_macd(self):
+        df = _make_ohlcv()
+        result = compute_indicators(df, ["MACD"])
+        assert "MACD_DIF" in result.columns
+        assert "MACD_DEA" in result.columns
+        assert "MACD_HIST" in result.columns
+        assert len(result) == 200
+
+    def test_multiple_indicators(self):
+        df = _make_ohlcv()
+        result = compute_indicators(df, ["MACD", "KDJ", "RSI"])
+        for col in ["MACD_DIF", "MACD_DEA", "MACD_HIST", "KDJ_K", "KDJ_D", "KDJ_J", "RSI"]:
+            assert col in result.columns
+
+    def test_keep_ohlcv_true(self):
+        df = _make_ohlcv()
+        result = compute_indicators(df, ["RSI"], keep_ohlcv=True)
+        for col in ["open", "high", "low", "close", "vol"]:
+            assert col in result.columns
+
+    def test_keep_ohlcv_false(self):
+        df = _make_ohlcv()
+        result = compute_indicators(df, ["RSI"], keep_ohlcv=False)
+        assert "close" not in result.columns
+        assert "RSI" in result.columns
+        # datetime 应保留
+        assert "datetime" in result.columns
+
+    def test_keep_ohlcv_false_no_time_cols(self):
+        df = _make_ohlcv()
+        df = df.drop(columns=["datetime"])
+        result = compute_indicators(df, ["RSI"], keep_ohlcv=False)
+        assert "close" not in result.columns
+        assert "RSI" in result.columns
+
+    def test_tail_parameter(self):
+        df = _make_ohlcv(200)
+        result = compute_indicators(df, ["MACD"], tail=30)
+        assert len(result) == 30
+        assert "MACD_DIF" in result.columns
+
+    def test_case_insensitive(self):
+        df = _make_ohlcv()
+        result = compute_indicators(df, ["macd", "kdj"])
+        assert "MACD_DIF" in result.columns
+        assert "KDJ_K" in result.columns
+
+    def test_custom_params(self):
+        df = _make_ohlcv()
+        r1 = compute_indicators(df, ["MACD"])
+        r2 = compute_indicators(df, ["MACD"], params={"MACD": {"SHORT": 10}})
+        # 不同参数应产生不同结果
+        assert not np.allclose(r1["MACD_DIF"].values, r2["MACD_DIF"].values, equal_nan=True)
+
+    def test_unknown_indicator_raises(self):
+        df = _make_ohlcv()
+        with pytest.raises(ValueError, match="未知指标"):
+            compute_indicators(df, ["FAKE_INDICATOR"])
+
+    def test_missing_input_columns_raises(self):
+        df = pd.DataFrame({"close": np.random.randn(200)})
+        with pytest.raises(ValueError, match="缺少必要列"):
+            compute_indicators(df, ["KDJ"])
+
+    def test_empty_dataframe(self):
+        df = pd.DataFrame()
+        result = compute_indicators(df, ["MACD"])
+        assert result.empty
+
+    def test_short_data_warning(self):
+        df = _make_ohlcv(50)
+        with warnings.catch_warnings(record=True) as w:
+            warnings.simplefilter("always")
+            compute_indicators(df, ["MACD"])
+            assert any("120" in str(warning.message) for warning in w)
+
+    def test_rsi_range(self):
+        df = _make_ohlcv(200)
+        result = compute_indicators(df, ["RSI"])
+        rsi = result["RSI"].dropna()
+        assert (rsi >= -10).all() and (rsi <= 110).all()
+
+    def test_boll_bands_order(self):
+        df = _make_ohlcv(200)
+        result = compute_indicators(df, ["BOLL"])
+        valid = result.dropna(subset=["BOLL_UPPER", "BOLL_LOWER"])
+        assert (valid["BOLL_UPPER"] >= valid["BOLL_LOWER"]).all()
+
+    def test_obv_with_volume(self):
+        df = _make_ohlcv()
+        result = compute_indicators(df, ["OBV"])
+        assert "OBV" in result.columns
+
+    def test_brar_needs_open(self):
+        df = _make_ohlcv()
+        result = compute_indicators(df, ["BRAR"])
+        assert "AR" in result.columns
+        assert "BR" in result.columns
+
+    def test_all_registered_indicators_run(self):
+        """确保所有注册的指标都能无错运行。"""
+        df = _make_ohlcv(250)
+        for name in _REGISTRY:
+            result = compute_indicators(df, [name])
+            spec = _REGISTRY[name]
+            for col in spec.outputs:
+                assert col in result.columns, f"{name} missing output {col}"
+
+    def test_result_index_reset(self):
+        df = _make_ohlcv()
+        result = compute_indicators(df, ["RSI"])
+        assert list(result.index) == list(range(len(result)))