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| """ | |
| Unit tests for core.analysis.technical | |
| """ | |
| import numpy as np | |
| import pandas as pd | |
| import pytest | |
| from core.analysis.technical import add_indicators, get_signals, signal_summary | |
| def sample_ohlcv() -> pd.DataFrame: | |
| """Generate 250 rows of synthetic OHLCV data.""" | |
| rng = np.random.default_rng(42) | |
| n = 250 | |
| close = 100 + np.cumsum(rng.normal(0, 1, n)) | |
| high = close + rng.uniform(0.5, 2.0, n) | |
| low = close - rng.uniform(0.5, 2.0, n) | |
| open_ = close + rng.normal(0, 0.5, n) | |
| vol = rng.integers(1_000_000, 10_000_000, n).astype(float) | |
| dates = pd.date_range("2024-01-01", periods=n, freq="B") | |
| return pd.DataFrame( | |
| {"Open": open_, "High": high, "Low": low, "Close": close, "Volume": vol}, | |
| index=dates, | |
| ) | |
| class TestAddIndicators: | |
| def test_returns_dataframe(self, sample_ohlcv): | |
| result = add_indicators(sample_ohlcv) | |
| assert isinstance(result, pd.DataFrame) | |
| def test_does_not_mutate_input(self, sample_ohlcv): | |
| original_cols = list(sample_ohlcv.columns) | |
| add_indicators(sample_ohlcv) | |
| assert list(sample_ohlcv.columns) == original_cols | |
| def test_expected_columns_present(self, sample_ohlcv): | |
| df = add_indicators(sample_ohlcv) | |
| expected = [ | |
| "sma_20", "sma_50", "sma_200", | |
| "ema_12", "ema_26", | |
| "macd", "macd_signal", "macd_hist", | |
| "rsi_14", | |
| "bb_upper", "bb_middle", "bb_lower", "bb_pct", | |
| "atr_14", | |
| "vol_sma_20", | |
| ] | |
| for col in expected: | |
| assert col in df.columns, f"Missing column: {col}" | |
| def test_rsi_bounds(self, sample_ohlcv): | |
| df = add_indicators(sample_ohlcv) | |
| rsi = df["rsi_14"].dropna() | |
| assert (rsi >= 0).all() and (rsi <= 100).all() | |
| class TestGetSignals: | |
| def test_returns_dict(self, sample_ohlcv): | |
| df = add_indicators(sample_ohlcv) | |
| signals = get_signals(df) | |
| assert isinstance(signals, dict) | |
| def test_valid_values(self, sample_ohlcv): | |
| df = add_indicators(sample_ohlcv) | |
| valid = {"BULLISH", "BEARISH", "NEUTRAL"} | |
| for k, v in get_signals(df).items(): | |
| assert v in valid, f"Signal '{k}' has invalid value '{v}'" | |
| def test_empty_dataframe(self): | |
| assert get_signals(pd.DataFrame()) == {} | |
| class TestSignalSummary: | |
| def test_bullish_majority(self): | |
| signals = {"A": "BULLISH", "B": "BULLISH", "C": "BEARISH"} | |
| assert signal_summary(signals) == "BULLISH" | |
| def test_bearish_majority(self): | |
| signals = {"A": "BEARISH", "B": "BEARISH", "C": "BULLISH"} | |
| assert signal_summary(signals) == "BEARISH" | |
| def test_tie_returns_mixed(self): | |
| signals = {"A": "BULLISH", "B": "BEARISH"} | |
| assert signal_summary(signals) == "MIXED" | |
| def test_empty_returns_neutral(self): | |
| assert signal_summary({}) == "NEUTRAL" | |