Initial release: TradeMind crypto trading bot with paper/live modes and strategy training

tests/test_trademind.py

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+"""Smoke-Tests für TradeMind (ohne Netzwerk & ohne echte Keys)."""
+import numpy as np
+import pandas as pd
+import pytest
+
+from trademind.config import Config, StrategyConfig, TradingConfig, TrainingConfig
+from trademind.strategy import Strategy
+from trademind.engine import Engine
+from trademind.trader import Trader
+from trademind.exchange import MockBroker, CcxtBroker
+from trademind.trainer import Trainer, eval_params, random_params
+
+
+@pytest.fixture
+def cfg() -> Config:
+    return Config(
+        trading=TradingConfig(),
+        strategy=StrategyConfig(),
+        training=TrainingConfig(generations=3, population=6),
+        exchanges={},
+    )
+
+
+@pytest.fixture
+def candles() -> pd.DataFrame:
+    rng = np.random.default_rng(0)
+    n = 300
+    close = 50_000 + np.cumsum(rng.standard_normal(n) * 500)
+    open_ = np.roll(close, 1)
+    open_[0] = 50_000
+    spread = np.abs(rng.standard_normal(n)) * 100 + 5
+    high = np.maximum(open_, close) + spread
+    low = np.minimum(open_, close) - spread
+    idx = pd.date_range(end=pd.Timestamp.utcnow().floor("h"), periods=n, freq="h")
+    return pd.DataFrame(
+        {"time": idx, "open": open_, "high": high, "low": low, "close": close,
+         "volume": rng.uniform(10, 100, n)}
+    )
+
+
+def test_strategy_prepare_and_decide(cfg, candles):
+    st = Strategy(cfg.strategy)
+    prep = st.prepare(candles)
+    assert all(k in prep for k in ("ema_fast", "ema_slow", "rsi", "atr"))
+    sigs = st.decide(prep)
+    assert len(sigs) == len(candles)
+    assert sigs[-1].price > 0
+
+
+def test_engine_run_produces_result(cfg, candles):
+    st = Strategy(cfg.strategy)
+    eng = Engine(cfg.trading, st)
+    res = eng.run(candles)
+    assert res.final_equity > 0
+    assert isinstance(res.summary().get("num_trades"), int)
+    assert res.equity_curve[0] > 0
+
+
+def test_paper_trader_roundtrip(cfg, candles):
+    broker = MockBroker(seed=1)
+    st = Strategy(cfg.strategy)
+    tr = Trader(cfg, broker, st)
+    res = tr.simulate()
+    assert res.final_equity >= 0
+    assert res.num_trades >= 0
+
+
+def test_trainer_improves_and_sets_weights(cfg, candles):
+    base = Strategy(cfg.strategy)
+    trainer = Trainer(cfg.training, base)
+    p0 = random_params(__import__("random").Random(1))
+    before = eval_params(p0, candles, cfg.trading, base, cfg.training)
+    best = trainer.train(candles, cfg.trading, base)
+    # after: best should be >= before (elitism guarantees)
+    after = eval_params(best, candles, cfg.trading, base, cfg.training)
+    assert after >= before - 1e-6
+
+
+def test_data_broker_falls_back_to_mock(cfg):
+    """Ohne Netzwerk/Exchange muss der Fallback auf Mock-Daten greifen."""
+    from trademind.cli import _data_broker
+
+    broker = _data_broker(cfg, data="auto", exchange="binance", seed=3)
+    df = broker.fetch_ohlcv("BTC/USDT", "1h", 50)
+    assert len(df) == 50
+    for col in ("open", "high", "low", "close"):
+        assert (df[col] > 0).all()
+
+
+def test_mock_broker_deterministic():
+    b1 = MockBroker(seed=3).fetch_ohlcv("BTC/USDT", "1h", 100)
+    b2 = MockBroker(seed=3).fetch_ohlcv("BTC/USDT", "1h", 100)
+    assert b1.equals(b2)
+
+
+def test_strategy_set_parameter(cfg):
+    st = Strategy(cfg.strategy)
+    p = st.parameters()
+    assert "fast_period" in p and "w_ema_cross" in p
+    st.set_parameter("fast_period", 20)
+    assert st.cfg.fast_period == 20
+    st.set_parameter("w_ema_cross", 1.5)
+    assert st.weights["ema_cross"] == pytest.approx(1.5)