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