feat(protocol): AST compiler to (df -> Series[Side]) signal fn
Implementa compile_strategy che produce funzione df -> Series[Side] con valutazione regole in ordine, prima-che-matcha vince, FLAT default e NaN per warmup degli indicatori. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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from __future__ import annotations
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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 multi_swarm.backtest.orders import Side
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from multi_swarm.protocol.compiler import compile_strategy
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from multi_swarm.protocol.parser import parse_strategy
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@pytest.fixture
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def ohlcv() -> pd.DataFrame:
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idx = pd.date_range("2024-01-01", periods=200, freq="1h", tz="UTC")
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close = np.linspace(100, 120, 200)
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return pd.DataFrame(
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{
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"open": close,
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"high": close + 0.5,
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"low": close - 0.5,
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"close": close,
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"volume": 1.0,
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},
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index=idx,
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)
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def test_compile_simple_long(ohlcv: pd.DataFrame) -> None:
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src = "(strategy (when (lt (indicator rsi 14) 100.0) (entry-long)))"
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ast = parse_strategy(src)
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fn = compile_strategy(ast)
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signals = fn(ohlcv)
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assert isinstance(signals, pd.Series)
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assert (signals == Side.LONG).all() or (signals.dropna() == Side.LONG).all()
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def test_compile_no_match_is_flat(ohlcv: pd.DataFrame) -> None:
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src = "(strategy (when (gt (indicator rsi 14) 1000.0) (entry-long)))"
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ast = parse_strategy(src)
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fn = compile_strategy(ast)
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signals = fn(ohlcv)
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assert (signals == Side.FLAT).any()
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def test_compile_two_rules_priority(ohlcv: pd.DataFrame) -> None:
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src = """
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(strategy
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(when (gt (feature close) 110.0) (entry-long))
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(when (lt (feature close) 105.0) (entry-short)))
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"""
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ast = parse_strategy(src)
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fn = compile_strategy(ast)
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signals = fn(ohlcv)
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last = signals.iloc[-1]
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assert last == Side.LONG # close finale e' 120, regola 1 matcha
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