16fdc43650
application/fleet: Territory (a hunter's mandate: family x universe x param grid) + FleetOrchestrator — searches each territory, evaluates every candidate REGIME-conditionally (layer 1), writes the regime- specialists it finds to the lifecycle store (layer 2) with honest global trial accounting. CLI hunt. Hunters sequential now (local GPU serializes), interface ready for concurrent/agent-proposed later. Live on cached futures: 2 hunters, 18 candidates -> 3 specialists (NQ trend in trend_up|low_vol; GC mean_reversion in trend_down|high_vol — a non-trend specialist the full sample would miss). 20/20 tests. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
38 lines
1.9 KiB
Python
38 lines
1.9 KiB
Python
"""Fleet orchestrator: a hunter searches a territory, evaluates regime-conditionally, and persists the
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regime-specialists it finds — with honest global trial accounting."""
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from __future__ import annotations
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import numpy as np
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from fxhnt.adapters.persistence import DuckDbAnalyticalStore, SqlStrategyStore
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from fxhnt.application import FleetOrchestrator, Territory
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from fxhnt.config import Settings
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from fxhnt.domain.models import AssetClass, Market, PriceSeries
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class FakeData:
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name = "fake"
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def fetch(self, market: Market, start=None, end=None) -> PriceSeries:
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rng = np.random.default_rng(sum(ord(c) for c in market.symbol)) # deterministic, uncorrelated
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close = 100.0 * np.cumprod(1.0 + rng.normal(0.001, 0.01, 1600)) # steady uptrend -> trend specialist
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return PriceSeries(market=market, dates=tuple(str(i) for i in range(1600)), close=close)
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def test_fleet_finds_persists_specialist_and_counts_trials(tmp_path) -> None:
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settings = Settings(analytical_path=str(tmp_path / "an.duckdb"), operational_dsn=f"sqlite:///{tmp_path / 'f.db'}")
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store = SqlStrategyStore(settings.operational_dsn)
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fleet = FleetOrchestrator(FakeData(), DuckDbAnalyticalStore(settings.analytical_path), store, settings)
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territories = [Territory(name="trend-hunter", kind="trend", markets=["AAA", "BBB"],
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asset_class=AssetClass.FUTURE, param_grid=[{"window": 100.0}])]
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report = fleet.hunt(territories)
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assert report.candidates_tested == 2
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assert report.global_trials == 2 # honest accounting
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assert report.specialists_found >= 1 # a steady uptrend yields a trend specialist
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saved = store.list()
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assert saved and saved[0].spec.kind == "trend"
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assert saved[0].specialist_regimes() # tagged with the regime(s) it works in
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assert any("trend_up" in r for r in saved[0].specialist_regimes())
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