722fd9f054
ShadowDecision already carries the V3.4 5-factor breakdown (base_leverage, dc_lev_mult, regime_size_mult, market_ob_mult, esof_size_mult), but the journal row and CH DDL dropped it — so a DARK soak would record decisions WITHOUT the factor decomposition that V3.4 exists to expose. Thread it through: - 22_violet_decisions.sql: 5 additive Nullable(Float64) breakdown columns. NULL on the legacy base-only path; populated once the launcher feeds live factor planes. Note added: on a pre-existing table use ALTER ... ADD COLUMN instead of the CREATE IF NOT EXISTS (no live table yet — VIOLET is DARK, never soaked). - shadow_journal.py: DecisionRow gains the 5 Optional[float] fields (ge=0.0, finite-guarded); journal() populates them via getattr(..., None) so the base-only path and duck-typed reject tests stay NULL/rejected rather than raising on attribute access. - test_violet_shadow_journal.py: breakdown round-trips on the full path; NULL on base-only; a negative multiplier is rejected at the row guard. The existing DecisionRow-fields == DDL-columns parity test still holds with the new columns. violet-only; no shared-file edits; no soak. 29 violet tests green (7 journal + 22 engine/DDL-apply). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
118 lines
4.4 KiB
Python
118 lines
4.4 KiB
Python
"""V3e: shadow-decision journal — DDL-shape parity, sink emission, reject-at-source."""
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from __future__ import annotations
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import re
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import sys
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from pathlib import Path
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from types import SimpleNamespace
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sys.path.insert(0, "/mnt/dolphinng5_predict")
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from prod.clean_arch.violet.decision_engine import ShadowDecision
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from prod.clean_arch.violet.shadow_journal import DecisionRow, TABLE, VioletDecisionJournal
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DDL = Path("/mnt/dolphinng5_predict/prod/clickhouse/violet/22_violet_decisions.sql")
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def _ddl_columns() -> set:
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body = DDL.read_text()
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inner = body[body.index("("): body.rindex(")")]
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return set(re.findall(r"`(\w+)`", inner))
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def _decision(**over):
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base = dict(
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ts_ns=10**12, scan_number=7, asset="BTCUSDT", side="SHORT", vel_div=-0.2,
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fraction=0.2, conviction_leverage=9.0, notional_fraction=1.8,
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target_exposure=124200.0, ars_score=1.48, bucket_idx=1, actuated=True,
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)
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base.update(over)
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return ShadowDecision(**base)
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def test_decisionrow_fields_equal_ddl_columns():
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assert set(DecisionRow.model_fields.keys()) == _ddl_columns()
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def test_journal_emits_validated_row_to_sink():
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captured = []
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j = VioletDecisionJournal(sink=lambda t, r: captured.append((t, r)), session_id="sess1")
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ok = j.journal(_decision(), mono_ns=999)
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assert ok and j.rows_emitted == 1
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table, row = captured[0]
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assert table == TABLE
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assert set(row.keys()) == _ddl_columns()
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assert row["asset"] == "BTCUSDT" and row["actuated"] == 1
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assert row["session_id"] == "sess1" and row["mono_ns"] == 999
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def test_reject_at_source_on_malformed_decision():
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captured = []
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j = VioletDecisionJournal(sink=lambda t, r: captured.append(r), session_id="s")
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# duck-typed bad decision: non-finite vel_div must be rejected before the sink.
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bad = SimpleNamespace(
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scan_number=1, asset="BTCUSDT", side="SHORT", vel_div=float("nan"),
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fraction=0.2, conviction_leverage=9.0, notional_fraction=1.8,
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target_exposure=1.0, ars_score=1.0, bucket_idx=1, actuated=True,
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)
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ok = j.journal(bad, mono_ns=1)
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assert ok is False
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assert j.rows_rejected == 1 and j.rows_emitted == 0
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assert captured == [] # nothing reached the spool
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def test_negative_exposure_rejected():
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j = VioletDecisionJournal(sink=lambda t, r: None, session_id="s")
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bad = SimpleNamespace(
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scan_number=1, asset="BTCUSDT", side="SHORT", vel_div=-0.2,
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fraction=0.2, conviction_leverage=9.0, notional_fraction=1.8,
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target_exposure=-5.0, ars_score=1.0, bucket_idx=1, actuated=True,
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)
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assert j.journal(bad, mono_ns=1) is False
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assert j.rows_rejected == 1
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_BREAKDOWN_COLS = (
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"base_leverage", "dc_lev_mult", "regime_size_mult",
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"market_ob_mult", "esof_size_mult",
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)
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def test_full_factor_breakdown_round_trips_into_row():
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captured = []
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j = VioletDecisionJournal(sink=lambda t, r: captured.append(r), session_id="s")
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dec = _decision(
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base_leverage=4.0, dc_lev_mult=1.5, regime_size_mult=1.2,
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market_ob_mult=1.4, esof_size_mult=0.95,
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)
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assert j.journal(dec, mono_ns=1) and j.rows_emitted == 1
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row = captured[0]
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assert set(row.keys()) == _ddl_columns() # parity holds with new columns
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assert row["base_leverage"] == 4.0 and row["dc_lev_mult"] == 1.5
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assert row["regime_size_mult"] == 1.2 and row["market_ob_mult"] == 1.4
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assert row["esof_size_mult"] == 0.95
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def test_base_only_path_leaves_breakdown_null():
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captured = []
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j = VioletDecisionJournal(sink=lambda t, r: captured.append(r), session_id="s")
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assert j.journal(_decision(), mono_ns=1) # no breakdown supplied
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row = captured[0]
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assert all(row[c] is None for c in _BREAKDOWN_COLS)
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def test_negative_breakdown_multiplier_rejected_at_source():
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j = VioletDecisionJournal(sink=lambda t, r: None, session_id="s")
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# ShadowDecision itself guards ge=0.0, so build a duck-typed decision that
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# smuggles a negative multiplier past the engine to prove the row guard catches it.
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bad = SimpleNamespace(
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scan_number=1, asset="BTCUSDT", side="SHORT", vel_div=-0.2,
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fraction=0.2, conviction_leverage=9.0, notional_fraction=1.8,
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target_exposure=1.0, ars_score=1.0, bucket_idx=1, actuated=True,
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base_leverage=4.0, dc_lev_mult=-0.5, regime_size_mult=1.0,
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market_ob_mult=1.0, esof_size_mult=1.0,
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)
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assert j.journal(bad, mono_ns=1) is False
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assert j.rows_rejected == 1
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