d24d9bc6bd
CRITICAL REFACTOR based on Fable's review (S9 roadmap item):
Before: flat enum conflating order types with TIF/instructions
OrderType had MARKET, LIMIT, IOC, FOK, POST_ONLY, REDUCE_ONLY, etc.
After: three orthogonal dimensions (FIX-aligned):
1. OrderType (Tag 40): what the order IS
LIMIT, MARKET, STOP_MARKET, STOP_LIMIT, TRIGGER_MARKET, TRIGGER_LIMIT,
TRAILING_STOP, OCO, TP_SL
2. TimeInForce (Tag 59): how long it LIVES
GTC, IOC, FOK, GTD
3. Instructions (Tag 18): behavioral modifiers
POST_ONLY, REDUCE_ONLY, HIDDEN, ICEBERG
Key corrections:
- POST_ONLY is an instruction on a LIMIT order, not a standalone type
- IOC/FOK are TimeInForce values, not order types
- BingX trailing_stop -> native TRAILING_STOP_MARKET (not TRIGGER_MARKET)
- FulfilmentAction.time_in_force: new field, default GTC
Exchange mappings restructured:
EXCHANGE_ORDER_TYPE_MAP: OrderType -> exchange native 'type' param
EXCHANGE_TIF_MAP: TimeInForce -> exchange native 'timeInForce' param
EXCHANGE_INSTRUCTION_MAP: Instruction -> exchange encoding
21 files changed. 380+ tests pass. Backward compatible.
76 lines
2.1 KiB
Python
76 lines
2.1 KiB
Python
"""
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Action model — compact menu for simultaneous-move tree search.
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Bad: enumerate every price tick x every quantity x every TTL x every TIF.
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Good: 8-24 meaningful actions per player, 3-12 per counterparty role.
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"""
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Any, Mapping, Optional, Tuple
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from malkhut.state import ActionKind, AgentRole, OrderType, Side
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# Lazy import to avoid circular dependency (training -> actions -> training)
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_TimeInForce = None
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def _get_TimeInForce():
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global _TimeInForce
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if _TimeInForce is None:
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from malkhut.training.order_types import TimeInForce
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_TimeInForce = TimeInForce
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return _TimeInForce
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@dataclass(frozen=True, slots=True)
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class FulfilmentAction:
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"""One atomic action candidate."""
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kind: ActionKind
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side: Optional[Side]
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order_type: Optional[OrderType]
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price_ticks_from_best: int
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qty_fraction: float
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ttl_ms: int
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cancel_order_id: Optional[str] = None
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reduce_only: bool = False
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post_only: bool = False
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time_in_force: str = "GTC"
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metadata: Mapping[str, Any] = field(default_factory=dict)
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@property
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def time_in_force_enum(self):
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TIF = _get_TimeInForce()
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return TIF(self.time_in_force)
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@dataclass(frozen=True, slots=True)
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class CounterpartyAction:
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"""Adversarially useful aggregate actions that alter book/fill outcomes."""
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role: AgentRole
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kind: ActionKind
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side: Optional[Side]
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price_ticks_from_best: int
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qty_fraction_of_top: float
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toxicity: float = 0.0
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metadata: Mapping[str, Any] = field(default_factory=dict)
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JointAction = Tuple[Any, ...] # (our_action, cp_action_1, cp_action_2, ...)
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@dataclass(frozen=True, slots=True)
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class PlannedPolicy:
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"""Output of the planner: distribution over actions + selected action."""
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actions: Tuple[FulfilmentAction, ...]
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probabilities: Tuple[float, ...]
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selected_action: FulfilmentAction
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diagnostics: Mapping[str, Any]
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@dataclass(frozen=True, slots=True)
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class RiskDecision:
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approved: bool
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action: Optional[FulfilmentAction]
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reason: str
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adjusted: bool = False
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