Daniel Sapkota
65 lines
2.1 KiB
Python
65 lines
2.1 KiB
Python
"""Pure reconciliation: desired TargetQuotes vs live orders -> minimal actions.
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The strategy emits a target quote set; this computes the smallest cancel/place
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set to reach it, applying churn tolerances so we don't burn queue position for
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sub-tick or sub-threshold size changes (v1's should_cancel instinct, generalized).
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No I/O — the gateway executes the returned plan.
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"""
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from __future__ import annotations
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from collections import defaultdict
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from dataclasses import dataclass, field
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from polymaker.domain import OpenOrder, Quote, TargetQuotes
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_EPS = 1e-9
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@dataclass(frozen=True, slots=True)
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class ReconcilePlan:
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to_cancel: list[str] = field(default_factory=list) # order ids
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to_place: list[Quote] = field(default_factory=list)
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@property
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def is_noop(self) -> bool:
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return not self.to_cancel and not self.to_place
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def reconcile(
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targets: TargetQuotes,
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live: list[OpenOrder],
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*,
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tick: float,
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reprice_ticks: int,
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resize_frac: float,
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) -> ReconcilePlan:
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"""Diff targets against live orders. Keep live orders that already satisfy a
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target within tolerance; cancel the rest; place targets with no match."""
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live_by_key: dict[tuple[str, str], list[OpenOrder]] = defaultdict(list)
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for o in live:
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live_by_key[(o.token_id, o.side.value)].append(o)
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keep: set[str] = set()
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to_place: list[Quote] = []
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price_tol = reprice_ticks * tick + _EPS
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for q in targets.quotes:
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candidates = live_by_key.get((q.token_id, q.side.value), [])
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match: OpenOrder | None = None
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for o in candidates:
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if o.order_id in keep:
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continue
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price_close = abs(o.price - q.price) <= price_tol
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size_close = q.size <= 0 or abs(o.size - q.size) <= resize_frac * q.size + _EPS
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if price_close and size_close:
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match = o
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break
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if match is not None:
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keep.add(match.order_id)
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else:
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to_place.append(q)
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to_cancel = [o.order_id for o in live if o.order_id not in keep]
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return ReconcilePlan(to_cancel=to_cancel, to_place=to_place)
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