"""Fixed, typed inputs shared by HTTP, AI and research producers.""" import hashlib import json from typing import Literal from pydantic import ConfigDict, Field, field_validator, model_validator from ..preparations.contracts import PreparationReference from ..schemas import Contract class SimulationSettings(Contract): instrumentType: Literal["EQUITY"] = "EQUITY" region: str = Field(min_length=1, max_length=50, pattern=r"^[A-Z0-9_]+$") universe: str = Field(min_length=1, max_length=100, pattern=r"^[A-Z0-9_]+$") delay: Literal[0, 1] decay: int = Field(default=0, ge=0, le=10000) neutralization: str = Field(default="INDUSTRY", min_length=1, max_length=50, pattern=r"^[A-Z_]+$") truncation: float = Field(default=0.08, ge=0, le=1) pasteurization: Literal["ON", "OFF"] = "ON" unitHandling: Literal["VERIFY"] = "VERIFY" nanHandling: Literal["ON", "OFF"] = "OFF" language: Literal["FASTEXPR"] = "FASTEXPR" visualization: bool = False maxTrade: Literal["ON", "OFF"] = "OFF" maxPosition: Literal["ON", "OFF"] = "OFF" class SuperSimulationSettings(SimulationSettings): """SUPER-only selection settings; platform metadata still determines availability.""" selectionHandling: Literal["POSITIVE", "NON_ZERO", "NON_NAN"] selectionLimit: int = Field(ge=1, le=100000, strict=True) componentActivation: Literal["IS", "OS"] class Candidate(Contract): client_item_id: str = Field(min_length=1, max_length=100) expression: str = Field(default="", max_length=20000) selection: str | None = Field(default=None, max_length=20000) combo: str | None = Field(default=None, max_length=20000) settings: SuperSimulationSettings | SimulationSettings alpha_type: Literal["REGULAR", "SUPER"] = "REGULAR" @field_validator("expression", "selection", "combo") @classmethod def nonempty(cls, value): return value.strip() if value is not None else None @model_validator(mode="after") def typed_input(self): if self.alpha_type == "SUPER": if self.expression or not self.selection or not self.combo: raise ValueError("SUPER 必须提供非空 selection/combo，不能提供 regular expression") if not isinstance(self.settings, SuperSimulationSettings): raise ValueError("SUPER 必须提供 selectionHandling、selectionLimit、componentActivation") elif not self.expression or self.selection is not None or self.combo is not None or isinstance(self.settings, SuperSimulationSettings): raise ValueError("REGULAR 必须提供非空 expression，不能包含 SUPER 表达式或设置") return self def platform_input(self): if self.alpha_type == "SUPER": return {"type": "SUPER", "selection": self.selection, "combo": self.combo, "settings": self.settings.model_dump()} return {"type": self.alpha_type, "regular": self.expression, "settings": self.settings.model_dump()} class Source(Contract): research_kind: str | None = Field(default=None, max_length=50) kind: str = Field(default="manual", min_length=1, max_length=100) reference: str | None = Field(default=None, max_length=200) batch_id: str | None = Field(default=None, max_length=200) input_snapshot_ids: list[str] = Field(default_factory=list, max_length=100) input_snapshot_id: str | None = Field(default=None, max_length=200) research_id: str | None = Field(default=None, max_length=200) parent_run_id: str | None = Field(default=None, max_length=36) hypothesis: str | None = Field(default=None, max_length=2000) superalpha_plan_id: str | None = Field(default=None, max_length=36) superalpha_plan_version: int | None = Field(default=None, ge=1) selection_snapshot_ids: list[str] = Field(default_factory=list, max_length=100) class SourceOutput(Source): """Project stored metadata onto the public source fields; input remains strict. Removed or internal keys are never returned or converted to snapshot references. Known fields still undergo normal validation. """ model_config = ConfigDict(extra="ignore") class DraftInput(Contract): preparation_refs: list[PreparationReference] = Field(default_factory=list, max_length=20) input_ids: list[str] = Field(default_factory=list, max_length=20) name: str = Field(min_length=1, max_length=200) source: Source = Field(default_factory=Source) candidates: list[Candidate] = Field(min_length=1, max_length=10000) @model_validator(mode="after") def unique_ids(self): if len({c.client_item_id for c in self.candidates}) != len(self.candidates): raise ValueError("client_item_id 在候选集合内必须唯一") return self class DraftUpdate(DraftInput): version: int = Field(ge=1) class PreviewInput(Contract): draft_id: str | None = Field(default=None, max_length=36) draft_version: int | None = Field(default=None, ge=1) selection: list[str] | None = Field(default=None, min_length=1, max_length=10000) inline: DraftInput | None = None @model_validator(mode="after") def one_input(self): if (self.inline is None) == (self.draft_id is None): raise ValueError("必须提供 inline 或 draft_id 之一") if self.draft_id and self.draft_version is None: raise ValueError("引用草稿时必须提供 draft_version") if self.inline and (self.draft_version is not None or self.selection is not None): raise ValueError("inline 已经是完整固定集合") return self class StartInput(Contract): preview_id: str = Field(min_length=1, max_length=36) version: int = Field(default=1, ge=1) idempotency_key: str = Field(min_length=1, max_length=100) class ControlInput(Contract): action: Literal["pause", "resume", "stop", "recover"] version: int = Field(ge=1) class RerunInput(Contract): item_ids: list[str] = Field(min_length=1, max_length=10000) class SchedulerInput(Contract): concurrency: int = Field(default=3, ge=1, le=8) batch_size: int = Field(default=8, ge=1, le=10) version: int = Field(ge=1) def fingerprint(payload: dict) -> str: return hashlib.sha256(json.dumps(payload, sort_keys=True, separators=(",", ":")).encode()).hexdigest() def group_key(candidate: dict): settings = candidate["settings"] return (candidate.get("alpha_type", "REGULAR"), *tuple(settings[k] for k in ("region", "delay", "language", "instrumentType"))) class ReferenceInput(Contract): progress_url: str = Field(min_length=1, max_length=2000) version: int = Field(ge=1) class SubsetInput(Contract): exclude_ids: list[str] = Field(min_length=1, max_length=10000) # OpenAPI outputs deliberately keep platform snapshots as extensible objects. class SchedulerOutput(Contract): concurrency: int batch_size: int version: int blocked_reason: str | None blocked_until: str | None class PreviewOutput(Contract): preview_id: str version: int name: str source: SourceOutput digest: str total: int batch_count: int batch_size: int duplicate_count: int duplicates: list[dict] items: list[Candidate] limit: int offset: int has_more: bool created_at: str class RunOutput(Contract): backtest_run_id: str preview_id: str name: str source: SourceOutput ai_context: dict control: Literal["active", "paused", "stopped"] status: str version: int total: int batch_size: int created_at: str updated_at: str counts: dict[str, dict[str, int]] cursor: int scheduler: SchedulerOutput class RunPage(Contract): items: list[RunOutput] total: int limit: int offset: int class ResultSnapshot(Contract): snapshot: dict observed_at: str complete: bool class ItemOutput(Contract): id: str client_item_id: str expression: str alpha_type: Literal["REGULAR", "SUPER"] = "REGULAR" selection: str | None = None combo: str | None = None settings: SuperSimulationSettings | SimulationSettings attempt_id: str platform_status: str collection_status: str persistence_status: str simulation_id: str | None alpha_id: str | None error: str | None result: ResultSnapshot | None class ResultPage(Contract): backtest_run_id: str total: int limit: int offset: int items: list[ItemOutput] class EventOutput(Contract): seq: int kind: str payload: dict created_at: str class EventPage(Contract): items: list[EventOutput] next_cursor: int has_more: bool