from typing import Optional
from pydantic import BaseModel, ConfigDict, Field


class DriftCalRow(BaseModel):
    sample_id: str
    scenario_id: str
    split: str
    shift_type: str = Field(description="none|covariate|label|concept|novel_class|adversarial")
    shift_magnitude: float
    difficulty: str = Field(description="easy|medium|hard|expert")
    label_binary: int = Field(ge=0, le=1)
    label_family: str
    family_id: int
    family_is_novel: bool
    perturbation_applied: bool
    perturbation_budget: float
    spurious_shuffled: bool = Field(
        description="True only in the spurious_ablation eval, where spurious "
        "feature columns have been permuted across rows to break their "
        "correlation with the label"
    )
    generator_seed: int
    timestamp_synth: int
    provenance: str = "synthetic:driftcal-v0.1-validation"
    qc_status: str = "unchecked"
    # feature_* columns are validated separately (70 numeric columns) rather
    # than declared individually here to keep the schema readable; see
    # DATASET_SCHEMA.md for the full per-feature-block description.

    model_config = ConfigDict(extra="allow")