# generated by datamodel-codegen:
#   filename:  potential_assessment_result.json

from __future__ import annotations

from typing import Literal

from pydantic import BaseModel, ConfigDict, Field, RootModel, conint, constr


class Value(RootModel[constr(pattern=r'^-?\d+(\.\d+)?$')]):
    root: constr(pattern=r'^-?\d+(\.\d+)?$')


class AdjustableMw(BaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    interval_minutes: Literal[15]
    date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
    values: list[Value] = Field(..., max_length=96, min_length=96)


class Assessment(BaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    resource_id: constr(min_length=1)
    adjustable_mw: AdjustableMw
    confidence: constr(pattern=r'^-?\d+(\.\d+)?$')
    fulfillment_rate: constr(pattern=r'^-?\d+(\.\d+)?$') | None
    evidence_days: conint(ge=0, le=9007199254740991)


class TotalAdjustableMw(BaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    interval_minutes: Literal[15]
    date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
    values: list[Value] = Field(..., max_length=96, min_length=96)


class PotentialAssessmentResult(BaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    market_date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
    assessments: list[Assessment]
    total_adjustable_mw: TotalAdjustableMw
    skill_version: constr(pattern=r'^\d+\.\d+\.\d+$')