52 lines
1.4 KiB
Python
52 lines
1.4 KiB
Python
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# generated by datamodel-codegen:
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# filename: potential_assessment_result.json
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from __future__ import annotations
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from typing import Literal
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from pydantic import BaseModel, ConfigDict, Field, RootModel, conint, constr
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class Value(RootModel[constr(pattern=r'^-?\d+(\.\d+)?$')]):
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root: constr(pattern=r'^-?\d+(\.\d+)?$')
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class AdjustableMw(BaseModel):
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model_config = ConfigDict(
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extra='forbid',
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)
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interval_minutes: Literal[15]
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date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
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values: list[Value] = Field(..., max_length=96, min_length=96)
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class Assessment(BaseModel):
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model_config = ConfigDict(
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extra='forbid',
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)
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resource_id: constr(min_length=1)
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adjustable_mw: AdjustableMw
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confidence: constr(pattern=r'^-?\d+(\.\d+)?$')
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fulfillment_rate: constr(pattern=r'^-?\d+(\.\d+)?$') | None
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evidence_days: conint(ge=0, le=9007199254740991)
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class TotalAdjustableMw(BaseModel):
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model_config = ConfigDict(
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extra='forbid',
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)
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interval_minutes: Literal[15]
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date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
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values: list[Value] = Field(..., max_length=96, min_length=96)
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class PotentialAssessmentResult(BaseModel):
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model_config = ConfigDict(
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extra='forbid',
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)
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market_date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
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assessments: list[Assessment]
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total_adjustable_mw: TotalAdjustableMw
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skill_version: constr(pattern=r'^\d+\.\d+\.\d+$')
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