vpp-ai-platform/skills-py/vpp_contracts/dispatch_optimization_result.py

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

from __future__ import annotations

from enum import StrEnum
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 TotalTargetMw(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 TargetMw(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 Allocation(BaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    unit_id: constr(min_length=1)
    target_mw: TargetMw


class Status(StrEnum):
    OPTIMAL = 'OPTIMAL'
    INFEASIBLE = 'INFEASIBLE'
    ERROR = 'ERROR'


class Solver(BaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    name: constr(min_length=1)
    version: constr(min_length=1)
    status: Status
    wall_time_ms: conint(ge=0, le=9007199254740991)


class DispatchOptimizationResult(BaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    market_date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
    total_target_mw: TotalTargetMw
    allocations: list[Allocation] = Field(..., min_length=1)
    shortfall_mwh: constr(pattern=r'^-?\d+(\.\d+)?$')
    solver: Solver
    skill_version: constr(pattern=r'^\d+\.\d+\.\d+$')