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"""Models for Mongo DB""" |
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from datetime import date, datetime |
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from pathlib import Path |
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from typing import Dict, List, Optional |
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from pydantic import BaseModel, Field |
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class DocumentBaseModel(BaseModel): |
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"""Base model for Mongo documents""" |
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id: str = Field(None, alias="_id") |
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inserted_at: Optional[datetime] |
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updated_at: Optional[datetime] |
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def dict(self, **kwargs) -> Dict: |
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"""Return a dictionary representation of the model""" |
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values = super().dict(**kwargs) |
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if "id" in values and values["id"]: |
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values["_id"] = values["id"] |
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if "exclude" in kwargs and "_id" in kwargs["exclude"]: |
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del values["_id"] |
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return values |
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class CircuitScheduleDoc(BaseModel): |
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"""EVC circuit schedule model""" |
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date: Optional[date] |
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frequency: Optional[str] |
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interval: Optional[int] |
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action: str |
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class TAGDoc(BaseModel): |
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tag_type: int |
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value: int |
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class UNIDoc(BaseModel): |
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"""UNI model""" |
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tag: TAGDoc |
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interface_id: str |
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class EVCBaseDoc(DocumentBaseModel): |
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"""Base model for EVC documents""" |
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uni_a: UNIDoc |
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uni_z: UNIDoc |
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name: str |
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start_date: Optional[datetime] |
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end_date: Optional[datetime] |
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queue_id: Optional[int] |
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bandwidth: int = 0 |
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primary_path: Optional[List] |
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backup_path: Optional[List] |
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current_path: Optional[List] |
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dynamic_backup_path: bool |
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creation_time: datetime |
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owner: Optional[str] |
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priority: int |
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circuit_scheduler: List[CircuitScheduleDoc] |
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archived: bool = False |
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metadata: Optional[Dict] = None |
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active: bool |
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enabled: bool |
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def __init__(self, *args, **kwargs): |
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super().__init__(*args, **kwargs) |
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@staticmethod |
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def projection() -> Dict: |
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"""Base projection of EVCBaseDoc model.""" |
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return { |
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"_id": 0, |
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"id": 1, |
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"uni_a": 1, |
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"uni_z": 1, |
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"name": 1, |
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"start_date": 1, |
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"end_date": 1, |
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"queue_id": 1, |
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"bandwidth": 1, |
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"primary_path": 1, |
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"backup_path": 1, |
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"current_path": 1, |
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"dynamic_backup_path": 1, |
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"creation_time": 1, |
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"owner": 1, |
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"priority": 1, |
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"circuit_scheduler": 1, |
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"archived": 1, |
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"metadata": 1, |
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"active": 1, |
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"enabled": 1, |
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} |