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Queue Statistics Dto

immichpy.client.generated.models.queue_statistics_dto.QueueStatisticsDto pydantic-model

Bases: BaseModel

QueueStatisticsDto

Show JSON schema: 
{
  "description": "QueueStatisticsDto",
  "properties": {
    "active": {
      "description": "Number of active jobs",
      "maximum": 9007199254740991,
      "minimum": -9007199254740991,
      "title": "Active",
      "type": "integer"
    },
    "completed": {
      "description": "Number of completed jobs",
      "maximum": 9007199254740991,
      "minimum": -9007199254740991,
      "title": "Completed",
      "type": "integer"
    },
    "delayed": {
      "description": "Number of delayed jobs",
      "maximum": 9007199254740991,
      "minimum": -9007199254740991,
      "title": "Delayed",
      "type": "integer"
    },
    "failed": {
      "description": "Number of failed jobs",
      "maximum": 9007199254740991,
      "minimum": -9007199254740991,
      "title": "Failed",
      "type": "integer"
    },
    "paused": {
      "description": "Number of paused jobs",
      "maximum": 9007199254740991,
      "minimum": -9007199254740991,
      "title": "Paused",
      "type": "integer"
    },
    "waiting": {
      "description": "Number of waiting jobs",
      "maximum": 9007199254740991,
      "minimum": -9007199254740991,
      "title": "Waiting",
      "type": "integer"
    }
  },
  "required": [
    "active",
    "completed",
    "delayed",
    "failed",
    "paused",
    "waiting"
  ],
  "title": "QueueStatisticsDto",
  "type": "object"
}

Config:

  • validate_by_name: True
  • validate_by_alias: True
  • validate_assignment: True
  • protected_namespaces: ()

Fields:

  • active (Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)])
  • completed (Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)])
  • delayed (Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)])
  • failed (Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)])
  • paused (Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)])
  • waiting (Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)])

active pydantic-field 

active: Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)]

Number of active jobs

completed pydantic-field 

completed: Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)]

Number of completed jobs

delayed pydantic-field 

delayed: Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)]

Number of delayed jobs

failed pydantic-field 

failed: Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)]

Number of failed jobs

paused pydantic-field 

paused: Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)]

Number of paused jobs

waiting pydantic-field 

waiting: Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)]

Number of waiting jobs

from_dict classmethod 

from_dict(obj: Optional[Dict[str, Any]]) -> Optional[Self]

Create an instance of QueueStatisticsDto from a dict

Source code in immichpy/client/generated/models/queue_statistics_dto.py 
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@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
    """Create an instance of QueueStatisticsDto from a dict"""
    if obj is None:
        return None

    if not isinstance(obj, dict):
        return cls.model_validate(obj)

    _obj = cls.model_validate(
        {
            "active": obj.get("active"),
            "completed": obj.get("completed"),
            "delayed": obj.get("delayed"),
            "failed": obj.get("failed"),
            "paused": obj.get("paused"),
            "waiting": obj.get("waiting"),
        }
    )
    return _obj

from_json classmethod 

from_json(json_str: str) -> Optional[Self]

Create an instance of QueueStatisticsDto from a JSON string

Source code in immichpy/client/generated/models/queue_statistics_dto.py 
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@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
    """Create an instance of QueueStatisticsDto from a JSON string"""
    return cls.from_dict(json.loads(json_str))

to_dict 

to_dict() -> Dict[str, Any]

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic's self.model_dump(by_alias=True):

  • None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.
Source code in immichpy/client/generated/models/queue_statistics_dto.py 
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def to_dict(self) -> Dict[str, Any]:
    """Return the dictionary representation of the model using alias.

    This has the following differences from calling pydantic's
    `self.model_dump(by_alias=True)`:

    * `None` is only added to the output dict for nullable fields that
      were set at model initialization. Other fields with value `None`
      are ignored.
    """
    excluded_fields: Set[str] = set([])

    _dict = self.model_dump(
        by_alias=True,
        exclude=excluded_fields,
        exclude_none=True,
    )
    return _dict

to_json 

to_json() -> str

Returns the JSON representation of the model using alias

Source code in immichpy/client/generated/models/queue_statistics_dto.py 
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def to_json(self) -> str:
    """Returns the JSON representation of the model using alias"""
    return json.dumps(to_jsonable_python(self.to_dict()))

to_str 

to_str() -> str

Returns the string representation of the model using alias

Source code in immichpy/client/generated/models/queue_statistics_dto.py 
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def to_str(self) -> str:
    """Returns the string representation of the model using alias"""
    return pprint.pformat(self.model_dump(by_alias=True))