Skip to content

Usage By User Dto

immichpy.client.generated.models.usage_by_user_dto.UsageByUserDto pydantic-model

Bases: BaseModel

UsageByUserDto

Show JSON schema: 
{
  "description": "UsageByUserDto",
  "properties": {
    "photos": {
      "description": "Number of photos",
      "maximum": 9007199254740991,
      "minimum": -9007199254740991,
      "title": "Photos",
      "type": "integer"
    },
    "quotaSizeInBytes": {
      "anyOf": [
        {
          "maximum": 9007199254740991,
          "minimum": -9007199254740991,
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "description": "User quota size in bytes (null if unlimited)",
      "title": "Quotasizeinbytes"
    },
    "usage": {
      "description": "Total storage usage in bytes",
      "maximum": 9007199254740991,
      "minimum": -9007199254740991,
      "title": "Usage",
      "type": "integer"
    },
    "usagePhotos": {
      "description": "Storage usage for photos in bytes",
      "maximum": 9007199254740991,
      "minimum": -9007199254740991,
      "title": "Usagephotos",
      "type": "integer"
    },
    "usageVideos": {
      "description": "Storage usage for videos in bytes",
      "maximum": 9007199254740991,
      "minimum": -9007199254740991,
      "title": "Usagevideos",
      "type": "integer"
    },
    "userId": {
      "description": "User ID",
      "format": "uuid",
      "title": "Userid",
      "type": "string"
    },
    "userName": {
      "description": "User name",
      "title": "Username",
      "type": "string"
    },
    "videos": {
      "description": "Number of videos",
      "maximum": 9007199254740991,
      "minimum": -9007199254740991,
      "title": "Videos",
      "type": "integer"
    }
  },
  "required": [
    "photos",
    "quotaSizeInBytes",
    "usage",
    "usagePhotos",
    "usageVideos",
    "userId",
    "userName",
    "videos"
  ],
  "title": "UsageByUserDto",
  "type": "object"
}

Config:

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

Fields:

  • photos (Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)])
  • quota_size_in_bytes (Optional[Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)]])
  • usage (Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)])
  • usage_photos (Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)])
  • usage_videos (Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)])
  • user_id (UUID)
  • user_name (StrictStr)
  • videos (Annotated[int, Field(le=9007199254740991, strict=True, ge=-9007199254740991)])

Validators:

photos pydantic-field 

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

Number of photos

quota_size_in_bytes pydantic-field 

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

User quota size in bytes (null if unlimited)

usage pydantic-field 

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

Total storage usage in bytes

usage_photos pydantic-field 

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

Storage usage for photos in bytes

usage_videos pydantic-field 

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

Storage usage for videos in bytes

user_id pydantic-field 

user_id: UUID

User ID

user_name pydantic-field 

user_name: StrictStr

User name

videos pydantic-field 

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

Number of videos

from_dict classmethod 

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

Create an instance of UsageByUserDto from a dict

Source code in immichpy/client/generated/models/usage_by_user_dto.py 
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
    """Create an instance of UsageByUserDto from a dict"""
    if obj is None:
        return None

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

    _obj = cls.model_validate(
        {
            "photos": obj.get("photos"),
            "quotaSizeInBytes": obj.get("quotaSizeInBytes"),
            "usage": obj.get("usage"),
            "usagePhotos": obj.get("usagePhotos"),
            "usageVideos": obj.get("usageVideos"),
            "userId": obj.get("userId"),
            "userName": obj.get("userName"),
            "videos": obj.get("videos"),
        }
    )
    return _obj

from_json classmethod 

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

Create an instance of UsageByUserDto from a JSON string

Source code in immichpy/client/generated/models/usage_by_user_dto.py 
94
95
96
97
@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
    """Create an instance of UsageByUserDto 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/usage_by_user_dto.py 
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
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,
    )
    # set to None if quota_size_in_bytes (nullable) is None
    # and model_fields_set contains the field
    if (
        self.quota_size_in_bytes is None
        and "quota_size_in_bytes" in self.model_fields_set
    ):
        _dict["quotaSizeInBytes"] = None

    return _dict

to_json 

to_json() -> str

Returns the JSON representation of the model using alias

Source code in immichpy/client/generated/models/usage_by_user_dto.py 
90
91
92
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/usage_by_user_dto.py 
86
87
88
def to_str(self) -> str:
    """Returns the string representation of the model using alias"""
    return pprint.pformat(self.model_dump(by_alias=True))

user_id_validate_regular_expression pydantic-validator 

user_id_validate_regular_expression(value)

Validates the regular expression

Source code in immichpy/client/generated/models/usage_by_user_dto.py 
67
68
69
70
71
72
73
74
75
76
77
@field_validator("user_id", mode="before")
def user_id_validate_regular_expression(cls, value):
    """Validates the regular expression"""
    if isinstance(value, str) and not re.match(
        r"^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-4[0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12})$",
        value,
    ):
        raise ValueError(
            r"must validate the regular expression /^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-4[0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12})$/"
        )
    return value