BaseAuthEvent¶

pydantic model gafaelfawr.events.BaseAuthEvent¶

Base class for authentication events.

Parameters:: data (Any)

Show JSON schema

{
   "title": "BaseAuthEvent",
   "description": "Base class for authentication events.",
   "type": "object",
   "properties": {
      "username": {
         "description": "Username of authenticated user",
         "title": "Username",
         "type": "string"
      },
      "service": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Service to which the user was authenticated",
         "title": "Service"
      },
      "quota": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "API quota for this service, if one is imposed",
         "title": "Quota"
      },
      "quota_used": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Amount of API quota used as of this request",
         "title": "Quota used"
      }
   },
   "required": [
      "username"
   ]
}

Fields:

quota (int | None)
quota_used (int | None)
service (str | None)
username (str)

field quota: int | None = None¶: API quota for this service, if one is imposed

field quota_used: int | None = None¶: Amount of API quota used as of this request

field service: str | None = None¶: Service to which the user was authenticated

field username: str [Required]¶: Username of authenticated user

asdict()¶

Returns this model in dictionary form. This method differs from pydantic’s dict by converting all values to their Avro representation. It also doesn’t provide the exclude, include, by_alias, etc. parameters that dict provides.

Return type:: Dict[str, Any]

classmethod fake(**data)¶

Creates a fake instance of the model.

Attributes:: data: Dict[str, Any] represent the user values to use in the instance

Parameters:: data (Any)
Return type:: AvroBaseModel

classmethod json_schema(*args, **kwargs)¶

Parameters:

args (Any)
kwargs (Any)

Return type:

str

serialize(serialization_type='avro')¶

Overrides the base AvroModel’s serialize method to inject this class’s standardization factory method

Parameters:: serialization_type (Literal['avro', 'avro-json'], default: 'avro')
Return type:: bytes

to_dict()¶

Return type:: Dict[str, Any]

validate_avro()¶

Validate that instance matches the avro schema

Return type:: bool

classmethod validate_structure()¶

Do runtime validation of fields.

Make sure all of the fields are compatible with the backing datastore (InfluxDB at the moment).

Return type:: None