miro_api.models.data_classification_team_settings

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The version of the OpenAPI document: v2.0 Generated by OpenAPI Generator (https://openapi-generator.tech)

Do not edit the class manually.

View Source

  1# coding: utf-8
  2
  3"""
  4Miro Developer Platform
  5
  6<img src=\"https://content.pstmn.io/47449ea6-0ef7-4af2-bac1-e58a70e61c58/aW1hZ2UucG5n\" width=\"1685\" height=\"593\">  ### Miro Developer Platform concepts  - New to the Miro Developer Platform? Interested in learning more about platform concepts?? [Read our introduction page](https://beta.developers.miro.com/docs/introduction) and familiarize yourself with the Miro Developer Platform capabilities in a few minutes.   ### Getting started with the Miro REST API  - [Quickstart (video):](https://beta.developers.miro.com/docs/try-out-the-rest-api-in-less-than-3-minutes) try the REST API in less than 3 minutes. - [Quickstart (article):](https://beta.developers.miro.com/docs/build-your-first-hello-world-app-1) get started and try the REST API in less than 3 minutes.   ### Miro REST API tutorials  Check out our how-to articles with step-by-step instructions and code examples so you can:  - [Get started with OAuth 2.0 and Miro](https://beta.developers.miro.com/docs/getting-started-with-oauth)   ### Miro App Examples  Clone our [Miro App Examples repository](https://github.com/miroapp/app-examples) to get inspiration, customize, and explore apps built on top of Miro's Developer Platform 2.0.
  7
  8The version of the OpenAPI document: v2.0
  9Generated by OpenAPI Generator (https://openapi-generator.tech)
 10
 11Do not edit the class manually.
 12"""  # noqa: E501
 13
 14
 15from __future__ import annotations
 16import pprint
 17import re  # noqa: F401
 18import json
 19
 20from pydantic import BaseModel, Field, StrictBool, StrictStr
 21from typing import Any, ClassVar, Dict, List, Optional
 22from typing import Optional, Set
 23from typing_extensions import Self
 24
 25
 26class DataClassificationTeamSettings(BaseModel):
 27    """
 28    DataClassificationTeamSettings
 29    """  # noqa: E501
 30
 31    default_label_id: Optional[StrictStr] = Field(
 32        default=None, description="Data classification default label id", alias="defaultLabelId"
 33    )
 34    enabled: Optional[StrictBool] = Field(default=None, description="Data classification enabled for team")
 35    type: Optional[StrictStr] = Field(
 36        default="team-data-classification-settings", description="Type of the object returned."
 37    )
 38    additional_properties: Dict[str, Any] = {}
 39    __properties: ClassVar[List[str]] = ["defaultLabelId", "enabled", "type"]
 40
 41    model_config = {
 42        "populate_by_name": True,
 43        "validate_assignment": True,
 44        "protected_namespaces": (),
 45    }
 46
 47    def to_str(self) -> str:
 48        """Returns the string representation of the model using alias"""
 49        return pprint.pformat(self.model_dump(by_alias=True))
 50
 51    def to_json(self) -> str:
 52        """Returns the JSON representation of the model using alias"""
 53        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
 54        return json.dumps(self.to_dict())
 55
 56    @classmethod
 57    def from_json(cls, json_str: str) -> Optional[Self]:
 58        """Create an instance of DataClassificationTeamSettings from a JSON string"""
 59        return cls.from_dict(json.loads(json_str))
 60
 61    def to_dict(self) -> Dict[str, Any]:
 62        """Return the dictionary representation of the model using alias.
 63
 64        This has the following differences from calling pydantic's
 65        `self.model_dump(by_alias=True)`:
 66
 67        * `None` is only added to the output dict for nullable fields that
 68          were set at model initialization. Other fields with value `None`
 69          are ignored.
 70        * Fields in `self.additional_properties` are added to the output dict.
 71        """
 72        excluded_fields: Set[str] = set(
 73            [
 74                "additional_properties",
 75            ]
 76        )
 77
 78        _dict = self.model_dump(
 79            by_alias=True,
 80            exclude=excluded_fields,
 81            exclude_none=True,
 82        )
 83        # puts key-value pairs in additional_properties in the top level
 84        if self.additional_properties is not None:
 85            for _key, _value in self.additional_properties.items():
 86                _dict[_key] = _value
 87
 88        return _dict
 89
 90    @classmethod
 91    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
 92        """Create an instance of DataClassificationTeamSettings from a dict"""
 93        if obj is None:
 94            return None
 95
 96        if not isinstance(obj, dict):
 97            return cls.model_validate(obj)
 98
 99        _obj = cls.model_validate(
100            {
101                "defaultLabelId": obj.get("defaultLabelId"),
102                "enabled": obj.get("enabled"),
103                "type": obj.get("type") if obj.get("type") is not None else "team-data-classification-settings",
104            }
105        )
106        # store additional fields in additional_properties
107        for _key in obj.keys():
108            if _key not in cls.__properties:
109                _obj.additional_properties[_key] = obj.get(_key)
110
111        return _obj

class DataClassificationTeamSettings(pydantic.main.BaseModel): View Source

 27class DataClassificationTeamSettings(BaseModel):
 28    """
 29    DataClassificationTeamSettings
 30    """  # noqa: E501
 31
 32    default_label_id: Optional[StrictStr] = Field(
 33        default=None, description="Data classification default label id", alias="defaultLabelId"
 34    )
 35    enabled: Optional[StrictBool] = Field(default=None, description="Data classification enabled for team")
 36    type: Optional[StrictStr] = Field(
 37        default="team-data-classification-settings", description="Type of the object returned."
 38    )
 39    additional_properties: Dict[str, Any] = {}
 40    __properties: ClassVar[List[str]] = ["defaultLabelId", "enabled", "type"]
 41
 42    model_config = {
 43        "populate_by_name": True,
 44        "validate_assignment": True,
 45        "protected_namespaces": (),
 46    }
 47
 48    def to_str(self) -> str:
 49        """Returns the string representation of the model using alias"""
 50        return pprint.pformat(self.model_dump(by_alias=True))
 51
 52    def to_json(self) -> str:
 53        """Returns the JSON representation of the model using alias"""
 54        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
 55        return json.dumps(self.to_dict())
 56
 57    @classmethod
 58    def from_json(cls, json_str: str) -> Optional[Self]:
 59        """Create an instance of DataClassificationTeamSettings from a JSON string"""
 60        return cls.from_dict(json.loads(json_str))
 61
 62    def to_dict(self) -> Dict[str, Any]:
 63        """Return the dictionary representation of the model using alias.
 64
 65        This has the following differences from calling pydantic's
 66        `self.model_dump(by_alias=True)`:
 67
 68        * `None` is only added to the output dict for nullable fields that
 69          were set at model initialization. Other fields with value `None`
 70          are ignored.
 71        * Fields in `self.additional_properties` are added to the output dict.
 72        """
 73        excluded_fields: Set[str] = set(
 74            [
 75                "additional_properties",
 76            ]
 77        )
 78
 79        _dict = self.model_dump(
 80            by_alias=True,
 81            exclude=excluded_fields,
 82            exclude_none=True,
 83        )
 84        # puts key-value pairs in additional_properties in the top level
 85        if self.additional_properties is not None:
 86            for _key, _value in self.additional_properties.items():
 87                _dict[_key] = _value
 88
 89        return _dict
 90
 91    @classmethod
 92    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
 93        """Create an instance of DataClassificationTeamSettings from a dict"""
 94        if obj is None:
 95            return None
 96
 97        if not isinstance(obj, dict):
 98            return cls.model_validate(obj)
 99
100        _obj = cls.model_validate(
101            {
102                "defaultLabelId": obj.get("defaultLabelId"),
103                "enabled": obj.get("enabled"),
104                "type": obj.get("type") if obj.get("type") is not None else "team-data-classification-settings",
105            }
106        )
107        # store additional fields in additional_properties
108        for _key in obj.keys():
109            if _key not in cls.__properties:
110                _obj.additional_properties[_key] = obj.get(_key)
111
112        return _obj

DataClassificationTeamSettings

default_label_id: Optional[Annotated[str, Strict(strict=True)]]

enabled: Optional[Annotated[bool, Strict(strict=True)]]

type: Optional[Annotated[str, Strict(strict=True)]]

additional_properties: Dict[str, Any]

model_config = {'populate_by_name': True, 'validate_assignment': True, 'protected_namespaces': ()}

def to_str(self) -> str: View Source

48    def to_str(self) -> str:
49        """Returns the string representation of the model using alias"""
50        return pprint.pformat(self.model_dump(by_alias=True))

Returns the string representation of the model using alias

def to_json(self) -> str: View Source

52    def to_json(self) -> str:
53        """Returns the JSON representation of the model using alias"""
54        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
55        return json.dumps(self.to_dict())

Returns the JSON representation of the model using alias

@classmethod

def from_json(cls, json_str: str) -> Optional[typing_extensions.Self]: View Source

57    @classmethod
58    def from_json(cls, json_str: str) -> Optional[Self]:
59        """Create an instance of DataClassificationTeamSettings from a JSON string"""
60        return cls.from_dict(json.loads(json_str))

Create an instance of DataClassificationTeamSettings from a JSON string

def to_dict(self) -> Dict[str, Any]: View Source

62    def to_dict(self) -> Dict[str, Any]:
63        """Return the dictionary representation of the model using alias.
64
65        This has the following differences from calling pydantic's
66        `self.model_dump(by_alias=True)`:
67
68        * `None` is only added to the output dict for nullable fields that
69          were set at model initialization. Other fields with value `None`
70          are ignored.
71        * Fields in `self.additional_properties` are added to the output dict.
72        """
73        excluded_fields: Set[str] = set(
74            [
75                "additional_properties",
76            ]
77        )
78
79        _dict = self.model_dump(
80            by_alias=True,
81            exclude=excluded_fields,
82            exclude_none=True,
83        )
84        # puts key-value pairs in additional_properties in the top level
85        if self.additional_properties is not None:
86            for _key, _value in self.additional_properties.items():
87                _dict[_key] = _value
88
89        return _dict

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.
Fields in self.additional_properties are added to the output dict.

@classmethod

def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[typing_extensions.Self]: View Source

 91    @classmethod
 92    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
 93        """Create an instance of DataClassificationTeamSettings from a dict"""
 94        if obj is None:
 95            return None
 96
 97        if not isinstance(obj, dict):
 98            return cls.model_validate(obj)
 99
100        _obj = cls.model_validate(
101            {
102                "defaultLabelId": obj.get("defaultLabelId"),
103                "enabled": obj.get("enabled"),
104                "type": obj.get("type") if obj.get("type") is not None else "team-data-classification-settings",
105            }
106        )
107        # store additional fields in additional_properties
108        for _key in obj.keys():
109            if _key not in cls.__properties:
110                _obj.additional_properties[_key] = obj.get(_key)
111
112        return _obj

Create an instance of DataClassificationTeamSettings from a dict

def model_post_init(self: pydantic.main.BaseModel, __context: Any) -> None: View Source

265def init_private_attributes(self: BaseModel, __context: Any) -> None:
266    """This function is meant to behave like a BaseModel method to initialise private attributes.
267
268    It takes context as an argument since that's what pydantic-core passes when calling it.
269
270    Args:
271        self: The BaseModel instance.
272        __context: The context.
273    """
274    if getattr(self, '__pydantic_private__', None) is None:
275        pydantic_private = {}
276        for name, private_attr in self.__private_attributes__.items():
277            default = private_attr.get_default()
278            if default is not PydanticUndefined:
279                pydantic_private[name] = default
280        object_setattr(self, '__pydantic_private__', pydantic_private)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that's what pydantic-core passes when calling it.

Args: self: The BaseModel instance. __context: The context.

model_fields = {'default_label_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='defaultLabelId', alias_priority=2, description='Data classification default label id'), 'enabled': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, description='Data classification enabled for team'), 'type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default='team-data-classification-settings', description='Type of the object returned.'), 'additional_properties': FieldInfo(annotation=Dict[str, Any], required=False, default={})}

model_computed_fields = {}

Inherited Members

pydantic.main.BaseModel: BaseModel; model_extra; model_fields_set; model_construct; model_copy; model_dump; model_dump_json; model_json_schema; model_parametrized_name; model_rebuild; model_validate; model_validate_json; model_validate_strings; dict; json; parse_obj; parse_raw; parse_file; from_orm; construct; copy; schema; schema_json; validate; update_forward_refs