miro_api.models.data_classification_label

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### Miro Developer Platform concepts - New to the Miro Developer Platform? Interested in learning more about platform concepts?? Read our introduction page and familiarize yourself with the Miro Developer Platform capabilities in a few minutes. ### Getting started with the Miro REST API - Quickstart (video): try the REST API in less than 3 minutes. - Quickstart (article): 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 ### Miro App Examples Clone our Miro App Examples repository to get inspiration, customize, and explore apps built on top of Miro's Developer Platform 2.0.

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, StrictInt, StrictStr
 21from typing import Any, ClassVar, Dict, List, Optional
 22from typing import Optional, Set
 23from typing_extensions import Self
 24
 25
 26class DataClassificationLabel(BaseModel):
 27    """
 28    Data classification label
 29    """  # noqa: E501
 30
 31    id: Optional[StrictStr] = Field(default=None, description="Label id.")
 32    color: Optional[StrictStr] = Field(default=None, description="Label color.")
 33    default: Optional[StrictBool] = Field(default=None, description="Label is default.")
 34    description: Optional[StrictStr] = Field(default=None, description="Label description.")
 35    name: Optional[StrictStr] = Field(default=None, description="Label name.")
 36    order_number: Optional[StrictInt] = Field(default=None, description="Label order number.", alias="orderNumber")
 37    sharing_recommendation: Optional[StrictStr] = Field(
 38        default=None,
 39        description="Sharing Recommendation (one of NO_SHARING_RESTRICTIONS, ONLY_WITHIN_ORGANIZATION, ONLY_WITHIN_TEAM or ONLY_WITH_AUTHORIZED_TEAM_MEMBERS ).",
 40        alias="sharingRecommendation",
 41    )
 42    guideline_url: Optional[StrictStr] = Field(
 43        default=None,
 44        description="Indicates the URL for the board classification label guidelines.",
 45        alias="guidelineUrl",
 46    )
 47    type: Optional[StrictStr] = Field(default="data-classification-label", description="Type of the object returned.")
 48    additional_properties: Dict[str, Any] = {}
 49    __properties: ClassVar[List[str]] = [
 50        "id",
 51        "color",
 52        "default",
 53        "description",
 54        "name",
 55        "orderNumber",
 56        "sharingRecommendation",
 57        "guidelineUrl",
 58        "type",
 59    ]
 60
 61    model_config = {
 62        "populate_by_name": True,
 63        "validate_assignment": True,
 64        "protected_namespaces": (),
 65    }
 66
 67    def to_str(self) -> str:
 68        """Returns the string representation of the model using alias"""
 69        return pprint.pformat(self.model_dump(by_alias=True))
 70
 71    def to_json(self) -> str:
 72        """Returns the JSON representation of the model using alias"""
 73        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
 74        return json.dumps(self.to_dict())
 75
 76    @classmethod
 77    def from_json(cls, json_str: str) -> Optional[Self]:
 78        """Create an instance of DataClassificationLabel from a JSON string"""
 79        return cls.from_dict(json.loads(json_str))
 80
 81    def to_dict(self) -> Dict[str, Any]:
 82        """Return the dictionary representation of the model using alias.
 83
 84        This has the following differences from calling pydantic's
 85        `self.model_dump(by_alias=True)`:
 86
 87        * `None` is only added to the output dict for nullable fields that
 88          were set at model initialization. Other fields with value `None`
 89          are ignored.
 90        * Fields in `self.additional_properties` are added to the output dict.
 91        """
 92        excluded_fields: Set[str] = set(
 93            [
 94                "additional_properties",
 95            ]
 96        )
 97
 98        _dict = self.model_dump(
 99            by_alias=True,
100            exclude=excluded_fields,
101            exclude_none=True,
102        )
103        # puts key-value pairs in additional_properties in the top level
104        if self.additional_properties is not None:
105            for _key, _value in self.additional_properties.items():
106                _dict[_key] = _value
107
108        return _dict
109
110    @classmethod
111    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
112        """Create an instance of DataClassificationLabel from a dict"""
113        if obj is None:
114            return None
115
116        if not isinstance(obj, dict):
117            return cls.model_validate(obj)
118
119        _obj = cls.model_validate(
120            {
121                "id": obj.get("id"),
122                "color": obj.get("color"),
123                "default": obj.get("default"),
124                "description": obj.get("description"),
125                "name": obj.get("name"),
126                "orderNumber": obj.get("orderNumber"),
127                "sharingRecommendation": obj.get("sharingRecommendation"),
128                "guidelineUrl": obj.get("guidelineUrl"),
129                "type": obj.get("type") if obj.get("type") is not None else "data-classification-label",
130            }
131        )
132        # store additional fields in additional_properties
133        for _key in obj.keys():
134            if _key not in cls.__properties:
135                _obj.additional_properties[_key] = obj.get(_key)
136
137        return _obj

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

 27class DataClassificationLabel(BaseModel):
 28    """
 29    Data classification label
 30    """  # noqa: E501
 31
 32    id: Optional[StrictStr] = Field(default=None, description="Label id.")
 33    color: Optional[StrictStr] = Field(default=None, description="Label color.")
 34    default: Optional[StrictBool] = Field(default=None, description="Label is default.")
 35    description: Optional[StrictStr] = Field(default=None, description="Label description.")
 36    name: Optional[StrictStr] = Field(default=None, description="Label name.")
 37    order_number: Optional[StrictInt] = Field(default=None, description="Label order number.", alias="orderNumber")
 38    sharing_recommendation: Optional[StrictStr] = Field(
 39        default=None,
 40        description="Sharing Recommendation (one of NO_SHARING_RESTRICTIONS, ONLY_WITHIN_ORGANIZATION, ONLY_WITHIN_TEAM or ONLY_WITH_AUTHORIZED_TEAM_MEMBERS ).",
 41        alias="sharingRecommendation",
 42    )
 43    guideline_url: Optional[StrictStr] = Field(
 44        default=None,
 45        description="Indicates the URL for the board classification label guidelines.",
 46        alias="guidelineUrl",
 47    )
 48    type: Optional[StrictStr] = Field(default="data-classification-label", description="Type of the object returned.")
 49    additional_properties: Dict[str, Any] = {}
 50    __properties: ClassVar[List[str]] = [
 51        "id",
 52        "color",
 53        "default",
 54        "description",
 55        "name",
 56        "orderNumber",
 57        "sharingRecommendation",
 58        "guidelineUrl",
 59        "type",
 60    ]
 61
 62    model_config = {
 63        "populate_by_name": True,
 64        "validate_assignment": True,
 65        "protected_namespaces": (),
 66    }
 67
 68    def to_str(self) -> str:
 69        """Returns the string representation of the model using alias"""
 70        return pprint.pformat(self.model_dump(by_alias=True))
 71
 72    def to_json(self) -> str:
 73        """Returns the JSON representation of the model using alias"""
 74        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
 75        return json.dumps(self.to_dict())
 76
 77    @classmethod
 78    def from_json(cls, json_str: str) -> Optional[Self]:
 79        """Create an instance of DataClassificationLabel from a JSON string"""
 80        return cls.from_dict(json.loads(json_str))
 81
 82    def to_dict(self) -> Dict[str, Any]:
 83        """Return the dictionary representation of the model using alias.
 84
 85        This has the following differences from calling pydantic's
 86        `self.model_dump(by_alias=True)`:
 87
 88        * `None` is only added to the output dict for nullable fields that
 89          were set at model initialization. Other fields with value `None`
 90          are ignored.
 91        * Fields in `self.additional_properties` are added to the output dict.
 92        """
 93        excluded_fields: Set[str] = set(
 94            [
 95                "additional_properties",
 96            ]
 97        )
 98
 99        _dict = self.model_dump(
100            by_alias=True,
101            exclude=excluded_fields,
102            exclude_none=True,
103        )
104        # puts key-value pairs in additional_properties in the top level
105        if self.additional_properties is not None:
106            for _key, _value in self.additional_properties.items():
107                _dict[_key] = _value
108
109        return _dict
110
111    @classmethod
112    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
113        """Create an instance of DataClassificationLabel from a dict"""
114        if obj is None:
115            return None
116
117        if not isinstance(obj, dict):
118            return cls.model_validate(obj)
119
120        _obj = cls.model_validate(
121            {
122                "id": obj.get("id"),
123                "color": obj.get("color"),
124                "default": obj.get("default"),
125                "description": obj.get("description"),
126                "name": obj.get("name"),
127                "orderNumber": obj.get("orderNumber"),
128                "sharingRecommendation": obj.get("sharingRecommendation"),
129                "guidelineUrl": obj.get("guidelineUrl"),
130                "type": obj.get("type") if obj.get("type") is not None else "data-classification-label",
131            }
132        )
133        # store additional fields in additional_properties
134        for _key in obj.keys():
135            if _key not in cls.__properties:
136                _obj.additional_properties[_key] = obj.get(_key)
137
138        return _obj

Data classification label

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

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

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

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

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

order_number: Optional[Annotated[int, Strict(strict=True)]]

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

guideline_url: Optional[Annotated[str, 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

68    def to_str(self) -> str:
69        """Returns the string representation of the model using alias"""
70        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

72    def to_json(self) -> str:
73        """Returns the JSON representation of the model using alias"""
74        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
75        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

77    @classmethod
78    def from_json(cls, json_str: str) -> Optional[Self]:
79        """Create an instance of DataClassificationLabel from a JSON string"""
80        return cls.from_dict(json.loads(json_str))

Create an instance of DataClassificationLabel from a JSON string

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

 82    def to_dict(self) -> Dict[str, Any]:
 83        """Return the dictionary representation of the model using alias.
 84
 85        This has the following differences from calling pydantic's
 86        `self.model_dump(by_alias=True)`:
 87
 88        * `None` is only added to the output dict for nullable fields that
 89          were set at model initialization. Other fields with value `None`
 90          are ignored.
 91        * Fields in `self.additional_properties` are added to the output dict.
 92        """
 93        excluded_fields: Set[str] = set(
 94            [
 95                "additional_properties",
 96            ]
 97        )
 98
 99        _dict = self.model_dump(
100            by_alias=True,
101            exclude=excluded_fields,
102            exclude_none=True,
103        )
104        # puts key-value pairs in additional_properties in the top level
105        if self.additional_properties is not None:
106            for _key, _value in self.additional_properties.items():
107                _dict[_key] = _value
108
109        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

111    @classmethod
112    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
113        """Create an instance of DataClassificationLabel from a dict"""
114        if obj is None:
115            return None
116
117        if not isinstance(obj, dict):
118            return cls.model_validate(obj)
119
120        _obj = cls.model_validate(
121            {
122                "id": obj.get("id"),
123                "color": obj.get("color"),
124                "default": obj.get("default"),
125                "description": obj.get("description"),
126                "name": obj.get("name"),
127                "orderNumber": obj.get("orderNumber"),
128                "sharingRecommendation": obj.get("sharingRecommendation"),
129                "guidelineUrl": obj.get("guidelineUrl"),
130                "type": obj.get("type") if obj.get("type") is not None else "data-classification-label",
131            }
132        )
133        # store additional fields in additional_properties
134        for _key in obj.keys():
135            if _key not in cls.__properties:
136                _obj.additional_properties[_key] = obj.get(_key)
137
138        return _obj

Create an instance of DataClassificationLabel 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 = {'id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, description='Label id.'), 'color': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, description='Label color.'), 'default': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, description='Label is default.'), 'description': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, description='Label description.'), 'name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, description='Label name.'), 'order_number': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], NoneType], required=False, alias='orderNumber', alias_priority=2, description='Label order number.'), 'sharing_recommendation': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='sharingRecommendation', alias_priority=2, description='Sharing Recommendation (one of NO_SHARING_RESTRICTIONS, ONLY_WITHIN_ORGANIZATION, ONLY_WITHIN_TEAM or ONLY_WITH_AUTHORIZED_TEAM_MEMBERS ).'), 'guideline_url': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='guidelineUrl', alias_priority=2, description='Indicates the URL for the board classification label guidelines.'), 'type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default='data-classification-label', 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