miro_api.models.shape_data_for_update

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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, StrictStr
 21from typing import Any, ClassVar, Dict, List, Optional
 22from typing import Optional, Set
 23from typing_extensions import Self
 24
 25
 26class ShapeDataForUpdate(BaseModel):
 27    """
 28    Contains shape item data, such as the content or the type of the shape.
 29    """  # noqa: E501
 30
 31    content: Optional[StrictStr] = Field(
 32        default=None,
 33        description="The text you want to display on the shape. **Note: When updating a shape type to one of the types below, existing `content` will be lost.** <br>**Not supported for shapes:** <ul>   <li>flow_chart_or</li>   <li>flow_chart_summing_junction</li> </ul>",
 34    )
 35    shape: Optional[StrictStr] = Field(
 36        default="rectangle",
 37        description="Defines the geometric shape of the item when it is rendered on the board. <details>   <summary>Basic shapes</summary>   <ul>     <li>rectangle</li>     <li>round_rectangle</li>     <li>circle</li>     <li>triangle</li>     <li>rhombus</li>     <li>parallelogram</li>     <li>trapezoid</li>     <li>pentagon</li>     <li>hexagon</li>     <li>octagon</li>     <li>wedge_round_rectangle_callout</li>     <li>star</li>     <li>flow_chart_predefined_process</li>     <li>cloud</li>     <li>cross</li>     <li>can</li>     <li>right_arrow</li>     <li>left_arrow</li>     <li>left_right_arrow</li>     <li>left_brace</li>     <li>right_brace</li>   </ul> </details> <details>   <summary>Flowchart shapes</summary>   <ul>     <li>flow_chart_connector</li>     <li>flow_chart_magnetic_disk</li>     <li>flow_chart_input_output</li>     <li>flow_chart_decision</li>     <li>flow_chart_delay</li>     <li>flow_chart_display</li>     <li>flow_chart_document</li>     <li>flow_chart_magnetic_drum</li>     <li>flow_chart_internal_storage</li>     <li>flow_chart_manual_input</li>     <li>flow_chart_manual_operation</li>     <li>flow_chart_merge</li>     <li>flow_chart_multidocuments</li>     <li>flow_chart_note_curly_left</li>     <li>flow_chart_note_curly_right</li>     <li>flow_chart_note_square</li>     <li>flow_chart_offpage_connector</li>     <li>flow_chart_or</li>     <li>flow_chart_predefined_process_2</li>     <li>flow_chart_preparation</li>     <li>flow_chart_process</li>     <li>flow_chart_online_storage</li>     <li>flow_chart_summing_junction</li>     <li>flow_chart_terminator</li>   </ul> </details>",
 38    )
 39    additional_properties: Dict[str, Any] = {}
 40    __properties: ClassVar[List[str]] = ["content", "shape"]
 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 ShapeDataForUpdate 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 ShapeDataForUpdate 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            {"content": obj.get("content"), "shape": obj.get("shape") if obj.get("shape") is not None else "rectangle"}
102        )
103        # store additional fields in additional_properties
104        for _key in obj.keys():
105            if _key not in cls.__properties:
106                _obj.additional_properties[_key] = obj.get(_key)
107
108        return _obj

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

 27class ShapeDataForUpdate(BaseModel):
 28    """
 29    Contains shape item data, such as the content or the type of the shape.
 30    """  # noqa: E501
 31
 32    content: Optional[StrictStr] = Field(
 33        default=None,
 34        description="The text you want to display on the shape. **Note: When updating a shape type to one of the types below, existing `content` will be lost.** <br>**Not supported for shapes:** <ul>   <li>flow_chart_or</li>   <li>flow_chart_summing_junction</li> </ul>",
 35    )
 36    shape: Optional[StrictStr] = Field(
 37        default="rectangle",
 38        description="Defines the geometric shape of the item when it is rendered on the board. <details>   <summary>Basic shapes</summary>   <ul>     <li>rectangle</li>     <li>round_rectangle</li>     <li>circle</li>     <li>triangle</li>     <li>rhombus</li>     <li>parallelogram</li>     <li>trapezoid</li>     <li>pentagon</li>     <li>hexagon</li>     <li>octagon</li>     <li>wedge_round_rectangle_callout</li>     <li>star</li>     <li>flow_chart_predefined_process</li>     <li>cloud</li>     <li>cross</li>     <li>can</li>     <li>right_arrow</li>     <li>left_arrow</li>     <li>left_right_arrow</li>     <li>left_brace</li>     <li>right_brace</li>   </ul> </details> <details>   <summary>Flowchart shapes</summary>   <ul>     <li>flow_chart_connector</li>     <li>flow_chart_magnetic_disk</li>     <li>flow_chart_input_output</li>     <li>flow_chart_decision</li>     <li>flow_chart_delay</li>     <li>flow_chart_display</li>     <li>flow_chart_document</li>     <li>flow_chart_magnetic_drum</li>     <li>flow_chart_internal_storage</li>     <li>flow_chart_manual_input</li>     <li>flow_chart_manual_operation</li>     <li>flow_chart_merge</li>     <li>flow_chart_multidocuments</li>     <li>flow_chart_note_curly_left</li>     <li>flow_chart_note_curly_right</li>     <li>flow_chart_note_square</li>     <li>flow_chart_offpage_connector</li>     <li>flow_chart_or</li>     <li>flow_chart_predefined_process_2</li>     <li>flow_chart_preparation</li>     <li>flow_chart_process</li>     <li>flow_chart_online_storage</li>     <li>flow_chart_summing_junction</li>     <li>flow_chart_terminator</li>   </ul> </details>",
 39    )
 40    additional_properties: Dict[str, Any] = {}
 41    __properties: ClassVar[List[str]] = ["content", "shape"]
 42
 43    model_config = {
 44        "populate_by_name": True,
 45        "validate_assignment": True,
 46        "protected_namespaces": (),
 47    }
 48
 49    def to_str(self) -> str:
 50        """Returns the string representation of the model using alias"""
 51        return pprint.pformat(self.model_dump(by_alias=True))
 52
 53    def to_json(self) -> str:
 54        """Returns the JSON representation of the model using alias"""
 55        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
 56        return json.dumps(self.to_dict())
 57
 58    @classmethod
 59    def from_json(cls, json_str: str) -> Optional[Self]:
 60        """Create an instance of ShapeDataForUpdate from a JSON string"""
 61        return cls.from_dict(json.loads(json_str))
 62
 63    def to_dict(self) -> Dict[str, Any]:
 64        """Return the dictionary representation of the model using alias.
 65
 66        This has the following differences from calling pydantic's
 67        `self.model_dump(by_alias=True)`:
 68
 69        * `None` is only added to the output dict for nullable fields that
 70          were set at model initialization. Other fields with value `None`
 71          are ignored.
 72        * Fields in `self.additional_properties` are added to the output dict.
 73        """
 74        excluded_fields: Set[str] = set(
 75            [
 76                "additional_properties",
 77            ]
 78        )
 79
 80        _dict = self.model_dump(
 81            by_alias=True,
 82            exclude=excluded_fields,
 83            exclude_none=True,
 84        )
 85        # puts key-value pairs in additional_properties in the top level
 86        if self.additional_properties is not None:
 87            for _key, _value in self.additional_properties.items():
 88                _dict[_key] = _value
 89
 90        return _dict
 91
 92    @classmethod
 93    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
 94        """Create an instance of ShapeDataForUpdate from a dict"""
 95        if obj is None:
 96            return None
 97
 98        if not isinstance(obj, dict):
 99            return cls.model_validate(obj)
100
101        _obj = cls.model_validate(
102            {"content": obj.get("content"), "shape": obj.get("shape") if obj.get("shape") is not None else "rectangle"}
103        )
104        # store additional fields in additional_properties
105        for _key in obj.keys():
106            if _key not in cls.__properties:
107                _obj.additional_properties[_key] = obj.get(_key)
108
109        return _obj

Contains shape item data, such as the content or the type of the shape.

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

shape: 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

49    def to_str(self) -> str:
50        """Returns the string representation of the model using alias"""
51        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

53    def to_json(self) -> str:
54        """Returns the JSON representation of the model using alias"""
55        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
56        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

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

Create an instance of ShapeDataForUpdate from a JSON string

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

63    def to_dict(self) -> Dict[str, Any]:
64        """Return the dictionary representation of the model using alias.
65
66        This has the following differences from calling pydantic's
67        `self.model_dump(by_alias=True)`:
68
69        * `None` is only added to the output dict for nullable fields that
70          were set at model initialization. Other fields with value `None`
71          are ignored.
72        * Fields in `self.additional_properties` are added to the output dict.
73        """
74        excluded_fields: Set[str] = set(
75            [
76                "additional_properties",
77            ]
78        )
79
80        _dict = self.model_dump(
81            by_alias=True,
82            exclude=excluded_fields,
83            exclude_none=True,
84        )
85        # puts key-value pairs in additional_properties in the top level
86        if self.additional_properties is not None:
87            for _key, _value in self.additional_properties.items():
88                _dict[_key] = _value
89
90        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

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

Create an instance of ShapeDataForUpdate 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 = {'content': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, description='The text you want to display on the shape. **Note: When updating a shape type to one of the types below, existing `content` will be lost.** <br>**Not supported for shapes:** <ul> <li>flow_chart_or</li> <li>flow_chart_summing_junction</li> </ul>'), 'shape': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default='rectangle', description='Defines the geometric shape of the item when it is rendered on the board. <details> <summary>Basic shapes</summary> <ul> <li>rectangle</li> <li>round_rectangle</li> <li>circle</li> <li>triangle</li> <li>rhombus</li> <li>parallelogram</li> <li>trapezoid</li> <li>pentagon</li> <li>hexagon</li> <li>octagon</li> <li>wedge_round_rectangle_callout</li> <li>star</li> <li>flow_chart_predefined_process</li> <li>cloud</li> <li>cross</li> <li>can</li> <li>right_arrow</li> <li>left_arrow</li> <li>left_right_arrow</li> <li>left_brace</li> <li>right_brace</li> </ul> </details> <details> <summary>Flowchart shapes</summary> <ul> <li>flow_chart_connector</li> <li>flow_chart_magnetic_disk</li> <li>flow_chart_input_output</li> <li>flow_chart_decision</li> <li>flow_chart_delay</li> <li>flow_chart_display</li> <li>flow_chart_document</li> <li>flow_chart_magnetic_drum</li> <li>flow_chart_internal_storage</li> <li>flow_chart_manual_input</li> <li>flow_chart_manual_operation</li> <li>flow_chart_merge</li> <li>flow_chart_multidocuments</li> <li>flow_chart_note_curly_left</li> <li>flow_chart_note_curly_right</li> <li>flow_chart_note_square</li> <li>flow_chart_offpage_connector</li> <li>flow_chart_or</li> <li>flow_chart_predefined_process_2</li> <li>flow_chart_preparation</li> <li>flow_chart_process</li> <li>flow_chart_online_storage</li> <li>flow_chart_summing_junction</li> <li>flow_chart_terminator</li> </ul> </details>'), '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