miro_api.models.shape_data_for_create
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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.
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 14from __future__ import annotations 15import pprint 16import re # noqa: F401 17import json 18 19from pydantic import BaseModel, Field, StrictStr 20from typing import Any, ClassVar, Dict, List, Optional 21from typing import Optional, Set 22from typing_extensions import Self 23 24 25class ShapeDataForCreate(BaseModel): 26 """ 27 Contains shape item data, such as the content or the type of the shape. 28 """ # noqa: E501 29 30 content: Optional[StrictStr] = Field( 31 default=None, 32 description="The text you want to display on the shape. <br>**Not supported for shapes:** <ul> <li>flow_chart_or</li> <li>flow_chart_summing_junction</li> </ul>", 33 ) 34 shape: Optional[StrictStr] = Field( 35 default="rectangle", 36 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>", 37 ) 38 additional_properties: Dict[str, Any] = {} 39 __properties: ClassVar[List[str]] = ["content", "shape"] 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 ShapeDataForCreate 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 ShapeDataForCreate 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 {"content": obj.get("content"), "shape": obj.get("shape") if obj.get("shape") is not None else "rectangle"} 101 ) 102 # store additional fields in additional_properties 103 for _key in obj.keys(): 104 if _key not in cls.__properties: 105 _obj.additional_properties[_key] = obj.get(_key) 106 107 return _obj
26class ShapeDataForCreate(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. <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 ShapeDataForCreate 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 ShapeDataForCreate 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
Contains shape item data, such as the content or the type of the shape.
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
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
57 @classmethod 58 def from_json(cls, json_str: str) -> Optional[Self]: 59 """Create an instance of ShapeDataForCreate from a JSON string""" 60 return cls.from_dict(json.loads(json_str))
Create an instance of ShapeDataForCreate from a JSON string
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):
Noneis only added to the output dict for nullable fields that were set at model initialization. Other fields with valueNoneare ignored.- Fields in
self.additional_propertiesare added to the output dict.
91 @classmethod 92 def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]: 93 """Create an instance of ShapeDataForCreate 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
Create an instance of ShapeDataForCreate from a dict
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.
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