100 lines
4.0 KiB
Python
100 lines
4.0 KiB
Python
# coding: utf-8
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"""
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PeerNetService API
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No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator)
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The version of the OpenAPI document: 0.0.1
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Generated by OpenAPI Generator (https://openapi-generator.tech)
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Do not edit the class manually.
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""" # noqa: E501
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from __future__ import annotations
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import pprint
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import re # noqa: F401
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import json
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from pydantic import BaseModel, ConfigDict, Field, StrictInt, StrictStr
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from typing import Any, ClassVar, Dict, List, Optional
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from openapi_client.models.google_protobuf_any import GoogleProtobufAny
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from typing import Optional, Set
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from typing_extensions import Self
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class Status(BaseModel):
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"""
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The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors).
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""" # noqa: E501
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code: Optional[StrictInt] = Field(default=None, description="The status code, which should be an enum value of [google.rpc.Code][google.rpc.Code].")
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message: Optional[StrictStr] = Field(default=None, description="A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the [google.rpc.Status.details][google.rpc.Status.details] field, or localized by the client.")
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details: Optional[List[GoogleProtobufAny]] = Field(default=None, description="A list of messages that carry the error details. There is a common set of message types for APIs to use.")
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__properties: ClassVar[List[str]] = ["code", "message", "details"]
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model_config = ConfigDict(
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populate_by_name=True,
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validate_assignment=True,
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protected_namespaces=(),
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)
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def to_str(self) -> str:
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"""Returns the string representation of the model using alias"""
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return pprint.pformat(self.model_dump(by_alias=True))
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def to_json(self) -> str:
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"""Returns the JSON representation of the model using alias"""
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# TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
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return json.dumps(self.to_dict())
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@classmethod
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def from_json(cls, json_str: str) -> Optional[Self]:
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"""Create an instance of Status from a JSON string"""
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return cls.from_dict(json.loads(json_str))
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def to_dict(self) -> Dict[str, Any]:
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"""Return the dictionary representation of the model using alias.
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This has the following differences from calling pydantic's
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`self.model_dump(by_alias=True)`:
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* `None` is only added to the output dict for nullable fields that
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were set at model initialization. Other fields with value `None`
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are ignored.
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"""
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excluded_fields: Set[str] = set([
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])
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_dict = self.model_dump(
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by_alias=True,
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exclude=excluded_fields,
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exclude_none=True,
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)
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# override the default output from pydantic by calling `to_dict()` of each item in details (list)
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_items = []
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if self.details:
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for _item in self.details:
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if _item:
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_items.append(_item.to_dict())
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_dict['details'] = _items
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return _dict
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@classmethod
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def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
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"""Create an instance of Status from a dict"""
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if obj is None:
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return None
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if not isinstance(obj, dict):
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return cls.model_validate(obj)
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_obj = cls.model_validate({
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"code": obj.get("code"),
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"message": obj.get("message"),
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"details": [GoogleProtobufAny.from_dict(_item) for _item in obj["details"]] if obj.get("details") is not None else None
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})
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return _obj
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