blob: 4cf34c5013e207e285a5daf612a045918b8b7182 [file] [log] [blame]
# coding: utf-8
"""
Airflow API
Airflow API. All endpoints located under ``/api/v2`` can be used safely, are stable and backward compatible. Endpoints located under ``/ui`` are dedicated to the UI and are subject to breaking change depending on the need of the frontend. Users should not rely on those but use the public ones instead.
The version of the OpenAPI document: 2
Generated by OpenAPI Generator (https://openapi-generator.tech)
Do not edit the class manually.
""" # noqa: E501
from __future__ import annotations
import pprint
import re # noqa: F401
import json
from pydantic import BaseModel, ConfigDict, Field, StrictInt, StrictStr, field_validator
from typing import Any, ClassVar, Dict, List, Optional
from typing_extensions import Annotated
from typing import Optional, Set
from typing_extensions import Self
class ConnectionBody(BaseModel):
"""
Connection Serializer for requests body.
""" # noqa: E501
conn_type: StrictStr
connection_id: Annotated[str, Field(strict=True, max_length=200)]
description: Optional[StrictStr] = None
extra: Optional[StrictStr] = None
host: Optional[StrictStr] = None
login: Optional[StrictStr] = None
password: Optional[StrictStr] = None
port: Optional[StrictInt] = None
var_schema: Optional[StrictStr] = Field(default=None, alias="schema")
__properties: ClassVar[List[str]] = ["conn_type", "connection_id", "description", "extra", "host", "login", "password", "port", "schema"]
@field_validator('connection_id')
def connection_id_validate_regular_expression(cls, value):
"""Validates the regular expression"""
if not re.match(r"^[\w.-]+$", value):
raise ValueError(r"must validate the regular expression /^[\w.-]+$/")
return value
model_config = ConfigDict(
populate_by_name=True,
validate_assignment=True,
protected_namespaces=(),
)
def to_str(self) -> str:
"""Returns the string representation of the model using alias"""
return pprint.pformat(self.model_dump(by_alias=True))
def to_json(self) -> str:
"""Returns the JSON representation of the model using alias"""
# TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
return json.dumps(self.to_dict())
@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
"""Create an instance of ConnectionBody from a JSON string"""
return cls.from_dict(json.loads(json_str))
def to_dict(self) -> Dict[str, Any]:
"""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.
"""
excluded_fields: Set[str] = set([
])
_dict = self.model_dump(
by_alias=True,
exclude=excluded_fields,
exclude_none=True,
)
return _dict
@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
"""Create an instance of ConnectionBody from a dict"""
if obj is None:
return None
if not isinstance(obj, dict):
return cls.model_validate(obj)
_obj = cls.model_validate({
"conn_type": obj.get("conn_type"),
"connection_id": obj.get("connection_id"),
"description": obj.get("description"),
"extra": obj.get("extra"),
"host": obj.get("host"),
"login": obj.get("login"),
"password": obj.get("password"),
"port": obj.get("port"),
"schema": obj.get("schema")
})
return _obj