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# coding: utf-8
"""
STACKIT Application Load Balancer API
This API offers an interface to provision and manage load balancing servers in your STACKIT project. It also has the possibility of pooling target servers for load balancing purposes. For each application load balancer provided, two VMs are deployed in your OpenStack project subject to a fee.
The version of the OpenAPI document: 2beta2.0.0
Generated by OpenAPI Generator (https://openapi-generator.tech)
Do not edit the class manually.
""" # noqa: E501
from __future__ import annotations
import json
import pprint
from typing import Any, ClassVar, Dict, List, Optional, Set
from pydantic import (
BaseModel,
ConfigDict,
Field,
StrictBool,
StrictStr,
)
from typing_extensions import Self
from stackit.alb.models.cookie_persistence import CookiePersistence
from stackit.alb.models.http_header import HttpHeader
from stackit.alb.models.path import Path
from stackit.alb.models.query_parameter import QueryParameter
class Rule(BaseModel):
"""
Rule
""" # noqa: E501
cookie_persistence: Optional[CookiePersistence] = Field(default=None, alias="cookiePersistence")
headers: Optional[List[HttpHeader]] = Field(default=None, description="Headers for the rule.")
path: Optional[Path] = None
path_prefix: Optional[StrictStr] = Field(
default=None,
description="Legacy path prefix match. Optional. If not set, defaults to root path '/'. Cannot be set if 'path' is used. Prefer using 'path.prefix' instead. Only matches on full segment boundaries, e.g. '/foo' matches '/foo' and '/foo/bar' but NOT '/foobar'.",
alias="pathPrefix",
)
query_parameters: Optional[List[QueryParameter]] = Field(
default=None, description="Query Parameters for the rule.", alias="queryParameters"
)
target_pool: Optional[StrictStr] = Field(
default=None, description="Reference target pool by target pool name.", alias="targetPool"
)
web_socket: Optional[StrictBool] = Field(
default=None,
description="If enabled, when client sends an HTTP request with and Upgrade header, indicating the desire to establish a Websocket connection, if backend server supports WebSocket, it responds with HTTP 101 status code, switching protocols from HTTP to WebSocket. Hence the client and the server can exchange data in real-time using one long-lived TCP connection.",
alias="webSocket",
)
__properties: ClassVar[List[str]] = [
"cookiePersistence",
"headers",
"path",
"pathPrefix",
"queryParameters",
"targetPool",
"webSocket",
]
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 Rule 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,
)
# override the default output from pydantic by calling `to_dict()` of cookie_persistence
if self.cookie_persistence:
_dict["cookiePersistence"] = self.cookie_persistence.to_dict()
# override the default output from pydantic by calling `to_dict()` of each item in headers (list)
_items = []
if self.headers:
for _item in self.headers:
if _item:
_items.append(_item.to_dict())
_dict["headers"] = _items
# override the default output from pydantic by calling `to_dict()` of path
if self.path:
_dict["path"] = self.path.to_dict()
# override the default output from pydantic by calling `to_dict()` of each item in query_parameters (list)
_items = []
if self.query_parameters:
for _item in self.query_parameters:
if _item:
_items.append(_item.to_dict())
_dict["queryParameters"] = _items
return _dict
@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
"""Create an instance of Rule from a dict"""
if obj is None:
return None
if not isinstance(obj, dict):
return cls.model_validate(obj)
_obj = cls.model_validate(
{
"cookiePersistence": (
CookiePersistence.from_dict(obj["cookiePersistence"])
if obj.get("cookiePersistence") is not None
else None
),
"headers": (
[HttpHeader.from_dict(_item) for _item in obj["headers"]]
if obj.get("headers") is not None
else None
),
"path": Path.from_dict(obj["path"]) if obj.get("path") is not None else None,
"pathPrefix": obj.get("pathPrefix"),
"queryParameters": (
[QueryParameter.from_dict(_item) for _item in obj["queryParameters"]]
if obj.get("queryParameters") is not None
else None
),
"targetPool": obj.get("targetPool"),
"webSocket": obj.get("webSocket"),
}
)
return _obj