cookie_persistence.py

# coding: utf-8

"""
    STACKIT Application Load Balancer API

    This API offers an interface to provision and manage Application Load Balancers in your STACKIT project.This solution offers modern L7 load balancing. Current features include TLS, path and prefix based routing aswell as routing based on headers, query parameters and keeping connections persistent with cookies and web sockets.  For each Application Load Balancer provided, two VMs are deployed in your STACKIT project and are subject to fees.

    The version of the OpenAPI document: 2.0.0
    Generated by OpenAPI Generator (https://openapi-generator.tech)

    Do not edit the class manually.
"""  # noqa: E501

from __future__ import annotations

import json
import pprint
import re  # noqa: F401
from typing import Any, ClassVar, Dict, List, Optional, Set

from pydantic import BaseModel, ConfigDict, Field, StrictStr, field_validator
from pydantic_core import to_jsonable_python
from typing_extensions import Annotated, Self


class CookiePersistence(BaseModel):
    """
    CookiePersistence contains the cookie-based session persistence configuration.
    """  # noqa: E501

    name: Optional[StrictStr] = Field(default=None, description="Cookie is the name of the cookie to use.")
    ttl: Optional[Annotated[str, Field(strict=True)]] = Field(
        default=None,
        description="TTL specifies the time-to-live for the cookie. The default value is 0s, and it acts as a session cookie, expiring when the client session ends. ",
    )
    __properties: ClassVar[List[str]] = ["name", "ttl"]

    @field_validator("ttl")
    def ttl_validate_regular_expression(cls, value):
        """Validates the regular expression"""
        if value is None:
            return value

        if not isinstance(value, str):
            value = str(value)

        if not re.match(r"^-?(?:0|[1-9][0-9]{0,11})(?:\.[0-9]{1,9})?s$", value):
            raise ValueError(r"must validate the regular expression /^-?(?:0|[1-9][0-9]{0,11})(?:\.[0-9]{1,9})?s$/")
        return value

    model_config = ConfigDict(
        validate_by_name=True,
        validate_by_alias=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"""
        return json.dumps(to_jsonable_python(self.to_dict()))

    @classmethod
    def from_json(cls, json_str: str) -> Optional[Self]:
        """Create an instance of CookiePersistence 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 CookiePersistence from a dict"""
        if obj is None:
            return None

        if not isinstance(obj, dict):
            return cls.model_validate(obj)

        _obj = cls.model_validate({"name": obj.get("name"), "ttl": obj.get("ttl")})
        return _obj