# coding: utf-8

"""
    Kubernetes

    No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator)

    The version of the OpenAPI document: release-1.37
    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 collections.abc import Mapping as _Mapping
from pydantic import AliasChoices, BaseModel, ConfigDict, Field
from typing import Any, ClassVar, Dict, List, Optional, cast as _cast
from kubernetes.aio.client.models.v1_pod_affinity_term import V1PodAffinityTerm
from kubernetes.aio.client.models.v1_weighted_pod_affinity_term import V1WeightedPodAffinityTerm
from typing import Optional, Set
from typing_extensions import Self
from pydantic_core import to_jsonable_python


_OPENAPI_GENERATOR_TO_DICT = "_openapi_generator_to_dict"


def _get_openapi_to_dict(value: Any) -> Any:
    # Reciprocal function references preserve inherited generated methods
    # without reserving model member names. Checking both directions also
    # rejects overrides whose decorators copy function attributes.
    to_dict = getattr(value, "to_dict", None)
    type_to_dict = getattr(type(value), "to_dict", None)
    if (
        not callable(to_dict)
        or getattr(to_dict, "__func__", None) is not type_to_dict
    ):
        return None

    openapi_to_dict = getattr(
        type_to_dict, _OPENAPI_GENERATOR_TO_DICT, None
    )
    if (
        not callable(openapi_to_dict)
        or getattr(
            openapi_to_dict,
            _OPENAPI_GENERATOR_TO_DICT,
            None,
        ) is not type_to_dict
    ):
        return None
    return openapi_to_dict


def _to_legacy_item(value: Any, serialize: bool) -> Any:
    to_dict = getattr(value, "to_dict", None)
    if _get_openapi_to_dict(value) is not None and callable(to_dict):
        return to_dict(serialize=serialize)
    if callable(to_dict):
        return to_dict()
    return value


def _to_legacy_value(value: Any, serialize: bool) -> Any:
    # python-legacy converted only immediate list elements or dictionary values:
    # https://github.com/OpenAPITools/openapi-generator/blob/c84b949df1a9ec04ba75989cb49b45c940c2f694/modules/openapi-generator/src/main/resources/python-legacy/model.mustache#L203-L231
    if isinstance(value, list):
        return [_to_legacy_item(item, serialize) for item in value]
    if isinstance(value, dict):
        return {
            key: _to_legacy_item(item, serialize)
            for key, item in value.items()
        }
    return _to_legacy_item(value, serialize)


def _to_openapi_value(value: Any) -> Any:
    if isinstance(value, list):
        return [_to_openapi_value(item) for item in value]
    if isinstance(value, dict):
        return {key: _to_openapi_value(item) for key, item in value.items()}

    to_openapi_dict = _get_openapi_to_dict(value)
    if to_openapi_dict is not None:
        return to_openapi_dict(value)

    to_dict = getattr(value, "to_dict", None)
    if callable(to_dict):
        return to_dict()
    return value


class V1PodAffinity(BaseModel):
    """
    Pod affinity is a group of inter pod affinity scheduling rules.

    Attributes:
      openapi_types (dict): The key is attribute name
                            and the value is attribute type.
      attribute_map (dict): The key is attribute name
                            and the value is json key in definition.
    """ # noqa: E501
    preferred_during_scheduling_ignored_during_execution: Optional[List[V1WeightedPodAffinityTerm]] = Field(default=None, validation_alias=AliasChoices("preferredDuringSchedulingIgnoredDuringExecution", "preferred_during_scheduling_ignored_during_execution"), serialization_alias="preferredDuringSchedulingIgnoredDuringExecution", description="The scheduler will prefer to schedule pods to nodes that satisfy the affinity expressions specified by this field, but it may choose a node that violates one or more of the expressions. The node that is most preferred is the one with the greatest sum of weights, i.e. for each node that meets all of the scheduling requirements (resource request, requiredDuringScheduling affinity expressions, etc.), compute a sum by iterating through the elements of this field and adding \"weight\" to the sum if the node has pods which matches the corresponding podAffinityTerm; the node(s) with the highest sum are the most preferred.")
    required_during_scheduling_ignored_during_execution: Optional[List[V1PodAffinityTerm]] = Field(default=None, validation_alias=AliasChoices("requiredDuringSchedulingIgnoredDuringExecution", "required_during_scheduling_ignored_during_execution"), serialization_alias="requiredDuringSchedulingIgnoredDuringExecution", description="If the affinity requirements specified by this field are not met at scheduling time, the pod will not be scheduled onto the node. If the affinity requirements specified by this field cease to be met at some point during pod execution (e.g. due to a pod label update), the system may or may not try to eventually evict the pod from its node. When there are multiple elements, the lists of nodes corresponding to each podAffinityTerm are intersected, i.e. all terms must be satisfied.")
    openapi_types: ClassVar[Dict[str, str]] = {
        "preferred_during_scheduling_ignored_during_execution": "List[V1WeightedPodAffinityTerm]",
        "required_during_scheduling_ignored_during_execution": "List[V1PodAffinityTerm]"
    }

    attribute_map: ClassVar[Dict[str, str]] = {
        "preferred_during_scheduling_ignored_during_execution": "preferredDuringSchedulingIgnoredDuringExecution",
        "required_during_scheduling_ignored_during_execution": "requiredDuringSchedulingIgnoredDuringExecution"
    }
    __properties: ClassVar[List[str]] = ["preferredDuringSchedulingIgnoredDuringExecution", "requiredDuringSchedulingIgnoredDuringExecution"]

    @classmethod
    def __preprocess_input_names(
        cls,
        obj: Any,
        remove_hidden_storage_names: bool = True,
    ) -> Any:
        if not isinstance(obj, _Mapping):
            return obj
        obj = dict(obj)
        if "preferredDuringSchedulingIgnoredDuringExecution" not in obj and "preferred_during_scheduling_ignored_during_execution" in obj:
            obj["preferredDuringSchedulingIgnoredDuringExecution"] = obj["preferred_during_scheduling_ignored_during_execution"]
        obj.pop("preferred_during_scheduling_ignored_during_execution", None)
        if "requiredDuringSchedulingIgnoredDuringExecution" not in obj and "required_during_scheduling_ignored_during_execution" in obj:
            obj["requiredDuringSchedulingIgnoredDuringExecution"] = obj["required_during_scheduling_ignored_during_execution"]
        obj.pop("required_during_scheduling_ignored_during_execution", None)
        return obj

    model_config = ConfigDict(
        validate_by_name=True,
        validate_by_alias=True,
        validate_assignment=True,
        extra="forbid",
        protected_namespaces=(),
    )


    def to_str(self) -> str:
        """Returns the string representation of the model"""
        return pprint.pformat(self.to_dict())

    def __repr__(self) -> str:
        """For print and pprint"""
        return self.to_str()

    def __eq__(self, other: object) -> bool:
        """Returns true if both objects are equal"""
        if not isinstance(other, V1PodAffinity):
            return False

        return self.to_dict() == other.to_dict()

    def __ne__(self, other: object) -> bool:
        """Returns true if both objects are not equal"""
        if not isinstance(other, V1PodAffinity):
            return True

        return not (self == other)


    def to_json(self) -> str:
        """Returns the JSON representation of the model using alias"""
        to_openapi_dict = _get_openapi_to_dict(self)
        if to_openapi_dict is not None:
            return json.dumps(to_jsonable_python(to_openapi_dict(self)))
        return json.dumps(to_jsonable_python(self.to_dict()))

    @classmethod
    def from_json(cls, json_str: str) -> Optional[Self]:
        """Create an instance of V1PodAffinity from a JSON string"""
        return cls.from_dict(json.loads(json_str))

    def to_dict(self, serialize: bool = False) -> Dict[str, Any]:
        """Return all declared model fields using public or wire names."""
        return {
            ("preferredDuringSchedulingIgnoredDuringExecution" if serialize else "preferred_during_scheduling_ignored_during_execution"): _to_legacy_value(getattr(self, "preferred_during_scheduling_ignored_during_execution", None), serialize),
            ("requiredDuringSchedulingIgnoredDuringExecution" if serialize else "required_during_scheduling_ignored_during_execution"): _to_legacy_value(getattr(self, "required_during_scheduling_ignored_during_execution", None), serialize),
        }

    def __openapi_generator_modern_projection(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 each item in preferred_during_scheduling_ignored_during_execution (list)
        _items = []
        if self.preferred_during_scheduling_ignored_during_execution:
            for _item_preferred_during_scheduling_ignored_during_execution in self.preferred_during_scheduling_ignored_during_execution:
                _items.append(_to_openapi_value(_item_preferred_during_scheduling_ignored_during_execution) if _item_preferred_during_scheduling_ignored_during_execution is not None else None)
            _dict['preferredDuringSchedulingIgnoredDuringExecution'] = _items
        # override the default output from pydantic by calling `to_dict()` of each item in required_during_scheduling_ignored_during_execution (list)
        _items = []
        if self.required_during_scheduling_ignored_during_execution:
            for _item_required_during_scheduling_ignored_during_execution in self.required_during_scheduling_ignored_during_execution:
                _items.append(_to_openapi_value(_item_required_during_scheduling_ignored_during_execution) if _item_required_during_scheduling_ignored_during_execution is not None else None)
            _dict['requiredDuringSchedulingIgnoredDuringExecution'] = _items
        return _dict

    setattr(
        to_dict,
        _OPENAPI_GENERATOR_TO_DICT,
        __openapi_generator_modern_projection,
    )
    setattr(
        __openapi_generator_modern_projection,
        _OPENAPI_GENERATOR_TO_DICT,
        to_dict,
    )
    del __openapi_generator_modern_projection

    @classmethod
    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
        """Create an instance of V1PodAffinity from a dict"""
        if obj is None:
            return None

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

        obj = _cast(
            Dict[str, Any],
            cls.__preprocess_input_names(
                obj,
                remove_hidden_storage_names=True,
            ),
        )

        _obj = cls.model_validate({
            "preferredDuringSchedulingIgnoredDuringExecution": [V1WeightedPodAffinityTerm.from_dict(_item) for _item in obj["preferredDuringSchedulingIgnoredDuringExecution"]] if obj.get("preferredDuringSchedulingIgnoredDuringExecution") is not None else None,
            "requiredDuringSchedulingIgnoredDuringExecution": [V1PodAffinityTerm.from_dict(_item) for _item in obj["requiredDuringSchedulingIgnoredDuringExecution"]] if obj.get("requiredDuringSchedulingIgnoredDuringExecution") is not None else None
        })
        return _obj