eQj/dZddlmZddlZddlZddlZddlmZddl m Z m Z m Z m Z ddlmZmZmZmZmZmZddlmZddlmZdd lmZmZdd lmZdd lmZd Zdd Z ddZ!ddZ"ddZ#Gdde Z$y)a  Kubernetes No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator) The version of the OpenAPI document: release-1.37 Generated by OpenAPI Generator (https://openapi-generator.tech) Do not edit the class manually. ) annotationsN)Mapping) AliasChoices BaseModel ConfigDictField)AnyClassVarDictListOptionalcast)V1PodAffinityTerm)V1WeightedPodAffinityTerm)r Set)Self)to_jsonable_python_openapi_generator_to_dictct|dd}tt|dd}t|rt|dd|uryt|td}t|rt|td|ury|S)Nto_dict__func__)getattrtypecallable_OPENAPI_GENERATOR_TO_DICT)valuer type_to_dictopenapi_to_dicts m/home/oem/CyberBrain26-unified/.venv/lib/python3.12/site-packages/kubernetes/client/models/v1_pod_affinity.py_get_openapi_to_dictr !seY-G4; 48L W  7J -\ A0$O _ %   &      ct|dd}t|t|r ||St|r|S|S)Nr) serialize)rr r)rr#rs r_to_legacy_itemr$<sBeY-GE".8G3D++y Lr!c t|tr|Dcgc]}t||c}St|tr.|j Dcic]\}}|t||c}}St||Scc}wcc}}w)N) isinstancelistr$dictitems)rr#itemkeys r_to_legacy_valuer,Es}%=BCTi0CC%#[[] T y1 1   5) ,, D s A5A:cPt|tr|Dcgc] }t|c}St|tr-|j Dcic]\}}|t|c}}St |}|||St |dd}t|r|S|Scc}wcc}}w)Nr)r&r'_to_openapi_valuer(r)r rr)rr*r+to_openapi_dictrs rr.r.Rs%49:D!$'::%>CkkmLd&t,,LL*51O"u%%eY-Gy L;Ls B B"cneZdZUdZededdddZded<ededd dd Zd ed <d d dZ ded<dddZ ded<ddgZ ded<e d" d#dZ edddddZd$dZd$dZd%dZd%dZd$dZe d&dZd'd(dZd)d Zeeeeeeee[e d*d!Zy)+ V1PodAffinityaH 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. N/preferredDuringSchedulingIgnoredDuringExecution4preferred_during_scheduling_ignored_during_executionalThe 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.)defaultvalidation_aliasserialization_alias descriptionz)Optional[List[V1WeightedPodAffinityTerm]].requiredDuringSchedulingIgnoredDuringExecution3required_during_scheduling_ignored_during_executionaIf 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.z!Optional[List[V1PodAffinityTerm]]zList[V1WeightedPodAffinityTerm]zList[V1PodAffinityTerm])r3r9zClassVar[Dict[str, str]] openapi_types attribute_mapzClassVar[List[str]]_V1PodAffinity__propertiesTct|ts|St|}d|vr d|vr|d|d<|jddd|vr d|vr|d|d<|jdd|S)Nr2r3r8r9)r&_Mappingr(pop)clsobjremove_hidden_storage_namess r__preprocess_input_namesz&V1PodAffinity.__preprocess_input_namesys #x(J3i RHK[\cdhj`bf\girKsAJ =QFIYZabfh]_cZdfoIp  r!cLtg}|jd|d}g}|jr4|jD] }|j| t |nd"||d<g}|j r4|j D] }|j| t |nd"||d<|S)acReturn 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. T)by_aliasexclude exclude_noneNr2r8)set model_dumpr3appendr.r9)rOexcluded_fields_dict_items:_item_preferred_during_scheduling_ignored_during_execution9_item_required_during_scheduling_ignored_during_executions r%__openapi_generator_modern_projectionz3V1PodAffinity.__openapi_generator_modern_projections%() % #     D DNROHOH AJ pjpv/0jk|@A AGMEC D  C CMQNFNF I ohot/0ijz~ FLEB C r!c |yt|ts|j|Sttt t f|j|d}|j|jd&|dDcgc]}tj|c}nd|jd&|dDcgc]}tj|c}ndd}|Scc}wcc}w)z/Create an instance of V1PodAffinity from a dictNT)rBr2r8)r2r8) r&r(model_validate_castr strr &_V1PodAffinity__preprocess_input_namesgetrr^r)r@rA_item_objs rr^zV1PodAffinity.from_dictsD ;#t$%%c* * cN  ( (,0 )  !!twt{t{|mtntzx{}nyo@pot@Y@c@cdi@j@p@Djmjqjqrbjcjoortdpe?ffk?P?Z?Z[`?a?fuy#   @p?fs 6C.C )T)rAr rBboolreturnr )ryrs)rUobjectryrx)r`rsryOptional[Self])F)r#rxryDict[str, Any])ryr|)rAzOptional[Dict[str, Any]]ryr{)__name__ __module__ __qualname____doc__rrr3__annotations__r9r:r;r< classmethodrtr model_configrPrRrVrXr\rar3_V1PodAffinity__openapi_generator_modern_projectionsetattrrr^rEr!rr1r1bsgltxLXYJLBLCYJXHgI8:cI]bkoCOP@BwCxN~Lp ^q 79Zq @a?X/M+ Ar?o/M+*[]M)NL%N-1 &*    L.1#>33 @ "-  -" .r!r1)rr ryr )rr r#rxryr )%r __future__rrLrerZcollections.abcrr>pydanticrrrrtypingr r r r r rrr-kubernetes.client.models.v1_pod_affinity_termr6kubernetes.client.models.v1_weighted_pod_affinity_termrrtyping_extensionsr pydantic_corerrr r$r,r.r1rEr!rrs` # /??EEK\ ",:6 -  \I\r!