perl/lib/Kubernetes/Object/V2beta1ResourceMetricSource.pm

=begin comment

Kubernetes

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

OpenAPI spec version: v1.13.5

Generated by: https://openapi-generator.tech

=end comment

=cut

#
# NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
# Do not edit the class manually.
# Ref: https://openapi-generator.tech
#
package Kubernetes::Object::V2beta1ResourceMetricSource;

require 5.6.0;
use strict;
use warnings;
use utf8;
use JSON qw(decode_json);
use Data::Dumper;
use Module::Runtime qw(use_module);
use Log::Any qw($log);
use Date::Parse;
use DateTime;


use base ("Class::Accessor", "Class::Data::Inheritable");


#
#ResourceMetricSource indicates how to scale on a resource metric known to Kubernetes, as specified in requests and limits, describing each pod in the current scale target (e.g. CPU or memory).  The values will be averaged together before being compared to the target.  Such metrics are built in to Kubernetes, and have special scaling options on top of those available to normal per-pod metrics using the \"pods\" source.  Only one \"target\" type should be set.
#
# NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech). Do not edit the class manually.
# REF: https://openapi-generator.tech
#

=begin comment

Kubernetes

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

OpenAPI spec version: v1.13.5

Generated by: https://openapi-generator.tech

=end comment

=cut

#
# NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
# Do not edit the class manually.
# Ref: https://openapi-generator.tech
#
__PACKAGE__->mk_classdata('attribute_map' => {});
__PACKAGE__->mk_classdata('openapi_types' => {});
__PACKAGE__->mk_classdata('method_documentation' => {}); 
__PACKAGE__->mk_classdata('class_documentation' => {});

# new object
sub new { 
    my ($class, %args) = @_; 

	my $self = bless {}, $class;
	
	foreach my $attribute (keys %{$class->attribute_map}) {
		my $args_key = $class->attribute_map->{$attribute};
		$self->$attribute( $args{ $args_key } );
	}
	
	return $self;
}  

# return perl hash
sub to_hash {
    return decode_json(JSON->new->convert_blessed->encode( shift ));
}

# used by JSON for serialization
sub TO_JSON { 
    my $self = shift;
    my $_data = {};
    foreach my $_key (keys %{$self->attribute_map}) {
        if (defined $self->{$_key}) {
            $_data->{$self->attribute_map->{$_key}} = $self->{$_key};
        }
    }
    return $_data;
}

# from Perl hashref
sub from_hash {
    my ($self, $hash) = @_;

    # loop through attributes and use openapi_types to deserialize the data
    while ( my ($_key, $_type) = each %{$self->openapi_types} ) {
    	my $_json_attribute = $self->attribute_map->{$_key}; 
        if ($_type =~ /^array\[/i) { # array
            my $_subclass = substr($_type, 6, -1);
            my @_array = ();
            foreach my $_element (@{$hash->{$_json_attribute}}) {
                push @_array, $self->_deserialize($_subclass, $_element);
            }
            $self->{$_key} = \@_array;
        } elsif (exists $hash->{$_json_attribute}) { #hash(model), primitive, datetime
            $self->{$_key} = $self->_deserialize($_type, $hash->{$_json_attribute});
        } else {
        	$log->debugf("Warning: %s (%s) does not exist in input hash\n", $_key, $_json_attribute);
        }
    }
  
    return $self;
}

# deserialize non-array data
sub _deserialize {
    my ($self, $type, $data) = @_;
    $log->debugf("deserializing %s with %s",Dumper($data), $type);
        
    if ($type eq 'DateTime') {
        return DateTime->from_epoch(epoch => str2time($data));
    } elsif ( grep( /^$type$/, ('int', 'double', 'string', 'boolean'))) {
        return $data;
    } else { # hash(model)
        my $_instance = eval "Kubernetes::Object::$type->new()";
        return $_instance->from_hash($data);
    }
}



__PACKAGE__->class_documentation({description => 'ResourceMetricSource indicates how to scale on a resource metric known to Kubernetes, as specified in requests and limits, describing each pod in the current scale target (e.g. CPU or memory).  The values will be averaged together before being compared to the target.  Such metrics are built in to Kubernetes, and have special scaling options on top of those available to normal per-pod metrics using the \"pods\" source.  Only one \"target\" type should be set.',
                                  class => 'V2beta1ResourceMetricSource',
                                  required => [], # TODO
}                                 );

__PACKAGE__->method_documentation({
    'name' => {
    	datatype => 'string',
    	base_name => 'name',
    	description => 'name is the name of the resource in question.',
    	format => '',
    	read_only => '',
    		},
    'target_average_utilization' => {
    	datatype => 'int',
    	base_name => 'targetAverageUtilization',
    	description => 'targetAverageUtilization is the target value of the average of the resource metric across all relevant pods, represented as a percentage of the requested value of the resource for the pods.',
    	format => '',
    	read_only => '',
    		},
    'target_average_value' => {
    	datatype => 'string',
    	base_name => 'targetAverageValue',
    	description => 'targetAverageValue is the target value of the average of the resource metric across all relevant pods, as a raw value (instead of as a percentage of the request), similar to the \"pods\" metric source type.',
    	format => '',
    	read_only => '',
    		},
});

__PACKAGE__->openapi_types( {
    'name' => 'string',
    'target_average_utilization' => 'int',
    'target_average_value' => 'string'
} );

__PACKAGE__->attribute_map( {
    'name' => 'name',
    'target_average_utilization' => 'targetAverageUtilization',
    'target_average_value' => 'targetAverageValue'
} );

__PACKAGE__->mk_accessors(keys %{__PACKAGE__->attribute_map});


1;