# coding: utf-8
# Copyright (c) 2016, 2025, Oracle and/or its affiliates.  All rights reserved.
# This software is dual-licensed to you under the Universal Permissive License (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl or Apache License 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose either license.

# NOTE: This class is auto generated by OracleSDKGenerator. DO NOT EDIT. API Version: 20200601

from .abstract_column import AbstractColumn
from oci.util import formatted_flat_dict, NONE_SENTINEL, value_allowed_none_or_none_sentinel  # noqa: F401
from oci.decorators import init_model_state_from_kwargs


@init_model_state_from_kwargs
class TimeClusterColumn(AbstractColumn):
    """
    Column returned by querylanguage TIMECLUSTER command.
    """

    def __init__(self, **kwargs):
        """
        Initializes a new TimeClusterColumn object with values from keyword arguments. The default value of the :py:attr:`~oci.log_analytics.models.TimeClusterColumn.type` attribute
        of this class is ``TIME_CLUSTER_COLUMN`` and it should not be changed.
        The following keyword arguments are supported (corresponding to the getters/setters of this class):

        :param type:
            The value to assign to the type property of this TimeClusterColumn.
            Allowed values for this property are: "COLUMN", "CHART_COLUMN", "CHART_DATA_COLUMN", "TIME_STATS_COLUMN", "TIME_STATS_DATA_COLUMN", "TIME_CLUSTER_COLUMN", "TIME_CLUSTER_DATA_COLUMN", "TABLE_COLUMN", "TIME_COLUMN", "TREND_COLUMN", "CLASSIFY_COLUMN"
        :type type: str

        :param display_name:
            The value to assign to the display_name property of this TimeClusterColumn.
        :type display_name: str

        :param sub_system:
            The value to assign to the sub_system property of this TimeClusterColumn.
            Allowed values for this property are: "LOG"
        :type sub_system: str

        :param values:
            The value to assign to the values property of this TimeClusterColumn.
        :type values: list[oci.log_analytics.models.FieldValue]

        :param is_list_of_values:
            The value to assign to the is_list_of_values property of this TimeClusterColumn.
        :type is_list_of_values: bool

        :param is_multi_valued:
            The value to assign to the is_multi_valued property of this TimeClusterColumn.
        :type is_multi_valued: bool

        :param is_case_sensitive:
            The value to assign to the is_case_sensitive property of this TimeClusterColumn.
        :type is_case_sensitive: bool

        :param is_groupable:
            The value to assign to the is_groupable property of this TimeClusterColumn.
        :type is_groupable: bool

        :param is_evaluable:
            The value to assign to the is_evaluable property of this TimeClusterColumn.
        :type is_evaluable: bool

        :param is_hidden:
            The value to assign to the is_hidden property of this TimeClusterColumn.
        :type is_hidden: bool

        :param value_type:
            The value to assign to the value_type property of this TimeClusterColumn.
            Allowed values for this property are: "BOOLEAN", "STRING", "DOUBLE", "FLOAT", "LONG", "INTEGER", "TIMESTAMP", "FACET", "TABLE"
        :type value_type: str

        :param original_display_name:
            The value to assign to the original_display_name property of this TimeClusterColumn.
        :type original_display_name: str

        :param internal_name:
            The value to assign to the internal_name property of this TimeClusterColumn.
        :type internal_name: str

        :param interval_gap:
            The value to assign to the interval_gap property of this TimeClusterColumn.
        :type interval_gap: str

        :param intervals:
            The value to assign to the intervals property of this TimeClusterColumn.
        :type intervals: list[int]

        :param group_by_columns:
            The value to assign to the group_by_columns property of this TimeClusterColumn.
        :type group_by_columns: list[oci.log_analytics.models.AbstractColumn]

        :param clusters:
            The value to assign to the clusters property of this TimeClusterColumn.
        :type clusters: dict(str, TimeStatsCluster)

        :param series:
            The value to assign to the series property of this TimeClusterColumn.
        :type series: list[oci.log_analytics.models.TimeClusterDataColumn]

        """
        self.swagger_types = {
            'type': 'str',
            'display_name': 'str',
            'sub_system': 'str',
            'values': 'list[FieldValue]',
            'is_list_of_values': 'bool',
            'is_multi_valued': 'bool',
            'is_case_sensitive': 'bool',
            'is_groupable': 'bool',
            'is_evaluable': 'bool',
            'is_hidden': 'bool',
            'value_type': 'str',
            'original_display_name': 'str',
            'internal_name': 'str',
            'interval_gap': 'str',
            'intervals': 'list[int]',
            'group_by_columns': 'list[AbstractColumn]',
            'clusters': 'dict(str, TimeStatsCluster)',
            'series': 'list[TimeClusterDataColumn]'
        }
        self.attribute_map = {
            'type': 'type',
            'display_name': 'displayName',
            'sub_system': 'subSystem',
            'values': 'values',
            'is_list_of_values': 'isListOfValues',
            'is_multi_valued': 'isMultiValued',
            'is_case_sensitive': 'isCaseSensitive',
            'is_groupable': 'isGroupable',
            'is_evaluable': 'isEvaluable',
            'is_hidden': 'isHidden',
            'value_type': 'valueType',
            'original_display_name': 'originalDisplayName',
            'internal_name': 'internalName',
            'interval_gap': 'intervalGap',
            'intervals': 'intervals',
            'group_by_columns': 'groupByColumns',
            'clusters': 'clusters',
            'series': 'series'
        }
        self._type = None
        self._display_name = None
        self._sub_system = None
        self._values = None
        self._is_list_of_values = None
        self._is_multi_valued = None
        self._is_case_sensitive = None
        self._is_groupable = None
        self._is_evaluable = None
        self._is_hidden = None
        self._value_type = None
        self._original_display_name = None
        self._internal_name = None
        self._interval_gap = None
        self._intervals = None
        self._group_by_columns = None
        self._clusters = None
        self._series = None
        self._type = 'TIME_CLUSTER_COLUMN'

    @property
    def interval_gap(self):
        """
        Gets the interval_gap of this TimeClusterColumn.
        Time span between each timestamp in the timeseries datapoints.


        :return: The interval_gap of this TimeClusterColumn.
        :rtype: str
        """
        return self._interval_gap

    @interval_gap.setter
    def interval_gap(self, interval_gap):
        """
        Sets the interval_gap of this TimeClusterColumn.
        Time span between each timestamp in the timeseries datapoints.


        :param interval_gap: The interval_gap of this TimeClusterColumn.
        :type: str
        """
        self._interval_gap = interval_gap

    @property
    def intervals(self):
        """
        Gets the intervals of this TimeClusterColumn.
        List of timestamps making up the timeseries datapoints.


        :return: The intervals of this TimeClusterColumn.
        :rtype: list[int]
        """
        return self._intervals

    @intervals.setter
    def intervals(self, intervals):
        """
        Sets the intervals of this TimeClusterColumn.
        List of timestamps making up the timeseries datapoints.


        :param intervals: The intervals of this TimeClusterColumn.
        :type: list[int]
        """
        self._intervals = intervals

    @property
    def group_by_columns(self):
        """
        Gets the group_by_columns of this TimeClusterColumn.
        Group by columns specified in the command.


        :return: The group_by_columns of this TimeClusterColumn.
        :rtype: list[oci.log_analytics.models.AbstractColumn]
        """
        return self._group_by_columns

    @group_by_columns.setter
    def group_by_columns(self, group_by_columns):
        """
        Sets the group_by_columns of this TimeClusterColumn.
        Group by columns specified in the command.


        :param group_by_columns: The group_by_columns of this TimeClusterColumn.
        :type: list[oci.log_analytics.models.AbstractColumn]
        """
        self._group_by_columns = group_by_columns

    @property
    def clusters(self):
        """
        Gets the clusters of this TimeClusterColumn.
        Timeseries clusters identified by the command.


        :return: The clusters of this TimeClusterColumn.
        :rtype: dict(str, TimeStatsCluster)
        """
        return self._clusters

    @clusters.setter
    def clusters(self, clusters):
        """
        Sets the clusters of this TimeClusterColumn.
        Timeseries clusters identified by the command.


        :param clusters: The clusters of this TimeClusterColumn.
        :type: dict(str, TimeStatsCluster)
        """
        self._clusters = clusters

    @property
    def series(self):
        """
        Gets the series of this TimeClusterColumn.
        List of series data sets for each statistical function specified in the command.


        :return: The series of this TimeClusterColumn.
        :rtype: list[oci.log_analytics.models.TimeClusterDataColumn]
        """
        return self._series

    @series.setter
    def series(self, series):
        """
        Sets the series of this TimeClusterColumn.
        List of series data sets for each statistical function specified in the command.


        :param series: The series of this TimeClusterColumn.
        :type: list[oci.log_analytics.models.TimeClusterDataColumn]
        """
        self._series = series

    def __repr__(self):
        return formatted_flat_dict(self)

    def __eq__(self, other):
        if other is None:
            return False

        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        return not self == other