"""Index List Class"""

# pylint: disable=R0904,R0913,R0917
import re
import itertools
import logging
from elasticsearch8.exceptions import NotFoundError, TransportError
from es_client.helpers.schemacheck import SchemaCheck
from es_client.helpers.utils import ensure_list
from curator.defaults import settings
from curator.exceptions import (
    ActionError,
    ConfigurationError,
    MissingArgument,
    NoIndices,
)
from curator.helpers.date_ops import (
    absolute_date_range,
    date_range,
    fix_epoch,
    get_date_regex,
    get_point_of_reference,
    get_unit_count_from_name,
    TimestringSearch,
)
from curator.helpers.getters import byte_size, get_indices
from curator.helpers.testers import verify_client_object
from curator.helpers.utils import chunk_index_list, report_failure, to_csv
from curator.validators.filter_functions import filterstructure


class IndexList:
    """IndexList class"""

    def __init__(self, client, search_pattern='*', include_hidden=False):
        verify_client_object(client)
        self.loggit = logging.getLogger('curator.indexlist')
        #: An :py:class:`~.elasticsearch.Elasticsearch` client object passed from
        #: param ``client``
        self.client = client
        #: Information extracted from indices, such as segment count, age, etc.
        #: Populated at instance creation time by private helper methods.
        #: **Type:** :py:class:`dict`
        self.index_info = {}
        #: The running list of indices which will be used by one of the
        #: :py:mod:`~.curator.actions` classes. Populated at instance creation
        #: time by private helper methods. **Type:** :py:class:`list`
        self.indices = []
        #: All indices in the cluster at instance creation time.
        #: **Type:** :py:class:`list`
        self.all_indices = []
        self.__get_indices(search_pattern, include_hidden)
        self.age_keyfield = None

    def __actionable(self, idx):
        self.loggit.debug('Index %s is actionable and remains in the list.', idx)

    def __not_actionable(self, idx):
        self.loggit.debug('Index %s is not actionable, removing from list.', idx)
        self.indices.remove(idx)

    def __excludify(self, condition, exclude, index, msg=None):
        if condition is True:
            if exclude:
                text = "Removed from actionable list"
                self.__not_actionable(index)
            else:
                text = "Remains in actionable list"
                self.__actionable(index)
        else:
            if exclude:
                text = "Remains in actionable list"
                self.__actionable(index)
            else:
                text = "Removed from actionable list"
                self.__not_actionable(index)
        if msg:
            self.loggit.debug('%s: %s', text, msg)

    def __get_indices(self, pattern, include_hidden):
        """
        Pull all indices into ``all_indices``, then populate ``indices`` and
        ``index_info``
        """
        self.loggit.debug('Getting indices matching search_pattern: "%s"', pattern)
        self.all_indices = get_indices(
            self.client, search_pattern=pattern, include_hidden=include_hidden
        )
        self.indices = self.all_indices[:]
        # if self.indices:
        #     for index in self.indices:
        #         self.__build_index_info(index)

    def __build_index_info(self, index):
        """
        Ensure that ``index`` is a key in ``index_info``. If not, create a
        sub-dictionary structure under that key.
        """
        self.loggit.debug('Building preliminary index metadata for %s', index)
        if index not in self.index_info:
            self.index_info[index] = self.__zero_values()

    def __map_method(self, ftype):
        methods = {
            'alias': self.filter_by_alias,
            'age': self.filter_by_age,
            'allocated': self.filter_allocated,
            'closed': self.filter_closed,
            'count': self.filter_by_count,
            'empty': self.filter_empty,
            'forcemerged': self.filter_forceMerged,
            'ilm': self.filter_ilm,
            'kibana': self.filter_kibana,
            'none': self.filter_none,
            'opened': self.filter_opened,
            'period': self.filter_period,
            'pattern': self.filter_by_regex,
            'space': self.filter_by_space,
            'shards': self.filter_by_shards,
            'size': self.filter_by_size,
        }
        return methods[ftype]

    def __remove_missing(self, err):
        """
        Remove missing index found in ``err`` from self.indices and return that name
        """
        missing = err.info['error']['index']
        self.loggit.warning('Index was initiallly present, but now is not: %s', missing)
        self.loggit.debug('Removing %s from active IndexList', missing)
        self.indices.remove(missing)
        return missing

    def __zero_values(self):
        """The default values for index metadata"""
        return {
            'age': {'creation_date': 0, 'name': 0},
            'docs': 0,
            'number_of_replicas': 0,
            'number_of_shards': 0,
            'primary_size_in_bytes': 0,
            'routing': {},
            'segments': 0,
            'size_in_bytes': 0,
            'state': '',
        }

    def _get_indices_segments(self, data):
        return self.client.indices.segments(index=to_csv(data))['indices'].copy()

    def _get_indices_settings(self, data):
        return self.client.indices.get_settings(index=to_csv(data))

    def _get_indices_stats(self, data):
        return self.client.indices.stats(index=to_csv(data), metric='store,docs')[
            'indices'
        ]

    def _bulk_queries(self, data, exec_func):
        slice_number = 10
        query_result = {}
        loop_number = (
            round(len(data) / slice_number)
            if round(len(data) / slice_number) > 0
            else 1
        )
        self.loggit.debug("Bulk Queries - number requests created: %s", loop_number)
        for num in range(0, loop_number):
            if num == (loop_number - 1):
                data_sliced = data[num * slice_number :]
            else:
                data_sliced = data[num * slice_number : (num + 1) * slice_number]
            query_result.update(exec_func(data_sliced))
        return query_result

    def mitigate_alias(self, index):
        """
        Mitigate when an alias is detected instead of an index name

        :param index: The index name that is showing up *instead* of what was expected

        :type index: str

        :returns: No return value:
        :rtype: None
        """
        self.loggit.debug('BEGIN mitigate_alias')
        self.loggit.debug(
            'Correcting an instance where an alias name points to index "%s"', index
        )
        data = self.client.indices.get(index=index)
        aliases = list(data[index]['aliases'])
        if aliases:
            for alias in aliases:
                if alias in self.indices:
                    self.loggit.warning(
                        'Removing alias "%s" from IndexList.indices', alias
                    )
                    self.indices.remove(alias)
                if alias in list(self.index_info):
                    self.loggit.warning(
                        'Removing alias "%s" from IndexList.index_info', alias
                    )
                    del self.index_info[alias]
        self.loggit.debug('Adding "%s" to IndexList.indices', index)
        self.indices.append(index)
        self.loggit.debug(
            'Adding preliminary metadata for "%s" to IndexList.index_info', index
        )
        self.__build_index_info(index)
        self.loggit.debug('END mitigate_alias')

    def alias_index_check(self, data):
        """
        Check each index in data to see if it's an alias.
        """
        # self.loggit.debug('BEGIN alias_index_check')
        working_list = data[:]
        for entry in working_list:
            if self.client.indices.exists_alias(name=entry):
                index = list(self.client.indices.get_alias(name=entry).keys())[0]
                self.loggit.warning(
                    '"%s" is actually an alias for index "%s"', entry, index
                )
                self.mitigate_alias(index)
                # The mitigate_alias step ensures that the class ivars are handled
                # properly. The following ensure that we pass back a modified list
                data.remove(entry)
                data.append(index)
        # self.loggit.debug('END alias_index_check')
        return data

    def indices_exist(self, data, exec_func):
        """Check if indices exist. If one doesn't, remove it. Loop until all exist"""
        self.loggit.debug('BEGIN indices_exist')
        checking = True
        working_list = {}
        verified_data = self.alias_index_check(data)
        while checking:
            try:
                working_list.update(exec_func(verified_data))
            except NotFoundError as err:
                data.remove(self.__remove_missing(err))
                continue
            except TransportError as err:
                if '413' in err.errors:
                    msg = (
                        'Huge Payload 413 Err - Trying to get information via '
                        'multiple requests'
                    )
                    self.loggit.debug(msg)
                    working_list.update(self._bulk_queries(verified_data, exec_func))
            checking = False
        # self.loggit.debug('END indices_exist')
        return working_list

    def data_getter(self, data, exec_func):
        """
        Function that prevents unnecessary code repetition for different data
        getter methods
        """
        self.loggit.debug('BEGIN data_getter')
        checking = True
        while checking:
            working_list = self.indices_exist(data, exec_func)
            if working_list:
                for index in list(working_list.keys()):
                    try:
                        sii = self.index_info[index]
                    except KeyError:
                        self.loggit.warning(
                            'Index %s was not present at IndexList initialization, '
                            ' and may be behind an alias',
                            index,
                        )
                        self.mitigate_alias(index)
                        sii = self.index_info[index]
                        working_list = {}
                        try:
                            working_list.update(self._bulk_queries(data, exec_func))
                        except NotFoundError as err:
                            data.remove(self.__remove_missing(err))
                            continue
                    yield sii, working_list[index], index
            checking = False
        # self.loggit.debug('END data_getter')

    def population_check(self, index, key):
        """Verify that key is in self.index_info[index], and that it is populated"""
        retval = True
        # self.loggit.debug('BEGIN population_check')
        # self.loggit.debug('population_check: %s, %s', index, key)
        if index not in self.index_info:
            # This is just in case the index was somehow not populated
            self.__build_index_info(index)
        if key not in self.index_info[index]:
            self.index_info[index][key] = self.__zero_values()[key]
        if self.index_info[index][key] == self.__zero_values()[key]:
            retval = False
        # self.loggit.debug('END population_check')
        return retval

    def needs_data(self, indices, fields):
        """Check for data population in self.index_info"""
        self.loggit.debug('Indices: %s, Fields: %s', indices, fields)
        needful = []
        working_list = self.indices_exist(indices, self._get_indices_settings)
        for idx in working_list:
            count = 0
            for field in fields:
                # If the return value is True for this field, it means it's populated
                if self.population_check(idx, field):
                    count += 1
            if count == 0:
                # All values are the default/zero
                needful.append(idx)
        if fields == ['state']:
            self.loggit.debug('Always check open/close for all passed indices')
            needful = list(working_list.keys())
        self.loggit.debug('These indices need data in index_info: %s', needful)
        return needful

    def get_index_settings(self):
        """
        For each index in self.indices, populate ``index_info`` with:
            creation_date
            number_of_replicas
            number_of_shards
            routing information (if present)
        """
        self.loggit.debug('Getting index settings -- BEGIN')
        self.empty_list_check()
        fields = ['age', 'number_of_replicas', 'number_of_shards', 'routing']
        for lst in chunk_index_list(self.indices):
            # This portion here is to ensure that we're not polling for data
            # unless we must
            needful = self.needs_data(lst, fields)
            if not needful:
                # All indices are populated with some data, so we can skip
                # data collection
                continue
            # Now we only need to run on the 'needful'
            for sii, wli, _ in self.data_getter(needful, self._get_indices_settings):
                sii['age']['creation_date'] = fix_epoch(
                    wli['settings']['index']['creation_date']
                )
                sii['number_of_replicas'] = wli['settings']['index'][
                    'number_of_replicas'
                ]
                sii['number_of_shards'] = wli['settings']['index']['number_of_shards']
                if 'routing' in wli['settings']['index']:
                    sii['routing'] = wli['settings']['index']['routing']
        self.loggit.debug('Getting index settings -- END')

    def get_index_state(self):
        """
        For each index in self.indices, populate ``index_info`` with:

            state (open or closed)

        from the cat API
        """
        self.loggit.debug('Getting index state -- BEGIN')
        self.empty_list_check()
        fields = ['state']
        for lst in chunk_index_list(self.indices):
            # This portion here is to ensure that we're not polling for data
            # unless we must
            needful = self.needs_data(lst, fields)
            # Checking state is _always_ needful.
            resp = self.client.cat.indices(
                index=to_csv(needful), format='json', h='index,status'
            )
            for entry in resp:
                try:
                    self.index_info[entry['index']]['state'] = entry['status']
                except KeyError:
                    self.loggit.warning(
                        'Index %s was not present at IndexList initialization, '
                        'and may be behind an alias',
                        entry['index'],
                    )
                    self.mitigate_alias(entry['index'])
                    self.index_info[entry['index']]['state'] = entry['status']
        # self.loggit.debug('Getting index state -- END')

    def get_index_stats(self):
        """
        Populate ``index_info`` with index ``size_in_bytes``,
        ``primary_size_in_bytes`` and doc count information for each index.
        """
        self.loggit.debug('Getting index stats -- BEGIN')
        self.empty_list_check()
        fields = ['size_in_bytes', 'docs', 'primary_size_in_bytes']
        # This ensures that the index state is populated
        self.get_index_state()
        # Don't populate working_list until after the get_index state as it
        # can and will remove missing indices
        working_list = self.working_list()
        for index in self.working_list():
            if self.index_info[index]['state'] == 'close':
                working_list.remove(index)
        if working_list:
            index_lists = chunk_index_list(working_list)
            for lst in index_lists:
                # This portion here is to ensure that we're not polling for data
                # unless we must
                needful = self.needs_data(lst, fields)
                if not needful:
                    # All indices are populated with some data, so we can skip
                    # data collection
                    continue
                # Now we only need to run on the 'needful'
                for sii, wli, index in self.data_getter(
                    needful, self._get_indices_stats
                ):
                    try:
                        size = wli['total']['store']['size_in_bytes']
                        docs = wli['total']['docs']['count']
                        primary_size = wli['primaries']['store']['size_in_bytes']
                        msg = (
                            f'Index: {index}  Size: {byte_size(size)}  Docs: {docs} '
                            f'PrimarySize: {byte_size(primary_size)}'
                        )
                        self.loggit.debug(msg)
                        sii['size_in_bytes'] = size
                        sii['docs'] = docs
                        sii['primary_size_in_bytes'] = primary_size
                    except KeyError:
                        msg = f'Index stats missing for "{index}" -- might be closed'
                        self.loggit.warning(msg)
        # self.loggit.debug('Getting index stats -- END')

    def get_segment_counts(self):
        """
        Populate ``index_info`` with segment information for each index.
        """
        self.loggit.debug('Getting index segment counts')
        self.empty_list_check()
        for lst in chunk_index_list(self.indices):
            for sii, wli, _ in self.data_getter(lst, self._get_indices_segments):
                shards = wli['shards']
                segmentcount = 0
                for shardnum in shards:
                    for shard in range(0, len(shards[shardnum])):
                        segmentcount += shards[shardnum][shard]['num_search_segments']
                sii['segments'] = segmentcount

    def empty_list_check(self):
        """Raise :py:exc:`~.curator.exceptions.NoIndices` if ``indices`` is empty"""
        self.loggit.debug('Checking for empty list')
        if not self.indices:
            msg = 'IndexList object is empty. No indices to act on.'
            self.loggit.debug(msg)
            raise NoIndices(msg)

    def working_list(self):
        """
        Return the current value of ``indices`` as copy-by-value to prevent list
        stomping during iterations
        """
        # Copy by value, rather than reference to prevent list stomping during
        # iterations
        self.loggit.debug('Generating working list of indices')
        return self.indices[:]

    def _get_name_based_ages(self, timestring):
        """
        Add indices to ``index_info`` based on the age as indicated by the index
        name pattern, if it matches ``timestring``

        :param timestring: An :py:func:`time.strftime` pattern
        """
        # Check for empty list before proceeding here to prevent non-iterable condition
        self.loggit.debug('Getting ages of indices by "name"')
        self.empty_list_check()
        tstr = TimestringSearch(timestring)
        for index in self.working_list():
            epoch = tstr.get_epoch(index)
            if isinstance(epoch, int):
                self.index_info[index]['age']['name'] = epoch
            else:
                msg = (
                    f'Timestring {timestring} was not found in index {index}. '
                    f'Removing from actionable list'
                )
                self.loggit.debug(msg)
                self.indices.remove(index)

    def _get_field_stats_dates(self, field='@timestamp'):
        """
        Add indices to ``index_info`` based on the values the queries return, as
        determined by the min and max aggregated values of ``field``

        :param field: The field with the date value.  The field must be mapped in
            elasticsearch as a date datatype. Default: ``@timestamp``
        """
        self.loggit.debug('Cannot query closed indices. Omitting any closed indices.')
        self.filter_closed()
        self.loggit.debug(
            'Cannot use field_stats with empty indices. Omitting any empty indices.'
        )
        self.filter_empty()
        self.loggit.debug(
            'Getting index date by querying indices for min & max value of %s field',
            field,
        )
        self.empty_list_check()
        index_lists = chunk_index_list(self.indices)
        for lst in index_lists:
            for index in lst:
                aggs = {
                    'min': {'min': {'field': field}},
                    'max': {'max': {'field': field}},
                }
                response = self.client.search(index=index, size=0, aggs=aggs)
                self.loggit.debug('RESPONSE: %s', response)
                if response:
                    try:
                        res = response['aggregations']
                        self.loggit.debug('res: %s', res)
                        data = self.index_info[index]['age']
                        data['min_value'] = fix_epoch(res['min']['value'])
                        data['max_value'] = fix_epoch(res['max']['value'])
                        self.loggit.debug('data: %s', data)
                    except KeyError as exc:
                        raise ActionError(
                            f'Field "{field}" not found in index "{index}"'
                        ) from exc

    def _calculate_ages(
        self, source=None, timestring=None, field=None, stats_result=None
    ):
        """
        This method initiates index age calculation based on the given parameters.
        Exceptions are raised when they are improperly configured.

        Set instance variable ``age_keyfield`` for use later, if needed.

        :param source: Source of index age. Can be: ``name``, ``creation_date``,
            or ``field_stats``
        :param timestring: An :py:func:`time.strftime` string to match the datestamp
            in an index name. Only used for index filtering by ``name``.
        :param field: A timestamp field name.  Only used for ``field_stats`` based
            calculations.
        :param stats_result: Either ``min_value`` or ``max_value``.  Only used
            in conjunction with ``source=field_stats`` to choose whether to reference
            the min or max result value.
        """
        self.age_keyfield = source
        if source == 'name':
            if not timestring:
                raise MissingArgument(
                    'source "name" requires the "timestring" keyword argument'
                )
            self._get_name_based_ages(timestring)
        elif source == 'creation_date':
            # Nothing to do here as this comes from `get_settings` in __init__
            pass
        elif source == 'field_stats':
            if not field:
                raise MissingArgument(
                    'source "field_stats" requires the "field" keyword argument'
                )
            if stats_result not in ['min_value', 'max_value']:
                raise ValueError(f'Invalid value for "stats_result": {stats_result}')
            self.age_keyfield = stats_result
            self._get_field_stats_dates(field=field)
        else:
            raise ValueError(
                f'Invalid source: {source}. Must be one of "name", "creation_date", '
                f'"field_stats".'
            )

    def _sort_by_age(self, index_list, reverse=True):
        """
        Take a list of indices and sort them by date.

        By default, the youngest are first with ``reverse=True``, but the oldest
        can be first by setting ``reverse=False``
        """
        # Do the age-based sorting here.
        # Build an temporary dictionary with just index and age as the key and
        # value, respectively
        temp = {}
        for index in index_list:
            try:
                if self.index_info[index]['age'][self.age_keyfield]:
                    temp[index] = self.index_info[index]['age'][self.age_keyfield]
                else:
                    msg = (
                        f'No date for "{index}" in IndexList metadata. '
                        f'Possible timestring mismatch. Excluding index "{index}".'
                    )
                    self.__excludify(True, True, index, msg)
            except KeyError:
                msg = (
                    f'{index} does not have key "{self.age_keyfield}" in IndexList '
                    f'metadata'
                )
                self.__excludify(True, True, index, msg)
        # Sort alphabetically prior to age sort to keep sorting consistent
        temp_tuple = sorted(temp.items(), key=lambda k: k[0], reverse=reverse)
        # If reverse is True, this will sort so the youngest indices are first.
        # However, if you want oldest first, set reverse to False.
        # Effectively, this should set us up to act on everything older than
        # meets the other set criteria. It starts as a tuple, but then becomes a list.
        sorted_tuple = sorted(temp_tuple, key=lambda k: k[1], reverse=reverse)
        return [x[0] for x in sorted_tuple]

    def filter_by_regex(self, kind=None, value=None, exclude=False):
        """
        Match indices by regular expression (pattern).

        :param kind: Can be one of: ``suffix``, ``prefix``, ``regex``, or
            ``timestring``. This option defines what ``kind`` of filter you will
            be building.
        :param value: Depends on ``kind``. It is the :py:func:`time.strftime` string if
            ``kind`` is ``timestring``. It's used to build the regular expression
            for other kinds.
        :param exclude: If ``exclude=True``, this filter will remove matching
            indices from ``indices``. If ``exclude=False``, then only matching
            indices will be kept in ``indices``. Default is ``False``
        """
        self.loggit.debug('Filtering indices by regex')
        if kind not in ['regex', 'prefix', 'suffix', 'timestring']:
            raise ValueError(f'{kind}: Invalid value for kind')
        # Stop here if None or empty value, but zero is okay
        if value == 0:
            pass
        elif not value:
            raise ValueError(
                'Invalid None value for "value". Cannot be "None" type, empty, or False'
            )
        if kind == 'timestring':
            regex = settings.regex_map()[kind].format(get_date_regex(value))
        else:
            regex = settings.regex_map()[kind].format(value)
        self.empty_list_check()
        pattern = re.compile(regex)
        for index in self.working_list():
            self.loggit.debug('Filter by regex: Index: %s', index)
            match = pattern.search(index)
            if match:
                self.__excludify(True, exclude, index)
            else:
                self.__excludify(False, exclude, index)

    def filter_by_age(
        self,
        source='name',
        direction=None,
        timestring=None,
        unit=None,
        unit_count=None,
        field=None,
        stats_result='min_value',
        epoch=None,
        exclude=False,
        unit_count_pattern=False,
    ):
        """
        Match indices by relative age calculations.

        :param source: Source of index age. Can be one of ``name``, ``creation_date``,
            or ``field_stats``
        :param direction: Time to filter, either ``older`` or ``younger``
        :param timestring: An :py:func:`time.strftime` string to match the datestamp
            in an index name. Only used for index filtering by ``name``.
        :param unit: One of ``seconds``, ``minutes``, ``hours``, ``days``, ``weeks``,
            ``months``, or ``years``.
        :param unit_count: The count of ``unit``. ``unit_count`` * ``unit`` will
            be calculated out to the relative number of seconds.
        :param unit_count_pattern: A regular expression whose capture group identifies
            the value for ``unit_count``.
        :param field: A timestamp field name.  Only used for ``field_stats`` based
            calculations.
        :param stats_result: Either ``min_value`` or ``max_value``.  Only used
            in conjunction with ``source=field_stats`` to choose whether to reference
            the minimum or maximum result value.
        :param epoch: An epoch timestamp used in conjunction with ``unit`` and
            ``unit_count`` to establish a point of reference for calculations.
            If not provided, the current time will be used.
        :param exclude: If ``exclude=True``, this filter will remove matching
            indices from ``indices``. If ``exclude`` is `False`, then only matching
            indices will be kept in ``indices``. Default is ``False``
        """
        self.loggit.debug('Filtering indices by age')
        # Get timestamp point of reference, por
        por = get_point_of_reference(unit, unit_count, epoch)
        if not direction:
            raise MissingArgument('Must provide a value for "direction"')
        if direction not in ['older', 'younger']:
            raise ValueError(f'Invalid value for "direction": {direction}')
        # This filter requires index settings.
        self.get_index_settings()
        self._calculate_ages(
            source=source, timestring=timestring, field=field, stats_result=stats_result
        )
        if unit_count_pattern:
            try:
                unit_count_matcher = re.compile(unit_count_pattern)
            # pylint: disable=broad-except
            except Exception as exc:
                # We got an illegal regex, so won't be able to match anything
                self.loggit.error(
                    'Regular expression failure. Will not match unit count. Error: %s',
                    exc,
                )
                unit_count_matcher = None
        for index in self.working_list():
            try:
                remove_this_index = False
                age = int(self.index_info[index]['age'][self.age_keyfield])
                # if age == 0:
                #     msg = (
                #         f'Evaluating {index} resulted in an epoch timestamp of '
                #         f'0, meaning there is no associated date. Removing from '
                #         f'the actionable list.'
                #     )
                #     self.loggit.debug(msg)
                #     self.indices.remove(index)
                #     continue
                msg = (
                    f'Index "{index}" age ({age}), direction: "{direction}", point of '
                    f'reference, ({por})'
                )
                # Because time adds to epoch, smaller numbers are actually older
                # timestamps.
                if unit_count_pattern:
                    msg = (
                        f'unit_count_pattern is set, trying to match pattern to '
                        f'index "{index}"'
                    )
                    self.loggit.debug(msg)
                    unit_count_from_index = get_unit_count_from_name(
                        index, unit_count_matcher
                    )
                    if unit_count_from_index:
                        self.loggit.debug(
                            'Pattern matched, applying unit_count of  "%s"',
                            unit_count_from_index,
                        )
                        adjustedpor = get_point_of_reference(
                            unit, unit_count_from_index, epoch
                        )
                        msg = (
                            f'Adjusting point of reference from {por} to {adjustedpor} '
                            f'based on unit_count of {unit_count_from_index} from '
                            f'index name'
                        )
                        self.loggit.debug(msg)
                    elif unit_count == -1:
                        # Unable to match pattern and unit_count is -1, meaning no
                        # fallback, so this index is removed from the list
                        msg = (
                            f'Unable to match pattern and no fallback value set. '
                            f'Removing index "{index}" from actionable list'
                        )
                        self.loggit.debug(msg)
                        remove_this_index = True
                        adjustedpor = por
                        # necessary to avoid exception if the first index is excluded
                    else:
                        # Unable to match the pattern and unit_count is set, so
                        # fall back to using unit_count for determining whether
                        # to keep this index in the list
                        self.loggit.debug(
                            'Unable to match pattern using fallback value of "%s"',
                            unit_count,
                        )
                        adjustedpor = por
                else:
                    adjustedpor = por
                if direction == 'older':
                    agetest = age < adjustedpor
                else:
                    agetest = age > adjustedpor
                self.__excludify(agetest and not remove_this_index, exclude, index, msg)
            except KeyError:
                msg = (
                    f'Index "{index}" does not meet provided criteria. '
                    f'Removing from list.'
                )
                self.loggit.debug(msg)
                self.indices.remove(index)

    def filter_by_space(
        self,
        disk_space=None,
        reverse=True,
        use_age=False,
        source='creation_date',
        timestring=None,
        field=None,
        stats_result='min_value',
        exclude=False,
        threshold_behavior='greater_than',
    ):
        """
        Remove indices from the actionable list based on space consumed, sorted
        reverse-alphabetically by default.  If you set ``reverse`` to ``False``,
        it will be sorted alphabetically.

        The default is usually what you will want. If only one kind of index is
        provided--for example, indices matching ``logstash-%Y.%m.%d`` --then
        reverse alphabetical sorting will mean the oldest will remain in the list,
        because lower numbers in the dates mean older indices.

        By setting ``reverse`` to ``False``, then ``index3`` will be deleted before
        ``index2``, which will be deleted before ``index1``

        ``use_age`` allows ordering indices by age. Age is determined by the
        index creation date by default, but you can specify an ``source`` of
        ``name``, ``max_value``, or ``min_value``. The ``name`` ``source`` requires
        the timestring argument.

        ``threshold_behavior``, when set to ``greater_than`` (default), includes
        if it the index tests to be larger than ``disk_space``. When set to
        ``less_than``, it includes if the index is smaller than ``disk_space``

        :param disk_space: Filter indices over *n* gigabytes
        :param threshold_behavior: Size to filter, either ``greater_than`` or
            ``less_than``. Defaults to ``greater_than`` to preserve backwards
            compatability.
        :param reverse: The filtering direction. (default: ``True``).  Ignored if
            ``use_age`` is ``True``
        :param use_age: Sort indices by age.  ``source`` is required in this case.
        :param source: Source of index age. Can be one of ``name``, ``creation_date``,
            or ``field_stats``. Default: ``creation_date``
        :param timestring: An :py:func:`time.strftime` string to match the datestamp
            in an index name. Only used if ``source=name`` is selected.
        :param field: A timestamp field name.  Only used if ``source=field_stats``
            is selected.
        :param stats_result: Either ``min_value`` or ``max_value``.  Only used if
            ``source=field_stats`` is selected. It determines whether to reference
            the minimum or maximum value of `field` in each index.
        :param exclude: If ``exclude=True``, this filter will remove matching
            indices from ``indices``. If ``exclude=False``, then only matching
            indices will be kept in ``indices``. Default is ``False``
        """
        self.loggit.debug('Filtering indices by disk space')
        # Ensure that disk_space is a float
        if not disk_space:
            raise MissingArgument('No value for "disk_space" provided')
        if threshold_behavior not in ['greater_than', 'less_than']:
            raise ValueError(
                f'Invalid value for "threshold_behavior": {threshold_behavior}'
            )
        # This filter requires both index stats and index settings
        self.get_index_stats()
        self.get_index_settings()
        disk_space = float(disk_space)
        disk_usage = 0.0
        disk_limit = disk_space * 2**30
        msg = (
            'Cannot get disk usage info from closed indices. Omitting any '
            'closed indices.'
        )
        self.loggit.debug(msg)
        self.filter_closed()
        if use_age:
            self._calculate_ages(
                source=source,
                timestring=timestring,
                field=field,
                stats_result=stats_result,
            )
            # Using default value of reverse=True in self._sort_by_age()
            self.loggit.debug('SORTING BY AGE')
            sorted_indices = self._sort_by_age(self.working_list())
        else:
            # Default to sorting by index name
            sorted_indices = sorted(self.working_list(), reverse=reverse)
        for index in sorted_indices:
            disk_usage += self.index_info[index]['size_in_bytes']
            msg = (
                f'{index}, summed disk usage is {byte_size(disk_usage)} and disk limit '
                f'is {byte_size(disk_limit)}.'
            )
            if threshold_behavior == 'greater_than':
                self.__excludify((disk_usage > disk_limit), exclude, index, msg)
            elif threshold_behavior == 'less_than':
                self.__excludify((disk_usage < disk_limit), exclude, index, msg)

    def filter_kibana(self, exclude=True):
        """
        Match any index named ``.kibana*`` in ``indices``. Older releases addressed
        index names that no longer exist.

        :param exclude: If ``exclude=True``, this filter will remove matching
            indices from ``indices``. If ``exclude=False``, then only matching
            indices will be kept in ``indices``. Default is ``True``
        """
        self.loggit.debug('Filtering kibana indices')
        self.empty_list_check()
        for index in self.working_list():
            pattern = re.compile(r'^\.kibana.*$')
            if pattern.match(index):
                self.__excludify(True, exclude, index)
            else:
                self.__excludify(False, exclude, index)

    def filter_forceMerged(self, max_num_segments=None, exclude=True):
        """
        Match any index which has ``max_num_segments`` per shard or fewer in the
        actionable list.

        :param max_num_segments: Cutoff number of segments per shard.
        :param exclude: If ``exclude=True``, this filter will remove matching
            indices from ``indices``. If ``exclude=False``, then only matching
            indices will be kept in ``indices``. Default is ``True``
        """
        self.loggit.debug('Filtering forceMerged indices')
        if not max_num_segments:
            raise MissingArgument('Missing value for "max_num_segments"')
        self.loggit.debug(
            'Cannot get segment count of closed indices. Omitting any closed indices.'
        )
        # This filter requires the index state (open/close), and index settings.
        self.get_index_state()
        self.get_index_settings()
        self.filter_closed()
        self.get_segment_counts()
        for index in self.working_list():
            # Do this to reduce long lines and make it more readable...
            shards = int(self.index_info[index]['number_of_shards'])
            replicas = int(self.index_info[index]['number_of_replicas'])
            segments = int(self.index_info[index]['segments'])
            msg = (
                f'{index} has {shards} shard(s) + {replicas} replica(s) '
                f'with a sum total of {segments} segments.'
            )
            expected_count = (shards + (shards * replicas)) * max_num_segments
            self.__excludify((segments <= expected_count), exclude, index, msg)

    def filter_closed(self, exclude=True):
        """
        Filter out closed indices from ``indices``

        :param exclude: If ``exclude=True``, this filter will remove matching
            indices from ``indices``. If ``exclude=False``, then only matching
            indices will be kept in ``indices``. Default is ``True``
        """
        self.loggit.debug('Filtering closed indices')
        # This filter requires index state (open/close)
        self.get_index_state()
        self.empty_list_check()
        for index in self.working_list():
            condition = self.index_info[index]['state'] == 'close'
            self.loggit.debug(
                'Index %s state: %s', index, self.index_info[index]['state']
            )
            self.__excludify(condition, exclude, index)

    def filter_empty(self, exclude=True):
        """
        Filter indices with a document count of zero. Indices that are closed
        are automatically excluded from consideration due to closed indices reporting
        a document count of zero.

        :param exclude: If ``exclude=True``, this filter will remove matching indices
            from ``indices``. If ``exclude=False``, then only matching indices
            will be kept in ``indices``. Default is ``True``
        """
        self.loggit.debug('Filtering empty indices')
        # This index requires index state (open/close) and index stats
        self.get_index_state()
        self.get_index_stats()
        self.filter_closed()
        self.empty_list_check()
        for index in self.working_list():
            condition = self.index_info[index]['docs'] == 0
            self.loggit.debug(
                'Index %s doc count: %s', index, self.index_info[index]['docs']
            )
            self.__excludify(condition, exclude, index)

    def filter_opened(self, exclude=True):
        """
        Filter out opened indices from ``indices``

        :param exclude: If ``exclude=True``, this filter will remove matching indices
            from ``indices``. If ``exclude=False``, then only matching indices
            will be kept in ``indices``. Default is ``True``
        """
        self.loggit.debug('Filtering open indices')
        # This filter requires index state (open/close)
        self.get_index_state()
        self.empty_list_check()
        for index in self.working_list():
            condition = self.index_info[index]['state'] == 'open'
            self.loggit.debug(
                'Index %s state: %s', index, self.index_info[index]['state']
            )
            self.__excludify(condition, exclude, index)

    def filter_allocated(
        self, key=None, value=None, allocation_type='require', exclude=True
    ):
        """
        Match indices that have the routing allocation rule of ``key=value`` from
        ``indices``

        :param key: The allocation attribute to check for
        :param value: The value to check for
        :param allocation_type: Type of allocation to apply
        :param exclude: If ``exclude=True``, this filter will remove matching indices
            from ``indices``. If ``exclude=False``, then only matching indices
            will be kept in ``indices``. Default is `T`rue`
        """
        self.loggit.debug('Filtering indices with shard routing allocation rules')
        if not key:
            raise MissingArgument('No value for "key" provided')
        if not value:
            raise MissingArgument('No value for "value" provided')
        if allocation_type not in ['include', 'exclude', 'require']:
            raise ValueError(f'Invalid "allocation_type": {allocation_type}')
        # This filter requires index settings
        self.get_index_settings()
        self.get_index_state()
        self.empty_list_check()
        for lst in chunk_index_list(self.indices):
            working_list = self._get_indices_settings(lst)
            if working_list:
                for index in list(working_list.keys()):
                    try:
                        has_routing = (
                            working_list[index]['settings']['index']['routing'][
                                'allocation'
                            ][allocation_type][key]
                            == value
                        )
                    except KeyError:
                        has_routing = False
                    # if has_routing:
                    msg = (
                        f'{index}: Routing (mis)match: '
                        f'index.routing.allocation.{allocation_type}.{key}={value}.'
                    )
                    self.__excludify(has_routing, exclude, index, msg)

    def filter_none(self):
        """The legendary NULL filter"""
        self.loggit.debug('"None" filter selected.  No filtering will be done.')

    def filter_by_alias(self, aliases=None, exclude=False):
        """
        Match indices which are associated with the alias or list of aliases
        identified by ``aliases``. Indices must appear in all aliases in list
        ``aliases`` or a 404 error will result, leading to no indices being matched.

        :param aliases: A list of alias names.
        :type aliases: list
        :param exclude: If ``exclude=True``, this filter will remove matching indices
            from ``indices``. If ``exclude=False``, then only matching indices
            will be kept in ``indices``. Default is ``False``
        """
        self.loggit.debug('Filtering indices matching aliases: "%s"', aliases)
        if not aliases:
            raise MissingArgument('No value for "aliases" provided')
        aliases = ensure_list(aliases)
        self.empty_list_check()
        for lst in chunk_index_list(self.indices):
            try:
                # get_alias will either return {} or a NotFoundError.
                has_alias = list(
                    self.client.indices.get_alias(
                        index=to_csv(lst), name=to_csv(aliases)
                    ).keys()
                )
                self.loggit.debug('has_alias: %s', has_alias)
            except NotFoundError:
                # if we see the NotFoundError, we need to set working_list to {}
                has_alias = []
            for index in lst:
                if index in has_alias:
                    isness = 'is'
                    condition = True
                else:
                    isness = 'is not'
                    condition = False
                msg = f'{index} {isness} associated with aliases: {aliases}'
                self.__excludify(condition, exclude, index, msg)

    def filter_by_count(
        self,
        count=None,
        reverse=True,
        use_age=False,
        pattern=None,
        source='creation_date',
        timestring=None,
        field=None,
        stats_result='min_value',
        exclude=True,
    ):
        """
        Remove indices from the actionable list beyond the number ``count``, sorted
        reverse-alphabetically by default.  If you set ``reverse=False``, it will
        be sorted alphabetically.

        The default is usually what you will want. If only one kind of index is
        provided--for example, indices matching ``logstash-%Y.%m.%d`` -- then
        reverse alphabetical sorting will mean the oldest will remain in the list,
        because lower numbers in the dates mean older indices.

        By setting ``reverse=False``, then ``index3`` will be deleted before
        ``index2``, which will be deleted before ``index1``

        ``use_age`` allows ordering indices by age. Age is determined by the index
        creation date by default, but you can specify an ``source`` of ``name``,
        ``max_value``, or ``min_value``. The ``name`` `source` requires the
        timestring argument.

        :param count: Filter indices beyond ``count``.
        :param reverse: The filtering direction. (default: ``True``).
        :param use_age: Sort indices by age.  ``source`` is required in this case.
        :param pattern: Select indices to count from a regular expression pattern.
            This pattern must have one and only one capture group. This can allow
            a single ``count`` filter instance to operate against any number of
            matching patterns, and keep ``count`` of each index in that group.
            For example, given a ``pattern`` of ``'^(.*)-\\d{6}$'``, it will match
            both ``rollover-000001`` and ``index-999990``, but not
            ``logstash-2017.10.12``. Following the same example, if my cluster
            also had ``rollover-000002`` through ``rollover-000010`` and
            ``index-888888`` through ``index-999999``, it will process both groups
            of indices, and include or exclude the ``count`` of each.
        :param source: Source of index age. Can be one of ``name``,
            ``creation_date``, or ``field_stats``. Default: ``creation_date``
        :param timestring: An :py:func:`time.strftime` string to match the datestamp
            in an index name. Only used if ``source=name``.
        :param field: A timestamp field name.  Only used if ``source=field_stats``.
        :param stats_result: Either ``min_value`` or ``max_value``.  Only used if
            ``source=field_stats``. It determines whether to reference the minimum
            or maximum value of ``field`` in each index.
        :param exclude: If ``exclude=True``, this filter will remove matching indices
            from ``indices``. If ``exclude=False``, then only matching indices
            will be kept in ``indices``. Default is ``True``
        """
        self.loggit.debug('Filtering indices by count')
        if not count:
            raise MissingArgument('No value for "count" provided')
        # This filter requires index state (open/close) and index settings
        self.get_index_state()
        self.get_index_settings()
        # Create a copy-by-value working list
        working_list = self.working_list()
        if pattern:
            try:
                regex = re.compile(pattern)
                if regex.groups < 1:
                    raise ConfigurationError(
                        f'No regular expression group found in {pattern}'
                    )
                if regex.groups > 1:
                    raise ConfigurationError(
                        f'More than 1 regular expression group found in {pattern}'
                    )
                # Prune indices not matching the regular expression the object
                # (And filtered_indices) We do not want to act on them by accident.
                prune_these = list(
                    filter(lambda x: regex.match(x) is None, working_list)
                )
                filtered_indices = working_list
                for index in prune_these:
                    msg = '{index} does not match regular expression {pattern}.'
                    condition = True
                    exclude = True
                    self.__excludify(condition, exclude, index, msg)
                    # also remove it from filtered_indices
                    filtered_indices.remove(index)
                # Presort these filtered_indices using the lambda
                presorted = sorted(
                    filtered_indices, key=lambda x: regex.match(x).group(1)
                )
            except Exception as exc:
                raise ActionError(
                    f'Unable to process pattern: "{pattern}". Error: {exc}'
                ) from exc
            # Initialize groups here
            groups = []
            # We have to pull keys k this way, but we don't need to keep them
            # We only need g for groups
            for _, g in itertools.groupby(
                presorted, key=lambda x: regex.match(x).group(1)
            ):
                groups.append(list(g))
        else:
            # Since pattern will create a list of lists, and we iterate over that,
            # we need to put our single list inside a list
            groups = [working_list]
        for group in groups:
            if use_age:
                if source != 'name':
                    self.loggit.warning(
                        'Cannot get age information from closed indices unless '
                        'source="name".  Omitting any closed indices.'
                    )
                    self.filter_closed()
                self._calculate_ages(
                    source=source,
                    timestring=timestring,
                    field=field,
                    stats_result=stats_result,
                )
                # Using default value of reverse=True in self._sort_by_age()
                sorted_indices = self._sort_by_age(group, reverse=reverse)
            else:
                # Default to sorting by index name
                sorted_indices = sorted(group, reverse=reverse)
            idx = 1
            for index in sorted_indices:
                msg = f'{index} is {idx} of specified count of {count}.'
                condition = True if idx <= count else False
                self.__excludify(condition, exclude, index, msg)
                idx += 1

    def filter_by_shards(
        self, number_of_shards=None, shard_filter_behavior='greater_than', exclude=False
    ):
        """
        Match ``indices`` with a given shard count.

        Selects all indices with a shard count ``greater_than`` ``number_of_shards``
        by default. Use ``shard_filter_behavior`` to select indices with shard
        count ``greater_than``, ``greater_than_or_equal``, ``less_than``,
        ``less_than_or_equal``, or ``equal`` to ``number_of_shards``.

        :param number_of_shards: shard threshold
        :param shard_filter_behavior: Do you want to filter on ``greater_than``,
            ``greater_than_or_equal``, ``less_than``, ``less_than_or_equal``,
            or ``equal``?
        :param exclude: If ``exclude=True``, this filter will remove matching indices
            from ``indices``. If ``exclude=False``, then only matching indices
            will be kept in ``indices``. Default is ``False``
        """
        self.loggit.debug("Filtering indices by number of shards")
        if not number_of_shards:
            raise MissingArgument('No value for "number_of_shards" provided')
        if shard_filter_behavior not in [
            'greater_than',
            'less_than',
            'greater_than_or_equal',
            'less_than_or_equal',
            'equal',
        ]:
            raise ValueError(
                f'Invalid value for "shard_filter_behavior": {shard_filter_behavior}'
            )
        if number_of_shards < 1 or (
            shard_filter_behavior == 'less_than' and number_of_shards == 1
        ):
            raise ValueError(
                f'Unacceptable value: {number_of_shards} -- "number_of_shards" cannot '
                f'be less than 1. A valid index will have at least one shard.'
            )
        # This filter requires index_settings to count shards
        self.get_index_settings()
        self.empty_list_check()
        for index in self.working_list():
            self.loggit.debug('Filter by number of shards: Index: %s', index)
            if shard_filter_behavior == 'greater_than':
                condition = (
                    int(self.index_info[index]['number_of_shards']) > number_of_shards
                )
            elif shard_filter_behavior == 'less_than':
                condition = (
                    int(self.index_info[index]['number_of_shards']) < number_of_shards
                )
            elif shard_filter_behavior == 'greater_than_or_equal':
                condition = (
                    int(self.index_info[index]['number_of_shards']) >= number_of_shards
                )
            elif shard_filter_behavior == 'less_than_or_equal':
                condition = (
                    int(self.index_info[index]['number_of_shards']) <= number_of_shards
                )
            else:
                condition = (
                    int(self.index_info[index]['number_of_shards']) == number_of_shards
                )
            self.__excludify(condition, exclude, index)

    def filter_period(
        self,
        period_type='relative',
        source='name',
        range_from=None,
        range_to=None,
        date_from=None,
        date_to=None,
        date_from_format=None,
        date_to_format=None,
        timestring=None,
        unit=None,
        field=None,
        stats_result='min_value',
        intersect=False,
        week_starts_on='sunday',
        epoch=None,
        exclude=False,
    ):
        """
        Match ``indices`` with ages within a given period.

        :param period_type: Can be either ``absolute`` or ``relative``.  Default
            is ``relative``. ``date_from`` and ``date_to`` are required when using
            ``period_type='absolute'``. ``range_from`` and ``range_to`` are required
            with ``period_type='relative'``.
        :param source: Source of index age. Can be ``name``, ``creation_date``,
            or ``field_stats``
        :param range_from: How many ``unit`` (s) in the past/future is the origin?
        :param range_to: How many ``unit`` (s) in the past/future is the end point?
        :param date_from: The simplified date for the start of the range
        :param date_to: The simplified date for the end of the range.  If this
            value is the same as ``date_from``, the full value of ``unit`` will be
            extrapolated for the range.  For example, if ``unit=months``, and
            ``date_from`` and ``date_to`` are both ``2017.01``, then the entire
            month of January 2017 will be the absolute date range.
        :param date_from_format: The :py:func:`time.strftime` string used to
            parse ``date_from``
        :param date_to_format: The :py:func:`time.strftime` string used to
            parse ``date_to``
        :param timestring: An :py:func:`time.strftime` string to match the datestamp
            in an index name. Only used for index filtering by ``name``.
        :param unit: One of ``hours``, ``days``, ``weeks``, ``months``, or ``years``.
        :param field: A timestamp field name.  Only used for ``field_stats`` based
            calculations.
        :param stats_result: Either ``min_value`` or ``max_value``.  Only used in
            conjunction with ``source='field_stats'`` to choose whether to reference
            the min or max result value.
        :param intersect: Only used when ``source='field_stats'``. If ``True``,
            only indices where both ``min_value`` and ``max_value`` are within the
            period will be selected. If ``False``, it will use whichever you specified.
            Default is ``False`` to preserve expected behavior.
        :param week_starts_on: Either ``sunday`` or ``monday``. Default is ``sunday``
        :param epoch: An epoch timestamp used to establish a point of reference for
            calculations. If not provided, the current time will be used.
        :param exclude: If ``exclude=True``, this filter will remove matching indices
            from ``indices``. If ``exclude=False``, then only matching indices
            will be kept in ``indices``. Default is ``False``
        """
        self.loggit.debug('Filtering indices by period')
        if period_type not in ['absolute', 'relative']:
            raise ValueError(
                f'Unacceptable value: {period_type} -- "period_type" must be either '
                f'"absolute" or "relative".'
            )
        if period_type == 'relative':
            func = date_range
            args = [unit, range_from, range_to, epoch]
            kwgs = {'week_starts_on': week_starts_on}
            if (not isinstance(range_from, int)) or (not isinstance(range_to, int)):
                raise ConfigurationError(
                    '"range_from" and "range_to" must be integer values'
                )
        else:
            func = absolute_date_range
            args = [unit, date_from, date_to]
            kwgs = {
                'date_from_format': date_from_format,
                'date_to_format': date_to_format,
            }
            for reqd in [date_from, date_to, date_from_format, date_to_format]:
                if not reqd:
                    raise ConfigurationError(
                        'Must provide "date_from", "date_to", "date_from_format", and '
                        '"date_to_format" with absolute period_type'
                    )
        # This filter requires index settings
        self.get_index_settings()
        try:
            start, end = func(*args, **kwgs)
        # pylint: disable=broad-except
        except Exception as exc:
            report_failure(exc)
        self._calculate_ages(
            source=source, timestring=timestring, field=field, stats_result=stats_result
        )
        for index in self.working_list():
            try:
                if source == 'field_stats' and intersect:
                    min_age = int(self.index_info[index]['age']['min_value'])
                    max_age = int(self.index_info[index]['age']['max_value'])
                    msg = (
                        f'Index "{index}", timestamp field "{field}", min_value '
                        f'({min_age}), max_value ({max_age}), period start: '
                        f'"{start}", period end, "{end}"'
                    )
                    # Because time adds to epoch, smaller numbers are actually older
                    # timestamps.
                    inrange = (min_age >= start) and (max_age <= end)
                else:
                    age = int(self.index_info[index]['age'][self.age_keyfield])
                    msg = (
                        f'Index "{index}" age ({age}), period start: "{start}", period '
                        f'end, "{end}"'
                    )
                    # Because time adds to epoch, smaller numbers are actually older
                    # timestamps.
                    inrange = (age >= start) and (age <= end)
                self.__excludify(inrange, exclude, index, msg)
            except KeyError:
                self.loggit.debug(
                    'Index "%s" does not meet provided criteria. Removing from list.',
                    index,
                )
                self.indices.remove(index)

    def filter_ilm(self, exclude=True):
        """
        Match indices that have the setting ``index.lifecycle.name``

        :param exclude: If ``exclude=True``, this filter will remove matching
            ``indices``. If ``exclude=False``, then only matching indices will be
            kept in ``indices``. Default is ``True``
        """
        self.loggit.debug('Filtering indices with index.lifecycle.name')
        index_lists = chunk_index_list(self.indices)
        if index_lists == [['']]:
            self.loggit.debug('Empty working list. No ILM indices to filter.')
            return
        for lst in index_lists:
            working_list = self._get_indices_settings(lst)
            if working_list:
                for index in list(working_list.keys()):
                    try:
                        subvalue = working_list[index]['settings']['index']['lifecycle']
                        has_ilm = 'name' in subvalue
                        msg = f"{index} has index.lifecycle.name {subvalue['name']}"
                    except KeyError:
                        has_ilm = False
                        msg = f'index.lifecycle.name is not set for index {index}'
                    self.__excludify(has_ilm, exclude, index, msg)

    def iterate_filters(self, filter_dict):
        """
        Iterate over the filters defined in ``config`` and execute them.

        :param filter_dict: The configuration dictionary

        .. note:: ``filter_dict`` should be a dictionary with the following form:
        .. code-block:: python

                { 'filters' : [
                        {
                            'filtertype': 'the_filter_type',
                            'key1' : 'value1',
                            ...
                            'keyN' : 'valueN'
                        }
                    ]
                }

        """
        self.loggit.debug('Iterating over a list of filters')
        # Make sure we actually _have_ filters to act on
        if 'filters' not in filter_dict or len(filter_dict['filters']) < 1:
            self.loggit.info('No filters in config.  Returning unaltered object.')
            return
        self.loggit.debug('All filters: %s', filter_dict['filters'])
        for fil in filter_dict['filters']:
            self.loggit.debug('Top of the loop: %s', self.indices)
            self.loggit.debug('Un-parsed filter args: %s', fil)
            # Make sure we got at least this much in the configuration
            chk = SchemaCheck(
                fil, filterstructure(), 'filter', 'IndexList.iterate_filters'
            ).result()
            msg = f'Parsed filter args: {chk}'
            self.loggit.debug(msg)
            method = self.__map_method(fil['filtertype'])
            del fil['filtertype']
            # If it's a filtertype with arguments, update the defaults with the
            # provided settings.
            if fil:
                self.loggit.debug('Filter args: %s', fil)
                self.loggit.debug('Pre-instance: %s', self.indices)
                method(**fil)
                self.loggit.debug('Post-instance: %s', self.indices)
            else:
                # Otherwise, it's a settingless filter.
                method()

    def filter_by_size(
        self,
        size_threshold=None,
        threshold_behavior='greater_than',
        exclude=False,
        size_behavior='primary',
    ):
        """
        Remove indices from the actionable list based on index size.

        ``threshold_behavior``, when set to ``greater_than`` (default), includes
        if it the index tests to be larger than ``size_threshold``. When set to
        ``less_than``, it includes if the index is smaller than ``size_threshold``

        :param size_threshold: Filter indices over *n* gigabytes
        :param threshold_behavior: Size to filter, either ``greater_than`` or
            ``less_than``. Defaults to ``greater_than`` to preserve backwards
            compatability.
        :param size_behavior: Size that used to filter, either ``primary`` or
            ``total``. Defaults to ``primary``
        :param exclude: If ``exclude=True``, this filter will remove matching indices
            from ``indices``. If ``exclude=False``, then only matching indices
            will be kept in ``indices``. Default is ``False``
        """
        self.loggit.debug('Filtering indices by index size')
        # Ensure that disk_space is a float
        if not size_threshold:
            raise MissingArgument('No value for "size_threshold" provided')
        if size_behavior not in ['primary', 'total']:
            raise ValueError(f'Invalid value for "size_behavior": {size_behavior}')
        if threshold_behavior not in ['greater_than', 'less_than']:
            raise ValueError(
                f'Invalid value for "threshold_behavior": {threshold_behavior}'
            )
        index_size_limit = float(size_threshold) * 2**30
        msg = (
            'Cannot get disk usage info from closed indices. '
            'Omitting any closed indices.'
        )
        self.loggit.debug(msg)
        # This filter requires index state (open/close) and index stats
        self.get_index_state()
        self.get_index_stats()
        self.filter_closed()
        # Create a copy-by-value working list
        working_list = self.working_list()
        for index in working_list:
            if size_behavior == 'primary':
                index_size = self.index_info[index]['primary_size_in_bytes']
            else:
                index_size = self.index_info[index]['size_in_bytes']
            msg = (
                f'{index}, index size is {byte_size(index_size)} and '
                f'size limit is {byte_size(index_size_limit)}.'
            )
            if threshold_behavior == 'greater_than':
                self.__excludify((index_size > index_size_limit), exclude, index, msg)
            elif threshold_behavior == 'less_than':
                self.__excludify((index_size < index_size_limit), exclude, index, msg)