Source code for google.cloud.monitoring_v3.query

# Copyright 2016 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Time series query for the `Google Stackdriver Monitoring API (V3)`_.

.. _Google Stackdriver Monitoring API (V3):
    https://cloud.google.com/monitoring/api/ref_v3/rest/v3/\
    projects.timeSeries/list
"""

import copy
import datetime

import six

from google.cloud.monitoring_v3 import _dataframe
from google.cloud.monitoring_v3 import types
from google.cloud.monitoring_v3.gapic import enums

_UTCNOW = datetime.datetime.utcnow  # To be replaced by tests.


[docs]class Query(object): """Query object for retrieving metric data. :type client: :class:`google.cloud.monitoring_v3.gapic. metric_service_client.MetricServiceClient` :param client: The client to use. :type project: str :param project: The project ID or number. :type metric_type: str :param metric_type: The metric type name. The default value is :data:`Query.DEFAULT_METRIC_TYPE <google.cloud.monitoring.query.Query.DEFAULT_METRIC_TYPE>`, but please note that this default value is provided only for demonstration purposes and is subject to change. See the `supported metrics`_. :type end_time: :class:`datetime.datetime` :param end_time: (Optional) The end time (inclusive) of the time interval for which results should be returned, as a datetime object. The default is the start of the current minute. The start time (exclusive) is determined by combining the values of ``days``, ``hours``, and ``minutes``, and subtracting the resulting duration from the end time. It is also allowed to omit the end time and duration here, in which case :meth:`~google.cloud.monitoring.query.Query.select_interval` must be called before the query is executed. :type days: int :param days: The number of days in the time interval. :type hours: int :param hours: The number of hours in the time interval. :type minutes: int :param minutes: The number of minutes in the time interval. :raises: :exc:`ValueError` if ``end_time`` is specified but ``days``, ``hours``, and ``minutes`` are all zero. If you really want to specify a point in time, use :meth:`~google.cloud.monitoring.query.Query.select_interval`. .. _supported metrics: https://cloud.google.com/monitoring/api/metrics """ DEFAULT_METRIC_TYPE = "compute.googleapis.com/instance/cpu/utilization" def __init__( self, client, project, metric_type=DEFAULT_METRIC_TYPE, end_time=None, days=0, hours=0, minutes=0, ): start_time = None if days or hours or minutes: if end_time is None: end_time = _UTCNOW().replace(second=0, microsecond=0) start_time = end_time - datetime.timedelta( days=days, hours=hours, minutes=minutes ) elif end_time is not None: raise ValueError("Non-zero duration required for time interval.") self._client = client self._project_path = self._client.project_path(project) self._end_time = end_time self._start_time = start_time self._filter = _Filter(metric_type) self._per_series_aligner = 0 self._alignment_period_seconds = 0 self._cross_series_reducer = 0 self._group_by_fields = () def __iter__(self): return self.iter() @property def metric_type(self): """The metric type name.""" return self._filter.metric_type @property def filter(self): """The filter string. This is constructed from the metric type, the resource type, and selectors for the group ID, monitored projects, resource labels, and metric labels. """ return str(self._filter)
[docs] def select_interval(self, end_time, start_time=None): """Copy the query and set the query time interval. Example:: import datetime now = datetime.datetime.utcnow() query = query.select_interval( end_time=now, start_time=now - datetime.timedelta(minutes=5)) As a convenience, you can alternatively specify the end time and an interval duration when you create the query initially. :type end_time: :class:`datetime.datetime` :param end_time: The end time (inclusive) of the time interval for which results should be returned, as a datetime object. :type start_time: :class:`datetime.datetime` :param start_time: (Optional) The start time (exclusive) of the time interval for which results should be returned, as a datetime object. If not specified, the interval is a point in time. :rtype: :class:`Query` :returns: The new query object. """ new_query = copy.deepcopy(self) new_query._end_time = end_time new_query._start_time = start_time return new_query
[docs] def select_group(self, group_id): """Copy the query and add filtering by group. Example:: query = query.select_group('1234567') :type group_id: str :param group_id: The ID of a group to filter by. :rtype: :class:`Query` :returns: The new query object. """ new_query = copy.deepcopy(self) new_query._filter.group_id = group_id return new_query
[docs] def select_projects(self, *args): """Copy the query and add filtering by monitored projects. This is only useful if the target project represents a Stackdriver account containing the specified monitored projects. Examples:: query = query.select_projects('project-1') query = query.select_projects('project-1', 'project-2') :type args: tuple :param args: Project IDs limiting the resources to be included in the query. :rtype: :class:`Query` :returns: The new query object. """ new_query = copy.deepcopy(self) new_query._filter.projects = args return new_query
[docs] def select_resources(self, *args, **kwargs): """Copy the query and add filtering by resource labels. Examples:: query = query.select_resources(zone='us-central1-a') query = query.select_resources(zone_prefix='europe-') query = query.select_resources(resource_type='gce_instance') A keyword argument ``<label>=<value>`` ordinarily generates a filter expression of the form:: resource.label.<label> = "<value>" However, by adding ``"_prefix"`` or ``"_suffix"`` to the keyword, you can specify a partial match. ``<label>_prefix=<value>`` generates:: resource.label.<label> = starts_with("<value>") ``<label>_suffix=<value>`` generates:: resource.label.<label> = ends_with("<value>") As a special case, ``"resource_type"`` is treated as a special pseudo-label corresponding to the filter object ``resource.type``. For example, ``resource_type=<value>`` generates:: resource.type = "<value>" See the `defined resource types`_. .. note:: The label ``"instance_name"`` is a metric label, not a resource label. You would filter on it using ``select_metrics(instance_name=...)``. :type args: tuple :param args: Raw filter expression strings to include in the conjunction. If just one is provided and no keyword arguments are provided, it can be a disjunction. :type kwargs: dict :param kwargs: Label filters to include in the conjunction as described above. :rtype: :class:`Query` :returns: The new query object. .. _defined resource types: https://cloud.google.com/monitoring/api/v3/monitored-resources """ new_query = copy.deepcopy(self) new_query._filter.select_resources(*args, **kwargs) return new_query
[docs] def select_metrics(self, *args, **kwargs): """Copy the query and add filtering by metric labels. Examples:: query = query.select_metrics(instance_name='myinstance') query = query.select_metrics(instance_name_prefix='mycluster-') A keyword argument ``<label>=<value>`` ordinarily generates a filter expression of the form:: metric.label.<label> = "<value>" However, by adding ``"_prefix"`` or ``"_suffix"`` to the keyword, you can specify a partial match. ``<label>_prefix=<value>`` generates:: metric.label.<label> = starts_with("<value>") ``<label>_suffix=<value>`` generates:: metric.label.<label> = ends_with("<value>") If the label's value type is ``INT64``, a similar notation can be used to express inequalities: ``<label>_less=<value>`` generates:: metric.label.<label> < <value> ``<label>_lessequal=<value>`` generates:: metric.label.<label> <= <value> ``<label>_greater=<value>`` generates:: metric.label.<label> > <value> ``<label>_greaterequal=<value>`` generates:: metric.label.<label> >= <value> :type args: tuple :param args: Raw filter expression strings to include in the conjunction. If just one is provided and no keyword arguments are provided, it can be a disjunction. :type kwargs: dict :param kwargs: Label filters to include in the conjunction as described above. :rtype: :class:`Query` :returns: The new query object. """ new_query = copy.deepcopy(self) new_query._filter.select_metrics(*args, **kwargs) return new_query
[docs] def align(self, per_series_aligner, seconds=0, minutes=0, hours=0): """Copy the query and add temporal alignment. If ``per_series_aligner`` is not :data:`Aligner.ALIGN_NONE`, each time series will contain data points only on the period boundaries. Example:: from google.cloud.monitoring import enums query = query.align( enums.Aggregation.Aligner.ALIGN_MEAN, minutes=5) It is also possible to specify the aligner as a literal string:: query = query.align('ALIGN_MEAN', minutes=5) :type per_series_aligner: str or :class:`~google.cloud.monitoring_v3.gapic.enums.Aggregation.Aligner` :param per_series_aligner: The approach to be used to align individual time series. For example: :data:`Aligner.ALIGN_MEAN`. See :class:`~google.cloud.monitoring_v3.gapic.enums.Aggregation.Aligner` and the descriptions of the `supported aligners`_. :type seconds: int :param seconds: The number of seconds in the alignment period. :type minutes: int :param minutes: The number of minutes in the alignment period. :type hours: int :param hours: The number of hours in the alignment period. :rtype: :class:`Query` :returns: The new query object. .. _supported aligners: https://cloud.google.com/monitoring/api/ref_v3/rest/v3/\ projects.timeSeries/list#Aligner """ new_query = copy.deepcopy(self) new_query._per_series_aligner = per_series_aligner new_query._alignment_period_seconds = seconds + 60 * (minutes + 60 * hours) return new_query
[docs] def reduce(self, cross_series_reducer, *group_by_fields): """Copy the query and add cross-series reduction. Cross-series reduction combines time series by aggregating their data points. For example, you could request an aggregated time series for each combination of project and zone as follows:: from google.cloud.monitoring import enums query = query.reduce(enums.Aggregation.Reducer.REDUCE_MEAN, 'resource.project_id', 'resource.zone') :type cross_series_reducer: str or :class:`~google.cloud.monitoring_v3.gapic.enums.Aggregation.Reducer` :param cross_series_reducer: The approach to be used to combine time series. For example: :data:`Reducer.REDUCE_MEAN`. See :class:`~google.cloud.monitoring_v3.gapic.enums.Aggregation.Reducer` and the descriptions of the `supported reducers`_. :type group_by_fields: strs :param group_by_fields: Fields to be preserved by the reduction. For example, specifying just ``"resource.zone"`` will result in one time series per zone. The default is to aggregate all of the time series into just one. :rtype: :class:`Query` :returns: The new query object. .. _supported reducers: https://cloud.google.com/monitoring/api/ref_v3/rest/v3/\ projects.timeSeries/list#Reducer """ new_query = copy.deepcopy(self) new_query._cross_series_reducer = cross_series_reducer new_query._group_by_fields = group_by_fields return new_query
[docs] def iter(self, headers_only=False, page_size=None): """Yield all time series objects selected by the query. The generator returned iterates over :class:`~google.cloud.monitoring_v3.types.TimeSeries` objects containing points ordered from oldest to newest. Note that the :class:`Query` object itself is an iterable, such that the following are equivalent:: for timeseries in query: ... for timeseries in query.iter(): ... :type headers_only: bool :param headers_only: Whether to omit the point data from the time series objects. :type page_size: int :param page_size: (Optional) The maximum number of points in each page of results from this request. Non-positive values are ignored. Defaults to a sensible value set by the API. :raises: :exc:`ValueError` if the query time interval has not been specified. """ if self._end_time is None: raise ValueError("Query time interval not specified.") params = self._build_query_params(headers_only, page_size) for ts in self._client.list_time_series(**params): yield ts
def _build_query_params(self, headers_only=False, page_size=None): """Return key-value pairs for the list_time_series API call. :type headers_only: bool :param headers_only: Whether to omit the point data from the :class:`~google.cloud.monitoring_v3.types.TimeSeries` objects. :type page_size: int :param page_size: (Optional) The maximum number of points in each page of results from this request. Non-positive values are ignored. Defaults to a sensible value set by the API. """ params = {"name": self._project_path, "filter_": self.filter} params["interval"] = types.TimeInterval() params["interval"].end_time.FromDatetime(self._end_time) if self._start_time: params["interval"].start_time.FromDatetime(self._start_time) if ( self._per_series_aligner or self._alignment_period_seconds or self._cross_series_reducer or self._group_by_fields ): params["aggregation"] = types.Aggregation( per_series_aligner=self._per_series_aligner, cross_series_reducer=self._cross_series_reducer, group_by_fields=self._group_by_fields, alignment_period={"seconds": self._alignment_period_seconds}, ) if headers_only: params["view"] = enums.ListTimeSeriesRequest.TimeSeriesView.HEADERS else: params["view"] = enums.ListTimeSeriesRequest.TimeSeriesView.FULL if page_size is not None: params["page_size"] = page_size return params
[docs] def as_dataframe(self, label=None, labels=None): """Return all the selected time series as a :mod:`pandas` dataframe. .. note:: Use of this method requires that you have :mod:`pandas` installed. Examples:: # Generate a dataframe with a multi-level column header including # the resource type and all available resource and metric labels. # This can be useful for seeing what labels are available. dataframe = query.as_dataframe() # Generate a dataframe using a particular label for the column # names. dataframe = query.as_dataframe(label='instance_name') # Generate a dataframe with a multi-level column header. dataframe = query.as_dataframe(labels=['zone', 'instance_name']) # Generate a dataframe with a multi-level column header, assuming # the metric is issued by more than one type of resource. dataframe = query.as_dataframe( labels=['resource_type', 'instance_id']) :type label: str :param label: (Optional) The label name to use for the dataframe header. This can be the name of a resource label or metric label (e.g., ``"instance_name"``), or the string ``"resource_type"``. :type labels: list of strings, or None :param labels: A list or tuple of label names to use for the dataframe header. If more than one label name is provided, the resulting dataframe will have a multi-level column header. Providing values for both ``label`` and ``labels`` is an error. :rtype: :class:`pandas.DataFrame` :returns: A dataframe where each column represents one time series. """ return _dataframe._build_dataframe(self, label, labels)
def __deepcopy__(self, memo): """Create a deepcopy of the query object. The `client` attribute is copied by reference only. :type memo: dict :param memo: the memo dict to avoid excess copying in case the object is referenced from its member. :rtype: :class:`Query` :returns: The new query object. """ new_query = copy.copy(self) new_query._filter = copy.deepcopy(self._filter, memo) return new_query
class _Filter(object): """Helper for assembling a filter string.""" def __init__(self, metric_type): self.metric_type = metric_type self.group_id = None self.projects = () self.resource_label_filter = None self.metric_label_filter = None def select_resources(self, *args, **kwargs): """Select by resource labels. See :meth:`Query.select_resources`. """ self.resource_label_filter = _build_label_filter("resource", *args, **kwargs) def select_metrics(self, *args, **kwargs): """Select by metric labels. See :meth:`Query.select_metrics`. """ self.metric_label_filter = _build_label_filter("metric", *args, **kwargs) def __str__(self): filters = ['metric.type = "{type}"'.format(type=self.metric_type)] if self.group_id is not None: filters.append('group.id = "{id}"'.format(id=self.group_id)) if self.projects: filters.append( " OR ".join( 'project = "{project}"'.format(project=project) for project in self.projects ) ) if self.resource_label_filter: filters.append(self.resource_label_filter) if self.metric_label_filter: filters.append(self.metric_label_filter) # Parentheses are never actually required, because OR binds more # tightly than AND in the Monitoring API's filter syntax. return " AND ".join(filters) def _build_label_filter(category, *args, **kwargs): """Construct a filter string to filter on metric or resource labels.""" terms = list(args) for key, value in six.iteritems(kwargs): if value is None: continue suffix = None if key.endswith( ("_prefix", "_suffix", "_greater", "_greaterequal", "_less", "_lessequal") ): key, suffix = key.rsplit("_", 1) if category == "resource" and key == "resource_type": key = "resource.type" else: key = ".".join((category, "label", key)) if suffix == "prefix": term = '{key} = starts_with("{value}")' elif suffix == "suffix": term = '{key} = ends_with("{value}")' elif suffix == "greater": term = "{key} > {value}" elif suffix == "greaterequal": term = "{key} >= {value}" elif suffix == "less": term = "{key} < {value}" elif suffix == "lessequal": term = "{key} <= {value}" else: term = '{key} = "{value}"' terms.append(term.format(key=key, value=value)) return " AND ".join(sorted(terms))