Class Query (2.23.0)

Query(
    client,
    project,
    metric_type="compute.googleapis.com/instance/cpu/utilization",
    end_time=None,
    days=0,
    hours=0,
    minutes=0,
)

Query object for retrieving metric data.

Parameters
Name	Description
`client`	`:class:google.cloud.monitoring_v3.gapic. metric_service_client.MetricServiceClient` The client to use.
`project`	`str` The project ID or number.
`metric_type`	`str` 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`_.
`end_time`	`datetime.datetime` (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 select_interval must be called before the query is executed.
`days`	`int` The number of days in the time interval.
`hours`	`int` The number of hours in the time interval.
`minutes`	`int` The number of minutes in the time interval.

Properties

filter

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.

metric_type

The metric type name.

Methods

deepcopy

__deepcopy__(memo)

Create a deepcopy of the query object.

The client attribute is copied by reference only.

Parameter
Name	Description
`memo`	`dict` the memo dict to avoid excess copying in case the object is referenced from its member.

Returns
Type	Description
`Query`	The new query object.

align

align(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 import monitoring
query = query.align(
    monitoring.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)

Parameters
Name	Description
`per_series_aligner`	`str or Aligner` The approach to be used to align individual time series. For example: :data:`Aligner.ALIGN_MEAN`. See Aligner and the descriptions of the `supported aligners`_.
`seconds`	`int` The number of seconds in the alignment period.
`minutes`	`int` The number of minutes in the alignment period.
`hours`	`int` The number of hours in the alignment period.

Returns
Type	Description
`Query`	The new query object. .. _supported aligners: https://cloud.google.com/monitoring/api/ref_v3/rest/v3/ projects.timeSeries/list#Aligner

as_dataframe

as_dataframe(label=None, labels=None)

Return all the selected time series as a pandas dataframe.

Note: Use of this method requires that you have pandas installed.

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'])

Parameters
Name	Description
`label`	`str` (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"`.
`labels`	`list of strings, or None` 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.

Returns
Type	Description
`pandas.DataFrame`	A dataframe where each column represents one time series.

iter

iter(headers_only=False, page_size=None)

Yield all time series objects selected by the query.

The generator returned iterates over xref_TimeSeries objects containing points ordered from oldest to newest.

Note that the Query object itself is an iterable, such that the following are equivalent::

for timeseries in query:
    ...

for timeseries in query.iter():
    ...

Parameters
Name	Description
`headers_only`	`bool` Whether to omit the point data from the time series objects.
`page_size`	`int` (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.

Exceptions
Type	Description
`ValueError	if the query time interval has not been specified.

reduce

reduce(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 import monitoring
query = query.reduce(monitoring.Aggregation.Reducer.REDUCE_MEAN,
                     'resource.project_id', 'resource.zone')

Parameters
Name	Description
`cross_series_reducer`	`str or Reducer` The approach to be used to combine time series. For example: :data:`Reducer.REDUCE_MEAN`. See Reducer and the descriptions of the `supported reducers`_.
`group_by_fields`	`strs` 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.

Returns
Type	Description
`Query`	The new query object. .. _supported reducers: https://cloud.google.com/monitoring/api/ref_v3/rest/v3/ projects.timeSeries/list#Reducer

select_group

select_group(group_id)

Copy the query and add filtering by group.

Example::

query = query.select_group('1234567')

Parameter
Name	Description
`group_id`	`str` The ID of a group to filter by.

Returns
Type	Description
`Query`	The new query object.

select_interval

select_interval(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.

Parameters
Name	Description
`end_time`	`datetime.datetime` The end time (inclusive) of the time interval for which results should be returned, as a datetime object.
`start_time`	`datetime.datetime` (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.

Returns
Type	Description
`Query`	The new query object.

select_metrics

select_metrics(*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 "_notequal" to the keyword, you can inequality:

<label>_notequal=<value> generates::

metric.label.<label> != <value>

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>

Parameter
Name	Description
`args`	`tuple` 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.

Returns
Type	Description
`Query`	The new query object.

select_projects

select_projects(*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')

Parameter
Name	Description
`args`	`tuple` Project IDs limiting the resources to be included in the query.

Returns
Type	Description
`Query`	The new query object.

select_resources

select_resources(*args, **kwargs)

Copy the query and add filtering by resource labels.

See more documentation at: https://cloud.google.com/monitoring/api/v3/filters#comparisons.

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=...).

Parameter
Name	Description
`args`	`tuple` 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.

Returns
Type	Description
`Query`	The new query object. .. _defined resource types: https://cloud.google.com/monitoring/api/v3/monitored-resources

Class Query (2.23.0)

Parameters

Properties

filter

metric_type

Methods

__deepcopy__

align

as_dataframe

Generate a dataframe with a multi-level column header including

iter

reduce

select_group

select_interval

select_metrics

select_projects

select_resources

deepcopy