opentelemetry.sdk.metrics.export
- class opentelemetry.sdk.metrics.export.AggregationTemporality(value)[source]
Bases:
IntEnum
The temporality to use when aggregating data.
Can be one of the following values:
- UNSPECIFIED = 0
- DELTA = 1
- CUMULATIVE = 2
- class opentelemetry.sdk.metrics.export.ConsoleMetricExporter(out=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>, formatter=<function ConsoleMetricExporter.<lambda>>, preferred_temporality=None, preferred_aggregation=None)[source]
Bases:
MetricExporter
Implementation of
MetricExporter
that prints metrics to the console.This class can be used for diagnostic purposes. It prints the exported metrics to the console STDOUT.
- export(metrics_data, timeout_millis=10000, **kwargs)[source]
Exports a batch of telemetry data.
- Parameters:
metrics – The list of opentelemetry.sdk.metrics.export.Metric objects to be exported
- Return type:
- Returns:
The result of the export
- class opentelemetry.sdk.metrics.export.InMemoryMetricReader(preferred_temporality=None, preferred_aggregation=None)[source]
Bases:
MetricReader
Implementation of MetricReader that returns its metrics from
get_metrics_data()
.This is useful for e.g. unit tests.
- get_metrics_data()[source]
Reads and returns current metrics from the SDK
- Return type:
Optional
[opentelemetry.sdk.metrics.export.MetricsData]
- shutdown(timeout_millis=30000, **kwargs)[source]
Shuts down the MetricReader. This method provides a way for the MetricReader to do any cleanup required. A metric reader can only be shutdown once, any subsequent calls are ignored and return failure status.
When a MetricReader is registered on a
MeterProvider
,shutdown()
will invoke this automatically.- Return type:
- class opentelemetry.sdk.metrics.export.MetricExporter(preferred_temporality=None, preferred_aggregation=None)[source]
Bases:
ABC
Interface for exporting metrics.
Interface to be implemented by services that want to export metrics received in their own format.
- Parameters:
preferred_temporality – Used by opentelemetry.sdk.metrics.export.PeriodicExportingMetricReader to configure exporter level preferred temporality. See opentelemetry.sdk.metrics.export.MetricReader for more details on what preferred temporality is.
preferred_aggregation – Used by opentelemetry.sdk.metrics.export.PeriodicExportingMetricReader to configure exporter level preferred aggregation. See opentelemetry.sdk.metrics.export.MetricReader for more details on what preferred aggregation is.
- abstract export(metrics_data, timeout_millis=10000, **kwargs)[source]
Exports a batch of telemetry data.
- Parameters:
metrics – The list of opentelemetry.sdk.metrics.export.Metric objects to be exported
- Return type:
- Returns:
The result of the export
- class opentelemetry.sdk.metrics.export.MetricExportResult(value)[source]
Bases:
Enum
Result of exporting a metric
Can be any of the following values:
- SUCCESS = 0
- FAILURE = 1
- class opentelemetry.sdk.metrics.export.MetricReader(preferred_temporality=None, preferred_aggregation=None)[source]
Bases:
ABC
Base class for all metric readers
- Parameters:
preferred_temporality – A mapping between instrument classes and aggregation temporality. By default uses CUMULATIVE for all instrument classes. This mapping will be used to define the default aggregation temporality of every instrument class. If the user wants to make a change in the default aggregation temporality of an instrument class, it is enough to pass here a dictionary whose keys are the instrument classes and the values are the corresponding desired aggregation temporalities of the classes that the user wants to change, not all of them. The classes not included in the passed dictionary will retain their association to their default aggregation temporalities.
preferred_aggregation – A mapping between instrument classes and aggregation instances. By default maps all instrument classes to an instance of DefaultAggregation. This mapping will be used to define the default aggregation of every instrument class. If the user wants to make a change in the default aggregation of an instrument class, it is enough to pass here a dictionary whose keys are the instrument classes and the values are the corresponding desired aggregation for the instrument classes that the user wants to change, not necessarily all of them. The classes not included in the passed dictionary will retain their association to their default aggregations. The aggregation defined here will be overridden by an aggregation defined by a view that is not DefaultAggregation.
- abstract _receive_metrics(metrics_data, timeout_millis=10000, **kwargs)[source]
Called by MetricReader.collect when it receives a batch of metrics
- Return type:
- collect(timeout_millis=10000)[source]
Collects the metrics from the internal SDK state and invokes the _receive_metrics with the collection.
- Parameters:
timeout_millis (
float
) – Amount of time in milliseconds before this function raises a timeout error.- Return type:
If any of the underlying
collect
methods called by this method fails by any reason (including timeout) an exception will be raised detailing the individual errors that caused this function to fail.
- abstract shutdown(timeout_millis=30000, **kwargs)[source]
Shuts down the MetricReader. This method provides a way for the MetricReader to do any cleanup required. A metric reader can only be shutdown once, any subsequent calls are ignored and return failure status.
When a MetricReader is registered on a
MeterProvider
,shutdown()
will invoke this automatically.- Return type:
- class opentelemetry.sdk.metrics.export.PeriodicExportingMetricReader(exporter, export_interval_millis=None, export_timeout_millis=None)[source]
Bases:
MetricReader
PeriodicExportingMetricReader is an implementation of MetricReader that collects metrics based on a user-configurable time interval, and passes the metrics to the configured exporter. If the time interval is set to math.inf, the reader will not invoke periodic collection.
The configured exporter’s
export()
method will not be called concurrently.- shutdown(timeout_millis=30000, **kwargs)[source]
Shuts down the MetricReader. This method provides a way for the MetricReader to do any cleanup required. A metric reader can only be shutdown once, any subsequent calls are ignored and return failure status.
When a MetricReader is registered on a
MeterProvider
,shutdown()
will invoke this automatically.- Return type:
- class opentelemetry.sdk.metrics.export.ExponentialHistogram(data_points, aggregation_temporality)[source]
Bases:
object
Represents the type of a metric that is calculated by aggregating as an ExponentialHistogram of all reported measurements over a time interval.
-
data_points:
Sequence
[ExponentialHistogramDataPoint
]
-
aggregation_temporality:
AggregationTemporality
-
data_points:
- class opentelemetry.sdk.metrics.export.ExponentialHistogramDataPoint(attributes, start_time_unix_nano, time_unix_nano, count, sum, scale, zero_count, positive, negative, flags, min, max, exemplars=<factory>)[source]
Bases:
object
Single data point in a timeseries whose boundaries are defined by an exponential function. This timeseries describes the time-varying scalar value of a metric.
- class opentelemetry.sdk.metrics.export.Gauge(data_points)[source]
Bases:
object
Represents the type of a scalar metric that always exports the current value for every data point. It should be used for an unknown aggregation.
-
data_points:
Sequence
[NumberDataPoint
]
-
data_points:
- class opentelemetry.sdk.metrics.export.Histogram(data_points, aggregation_temporality)[source]
Bases:
object
Represents the type of a metric that is calculated by aggregating as a histogram of all reported measurements over a time interval.
-
data_points:
Sequence
[HistogramDataPoint
]
-
aggregation_temporality:
AggregationTemporality
-
data_points:
- class opentelemetry.sdk.metrics.export.HistogramDataPoint(attributes, start_time_unix_nano, time_unix_nano, count, sum, bucket_counts, explicit_bounds, min, max, exemplars=<factory>)[source]
Bases:
object
Single data point in a timeseries that describes the time-varying scalar value of a metric.
- class opentelemetry.sdk.metrics.export.Metric(name, description, unit, data)[source]
Bases:
object
Represents a metric point in the OpenTelemetry data model to be exported.
- class opentelemetry.sdk.metrics.export.MetricsData(resource_metrics)[source]
Bases:
object
An array of ResourceMetrics
-
resource_metrics:
Sequence
[ResourceMetrics
]
-
resource_metrics:
- class opentelemetry.sdk.metrics.export.NumberDataPoint(attributes, start_time_unix_nano, time_unix_nano, value, exemplars=<factory>)[source]
Bases:
object
Single data point in a timeseries that describes the time-varying scalar value of a metric.
- class opentelemetry.sdk.metrics.export.ResourceMetrics(resource, scope_metrics, schema_url)[source]
Bases:
object
A collection of ScopeMetrics from a Resource
-
scope_metrics:
Sequence
[ScopeMetrics
]
-
scope_metrics:
- class opentelemetry.sdk.metrics.export.ScopeMetrics(scope, metrics, schema_url)[source]
Bases:
object
A collection of Metrics produced by a scope
-
scope:
InstrumentationScope
-
scope:
- class opentelemetry.sdk.metrics.export.Sum(data_points, aggregation_temporality, is_monotonic)[source]
Bases:
object
Represents the type of a scalar metric that is calculated as a sum of all reported measurements over a time interval.
-
data_points:
Sequence
[NumberDataPoint
]
-
aggregation_temporality:
AggregationTemporality
-
data_points: