[python] Move histogram metric from internal to public interface/files

sdks/python/apache_beam/internal/metrics/metric.py

@@ -35,17 +35,13 @@
 from typing import Type
 from typing import Union
 
-from apache_beam.internal.metrics.cells import HistogramCellFactory
 from apache_beam.metrics import monitoring_infos
-from apache_beam.metrics.execution import MetricUpdater
 from apache_beam.metrics.metric import Metrics as UserMetrics
-from apache_beam.metrics.metricbase import Histogram
 from apache_beam.metrics.metricbase import MetricName
 
 if TYPE_CHECKING:
   from apache_beam.metrics.cells import MetricCell
   from apache_beam.metrics.cells import MetricCellFactory
-  from apache_beam.utils.histogram import BucketType
 
 # Protect against environments where bigquery library is not available.
 # pylint: disable=wrong-import-order, wrong-import-position
@@ -82,46 +78,6 @@ def counter(
         MetricName(namespace=None, name=None, urn=urn, labels=labels),
         process_wide=process_wide)
 
-  @staticmethod
-  def histogram(
-      namespace: Union[Type, str],
-      name: str,
-      bucket_type: 'BucketType',
-      logger: Optional['MetricLogger'] = None) -> 'Metrics.DelegatingHistogram':
-    """Obtains or creates a Histogram metric.
-
-    Args:
-      namespace: A class or string that gives the namespace to a metric
-      name: A string that gives a unique name to a metric
-      bucket_type: A type of bucket used in a histogram. A subclass of
-        apache_beam.utils.histogram.BucketType
-      logger: MetricLogger for logging locally aggregated metric
-
-    Returns:
-      A Histogram object.
-    """
-    namespace = UserMetrics.get_namespace(namespace)
-    return Metrics.DelegatingHistogram(
-        MetricName(namespace, name), bucket_type, logger)
-
-  class DelegatingHistogram(Histogram):
-    """Metrics Histogram that Delegates functionality to MetricsEnvironment."""
-    def __init__(
-        self,
-        metric_name: MetricName,
-        bucket_type: 'BucketType',
-        logger: Optional['MetricLogger']) -> None:
-      super().__init__(metric_name)
-      self.metric_name = metric_name
-      self.cell_type = HistogramCellFactory(bucket_type)
-      self.logger = logger
-      self.updater = MetricUpdater(self.cell_type, self.metric_name)
-
-    def update(self, value: object) -> None:
-      self.updater(value)
-      if self.logger:
-        self.logger.update(self.cell_type, self.metric_name, value)
-
 
 class MetricLogger(object):
   """Simple object to locally aggregate and log metrics."""