def test_create_log_metric(self):
# Setup Expected Response
name = 'name3373707'
description = 'description-1724546052'
filter_ = 'filter-1274492040'
value_extractor = 'valueExtractor2047672534'
expected_response = {
'name': name,
'description': description,
'filter': filter_,
'value_extractor': value_extractor
}
expected_response = logging_metrics_pb2.LogMetric(**expected_response)
# Mock the API response
channel = ChannelStub(responses=[expected_response])
patch = mock.patch('google.api_core.grpc_helpers.create_channel')
with patch as create_channel:
create_channel.return_value = channel
client = logging_v2.MetricsServiceV2Client()
# Setup Request
parent = client.project_path('[PROJECT]')
metric = {}
response = client.create_log_metric(parent, metric)
assert expected_response == response
assert len(channel.requests) == 1
expected_request = logging_metrics_pb2.CreateLogMetricRequest(
parent=parent, metric=metric)
actual_request = channel.requests[0][1]
assert expected_request == actual_request
def test_create_log_metric(self):
# Setup Expected Response
name = "name3373707"
description = "description-1724546052"
filter_ = "filter-1274492040"
value_extractor = "valueExtractor2047672534"
expected_response = {
"name": name,
"description": description,
"filter": filter_,
"value_extractor": value_extractor,
}
expected_response = logging_metrics_pb2.LogMetric(**expected_response)
# Mock the API response
channel = ChannelStub(responses=[expected_response])
patch = mock.patch("google.api_core.grpc_helpers.create_channel")
with patch as create_channel:
create_channel.return_value = channel
client = logging_v2.MetricsServiceV2Client()
# Setup Request
parent = client.project_path("[PROJECT]")
metric = {}
response = client.create_log_metric(parent, metric)
assert expected_response == response
assert len(channel.requests) == 1
expected_request = logging_metrics_pb2.CreateLogMetricRequest(
parent=parent, metric=metric)
actual_request = channel.requests[0][1]
assert expected_request == actual_request
def create_log_metric(
self,
parent,
metric,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
"""
Creates a logs-based metric.
Example:
>>> from google.cloud import logging_v2
>>>
>>> client = logging_v2.MetricsServiceV2Client()
>>>
>>> parent = client.project_path('[PROJECT]')
>>>
>>> # TODO: Initialize `metric`:
>>> metric = {}
>>>
>>> response = client.create_log_metric(parent, metric)
Args:
parent (str): The resource name of the project in which to create the metric:
::
"projects/[PROJECT_ID]"
The new metric must be provided in the request.
metric (Union[dict, ~google.cloud.logging_v2.types.LogMetric]): The new logs-based metric, which must not have an identifier that
already exists.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.logging_v2.types.LogMetric`
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will
be retried using a default configuration.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
A :class:`~google.cloud.logging_v2.types.LogMetric` instance.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
"""
# Wrap the transport method to add retry and timeout logic.
if "create_log_metric" not in self._inner_api_calls:
self._inner_api_calls[
"create_log_metric"] = google.api_core.gapic_v1.method.wrap_method(
self.transport.create_log_metric,
default_retry=self._method_configs["CreateLogMetric"].
retry,
default_timeout=self._method_configs["CreateLogMetric"].
timeout,
client_info=self._client_info,
)
request = logging_metrics_pb2.CreateLogMetricRequest(
parent=parent,
metric=metric,
)
if metadata is None:
metadata = []
metadata = list(metadata)
try:
routing_header = [("parent", parent)]
except AttributeError:
pass
else:
routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata(
routing_header)
metadata.append(routing_metadata)
return self._inner_api_calls["create_log_metric"](request,
retry=retry,
timeout=timeout,
metadata=metadata)
def create_log_metric(self,
parent,
metric,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None):
"""
Creates a logs-based metric.
Example:
>>> from google.cloud import logging_v2
>>>
>>> client = logging_v2.MetricsServiceV2Client()
>>>
>>> parent = client.project_path('[PROJECT]')
>>> metric = {}
>>>
>>> response = client.create_log_metric(parent, metric)
Args:
parent (str): The resource name of the project in which to create the metric:
::
\"projects/[PROJECT_ID]\"
The new metric must be provided in the request.
metric (Union[dict, ~google.cloud.logging_v2.types.LogMetric]): The new logs-based metric, which must not have an identifier that
already exists.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.logging_v2.types.LogMetric`
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
A :class:`~google.cloud.logging_v2.types.LogMetric` instance.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
"""
if metadata is None:
metadata = []
metadata = list(metadata)
request = logging_metrics_pb2.CreateLogMetricRequest(
parent=parent,
metric=metric,
)
return self._create_log_metric(request,
retry=retry,
timeout=timeout,
metadata=metadata)