def test_apply_recommendation_field_headers():
client = RecommendationServiceClient(
credentials=ga_credentials.AnonymousCredentials(), )
# Any value that is part of the HTTP/1.1 URI should be sent as
# a field header. Set these to a non-empty value.
request = recommendation_service.ApplyRecommendationRequest()
request.customer_id = 'customer_id/value'
# Mock the actual call within the gRPC stub, and fake the request.
with mock.patch.object(type(client.transport.apply_recommendation),
'__call__') as call:
call.return_value = recommendation_service.ApplyRecommendationResponse(
)
client.apply_recommendation(request)
# Establish that the underlying gRPC stub method was called.
assert len(call.mock_calls) == 1
_, args, _ = call.mock_calls[0]
assert args[0] == request
# Establish that the field header was sent.
_, _, kw = call.mock_calls[0]
assert (
'x-goog-request-params',
'customer_id=customer_id/value',
) in kw['metadata']
def test_apply_recommendation(
transport: str = 'grpc',
request_type=recommendation_service.ApplyRecommendationRequest):
client = RecommendationServiceClient(
credentials=ga_credentials.AnonymousCredentials(),
transport=transport,
)
# Everything is optional in proto3 as far as the runtime is concerned,
# and we are mocking out the actual API, so just send an empty request.
request = request_type()
# Mock the actual call within the gRPC stub, and fake the request.
with mock.patch.object(type(client.transport.apply_recommendation),
'__call__') as call:
# Designate an appropriate return value for the call.
call.return_value = recommendation_service.ApplyRecommendationResponse(
)
response = client.apply_recommendation(request)
# Establish that the underlying gRPC stub method was called.
assert len(call.mock_calls) == 1
_, args, _ = call.mock_calls[0]
assert args[0] == recommendation_service.ApplyRecommendationRequest()
# Establish that the response is the type that we expect.
assert isinstance(response,
recommendation_service.ApplyRecommendationResponse)
def test_apply_recommendation_flattened_error():
client = RecommendationServiceClient(
credentials=ga_credentials.AnonymousCredentials(), )
# Attempting to call a method with both a request object and flattened
# fields is an error.
with pytest.raises(ValueError):
client.apply_recommendation(
recommendation_service.ApplyRecommendationRequest(),
customer_id='customer_id_value',
operations=[
recommendation_service.ApplyRecommendationOperation(
resource_name='resource_name_value')
],
)
def apply_recommendation(
self,
request: recommendation_service.ApplyRecommendationRequest = None,
*,
customer_id: str = None,
operations: Sequence[
recommendation_service.ApplyRecommendationOperation
] = None,
retry: retries.Retry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> recommendation_service.ApplyRecommendationResponse:
r"""Applies given recommendations with corresponding
apply parameters.
Args:
request (:class:`google.ads.googleads.v5.services.types.ApplyRecommendationRequest`):
The request object. Request message for
[RecommendationService.ApplyRecommendation][google.ads.googleads.v5.services.RecommendationService.ApplyRecommendation].
customer_id (:class:`str`):
Required. The ID of the customer with
the recommendation.
This corresponds to the ``customer_id`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
operations (:class:`Sequence[google.ads.googleads.v5.services.types.ApplyRecommendationOperation]`):
Required. The list of operations to apply
recommendations. If partial_failure=false all
recommendations should be of the same type There is a
limit of 100 operations per request.
This corresponds to the ``operations`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry.Retry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ads.googleads.v5.services.types.ApplyRecommendationResponse:
Response message for
[RecommendationService.ApplyRecommendation][google.ads.googleads.v5.services.RecommendationService.ApplyRecommendation].
"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
if request is not None and any([customer_id, operations]):
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# Minor optimization to avoid making a copy if the user passes
# in a recommendation_service.ApplyRecommendationRequest.
# There's no risk of modifying the input as we've already verified
# there are no flattened fields.
if not isinstance(
request, recommendation_service.ApplyRecommendationRequest
):
request = recommendation_service.ApplyRecommendationRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if customer_id is not None:
request.customer_id = customer_id
if operations is not None:
request.operations = operations
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[
self._transport.apply_recommendation
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata(
(("customer_id", request.customer_id),)
),
)
# Send the request.
response = rpc(
request, retry=retry, timeout=timeout, metadata=metadata,
)
# Done; return the response.
return response