def test_predict(transport: str = "grpc"):
client = PredictionServiceClient(
credentials=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 = prediction_service.PredictRequest()
# Mock the actual call within the gRPC stub, and fake the request.
with mock.patch.object(type(client._transport.predict), "__call__") as call:
# Designate an appropriate return value for the call.
call.return_value = prediction_service.PredictResponse(
recommendation_token="recommendation_token_value",
items_missing_in_catalog=["items_missing_in_catalog_value"],
dry_run=True,
next_page_token="next_page_token_value",
)
response = client.predict(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 response is the type that we expect.
assert isinstance(response, pagers.PredictPager)
assert response.recommendation_token == "recommendation_token_value"
assert response.items_missing_in_catalog == ["items_missing_in_catalog_value"]
assert response.dry_run is True
assert response.next_page_token == "next_page_token_value"
def predict(
self,
request: prediction_service.PredictRequest = None,
*,
retry: retries.Retry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> pagers.PredictPager:
r"""Makes a recommendation prediction. If using API Key based
authentication, the API Key must be registered using the
[PredictionApiKeyRegistry][google.cloud.recommendationengine.v1beta1.PredictionApiKeyRegistry]
service. `Learn
more </recommendations-ai/docs/setting-up#register-key>`__.
Args:
request (:class:`~.prediction_service.PredictRequest`):
The request object. Request message for Predict method.
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:
~.pagers.PredictPager:
Response message for predict method.
Iterating over this object will yield
results and resolve additional pages
automatically.
"""
# Create or coerce a protobuf request object.
request = prediction_service.PredictRequest(request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = gapic_v1.method.wrap_method(self._transport.predict,
default_timeout=None,
client_info=_client_info)
# Send the request.
response = rpc(request,
retry=retry,
timeout=timeout,
metadata=metadata)
# This method is paged; wrap the response in a pager, which provides
# an `__iter__` convenience method.
response = pagers.PredictPager(method=rpc,
request=request,
response=response)
# Done; return the response.
return response
def __init__(
self,
method: Callable[[prediction_service.PredictRequest],
prediction_service.PredictResponse],
request: prediction_service.PredictRequest,
response: prediction_service.PredictResponse,
):
"""Instantiate the pager.
Args:
method (Callable): The method that was originally called, and
which instantiated this pager.
request (:class:`~.prediction_service.PredictRequest`):
The initial request object.
response (:class:`~.prediction_service.PredictResponse`):
The initial response object.
"""
self._method = method
self._request = prediction_service.PredictRequest(request)
self._response = response
def __init__(self,
method: Callable[..., prediction_service.PredictResponse],
request: prediction_service.PredictRequest,
response: prediction_service.PredictResponse,
*,
metadata: Sequence[Tuple[str, str]] = ()):
"""Instantiate the pager.
Args:
method (Callable): The method that was originally called, and
which instantiated this pager.
request (google.cloud.recommendationengine_v1beta1.types.PredictRequest):
The initial request object.
response (google.cloud.recommendationengine_v1beta1.types.PredictResponse):
The initial response object.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
"""
self._method = method
self._request = prediction_service.PredictRequest(request)
self._response = response
self._metadata = metadata
def predict(
self,
request: prediction_service.PredictRequest = None,
*,
name: str = None,
user_event: gcr_user_event.UserEvent = None,
retry: retries.Retry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> pagers.PredictPager:
r"""Makes a recommendation prediction. If using API Key based
authentication, the API Key must be registered using the
[PredictionApiKeyRegistry][google.cloud.recommendationengine.v1beta1.PredictionApiKeyRegistry]
service. `Learn
more </recommendations-ai/docs/setting-up#register-key>`__.
Args:
request (google.cloud.recommendationengine_v1beta1.types.PredictRequest):
The request object. Request message for Predict method.
name (str):
Required. Full resource name of the format:
``{name=projects/*/locations/global/catalogs/default_catalog/eventStores/default_event_store/placements/*}``
The id of the recommendation engine placement. This id
is used to identify the set of models that will be used
to make the prediction.
We currently support three placements with the following
IDs by default:
- ``shopping_cart``: Predicts items frequently bought
together with one or more catalog items in the same
shopping session. Commonly displayed after
``add-to-cart`` events, on product detail pages, or
on the shopping cart page.
- ``home_page``: Predicts the next product that a user
will most likely engage with or purchase based on the
shopping or viewing history of the specified
``userId`` or ``visitorId``. For example -
Recommendations for you.
- ``product_detail``: Predicts the next product that a
user will most likely engage with or purchase. The
prediction is based on the shopping or viewing
history of the specified ``userId`` or ``visitorId``
and its relevance to a specified ``CatalogItem``.
Typically used on product detail pages. For example -
More items like this.
- ``recently_viewed_default``: Returns up to 75 items
recently viewed by the specified ``userId`` or
``visitorId``, most recent ones first. Returns
nothing if neither of them has viewed any items yet.
For example - Recently viewed.
The full list of available placements can be seen at
https://console.cloud.google.com/recommendation/datafeeds/default_catalog/dashboard
This corresponds to the ``name`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
user_event (google.cloud.recommendationengine_v1beta1.types.UserEvent):
Required. Context about the user,
what they are looking at and what action
they took to trigger the predict
request. Note that this user event
detail won't be ingested to userEvent
logs. Thus, a separate userEvent write
request is required for event logging.
This corresponds to the ``user_event`` 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.cloud.recommendationengine_v1beta1.services.prediction_service.pagers.PredictPager:
Response message for predict method.
Iterating over this object will yield
results and resolve additional pages
automatically.
"""
# 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.
has_flattened_params = any([name, user_event])
if request is not None and has_flattened_params:
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 prediction_service.PredictRequest.
# There's no risk of modifying the input as we've already verified
# there are no flattened fields.
if not isinstance(request, prediction_service.PredictRequest):
request = prediction_service.PredictRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if name is not None:
request.name = name
if user_event is not None:
request.user_event = user_event
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[self._transport.predict]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Send the request.
response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
# This method is paged; wrap the response in a pager, which provides
# an `__iter__` convenience method.
response = pagers.PredictPager(
method=rpc, request=request, response=response, metadata=metadata,
)
# Done; return the response.
return response