def test_predict_field_headers():
client = PredictionServiceClient(
credentials=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 = prediction_service.PredictRequest()
request.name = "name/value"
# Mock the actual call within the gRPC stub, and fake the request.
with mock.patch.object(type(client._transport.predict),
"__call__") as call:
call.return_value = prediction_service.PredictResponse()
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 field header was sent.
_, _, kw = call.mock_calls[0]
assert (
"x-goog-request-params",
"name=name/value",
) in kw["metadata"]
def test_predict_flattened():
client = PredictionServiceClient(
credentials=credentials.AnonymousCredentials(), )
# 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()
# Call the method with a truthy value for each flattened field,
# using the keyword arguments to the method.
client.predict(
name="name_value",
payload=data_items.ExamplePayload(image=data_items.Image(
image_bytes=b"image_bytes_blob")),
params={"key_value": "value_value"},
)
# Establish that the underlying call was made with the expected
# request object values.
assert len(call.mock_calls) == 1
_, args, _ = call.mock_calls[0]
assert args[0].name == "name_value"
assert args[0].payload == data_items.ExamplePayload(
image=data_items.Image(image_bytes=b"image_bytes_blob"))
assert args[0].params == {"key_value": "value_value"}
def test_predict_flattened_error():
client = PredictionServiceClient(
credentials=credentials.AnonymousCredentials(), )
# Attempting to call a method with both a request object and flattened
# fields is an error.
with pytest.raises(ValueError):
client.predict(
prediction_service.PredictRequest(),
name="name_value",
payload=data_items.ExamplePayload(image=data_items.Image(
image_bytes=b"image_bytes_blob")),
params={"key_value": "value_value"},
)
def test_predict(transport: str = "grpc",
request_type=prediction_service.PredictRequest):
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 = request_type()
# 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()
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] == prediction_service.PredictRequest()
# Establish that the response is the type that we expect.
assert isinstance(response, prediction_service.PredictResponse)