def test_get_rest_flattened_error():
client = MachineTypesClient(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.get(
compute.GetMachineTypeRequest(),
project="project_value",
zone="zone_value",
machine_type="machine_type_value",
)
def get(
self,
request: compute.GetMachineTypeRequest = None,
*,
project: str = None,
zone: str = None,
machine_type: str = None,
retry: retries.Retry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> compute.MachineType:
r"""Returns the specified machine type. Gets a list of
available machine types by making a list() request.
Args:
request (google.cloud.compute_v1.types.GetMachineTypeRequest):
The request object. A request message for
MachineTypes.Get. See the method description for
details.
project (str):
Project ID for this request.
This corresponds to the ``project`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
zone (str):
The name of the zone for this
request.
This corresponds to the ``zone`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
machine_type (str):
Name of the machine type to return.
This corresponds to the ``machine_type`` 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.compute_v1.types.MachineType:
Represents a Machine Type resource.
You can use specific machine types for your VM
instances based on performance and pricing
requirements. For more information, read Machine
Types. (== resource_for {$api_version}.machineTypes
==)
"""
# 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([project, zone, machine_type])
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 compute.GetMachineTypeRequest.
# There's no risk of modifying the input as we've already verified
# there are no flattened fields.
if not isinstance(request, compute.GetMachineTypeRequest):
request = compute.GetMachineTypeRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if project is not None:
request.project = project
if zone is not None:
request.zone = zone
if machine_type is not None:
request.machine_type = machine_type
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[self._transport.get]
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
def __call__(
self,
request: compute.GetMachineTypeRequest,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> compute.MachineType:
r"""Call the get method over HTTP.
Args:
request (~.compute.GetMachineTypeRequest):
The request object. A request message for
MachineTypes.Get. See the method
description for details.
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:
~.compute.MachineType:
Represents a Machine Type resource.
You can use specific machine types for
your VM instances based on performance
and pricing requirements. For more
information, read Machine Types.
"""
http_options = [
{
"method": "get",
"uri": "/compute/v1/projects/{project}/zones/{zone}/machineTypes/{machine_type}",
},
]
request_kwargs = compute.GetMachineTypeRequest.to_dict(request)
transcoded_request = path_template.transcode(http_options, **request_kwargs)
uri = transcoded_request["uri"]
method = transcoded_request["method"]
# Jsonify the query params
query_params = json.loads(
compute.GetMachineTypeRequest.to_json(
compute.GetMachineTypeRequest(transcoded_request["query_params"]),
including_default_value_fields=False,
use_integers_for_enums=False,
)
)
query_params.update(self._get_unset_required_fields(query_params))
# Send the request
headers = dict(metadata)
headers["Content-Type"] = "application/json"
response = getattr(self._session, method)(
# Replace with proper schema configuration (http/https) logic
"https://{host}{uri}".format(host=self._host, uri=uri),
timeout=timeout,
headers=headers,
params=rest_helpers.flatten_query_params(query_params),
)
# In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
# subclass.
if response.status_code >= 400:
raise core_exceptions.from_http_response(response)
# Return the response
return compute.MachineType.from_json(
response.content, ignore_unknown_fields=True
)