fix: allow any set query_params to work with query.iter() (#83)

Construct a `ListTimeSeriesRequest` from the query params rather than passing them directly to the function. This is important when one of the params is "optional" and is not available as a kwarg on the `list_time_series()` method.


For example, `aggregation` must be set on the request object.

Fixes #80 

```py

    def list_time_series(
        self,
        request: metric_service.ListTimeSeriesRequest = None,
        *,
        name: str = None,
        filter: str = None,
        interval: common.TimeInterval = None,
        view: metric_service.ListTimeSeriesRequest.TimeSeriesView = None,
        retry: retries.Retry = gapic_v1.method.DEFAULT,
        timeout: float = None,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> pagers.ListTimeSeriesPager:
```

```py
class ListTimeSeriesRequest(proto.Message):
    r"""The ``ListTimeSeries`` request.

    Attributes:
        name (str):
            Required. The project on which to execute the request. The
            format is:

            ::

                projects/[PROJECT_ID_OR_NUMBER]
        filter (str):
            Required. A `monitoring
            filter <https://cloud.google.com/monitoring/api/v3/filters>`__
            that specifies which time series should be returned. The
            filter must specify a single metric type, and can
            additionally specify metric labels and other information.
            For example:

            ::

                metric.type = "compute.googleapis.com/instance/cpu/usage_time" AND
                    metric.labels.instance_name = "my-instance-name".
        interval (~.common.TimeInterval):
            Required. The time interval for which results
            should be returned. Only time series that
            contain data points in the specified interval
            are included in the response.
        aggregation (~.common.Aggregation):
            Specifies the alignment of data points in individual time
            series as well as how to combine the retrieved time series
            across specified labels.

            By default (if no ``aggregation`` is explicitly specified),
            the raw time series data is returned.
        order_by (str):
            Unsupported: must be left blank. The points
            in each time series are currently returned in
            reverse time order (most recent to oldest).
        view (~.metric_service.ListTimeSeriesRequest.TimeSeriesView):
            Required. Specifies which information is
            returned about the time series.
        page_size (int):
            A positive number that is the maximum number of results to
            return. If ``page_size`` is empty or more than 100,000
            results, the effective ``page_size`` is 100,000 results. If
            ``view`` is set to ``FULL``, this is the maximum number of
            ``Points`` returned. If ``view`` is set to ``HEADERS``, this
            is the maximum number of ``TimeSeries`` returned.
        page_token (str):
            If this field is not empty then it must contain the
            ``nextPageToken`` value returned by a previous call to this
            method. Using this field causes the method to return
            additional results from the previous method call.
    """

```

Author: busunkim96

google/cloud/monitoring_v3/query.py

@@ -443,7 +443,9 @@ def iter(self, headers_only=False, page_size=None):
             raise ValueError("Query time interval not specified.")
 
         params = self._build_query_params(headers_only, page_size)
-        for ts in self._client.list_time_series(**params):
+
+        request = monitoring_v3.ListTimeSeriesRequest(**params)
+        for ts in self._client.list_time_series(request):
             yield ts
 
     def _build_query_params(self, headers_only=False, page_size=None):

tests/unit/test_query.py

@@ -394,6 +394,10 @@ def test_iteration_headers_only(self):
         client = self._create_client(channel)
         query = self._make_one(client, PROJECT, METRIC_TYPE)
         query = query.select_interval(start_time=T0, end_time=T1)
+
+        # add a temporal alignment to test that "aggregation" query params is
+        # correctly processed
+        query = query.align(monitoring_v3.Aggregation.Aligner.ALIGN_MAX, seconds=3600)
         response = list(query.iter(headers_only=True))
 
         self.assertEqual(len(response), 2)
@@ -412,6 +416,10 @@ def test_iteration_headers_only(self):
             filter='metric.type = "{type}"'.format(type=METRIC_TYPE),
             interval=self._make_interval(T1, T0),
             view=monitoring_v3.ListTimeSeriesRequest.TimeSeriesView.HEADERS,
+            aggregation=monitoring_v3.Aggregation(
+                per_series_aligner=monitoring_v3.Aggregation.Aligner.ALIGN_MAX,
+                alignment_period={"seconds": 3600},
+            ),
         )
         request = channel.requests[0][1]
         self.assertEqual(request, expected_request)