Miscellaneous cleanup (#1042)

* Always use "ns" precision in numpy.datetime64's.

* Remove unused utility function.

* Remove whitespace in template - I think this a regression in pyows.

* And I think this is a numpy2 thing?

* Fix documentation typos.

datacube_ows/data.py

@@ -901,8 +901,8 @@ def feature_info(args):
                     elif pt_native.crs != ds.crs:
                         pt_native = geo_point.to_crs(ds.crs)
                     if ds.extent and ds.extent.contains(pt_native):
-                        # tolist() converts a numpy datetime64 to a python datatime
-                        dt = stacker.group_by.group_by_func(ds).tolist()
+                        # convert numpy datetime64 to a python datatime
+                        dt = Timestamp(stacker.group_by.group_by_func(ds)).to_pydatetime()
                         if params.product.time_resolution.is_subday():
                             feature_json["data_available_for_dates"].append(dt.isoformat())
                         else:

datacube_ows/ogc_utils.py

@@ -64,20 +64,6 @@ def solar_date(dt: datetime.datetime, tz: datetime.tzinfo) -> datetime.date:
     return dt.astimezone(tz).date()
 
 
-def local_date(ds: "datacube.model.Dataset", tz: Optional[datetime.tzinfo] = None) -> datetime.date:
-    """
-    Calculate the local (solar) date for a dataset.
-
-    :param ds: An ODC dataset object
-    :param tz: (optional) A timezone object. If not provided, determine the timezone from extent of the dataset.
-    :return: A date object.
-    """
-    dt_utc: datetime.datetime = dataset_center_time(ds)
-    if not tz:
-        tz = tz_for_geometry(ds.extent)
-    return solar_date(dt_utc, tz)
-
-
 def tz_for_dataset(ds: "datacube.model.Dataset") -> datetime.tzinfo:
     """
     Determine the timezone for a dataset (using it's extent)

datacube_ows/templates/wms_capabilities.xml

@@ -89,9 +89,7 @@
         {% elif lyr.regular_time_axis %}
         <Dimension name="time" units="ISO8601" default="{{ lyr.default_time.isoformat() }}">{{ lyr.time_axis_representation() }}</Dimension>
         {% elif lyr_ranges.times|length > 1 %}
-        <Dimension name="time" units="ISO8601" default="{{ lyr.default_time.isoformat() }}">
-            {% for t in lyr_ranges.times %}{{ t.isoformat() }}{% if not loop.last %},{% endif %}{% endfor %}
-        </Dimension>
+        <Dimension name="time" units="ISO8601" default="{{ lyr.default_time.isoformat() }}">{% for t in lyr_ranges.times %}{{ t.isoformat() }}{% if not loop.last %},{% endif %}{% endfor %}</Dimension>
         {% endif %}
 
         {% if lyr.attribution %}

datacube_ows/utils.py

@@ -70,7 +70,7 @@ def group_by_begin_datetime(pnames: Optional[List[str]] = None,
             ds.time.begin.year,
             ds.time.begin.month,
             ds.time.begin.day,
-            tzinfo=pytz.utc))
+            tzinfo=pytz.utc), "ns")
     else:
         grp_by = lambda ds: npdt64(datetime.datetime(
             ds.time.begin.year,
@@ -79,7 +79,7 @@ def group_by_begin_datetime(pnames: Optional[List[str]] = None,
             ds.time.begin.hour,
             ds.time.begin.minute,
             ds.time.begin.second,
-            tzinfo=ds.time.begin.tzinfo))
+            tzinfo=ds.time.begin.tzinfo), "ns")
     return GroupBy(
         dimension='time',
         group_by_func=grp_by,
@@ -120,7 +120,9 @@ def group_by_mosaic(pnames: Optional[List[str]] = None) -> "datacube.api.query.G
         sort_key = lambda ds: (solar_day(ds), base_sort_key(ds))
     return GroupBy(
         dimension='time',
-        group_by_func=lambda n: npdt64(datetime.datetime(1970, 1, 1, tzinfo=datetime.timezone.utc)),
+        group_by_func=lambda n: npdt64(
+            datetime.datetime(1970, 1, 1, tzinfo=datetime.timezone.utc),
+            "ns"),
         units='seconds since 1970-01-01 00:00:00',
         sort_key=sort_key
     )

datacube_ows/wcs1_utils.py

@@ -350,7 +350,7 @@ def get_coverage_data(req, qprof):
             )
             if req.product.time_resolution.is_subday():
                 timevals = [
-                    numpy.datetime64(dt.astimezone(pytz.utc).isoformat())
+                    numpy.datetime64(dt.astimezone(pytz.utc).isoformat(), "ns")
                     for dt in req.times
                 ]
             else:

docs/cfg_styling.rst

@@ -412,9 +412,9 @@ In addition to the custom includes defined `at the layer level
 If the GetFeatureInfo requests a style AND multiple dates, then the multi-date handler
 can define additional custom feature info.
 
-An additional dictionary is appended to the `propoerties::data` list, that already contains a dictionary
+An additional dictionary is appended to the `properties::data` list, that already contains a dictionary
 for each date returned by the query. The additional dictionary has ``"time": "all"`` and the fields
 defined by the multi-date handler custom_includes entry.
 
-Unlike other ``custom_include`` entries, the functions specified by the mult-date version is passed
+Unlike other ``custom_include`` entries, the functions specified by the multi-date version is passed
 a MULTI_DATE, single-pixel, multi-band ``xarray.Dataset``.  (Note that no ODC metadata is passed.)

tests/test_ogc_utils.py

@@ -70,16 +70,6 @@ def test_tz_bad_coords():
         tzinf = datacube_ows.ogc_utils.tz_for_coord(-88.8, 155.2)
 
 
-def test_local_date(dummy_ds):
-    ld = datacube_ows.ogc_utils.local_date(dummy_ds)
-    assert ld.year == 2020
-    assert ld.day == 26
-    tz = datacube_ows.ogc_utils.tz_for_dataset(dummy_ds)
-    ld = datacube_ows.ogc_utils.local_date(dummy_ds, tz)
-    assert ld.year == 2020
-    assert ld.day == 26
-
-
 def test_month_date_range_wrap():
     d = datetime.date(2019, 12, 1)
     a, b = datacube_ows.ogc_utils.month_date_range(d)