bad type check fix

sup3r/postprocessing/collectors/nc.py

@@ -79,17 +79,18 @@ def collect(
             logger.info(f'overwrite=True, removing {out_file}.')
             os.remove(out_file)
 
-        if not os.path.exists(out_file):
+        tmp_file = out_file + '.tmp'
+        if not os.path.exists(tmp_file):
             res_kwargs = res_kwargs or {}
             out = xr.open_mfdataset(collector.flist, **res_kwargs)
             features = list(out.data_vars) if features == 'all' else features
             features = set(features).intersection(_lowered(out.data_vars))
             for feat in features:
-                mode = 'a' if os.path.exists(out_file) else 'w'
+                mode = 'a' if os.path.exists(tmp_file) else 'w'
                 out[feat].load().to_netcdf(
-                    out_file, mode=mode, engine='h5netcdf', format='NETCDF4'
+                    tmp_file, mode=mode, engine='h5netcdf', format='NETCDF4'
                 )
-                logger.info(f'Finished writing {feat} to {out_file}.')
+                logger.info(f'Finished writing {feat} to {tmp_file}.')
 
         if write_status and job_name is not None:
             status = {
@@ -102,6 +103,8 @@ def collect(
             Status.make_single_job_file(
                 os.path.dirname(out_file), 'collect', job_name, status
             )
+        os.replace(tmp_file, out_file)
+        logger.info('Moved %s to %s.', tmp_file, out_file)
 
         logger.info('Finished file collection.')
 

sup3r/preprocessing/accessor.py

@@ -17,7 +17,7 @@
     _lowered,
     _mem_check,
     dims_array_tuple,
-    is_strings,
+    is_type_of,
     ordered_array,
     ordered_dims,
     parse_ellipsis,
@@ -97,7 +97,7 @@ def parse_keys(self, keys):
         dataset that can be passed to isel and transposed to standard dimension
         order."""
         keys = keys if isinstance(keys, tuple) else (keys,)
-        has_feats = is_strings(keys[0])
+        has_feats = is_type_of(keys[0], str)
         just_coords = keys[0] == []
         features = (
             list(self.coords)
@@ -132,7 +132,7 @@ def __getitem__(
         out = self._ds[features]
         out = self.ordered(out) if single_feat else type(self)(out)
         slices = {k: v for k, v in slices.items() if k in out.dims}
-        no_slices = is_strings(keys)
+        no_slices = is_type_of(keys, str)
         just_coords = all(f in self.coords for f in parse_to_list(features))
         is_fancy = self._needs_fancy_indexing(slices.values())
 
@@ -170,7 +170,7 @@ def __setitem__(self, keys, data):
             then this is expected to have a trailing dimension with length
             equal to the length of the list.
         """
-        if is_strings(keys):
+        if is_type_of(keys, str):
             if isinstance(keys, (list, tuple)) and hasattr(data, 'data_vars'):
                 data_dict = {v: data[v] for v in keys}
             elif isinstance(keys, (list, tuple)):
@@ -314,8 +314,9 @@ def sample(self, idx):
         ``(slice(0, 3), slice(1, 10), slice(None), ['u_10m', 'v_10m'])``"""
         isel_kwargs = dict(zip(Dimension.dims_3d(), idx[:-1]))
         features = (
-            self.features if not is_strings(idx[-1]) else _lowered(idx[-1])
+            _lowered(idx[-1]) if is_type_of(idx[-1], str) else self.features
         )
+
         out = self._ds[features].isel(**isel_kwargs)
         return self.ordered(out.to_array()).data
 

sup3r/preprocessing/base.py

@@ -20,7 +20,7 @@
 
 import sup3r.preprocessing.accessor  # noqa: F401 # pylint: disable=W0611
 from sup3r.preprocessing.accessor import Sup3rX
-from sup3r.preprocessing.utilities import composite_info
+from sup3r.preprocessing.utilities import composite_info, is_type_of
 
 logger = logging.getLogger(__name__)
 
@@ -359,9 +359,7 @@ def wrap(self, data):
         if data is None:
             return data
 
-        check_sup3rds = all(isinstance(d, Sup3rDataset) for d in data)
-        check_sup3rds = check_sup3rds or isinstance(data, Sup3rDataset)
-        if check_sup3rds:
+        if is_type_of(data, Sup3rDataset):
             return data
 
         if isinstance(data, tuple) and len(data) == 2:

sup3r/preprocessing/utilities.py

@@ -381,23 +381,16 @@ def contains_ellipsis(vals):
     )
 
 
-def is_strings(vals):
-    """Check if vals is a string or iterable of all strings."""
-    return isinstance(vals, str) or (
+def is_type_of(vals, vtype):
+    """Check if vals is an instance of type or group of that type."""
+    return isinstance(vals, vtype) or (
         isinstance(vals, (set, tuple, list))
-        and all(isinstance(v, str) for v in vals)
+        and all(isinstance(v, vtype) for v in vals)
     )
 
 
 def _get_strings(vals):
-    return [v for v in vals if is_strings(v)]
-
-
-def _is_ints(vals):
-    return isinstance(vals, int) or (
-        isinstance(vals, (list, tuple, np.ndarray))
-        and all(isinstance(v, int) for v in vals)
-    )
+    return [v for v in vals if is_type_of(v, str)]
 
 
 def _lowered(features):

tests/batch_queues/test_bq_general.py

@@ -126,7 +126,7 @@ def test_dual_batch_queue():
     ]
     sampler_pairs = [
         DualSampler(
-            Sup3rDataset((lr.data, hr.data)),
+            Sup3rDataset(low_res=lr.data, high_res=hr.data),
             hr_sample_shape,
             s_enhance=2,
             t_enhance=2,
@@ -179,7 +179,7 @@ def test_pair_batch_queue_with_lr_only_features():
     ]
     sampler_pairs = [
         DualSampler(
-            Sup3rDataset((lr, hr)),
+            Sup3rDataset(low_res=lr.data, high_res=hr.data),
             hr_sample_shape,
             s_enhance=2,
             t_enhance=2,
@@ -234,7 +234,7 @@ def test_bad_enhancement_factors():
         with pytest.raises(AssertionError):
             sampler_pairs = [
                 DualSampler(
-                    Sup3rDataset((lr, hr)),
+                    Sup3rDataset(low_res=lr.data, high_res=hr.data),
                     hr_sample_shape,
                     s_enhance=s_enhance,
                     t_enhance=t_enhance,