fix flake8 errors with new flake8 package

hsds/util/arrayUtil.py

@@ -164,24 +164,27 @@ def fillVlenArray(rank, data, arr, index):
             data_json,
         ]  # listify
 
-    if isVlen(data_dtype):
-        arr = np.zeros((npoints,), dtype=data_dtype)
-        fillVlenArray(np_shape_rank, data_json, arr, 0)
+    if not (None in data_json):
+        if isVlen(data_dtype):
+            arr = np.zeros((npoints,), dtype=data_dtype)
+            fillVlenArray(np_shape_rank, data_json, arr, 0)
+        else:
+            try:
+                arr = np.array(data_json, dtype=data_dtype)
+            except UnicodeEncodeError as ude:
+                msg = "Unable to encode data"
+                raise ValueError(msg) from ude
+        # raise an exception of the array shape doesn't match the selection shape
+        # allow if the array is a scalar and the selection shape is one element,
+        # numpy is ok with this
+        if arr.size != npoints:
+            msg = "Input data doesn't match selection number of elements"
+            msg += f" Expected {npoints}, but received: {arr.size}"
+            raise ValueError(msg)
+        if arr.shape != data_shape:
+            arr = arr.reshape(data_shape)  # reshape to match selection
     else:
-        try:
-            arr = np.array(data_json, dtype=data_dtype)
-        except UnicodeEncodeError as ude:
-            msg = "Unable to encode data"
-            raise ValueError(msg) from ude
-    # raise an exception of the array shape doesn't match the selection shape
-    # allow if the array is a scalar and the selection shape is one element,
-    # numpy is ok with this
-    if arr.size != npoints:
-        msg = "Input data doesn't match selection number of elements"
-        msg += f" Expected {npoints}, but received: {arr.size}"
-        raise ValueError(msg)
-    if arr.shape != data_shape:
-        arr = arr.reshape(data_shape)  # reshape to match selection
+        arr = np.array([]).astype(data_dtype)
 
     return arr
 

hsds/util/hdf5dtype.py

@@ -551,7 +551,7 @@ def getNumpyTypename(hdf5TypeName, typeClass=None):
 
 def createBaseDataType(typeItem):
     dtRet = None
-    if type(typeItem) == str:
+    if isinstance(typeItem, str):
         # should be one of the predefined types
         dtName = getNumpyTypename(typeItem)
         dtRet = np.dtype(dtName)
@@ -717,7 +717,7 @@ def createDataType(typeItem):
         dtRet = np.dtype(dtName)
         return dtRet  # return predefined type
 
-    if type(typeItem) != dict:
+    if not isinstance(typeItem, dict):
         raise TypeError("invalid type")
 
     if "class" not in typeItem:
@@ -735,7 +735,7 @@ def createDataType(typeItem):
         subtypes = []
         for field in fields:
 
-            if type(field) != dict:
+            if not isinstance(field, dict):
                 raise TypeError("Expected dictionary type for field")
             if "name" not in field:
                 raise KeyError("'name' missing from field")

tests/integ/helper.py

@@ -53,7 +53,7 @@ def getRangeGetEndpoint():
 
 def validateId(id):
     """Return true if the parameter looks like a UUID"""
-    if type(id) != str:
+    if not isinstance(id, str):
         # should be a string
         return False
     if len(id) != 38:

tests/unit/array_util_test.py

@@ -738,6 +738,20 @@ def testGetNumpyValue(self):
             self.assertTrue(False)
         except ValueError:
             pass  # expected
+
+    def testJsonToArrayOnNoneArray(self):
+        data_dtype = np.dtype("i4")
+        data_shape = [0, ]
+        data_json = [None]
+        arr = None
+
+        try:
+            arr = jsonToArray(data_shape, data_dtype, data_json)
+        except Exception as e:
+            print(f"Exception while testing jsonToArray on array with None elements: {e}")
+
+        self.assertTrue(len(arr) == 0)
+        self.assertTrue(arr.dtype == data_dtype)
 
 
 if __name__ == "__main__":