BUG: Make np.record work on structured fields with no fields

This replaces some more uses of `bool(dt.fields)` and `bool(dt.names)` with `dt.names is not None`. `dt.fields is not None` would have worked too, but checking `.names` is more prevalent elsewhere
numpy · charris · Aug 23, 2019 · Aug 16, 2019 · Aug 17, 2019 · Aug 17, 2019
commit 5fbce6d395a6bfd1ec25022dcee4eef8c5bbad17
diff --git a/numpy/core/records.py b/numpy/core/records.py
@@ -254,7 +254,7 @@ def __getattribute__(self, attr):
             except AttributeError:
                 #happens if field is Object type
                 return obj
-            if dt.fields:
+            if dt.names is not None:
                 return obj.view((self.__class__, obj.dtype.fields))
             return obj
         else:
@@ -279,7 +279,7 @@ def __getitem__(self, indx):
         obj = nt.void.__getitem__(self, indx)
 
         # copy behavior of record.__getattribute__,
-        if isinstance(obj, nt.void) and obj.dtype.fields:
+        if isinstance(obj, nt.void) and obj.dtype.names is not None:
             return obj.view((self.__class__, obj.dtype.fields))
         else:
             # return a single element
@@ -431,7 +431,7 @@ def __new__(subtype, shape, dtype=None, buf=None, offset=0, strides=None,
         return self
 
     def __array_finalize__(self, obj):
-        if self.dtype.type is not record and self.dtype.fields:
+        if self.dtype.type is not record and self.dtype.names is not None:
             # if self.dtype is not np.record, invoke __setattr__ which will
             # convert it to a record if it is a void dtype.
             self.dtype = self.dtype
@@ -459,7 +459,7 @@ def __getattribute__(self, attr):
         # with void type convert it to the same dtype.type (eg to preserve
         # numpy.record type if present), since nested structured fields do not
         # inherit type. Don't do this for non-void structures though.
-        if obj.dtype.fields:
+        if obj.dtype.names is not None:
             if issubclass(obj.dtype.type, nt.void):
                 return obj.view(dtype=(self.dtype.type, obj.dtype))
             return obj
@@ -474,7 +474,7 @@ def __setattr__(self, attr, val):
 
         # Automatically convert (void) structured types to records
         # (but not non-void structures, subarrays, or non-structured voids)
-        if attr == 'dtype' and issubclass(val.type, nt.void) and val.fields:
+        if attr == 'dtype' and issubclass(val.type, nt.void) and val.names is not None:
        
8000
     val = sb.dtype((record, val))
 
         newattr = attr not in self.__dict__
@@ -508,7 +508,7 @@ def __getitem__(self, indx):
         # copy behavior of getattr, except that here
         # we might also be returning a single element
         if isinstance(obj, ndarray):
-            if obj.dtype.fields:
+            if obj.dtype.names is not None:
                 obj = obj.view(type(self))
                 if issubclass(obj.dtype.type, nt.void):
                     return obj.view(dtype=(self.dtype.type, obj.dtype))
@@ -564,7 +564,7 @@ def field(self, attr, val=None):
 
         if val is None:
             obj = self.getfield(*res)
-            if obj.dtype.fields:
+            if obj.dtype.names is not None:
                 return obj
             return obj.view(ndarray)
         else:

diff --git a/numpy/core/tests/test_records.py b/numpy/core/tests/test_records.py
@@ -437,6 +437,33 @@ def test_missing_field(self):
         arr = np.zeros((3,), dtype=[('x', int), ('y', int)])
         assert_raises(ValueError, lambda: arr[['nofield']])
 
+    @pytest.mark.parametrize('nfields', [0, 1, 2])
+    def test_assign_dtype_attribute(self, nfields):
+        dt = np.dtype([('a', np.uint8), ('b', np.uint8), ('c', np.uint8)][:nfields])
+        data = np.zeros(3, dt).view(np.recarray)
+
+        # the original and resulting dtypes differ on whether they are records
+        assert data.dtype.type == np.record
+        assert dt.type != np.record
+
+        # ensure that the dtype remains a record even when assigned
+        data.dtype = dt
+        assert data.dtype.type == np.record
+
+    @pytest.mark.parametrize('nfields', [0, 1, 2])
+    def test_nested_fields_are_records(self, nfields):
+        """ Test that nested structured types are treated as records too """
+        dt = np.dtype([('a', np.uint8), ('b', np.uint8), ('c', np.uint8)][:nfields])
+        dt_outer = np.dtype([('inner', dt)])
+
+        data = np.zeros(3, dt_outer).view(np.recarray)
+        assert isinstance(data, np.recarray)
+        assert isinstance(data['inner'], np.recarray)
+
+        data0 = data[0]
+        assert isinstance(data0, np.record)
+        assert isinstance(data0['inner'], np.record)
+
 
 def test_find_duplicate():
     l1 = [1, 2, 3, 4, 5, 6]