Adding test for virtual column plus typo.

packages/vaex-core/vaex/dataframe_protocol.py

@@ -71,7 +71,7 @@ class _DtypeKind(enum.IntEnum):
     DATETIME = 22
     CATEGORICAL = 23
 
-def convert_column_to_ndarray(col):
+def convert_column_to_ndarray(col) -> np.ndarray:
     """
     Convert an int, uint, float or bool column to a numpy array
     """
@@ -111,7 +111,7 @@ def buffer_to_ndarray(_buffer, _dtype) -> np.ndarray:
 
     return x
 
-def convert_categorical_column(col):
+def convert_categorical_column(col) -> Tuple[np.ndarray, np.ndarray]:
     """
     Convert a categorical column to a numpy array of codes, values and categories/labels
     """
@@ -136,7 +136,7 @@ class _VaexBuffer:
     Data in the buffer is guaranteed to be contiguous in memory.
     """
 
-    def __init__(self, x):
+    def __init__(self, x) -> None:
         """
         Handle only regular columns (= numpy arrays) for now.
         """
@@ -191,7 +191,7 @@ class _VaexColumn:
           doesn't need its own version or ``__column__`` protocol.
     """
 
-    def __init__(self, column, metadata : dict = {}):
+    def __init__(self, column, metadata : dict = {}) -> None:
         """
         Note: assuming column is an expression.
         """
@@ -440,7 +440,7 @@ def __init__(self, df, nan_as_null : bool = False) -> None:
         self._nan_as_null = nan_as_null
 
     @property
-    def metadata(self):
+    def metadata(self) -> Dict[str, Any]:
         is_category = {}
         labels = {}
         for i in self._df.get_names():
@@ -486,4 +486,4 @@ def get_chunks(self, n_chunks : Optional[int] = None) -> Iterable['_VaexDataFram
         """
         Return an iterator yielding the chunks.
         """
-        return {} # TODO
+        return {} # TODO

tests/dataframe_protocol_test.py

@@ -39,6 +39,18 @@ def test_categorical():
 	assert  df2['year'].tolist() == df['year'].tolist()
 	assert  df2['weekday'].tolist() == df['weekday'].tolist()
 
+def test_mixed_intfloatbool():
+	df = vaex.from_arrays(
+		x=np.array([True, True, False]),
+		y=np.array([1, 2, 0]),
+		z=np.array([9.2, 10.5, 11.8]))
+	df.add_virtual_column("r", "sqrt(y**2 + z**2)")
+	df2 = from_dataframe_to_vaex(df)
+	assert  df2.x.tolist() == df.x.tolist()
+	assert  df2.y.tolist() == df.y.tolist()
+	assert  df2.z.tolist() == df.z.tolist()
+	assert  df2.r.tolist() == df.r.tolist()
+
 def test_arrow_dictionary():
 	# ERRORS!
 	indices = pa.array([0, 1, 0, 1, 2, 0, None, 2])
@@ -52,5 +64,4 @@ def test_arrow_dictionary():
 	assert col.describe_categorical == (False, True, {0: 'foo', 1: 'bar', 2: 'baz'})
 
 	df2 = from_dataframe_to_vaex(df)
-	assert  df2.x.tolist() == df.x.tolist()
-
+	assert  df2.x.tolist() == df.x.tolist()