Add some basic casting unit tests in Python

Change-Id: I3aacb21ca4f4090cee83da8e730c2a19ca2d0d99

cpp/src/arrow/compute/compute-test.cc

@@ -324,9 +324,6 @@ TEST_F(TestCast, UnsupportedTarget) {
 }
 
 TEST_F(TestCast, DateTimeZeroCopy) {
-  CastOptions options;
-  options.allow_int_overflow = false;
-
   vector<bool> is_valid = {true, false, true, true, true};
 
   std::shared_ptr<Array> arr;

python/pyarrow/tests/test_array.py

@@ -211,6 +211,73 @@ def test_list_from_arrays():
     assert result.equals(expected)
 
 
+def _check_cast_case(case, safe=True):
+    in_data, in_type, out_data, out_type = case
+
+    in_arr = pa.Array.from_pandas(in_data, type=in_type)
+
+    casted = in_arr.cast(out_type, safe=safe)
+    expected = pa.Array.from_pandas(out_data, type=out_type)
+    assert casted.equals(expected)
+
+
+def test_cast_integers_safe():
+    safe_cases = [
+        (np.array([0, 1, 2, 3], dtype='i1'), pa.int8(),
+         np.array([0, 1, 2, 3], dtype='i4'), pa.int32()),
+        (np.array([0, 1, 2, 3], dtype='i1'), pa.int8(),
+         np.array([0, 1, 2, 3], dtype='u4'), pa.uint16()),
+        (np.array([0, 1, 2, 3], dtype='i1'), pa.int8(),
+         np.array([0, 1, 2, 3], dtype='u1'), pa.uint8()),
+        (np.array([0, 1, 2, 3], dtype='i1'), pa.int8(),
+         np.array([0, 1, 2, 3], dtype='f8'), pa.float64())
+    ]
+
+    for case in safe_cases:
+        _check_cast_case(case)
+
+    unsafe_cases = [
+        (np.array([50000], dtype='i4'), pa.int32(), pa.int16()),
+        (np.array([70000], dtype='i4'), pa.int32(), pa.uint16()),
+        (np.array([-1], dtype='i4'), pa.int32(), pa.uint16()),
+        (np.array([50000], dtype='u2'), pa.uint16(), pa.int16())
+    ]
+    for in_data, in_type, out_type in unsafe_cases:
+        in_arr = pa.Array.from_pandas(in_data, type=in_type)
+
+        with pytest.raises(pa.ArrowInvalid):
+            in_arr.cast(out_type)
+
+
+def test_cast_integers_unsafe():
+    # We let NumPy do the unsafe casting
+    unsafe_cases = [
+        (np.array([50000], dtype='i4'), pa.int32(),
+         np.array([50000], dtype='i2'), pa.int16()),
+        (np.array([70000], dtype='i4'), pa.int32(),
+         np.array([70000], dtype='u2'), pa.uint16()),
+        (np.array([-1], dtype='i4'), pa.int32(),
+         np.array([-1], dtype='u2'), pa.uint16()),
+        (np.array([50000], dtype='u2'), pa.uint16(),
+         np.array([50000], dtype='i2'), pa.int16())
+    ]
+
+    for case in unsafe_cases:
+        _check_cast_case(case, safe=False)
+
+
+def test_cast_signed_to_unsigned():
+    safe_cases = [
+        (np.array([0, 1, 2, 3], dtype='i1'), pa.uint8(),
+         np.array([0, 1, 2, 3], dtype='u1'), pa.uint8()),
+        (np.array([0, 1, 2, 3], dtype='i2'), pa.uint16(),
+         np.array([0, 1, 2, 3], dtype='u2'), pa.uint16())
+    ]
+
+    for case in safe_cases:
+        _check_cast_case(case)
+
+
 def test_simple_type_construction():
     result = pa.lib.TimestampType()
     with pytest.raises(TypeError):

python/pyarrow/tests/test_convert_pandas.py

@@ -288,7 +288,7 @@ class TestPandasConversion(unittest.TestCase):
         schema = pa.schema([field])
         self._check_pandas_roundtrip(df, expected_schema=schema)
 
-    def test_all_nulls_to_numeric(self):
+    def test_all_nulls_cast_numeric(self):
         arr = np.array([None], dtype=object)
 
         def _check_type(t):