Fortity numpy array typehint parsing (deephaven#4671)

py/server/deephaven/dtypes.py

@@ -389,7 +389,14 @@ def _component_np_dtype_char(t: type) -> Optional[str]:
     if not component_type and sys.version_info.minor > 8:
         import types
         if isinstance(t, types.GenericAlias) and (issubclass(t.__origin__, Sequence) or t.__origin__ == np.ndarray):
-            component_type = t.__args__[1].__args__[0] if t.__args__[0] == typing.Any else t.__args__[0]
+            nargs = len(t.__args__)
+            if nargs == 1:
+                component_type = t.__args__[0]
+            elif nargs == 2:  # for npt.NDArray[np.int64], etc.
+                a0 = t.__args__[0]
+                a1 = t.__args__[1]
+                if a0 == typing.Any and isinstance(a1, types.GenericAlias):
+                    component_type = a1.__args__[0]
 
     if component_type:
         return _np_dtype_char(component_type)

py/server/tests/test_pyfunc_return_java_values.py

@@ -2,11 +2,13 @@
 #     Copyright (c) 2016-2023 Deephaven Data Labs and Patent Pending
 #
 import datetime
+import typing
 import unittest
 from typing import List, Union, Tuple, Sequence
 
 import numba as nb
 import numpy as np
+import numpy.typing as npt
 import pandas as pd
 
 from deephaven import empty_table, dtypes, DHError
@@ -211,14 +213,31 @@ def f() -> np.ndarray[np.int64]:
         self.assertIn("not support multi-dimensional arrays", str(cm.exception))
 
     def test_npt_NDArray_return_type(self):
-        import numpy.typing as npt
-
         def f() -> npt.NDArray[np.int64]:
             return np.array([1, 2], dtype=np.int64)
 
         t = empty_table(10).update(["X1 = f()"])
         self.assertEqual(t.columns[0].data_type, dtypes.long_array)
 
+    def test_ndarray_weird_cases(self):
+        def f() -> np.ndarray[typing.Any]:
+            return np.array([1, 2], dtype=np.int64)
+
+        t = empty_table(10).update(["X1 = f()"])
+        self.assertEqual(t.columns[0].data_type, dtypes.PyObject)
+
+        def f1() -> npt.NDArray[typing.Any]:
+            return np.array([1, 2], dtype=np.int64)
+
+        t = empty_table(10).update(["X1 = f1()"])
+        self.assertEqual(t.columns[0].data_type, dtypes.PyObject)
+
+        def f2() -> np.ndarray[typing.Any, np.int64]:
+            return np.array([1, 2], dtype=np.int64)
+
+        t = empty_table(10).update(["X1 = f2()"])
+        self.assertEqual(t.columns[0].data_type, dtypes.PyObject)
+
 
 if __name__ == '__main__':
     unittest.main()