[GitHub] [spark] xinrong-meng commented on a diff in pull request #37635: [WIP][SPARK-40131][PYTHON] Support NumPy ndarray in built-in functions

[GitBox <gi...@apache.org>]

xinrong-meng commented on code in PR #37635:
URL: https://github.com/apache/spark/pull/37635#discussion_r954103989


##########
python/pyspark/sql/types.py:
##########
@@ -2256,11 +2260,47 @@ def convert(self, obj: datetime.timedelta, gateway_client: GatewayClient) -> Jav
         )
 
 
+class NumpyScalarConverter:
+    def can_convert(self, obj: Any) -> bool:
+        return has_numpy and isinstance(obj, np.generic)
+
+    def convert(self, obj: "np.generic", gateway_client: GatewayClient) -> Any:
+        return obj.item()
+
+
+class NumpyArrayConverter:
+    def can_convert(self, obj: Any) -> bool:
+        return has_numpy and isinstance(obj, np.ndarray)
+
+    def convert(self, obj: "np.ndarray", gateway_client: GatewayClient) -> JavaObject:
+        from pyspark import SparkContext
+
+        gateway = SparkContext._gateway
+        assert gateway is not None
+
+        plist = obj.tolist()
+        ptpe = type(plist[0]) if len(plist) > 0 else float
+        tpe_dict = {
+            int: gateway.jvm.int,
+            float: gateway.jvm.double,
+            bool: gateway.jvm.boolean,
+            str: gateway.jvm.String,
+        }
+        jarr = gateway.new_array(tpe_dict[ptpe], len(plist))
+        for i in range(len(plist)):
+            jarr[i] = plist[i]
+        return jarr
+
+
 # datetime is a subclass of date, we should register DatetimeConverter first
 register_input_converter(DatetimeNTZConverter())
 register_input_converter(DatetimeConverter())
 register_input_converter(DateConverter())
 register_input_converter(DayTimeIntervalTypeConverter())
+register_input_converter(NumpyScalarConverter())
+# NumPy array satisfies py4j.java_collections.ListConverter,
+# so prepend NumpyArrayConverter
+register_input_converter(NumpyArrayConverter(), prepend=True)

Review Comment:
   ```py
   >>> from py4j.java_collections import ListConverter
   >>> ndarr = np.array([1, 2])
   >>> ListConverter().can_convert(ndarr)
   True
   ```



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