[GitHub] [spark] HyukjinKwon commented on a change in pull request #32955: [SPARK-35344][PYTHON] Support creating a Column of numpy literal value in pandas-on-Spark

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HyukjinKwon commented on a change in pull request #32955:
URL: https://github.com/apache/spark/pull/32955#discussion_r655853638



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File path: python/pyspark/pandas/spark/functions.py
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@@ -32,6 +41,22 @@ def repeat(col: Column, n: Union[int, Column]) -> Column:
     return _call_udf(sc, "repeat", _to_java_column(col), n)
 
 
+def lit(literal: Any) -> Column:
+    """
+    Creates a Column of literal value.
+    """
+    if isinstance(literal, np.int64):

Review comment:
       @xinrong-databricks, I think we can just support this natively all across PySpark. Can you add an input converter here (https://github.com/apache/spark/blob/20750a3f9e13a2f02860859f87bbc38a18cba85e/python/pyspark/sql/types.py#L1608-L1622) and see if it works?
   
   Also, I think we can simplify it by `item()` (https://stackoverflow.com/a/11389998/2438480) with  `np.generic` type check (https://numpy.org/doc/stable/reference/arrays.scalars.html).
   
   cc @ueshin @itholic too




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