use type directly instead of converting to string

Author: sfc-gh-yuwang

src/snowflake/snowpark/context.py

@@ -45,7 +45,7 @@
 
 # internal only dictionary store the default precision of integral types, if the type does not appear in the
 # dictionary, the default precision is None.
-# example: _integral_type_default_precision = {"IntegerType": 9}, IntegerType default _precision is 9 now
+# example: _integral_type_default_precision = {IntegerType: 9}, IntegerType default _precision is 9 now
 _integral_type_default_precision = {}
 
 

src/snowflake/snowpark/types.py

@@ -371,9 +371,8 @@ def _fill_ast(self, ast: proto.DataType) -> None:
 # Numeric types
 class _IntegralType(_NumericType):
     def __init__(self, **kwargs) -> None:
-        class_name = type(self).__name__
         self._precision = kwargs.pop(
-            "_precision", context._integral_type_default_precision.get(class_name, None)
+            "_precision", context._integral_type_default_precision.get(type(self), None)
         )
 
         if kwargs != {}:

tests/integ/test_datatypes.py

@@ -557,8 +557,8 @@ def test_integral_type_default_precision(mock_default_precision):
 @pytest.mark.parametrize(
     "mock_default_precision",
     [
-        {"IntegerType": 5, "LongType": 4},
-        {"LongType": 19, "IntegerType": 10},
+        {IntegerType: 5, LongType: 4},
+        {LongType: 19, IntegerType: 10},
     ],
 )
 def test_end_to_end_default_precision(session, precision, mock_default_precision):
@@ -585,21 +585,20 @@ def test_end_to_end_default_precision(session, precision, mock_default_precision
         assert df.schema.fields[0].datatype._precision == precision
         assert (
             df.schema.fields[1].datatype._precision
-            == mock_default_precision["IntegerType"]
+            == mock_default_precision[IntegerType]
         )
         assert (
-            df.schema.fields[2].datatype._precision
-            == mock_default_precision["LongType"]
+            df.schema.fields[2].datatype._precision == mock_default_precision[LongType]
         )
 
         df.write.save_as_table(table_name, mode="overwrite", table_type="temp")
         result = session.sql(f"select * from {table_name}")
         assert result.schema.fields[0].datatype._precision == precision
         assert (
             result.schema.fields[1].datatype._precision
-            == mock_default_precision["IntegerType"]
+            == mock_default_precision[IntegerType]
         )
         assert (
             result.schema.fields[2].datatype._precision
-            == mock_default_precision["LongType"]
+            == mock_default_precision[LongType]
         )