Hello Alberto,

thanks for the quick answer! Actually I want to pass a dataframe to the function, like:

@Dlt.table(
  name="test"
)
def create_table():
  test_df = spark.createDataFrame(["9","10","11","13"], "string").toDF("id")
  
  final_df = spark.sql("SELECT * FROM {df} WHERE id > 9", df=test_df)
   
  return final_df

 TypeError: _override_spark_functions.<locals>._dlt_sql_fn() got an unexpected keyword argument 'df',

And I get the same error when trying to only pass an integer for testing purposes, like

@Dlt.table(
  name="test"
)
def create_table():
  test_df = spark.sql("SELECT * FROM range(10) WHERE id > {bound1} AND id < {bound2}", bound1=7, bound2=9)
   
  return test_df

TypeError: _override_spark_functions.<locals>._dlt_sql_fn() got an unexpected keyword argument 'bound1',

Both spark.sql() statements work outside a DLT pipeline. So it seems like this is an DLT specific issue.