How to implement explode functionality in Snowpark(Python) dataframe without using the explode() function?

I am working in Snowpark (Python), and I am using snowflake-snowpark-python library version 1.0.0. I have a version constraint, and hence cant upgrade. In this version, the function explode() is not supported.

How can I implement the same functionality using Snowpark Dataframe, without actually using explode() function? I have only one column that needs to be exploded.
My df looks like this:
df = session.create_dataframe(["rest_of_the_row",["A|B|C"]],schema=["record",product_code"])

My expected output is:

+----------------+------------+ 
|    record      |product_code|
+----------------+------------+
| rest_of_the_row| A          |
| rest_of_the_row| B          |
| rest_of_the_row| C          |
+----------------+------------+

I am further doing aggregations based on product_code.
Please suggest, how can I achieve this with my own implementation of explode() ?

I couldn't get your df statement to work so you may want to correct it. Assuming this is what your data looks like:

df = session.create_dataframe([{"record": "rest_of_the_row","product_code": "A|B|C"}])

df.show()

------------------------------------
|"RECORD"         |"PRODUCT_CODE"  |
------------------------------------
|rest_of_the_row  |A|B|C           |
------------------------------------

Then you can use split_to_table for this:

from snowflake.snowpark import functions as F
df.join_table_function("split_to_table", df['product_code'], F.lit("|")) \
  .select(F.col("RECORD"), F.col("VALUE").alias("PRODUCT_CODE")) \
  .show()

Explode takes an ARRAY or MAP (OBJECT) type as input, where as your input is a delimited string, so I don't think explode would work in your case anyway.