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Snowpark Use Cases

There are many use cases that the DataOps development environment optimizes, including development and testing with Snowpark using DataFrame.

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Examples on this page are using DevReady, the DataOps development environment in your browser.

Simple data frames example​

The DataOps development environment is fully pre-configured with all the main libraries and tools required for Snowpark development and testing.

If you look at the most straightforward script for developing with Snowpark using DataFrame:

from snowflake.snowpark import Session
import os

connection_parameters = {
  "account": os.environ['SNOWPARK_ACCOUNT'],
  "user": os.environ['SNOWPARK_USER'],
  "password": os.environ['SNOWPARK_PASSWORD'],
  "role": os.environ['SNOWPARK_ROLE'],
  "warehouse": os.environ['SNOWPARK_WAREHOUSE'],
  "database": os.environ['SNOWPARK_DATABASE'],
  "schema": os.environ['SNOWPARK_SCHEMA']
}


session = Session.builder.configs(connection_parameters).create()
df = session.create_dataframe([[1, 2], [3, 4]], schema=["a", "b"])
df = df.filter(df.a > 1)
df.show()
pandas_df = df.to_pandas()
result = df.collect()

You can click the Play button in the top right-hand corner, and DevReady will run this code locally, using Snowpark to execute the relevant pieces within Snowflake:

UDF/Stored procedure example​

To take a slightly more advanced example where you want to create a User Defined Function (UDF) or a Stored Procedure (SPROC) of your own design, e.g.:

from snowflake.snowpark import Session, GroupingSets
from snowflake.snowpark.functions import col,udf,sproc
from snowflake.snowpark.types import IntegerType
from snowflake.snowpark.functions import row_number
import os
import snowflake.snowpark
from snowflake.connector import connect

connection_parameters = {
  "account": os.environ['SNOWPARK_ACCOUNT'],
  "user": os.environ['SNOWPARK_USER'],
  "password": os.environ['SNOWPARK_PASSWORD'],
  "role": os.environ['SNOWPARK_ROLE'],
  "warehouse": os.environ['SNOWPARK_WAREHOUSE'],
  "database": os.environ['SNOWPARK_DATABASE'],
  "schema": os.environ['SNOWPARK_SCHEMA']
}

session = Session.builder.configs(connection_parameters).create()

@sproc(name="udf_demo", replace=True, packages=["numpy","xgboost","snowflake-snowpark-python","scikit-learn"])

def my_copy(session: snowflake.snowpark.Session) -> str:
    return session.get_current_account()

print("Running SPROC and UDF ...")
print(session.sql("call udf_demo()").collect())
print("Done SPROC and UDF ...")

Again use the Play button to run this:

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