Snowpark for Python basics in Snowflake - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ service_behavior

intermediate

What is the output of this Snowpark Python code snippet?

Consider the following Snowpark Python code that creates a DataFrame and applies a filter:

from snowflake.snowpark import Session

session = Session.builder.configs({"account": "xyz", "user": "abc", "password": "***", "role": "SYSADMIN", "warehouse": "COMPUTE_WH", "database": "TEST_DB", "schema": "PUBLIC"}).create()
df = session.create_dataframe([(1, 'apple'), (2, 'banana'), (3, 'cherry')], schema=["id", "fruit"])
filtered_df = df.filter(df["id"] > 1)
result = filtered_df.collect()

What will result contain?

Snowflake

from snowflake.snowpark import Session

session = Session.builder.configs({"account": "xyz", "user": "abc", "password": "***", "role": "SYSADMIN", "warehouse": "COMPUTE_WH", "database": "TEST_DB", "schema": "PUBLIC"}).create()
df = session.create_dataframe([(1, 'apple'), (2, 'banana'), (3, 'cherry')], schema=["id", "fruit"])
filtered_df = df.filter(df["id"] > 1)
result = filtered_df.collect()

A []

B [Row(id=1, fruit='apple')]

C [Row(id=2, fruit='banana'), Row(id=3, fruit='cherry')]

D SyntaxError due to incorrect filter syntax

💡 Hint

Remember that filter keeps rows where the condition is true.

The filter df["id"] > 1 keeps rows with id 2 and 3. The collect() method returns these rows as a list of Row objects.

🧠 Conceptual

intermediate

Which Snowpark Python method creates a DataFrame from a local list?

You want to create a Snowpark DataFrame from a Python list of tuples. Which method should you use?

A session.new_dataframe()

B session.create_dataframe()

C session.load_table()

D session.read_csv()

💡 Hint

Look for the method that directly accepts Python data.

The create_dataframe() method creates a DataFrame from local Python data like lists or tuples.

❓ Architecture

advanced

What happens when you call collect() on a Snowpark DataFrame?

In Snowpark for Python, what is the behavior of the collect() method on a DataFrame?

A It executes the query and returns all rows as a list of Row objects to the client.

B It streams the data row by row without loading all into memory.

C It saves the DataFrame as a table in the database without returning data.

D It only returns the schema of the DataFrame without executing the query.

💡 Hint

Think about what happens when you want to get all data from Snowflake to Python.

The collect() method runs the query and fetches all results into a list of Row objects in Python memory.

❓ security

advanced

Which practice improves security when connecting to Snowflake with Snowpark for Python?

When configuring a Snowpark Session in Python, which option is the most secure way to handle authentication?

A Using environment variables or external secrets manager for credentials

B Sharing credentials in plain text over email

C Hardcoding username and password directly in the script

D Using default public credentials without authentication

💡 Hint

Think about how to keep passwords safe and not expose them in code.

Using environment variables or a secrets manager keeps credentials out of code and reduces risk of leaks.

✅ Best Practice

expert

What is the best practice for managing Snowpark Session lifecycle in a Python application?

In a Python app using Snowpark, how should you manage the Session object to optimize resource use and avoid errors?

A Create a new Session for every query and close it immediately after

B Never close the Session to keep it always open

C Create multiple Sessions in parallel without closing any

D Create one Session per application run and reuse it for all queries, closing it at the end

💡 Hint

Consider resource efficiency and connection limits.

Reusing a single Session per app run reduces overhead and avoids exhausting connections. Closing it at the end cleans up resources.