User-defined functions with Snowpark in Snowflake - Step-by-Step Execution

Process Flow - User-defined functions with Snowpark

Define function in Snowpark

↓

Register function in Snowflake

↓

Call function in SQL or Snowpark

↓

Function executes with input

↓

Returns output to caller

This flow shows how you create a function in Snowpark, register it in Snowflake, then call it to get results.

Execution Sample

Snowflake

from snowflake.snowpark import Session
from snowflake.snowpark.functions import udf

@udf
def add_one(x: int) -> int:
    return x + 1

session.udf.register(add_one, name='add_one')

Defines a simple function that adds 1 to a number and registers it as a Snowflake UDF.

Process Table

Step	Action	Input	Function Execution	Output
1	Define function add_one	N/A	Function code stored	N/A
2	Register function in Snowflake	N/A	Function linked to Snowflake	N/A
3	Call add_one with input 5	5	Compute 5 + 1	6
4	Call add_one with input 10	10	Compute 10 + 1	11
5	Call add_one with input -3	-3	Compute -3 + 1	-2
6	Call add_one with input 0	0	Compute 0 + 1	1
7	No more calls	N/A	N/A	Execution ends

💡 All function calls completed, no more inputs to process.

Status Tracker

Variable	Start	After Call 1	After Call 2	After Call 3	After Call 4	Final
input_value	N/A	5	10	-3	0	N/A
output_value	N/A	6	11	-2	1	N/A

Key Moments - 3 Insights

Why do we register the function after defining it?

Registering links the Python function to Snowflake so it can be called inside SQL or Snowpark, as shown in step 2 of the execution_table.

What happens if we call the function with a negative number?

The function still adds 1 correctly, as seen in step 5 where input -3 returns output -2.

Can the function be called multiple times with different inputs?

Yes, each call runs the function with the new input and returns the output, demonstrated in steps 3 to 6.

Visual Quiz - 3 Questions

Look at the execution_table, what is the output when the input is 10?

A 9

B 10

C 11

D 12

💡 Hint

Check row 4 in the execution_table where input is 10.

At which step does the function get registered in Snowflake?

A Step 2

B Step 3

C Step 1

D Step 4

💡 Hint

Look at the Action column in the execution_table for registration.

If we call add_one with input 0, what will be the output?

A 0

B 1

C -1

D 2

💡 Hint

Refer to step 6 in the execution_table for input 0.

Concept Snapshot

User-defined functions (UDFs) in Snowpark let you write Python code to run inside Snowflake.
Define the function in Python, then register it with session.udf.register.
Call the function in SQL or Snowpark with inputs.
The function runs inside Snowflake and returns outputs.
This allows custom logic close to your data.

Full Transcript

This visual execution shows how to create and use user-defined functions with Snowpark in Snowflake. First, you define a Python function that does some work, like adding one to a number. Then you register this function with Snowflake so it can be called inside SQL or Snowpark code. When you call the function with different inputs, Snowflake runs the function code and returns the results. The execution table traces each step: defining, registering, calling with inputs, and outputs returned. The variable tracker shows how inputs and outputs change with each call. Key moments clarify why registration is needed, how negative inputs work, and that multiple calls are possible. The quiz tests understanding of outputs and steps. This helps beginners see how Snowpark UDFs work step-by-step.

Practice

1. What is the main purpose of user-defined functions (UDFs) in Snowflake using Snowpark?

easy

A. To manage user permissions and roles

B. To create new database tables automatically

C. To run custom code inside Snowflake and reuse logic

D. To monitor Snowflake account usage

Solution

1. Step 1: Understand what UDFs do

   User-defined functions let you write your own code to run inside Snowflake, which helps reuse logic.

2. Step 2: Identify the main purpose

   UDFs simplify queries by encapsulating custom logic, not managing tables, permissions, or monitoring.

3. Final Answer:

   To run custom code inside Snowflake and reuse logic -> Option C

4. Quick Check:

   UDFs = Custom code reuse [OK]

Hint: UDFs run your own code inside Snowflake [OK]

Common Mistakes:

• Thinking UDFs create tables
• Confusing UDFs with security roles
• Assuming UDFs monitor usage

2. Which of the following is the correct way to define a simple Python UDF in Snowpark that adds 10 to an integer input?

easy

A. def add_ten(x): return x + 10

B. def add_ten(x): x + 10

C. def add_ten(x): print(x + 10)

D. def add_ten(x): return x - 10

Solution

1. Step 1: Check function syntax

   A Python function must use 'return' to output a value; def add_ten(x): return x + 10 correctly returns x + 10.

2. Step 2: Verify logic correctness

   def add_ten(x): return x + 10 adds 10 to input x, matching the requirement; others either miss return or subtract.

3. Final Answer:

   def add_ten(x): return x + 10 -> Option A

4. Quick Check:

   Return correct value with 'return' keyword [OK]

Hint: Always use 'return' to output from Python UDFs [OK]

Common Mistakes:

• Omitting the return statement
• Using print instead of return
• Returning wrong calculation

3. Given this Snowpark Python UDF code:

def multiply_by_two(x):
    return x * 2

result = multiply_by_two(5)

What is the value of result?

medium

A. 5

B. None

C. 25

D. 10

Solution

1. Step 1: Understand the function logic

   The function multiplies input x by 2 and returns the result.

2. Step 2: Calculate the function output for input 5

   5 multiplied by 2 equals 10, so result is 10.

3. Final Answer:

   10 -> Option D

4. Quick Check:

   5 * 2 = 10 [OK]

Hint: Multiply input by 2 to get output [OK]

Common Mistakes:

• Confusing multiplication with addition
• Assuming function returns None without return
• Mistaking input for output

4. You wrote this Snowpark Python UDF:

def square(x):
    x * x

When you run it, you get no output. What is the problem?

medium

A. Function name is invalid

B. Missing return statement to output the result

C. Syntax error due to missing colon

D. Input parameter x is not defined

Solution

1. Step 1: Check function syntax

   The function lacks a 'return' statement, so it does not output any value.

2. Step 2: Understand Python function behavior

   Without 'return', the function returns None by default, causing no output.

3. Final Answer:

   Missing return statement to output the result -> Option B

4. Quick Check:

   Functions need 'return' to output values [OK]

Hint: Always include 'return' to output from functions [OK]

Common Mistakes:

• Assuming last expression auto-returns
• Thinking function name causes error
• Confusing missing colon with missing return

5. You want to create a Snowpark Python UDF that returns the length of a string only if it is not empty; otherwise, it returns 0. Which function correctly implements this?

hard

A. def str_length(s):
if s:
return len(s)
else:
return 0

B. def str_length(s):
return len(s) if s != '' else 0

C. def str_length(s):
if s == '':
return len(s)
else:
return 0

D. def str_length(s):
return len(s) or 0

Solution

1. Step 1: Understand the condition for empty string

   Empty strings are falsy in Python, so 'if s:' checks if string is not empty.

2. Step 2: Verify correct return values

   If string is not empty, return its length; else return 0. def str_length(s): if s: return len(s) else: return 0 matches this logic exactly.

3. Final Answer:

   def str_length(s): if s: return len(s) else: return 0 -> Option A

4. Quick Check:

   Check string truthiness to decide length [OK]

Hint: Use 'if s:' to check non-empty string [OK]

Common Mistakes:

• Checking 's != \"\"' crashes on None
• Returning length for empty string incorrectly
• Using 'or' without proper condition