Kickstart Snowpark with Python

Description:

Unlock the full potential of Snowpark, the innovative developer experience for Snowflake. This course equips you with the expertise to leverage your preferred language—Scala, Java, or Python—alongside the SQL interface. Discover how to harness the Snowpark API to create a customized software development environment. Say goodbye to exporting data to external environments and tap into Snowflake's powerful computing capabilities. Dive into reading and writing operations, transformations, queries, and the creation of Python UDFs (user-defined functions) using Snowpark.

Duration: 1 day

Course Code: BDT300

Learning Objectives

By the end of this course, you will:

• Get Started with Snowpark and Python Integration in Snowflake
• Leverage Snowpark for -Efficient Structured Data Reading and Writing in Snowflake
• Master the Art of Handling Semi-Structured Data Using Snowpark
• Perform Real-Time Data -Transformations While --Loading with Snowpark
• Seamlessly Integrate Third-Party Python Libraries to Create User-Defined Functions (UDFs) in Snowpark.

• Basic knowledge Snowflake and Python.

• This course is designed for anyone interested in using the Snowpark API using Python. It is geared towards data engineers, architects, QA engineers, BI professionals, and data analysts who want to use Python to handle data processing in Snowflake.

• This course is designed for anyone interested in using the Snowpark API using Python. It is geared towards data engineers, architects, QA engineers, BI professionals, and data analysts who want to use Python to handle data processing in Snowflake.

Course Outline:

1. Introduction to Snowpark and Python Integration

• Overview of Snowpark and its importance in Snowflake data processing
• Brief introduction to Python’s role in Snowpark development
• Setting up Snowpark development environment with Python
• Hands-on: Execute a basic Python script to use Snowpark API

2. Use Snowpark to read and write structured data in Snowflake

• Create Snowpark Dataframe
• Apply schema to Dataframe
• Read from S3: CSV and JSON
• Write from S3 to Snowflake table, CSV, JSON
• Hands-on lab with these topics

3. Handling semi-structured data with Snowpark

• Create dataframe from S3 JSON files
• Copy data into snowflake dataframe
• Create dataframe from parquet files
• Copy data into S3 parquet files into Snowflake table
• Handle error records
• Hands-on labs with these topics

4. Perform transformations while loading

• Using the Snowpark’ aggregation framework
• Perform grouping of data
• Using Window functions
• Using Join and the “using” clause
• Hands-on labs with these topics

5. Integration third party Python libraries to create UDF

• Build generic usable components library in Python
• Create Snowpark UDF
• Using vectorized UDFs
• Integrating external packages
• Hands-on lab with these topics

Training material provided: Yes (Digital format)

Hands-on Lab: Instructions will be provided to students to create “trial” snowflake account. Instructions will be provided in class to install and use Snowpark