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The Ultimate Guide to Snowpark

You're reading from The Ultimate Guide to Snowpark Design and deploy Snowflake Snowpark with Python for efficient data workloads

Product type Paperback

Published in May 2024

Publisher Packt

ISBN-13 9781805123415

Length 254 pages

Edition 1st Edition

Languages

Python

Tools

Snowflake

Concepts

Data Engineering

Authors (2):

Shankar Narayanan SGS

Vivekanandan SS

View More author details

Table of Contents (14) Chapters

Preface

1. Part 1: Snowpark Foundation and Setup

2. Chapter 1: Discovering Snowpark FREE CHAPTER

3. Chapter 2: Establishing a Foundation with Snowpark

4. Part 2: Snowpark Data Workloads

5. Chapter 3: Simplifying Data Processing Using Snowpark

6. Chapter 4: Building Data Engineering Pipelines with Snowpark

7. Chapter 5: Developing Data Science Projects with Snowpark

8. Chapter 6: Deploying and Managing ML Models with Snowpark

9. Part 3: Snowpark Applications

10. Chapter 7: Developing a Native Application with Snowpark

11. Chapter 8: Introduction to Snowpark Container Services

12. Index

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13. Other Books You May Enjoy

Configuring the Snowpark development environment

The first step in developing Snowpark is to set up the Snowpark development environment. Developers have much flexibility regarding which integrated development environments (IDEs) they can use to get started with Snowpark; the only thing they need to do is install the Snowpark client application programmable interface (API) and connect to their Snowflake account. The development environment can be a local Python environment that contains your favorite IDE or the new Snowflake Python worksheets in Snowsight. This section will cover setting up a Snowpark Python worksheet and the local development environment.

Snowpark Python worksheet

Snowflake released Snowflake Worksheets for Python, a new type of worksheet in Snowsight for developing a Python-based Snowpark environment from within Snowflake. This game-changing feature allows developers to easily leverage the power of Snowpark Python within Snowsight to perform data processing...

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Authors (2)

Shankar Narayanan SGS

Shankar Narayanan SGS

Shankar Narayanan is a Technical Architect with over a decade of diverse experience leading and delivering large-scale Data and Cloud implementations for Fortune 500 companies across various industries. He has successfully implemented Snowflake Data Cloud for many organizations leading the customers to adopt Snowflake. He holds a bachelor's and master's degree in Computer science and holds many certifications in multi-cloud platforms and Snowflake. He is an award-winning blogger and actively contributes to various technical publications and open-source projects. For his technical contribution to the community, He has been selected as SAP Community Topic leader by SAP and is selected as one of the 72 Snowflake Data Heroes by Snowflake.

See other products by Shankar Narayanan SGS

Vivekanandan SS

Vivekanandan SS

Vivekanandan spearheads the GenAI enablement team at Verizon, leveraging over a decade of expertise in Data Science and Big Data. His professional journey spans across building analytics solutions and products across diverse domains, and proficient in cloud analytics and data warehouses. He holds a bachelor's degree in Industrial engineering from Anna University, a long distance program in Big Data analytics from IIM, Bangalore, and a master's in Data Science from Eastern University. As a seasoned trainer, he imparts his knowledge, specializing in Snowflake and GenAI, also a data science guest faculty and advisor for various educational institutes. His solution is ranked in the top 1 percentile in Kaggle Kernels globally.

See other products by Vivekanandan SS

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