Snowflake extends native Python support and data access to improve data cloud programmability – PCR

Of snow flakes Release of Snowpark for Python Native integration with Streamlit For rapid application development and iteration currently under development.

Snow parkSnowflake’s developer framework allows data scientists, data engineers, and application developers to build scalable pipelines, applications, and machine learning (ML) workflows directly in Snowflake using their preferred languages ​​and libraries. Opened a rich programming environment for. Snowflake extends what users can build with Snowpark for Python, giving them seamless access to Python’s open source package and library-rich ecosystem in the data cloud.

With a secure Python sandbox, Snowpark for Python runs on the same Snowflake computing infrastructure as applications written in the Snowflake pipeline and other languages. This gives Snowpark for Python the same scalability, resiliency, security, and compliance benefits that developers expect when building with Snowflake. Developers can use Snowpark to integrate Python-based data processing with Snowflake, giving them a unique opportunity to streamline and modernize their data processing architecture.

It is popular with developers due to Python’s robust syntax and rich ecosystem of open source packages. The ongoing partnership between Snowflake and Anaconda will give Snowflake seamless access to more Python packages, ensuring that all code runs in a secure sandbox environment. The Snow park acceleration The program has also continued to grow, primarily due to Snowflake’s advances in Python, with more and more partners building with Python to extend the power of DataCloud in the language of their choice.

Allegis Group, a global talent solutions company, relies on Snowpark to support ML and artificial intelligence (AI) solutions that leverage data from the Allegis Enterprise Data Platform on Snowflake.

Joe Norte, AI and MDM Architect for Allegis Group, said: It’s a framework suitable for data science and application development, providing teams with a seamless experience, easily working with data, bringing everyone together on the same platform, and reducing time to value. “

Christian Kleinerman, Senior Vice President of Products at Snowflake, said: “Our latest innovations extend the value of your data-driven ecosystem, make your data more accessible, and enable new ways to develop with data directly at Snowflake. Combined with Snowflake’s best-in-class data security and privacy, is changing the way teams experiment, iterate, and collaborate on data to add value. “

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Snowflake extends native Python support and data access to improve data cloud programmability – PCR

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