Description
In this talk, we’ll explore the challenges of running Python in enterprise data teams and share lessons learned from building for PyData developers at Snowflake, with an emphasis on flexibility, performance, and library compatibility. We'll focus on two key aspects: APIs and runtimes. First, we'll look at how you can run pandas at all data scales using Modin, and how this interoperates with other tools in the PyData stack. Then, we'll discuss ways to manage runtime compatibility, from customizing environments to working within notebook-based workflows.