PyData Zurich: Rust in ML & Polars validation

Talk #1: Rust in the data science and machine learning stack

The Python ecosystem has seen the emergence of several high-profile tools and libraries developed with the Rust programming language, including the ruff linter/formatter, the uv package/project manager, the polars dataframe library, the pydantic data validation library, and HuggingFace's tokenizers.

This talk will explore the role that Rust can play in the data science and machine learning stack, through case studies, high-level considerations, and practical examples. It will include a concise introduction to the language and techniques for integrating it with Python.

We aim to give attendees the tools to understand when it makes sense to reach for Rust, particularly in the context of data-intensive applications, and how to do so effectively.

Talk #2: Dataframely — A declarative, polars-native data frame validation library

In this talk, we will talk about the motivation behind building dataframely in more detail and lead the audience through its key features. We will also touch upon our learnings in developing robust data pipelines that establish clear contracts for the design of data transformations. In our experience, this significantly improves communication among developers and comprehensibility of the entire pipeline.

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The event is kindly hosted and sponsored by Galaxus. The talks will be followed by informal drinks.