Adventures in Machine Learning Maintaining Backward Compatibility in Software Projects: Strategies from Industry Experts - ML 164
Aug 29, 2024
59:52
Today, host Michael Berk and Ben Wilson dive deep into the multifaceted world of software engineering and data science with their insightful guest, Sandy Ryza a lead engineer from Dagster Labs. In this episode, they explore a range of intriguing topics, from the impact of the broken windows theory on code quality to the delicate balance of maintaining backward compatibility in evolving software projects.
Sandy talks about the challenges and learnings in transitioning from data science back to software engineering, including dependency management and designing for diverse use cases. They touch on the importance of clear naming conventions, tooling, and infrastructure enforcement to maintain high code quality. Plus, they discuss the intricate process of selecting and managing Python libraries, the satisfaction of refactoring old code, and the necessity of balancing new feature development with stability.
Michael and Ben will guide us through these essential discussions, emphasizing the significance of user-centric API design and the benefits of open source software. They also get practical advice on navigating API changes and managing dependencies effectively, with real-world examples from Dagster, Spark Time Series, and the libraries Numba and Pydantic.
Join them for an episode packed with valuable insights and strategies for becoming a top-end developer! Don’t forget to follow Sandy on Twitter and check out Dagster.io for more information on his work.
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Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
Sandy talks about the challenges and learnings in transitioning from data science back to software engineering, including dependency management and designing for diverse use cases. They touch on the importance of clear naming conventions, tooling, and infrastructure enforcement to maintain high code quality. Plus, they discuss the intricate process of selecting and managing Python libraries, the satisfaction of refactoring old code, and the necessity of balancing new feature development with stability.
Michael and Ben will guide us through these essential discussions, emphasizing the significance of user-centric API design and the benefits of open source software. They also get practical advice on navigating API changes and managing dependencies effectively, with real-world examples from Dagster, Spark Time Series, and the libraries Numba and Pydantic.
Join them for an episode packed with valuable insights and strategies for becoming a top-end developer! Don’t forget to follow Sandy on Twitter and check out Dagster.io for more information on his work.
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.