Creating Reusable Python Code: From Notebooks to Scripts to Packages

Python’s popularity stems in large part from its convenience for creating quick data analyses in Jupyter notebooks. This workshop will explore how to extend code in such notebooks to make it easier for your colleagues to validate and extend your analyses. We will cover writing simple scripts as well as more complicated tools with command-line interfaces. Time allowing, we will also discuss the benefits of grouping related scripts into packages, and introduce the basics of structuring packages using object-oriented design.

Be sure to also attend "Good Practices for Research Software Engineering" (https://my.princeton.edu/rsvp?id=1924479) which starts 1-hour before "Creating Reusable Python Code: From Notebooks to Scripts to Packages" in the same room.

Meet the Facilitator:
Michal Grzadkowski joined Princeton Research Computing in 2021 after five years working as a Research Software Engineer at Oregon Health & Science University, where his primary project involved studying the application of machine learning models to better understand the impacts of mutations commonly implicated in tumorigenesis. This involved implementing novel methods for representing the taxonomies of mutations present in cancer cohorts, as well as developing software for deploying and consolidating thousands of classification models on a high-performance compute cluster. His present work focuses on optimizing pipelines for generating quantitative assessments of the contributions various types of assets can make to a power grid’s ability to satisfy the demand for electricity over a given time frame.

What to Expect:
Single Workshop

To request accommodations for this event, please contact the workshop or event facilitator at least 3 working days prior to the event.

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Co-hosted with: PICSciE/Research Computing

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