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How to Package and Publish Your Python Code

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Training/Workshop Programming Languages Research & Data Analysis

Wed, Jan 14, 2026

1 PM – 2:30 PM EST (GMT-5)

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Are you looking to share your Python code? This workshop will show participants the best practices for making a compatible and installable Python package. Participants will work through a set of hands-on exercises that cover the various steps required to publish a package on the Python Package Index (PyPI).

Pre-Workshop Instructions: Please make sure that you have a GitHub account to get access to workshop codes. You will also need to have a Python installation. This can be accomplished by (1) having a local installation of Python (e.g., Anaconda Python),  or (2) using the Adroit cluster. For (1) see these directions. For (2) request an account on Adroit (VPN required if off-campus). Additional details for Adroit can be found in this guide.

More Software Engineering Training

Below is the full line-up of the Winter 2026 software engineering training by Research Computing:

Good Practices for Research Software Engineering on 1/12
Intro to Version Control with Git and GitHub on 1/12
Attaining vim Fluency: Edit as Fast as You Think on 1/13
Creating Reusable Python Code: From Notebooks to Scripts to Packages on 1/13
How to Package and Publish Your Python Code on 1/14
Gotcha! How to Write Software Tests to Improve Code Quality on 1/14
Debugging and Profiling Code in Python on 1/15
Continuous Integration and Continuous Delivery (CI/CD) with GitHub Workflows on 1/15
Tools That Help You Write Better Code on 1/16
Introduction to Software Reverse Engineering with Ghidra on 1/16

More Training Workshops

See the entire Research Computing Winter 2026 training program.

Speakers

Giannis Paraskevakos's profile photo

Giannis Paraskevakos

Ioannis joined the RSE group in 2023 to contribute to the Simons Observatory data analysis pipelines. Prior to that, he worked at an AI startup as the backend distributed systems engineer building the pipeline systems to combine external data and language models. His Ph.D research was focused on efficiently and effectively executing scientific data analytics on Supercomputer.

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Co-hosted with: GradFUTURES