Debugging & Profiling Code, in Python and R

Looking for best practices to find bugs in your code? Looking for ways to improve the performance of the code that you write? Fortunately, there are tools available to users to speed up these tasks that are more robust than merely inserting and deleting print statements. This session will cover best practices for intermediate level code debugging and profiling to identify bugs and bottlenecks in the code that consume more than expected amount of resources. We will primarily focus on Python and R with some hands-on exercises. Participants will need to install some tools in advance to participate in the exercises--the facilitator will contact you in advance of the session to let you know how to install the needed software.

Learning objectives:

This workshop is geared toward computational researchers interested in learning debugging tools and best practices. Attendees will learn the best practices for debugging code and gain hands-on experience using debugging tools.

Knowledge prerequisites:

Basic Linux and some programming experience in Python and/or R

Hardware/software prerequisites:

Overarching requirements for all PICSciE workshops are listed on the advance setup guide for PICSciE virtual workshops (https://researchcomputing.princeton.edu/learn/workshops-live-training/hardware-and-software-requirements-picscie-workshops). In addition, for the hands-on portions of this session, participants will need some Python or R software on their laptops, depending on their preferred language.
Python users should install the Anaconda Python 3 distribution –" which includes Jupyter notebooks, NumPy, and conda –" on their laptops in advance. R users should have both R and RStudio installed on their laptops. Instructions for all this can be found on the PICSciE workshops requirements page for both Python and R (https://researchcomputing.princeton.edu/learn/workshops-live-training/hardware-and-software-requirements-picscie-workshops).

Alternately, participants who prefer to run Jupyter or RStudio remotely on one of Princeton’s systems can do so via the “myadroit” web interface to the Adroit cluster. To do so, you should first register for an account on Adroit (https://researchcomputing.princeton.edu/systems/adroit), as described in the advance setup guide for PICSciE workshops (https://researchcomputing.princeton.edu/learn/workshops-live-training/hardware-and-software-requirements-picscie-workshops). Then, connect to “myadroit” and start a Jupyter or RStudio session, as described at https://github.com/PrincetonUniversity/hpc_beginning_workshop/tree/master/03_web_interface.

Finally, the workshop format will be a short introduction using slides followed by instructor-led hands-on exercises. I strongly recommended trying to participate in the exercises, as attempting to read and debug code is the best way to learn debugging. If you’d like to participate in the Python and R hands-on activities, please follow the instructions to setup your laptop or desktop environment for debugging here: https://github.com/PrincetonUniversity/intro_debugging/blob/master/00_install/local_install_instructions.md (some overlap with the instructions at the links above, but some parts are additional, e.g. creating a conda environment for the session, or installing PyCharm).

All presentation materials are here: https://princetonuniversity.github.io/PUbootcamp_winter2021/. Additional materials are in this Github repo: https://github.com/PrincetonUniversity/intro_debugging.

Session format:

Lecture, demo, and hands-on exercises

What to expect:
Single workshop (one-off workshop –" 2 hours total)

Meet the facilitator:
Abhishek Biswas is a Research Software Engineer in the Department of Research Computing. He works on software engineering projects for various labs in the Department of Molecular Biology. He is generally involved in development of scalable high-performance computing and visualization pipelines for analyzing genomics, proteomics, and imaging datasets.

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

Wintersession | View More Events
Co-hosted with: PICSciE/Research Computing

Contact the organizers