Tuesday 13 February 2024, 9:30am to 11:30am
RegistrationRegistration not required - just turn up
Code ClinicStop wasting valuable time trying to code on your own, get help...
Stop wasting valuable time trying to code on your own, get help!
The RSE group are trialling weekly support sessions for the Lent term (Jan - Mar). There are run by the RSE team (which is part of the Data Science Institute). These sessions are open to any researchers at Lancaster University (Academics, Professional Services, PDRAs, and PhD students) to get help with programming problems, and to get more general advice on best practises for writing code.
At each session, members for the RSE team will be on hand to advise, troubleshoot and suggest ways to improve your computational workflows.
Who are these for? If you are
- Thinking of ways to improve your code?
- Want to automate a task (e.g: series of scripts)?
- Unsure of which software tools to use for your project?
- You have a lot of data and need help organising, storing, accessing or visualising it?
- Need some advice on optimising your code?
- Want to know whether your code could run faster on multiple cores or GPUs?
- Want to re-write your code written in one language (e.g: Excel) in another language such as Python?
- Need help with version control?
- Want to know more about making your code open and/or citable?
then these are for you and we can help.
The Open Research Lab in the Library
Every Tuesday (09:30 - 11:30).
Book a slot
Whilst booking is not essential, it is advised. Sign up for the event on libCal, and you will be emailed a 20-minute slot in the session. Non - booked drop-ins will be helped as soon as possible, but bookings will take priority.
Preparing for your session
- Please provide examples of the code you are working on, if possible. Often the best way to do this is via a “Minimal, Reproducible Example” (https://stackoverflow.com/help/minimal-reproducible-example) but sometimes this isn’t possible. It is good software engineering practice to share code using collaborative version control (e.g. GitHub) and it is good open research practice to do this publicly, although these practices are not always possible.
- Sometimes helping with the problem requires us to understand your data. Sharing data is not always possible. A readme or data dictionary is particularly useful in these situations.
- Please provide any information you can on the hardware, operating system, packages you are using.
Cancelling your session
If you cannot attend the session, please cancel the registration as soon as you can.
Any questions before your session?
If you have any questions before the session, or aren't sure if it is suited to you, the please email us at email@example.com
Interested in getting involved?
If you would like to get involved as a helper, please contact firstname.lastname@example.org