Preliminary Work¶
We welcome all types of learners to our event, from professional software developers to people just getting started. Based on previous experience, participants gain more from our hackweeks when they arrive having a preliminary understand of some of the foundational tools of data science workflows. These skills include knowing how to:
navigate a Jupyter Notebook environment
conduct file management, text editing and other basic tasks from a command line interface
add and commit changes in Git, and push and pull content from GitHub
create simple scientific workflows in Python
SnowEx Software Carpentry Session¶
We will be offering a preliminary training session for anyone wishing to brush up on fundamentals, or for those of you who are new to open source workflows. This will be a two day event modeled after a Software Carpentry training.
Note
We will be hosting a SnowEx Software Carpentry training as a virtual event during June 21 - 22.
You can view our Software Carpentry Schedule for more information.
Required setup¶
Attention
Please make sure to find some time to go through the below material before the hackweek.
GitHub Account¶
Everyone attending snowex-hackweek will require obtaining a GitHub account. Visit our GitHub instruction page to learn how!
Slack Account¶
All of our communication throughout the hackweek will be done using the SnowEx Slack workspace. With your invite to the hackweek, you should also have received a separate email to join the Slack workspace. Upon accepting the invite, please take a moment to complete your Slack profile. Having your name and picture with your Slack account helps us and your peers to identify you on Slack and builds a more personal community throughout the week.
JupyterHub¶
We will offer all tutorials within the Jupyter Hub computing environment. Visit our Introduction to Jupyter Hub page to learn more!
Git¶
All content of the hackweek will be shared via GitHub and interacting with the
website will be done via the git
command. Visit Setting up the git
command
to learn how to configure that!
Optional setup¶
Python¶
Dive deeper into how Python is managed and installed on the JupyterHub and how you can install that on your personal machine.