Student repositories

For every lab, we will create a repository (repo) for each student. For example, if your CWL is goatcabin then for DSCI 521 lab 1 there will be a repository called DSCI_521_lab1_goatcabin. To see a list of all repositories that you have access to, navigate to the homepage of your year’s organization; for example, for the 2020-21 cohort, go to

NOTE: please do not confuse your personal lab-specific repository with the general course repository, which will be named something like DSCI_521_platforms-dsci_students. That repo is public to all students and is where you can access lectures, due dates, readings, etc.

How to submit

We anticipate that you will clone your lab-specific repository and do your work from within there. To submit your labs you must both push your work to and submit your rendered HTML file to Canvas. Your assignment will come bundled with a short script to render to HTML and push your work to Canvas. It is your responsibility to make sure your lab is submitted to both places and failure to do so will result in a deduction of mechanics marks.

Your notebook should include a link to your GitHub repository so that the TAs can click this when they are grading your HTML submission on Canvas (this will make it quicker for us to return your grades). You can push changes as many times as you want before the deadline; only the final version will be graded.

Your submission on GitHub


For your lab submission to GitHub, you are expected to commit regularly, not just once when you are done. You are required to make at least 3 commits per lab, and expected to make many more than that in practice. You may have mechanics marks from your lab if you fail to meet this minimum requirement.

Repo structure

You should have a well organized lab repo/directory structure, where your files are organized in a sane directory structure, e.g., data in a data directory, results in a results directory, etc. In cases where your lab repo is already organized into a directory structure, you can assume that structure is acceptable unless notified otherwise.

If the lab contains any autograded content (this would be a Jupyter notebook with “autograde” rubrics in it), please do not rename the main lab file or move it into a subdirectory as this causes problems for the autograding scripts.


In the main file in the lab/assignment repo, there is a place to optionally provide feedback on the lab. You are encouraged but not required to fill this in.


Your work must be reproducible from beginning to end. This requirement will become more relevant in the later parts of the program as you progress to more advanced analyses. A reproducible lab submission means:

  • All data must be in the repo, or linked to and grabbed by your code (e.g., curl, wget, read_csv("<URL>") etc) unless you are specifically instructed in the lab to not push your data to the repo.
  • All data cleaning/wrangling must be done programmatically (i.e., in R, Python, etc) so that it is reproducible.
  • All dependencies are listed (using a package or environment management strategy could make this easier in some cases… up to you!).

Make it easy for others to run your code

  • At the beginning of each code source file, load any necessary packages, so your dependencies are obvious.
  • At the beginning of each code source file, import anything coming from an external file. This will make it easy for someone to see which data files are required, edit to reflect their locals paths if necessary, etc. There are situations where you might not keep data in the repo itself (e.g., you are downloading data from a website).
  • Pretend you are someone else. Clone a fresh copy of your own repo from GitHub, read your instructions to re-run your code. Does it “just work”? It should!


The lab deadlines are given on the course repo and/or MDS calendar. These are hard deadlines. In particular, when the deadline passes you will lose write access to the repository. The default deadline for labs is Saturday at 6pm, but there may be some exceptions. For the policy on late submissions, see the MDS policies page.


You will receive your grades through Canvas.

Privacy notes

  • Your lab repos are visible to yourself, your TAs, all the core MDS staff, and some system administrators.

  • Although only the final version will be graded, all of your commits will be viewable, so don’t commit something private (like your email password) to your lab repo. Committing something and then removing it with another commit doesn’t remove it from the git history! It is theoretically possible to pull all traces of something out of the git history, but it’s not fun and uses more advanced git features.

  • and are run on Canadian servers, so all your data will be kept within Canada.