README.md

HPC Containers Survey

This is the HPC Containers survey started in 2024 Raw results are organized by year in the data folder and cleaned (UI ready) data in _data for jekyll to find. and will be deployed to an interface on GitHub pages (more likely).

• Results Data that is downloaded from the Google Form (5/11/2024)
• Cleaned Data that is used on the site.

Summary

• 2024 We got a total of 202 responses!

Development

Local

To develop the survey, you'll need to install jekyll and bundler and then after cloning the repository:

$ bundle install
$ bundle exec jekyll serve

And open your browser to http://127.0.0.1:4000/hpc-containers-survey/ to see the interface.

Docker Compose

If you want to run docsy jekyll via a container for development (dev) or production (prod) you can use containers. This approach requires installing docker-ce that now includes docker-compose. You can see the configuration in the docker-compose.yaml file.

Start Container

Once your docker-compose to download the base container and bring up the server:

$ docker compose up

You can then open your browser to http://localhost:4000 to see the server running. Depending on if you choose 0.0.0.0 or localhost you might have to go past the security warning about certificates.

Production

If you are deploying a container to production, you should remove the line to mount the bundles directory to the host in the docker-compose.yml. Change:

    volumes: 
      - "./:/srv/jekyll"
      - "./vendor/bundle:/usr/local/bundle"
      # remove "./vendor/bundle:/usr/local/bundle" volume when deploying in production

to:

    volumes: 
      - "./:/srv/jekyll"

This additional volume is optimal for development so you can cache the bundle dependencies, but should be removed for production.

Note : changes baseurl: "" in _config.yml when you are running in local and prod according to the requirement.

Instructions

1. Prepare Data

Since we need to do a bit of aggregation over values, the next step is to run the data file against the scripts/prepare_data.py to generate the output file. It doesn't need any special dependencies so you should be able to use your system Python. You can target the file of interest directly, and it will rewrite to the same folder and filename as json.

$ python scripts/prepare_data.py data/raw/2024/containers-in-hpc.csv

This will generate a parsed json file of results:

$ ls _data/
containers-in-hpc.json

Finally, some manual work is needed to clean the results (e.g., consolidate different variations of NA into one "NA" category, or other responses into an "Other" and that can be found in _data/cleaned. This is the data that goes into the site for graphs, and the file in root (the json we just produced) should be looked at when deriving manual insights.

Embed Results

You should then add a result to the _results folder, where each file coincides with a question (e.g., if we have the same question over two years it will be easy to compare the results). If you have a new question, just create a new page! The original creator @vsoch chose Chart.js, but of course you can change this plotting library if you like.

5. Share Results!

Finally, make a new post under _posts that follows suit of the other post to share an announcement for the results.

2024

• Survey Form

Resources and Thanks

• color palettes that are used in the plots can be seen here.
• jekyll-serif-theme