README.md

covid-self-report

Github action to generate datasets

This github action can automatically generate datasets based on collected data. It will generate 3 kinds of files:

• globally merged data which takes all daily changes (daily variations) and appends them in a single CSV file. Tracks all variations since the beginning, also known as merge-all-days.csv
• Daily changes from the start, tracks all variations and merge them with previous data, same as daily changes but aggregated across time, one CSV file per day, also known as daily-reports
• Daily changes, tracks all variations and write them to CSV files one per day

Action configuration

This action can be configured with the following variables:

• daily_export_json_url required which is your firebase daily json exporting function URL
• geo_locations_csv_url ** required** which is the URL to the geolocation file for your instance (github raw)
• daily_export_json_token required the security token to access the json export function, AS SECRET
• merged_dataset_name the name of the globally merged dataset file, by default merge-all-days.csv
• daily_report_name the name of the daily reports, by default is daily-changes/{date}.csv where date is replaced by YEAR-MONTH-DAY. This means you'll have one file per day in a daily-reports directory
• daily_merged_report_name the name of the aggregated daily reports, by default daily-reports/{date}.csv where date is replaced by YEAR-MONTH-DAY. This means you'll have one file per day in a daily-aggregated directory
• csv_separator, by default ,
• today_filename filename of the today file (to have a unique route to latest data)

Using this action

1. You should have a repository dedicated for your datasets.
2. In your project, create a new .github/workflows/main.yml file
3. Put the following content in it

on:
    schedule:
        - cron: '0 * * * *' # runs the aggregation every hour

jobs:
    aggregate:
        runs-on: ubuntu-latest
        name: Automatic datasets generation
        steps:
            - name: Checkout
              uses: actions/checkout@v2
            - name: aggregation
              uses: ch-covid-19/data-github-action@master
              with:
                  daily_export_json_url: #...
                  geo_locations_csv_url: #...
                  daily_export_json_token: ${{ secrets.readToken }}
                  # Put other variables value here if you want
            - name: Commit changes
              run: |
                  git config --local user.email "YOUR EMAIL ADDRESS"
                  git config --local user.name "YOUR PSEUDO"
                  git add .
                  git commit -m "performed automatic datasets generation"
            - name: Push changes
              uses: ad-m/github-push-action@master
              with:
                  github_token: ${{ secrets.GITHUB_TOKEN }}

4. In order for the action to work properly, your project structure MUST match what you've defined in the action configuration variables. For example, if you use default values for daily_report_name and daily_merged_report_name, the action will try to write in daily-reports and daily-changes directories, if those don't exist the action will crash. To take care of this, you can create those directories and add a .gitkeep file in both of them, this will make sure they exist on github.

5. Push to your dataset repository and go to Actions tab to see it working!

Managing secrets

Github secrets are a way to provide secret data to your actions without writing them directly in your workflow yml file (and thus making it available for everyone). Instead you can use the ${{ secrets.mySecret }} template code to dynamically provide them. To create a secret:

• go to your datasets repository settings (where the action will work)
• On the left menu go to secrets
• From there you can add and manage secrets, you can then easily add a readToken secret