A COVID-19 tracker using the corona.lmao.ninja API
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Michael De Roover 0be817e929
Minor readme edit
3 hours ago
.gitignore Make cv work without external vars 3 months ago
README.md Minor readme edit 3 hours ago
cv Make getpct a little bit cleaner 4 hours ago


A COVID-19 tracker using the corona.lmao.ninja API

This is a COVID-19 tracker for Linux, allowing you to track, review and save statistics for your country, others or worldwide.

The data files are retrieved from corona.lmao.ninja which in turn receives its data from the Johns Hopkins University over at GitHub. Basically every application uses these, and I am also cross-verifying this. So far all the data appears consistent, although the stats from this program are more detailed than most others.

I wrote this application mostly to get as much data about the COVID-19 outbreak as possible and try to present it in a clean manner. I hope you’ll enjoy using it too.


This application depends on jq to parse the JSON output from corona.lmao.ninja. Most distributions provide this program from their repositories.


You can clone this repository to your computer using git clone https://git.ghnou.su/ghnou/cv. Afterwards you can run cv directly from it, without needing to install it. If you would like to install it, you can copy the program to /usr/local/bin or ~/.local/bin.

From the cloned repository you can run the application using ./cv [country], e.g. ./cv Belgium. For worldwide stats you can use ./cv all. If you wouldn’t want to type out your country every time, you can pass an environment variable $country. So something like country=Belgium ./cv would work too. In that case it would be best to load this variable from file (such as /etc/environment, ~/.bashrc or similar).

Data Collection

This program does not track any personal data or contact my servers to function. You can read the source code to confirm this.

The API responses from corona.lmao.ninja are saved to your local machine for subsequent data retrievals in ~/Documents/cv. This could be used to review stats from earlier days, and I’d like to implement a time-series view using these in the future.