Testing - Processing iRacing race results file in a Cartesi Maching

This project contains code used to test the Descartes SDK, documented in https://cartesi.io/docs/, by processing a iRacing race results file in a Cartesi machine.

Getting Started

Requirements

docker
docker-compose
node 12.x
yarn
truffle

Environment

Download and run the Descartes SDK Environment ready-to-use artifact by executing:

wget https://github.com/cartesi/descartes-tutorials/releases/download/v0.2.0/descartes-env-0.2.0.tar.gz
tar -xzvf descartes-env-0.2.0.tar.gz

Then, start it up by running:

cd descartes-env
docker-compose up

Cartesi Playground

Clone this project and use the cartesi/playground Docker image, making sure to map the current directory:

docker run -it --rm \
  -e USER=$(id -u -n) \
  -e GROUP=$(id -g -n) \
  -e UID=$(id -u) \
  -e GID=$(id -g) \
  -v `pwd`:/home/$(id -u -n) \
  -w /home/$(id -u -n) \
  cartesi/playground:0.1.1 /bin/bash

Pack the processresult.sh script, that does the processing of the iRacing results file provided, for usage within a Cartesi Machine. For that build an ext2 file-system with the script file by running:

mkdir ext2
cp processresult.sh ext2

Still inside the playground, use the genext2fs tool to generate the file-system with those contents:

genext2fs -b 1024 -d ext2 processresult.ext2

Use the truncate tool to pad the results.csv file to 8K, and output.raw to 4K for usage with the Cartesi machine:

truncate -s 8K results.csv
truncate -s 4K output.raw

Still within the playground, execute the following command to process the iRacing race results file in a cartesi machine:

cartesi-machine \
  --flash-drive="label:processresult,filename:processresult.ext2" \
  --flash-drive="label:input,length:1<<13,filename:results.csv" \
  --flash-drive="label:output,length:1<<12,filename:output.raw,shared" \
  -- $'cd /mnt/processresult ; dd if=$(flashdrive input) of=results.raw ; ./processresult.sh results.raw > $(flashdrive output)'

The result of the processing will be stored in the output.raw file.

Aditional info regarding processing race results

The processing done above serves just as an example, in a real scenario we have to consider the following:

Each game has it's own format regarding race results and so will have it's own processing script too.
Each private league is going to be able to assign it's own points, bonus and penalties according to the race results. Also each league will have it's own prize scheme (crypto awarded for position) and deduction system (crypto deducted for damage/incidents). So it will exist another input file, a configuration file with parameters such as:
- Mapping for each position points;
- Bonus points according to league criteria (for example bonus for most laps led);
- Penalty points regarding incidents;
- Crypto prize for postion;
- Crypto deduction regarding incidents/damage;