CODENJOY Solution Runner

Makes possible to store Codenjoy players solutions and check them in isolated manner.

Introduction

For many and many years Codenjoy players had to configure and run their game clients locally. The clients should connect to a game server via websockets and try to pass a level using player's custom implementation of an algorithm. In such circumstances there are some problems. One of them is an inability to save the history of attempts in one place, and another one, which is more important, even if it could be possible, we can not be sure if the attempts are successful of not until we launch them by ourselves.

So this application is intended to solve these problems described above. It brings Codenjoy and its users several new opportunities. For example, Codenjoy now could be also a testing and hiring system for modern and progressive companies and teams.

How it works

The app uses Git and Docker for its purposes. It consumes requests that contains URL of public Git repository with a player's solution and link to Codenjoy server with the player's id and code. Further, it pulls the solution from master branch of the repo, save it locally with, build it and run it in new separate Docker container. Build and runtime logs accumulate in the solution folder and can be given to front-end.

How to run

Run with Maven right on the local host

The command below will build the application using Maven and run in right on the local host:

$ sh ./build/run_with_maven_war.sh

or

$ sh ./build/run_with_maven_spring.sh

For configuring application's behaviour you can set these environment variables.

Variable	Defaults	Description
context	/client-runner	Web application context
server.port	8081	Web application port
service.solutions.path	./solutions	Where to store downloaded solutions
service.solutions.pattern	yyyy-MM-dd'_'HH-mm-ss	How to name each solution folder
docker.container.memoryLimitMB	0	Memory limit in MB
docker.container.cpuPeriod	100000	Limit the CPU CFS (Completely Fair Scheduler) period
docker.container.cpuQuota	-1	Limit the CPU CFS quota

Run in Docker container [Recommended]

The command below will build and start a container with the app and with default config:

$ sh ./build/run_with_docker-compose.sh

For configuring container's port or folder path, where solutions will be stored, change docker-compose/.env file:

$ nano ./docker-compose/.env

For configuring application's behaviour, change docker-compose/client-runner.env file with variables from the table above:

& nano ./docker-compose/client-runner.env

Client platforms support

At the moment solution runner supports client, written in:

• Java with Maven
• Ruby
• Python
• JavaScript (Node.js)

How to add a new platform support

There are an enum class com.codenjoy.clientrunner.model.Platform and folder with dockerfiles in src/main/resources. In order to add support for another platform, you should define this platform in the enum following already existing principle, and after that create valid Dockerfile and store it in src/main/resources/dockerfiles/<platform_name_lowercase>/Dockerfile.

For example, lets add Python support (which is already added, of course):

1. In com.codenjoy.clientrunner.model.Platform write PYTHON("main.py"), where "main.py" is Python-specific project file which helps client runner automatically detect incoming solution's platform.

2. Create new Dockerfile and store it in src/main/resources/dockerfiles/python/Dockerfile:

FROM python:3

ARG CODENJOY_URL
ENV CODENJOY_URL_VAR=$CODENJOY_URL

COPY . /app

ENTRYPOINT python -u /app/main.py "${CODENJOY_URL_VAR}"

Pay attention that there is necessary CODENJOY_URL argument which is URL with a player's id and code. It's automatically passed to all launched clients.