An online code compiler for Java, C, C++ and Python for competitive programming and coding interviews. This service execute your code remotely using docker containers to separate the different environements of executions.

Supports Rest Calls, Apache Kafka and Rabbit MQ Messages.

{
    "input": "9",
    "expectedOutput": "0\n1\n2\n3\n4\n5\n6\n7\n8\n9\n",
    "sourceCode": "public class Test1 {\npublic static void main(String[] args) {\nint i = 0;\nwhile (i < 10) {\nSystem.out.println(i++);\n}}}",
    "language": "JAVA",
    "timeLimit": 15,
    "memoryLimit": 500
}

{
    "output": "0\n1\n2\n3\n4\n5\n6\n7\n8\n9\n",
    "expectedOutput": "0\n1\n2\n3\n4\n5\n6\n7\n8\n9\n",
    "status": "Accepted",
    "date": [2021,12,1,22,10,24,311828000]
}

To run this project you need a docker engine running on your machine.

Build docker image by typing the following command :

docker image build . -t compiler

Run the container by typing the following command

sudo docker container run -p 8080:8082 -v /var/run/docker.sock:/var/run/docker.sock -e DELETE_DOCKER_IMAGE=true -e EXECUTION_MEMORY_MAX=10000 -e EXECUTION_MEMORY_MIN=0 -e EXECUTION_TIME_MAX=15 -e EXECUTION_TIME_MIN=0 -t compiler

• The value of the env variable DELETE_DOCKER_IMAGE is by default set to true, and that means that each docker image is deleted after the execution of the container.
• The value of the env variable EXECUTION_MEMORY_MAX is by default set to 10 000 MB, and represents the maximum value of memory limit that we can pass in the request. EXECUTION_MEMORY_MIN is by default set to 0.
• The value of the env variable EXECUTION_TIME_MAX is by default set to 15 sec, and represents the maximum value of time limit that we can pass in the request. EXECUTION_TIME_MIN is by default set to 0.

It might be a good idea if you run a Portainer instance and mount it to the same volume, in order to have a total view of created images and running containers.

docker container run -p 9000:9000 -v /var/run/docker.sock:/var/run/docker.sock portainer/portainer

You can use the provided helm chart to deploy the project on k8s

helm install compiler ./k8s/helm_charts/compiler_chart

Note if you are running k8s using Minikube :

• you can reuse the Docker daemon from Minikube by running this command : eval $(minikube docker-env).
• set image pull policy to Never in the values.yml file.

There is four endpoints, one for Java, one for C, one for C ++ and another for Python. The call is done through POST requests to the following urls :

• localhost:8080/compiler/java
• localhost:8080/compiler/c
• localhost:8080/compiler/cpp
• localhost:8080/compiler/python

For the documentation visit the swagger page at the following url : http://localhost:8080/swagger-ui.html

• Accepted
• Wrong Answer
• Compilation Error
• Runtime Error
• Time Limit Exceeded
• Memory Limit Exceeded

{
    "output": "0\n1\n2\n3\n",
    "expectedOutput": "0\n1\n2\n3\n4\n5\n6\n7\n8\n9\n",
    "status": "Wrong Answer",
    "date": [2021,12,2 ,22,10,24,311828000]
}

{
    "output": "",
    "expectedOutput": "test compiler\n",
    "status": "Compilation Error",
    "date": [2021,12,1 ,22,10,24,311828000]
}

{
    "output": "",
    "expectedOutput": "test\ntest\ntest\n",
    "status": "Time Limit Exceeded",
    "date": [2021,12,3 ,22,10,24,311828000]
}

{
    "output": "abc\n",
    "expectedOutput": "abc\n",
    "status": "Accepted",
    "date": [2021,12,4 ,22,10,24,311828000]
}

It is also possible to visualize information about the images and docker containers that are currently running using these endpoints

We generate an entrypoint.sh file depending on the information given by the user (time limit, memory limit, programming language, and also the inputs).

You can use the compiler with an event driven architecture. To enable kafka mode you can pass to the container the following env variables :

• ENABLE_KAFKA_MODE : True or False
• KAFKA_INPUT_TOPIC : Input topic, json request
• KAFKA_OUTPUT_TOPIC : Output topic, json response
• KAFKA_CONSUMER_GROUP_ID : Consumer group
• KAFKA_HOSTS : List of brokers

sudo docker container run -p 8080:8082 -v /var/run/docker.sock:/var/run/docker.sock -e DELETE_DOCKER_IMAGE=true -e EXECUTION_MEMORY_MAX=10000 -e EXECUTION_MEMORY_MIN=0 -e EXECUTION_TIME_MAX=15 -e EXECUTION_TIME_MIN=0 -e ENABLE_KAFKA_MODE=true -e KAFKA_INPUT_TOPIC=topic.input -e KAFKA_OUTPUT_TOPIC=topic.output -e KAFKA_CONSUMER_GROUP_ID=compilerId -e KAFKA_HOSTS=ip_broker1,ip_broker2,ip_broker3 -t compiler

To enable Rabbit MQ mode you can pass to the container the following env variables :

• ENABLE_RABBITMQ_MODE : True or False
• RABBIT_QUEUE_INPUT : Input queue, json request
• RABBIT_QUEUE_OUTPUT : Output queue, json response
• RABBIT_USERNAME : Rabbit MQ username
• RABBIT_PASSWORD : Rabbit MQ password
• RABBIT_HOSTS : List of brokers

sudo docker container run -p 8080:8082 -v /var/run/docker.sock:/var/run/docker.sock -e DELETE_DOCKER_IMAGE=true -e EXECUTION_MEMORY_MAX=10000 -e EXECUTION_MEMORY_MIN=0 -e EXECUTION_TIME_MAX=15 -e EXECUTION_TIME_MIN=0 -e ENABLE_RABBITMQ_MODE=true -e RABBIT_QUEUE_INPUT=queue.input -e RABBIT_QUEUE_OUTPUT=queue.output -e RABBIT_USERNAME=guest -e RABBIT_PASSWORD=guest -e RABBIT_HOSTS=ip_broker1,ip_broker2,ip_broker3 -t compiler

Check out exposed prometheus metrics using the following url : http://localhost:8080/actuator/prometheus

• Zakaria Maaraki - Initial work - zakariamaaraki