PythonESE

PythonESE is a Python web app to execute logic programs with different solvers, using the EmbASP framework.

IMPORTANT NOTE

The project is still at an early stage of development
It currently supports only the following formalisms and solvers:

• ASP (Answer Set Programming)
  • DLV2
  • DLV
  • Clingo
• Datalog
  • I-DLV

We encourage any feedback, but we do NOT recommend it for production yet.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

It requires only Python® and the Tornado package.

Installing

Download the Latest Release of PythonESE

Go to the directory where you downloaded the release and run the following command:

 python setup.py install

Running

Can be invoked using the WebSocket protocol, as explained in the Wiki of EmbASPServerExecutor

Dockerization

This repository provides also Docker containerization for PythonESE. Docker enables the encapsulation of the PythonESE Module within a lightweight, portable container, ensuring smooth deployment across various environments.

Getting Started

Deploying PythonESE using Docker is straightforward:

Installation

Ensure Docker is installed on your system (refer to the official Docker documentation for installation instructions). Then, clone this repository using the following command:

git clone https://github.com/DeMaCS-UNICAL/PythonESE.git

Building the Docker Image

A Docker image is a package that contains all the necessary to run application and it's used to create Docker containers. To create one navigate to the cloned repository directory and build the Docker image using the provided Dockerfile:

docker build -t python-ese .

Running the Docker Container

Once the Docker image is built, you can run a Docker container using the following command:

docker run -d --network host --mount type=bind,source=[your/path/to/config],target=/app/config --privileged=true python-ese 

The --network host option in the docker run command tells Docker to use the host network for the container. This means the container shares the same network stack as the host and can access network services running on the host directly.

The --mount type=bind, source=[your/path/to/config], target=/app/config option is used to create a bind mount. A bind mount is a type of mount that allows you to map a host file or directory to a container file or directory (for more information refer to the official Docker documentation). In this case we use mounts to provide the configuration file to the container.

The configuration file is a JSON file that contains the configuration of PythonESE. It must be placed in a directory on the host and the full path to this directory must be specified in the source option of the --mount option. The JSON schema needs also to be in the same directory.

For examples on how to create or modify the configuration file refer to the ne xt section. If no configuration file is provided the default configuration will be used.

The --privileged=true option is used to give the container full access to the host system. This is necessary to run the logic solvers like Clingo in a safe environment using Bubblewrap.

Configuration

config.json

This configuration file contains the settings for the PythonESE module.

Paths

This section contains paths to various resources.

• executables: Paths to different Logic Solvers like dlv, clingo, dlv2, idlv, and a timeout script(we use this).
• certificate: Paths to the certificate and key files for secure communication.

Server Properties

This section contains properties related to the server.

• port_number: The port number on which the server is running.
• cors_origins: A list of origins that are allowed to access the server resources.

Output

This section contains properties related to the output of the logic solvers.

• max_chars: The maximum number of characters that the output can contain.

Limits

This section contains limits for the execution of the logic solvers.

• time: The maximum amount of time (in seconds) that the solver is allowed to run.
• memory: The maximum amount of memory (in kilobytes) that the solver is allowed to use.

Available Options

This section contains options that can be passed to the logic solvers. Each solver has its own set of options.

Built With

• EmbASP - To execute logic programs with different solvers
• Tornado - To manage the web app
• timeout - To limit time and memory consumption of the executors under Linux

Versioning

We use Semantic Versioning for versioning. For the versions available, see the releases on this repository.

Credits

• Stefano Germano

From the Department of Mathematics and Computer Science of the University of Calabria and the Department of Computer Science of the University of Oxford

License

This project is licensed under the MIT License