gym-csle-cyborg

An OpenAI gym reinforcement learning environment API for the CybORG environment

PyPI version PyPI - Downloads

Requirements

  • Python 3.8+
  • csle-base
  • csle-common
  • csle-attacker
  • csle-defender
  • csle-collector
  • gymnasium for specifying the RL environment API

Development Requirements

  • Python 3.8+
  • flake8 (for linting)
  • flake8-rst-docstrings (for linting docstrings)
  • tox (for automated testing)
  • pytest (for unit tests)
  • pytest-cov (for unit test coverage)
  • pytest-mock (for mocking tests)
  • pytest-grpc (for grpc tests)
  • mypy (for static typing)
  • mypy-extensions (for static typing)
  • mypy-protobuf (for static typing)
  • types-PyYaml (for static typing)
  • types-paramiko (for static typing)
  • types-protobuf (for static typing)
  • types-requests (for static typing)
  • types-urllib3 (for static typing)
  • sphinx (for API documentation)
  • sphinxcontrib-napoleon (for API documentation)
  • sphinx-rtd-theme (for API documentation)

Installation

# install from pip
pip install gym-csle-cyborg==<version>
# local install from source
$ pip install -e gym-csle-cyborg
# or (equivalently):
make install
# force upgrade deps
$ pip install -e gym-csle-cyborg --upgrade
# git clone and install from source
git clone https://github.com/Limmen/csle
cd csle/simulation-system/libs/gym-csle-cyborg
pip3 install -e .
# Install development dependencies
$ pip install -r requirements_dev.txt

Development tools

Install all development tools at once:

make install_dev

or

pip install -r requirements_dev.txt

API documentation

This section contains instructions for generating API documentation using sphinx.

Latest Documentation

The latest documentation is available at https://limmen.dev/csle/docs/gym-csle-cyborg

Generate API Documentation

First make sure that the CSLE_HOME environment variable is set:

echo $CSLE_HOME

Then generate the documentation with the commands:

cd docs
sphinx-apidoc -f -o source/ ../src/gym_csle_cyborg/
make html

To update the official documentation at https://limmen.dev/csle, copy the generated HTML files to the documentation folder:

cp -r build/html ../../../../docs/_docs/gym-csle-cyborg

To run all documentation commands at once, use the command:

make docs

Static code analysis

To run the Python linter, execute the following command:

flake8 .
# or (equivalently):
make lint

To run the mypy type checker, execute the following command:

mypy .
# or (equivalently):
make types

Unit tests

To run the unit tests, execute the following command:

pytest
# or (equivalently):
make unit_tests

To run tests of a specific test suite, execute the following command:

pytest -k "ClassName"

To generate a coverage report, execute the following command:

pytest --cov=gym_csle_cyborg

Run tests and code analysis in different python environments

To run tests and code analysis in different python environemnts, execute the following command:

tox
# or (equivalently):
make tests

Create a new release and publish to PyPi

First build the package by executing:

python3 -m build
# or (equivalently)
make build

After running the command above, the built package is available at ./dist.

Push the built package to PyPi by running:

python3 -m twine upload dist/*
# or (equivalently)
make push

To run all commands for the release at once, execute:

make release

Author & Maintainer

Kim Hammar kimham@kth.se

Copyright and license

LICENSE

Creative Commons

(C) 2020-2025, Kim Hammar

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.10.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for Limmen from gravatar.com Limmen

Credits

Author: Kim Hammar

Maintainer: Kim Hammar

License

## creative commons # Attribution-ShareAlike 4.0 International Creative Commons Corporation (“Crea...

Requires

Python >=3.8

Tags

Reinforcement-Learning Cyber-Security Markov-Games Markov-Decision-Processes

Classifiers

Report project as malware

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