This project aims to bring a reinforcement learning environment to the trading community. There are always competing priorities among the community, and we want to make sure that we are able to achieve together a project that is reliable, sustainable, and maintainable.

• We should have reliable codes in this project
  • reliable code with tests
  • reliable code that works
  • reliable code runs without consuming excessive resources
• We should help each other to achieve SOTA results together
• We should write clear codes
  • Code should not be redundant
  • Code should have documentation inline (standard pep format)
  • Code should be organized into classes and functions
• We should leverage outside tools as it makes sense
• We work together, and are kind, patient, and clear in our communication. Jerks are not welcome.

• Filing an issue is a great way to help improve the project

• You found a bug and a way to fix it
• You have contributed to an issue that was prioritized by the coordinators of this project
• You have new functionality that you're adding that you've written issues for and has documentation + Tests

• Please tag @bruceyang, @spencerromo, or @xiaoyang in every PR. (P.S. we're looking for more collaborators with software experience!)
• Please reference or write and reference an issue
• Please have clear commit messages
• Please write detailed documentation and tests for every added piece of functionality
• Please try to not break existing functionality, or if you need to, please plan to justify this necessity and coordinate with the collaborators
• Please be patient and respectful with feedback
• Please use pre-commit hooks

pip install pre-commit
pre-commit install

# Locally
python3 -m unittest discover

# Docker
./docker/bin/build_container.sh
./docker/bin/test.sh