HG Systematic

This is a library of utilities and examples to highlight how HGraph can be used to implement systematic trading strategies.

See this for more information.

Development

This project uses uv for environment and dependency management. See https://docs.astral.sh/uv/ for installation instructions.

Here are some useful commands:

Create a local virtual environment in the project directory (./.venv) with Python 3.12:

uv venv --python 3.12

Install the project and its dependencies:

# Base dependencies
uv sync

# Include documentation dependencies
uv sync --extra docs

# Install all optional extras (e.g. tests, adaptors)
uv sync --all-extras --all-groups

PyCharm can use the interpreter from ./.venv (created by uv) to set up the project. Recent versions of PyCharm support uv, use the "uv" interpreter type.

Run Tests

# No Coverage
uv run pytest

# Generate Coverage Report
uv run pytest --cov=hg_systematic --cov-report=xml

Project links

Data verified by PyPI on Jul 25, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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  • Released:
Newer release available (0.2.2)

1 maintainer

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

Credits

Author: Howard Henson

GitHub Statistics

Data verified by PyPI on Jul 25, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MIT

Requires

Python >=3.12

Provides Extra

docs test

Tags

forward propogating graph fpg frp functional functional reactive programming graph reactive strategy systematic time series time-series trading

Classifiers

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