A functional reactive programming engine with a Python front-end.
This provides a DSL and runtime to support the computation of results over time, featuring a graph based directed acyclic dependency graph and the concept of time-series properties. The language is function-based, and promotes composition to extend behaviour.
Here is a simple example:
from hgraph import graph, run_graph, const
from hgraph.nodes import debug_print
@graph
def main():
a = const(1)
c = a + 2
debug_print("a + 2", c)
run_graph(main)Results in:
[1970-01-01 00:00:00.000385][1970-01-01 00:00:00.000001] a + 2: 3
See this for more information.
The project is currently configured to make use of uv for dependency management. Take a look at the website to see how best to install the tool.
Here are some useful commands:
First, create a virtual environment in the project directory:
uv venvThen use the following command to install the project and its dependencies:
# Install the project with all dependencies
uv pip install -e .
# Install with optional dependencies
uv pip install -e ".[docs,web,notebook]"
# Install with all optional dependencies
uv pip install -e ".[docs,web,notebook,test]"PyCharm can make use of the virtual environment created by uv to setup the project.
# No Coverage
python -m pytest# Generate Coverage Report
python -m pytest --cov=hgraph --cov-report=xml