Published 2020-02-23T21:00:00.002Z by Physics Derivation Graph
So far I've been hesitant on collaborations involving software in the Physics Derivation Graph. I didn't have a good path for integration of contributions, especially of complex features. I think I can provide both more details explanation of what would be helpful, as well as a clear integration path.
For example, in this post I provided a set of valid and invalid and ambiguous Latex examples. I did not provide details on how I would integrate a suggested solution written by a contributor.
Here are three specific aspects I would need for integration of contributed code:
I will write doctests in Python. That way I can express the function as it would be integrated in the PDG project code
The contributed Python script should run inside a Docker image. That way the dependencies are made explicit
The "docker build" can assume to have Internet access, but the "docker run" process should assume no Internet connection
As an example from the above blog post, I can express the interface as a Python3 function def is_expression_valid_latex(expr_latex: str) -> bool: """ >>> is_expression_valid_latex("a = b") True >>> is_expression_valid_latex("a = b +") True >>> is_expression_valid_latex("\si a") False """
By using sys.stdin, we could expose that function to the container such that the following would be an acceptance test: docker run -it --rm demo:latest python3 /opt/my_script.py "a = b" True