expressive

A library for quickly applying symbolic expressions to NumPy arrays

By enabling callers to front-load sample data, developers can move the runtime cost of Numba's JIT to the application's initial loading (or an earlier build) and also avoid exec during runtime, which is otherwise needed when lambdifying symbolic expressions

Inspired in part by this Stack Overflow Question Using numba.autojit on a lambdify'd sympy expression

installation

via pip https://pypi.org/project/expressive/

pip install expressive

usage

refer to tests for examples for now

generally follow a workflow like

create instance expr = Expressive("a + log(b)")
build instance expr.build(sample_data)
instance is now callable expr(full_data)

The data should be provided as dict of NumPy arrays

sample_data = {  # types are used to compile a fast version for full data
    "a": numpy.array([1,2,3,4], dtype="int64"),
    "b": numpy.array([4,3,2,1], dtype="int64"),
}
full_data = {
    "a": numpy.array(range(1_000_000), dtype="int64"),
    "b": numpy.array(range(1_000_000), dtype="int64"),
}

testing

Only docker and docker compose (v2) are require, which are used to host/generate the test environment

Then just directly run the test script from the root of the repository, it will build the docker test environment and run itself inside it automatically

sudo apt install docker.io docker-compose-v2
./test/runtests.sh

contributing

The development process is currently private (though most fruits are available here!), largely due to this being my first public project with the potential for other users than myself, and so the potential for more public gaffes is far greater

Please refer to CONTRIBUTING.md and LICENSE.txt and feel free to provide feedback, bug reports, etc. via Issues, subject to the former

additional future intentions for contributing

improve internal development history as time, popularity, and practicality allows
move to parallel/multi-version/grid CI over all-in-1, single-version dev+test container
greatly relax dependency version requirements to improve compatibility