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I recently published the redsho package for hyperparameter optimization. More than anything, I want it to be useful. I find it helpful to start with a working example. To this end I created a second repo called redsho-examples that walks through how to do it. codeberg.org/brohrer/reds...

Usage 1. Start with an evaluation function def evaluate(*, a, b, c): return a * b**3 % c (The leading * tells Python that everything that follows is a required keyword argument) 2. Build a collection of values to try for each parameter values = {"a": [4, 7, 9], "b": [2, 5, 6], "c": [5, 8, 11]}

3. Call the optimizer from redsho.optimizer import optimize error, params = optimize(evaluate, values) where error is the lowest error achieved, and params is the parameter values that achieved it.

As of right now, there are 4 examples, each in their own subdirectory: 1. sinc: optimizes a 2D variant of the sinc function, sin(x)/x codeberg.org/brohrer/reds... 2. perf: tests the execution time bottleneck in redsho and helps to streamline it codeberg.org/brohrer/reds...