piteren/pypaq
little Python tools, mainly useful for tasks related to machine learning, etc.
What's novel
little Python tools, mainly useful for tasks related to machine learning, etc.
Code Analysis
13 files read · 3 roundsA personal Python utility library providing a parameter space management system (PaSpa) with mixed-type axis sampling, genetic crossing, adaptive SVR-based space estimation, multiprocessing utilities, and file I/O helpers for ML experimentation workflows.
Strengths
The PaSpa parameter space engine is genuinely non-trivial, handling mixed-type axes (continuous, discrete, heterogeneous) with normalized distance, noise-based sampling, and genetic crossing algorithms. The RBFRegressor implements a real adaptive hyperparameter search strategy with cross-validation on each update.
Weaknesses
Tests are informal and exploratory (heavy use of print statements, some tests are more like scripts than assertions), and the ConfigManager has a performance issue reading/writing JSON on every attribute access. The README is minimal and doesn't describe the actual capabilities of the parameter space system.
Score Breakdown
Signal breakdown
Innovation
Craft
Traction
Scope
Evidence
Commits
67
Contributors
1
Files
61
Active weeks
23
Repository
Language
Python
Stars
1
Forks
0
License
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