v0.1.0

First public release of genetic-algorithm — a dependency-free Python genetic-algorithm engine whose fitness criterion is a swappable plugin.

Highlights:

• Stdlib-only evolutionary engine: population, roulette/elitist selection, 1/k-point crossover, multiple mutation operators, elitism, optional threading.
• Pluggable fitness: a small FitnessFunction protocol plus a registry (register_fitness/get_fitness), with ready-made plugins (max_value, negative_sphere, target_vector, weighted_sum).
• Separating the search engine from the judgment of "better" makes the same loop the reusable search core of an autoresearcher (generate -> evaluate -> select -> repeat), including LLM-as-a-judge criteria.
• Examples (optimize_sphere, autoresearcher), Sphinx docs, full CI (lint/format/type-check, tests with 99%+ coverage gate, CodeQL, dependency & license scans), and Apache-2.0.

Open source by Santander AI Lab.