Release Initial Release · ori88c/weighted-random-item-sampler

Key Features

Weighted Random Sampling: Sampling items with proportional probability to their weight.
Efficiency: O(log(n)) time and O(1) space per sample, making this class suitable for performance-demanding applications where the set of items is large and the sampling frequency is high.
Comprehensive documentation: The class is thoroughly documented, enabling IDEs to provide helpful tooltips that enhance the coding experience.
Tests: Fully covered by unit tests.
No external runtime dependencies: Only development dependencies are used.
ES2020 Compatibility: The tsconfig target is set to ES2020, ensuring compatibility with ES2020 environments.
TypeScript support.