Releases: ori88c/weighted-random-item-sampler
Releases · ori88c/weighted-random-item-sampler
README and Documentation improvements
Key Features
- Documentation improvements.
- README improvements. In particular, adding an Algorithm section.
README formatting improvements
Initial Release
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
tsconfigtarget is set to ES2020, ensuring compatibility with ES2020 environments. - TypeScript support.