KISS random number generation#
scikitplot.random provides a NumPy-like KISS random-number-generation surface with seed sequences, bit generators, stateful generators, serialization, and convenience distribution functions.
Important
A deterministic pseudo-random stream is reproducible state, not cryptographic randomness. Do not use this module for passwords, tokens, keys, nonces, or any other security-sensitive entropy.
Create a KISS generator with default_rng or kiss_context.
Choose 32/64-bit generators, seed sequences, spawning, and deterministic streams.
Snapshot, pickle, JSON-style serialization, and restore state deliberately.
Understand NumPy-like semantics, distributions, and what reproducibility does and does not promise.
Generator, bit generator, seed sequence, RandomState compatibility, and convenience functions.
Compiled-extension requirements, thread/process use, and state-version compatibility.
Which page should I use?#
Start with Getting started. Then choose the page that owns the decision you are making: architecture and lifecycle, configuration, persistence, performance, public API, or limits. The guide intentionally separates those concerns so examples do not accidentally become policy.
Examples#
See Random for executable examples that accompany this guide.