Number Generator

The Number Generator tool produces random values within a user-defined range. It supports reproducibility through an optional seed and offers multiple sampling strategies. It is designed for testers, developers, and data scientists who need deterministic data or quick value generation for simulations and QA datasets. It supports both integer and decimal outputs. It enables repeatable experiments and rapid data seeding for pipelines. Its compact logic makes it suitable for automation and integration into test frameworks. Example: min=0, max=100, count=5 with seed=42 yields the same five numbers on every run when the seed is applied.

Inputs include: min, max, count, decimals, distribution, and seed. Validation enforces min <= max, count >= 1, decimals in 0-6. If seed is provided, results are reproducible; otherwise outcomes vary. For uniform distribution, values are drawn from a standard RNG scaled to [min, max]. For normal distribution, values are drawn from a Gaussian and truncated to the defined range.

Outputs are a list of numbers formatted per the decimals setting. Each value is presented with fixed decimals when requested or as integers otherwise. The tool can return a single value when count=1 or an array for multiple samples, enabling downstream data shaping.

Unique value propositions include deterministic seeding, selectable distribution types, clear validation rules, and a compact implementation suitable for automation. Typical use cases: seed test databases, drive Monte Carlo experiments, generate input fuzz data, or create repeatable demo datasets.