ToolzyLab
Generate fully custom random numbers for giveaways, games, simulations, classrooms, testing, lucky draws, and everyday quick picks. Create single or bulk results, use decimals, avoid duplicates, filter odd or even values, force multiples, exclude values, and export clean results instantly.
Switch between a single random result and bulk generation with statistics.
Define your minimum and maximum values, then control how many results should be generated.
Make results more specific with uniqueness, parity, multiples, and exclusion rules.
The first generated number is emphasized here; the complete list appears in the results section below.
Generate, regenerate, copy, download, or clear results from right under the preview.
Use this area to review all numbers clearly. In bulk mode, quick stats and distribution are shown below.
No numbers generated yet.
Use unique mode for lucky draws, raffles, and classroom picks. Use decimal mode for simulations, calculations, and testing. If you combine too many filters with a very small range, valid results may run out — so the tool checks that and warns cleanly instead of generating bad output.
Random results depend on the source of randomness and the size of the allowed set. Choose minimum, maximum, count, decimals, integer type, multiple constraint, exclusions, uniqueness, sorting, and output view, then confirm range inclusivity and whether the result is for games, sampling, testing, or a security-sensitive purpose.
An inclusive integer range from 1 to 10 has ten possible values before exclusions. Requiring multiples or unique results can shrink the set further. Validate that the requested count is feasible instead of looping indefinitely. Decimal values are drawn from a finite precision grid, not from every real number.
Animation is presentation, and sorting occurs after generation. For casual games, classroom picks, fixtures, and mock data, browser randomness may be sufficient. Security tokens, keys, regulated drawings, scientific sampling, and auditable lotteries need a documented cryptographically secure or independently verified process.
Randomness does not promise an even pattern in a small sample. Unique mode prevents repeats only within that draw. Lottery presets do not improve winning odds, and generated results should not be presented as predictions. Save the seed or use deterministic test fixtures when reproducibility matters.
Verify the allowed population and randomness requirement before using the result.
Technical references: MDN cryptographic random values
Check the page rule; this generator is designed around an allowed range including its stated bounds. Verify examples when a downstream workflow expects exclusive limits.
The requested count may exceed the values left after range, type, multiple, precision, and exclusion constraints.
No. The decimal-place setting creates a finite grid of representable outputs and normal floating-point limitations can apply.
It changes presentation order after selection, not which values were chosen. Preserve original order if sequence itself matters.
Use a purpose-built cryptographic generator with sufficient entropy and a suitable token format. A general numeric picker is not a security design.
No. They only generate a valid-looking random selection under the preset. They do not affect or predict an independent lottery draw.