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Object Schema Definition
Input UUIDs (One per line)
Result Objects (JSON)
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About

This tool transforms universally unique identifiers (UUIDs) into rich, structured objects using deterministic algorithms. Unlike standard random generators which produce different results every time, this system uses the entropy already contained within the UUID string to drive the generation. If the input UUID is the same, the output object is mathematically guaranteed to be identical.

The core mechanism operates by slicing specific segments of the hexadecimal UUID and normalizing them into a scalar value S. This scalar is derived by dividing the integer value of the hex segment h by the maximum possible value for that segment length hmax. This creates a consistent seed ($0.0 \le S \le 1.0$) used to map values to integers, floats, arrays, or booleans.

uuid mock-data deterministic-generation json-schema procedural-generation

Formulas

The normalization of a hexadecimal segment into a usable probability seed follows this high-precision ratio:

S = int(segment)16L 1

Where segment is the hexadecimal substring extracted from the UUID, and L is the length of that substring (number of characters). The denominator represents the maximum possible value for a hex string of length L (e.g., if L=2, max is 255 or FF).

Reference Data

TransformationInput TypeAlgorithm LogicUse Case
Integer RangeHex Slicefloor( S × ( maxmin + 1 ) + min )Age, ID, Quantity, Score
Float RangeHex SliceS × ( maxmin ) + minCoordinates, Prices, Weights
Array PickHex SliceArr[ floor( S × length ) ]Names, Categories, Enums
BooleanHex SliceS0.5Active Status, Flags
Hex ColorHex Slice# hex( floor( S × 16777215 ) )Profile Themes, UI Elements

Frequently Asked Questions

UUID-based generation is deterministic. The same UUID will always produce the exact same "Random" Object. This is critical for procedural generation in games (where a seed must recreate a world) or testing (where you need consistent user profiles across environments).
The tool uses BigInt arithmetic to handle hex segments of any length up to 32 characters. However, standard floating-point precision (IEEE 754) is applied after the division, providing approximately 15-17 decimal digits of precision for the scalar seed.
Collisions depend on the source UUIDs and the schema definitions. If you map a short hex segment (e.g., 1 char, 16 possibilities) to a large array (e.g., 100 names), collisions are guaranteed. Increase the slice length to reduce collision probability.
Currently, this tool supports uniform distribution for array selection. To simulate weights, populate the input array with duplicate values (e.g., ['Common', "Common", "Common", 'Rare'] gives 75% chance for Common).