Simple Random Number Generator
Professional random number generator supporting integer and float generation with uniqueness, sorting, decimal places and other parameter settings
Parameter Settings
Allows generating duplicate random numbers
Included
Excluded
Documentation
What is Random Number Generator
A random number generator is a tool that can generate sequences of random numbers. This tool supports generating integers and floating-point numbers, with customizable value range, count, duplicate settings, and sorting options. Generated random numbers can be used for test data generation, lottery activities, math exercises, game development, and many other scenarios.
Parameter Description
Number Type
Choose to generate integers or floating-point numbers (decimals)
Allow Duplicate Values
Choose whether to allow generating duplicate random numbers
Decimal Places
Number of decimal places in float mode (1-10 places)
Sort Order
Result sorting: no sort, ascending, or descending
Result Separator
Custom separators support: tab(\t), newline(\n), semicolon(;), colon(:), slash(/), underscore(_), and any other characters
Use Cases
Test Data Generation
Generate random test data for software testing
Lottery Activities
Generate random numbers for lottery or selection
Math Exercises
Generate random numbers for math problems
Game Development
Generate random values for games
About Random Numbers
Random number generation has various implementation methods, each with specific application scenarios. Ideal random numbers should be unpredictable, meaning each number is completely independent of previous numbers.
True Random Numbers: Generated through physical processes such as hardware noise, radioactive decay, atmospheric noise, and other natural phenomena. These random numbers have true unpredictability but are costly to generate and technically complex to implement.
Pseudo-Random Numbers: Number sequences generated by mathematical algorithms that appear random but are actually deterministic. This tool uses pseudo-random algorithms with good statistical properties and sufficiently long periods to meet most application needs.
For everyday applications, testing, gaming, and similar scenarios, pseudo-random numbers are completely sufficient. They are fast to generate, reproducible (same seed produces same sequence), and well-suited for program development and data analysis.
Notes
- • In no-duplicate mode, integer count cannot exceed the value range size
- • Float mode supports 1-10 decimal places; integer mode only generates integers
- • Random number range is [min, max), including minimum but excluding maximum
- • Maximum must be greater than minimum, otherwise valid random numbers cannot be generated
- • Recommended count limit is 10000 for optimal performance
- • In no-duplicate mode, a small value range significantly affects generation efficiency
- • Custom separators support escape characters like \t (tab) and \n (newline)
FAQ
Why are the generated random numbers not random enough?
This tool uses a pseudo-random number algorithm (Math.random()), which is sufficiently random for most application scenarios. For higher security random numbers, consider using the Web Crypto API.
Why can't I generate more unique random numbers?
In no-duplicate mode, the number of unique integers is limited by the value range. For example, a range of 0-100 can only generate up to 100 non-repeating integers.
What is the precision in float mode?
Float mode supports 1-10 decimal places precision. Due to JavaScript floating-point characteristics, actual precision may have minor errors, but this is negligible for most application scenarios.
Can the generated random numbers be used for cryptography?
Not recommended. This tool generates pseudo-random numbers, which are not suitable for cryptographic applications such as key generation and encryption. For such needs, please use dedicated cryptographic random number generators.
Why is generation sometimes slow?
In no-duplicate mode, when the requested count approaches the value range size, generation slows down because multiple attempts are needed to find non-repeating numbers. Consider increasing the value range.