Random Integer Generator
Generate random whole numbers (integers) with customizable ranges - perfect for games, simulations, and random selection
Our random integer generator creates cryptographically secure whole numbers within your specified range. Generate unique integers, sorted sequences, or bulk random numbers for games, statistical simulations, lottery draws, and test data. Perfect for developers, mathematicians, and anyone needing truly random whole number selection with uniform distribution and no bias.
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What is a Random Integer?
An integer is a whole number without fractional or decimal components. Integers include positive numbers (1, 2, 3...), negative numbers (-1, -2, -3...), and zero (0). Our random integer generator uses cryptographically secure algorithms to ensure truly unpredictable values with uniform distribution across your specified range.
Integers are fundamental in mathematics and computer science, used for counting, indexing, identification, and discrete calculations where fractional values don't make sense (you can't have 2.5 people or roll 3.7 on a die). This generator ensures every integer in your range has exactly equal probability of selection.
Integer Generator Configuration Options
Range Configuration (Min/Max Values)
Quantity (1-1000 integers)
Unique Numbers Option
Sorting Options
How to Generate Random Integers
[STEP 1] Set Range
Configure minimum and maximum values to define your integer range (e.g., 1-100 for percentages, 1-6 for dice rolls).
[STEP 2] Set Quantity
Choose how many integers to generate (1-1000). Each number is independently generated with cryptographic randomness.
[STEP 3] Configure Options
Enable unique mode to prevent duplicates for lottery draws, or enable sorted mode to arrange results in ascending order.
[STEP 4] Generate & Export
Click EXECUTE GENERATION to create your random integers. View statistics (sum, average), copy individual numbers or all at once, and export results as TXT, CSV, or JSON for integration into your projects.
Integer Generator Best Practices
- _ Range Validation - Always ensure minimum value is less than maximum for valid generation.
- _ Unique Mode Limits - When using unique mode, quantity cannot exceed range size (e.g., can't generate 10 unique integers from range 1-5).
- _ Zero Handling - Decide if zero should be included in your range based on your use case (percentages often exclude zero).
- _ Negative Numbers - Use negative ranges for temperature simulations, coordinate systems, or financial calculations involving debt.
- _ Large Ranges - For ranges exceeding 1 million, consider performance implications and whether you truly need that scope.
- _ Cryptographic Quality - Suitable for non-security applications like games and simulations; use dedicated cryptographic tools for security keys.
Technical Implementation
Our integer generator employs cryptographically secure random number generation (CSPRNG) with uniform distribution across specified ranges. The system uses rejection sampling when necessary to ensure unbiased selection:
// Random integer generation with uniform distribution Algorithm: Uniform Integer Generation N = min + ⌊R × (max - min + 1)⌋ where R ∈ [0,1) is uniformly distributed CSPRNG value // Example: Generate integer between 1 and 100 N = 1 + ⌊R × 100⌋ → produces integers {1, 2, 3, ..., 100} // Probability for each integer: P(n) = 1/(max-min+1)