{"id":9597,"date":"2025-07-30T13:33:57","date_gmt":"2025-07-30T13:33:57","guid":{"rendered":"https:\/\/www.kaashivinfotech.com\/blog\/?p=9597"},"modified":"2025-07-30T13:33:57","modified_gmt":"2025-07-30T13:33:57","slug":"random-number-generator-in-2025","status":"publish","type":"post","link":"https:\/\/www.kaashivinfotech.com\/blog\/random-number-generator-in-2025\/","title":{"rendered":"Random Number Generator Explained: How Computers Pick Numbers (With Python, Java & Excel Examples)"},"content":{"rendered":"
Random Number Generator: Why It Matters<\/h2>\n
A random number generator (RNG) is\u00a0a device or algorithm that produces a sequence of numbers or symbols that appear random, meaning they are unpredictable and lack any discernible pattern.<\/p>\n
People earn daily from creating random number in cryptography, simulations, games, and scientific models. Behind most online transactions sits an RNG\u2014or a secure rng<\/strong>. CIA-grade RNG? Real. Critical.<\/p>\n
Even developers use pseudo\u2011random generation in day-to-day code. So in this article you\u2019ll see how programmers generate numbers (like a 6 digit random number generator), using Python or Java, or even Excel for quick business tasks.<\/p>\n
<\/p>\n
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\ud83c\udfaf Key Highlights<\/h2>\n
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\u2705 What a random number generator<\/strong> really is (beyond dice & lottery)<\/p>\n<\/li>\n
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\ud83d\udd0d Difference between true randomness<\/strong> and algorithmicaly generated random number<\/strong><\/p>\n<\/li>\n
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\ud83d\udcbb How to build a 6 digit random number generator<\/strong><\/p>\n<\/li>\n
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\ud83d\udc0d Example code for random number generator Python<\/strong>, Java, and Excel<\/p>\n<\/li>\n
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\ud83d\udcca Real data, stats, and career insights for aspiring developers<\/p>\n<\/li>\n<\/ul>\n
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\ud83c\udfae RNG in Real Life: Why It Matters to You<\/h2>\n
You\u2019ve probably used a random number generator<\/strong> today without even realizing it.<\/p>\n
Here\u2019s how they sneaks into daily life:<\/p>\n
\ud83d\udcb3 Banking & Security<\/strong>: OTPs, CAPTCHA challenges, and secure tokens rely on 6-digit random number generators<\/strong>.<\/p>\n<\/li>\n
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\ud83e\uddea Science & Simulations<\/strong>: From weather forecasts to physics experiments, RNG is behind the scenes in simulations like Monte Carlo methods.<\/p>\n<\/li>\n
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\ud83d\udcc8 Marketing & A\/B Testing<\/strong>: Marketers randomly split users into test groups to improve conversions\u2014thanks to PRNGs.<\/p>\n<\/li>\n<\/ul>\n
TL;DR: RNGs aren\u2019t just theory\u2014they shape how the modern world works.<\/p>\n
Applications<\/figcaption><\/figure>\n\n
\ud83c\udfb2 True vs Pseudorandom (RNG Uncovered)<\/h2>\n
Let\u2019s break this down:<\/p>\n
\ud83c\udf2a\ufe0f What is a True Random Number?<\/strong><\/h3>\n
A true random number<\/strong> is… well, truly random! It\u2019s generated from a physical, unpredictable source<\/strong> \u2014 like atmospheric noise, radioactive decay, or even lava lamps (no joke, Cloudflare actually does that!).<\/p>\n
Unlike algorithms, there’s no pattern or repeatability<\/strong>. That’s why true randomness is often used in encryption<\/strong>, lottery systems<\/strong>, and high-stakes security scenarios where predictability could be dangerous.<\/p>\n
In your everyday coding life, you won\u2019t often need true randomness \u2014 but understanding it helps when dealing with security<\/strong> or cryptographic keys<\/strong>.<\/p>\n
True Random Number Generator (TRNG)<\/strong><\/h4>\n
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Captures real randomness\u2014from atmospheric noise, hardware quirks, or even radioactive decay.<\/p>\n<\/li>\n
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Non-deterministic, no pattern.<\/p>\n<\/li>\n
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Used in cryptography and security-critical systems.<\/p>\n<\/li>\n<\/ul>\n
\ud83e\udd16 What is a Pseudorandom Number?<\/strong><\/h3>\n
Most of the \u201crandom\u201d numbers you see in programming (like in Python or Java) aren\u2019t truly random. They\u2019re pseudorandom<\/strong> \u2014 meaning they\u2019re generated by an algorithm<\/strong>, and based on an initial value called a seed<\/strong>.<\/p>\n
They \u201clook random,\u201d but are completely predictable<\/strong> if you know the seed.<\/p>\n
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So if you\u2019ve ever run random.seed(42)<\/code> in Python, you\u2019re actually controlling your randomness \u2014 which is super useful in testing or simulations.<\/p>\n<\/blockquote>\n
For 99% of coding work \u2014 from web development to data science \u2014 pseudorandom numbers are more than good enough<\/strong>. They\u2019re fast, efficient, and easy to reproduce.<\/p>\n
Pseudorandom Number Generator (PRNG or rng)<\/strong><\/h4>\n
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Based on algorithm + seed.<\/p>\n<\/li>\n
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Deterministic\u2014you get the same sequence if seed repeats.<\/p>\n<\/li>\n
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Fast, reproducible, ideal for testing and simulations.<\/p>\n<\/li>\n<\/ul>\n
According to research by NIST, PRNG performance varies. But strong PRNGs (like Xoroshiro256+ or PCG) can handle billions of draws per second\u2014with enough unpredictability for many real-world uses.<\/p>\n
\ud83d\udcca TRNG vs PRNG: What\u2019s the Real Difference?<\/h2>\n
\ud83d\udccdPlace it right after your TRNG and PRNG definitions.<\/strong><\/p>\n
Purpose:<\/strong> Clear visual comparison for readers; improves skimmability and SEO.<\/p>\n
\u270d\ufe0f Content:<\/h3>\n
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Feature<\/th>\n
TRNG (True Random Number Generator)<\/strong><\/th>\n
PRNG (Pseudo-Random Number Generator)<\/strong><\/th>\n<\/tr>\n<\/thead>\n\n
\u26a0\ufe0f Most apps use PRNGs because they\u2019re fast and good enough for non-security tasks.<\/em><\/p>\n<\/blockquote>\n
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\ud83e\uddee How the Linear Congruential Generator Works (Algorithm Deep Dive)<\/h2>\n
\ud83d\udd01 What is a Linear Congruential Generator (LCG)?<\/strong><\/h3>\n
The Linear Congruential Generator<\/strong> is like the grandparent of pseudorandom generators \u2014 a mathematical method used to churn out a sequence of numbers that feel<\/strong> random.<\/p>\n
Here\u2019s the core formula:<\/p>\n
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X\u2099 = (a * X\u2099\u208b\u2081 + b) <span class="hljs-built_in">mod<\/span> m \n<\/code><\/div>\n<\/div>\n
It’s simple, fast, and still used under the hood in some libraries \u2014 but not secure enough for cryptography or serious randomness. If you’re into algorithms<\/strong> or prepping for coding interviews, LCGs often pop up in questions about building RNGs from scratch.<\/p>\n
\nIt\u2019s old-school\u2014but a great starting point. The Linear Congruential Generator<\/strong> follows:<\/p>\n
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X\u2099 = (a * X\u2099\u208b\u2081 + b) <span class="hljs-comment">% m<\/span> \n<\/code><\/div>\n<\/div>\n
\ud83d\udd10 Use SecureRandom<\/code> when you need unpredictability (e.g., tokens, passwords).<\/em><\/p>\n
\ud83d\udca1 Tip: You can also create 6-digit random numbers in Java like this: int num = 100000 + rand.nextInt(900000);<\/code><\/p>\n
Random Number Generator in Excel<\/h2>\n
Excel: No Code Needed<\/h3>\n
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Use =RANDBETWEEN(100000, 999999)<\/code><\/p>\n<\/li>\n
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Or =RAND()<\/code> gives 0 \u2264 x < 1, multiply by a range, floor it, add offset\u2026<\/p>\n<\/li>\n<\/ul>\n
That\u2019s your random number generator in Excel<\/strong>\u2014quick and dirty tool for paperwork or prototypes.<\/p>\nRandom Number Using Python Java and excel<\/figcaption><\/figure>\n\n
\ud83d\udcca Security & Career Angle: When RNG Matters in Real Jobs<\/h2>\n
Here\u2019s where it gets interesting: If you\u2019re building anything that demands unpredictability\u2014e.g., password generation, token creation, lottery systems\u2014using a simple PRNG just won\u2019t cut it.<\/p>\n
Large tech firms like Apple, Google, and AWS rely on cryptographically secure RNGs<\/strong> (CSPRNGs) that feed directly from hardware sources.<\/p>\n
Career tip:<\/strong> Knowing the difference between basic RNG and cryptographically secure RNG is a skill that can set your resume apart when applying to backend engineering or security roles.<\/p>\n\n
\ud83d\udd04 What Happens When the Seed Repeats?<\/h2>\n
If you reuse the same seed:<\/p>\n
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PRNG will generate the same sequence.<\/p>\n<\/li>\n
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That\u2019s great for debugging, but not for security.<\/p>\n<\/li>\n<\/ul>\n
Example:<\/p>\n
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<span class="hljs-keyword">function<\/span> <span class="hljs-title function_">simpleLCG<\/span>(<span class="hljs-params">seed<\/span>) { \n <span class="hljs-keyword">let<\/span> m = <span class="hljs-number">1e9<\/span>+<span class="hljs-number">7<\/span>, a = <span class="hljs-number">1664525<\/span>, b = <span class="hljs-number">1013904223<\/span>; \n <span class="hljs-keyword">return<\/span> (a * seed + b) % m; \n} \n<span class="hljs-variable language_">console<\/span>.<span class="hljs-title function_">log<\/span>(<span class="hljs-title function_">simpleLCG<\/span>(<span class="hljs-number">123<\/span>)); <span class="hljs-comment">\/\/ always same<\/span> \n<\/code><\/div>\n<\/div>\n
A reused seed = predictable output. Not good for encryption.<\/p>\n
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\ud83c\udf31 Real-World Use Cases of RNG in 2025<\/h2>\n
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Games & simulations<\/strong>: RNGs defines loot, simulation randomness.<\/p>\n<\/li>\n
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Cryptocurrency wallets<\/strong>: Rely on secure RNGs for private key generation.<\/p>\n<\/li>\n
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Data science & Monte Carlo methods<\/strong>: Simulate uncertainty in finance or physics.<\/p>\n<\/li>\n
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Automated tests<\/strong>: Use deterministic rng for reproducible unit testing.<\/p>\n<\/li>\n<\/ul>\n
According to Kaggle data, Monte Carlo methods power 40% of risk modeling in finance. Randomness = insight.<\/p>\n
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\ud83c\udfb2 Monte Carlo Methods \u2014 Explained Like You\u2019re 10<\/h3>\n
Imagine you have a big jar filled with red and blue marbles<\/strong>, but you don\u2019t know how many of each.<\/p>\n
Now you close your eyes and randomly pick out<\/strong> one marble at a time, write down its color, and then put it back in the jar.<\/p>\n
You do this 100 times<\/strong>.<\/p>\n
Let\u2019s say:<\/p>\n
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70 times you pulled out a blue<\/strong> marble<\/p>\n<\/li>\n
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30 times you got a red<\/strong> one<\/p>\n<\/li>\n<\/ul>\n
Now, you can guess: \u201cHmm\u2026 maybe 70% of the marbles are blue and 30% are red.\u201d<\/p>\n
That\u2019s Monte Carlo! \u2705<\/p>\n
You didn\u2019t count all the marbles \u2014 you just used random sampling<\/strong> to estimate what’s inside. And the more times you do it, the better your estimate becomes.<\/p>\nMonte Carlo Simulation<\/figcaption><\/figure>\n\n
\ud83e\udde0 Real-life uses<\/strong> of Monte Carlo methods include:<\/p>\n
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Weather predictions<\/p>\n<\/li>\n
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Risk analysis in finance<\/p>\n<\/li>\n
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Simulating traffic flow<\/p>\n<\/li>\n
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Even helping doctors estimate success of treatments!<\/p>\n<\/li>\n<\/ul>\n
And yes \u2014 you can build these simulations with tools like Python<\/strong>, Excel<\/strong>, or Java<\/strong> using a generator<\/strong>.<\/p>\n
\ud83d\udd22 6-Digit Random Number Generator: The Most Used Format<\/h2>\n
Need a 6-digit number for OTPs, user IDs, or mock data? This is one of the most common format of RNGs.<\/p>\n
\ud83e\uddee How to generate a 6-digit random number:<\/h3>\n
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In Excel<\/strong>: Use this formula: =RANDBETWEEN(100000, 999999)<\/code> It gives a new random 6-digit number every time the sheet updates.<\/p>\n<\/li>\n
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In Python<\/strong>:<\/p>\n
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<span class="hljs-keyword">import<\/span> random \n<span class="hljs-built_in">print<\/span>(random.randint(<span class="hljs-number">100000<\/span>, <span class="hljs-number">999999<\/span>)) \n<\/code><\/div>\n<\/div>\n
If you need something more secure<\/strong>, like for login codes:<\/p>\n
![\"random](\"https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/07\/What-is-a-Random-Number-Generator.png\")
<\/p>\n![\"random](\"https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/07\/Random-Number-Generator-Applications.png\")
![\"random](\"https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/07\/Random-Number-Using-Python-Java-and-excel.png\")
![\"random](\"https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/07\/Monte-Carlo-Simulation-683x1024.png\")