🦥 Random isn’t “Random”

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Why Random isn’t “Random”

A few years ago, I was in a final-round technical interview.

Fun little zoom call. Multiple interviewers. My hands were sweating like crazy.

After finishing all the normal interview problems we had some extra time.

So they asked me a fun bonus question:

Easy enough, right? I asked if I can use the random package and they said sure.

Now in my head I thought “Wow this is way easier than the other questions.”

The solution basically looks like this with the random package.

#Simplified version - shuffling numbers in an array
import random
deck = [1,2,3,4]
#Yep the random package has a shuffle method.
random.shuffle(deck)

Boom. Done.

At this point I felt pretty confident, but then one interviewer hit me with this question:

And that’s where I froze. Because I had no idea.

Is random actually random?

Well… Computers Can’t Do “True” Random

Here’s the thing: computers are deterministic machines.

If you give them the same input, you’ll always get the same output.

There’s no “surprise” in them.

So by default, they can’t create real randomness on their own.

(There are ways to get closer to “true” randomness though… we’ll get to that later)

What is the computer doing then?

When you ask your computer for randomness, it doesn’t pull chaos out of thin air. Instead, it uses a pseudorandom number generator (PRNG).

These are algorithms that produces numbers that look random but are actually predictable if you know the starting point which is called the seed.

PRNGs in simple terms

PRNGs usually consist of two parts:

1. The seed

2. A math algorithm that spits out numbers.

The seed is the starting point and the math algorithm uses that seed to generate a sequence of numbers.

If you’re curious here’s a list of PRNGs

Why do we need a seed?

To reproduce the “random” result. Weird, I know.

• Same seed → you always get the exact same sequence of numbers.

• Different seed → you get a different sequence.

Example you can try

import random

random.seed(42)  
print([random.randint(1, 10) for _ in range(5)])

The output you should get is [2, 1, 5, 4, 4].

No matter how many times you run it, you’ll always get those numbers.

Why is this useful?

Because reproducibility matters:

• In ML experiments, you want the same “random split” of data.

• In debugging, you want to replay the same test run.

• In games, you want to recreate the same world from a seed (Minecraft)

So “random” in this case isn’t true randomness. It’s just math following rules.

Where Do Seeds Come From?

Okay, so if PRNGs need seeds, where do those come from?

Most languages/libraries default to seeding from something unpredictable like:

• The current system time in nanoseconds

• CPU state

• Operating system entropy pools (hardware events like mouse movement, disk noise, or network jitter)

This makes it much harder to predict the seed, but still not truly random since it only generates it once.

♠️ Back to the Deck Shuffle

Now we only covered how the “random” part works, but how does the shuffle work?

Most programming language’s random package under the hood uses an algorithm called the Fisher-Yates shuffle.

Here’s the implementation in Python (thanks wikipedia):

def shuffle(numbers: list[int]) -> list[int]:
    for i in range(len(numbers) - 1, 0, -1):
        #IMPORTANT PART!
        j = random.randint(0, i)
        numbers[i], numbers[j] = numbers[j], numbers[i]
    return numbers

You see that random.randomint(0,i) 

That is what’s making this implementation possible.

The randomness of that shuffle is only as good as the random numbers it generates.

If the PRNG is weak, patterns can emerge.

And that means it’s not that “random.”

🔐 Crypto-Grade Randomness

WAIT A MINUTE… If patterns can exist, doesn’t that mean encryptions and random password generators are not that secure?

Couldn’t attackers could guess the seed and reproduce the sequence.

Well… yes (it would still take some work though)

But don’t worry, modern systems provide cryptographically secure PRNGs (CSPRNGs).

These pull from operating system entropy pools and use algorithms that are designed to be unpredictable.

Example

# Python's secure randomness
import secrets
print(secrets.token_hex(16))

These are what you’d use for things like passwords, API keys, or cryptography.

Even someone with full knowledge of the algorithm still can’t predict the outputs.

Fun fact: Cloudflare use lava lamps on a wall to help generate encryptions

They literally point cameras at the bubbling patterns and feed that noise into their systems to help with their “random” encryptions.

Takeaway

That interviewer asked a really good question. I don’t know if this was the answer they were looking for, but still a good question.

If I could go back to that interview, I’d probably say something like this:

If I said that, I probably would’ve gotten the job…

But hey, maybe it’ll help you with one.

Thanks to everyone who submitted!

grcc492, Melvis-07, Yeshua235 , AspenTheRoyal, gcavelier (used a crate/package to handle it. Practical. I respect it), jsjasee, NeoScripter, and Suji-droid!

A lot of you solved it with dfs and bfs great job!

Keyword Cipher

A Keyword Cipher replaces each letter of a message with a letter from a shifted alphabet built using a keyword.

1. Start with the keyword.

2. Add the remaining letters of the alphabet (A–Z) in order, skipping any that already appeared in the keyword.

   • Example keyword: "KEYWORD"

   • Cipher alphabet: KEYWORDABCFGHIJLMNPQSTUVXZ

3. Encrypt by replacing each letter in the message with the letter at the same position in the cipher alphabet.

   • Plain alphabet: ABCDEFGHIJKLMNOPQRSTUVWXYZ

   • Cipher alphabet: KEYWORDABCFGHIJLMNPQSTUVXZ

Write a function that takes a key and a message, and returns the encrypted message.

Examples

keyword_cipher("keyword", "abchij")
Output = "keyabc"

keyword_cipher("purplepineapple", "abc")
output = "pur"

keyword_cipher("mubashir", "edabit")
output = "samucq"

keyword_cipher("etaoinshrdlucmfwypvbgkjqxz", "abc")
Output = "eta"

keyword_cipher("etaoinshrdlucmfwypvbgkjqxz", "xyz")
Output = "qxz"

keyword_cipher("etaoinshrdlucmfwypvbgkjqxz", "aeiou")
Output = "eirfg"

How To Submit Answers

Reply with

• A link to your solution (github, twitter, personal blog, portfolio, replit, etc)

• or if you’re on the web version leave a comment!

• If you want to be mentioned here, I’d prefer if you sent a GitHub link or Replit!

That’s all from me!

Have a great week, be safe, make good choices, and have fun coding.

If I made a mistake or you have any questions, feel free to comment below or reply to the email!

See you all next week.

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