I Removed Every Variable From My Python Code — Here’s What I Learned

What if I told you Python doesn’t need variables to work?

I Removed Every Variable From My Python Code — Here’s What I Learned

Can Python even function without variables? I put it to the test — and discovered something unexpected about functional programming, mindset shifts, and what clean code really means.

I Tried Writing Python Without Variables — And It Changed the Way I Code

When you first learn Python, one of the earliest lessons is how to assign values to variables. x = 5, name = "Alice", result = calculate_total(price, tax) — variables are everywhere. So much so that we take them for granted.

But what happens if you remove them?

No assignments. No state. No x = ..., y = ..., or temp = .... Just pure logic, data flow, and function calls.

Out of curiosity (and a healthy dose of masochism), I decided to write an entire program in Python — without a single variable. What started as a silly challenge quickly turned into a mind-bending exercise in how we think about programming itself.

Let me take you through what I learned, the unexpected power of statelessness, and how this experiment made me a better Python developer.

Why Would Anyone Do This?

Before you call it pointless, here’s what motivated the idea:

• To break my routine mental models. I rely heavily on variables, but are they necessary?
• To explore Python’s functional capabilities. Can I write real code using only function composition and recursion?
• To understand stateless logic more deeply. Especially with the rise of functional languages like Haskell or tools like React Hooks, this idea felt more relevant than ever.

This wasn’t just about minimalism or intellectual flexing. It was a hands-on way to examine what Python is really capable of — and what I was capable of as a developer.

The Challenge Setup: What “No Variables” Actually Means

For this experiment, I defined the rules as follows:

• No assignment statements. No =, no :=, no globals(), no locals().
• No mutable state or object attributes.
• Purely functional style. Everything must return values directly or via function composition.

What did I build? A simple but non-trivial recursive JSON parser that extracted specific data and transformed it — think of traversing nested dictionaries and lists to pull out all email addresses.

Round 1: The Horror of Losing Familiar Tools

Here’s what hit me immediately:

• You can’t store intermediate results.

# Not allowed 
emails = extract_emails(data) 
filtered = filter_valid(emails)

Instead, you must chain:

print( 
    filter_valid( 
        extract_emails(data) 
    ) 
)

And it gets worse when recursion kicks in:

def get_emails(data): 
    return ( 
        [data] if is_email(data) else [] 
        if isinstance(data, str) else 
        sum( 
            map(get_emails, data.values() if isinstance(data, dict) else data), 
            [] 
        ) 
    )

This was surprisingly hard to read — and even harder to debug.

Round 2: Embracing Function Composition and Recursion

Once I leaned into functional techniques, things began to shift.

Tricks That Helped:

• Recursive expressions instead of loops
• map() and filter() instead of list comprehensions
• Using functools.reduce() to collapse sequences
• lambda functions in creative (sometimes cursed) ways

Example: A recursive flatten function

from functools import reduce 
 
flatten = lambda lst: ( 
    reduce( 
        lambda acc, x: acc + flatten(x) if isinstance(x, list) else acc + [x], 
        lst, [] 
    ) 
)

Still readable? Barely. Still functional? 100%.

What I Learned (The Hard Way)

1. State is a crutch — but a helpful one

Variables are a form of mental scaffolding. They help structure ideas into bite-sized, nameable steps. Removing them forced me to hold the entire transformation in my head, which is cognitively expensive.

2. Readability goes down fast

Functional purity often comes at the cost of clarity. Without descriptive names, you rely heavily on understanding nested expressions — which isn’t friendly to collaborators or your future self.

3. Python isn’t designed to be purely functional — and that’s okay

While you can use Python in a purely functional, stateless way, it’s not idiomatic. The syntax starts to feel like a hack, and you’ll miss things like pattern matching, immutability by default, and tail call optimization.

But you do learn how to think more declaratively.

When Writing Stateless Code Makes Sense

Despite the pain, this experiment showed me where removing variables can be valuable — even in real-world code:

Writing small, reusable functions

Functions with no side effects are easier to test, debug, and reuse.

Working in functional pipelines (e.g., map → filter → reduce)

Great for data processing tasks, especially with Pandas, PySpark, or functional APIs.

Designing APIs and microservices

Statelessness is a feature in distributed systems.

Code golfing or constraint-based coding

Want to improve your skills? Try removing one language feature at a time and see what you learn.

A Balanced Approach: The Hybrid Style

After this exercise, I didn’t ditch variables forever — far from it. But I became much more conscious of how and when I use them.

Here’s how I code now:

• Keep pure logic pure — no sneaky state changes.
• Use variables sparingly and descriptively.
• Avoid reassigning the same variable multiple times.
• Refactor complex expressions into named helper functions instead of nesting deeply.

It’s not about being dogmatic. It’s about being deliberate.

Final Thoughts: The Real Point Isn’t About Variables

This wasn’t about proving that variables are “bad” or functional programming is “better.” It was about stepping outside the comfort zone and forcing myself to see code differently.

By stripping away variables — something so fundamental — I had to confront the essence of logic, flow, and transformation.

If you’re feeling stuck, burned out, or just curious, I recommend trying this challenge yourself.

It might break your brain — and that’s a good thing.

Sometimes, the best way to grow as a developer is to take away what feels essential — and see what remains.