Why You Need to Learn Functional Programming: And What It Is

Introduction: Setting the Scene

We were in the early planning stages of a high-stakes project—one of those “if this goes down, the company goes down” systems. Pressure was mounting, deadlines were closing in, and even before a single line of code was written, it already felt like the architecture was being held together with duct tape and desperate prayers.

Enter the new senior developer, Kazem Arjmand— who seemed unnervingly calm during our design meetings. While the rest of us were anticipating future bugs before we even started coding, he kept dropping cryptic hints about something called functional programming (FP).

At the time, all I knew was that it was some “academic” style of programming. What I didn’t realize was that it’s a paradigm—just like object-oriented programming (OOP)—but one built on a few core principles:

• Pure functions: Functions that always return the same result with the same input, with no hidden side effects.
• Immutability: Data doesn’t get changed in place; instead, new versions get created.
• First-class functions: Functions can be treated as values—passed around like variables.
• Currying: Transforming a function with multiple arguments into a chain of single-argument functions.

Note: This isn’t everything about FP—it’s just the most basic but crucial keys. The rest is up to you to explore.

I remember thinking: Really? Now’s not the time to reinvent the wheel. We don’t need new paradigms, we need fewer upcoming headaches.

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The Problem: What Wasn't Working

Our project’s plan wasn’t small—it was set to have thousands of lines of business logic, multiple services passing state around, and more side effects than a bad diet pill. Even in the design phase, we could already predict the state bugs that would haunt us: values changing unpredictably, functions mutating objects behind our backs, strange race conditions likely waiting in production.

I recall late nights sketching flow diagrams, muttering:

“But if this value is true here and false later… how do we guarantee consistency?”

One evening, I shared my dread with Kazem:

Me: “This whole thing is going to eat me alive. These bugs are going to feel like chasing ghosts.”

Kazem: “You should try using pure functions and immutability. It’ll give your code predictability.”

In OOP, we often keep changing object state as the program runs. In FP, you work differently—you write functions that transform data rather than mutate it. And sometimes, you even break down big functions into smaller chains using currying.

Predictability sounded like a dream. But honestly, I thought: Yeah, sure… and dragons are real too.

The Spark: Discovering Functional Programming

The turning point came when the senior dev sat down with me and sketched out a simple example of currying:

// Normal function
function add(a, b) {
  return a + b;
}

add(2, 3); // 5

// Curried version
function curriedAdd(a) {
  return function(b) {
    return a + b;
  };
}

curriedAdd(2)(3); // 5

// Real world Example 

const distances = [1,2,6,2]

const factor = getFactor();

const convertMeterToKiloMeter = curriedAdd(factor);

const newDistances = distances.map(convertMeterToKiloMeter);
// [100,200,600,200]

Suddenly, it clicked. This wasn’t abstract theory—it was a way to build reusable, composable tools. Functions could be “preloaded” with context and reused without rewriting logic.

Me (internally): Wait… is this what programming is supposed to feel like?

Kazem: “See? Small functions can be chained and reused everywhere. It’s like Lego for code.”

Me: Mind. Officially. Blown.

The Struggle: Learning Curve and Resistance

Of course, the theory was simple. The practice? Not so much.

Functional programming has its own toolkit—map, reduce, filter, higher-order functions, currying—and using functions as building blocks can feel alien at first.

Refactoring even planned code structures felt painful. I’d draft something elegant, then stare at a problem for half an hour because I forgot immutability forbade direct changes.

But small wins kept me going. Like the first pure utility function I tested—no mocking, no setup headaches. It just… worked.

My brain oscillated daily between “This is amazing” and “Why do I hate myself for doing this?”

The Victory: Real Benefits Observed

By the time we got deeper into implementation, the benefits were undeniable:

• Fewer bugs: predictable code meant fewer “mystery” issues.
• Easier testing: pure functions were testable in isolation.
• More clarity: functions became smaller and more focused.

I compared one of our early design drafts (OOP + mutability) with the new functional rewrite:

• Before: side effects, global state mutation, debugging nightmares.
• After: pure functions, currying for flexibility, immutable state, testable in isolation.

It was like turning on the lights in a room I hadn’t even entered yet.

Wider Perspective: How Functional Programming Fits with OOP

Here’s the thing: functional programming isn’t out to kill OOP. It complements it.

• Keep classes for modeling domains and enforcing structure.
• Use FP for data handling, transformations, and logic.

The mix made me realize programming wasn’t about choosing one true paradigm—it was about knowing when to use the right tools.

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How Readers Can Start Their Journey

If you’re curious about functional programming but intimidated, start small:

1. Write your first pure function — no side effects.
2. Replace one loop with map or filter.
3. Try a curried function to see how partial application feels.

Think of it like training wheels—you don’t need to flip your whole project on day one.

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Conclusion: Reflection and Invitation

That project ended up being one of the rare ones I look back at with pride—not fear. Functional programming wasn’t a silver bullet, but it reshaped my mindset and gave me a new set of tools to fight complexity.

If you’ve ever felt like you’re battling unpredictable code demons, maybe it’s time to give pure functions—and maybe even a bit of currying—a try. Your future self will thank you.

And if you’ve already taken the leap into FP, I’d love to hear your story. Who knows—you might inspire the next skeptical developer to take the plunge.

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Explore more

• Scalfani, Charles — “Functional Programming Made Easier: A Step-by-Step Guide.” A beginner-to-advanced path using PureScript, covering essentials like pure functions, immutability, currying, composition, ADTs, functors, applicatives, monads, and even practical full‑stack exercises; ideal after learning basics in JS to deepen real FP thinking.

Note :  this is the book learned a lot from during the FP journey, and this mention isn’t sponsored or an ad—just a genuine recommendation.