What Is Programming? Compiled vs Interpreted Languages – What Beginners Need to Know

So you’ve decided to learn programming — brilliant! But now you’re hearing words like compiler, interpreter, libraries, packages. Feeling overwhelmed?

Don’t worry — this post explains everything using something everyone understands: cooking.

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Quick Analogy: Programming Is Like Cooking

Real Life	Programming
You (the chef)	You (the programmer)
Recipe in another language	Code (C++, Python, etc.)
Robot cooks	Computer hardware
Translator	Compiler / Interpreter
Spice mixes & sauces	Libraries / Packages

You want your robot cooks (your computer) to follow your recipe (your code), but they only understand machine language (1s and 0s). So you need a translator — either a compiler or an interpreter — to help.

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Compiled Languages (e.g. C, C++)

Analogy: You translate the entire recipe before cooking starts.

How It Works

1. You write your recipe in C/C++.
2. A compiler translates the entire code into machine language.
3. Your computer runs the translated version quickly and efficiently.

C code → compiler → machine code → run

Pros

• Very fast after translation
• Can be optimised to run better (e.g. simplify steps, reuse values)

Cons

• Slower to start — you must compile before running
• Harder to debug — errors show up after full translation

What You Need to Install

• A compiler (e.g. g++)
• Optional libraries (e.g. for graphics, maths, sound)

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How to Make a .exe File (C++)

When you compile C++ code using g++, it already creates a .exe file on Windows:

g++ hello.cpp -o hello.exe

Double-click the .exe file to run your program without the terminal!

Want a Basic Graphical Interface (UI)?

Use a library like WinAPI, SFML, or Qt (a bit more advanced):

#include <windows.h>

int main() {
    MessageBox(0, "Hello!", "Greeting", MB_OK);
    return 0;
}

Compile it the same way — and your .exe pops up a window!

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Interpreted Languages (e.g. Python)

Analogy: A live translator reads the recipe step-by-step as you cook.

How It Works

1. You write your recipe in Python.
2. An interpreter reads and runs each line in real time.

Python code → interpreter reads line-by-line → runs immediately

Pros

• Quick to start and test
• Easy to fix mistakes — interpreter stops exactly where the error happens

Cons

• Slower performance — it reads as it goes
• Less optimised — it doesn’t improve your code

What You Need to Install

• Python interpreter
• Packages (e.g. numpy, pandas)
• Package managers like pip or conda

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How to Make a .exe File (Python)

Python normally runs in the terminal, but you can convert your script to a .exe file using:

pip install pyinstaller
pyinstaller --onefile hello.py

This creates dist/hello.exe — now your Python script runs like a standalone app!

Want a Basic Graphical Interface (UI)?

Use the built-in Tkinter module:

import tkinter as tk

def say_hello():
    name = entry.get()
    label.config(text="Hello, " + name + "!")

root = tk.Tk()
root.title("Greeting App")

entry = tk.Entry(root)
entry.pack()

button = tk.Button(root, text="Say Hello", command=say_hello)
button.pack()

label = tk.Label(root)
label.pack()

root.mainloop()

Save as hello_gui.py, then convert to .exe:

pyinstaller --onefile --windowed hello_gui.py

Now you have a basic .exe app with a window interface!

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Why It Matters in Machine Learning

• Python is the go-to language — easy to write, read, and test ideas.
• Behind the scenes, tools like TensorFlow and PyTorch use compiled C++ for performance.
• It’s like Python is the friendly head chef, and C++ is the super-fast robot sous chef.

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Side-by-Side Comparison

Feature	Compiled Language (C/C++)	Interpreted Language (Python)
Translator	Compiler	Interpreter
When Code Runs	After compiling	While reading each line
Speed	Very fast	Slower
Debugging	Harder — fix after compile	Easier — errors show up live
Beginner-Friendly?	Less — more setup	Yes — quick to try things
Used in ML?	Yes — behind the scenes	Yes — main interface
What to Install	Compiler + Libraries	Interpreter + Packages
Can Make .exe?	Yes — auto from compiler	Yes — using PyInstaller
UI Option	WinAPI, Qt, SFML (advanced)	Tkinter (built-in)

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Let’s Try a Simple Program: “Hello, {Your Name}”

1 - Python (Interpreted Language)

What to install:

• Python interpreter
• Any text editor (e.g. Notepad or VS Code)

Code:

name = input("What's your name? ")
print("Hello, " + name + "!")

Run:

python hello.py

Make into .exe:

pyinstaller --onefile hello.py

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2 - C++ (Compiled Language)

What to install:

• A C++ compiler like g++
• A text/code editor

Code:

#include <iostream>
using namespace std;

int main() {
    string name;
    cout << "What's your name? ";
    cin >> name;
    cout << "Hello, " << name << "!" << endl;
    return 0;
}

Compile & run:

g++ hello.cpp -o hello.exe
./hello

Your .exe is ready to share!

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Final Thought

Knowing whether your language is compiled or interpreted is like knowing whether you’re cooking from scratch or using a meal kit.

• Want full control and speed? Compiled languages are great.
• Want fast results and simplicity? Interpreted languages like Python are perfect.
• Want a real .exe app with buttons? You can do it in both — just pick your tool.

Programming is like cooking — it’s not about having the fanciest kitchen. It’s about learning the basics, experimenting, and making things that work.