🐍 Module 05 — Your First Code

Part 2 — Thinking Like an Engineer · Previous: How to Think Like a Programmer · Next: Data: The World’s New Oil

What you’ll learn

Why it matters

In Module 04 you wrote algorithms in pseudocode — structured English for humans. Today we take the final step: writing instructions a computer will actually run. That moment — typing something, pressing Run, and watching a machine obey you — is a small, permanent change in how you see every app on your phone. After today, software stops being magic. It’s instructions, and you can write them.

You don’t need to install anything. Everything in this module runs in a free website in your browser, on any laptop or phone. The lab tells you exactly where to go.

🐍 Why Python?

A programming language is a set of writing rules that both humans and computers can understand — you write in it, and the computer runs it. There are hundreds of programming languages. We start with Python, and here’s why:

⚠️ Watch out: the goal of today is not to memorize Python. It’s to recognize the five moving parts every language shares: speaking, remembering, listening, deciding, repeating. Learn these once and every other language is the same story with different spelling.

📢 print() — the program speaking

Here is a complete, genuine Python program. One line:

print("Hello, world!")

Run it, and the screen shows: Hello, world!

Line by line (there’s only one): print is Python’s word for “display this on the screen.” The parentheses () hold what to display. The quotation marks say “this is text, show it exactly as written.”

🌉 Analogy: print is the program’s mouth. A program does its work silently, inside the machine. Every time you want it to say something out loud, you give it a print line.

Where the analogy breaks down: a mouth speaks and the words vanish. print writes to the screen, where the words stay — more like a mouth attached to a ticker-tape machine.

By tradition, “Hello, world!” is every programmer’s first program. When you run it in the lab, you’ll be joining a ritual that goes back to the 1970s.

🫙 Variables — the program remembering

A variable is a named container that stores a piece of information so the program can use it later. Remember the “oldest so far” note from Module 04? That note was a variable.

🌉 Analogy: a variable is a labeled jar on a kitchen shelf. The label says sugar; the contents are whatever you put in. You can look inside whenever you like, and you can empty the jar and put something new in — the label stays the same.

Where the analogy breaks down: pour new contents into a real jar and the old contents are still around somewhere (on the counter, probably). Put a new value in a variable and the old value is gone, instantly and completely.

name = "Priya"
age = 34
print(name)
print(age)

Line by line:

  1. name = "Priya" — make a jar labeled name, put the text "Priya" inside. In code, = doesn’t mean “equals” like in school math; it means “store this on the right into the jar on the left.”
  2. age = 34 — a second jar, labeled age, containing the number 34.
  3. print(name) — no quotation marks this time! So Python doesn’t print the word name; it opens the jar called name and prints what’s inside: Priya.
  4. print(age) — opens the other jar: 34.

And you can swap contents: if a later line says age = 35, the jar now holds 35, and the 34 is gone. Happy birthday.

🔢 Numbers vs. text: why 5 and "5" are different

A quick but important preview. Python treats kinds of information differently. A data type is the kind of value something is — for now, two kinds matter:

Why care? Because 5 + 5 is 10, but "5" + "5" is "55" — Python glues strings together instead of adding them. To Python, "5" is not a quantity; it’s a character, the same kind of thing as "a" or "?". Confusing numbers with strings is one of the most common beginner stumbles, so when it happens to you, you’ll know: check the quotation marks. (We’ll dig deeper into kinds of data in Module 06.)

✅ Check yourself

  1. What does the = sign do in city = "Lagos"?
  2. What will print(city) show — the word city or the word Lagos?
  3. Is "34" a number or a string?
Show answer 1. It stores the value on the right (`"Lagos"`) into the variable (jar) named on the left (`city`). 2. `Lagos` — no quotation marks around `city` means "open the jar and show what's inside." 3. A string. The quotation marks make it text, even though it looks like a number. `"34" + "1"` would give `"341"`, not 35.

👂 input() — the program listening

print is the mouth; input is the ear. The input instruction makes the program pause, wait for the person at the keyboard to type something, and hand over whatever they typed.

name = input("What is your name? ")
print("Nice to meet you, " + name)

Line by line:

  1. name = input("What is your name? ") — display the question, then wait. Whatever the person types goes into the jar labeled name.
  2. print("Nice to meet you, " + name) — glue two strings together: the fixed text and the contents of the jar. If you typed Sam, the screen shows Nice to meet you, Sam.

Two lines, and your program is already interactive — it behaves differently for every person who runs it. One catch worth knowing now: everything input hands you is a string, even if the person types 34. Keep that in your back pocket; it explains a classic beginner surprise in the lab.

🚦 if / elif / else — forks in the road

Programs constantly choose between paths — the diamonds in your Module 04 flowchart. In Python, the diamond is spelled if.

🌉 Analogy: if is a bouncer at a club door, checking IDs. If you’re 18 or over → come in. Otherwise → sorry, not tonight. One check, two paths, everybody goes down exactly one of them.

Where the analogy breaks down: a human bouncer can be argued with, or waves in someone who looks 25. The if never bends. 17 years and 364 days is a no.

age = 20
if age >= 18:
    print("Welcome in!")
elif age >= 16:
    print("You can enter, but no wristband.")
else:
    print("Sorry, come back in a few years.")

Line by line:

  1. age = 20 — a jar with 20 in it.
  2. if age >= 18: — the first check: is the value in age greater than or equal to 18? The colon : means “here comes what to do if yes.”
  3. ` print(“Welcome in!”)` — notice this line is pushed to the right. That indent is how Python knows this line belongs inside the if. It runs only when the check passes.
  4. elif age >= 16: — short for “else if”: a second check, tried only if the first one failed.
  5. Its indented line — runs only if check 1 failed and check 2 passed.
  6. else: — the catch-all: what to do if every check above failed.
  7. Its indented line — the “sorry” message.

With age = 20, the first check passes, so the screen shows Welcome in! — and Python skips the rest entirely. One fork, one path taken.

🔁 Loops — the program repeating

Module 04’s big insight: computers are phenomenal at repetition. Loops are how you ask for it. Python has two, and the difference is what kind of stopping you want.

A for loop repeats once for each item in a collection.

🌉 Analogy: unpacking a shopping basket. For each item in the basket: take it out, put it away. You don’t decide in advance how many times to repeat — the basket decides. Empty basket, loop over.

for friend in ["Amara", "Ben", "Chloe"]:
    print("Hello, " + friend + "!")

Line 1: “for each item in this list of three names, calling the current one friend, do the indented lines.” Line 2 runs three times, and each time the jar friend holds the next name. Output:

Hello, Amara!
Hello, Ben!
Hello, Chloe!

A while loop repeats as long as a condition stays true.

🌉 Analogy: a recipe that says “stir until thick.” Nobody tells you how many stirs. You stir, check, stir, check — and stop the moment the condition changes.

Where both analogies break down: you would eventually stop stirring out of boredom or suspicion that something’s wrong. A computer will not. If the condition never changes, a while loop runs forever — the famous infinite loop, and every programmer has caused one. (The fix is undramatic: stop the program and find out why your condition never became false.)

countdown = 3
while countdown > 0:
    print(countdown)
    countdown = countdown - 1
print("Lift off!")

Line by line: start the jar at 3. While the jar holds more than 0: print it, then put back one less than what’s inside. So it prints 3, 2, 1 — then the check countdown > 0 fails (0 is not more than 0), the loop ends, and the final unindented line prints Lift off!.

✅ Check yourself

  1. You want to send the same message to everyone in your contacts list. for loop or while loop?
  2. You want to keep asking for a password until the right one is typed. for or while?
  3. In the countdown, what would happen if we forgot the line countdown = countdown - 1?
Show answer 1. `for` — you have a collection, and you want one repeat per item. 2. `while` — you don't know how many tries it will take; repeat *while* the password is wrong. 3. The jar would stay at 3 forever, `countdown > 0` would always be true, and the program would print 3 endlessly — an infinite loop.

🧩 Putting it all together: one small, complete program

Everything above, in one program you’ll build yourself in the lab. Read it slowly — you now know every piece.

print("Welcome to the Rocket Club!")
name = input("What is your name? ")
age = int(input("How old are you? "))

if age >= 12:
    print("You're cleared for launch, " + name + "!")
    countdown = 5
    while countdown > 0:
        print(countdown)
        countdown = countdown - 1
    print("Lift off! 🚀")
else:
    print("Sorry " + name + ", pilots must be 12 or older.")
    print("Come back in " + str(12 - age) + " years!")

The walkthrough:

Fifteen lines. Speaking, listening, remembering, converting, deciding, repeating. That is — honestly — the skeleton of most software you have ever used, at a much smaller scale.

🩹 Errors are normal (and weirdly polite)

At some point today you will see something like:

File "main.py", line 3
    print("Hello"
                 ^
SyntaxError: '(' was never closed

Your first instinct will be I broke it. You didn’t. Nothing is broken, and nobody is judging you.

🌉 Analogy: an error message is the computer being a pedantic proofreader. It read your instructions, hit something it couldn’t understand, and handed the page back with a note: which line (line 3), where on the line (the little ^ arrow), and what confused it (a bracket was opened and never closed).

Where the analogy breaks down: a proofreader reads the whole page and marks everything. The computer stops at the first problem it hits and refuses to go on. Fix that one, run again, and it will tell you about the next — one complaint at a time.

The habit to build from day one: read the message. Beginners look away from error text as if it were an angry red exam mark. It isn’t — it’s the machine doing half your detective work from Module 04 for you, usually naming the exact line. Professional programmers see errors every single working day. The difference between a beginner and a pro is not fewer errors; it’s less fear of them.

💪 What you can and can’t do now — honestly

Let’s be straight with each other, because motivation built on hype collapses fast.

What you cannot do yet: build Instagram. Real apps involve screens, databases, servers, and teams — the topics of Parts 3, 4, and 5 of this course. Anyone who promises “build the next Facebook in a weekend” is selling something.

What you genuinely can do, or nearly can: automate small, boring chores. A program that renames 200 photo files. One that adds up expenses. One that picks whose turn it is to do the dishes. One that quizzes your kid on multiplication tables. These sound humble. They are the actual daily magic of knowing how to code — thousands of people save hours every week with programs the size of the rocket example above. (The Automate the Boring Stuff book in this module’s resources is an entire, wonderful free book about exactly this.)

🎁 Recap

🌉 Next up

Every program you wrote today worked on little scraps of information — a name, an age, a list of three friends. Real software works on oceans of information: every photo, message, and payment you’ve ever made. In Module 06 — Data: The World’s New Oil, we look at what data actually is, the containers programs keep it in, and why companies are so hungry for yours.

But first: the lab. Today is the day you actually run code. Go press the button.