Lesson 01
Iterators, Generators, and Decorators — Demand-Driven Python
Learn iterators with a Netflix analogy, generators as a water tap, and decorators as gift wrapping—then map iter(), yield, and @ to Python.
is the remote;next()is the button - Generator — Water tap:
yieldpours one glass at a time, not the whole tank - Decorator — Gift wrap:
@adds presentation without changing the phone inside - How
iter(),yield, and@decoratorwork together in Python
One simple picture
![iterator walks data generator creates decorator adds extra](data:image/svg+xml;charset=utf-8,%3Csvg%20font-family%3D%27ui-sans-serif%2C-apple-system%2Csystem-ui%2CArial%27%20width%3D%27100%25%27%20xmlns%3D%27http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%27%20viewBox%3D%270%200%20320%2096%27%3E%20%3Crect%20width%3D%27320%27%20height%3D%2796%27%20rx%3D%2716%27%20fill%3D%27%23F8FAFC%27%2F%3E%20%3Crect%20x%3D%2710%27%20y%3D%2718%27%20width%3D%2790%27%20height%3D%2760%27%20rx%3D%2710%27%20fill%3D%27%23DBEAFE%27%20stroke%3D%27%232563EB%27%2F%3E%20%3Ctext%20x%3D%2755%27%20y%3D%2736%27%20font-size%3D%2710%27%20font-weight%3D%27bold%27%20text-anchor%3D%27middle%27%20fill%3D%27%231D4ED8%27%3EIterator%3C%2Ftext%3E%20%3Ctext%20x%3D%2755%27%20y%3D%2750%27%20font-size%3D%278%27%20text-anchor%3D%27middle%27%20fill%3D%27%231E40AF%27%3EOne%20by%20one%3C%2Ftext%3E%20%3Cpath%20d%3D%27M100%2048%20H118%27%20stroke%3D%27%2364748B%27%20stroke-dasharray%3D%273%203%27%2F%3E%20%3Cpolygon%20points%3D%27116%2C44%20122%2C48%20116%2C52%27%20fill%3D%27%2364748B%27%2F%3E%20%3Crect%20x%3D%27122%27%20y%3D%2718%27%20width%3D%2790%27%20height%3D%2760%27%20rx%3D%2710%27%20fill%3D%27%23D1FAE5%27%20stroke%3D%27%23059669%27%2F%3E%20%3Ctext%20x%3D%27167%27%20y%3D%2736%27%20font-size%3D%2710%27%20font-weight%3D%27bold%27%20text-anchor%3D%27middle%27%20fill%3D%27%23047857%27%3EGenerator%3C%2Ftext%3E%20%3Ctext%20x%3D%27167%27%20y%3D%2750%27%20font-size%3D%278%27%20text-anchor%3D%27middle%27%20fill%3D%27%23065F46%27%3ECreates%20on%3C%2Ftext%3E%20%3Ctext%20x%3D%27167%27%20y%3D%2760%27%20font-size%3D%278%27%20text-anchor%3D%27middle%27%20fill%3D%27%23065F46%27%3Edemand%3C%2Ftext%3E%20%3Cpath%20d%3D%27M212%2048%20H230%27%20stroke%3D%27%2364748B%27%20stroke-dasharray%3D%273%203%27%2F%3E%20%3Cpolygon%20points%3D%27228%2C44%20234%2C48%20228%2C52%27%20fill%3D%27%2364748B%27%2F%3E%20%3Crect%20x%3D%27234%27%20y%3D%2718%27%20width%3D%2776%27%20height%3D%2760%27%20rx%3D%2710%27%20fill%3D%27%23FDE68A%27%20stroke%3D%27%23D97706%27%2F%3E%20%3Ctext%20x%3D%27272%27%20y%3D%2736%27%20font-size%3D%2710%27%20font-weight%3D%27bold%27%20text-anchor%3D%27middle%27%20fill%3D%27%2392400E%27%3EDecorator%3C%2Ftext%3E%20%3Ctext%20x%3D%27272%27%20y%3D%2750%27%20font-size%3D%278%27%20text-anchor%3D%27middle%27%20fill%3D%27%2378350F%27%3EAdds%20extra%3C%2Ftext%3E%20%3Ctext%20x%3D%27160%27%20y%3D%2788%27%20font-size%3D%278%27%20text-anchor%3D%27middle%27%20fill%3D%27%2364748B%27%3EWalks%20data%20%C2%B7%20Creates%20data%20%C2%B7%20Enhances%20functions%3C%2Ftext%3E%20%3C%2Fsvg%3E
| Story | Python idea | Real-life action |
|---|---|---|
| Netflix Next | Iterator | One episode when you ask |
| Water tap | Generator | One glass when you open |
| Gift wrap | Decorator | Same item, extra layer |
1. Iterator = Netflix "Next Episode"
You do not download all 500 episodes. You press Next, and Netflix gives you one episode.
![Netflix press Next get one episode at a time](data:image/svg+xml;charset=utf-8,%3Csvg%20font-family%3D%27ui-sans-serif%2C-apple-system%2Csystem-ui%2CArial%27%20width%3D%27100%25%27%20xmlns%3D%27http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%27%20viewBox%3D%270%200%20320%20120%27%3E%20%3Crect%20width%3D%27320%27%20height%3D%27120%27%20rx%3D%2716%27%20fill%3D%27%23111827%27%2F%3E%20%3Ctext%20x%3D%2716%27%20y%3D%2718%27%20font-size%3D%2710%27%20font-weight%3D%27bold%27%20fill%3D%27%23F59E0B%27%3ENETFLIX%3C%2Ftext%3E%20%3Crect%20x%3D%2716%27%20y%3D%2734%27%20width%3D%2780%27%20height%3D%2756%27%20rx%3D%278%27%20fill%3D%27%23DC2626%27%2F%3E%20%3Ctext%20x%3D%2756%27%20y%3D%2752%27%20font-size%3D%278%27%20text-anchor%3D%27middle%27%20fill%3D%27%23FFFFFF%27%3EEpisode%201%3C%2Ftext%3E%20%3Ctext%20x%3D%2756%27%20y%3D%2766%27%20font-size%3D%277%27%20text-anchor%3D%27middle%27%20fill%3D%27%23FECACA%27%3Eplaying%3C%2Ftext%3E%20%3Cpath%20d%3D%27M96%2062%20H106%27%20stroke%3D%27%239CA3AF%27%20stroke-dasharray%3D%273%203%27%2F%3E%20%3Cpolygon%20points%3D%27104%2C58%20110%2C62%20104%2C66%27%20fill%3D%27%239CA3AF%27%2F%3E%20%3Crect%20x%3D%27112%27%20y%3D%2734%27%20width%3D%2780%27%20height%3D%2756%27%20rx%3D%278%27%20fill%3D%27%23374151%27%2F%3E%20%3Ctext%20x%3D%27152%27%20y%3D%2752%27%20font-size%3D%278%27%20text-anchor%3D%27middle%27%20fill%3D%27%23FFFFFF%27%3EEpisode%202%3C%2Ftext%3E%20%3Cpath%20d%3D%27M192%2062%20H202%27%20stroke%3D%27%239CA3AF%27%20stroke-dasharray%3D%273%203%27%2F%3E%20%3Cpolygon%20points%3D%27200%2C58%20206%2C62%20200%2C66%27%20fill%3D%27%239CA3AF%27%2F%3E%20%3Crect%20x%3D%27208%27%20y%3D%2734%27%20width%3D%2780%27%20height%3D%2756%27%20rx%3D%278%27%20fill%3D%27%23374151%27%2F%3E%20%3Ctext%20x%3D%27248%27%20y%3D%2752%27%20font-size%3D%278%27%20text-anchor%3D%27middle%27%20fill%3D%27%23FFFFFF%27%3EEpisode%203%3C%2Ftext%3E%20%3Ctext%20x%3D%27160%27%20y%3D%27108%27%20font-size%3D%278%27%20text-anchor%3D%27middle%27%20fill%3D%27%23D1D5DB%27%3EPress%20Next%20%E2%80%94%20get%20one%20episode%20%28next%28%29%29%3C%2Ftext%3E%20%3C%2Fsvg%3E
Python version:
movies = ["Ep1", "Ep2", "Ep3"]
it = iter(movies)
print(next(it)) # Ep1
print(next(it)) # Ep2
print(next(it)) # Ep3What's happening?
iter()creates the remote controlnext()presses the Next button- When episodes finish →
StopIteration
Try the mixed-type list vals = [10, "RS", 23.45, True] in the playground below.
Deep dive: iter() and next().
2. Generator = Water Tap
A water tank holds 1000 liters. Your tap gives only the water you ask for — not all 1000 liters at once.
:
yield "Glass 1"
yield "Glass 2"
yield "Glass 3"
tap = water()
print(next(tap)) # Glass 1
print(next(tap)) # Glass 2Every yield is like opening the tap for one glass. The function pauses until the next next() or for step.
The getcourses() generator with PYTHON, HTML, C, C++ uses the same pattern in the playground.
Deep dive: Generators and yield.
3. Decorator = Gift Wrapping
Your friend gives you a phone. You wrap it in gift paper. The phone is unchanged — you only added something around it.
:
def inner():
item = func()
return "Gift: " + item
return inner
@gift_wrap
def phone():
return "iPhone"
print(phone()) # Gift: iPhoneThe decorator does not rewrite phone(). It only wraps what comes back.
The @square example on getval() (returns 5.0, squares to 25.0) is in the playground — same wrapping idea with math instead of a bow.
Deep dive: Decorators overview.
yield vs return — The Delivery Guy Story
 + next() |
Press Next → one episode |
| Water tap | yield |
Open tap → one glass |
| Gift wrap | @decorator |
Wrap → same gift, better presentation |
Each Python keyword maps to a real-life action you already know:
iter()→ create the remote controlnext()→ press Nextyield→ pour one glass@decorator→ wrap the gift
Complete example
Run the playground for the full script — list iterator, getcourses, @square, and StringIO:
from io import StringIO
vals = [10, "RS", 23.45, True]
itr = iter(vals)
print(type(vals), type(itr))
print(next(itr))
print(next(itr))
def getcourses():
yield "PYTHON"
yield "HTML"
yield "C"
yield "C++"
g = getcourses()
print(type(g), next(g), next(g))
def square(m):
def calculate():
n = m()
return n, n ** 2
return calculate
@square
def getval():
return 5.0
n, sq = getval()
print("Square({})={}".format(n, sq))
names = StringIO("Swathi\nRahul\nPriya\n")
print(list(names))Expected output (simplified):
10
RS
PYTHON HTML
Square(5.0)=25.0
['Swathi\n', 'Rahul\n', 'Priya\n']Interview questions
-
What is the difference between an iterable and an iterator?
An iterable (like a list) can create an iterator. An iterator remembers its position and produces one item at a time using
next(). -
Why is
yieldmore memory efficient thanreturn?yieldgenerates values only when needed — like one glass from the tap, not emptying the whole tank. -
What does
@decoratoractually do?@decoratoris shorthand forfunction = decorator(function). It replaces the original function with the wrapped version.
Key takeaway
Do work only when needed.
- Iterator (Netflix) → reads existing data one episode at a time
- Generator (tap) → creates data one glass at a time with
yield - Decorator (gift wrap) → extends behavior without rewriting the original function
Next: iter() and next().
Loading playground…
Check your understanding
Iterators generators decorators overview quiz
Why do the iterator notes exist?
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