Week 02 · Intermediate Track

Week 2 — Comprehensions & Generators

Write concise, readable data transformations with list, dict, and set comprehensions. Then step into generators and yield for memory-efficient iteration.

Intermediate Track2 min readFree lesson

Level: Intermediate | Prerequisite: Week 1 (Advanced Functions)

Learning Goals

Write list, dictionary, and set comprehensions
Understand generator functions and expressions
Write memory-efficient code

1. List Comprehensions

[expression for variable in sequence if condition] Create a list in one line.

#Existing
squares = []
for x in range(10):
    squares.append(x * x)

#Comprehension
squares = [x * x for x in range(10)]

Add conditions:

even_sq = [x * x for x in range(10) if x % 2 == 0]
# [0, 4, 16, 36, 64]

Nested:

pairs = [(i, j) for i in range(3) for j in range(3) if i != j]

2. Dictionary and Set Comprehensions

words = ["apple", "banana", "cherry"]

#Dictionary: {key: value for ...}
length_map = {w: len(w) for w in words}
# {'apple': 5, 'banana': 6, 'cherry': 6}

#Set: {expression for ...}
unique_lens = {len(w) for w in words}
# {5, 6}

3. Generator Functions

return instead of yield. Produce results one by one as needed, not all at once.

def fib(n):
    a, b = 0, 1
    for _ in range(n):
        yield a
        a, b = b, a + b

for x in fib(10):
    print(x, end=" ")    # 0 1 1 2 3 5 8 13 21 34

If you want to see them all at once as a list, use list(fib(10)).

4. Generator Expressions

Use parentheses instead of brackets → save memory.

#List comprehension (eats up all the memory)
total = sum([x * x for x in range(1_000_000)])

#Generator expression (one at a time)
total = sum(x * x for x in range(1_000_000))

5. When to use which?

Situation	Tool
Small data + need index	List comprehension
Large data + single pass	Generator
Key-value mapping	Dictionary comprehension
Remove duplicates	Set comprehension

Key Examples (examples/)

File	Content
`01_list_comp.py`	List comprehension
`02_dict_set_comp.py`	Dictionary/Set
`03_generator.py`	Generator function
`04_generator_expr.py`	Generator expression (compare memory)

⚠️ Common Mistakes

Comprehension is too long and complicated — if readability drops, just use a for loop
Iterate the generator twice — once fully iterated, it will be empty. Needs to be called again.
If yield is anywhere in the function, the entire function is a generator — cannot return normal values with return

❓ FAQ

Q1. Are comprehensions always faster than for loops? A. Usually slightly faster. The biggest difference is readability and expression of intent.

Q2. Can we know the length of a generator? A. No. If you need the length, convert it to a list (memory usage).

Q3. Can there be multiple yields? A. Yes. Each time it is called, it executes up to the next yield.

📝 Exercises (exercises/)

exercise1.md — primes from 1 to 100 (comprehension)
exercise2.md — mapping word lengths
exercise3.md — large file line-by-line generator

Next Week

Week 3. Modules and Packages

Example files

The runnable files used in this lesson. Copy them into your own project and experiment.

examples/01_list_comp.pyPython

#Basic
squares = [x * x for x in range(10)]
print(squares)

#Condition Filter
even_sq = [x * x for x in range(10) if x % 2 == 0]
print(even_sq)

#Nested
pairs = [(i, j) for i in range(3) for j in range(3) if i != j]
print(pairs)

#String Processing
words = ["Hello", "World", "Python"]
upper = [w.upper() for w in words]
print(upper)

examples/02_dict_set_comp.pyPython

words = ["apple", "banana", "cherry"]

#Dictionary Comprehension
length_map = {w: len(w) for w in words}
print(length_map)

#Inverting Key-Value
d = {"a": 1, "b": 2, "c": 3}
inv = {v: k for k, v in d.items()}
print(inv)

#Set Comprehension
unique_lens = {len(w) for w in words}
print(unique_lens)

text = "the quick brown fox jumps over the lazy dog"
unique_words = {w for w in text.split()}
print(len(unique_words))

examples/03_generator.pyPython

def fib(n):
    a, b = 0, 1
    for _ in range(n):
        yield a
        a, b = b, a + b

for x in fib(10):
    print(x, end=" ")
print()

#Receive all at once as a list
print(list(fib(10)))

#Infinite generator
def naturals():
    n = 1
    while True:
        yield n
        n += 1

import itertools
first_5 = list(itertools.islice(naturals(), 5))
print(first_5)

examples/04_generator_expr.pyPython

import sys

#List comprehension — eats up all the memory
list_sq = [x * x for x in range(1_000_000)]
print(f"list memory: {sys.getsizeof(list_sq):,} bytes")

#Generator expression — one at a time
gen_sq = (x * x for x in range(1_000_000))
print(f"generator memory: {sys.getsizeof(gen_sq):,} bytes")

#The result is the same
print(sum(x * x for x in range(100)))

Assignment

Goal

Select only the prime numbers between 1 and 100 and make a list. Use comprehension.

Hint

Define the is_prime(n) function first
primes = [n for n in range(2, 101) if is_prime(n)]

Input/Output Example

[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97]
Total 25

Assignment 2. Word Length Mapping

Goal

Create a {Word: Length} dictionary from a list of words.

Requirements

Use dictionary comprehension
Duplicate words only once

Input Example

words = ["apple", "banana", "apple", "cherry", "date", "banana"]

Output Example

{'apple': 5, 'banana': 6, 'cherry': 6, 'date': 4}

Assignment 3. Large File Line Generator

Goal

Write a generator read_lines(path) that yields file contents line by line.

Requirements

Do not load the entire large file into memory at once
Exclude empty lines and spaces (skip if empty after strip)

Example of use

for line in read_lines("data.txt"):
    print(line)

Challenge

Also write a chunked_lines(path, n) that yields lines grouped by N

Show the reference solution

Try the assignment yourself first — comparing your attempt with a working solution is where most of the learning happens.

solution1.pyPython

def is_prime(n):
    if n < 2:
        return False
    if n == 2:
        return True
    if n % 2 == 0:
        return False
    return all(n % i for i in range(3, int(n ** 0.5) + 1, 2))

primes = [n for n in range(2, 101) if is_prime(n)]
print(primes)
print(f"Total {len(primes)} items")

solution2.pyPython

words = ["apple", "banana", "apple", "cherry", "date", "banana"]

length_map = {w: len(w) for w in set(words)}
print(length_map)

#Input order maintained version
length_map2 = {}
for w in words:
    length_map2.setdefault(w, len(w))
print(length_map2)

solution3.pyPython

def read_lines(path):
    with open(path, encoding="utf-8") as f:
        for line in f:
            line = line.strip()
            if line:
                yield line

def chunked_lines(path, n):
    chunk = []
    for line in read_lines(path):
        chunk.append(line)
        if len(chunk) >= n:
            yield chunk
            chunk = []
    if chunk:
        yield chunk

#For testing (reading own file)
import sys, pathlib
self_path = pathlib.Path(__file__)
for line in read_lines(self_path):
    print(line)
print("---")
for chunk in chunked_lines(self_path, 3):
    print("Chunk:", chunk)
    print("---")

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