Comprehensions build lists, dicts, or sets in a compact, readable way. Instead of a loop with append, you write the transformation in one line. They're idiomatic Python—you'll see them everywhere. List comprehensions are most common; dict and set comprehensions follow the same pattern.

What you'll learn:

• List: [expr for x in iterable]
• With condition: [expr for x in iterable if condition]
• Dict: {key: value for x in iterable}
• Set: {expr for x in iterable}

# List comprehension
squares = [x**2 for x in range(5)]
print(squares)

# With condition
evens = [x for x in range(10) if x % 2 == 0]
print(evens)

# Dict comprehension
word_lengths = {word: len(word) for word in ["apple", "banana", "cherry"]}
print(word_lengths)

# Set comprehension
unique_lengths = {len(word) for word in ["apple", "banana", "apple"]}
print(unique_lengths)

# Nested
matrix = [[i * j for j in range(3)] for i in range(3)]
print(matrix)

The general form is [expression for item in iterable if condition]. Dict uses {key: value}; set uses {expression}. Nested comprehensions build nested structures.

To run this program:

$ python source/comprehensions.py
[0, 1, 4, 9, 16]
[0, 2, 4, 6, 8]
{'apple': 5, 'banana': 6, 'cherry': 6}
{5, 6}
[[0, 0, 0], [0, 1, 2], [0, 2, 4]]

Tip: Keep comprehensions readable. If they get long or complex, use a regular loop instead.

Try it: Use a list comprehension to get the uppercase version of each string in a list.

Source: comprehensions.py

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