Comprehensions — list, dict, set, generator

One-line loops that build collections. Faster and more Pythonic than for+append.

script.py v3.1

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

# With filter
evens = [x for x in range(10) if x % 2 == 0]
print('evens:', evens)

# With if/else (different from filter!)
labels = ['even' if x % 2 == 0 else 'odd' for x in range(5)]
print('labels:', labels)

# Dict comprehension
square_dict = {x: x*x for x in range(5)}
print('square_dict:', square_dict)

# Set comprehension
unique_lens = {len(w) for w in ['a', 'bb', 'ccc', 'bb', 'a']}
print('unique_lens:', unique_lens)

# Generator expression (lazy — uses () not [])
gen = (x*x for x in range(5))
print('gen:', gen)  # generator object
print('list(gen):', list(gen))  # consume it

# Nested comprehension (matrix transpose)
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
transposed = [[row[i] for row in matrix] for i in range(3)]
print('transposed:', transposed)

Python output click Run to execute

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🧠 How it works

[expr for x in iter if cond] — list comprehension. The if is a FILTER (skips items where cond is False). [a if cond else b for x in iter] — if/else EXPRESSION (maps each item to a or b). Different syntax! {k: v for k, v in iter} — dict comprehension. {x for x in iter} — set comprehension (deduplicates). (expr for x in iter) — generator expression. Lazy — produces values on demand. Memory-efficient for big data. Comprehensions are FASTER than for+append because the loop runs in C, not Python. Don't overdo it — if your comprehension is more than 1 line, use a regular for loop for readability.

✏️ Try these changes

Change [x*x for x in range(5)] to [x*x for x in range(5) if x % 2 == 0]
→ only squares of evens: [0, 4, 16]
Change the if/else to 'positive' if x > 0 else 'zero' if x == 0 else 'negative'
→ nested ternary (hard to read — use a function)
Change square_dict to {x: x*x for x in range(10) if x % 2 == 0}
→ only even keys
Change the generator to a list: list(x*x for x in range(5))
→ same as list comprehension

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Strings — f-strings, methods, slicing