Python List Comprehensions — 5 Patterns You'll Actually Use

About this lesson

A list comprehension is a one-line for loop that builds a list. Same algorithm, fewer characters, and faster because the loop runs in C instead of Python bytecode. This tutorial walks the five patterns you'll meet in real code, on a tiny numeric example, plus the one case where a regular for loop is still the right call. The five patterns: map (transform each element), filter (keep elements that pass), map and filter combined, flatten (nested for-clauses), and dict and set comprehensions (same syntax, different brackets). Then a timing comparison on 100,000 items showing the comprehension runs roughly twice as fast as the equivalent for-plus-append loop. And finally, the rule for when NOT to reach for a comprehension — anywhere the body needs multiple statements, side effects, or a break or continue. What You'll Build: - list_comp.py — one file, five numbered comprehension patterns, a 100k-item speed comparison, and a deliberate for-loop counterexample for the case where comprehension stops being the right tool. - Pattern 1: map — [x * x for x in nums]. Transform each element. The for+append equivalent is four lines; the comprehension is one. - Pattern 2: filter — [x for x in nums if x % 2 == 0]. Keep elements matching a condition. The if clause goes at the end. - Pattern 3: map and filter combined — [x * x for x in nums if x gt 3]. Same shape, both clauses in one expression. - Pattern 4: flatten — [item for row in matrix for item in row]. Multiple for clauses read left-to-right like nested for loops. The outer for goes first, the inner second. - Pattern 5: dict and set comprehensions — {w: len(w) for w in words} and {x % 3 for x in range(100)}. Same syntax, curly braces. With a colon you get a dict; without, you get a set. - Speed — the comprehension version of a 100,000-item loop runs about 2x faster than the equivalent for-plus-append. Same work, less Python-level overhead, more of the loop runs in C under the hood. - When NOT to use a comprehension — when the

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