The Tool Desk
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Convert a simple append loop
Start with a loop that builds a list by appending exactly one result for each item:
squares = []
for number in numbers:
squares.append(number * number)Replace it with a list comprehension whose expression is the value passed to append(), and whose for clause uses the same iteration target and iterable:
squares = [number * number for number in numbers]This is a sound refactor when the loop visits the same iterable once, computes the same expression once per item, and appends results in the same order—with no other behavior that the program depends on. The [Python Tutorial’s data-structures chapter](https://docs.python.org/3.15/tutorial/datastructures.html) shows list comprehensions alongside equivalent loops.
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Preserve filtering
If the loop appends only when a condition is true, put that condition after the comprehension’s for clause:
positive = []
for value in values:
if value > 0:
positive.append(value)positive = [value for value in values if value > 0]The condition is tested for each candidate before its value is included. Keep the original condition and its place in the iteration. In nested loops, a filter belongs at the level where the original if ran; moving it can change which results are produced. The [Python expression reference](https://docs.python.org/3.15/reference/expressions.html#displays-for-lists-sets-and-dictionaries) describes comprehension filters.
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Translate nested loops in their original order
Each additional for clause represents a nested loop. Write clauses from outermost to innermost so traversal and output order remain consistent:
pairs = []
for left in left_values:
for right in right_values:
pairs.append((left, right))pairs = [(left, right) for left in left_values for right in right_values]Use parentheses around a tuple result, as in (left, right). If the inner iterable depends on the outer variable, preserve that dependency in the corresponding clause, for example [x * y for x in range(10) for y in range(x, x + 10)]. The [Functional Programming HOWTO](https://docs.python.org/3.14/howto/functional.html#list-comprehensions) explains how multiple clauses correspond to nested loops; two unfiltered sequences of three values each produce nine combinations.
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For complicated nesting, keep the explicit loops or move the logic to a helper function if the comprehension hides the control flow. The [Python Tutorial](https://docs.python.org/3.15/tutorial/datastructures.html) also shows nested comprehensions and their loop equivalents.
Check behavior before replacing the loop
- Iteration and result order: Use the same iterable and preserve the original outer-to-inner clause order. Comprehensions produce values in the order implied by their clauses.
- Appended value: Make the expression match what the loop passed to
append(). For tuples, use a tuple expression such as(x, y). - Filtering: Preserve each condition’s truth test and attach it to the same loop level as before.
- Side effects: Keep a loop if it also logs, mutates other objects, increments counters, catches exceptions, or performs other work that matters. Do not bury required work in side-effecting expressions merely to shorten the code.
- Post-loop variable use: In Python 3, a comprehension’s iteration variable has its own scope and does not leak into the surrounding scope. If later code relies on the loop target’s value after the loop, a direct replacement changes behavior. See the [Python Language Reference](https://docs.python.org/3.14/reference/expressions.html#displays-for-lists-sets-and-dictionaries).
- Control flow and resource handling: A comprehension is not a direct substitute for a loop that uses
break, a loopelse, exception or resource-management blocks, or other multi-statement control flow. Keep the loop when those behaviors matter. - Evaluation order: Consider any expressions whose effects depend on order. The [Python Language Reference, section 6.16](https://docs.python.org/3.14/reference/expressions.html#evaluation-order) states, “Python evaluates expressions from left to right.”
Watch for scope and syntax differences
Comprehensions run in an implicitly nested scope, so a comprehension in a class body has a documented interaction with class-local names. Avoid relying on a class-body local being visible inside the comprehension; consult the [Python Execution Model](https://docs.python.org/3.11/reference/executionmodel.html#interaction-with-dynamic-features).
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Use square brackets when the goal is to build a list immediately. Parentheses produce a generator expression, which yields values lazily instead of constructing the list at that point. The distinction is documented in the [Python Language Reference](https://docs.python.org/3.14/reference/expressions.html#generator-expressions).
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.When to keep the explicit loop
A comprehension is a good fit when it makes a straightforward list-building operation easier to read. Keep the loop when it has meaningful work beyond producing the list, depends on post-loop variable behavior, uses unsupported control flow or resource handling, or would become hard to follow when compressed. The goal is equivalent behavior and maintainable code, not the shortest possible spelling.
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