Reviewed by Aditya Kumar · Last reviewed 2026-03-24
**Why List Semantics Matter:** lst += [x] mutates in-place; lst = lst + [x] creates new list—affects performance and shared references. In pipelines, unintended mutation causes subtle bugs. **Operations & Complexity:** append O(1) amortized; insert(0, x) O(n); extend O(k); in...
This easy-level Python/Coding question appears frequently in data engineering interviews at companies like McKinsey. While less common, it tests deeper understanding that distinguishes strong candidates.
Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.
Why List Semantics Matter: lst += [x] mutates in-place; lst = lst + [x] creates new list—affects performance and shared references. In pipelines, unintended mutation causes subtle bugs.
Operations & Complexity: append O(1) amortized; insert(0, x) O(n); extend O(k); in O(n). For repeated prepend: use collections.deque (O(1) appendleft). For sorted insert: bisect.insort O(n).
Production Gotcha: Never modify a list while iterating—use [x for x in lst if cond] or iterate over lst[:]. For large sequences, consider NumPy array or generator.
lst.extend([1,2]) # in-place, preferred for batch add
lst = lst + [1,2] # new list, use when need immutable copy
Red Flag: Using lst += x (type error for non-iterable). Pro-Move: 'We use deque for our pipeline stage buffers—O(1) at both ends for producer-consumer pattern.'
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According to DataEngPrep.tech, this is one of the most frequently asked Python/Coding interview questions, reported at 1 company. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.