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List Comprehension - example

Python/Codingeasy0.7 min readPremium

**Why List Comprehensions at Scale:** They're syntactic sugar for map+filter but execute in C-optimized loops. However, they materialize the entire list in memory—O(n) allocation up front. **Trade-offs:** (1) List comp vs loop: Same big-O; list comp often 20–30% faster due to...

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Frequency
Low
Asked at 1 company
Category
179
questions in Python/Coding
Difficulty Split
127E|24M|28H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
LTIMindtree

Why This Question Matters

This easy-level Python/Coding question appears frequently in data engineering interviews at companies like LTIMindtree. While less common, it tests deeper understanding that distinguishes strong candidates.

How to Approach This

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.

Expert Answer
134 words

Why List Comprehensions at Scale: They're syntactic sugar for map+filter but execute in C-optimized loops. However, they materialize the entire list in memory—O(n) allocation up front.

Trade-offs: (1) List comp vs loop: Same big-O; list comp often 20–30% faster due to specialized bytecode. (2) List comp vs generator: [x for x in huge] loads all; (x for x in huge) streams. For 100M rows, list comp = OOM; generator = constant memory. (3) Nested: [item for row in matrix for item in row]—readable but consider itertools.chain for very wide matrices.

Production Rule: Use generator expressions when result feeds another iterator (e.g., sum(x*2 for x in stream)). Materialize only when you need random access or multiple passes.

squares = [x**2 for x in range(10)]
valid_ids = (r['id'] for r in records if r.get('status') == 'active')

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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 a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.

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