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What is the difference between a set and a list in Python?

Python/Codingeasy0.4 min readPremium

**List**: Ordered; allows duplicates; indexable; O(n) lookup. **Set**: Unordered; unique elements only; hash-based; O(1) average lookup. **Why it matters**: Set membership and deduplication are fast; lists preserve order and support duplicates. **Scalability trade-off**: Sets...

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Frequency
Low
Asked at 2 companies
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
AltimetrikInfosys
Interview Pro Tip

Red Flag: Using a list for membership checks in a loop—O(n²). Pro-Move: 'I use sets for lookups and dedup; for order-preserving dedup I use dict.fromkeys(seq) or OrderedDict.'

Key Concepts Tested
python

Why This Question Matters

This easy-level Python/Coding question appears frequently in data engineering interviews at companies like Altimetrik, Infosys. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (python) will help you answer variations of this question confidently.

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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
83 words

List: Ordered; allows duplicates; indexable; O(n) lookup. Set: Unordered; unique elements only; hash-based; O(1) average lookup. Why it matters: Set membership and deduplication are fast; lists preserve order and support duplicates. Scalability trade-off: Sets use more memory per element (hash + overhead); lists are compact. For large dedup, set wins on lookup; for ordered data, list is required. Cost implication: Repeated x in list is O(n) per check; x in set is O(1). Use sets for membership and uniqueness; lists for ordered sequences.

The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations covering performance optimization and real-world examples.

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According to DataEngPrep.tech, this is one of the most frequently asked Python/Coding interview questions, reported at 2 companies. 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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