Contains Duplicate
Detailed guide and Python implementation for the 'Contains Duplicate' problem.
1. Concept Overview
The 'Contains Duplicate' problem is a key challenge in the Arrays & Hashing section.
This implementation focuses on easy-level logic in Python.
We prioritize technical accuracy and code readability in our provided solutions.
2. Real-World Applications
3. Visual Intuition
Visualizing the logic flow for Contains Duplicate.
4. Prerequisites
5. Step-by-Step Thinking
1. Understand the problem
Read the problem statement for Contains Duplicate carefully.
2. Formulate brute force
Draft a simple iterative solution.
3. Identify inefficiency
Look for redundant calculations.
4. Optimize search path
Use hashing or sorting to speed up the process.
5. Final Implementation
Clean up the code for production standards.
Problem Statement
Given an integer array nums, return True if any value appears at least twice in the array, and return False if every element is distinct.
Write a function containsDuplicate(nums: List[int]) -> bool.
- •1 <= len(nums) <= 10^5
- •-10^9 <= nums[i] <= 10^9
Examples
nums = [1, 2, 3, 1]
True
The element 1 appears at index 0 and index 3, so there is a duplicate.
nums = [1, 2, 3, 4]
False
All elements are distinct.
nums = [1, 1, 1, 3, 3, 4, 3, 2, 4, 2]
True
Multiple elements repeat: 1, 3, 4, and 2.
Need a Hint?
Edge Cases to Watch
- Empty input structures
- Single element inputs
- Large numerical bounds
Ready to Solve?
Open the problem in PyRun's browser-based Python editor. Your code runs fully offline — no server required.
Interview Insights & Variations
Complexity Analysis Breakdown
Why Time: Directly evaluates all possibilities.
Why Space: Uses standard local memory.
Why Time: Optimized paths reduce total operations.
Why Space: May trade memory for speed.
Optimized Solution Python Code
Optimized Solution Python Code
def contains_duplicate_opt(nums):
seen = set()
for num in nums:
if num in seen:
return True
seen.add(num)
return FalseBrute Force Code (Spoiler Guarded)
Brute Force Code (Spoiler Guarded)
def contains_duplicate_brute(nums):
n = len(nums)
for i in range(n):
for j in range(i + 1, n):
if nums[i] == nums[j]:
return True
return FalseAlgorithm Pattern Checklist
When dealing with Arrays & Hashing data patterns.
Core Prerequisites
Revision Key Notes
Common Mistakes & Pitfalls
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