Search in Almost Sorted Array
Detailed guide and Python implementation for the 'Search in Almost Sorted Array' problem.
1. Concept Overview
The 'Search in Almost Sorted Array' problem is a key challenge in the Searching & Sorting 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 Search in Almost Sorted Array.
4. Prerequisites
5. Step-by-Step Thinking
1. Understand the problem
Read the problem statement for Search in Almost Sorted Array 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
Write a function search_almost_sorted(arr, target) that searches for a target value in an almost sorted array arr. An almost sorted array is one in which an element that should be at index i in a fully sorted array can instead be at index i-1, i, or i+1. Return the 0-based index of the target if found, otherwise return -1.
- •1 <= len(arr) <= 10^5
- •-10^9 <= arr[i], target <= 10^9
- •All elements in arr are unique.
Examples
search_almost_sorted([10, 3, 40, 20, 50, 80, 70], 40)
2
40 is at index 2 (which is its correct position in a fully sorted version).
search_almost_sorted([10, 3, 40, 20, 50, 80, 70], 90)
-1
90 does not exist in the array.
Need a Hint?
Edge Cases to Watch
- Empty input structures
- Single element inputs
- Large numerical bounds
Ready to Solve?
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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 search_almost_sorted_opt(arr, x):
l, r = 0, len(arr) - 1
while l <= r:
m = (l + r) // 2
if arr[m] == x: return m
if m > l and arr[m-1] == x: return m - 1
if m < r and arr[m+1] == x: return m + 1
if arr[m] > x: r = m - 2
else: l = m + 2
return -1Brute Force Code (Spoiler Guarded)
Brute Force Code (Spoiler Guarded)
def search_almost_sorted_brute(arr, x):
try: return arr.index(x)
except: return -1Algorithm Pattern Checklist
When dealing with Searching & Sorting data patterns.
Core Prerequisites
Revision Key Notes
Common Mistakes & Pitfalls
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