Master Binary Search in C (and Python) for Faster Code

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When you're working with sorted data, linear search is like walking down a hallway checking every door. Binary search? It's like teleporting to the middle and asking: higher or lower?

This week, we're diving into how binary search works, when to use it, and how to implement it in both C and Python. It's a staple in coding interviews, game dev, systems programming, and real-world apps like search engines, databases, and file systems.

How It Works

Binary search divides a sorted list in half, compares your target value with the middle element, and narrows the search range based on the result. This continues until the target is found or the range is empty.

It runs in O(log n) time, dramatically faster than O(n) linear search for large datasets.

def binary_search(arr, target):
    left, right = 0, len(arr) - 1
    
    while left <= right:
        mid = (left + right) // 2
        if arr[mid] == target:
            return mid  # Found
        elif arr[mid] < target:
            left = mid + 1
        else:
            right = mid - 1
    
    return -1  # Not found

Not comfortable with Python? It’s easy to get started. Here’s how to learn Python.

And note how it looks in C:

int binarySearch(int arr[], int size, int target) {
    int left = 0, right = size - 1;
    
    while (left <= right) {
        int mid = left + (right - left) / 2;  // avoid overflow
        if (arr[mid] == target)
            return mid;
        else if (arr[mid] < target)
            left = mid + 1;
        else
            right = mid - 1;
    }
    
    return -1;
}

Binary search is the fastest way to search sorted data. If your data isn't sorted, sort it first—or use a different approach. For everything from logins to file lookup, binary search is a key part of your algorithm toolkit.

Common Use Cases:

• Searching large sorted arrays or lists

• Index lookups in databases

• Log file analysis

• Efficient condition checks (e.g., finding the smallest/biggest index that satisfies a condition)

• Real-time applications with strict speed requirements

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