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This PR adds an implementation of the Product Except Self problem in Python.
The algorithm returns an array where each element is the product of all numbers in the input except the one at that index — without using division and in O(n) time.

Key Details:

Algorithm Used: Prefix & Suffix product technique

Time Complexity: O(n)

Space Complexity: O(1) (extra space ignored for output array)

Approach:

Compute prefix products while traversing left → right.

Track a running suffix product while traversing right → left.

Multiply prefix × suffix for each index to get the result.

Also includes an alternate version using explicit prefix/suffix arrays for clarity.

Files Added:

product_except_self.py → Main implementation with docstrings, examples, and an optional extra-space version.

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💎 Code Quality Check Results

❌ Missing Algorithm Description

These files don't explain what the algorithm does:

  • Python/algorithms/mathematical/product_except_self.py

Required: Add a description explaining the algorithm, its purpose, and how it works

📚 Quality Standards

To maintain high quality, every contribution should include:

  1. ✍️ Algorithm Description

    • Explain what the algorithm does
    • Describe the approach and methodology
    • Include use cases or applications
  2. 📊 Complexity Analysis

    • Time complexity (e.g., O(n log n))
    • Space complexity (e.g., O(n))
    • Brief explanation of why
  3. 💬 Meaningful Comments

    • Explain complex logic
    • Document function parameters
    • Add inline comments for clarity
  4. ✅ Test Cases/Examples

    • Demonstrate the code works
    • Show different input scenarios
    • Include edge cases

💡 Example Template

"""
Binary Search Algorithm

Description: Searches for a target value in a sorted array using divide-and-conquer

Time Complexity: O(log n) - halves search space each iteration
Space Complexity: O(1) - only uses constant extra space
"""

def binary_search(arr, target):
    # Initialize pointers
    left, right = 0, len(arr) - 1

    while left <= right:
        mid = (left + right) // 2

        # Check if target found
        if arr[mid] == target:
            return mid
        # Search right half
        elif arr[mid] < target:
            left = mid + 1
        # Search left half
        else:
            right = mid - 1

    return -1  # Not found

# Test cases
if __name__ == "__main__":
    test_arr = [1, 3, 5, 7, 9]
    print(binary_search(test_arr, 5))  # Output: 2
    print(binary_search(test_arr, 6))  # Output: -1

🔧 How to Fix

  1. Review each file mentioned above
  2. Add the missing documentation
  3. Push your changes
  4. The workflow will re-run automatically

💪 You've Got This!

These checks help maintain quality and make your contribution more valuable to learners. Thank you for taking the time to improve! 🙏


Quality over quantity - let's build something amazing together! 🌟

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🎉 Welcome to Hacktoberfest 2025, @MeloveGupta! 🎃

Thank you for your first contribution to our DSA repository! Here's what happens next:

🔍 Automatic Checks

  • Code Validation: Passed
  • 🧪 Compilation Tests: Passed

📋 Next Steps

🎯 Great job! Your code compiled successfully. Maintainers @Karanjot786 and @Pradeepsingh61 will review your PR soon.

🎁 What You Get

  • 🏆 Hacktoberfest Credit: This PR counts toward your 6 PR goal for exclusive T-shirt + Tree!
  • 🌟 Hall of Fame: You'll be featured in our contributors list
  • 📚 Learning: Code review feedback from experienced developers

💡 Tips for Success

  • Follow our Contributing Guidelines
  • Add comments explaining your algorithm
  • Include time/space complexity analysis
  • Test your code before submitting

Welcome to the community! 🚀

@github-actions github-actions bot requested a review from Karanjot786 October 27, 2025 06:52
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🤖 Automated PR Status

🔍 Code Validation

Passed - File naming and structure look good!

🧪 Compilation Tests

Passed - All code compiles successfully!

📋 Overall Status

🎉 Ready for Review - Your PR has passed all automated checks!
👥 Maintainers have been notified for review.


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