How can I improve my binary search implementation in Python?

To directly address your concern about checking the conditions, yes, in that line you should use ">= n" instead of just "> n". It ensures that if n is in the list, your code will handle it appropriately. Also, just a small tip: using 'elif' instead of multiple 'if' statements can simplify your logic and reduce confusion about the conditions.

Dealing with duplicates in binary search isn't a problem as long as your logic is sound. If you find an instance of the value (like 5 when searching for 6), just look for more occurrences by checking the adjacent values. As for efficiency, avoid copying lists unnecessarily. Use the indices to modify your bounds instead, and remember that more code doesn't mean better performance. Each check should refine your search.

Naming your variables more descriptively would help a lot. It makes your code easier to read and debug. Instead of slicing the list and working with small sections, stick to the conventional binary search method of using indices. Also, when checking for conditions, make sure to include 'equal to n' in your logic to ensure you account for all cases. A good practice when dealing with potential duplicates is to sort and set the list first to streamline your search.

Your approach is copying parts of the list during every iteration, which can really slow things down. Instead of slicing the list, you should use indexes to track your search range. Start with a 'start' index at 0 and an 'end' index at the length of the list. Keep updating these indexes based on whether your midpoint is greater or less than n. This way, you're not creating new lists, and your search will be much faster!

First off, stop creating new arrays. It defeats the purpose of binary search, which is all about efficient searching! You should maintain upper and lower bounds as integers. When your search loop ends, you can check the bounds to find your closest value under n. If you have a valid entry, just return it; if not, make sure you're handling edge cases properly to avoid index errors.