Learn Big O notation explained in plain English without complex math. Discover how algorithm efficiency scales with data size and why it matters for programming performance.
Learn what O(log n) time complexity means in Big O notation. Discover why logarithmic algorithms are highly efficient, see practical examples like binary search, and understand how to identify logarithmic time complexity in your code.
Discover why Python's range objects perform lightning-fast membership tests even with astronomical numbers. Learn about the mathematical optimizations that make range() operations O(1) time complexity.