Using filter() for Selection

Filter operations are lazy by default in Python 3. The filter object only computes results as you iterate through it. This means you can filter a massive dataset without loading everything into memory at once. Each element is tested and yielded one at a time. This lazy evaluation is crucial for processing data that does not fit in memory, a common situation in data engineering. Basic filter() Usage The predicate function must return a truthy or falsy value. Elements where the predicate returns True are kept; others are discarded. Like map(), filter() returns an iterator, so we wrap in list() to see all results. Python's truthy and falsy evaluation makes predicates flexible. Your function does not need to return exactly True or False. Returning a non-empty string, a non-zero number, or any