Python Generators Let You Process Large Files Without Exhausting RAM

Python scripts often consume excessive memory because they load entire datasets at once using methods like readlines(), which can crash processes on memory-limited servers. Generators solve this by using the yield keyword to produce one value at a time, keeping memory usage flat regardless of file size. A generator function pauses execution after each yield and resumes only when the next value is requested, making it ideal for streaming large files or datasets. Generator expressions offer a compact alternative to list comprehensions, using parentheses instead of square brackets, though both are single-use and become exhausted once fully iterated. For batch processing, Python's itertools.islice can slice generators lazily, enabling efficient chunked operations such as database inserts without loading all records into memory.