Have you worked with generators and decorators? Which functions have you used?

I have used generators to create memory‑efficient iterators for large data streams. For instance, I wrote a generator that reads a CSV file line by line using the csv module, yielding each row as a dictionary, which allowed me to process millions of records without loading the entire file into memory. I also employed decorators to add functionality to these generators. A common pattern is a @timed decorator that measures the execution time of a generator function, printing the duration when the generator is exhausted. Another example is a @memoize decorator that caches the results of a pure function, which can be applied to a generator that yields expensive computations. These tools together help write clean, modular, and efficient code in Python.