Module 13
Iterators, Generators, and Decorators
Learn advanced Python execution patterns and reusable behavior wrapping.
01
Iterators, Generators, and Decorators — Demand-Driven Python
Learn iterators with a Netflix analogy, generators as a water tap, and decorators as gift wrapping—then map iter(), yield, and @ to Python.
02
Python iter() and next() — Iterate One Item at a Time
Use iter() and next() to walk an iterable one item at a time, catch StopIteration, and see why iterators skip indexing and slicing.
03
Iterate list, tuple, str, set, and dict — Iterator Type Names
Map list, tuple, str, set, and dict to everyday stories—basket, queue, letters, lottery, keys—then match Python iterator type names.
04
Python Generators and yield — Values On Demand
Learn Python generators with YouTube autoplay: yield pauses, return finishes, next() resumes, kvrange patterns, and StopIteration when empty.
05
Python kvrange Generator — start, stop, step, and InputError
Learn kvrange as a bus route: start, stop, step, yield on each stop, next()+for handoff, InputError ticket, and inclusive stop vs range().
06
Python Decorators — Wrap a Function with an Inner Function
Learn Python decorators as gift wrapping: square(getval) returns calculate(), pass the function not getval(), and reuse one wrapper for logging.
07
Python @decorator Syntax — Stack square, sqrt, cube, and Text Pipelines
Learn @ decorator syntax visually: phone-plus-apps analogy, bottom-up stack order, stacked math tuple, and text pipeline.