The Five Kinds of Python Functions
summary
Clear claims and runnable code: five concrete function types are demonstrated with working examples — diesel-engine RPM case study (a naive model then a fitted transform that still needs correction), map/filter/zip laziness showing how Python 3’s lazy built-ins and range avoid huge intermediates, and memoization with lru_cache plus callable objects and generator use (Syracuse/Collatz generator) to scale to large inputs only when cached. Tools: builtins, itertools, functools; performance tradeoffs and when things actually break are shown.
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chapters (14)
- 0:00Introduction
- 5:22Breaking mathematical purity
- 6:05Basic functions and docstrings
- 12:56Higher order functions
- 16:27Mapping with map and comprehensions
- 23:11Lazy evaluation with iterators
- 28:28Combining functions with zip
- 37:55Function wrappers for methods
- 41:31Lambda functions
- 48:54Callable objects and memoization
- 57:10Generator functions
- 1:02:35Recursive generators
- 1:08:37Yield versus return
- 1:12:28Summary
