# memoized recursion

Published articles for memoized recursion.

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## A Spoonful of Python (and Dynamic Programming)

DevFeed: [A Spoonful of Python (and Dynamic Programming)](<https://devfeed.tech/articles/a-spoonful-of-python-and-dynamic-programming-40254.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2012/01/12/a-spoonful-of-python/>)

Published: 2012-01-12T23:11:26Z

Content type: tutorial

Language: en

Sources: [Jeremy Kun](<https://devfeed.tech/sources/jeremy-kun.md>)

Topics: [Python](<https://devfeed.tech/topics/python.md>), [Programming](<https://devfeed.tech/topics/programming.md>), [Algorithm](<https://devfeed.tech/topics/algorithm.md>)

Tags: [dynamic-programming](<https://devfeed.tech/tags/dynamic-programming.md>), [fibonacci](<https://devfeed.tech/tags/fibonacci.md>), [memoized-recursion](<https://devfeed.tech/tags/memoized-recursion.md>), [primer](<https://devfeed.tech/tags/primer.md>), [python](<https://devfeed.tech/tags/python.md>), [recursion](<https://devfeed.tech/tags/recursion.md>)

### AI overview

A Python primer covering built-in types such as lists, tuples, and dictionaries, with examples involving Fibonacci numbers and optimal coin change. It introduces dynamic programming and compares inefficient recursive and recursionless approaches.

### Source excerpt

This primer is a third look at Python, and is admittedly selective in which features we investigate (for instance, we don't use classes, as in our second primer on random psychedelic images). We do assume some familiarity with the syntax and basic concepts of the language. For a first primer on Python, see A Dash of Python. We'll investigate some of Python's useful built-in types, including lists, tuples, and dictionaries, and we use them to computing Fibonacci numbers and "optimal" coin change.