How I ended up to tries today?
Well, I started my day motivated for week 3 on Coursera! During the lesson on class hierarchies, what actually got my attention were class extensions. My train of thought had to question and research many terms, so I will try to sum it all up here in this very short post.
How-to-do-it vs Why-use-it
Although I have used class extensions before, sometimes is good to get back to things and pay attention to the detail. Although I didn’t get something super new on the topic, somehow I feel like I am finally getting the point of “functional” and “immutability”, and really understanding more on data structures; what opened my eyes was persistent data structures, which were referred as the cornerstone of scaling functional programming in the video. And what really made my day, was this video on tries. But first things first…
Persistent? What are tries? Why do we care about immutability? How many times a day do pandas poop?
I want to avoid the “googlish-theoritical” stuff, so:
A data structure is persistent if, when changed, can still preserve its previous version brain exploded
A trie ( pronounced like try) is a persistent, concurrent, tree-like data structure.
They can be used for efficient information re trie val and common use case are dictionaries for predictive text (e.g. google search).
Tries vs Hash Tables:They need no hash function, so no key collisions. Every key is unique as every path to a value is unique.
But it comes with a price -> sometimes search can get slow.
And last but not least… Pandas can poop up to 40 times a day #factOfTheDay
I know that this is not a fascinating post on tries, but I am still trieng… 😅