Data Structures: Heaps!
Today we finish our Data Structures series! We have one more structure to look at, and that is the Heap! This structure often gets overlooked when people think of data structures, since its role is a bit narrow and specific. You can look at the full rundown on the series page here. If you've missed any of our previous structure summaries, here's the list:
That's all for our Data Structures series! The blog will be back soon with more content!
Data Structures: Sequences!
Haskell's basic "list" type works like a singly linked list. However, the lack of access to elements at the back means it isn't useful for a lot of algorithms. A double ended linked list (AKA a queue) allows a lot more flexibility.
In Haskell, we can get this double-ended behavior with the Sequence type. This type works like lists in some ways, but it has a lot of unique operators and mechanics. So it's worth reading up on it here in the latest part of our Data Structures Series. Here's a quick review of the series so far:
We have one more structure to look at next time, so this series is going to bleed into August a bit, so make sure to come back next week!
Data Structures: Vectors!
Last week we started looking at less common Haskell data structures, starting with Arrays. Today we're taking one step further and looking at Vectors. These combine some of the performance mechanics of arrays with the API of lists. Many operations are quite a bit faster than you can find with lists.
For a full review, here's a list of the structures we've covered so far:
We've got two more structures coming up, so stay tuned!
Data Structures: Hash Maps!
Throughout this month we've been exploring the basics of many different data structures in Haskell. I started out with a general process called 10 Steps for understanding Data Structures in Haskell. And I've now applied that process to four common structures in Haskell:
Today we're taking the next logical step in the progression and looking at Hash Maps. Starting later this week, we'll start looking as lesser-known Haskell structures that don't fit some of the common patterns we've been seeing so far! So keep an eye on this blog page as well as the Data Structures Series page!
Data Structures: Hash Sets!
Last week I presented 10 Steps for understanding Data Structures in Haskell. In our new Data Structures Series you'll be able to see these steps applied to all the different data structures we can use in Haskell.
Today, marks the fourth article in this series, describing the Hash Set data type. If you missed the last few parts, you can also head to the Series Page and take a look!
Data Structures: Maps!
Last week I presented 10 Steps for understanding Data Structures in Haskell. In our new Data Structures Series you'll be able to see these steps applied to all the different data structures we can use in Haskell.
Today, we're debuting the third part of the series, looking at the Map data type. If you missed the last couple parts, you can also head to the Series Page and take a look!
10 Steps to Understanding Data Structures in Haskell
Last year I completed Advent of Code, which presented a lot of interesting algorithmic challenges. One thing these problems really forced me to do was focus more clearly on using appropriate data structures, often going beyond the basics.
And looking back on that, it occurred to me that I hadn't really seen many tutorials on Haskell structures beyond lists and maps. Nor in fact, had I thought to write any myself! I've touched on sequences and arrays, but usually in the context of another topic, rather than focusing on the structure itself.
So after thinking about it, I decided it seemed worthwhile to start doing some material providing an overview on all the different structures you can use in Haskell. So data structures will be our "blog topic" starting in this month of July, and probably actually going into August. I'll be adding these overviews in a permanent series, so each blog post over the next few Mondays and Thursdays will link to the newest installment in that series.
But even beyond providing a basic overview of each type, I thought it would be helpful to come up with a process for learning new data structures - a process I could apply to learning any structure in any langugage. Going to the relevant API page can always be a little overwhelming. Where do you start? Which functions do you actually need?
So I made a list of the 10 steps you should take when learning the API for a data structure in a new language. The first of these have to do with reminding yourself what the structure is used for. Then you get down to the most important actions to get yourself started using that structure in code.
The 10 Steps
- What operations does it support most efficiently? (What is it good at?)
- What is it not as good at?
- How many parameters does the type use and what are their constraints.
- How do I initialize the structure?
- How do I get the size of the structure?
- How do I add items to the structure?
- How do I access (or get) elements from the structure?
- If possible, how do I delete elements from the structure?
- How do I combine two of these structures?
- How should I import the functions of this structure?
Each part of the series will run through these steps for a new structure, focusing on the basic API functions you'll need to know. To see my first try at using this approach where I go over the basic list type, head over to the first part of the series! As I update the series with more advanced structures I'll add more links to this post.
If you want to quickly see all the APIs for the structures we'll be covering, head to our eBooks page and download the FREE Data Structures at a Glance eBook!
