Skip to main content

Scala - Learning by understanding Functional Programming Terminology Part 2

Introduction
lambda, who named lambda lambda? why did they call it lambda, is it simple or complex?
map, what is it? why name map - map? why did they call it map, is it simple or complex?
functor, why name functor a functor? what is it? why did they call it functor is it simple or complex?
In Part 1 we have covered background on FP, why we should use, why not, where it's strength is and where it's weaknesses are. In this part (2) we are going to move on and discuss more FP terminology.
Lambda
Is lambda a function? anonymous function only? a subset of mathematics? both? let's do some research:
Anonymous functions originate in the work of Alonzo Church in his invention of the lambda calculus in 1936, before electronic computers, in which all functions are anonymous.[2] In several programming languages, anonymous functions are introduced using the keyword lambda, and anonymous functions are often referred to as lambdas or lambda abstractions. Anonymous functions have been a feature of programming languages since Lisp in 1958, and a growing number of modern programming languages support anonymous functions.
So what can we learn from this?
  1. lambda -> anonymous function
  2. lambda calculus -> give me a computation and i'll represent it in lambda calculus as anonymous functions
  3. lambda -> a greek letter alonzo church have chosen to represent those functions or binding of variables to function.
In addition. According to stackoverflow answer with 812 upvotes:
Lambda comes from the Lambda Calculus and refers to anonymous functions in programming. Why is this cool? It allows you to write quick throw away functions without naming them. It also provides a nice way to write closures. With that power you can do things like this.
So to sum up
  1. lambda -> anonymous function.
  2. lambda calculus -> computations expressed as math functions.
  3. lambda -> alonzo church represents a function with this greek letter.
map
If you tell a non FP developer, "hey I just wrote a function and I named it map what do you think it's doing?". He might answer, "maybe something with google maps?" . Well actually you could name map traverse or something like that the thing is that if FP is closely related to functional programming, and functional programming is closely related to math then we had better stick with the mathematical terms as awuful and non descriptive as they are.
In our case map is actually a good name, it's mapping from one item on our source structure to another item in our destination structure. you cannot really deduce from the name only that the destination structure has the same shape as the source structure, but if you talk to mathematician he can deduce it, and we love mathematician's deductions, we are wannabe FP after all aren't we? The great book Scala Design Patterns By Ivan Nikolov says:
Following common conventions would make things much simpler
and this is exactly what the map name is all about.
Do you write loops? you do this all day right? Do you write loops that convert each item in a list into another? well map is exactly that, nothing special here, you do this all day.
map - are you iterating something and applying a function to ieach item?. are you looping too much? maybe all the stuff you are looping on can inherit from something? let them inherit from map.
Martin Fowler in his great map article has a great image for map:

wikipedia mathematical declaration of map is:
In many programming languages, map is the name of a higher-order function that applies a given function to each element of a list, returning a list of results in the same order. It is often called apply-to-all when considered in functional form.
well so we have map which iterates something and applies a function but wikipedia says:
map for scala list:
final def map[B](f: (A)  B): List[B]
First question comes to mind, we have just defined map to take a type parameter [B] but what about type parameter [A] why didn't we define it also?
Well, if you look at the definition of List trait itself you would see that [A] is the type of the list, so it's already defined.
to define map in haskell on list which is denoted by [] , you do the below which let's you see the whole picture in a very compact way.
map :: (a -> b) -> [a] -> [b]
so we have an input function from a to b and we transform list [a] to list [b] now you see why haskell is more compact and much easy to lern FP concepts, I told you. But once you get the hang of scala it's rather good also.
Now in almost all languages you can see the same thing, transforming from one kind of element to another and the shape stays the same for you.. for exmaple in ruby
[1,2,3,4].map {|i| i + 1}
# => [2, 3, 4, 5]
in closure:
(map #(+ % 1) [1 2 3 4])
;; => (2 3 4 5)
So we just take each element apply the map higher order function which takes another function, and it does it's mapping over the list and returns us a new list or the same object of the same type.
Conclusion
I think we have covered the basics terms here, maplambda, which gives us the basis for functional programming, we have seen like our first higher order function map which takes another function, which is pretty awesome, in the next post we would continue to functor and friends.

Comments

Popular posts from this blog

Functional Programming in Scala for Working Class OOP Java Programmers - Part 1

Introduction Have you ever been to a scala conf and told yourself "I have no idea what this guy talks about?" did you look nervously around and see all people smiling saying "yeah that's obvious " only to get you even more nervous? . If so this post is for you, otherwise just skip it, you already know fp in scala ;) This post is optimistic, although I'm going to say functional programming in scala is not easy, our target is to understand it, so bare with me. Let's face the truth functional programmin in scala is difficult if is difficult if you are just another working class programmer coming mainly from java background. If you came from haskell background then hell it's easy. If you come from heavy math background then hell yes it's easy. But if you are a standard working class java backend engineer with previous OOP design background then hell yeah it's difficult. Scala and Design Patterns An interesting point of view on scala, is

Alternatives to Using UUIDs

  Alternatives to Using UUIDs UUIDs are valuable for several reasons: Global Uniqueness : UUIDs are designed to be globally unique across systems, ensuring that no two identifiers collide unintentionally. This property is crucial for distributed systems, databases, and scenarios where data needs to be uniquely identified regardless of location or time. Standardization : UUIDs adhere to well-defined formats (such as UUIDv4) and are widely supported by various programming languages and platforms. This consistency simplifies interoperability and data exchange. High Collision Resistance : The probability of generating duplicate UUIDs is extremely low due to the combination of timestamp, random bits, and other factors. This collision resistance is essential for avoiding data corruption. However, there are situations where UUIDs may not be the optimal choice: Length and Readability : UUIDs are lengthy (typically 36 characters in their canonical form) and may not be human-readable. In URLs,

Dev OnCall Patterns

Introduction Being On-Call is not easy. So does writing software. Being On-Call is not just a magic solution, anyone who has been On-Call can tell you that, it's a stressful, you could be woken up at the middle of the night, and be undress stress, there are way's to mitigate that. White having software developers as On-Calls has its benefits, in order to preserve the benefits you should take special measurements in order to mitigate the stress and lack of sleep missing work-life balance that comes along with it. Many software developers can tell you that even if they were not being contacted the thought of being available 24/7 had its toll on them. But on the contrary a software developer who is an On-Call's gains many insights into troubleshooting, responsibility and deeper understanding of the code that he and his peers wrote. Being an On-Call all has become a natural part of software development. Please note I do not call software development software engineering b