I think "purely functional, not a single re-assigned variable" often introduces significant extra complexity, when Ruby is a language that embraces both functional and imperative programming.

One of my favorite aspects of Ruby is how easy it is to write in a functional programming style, and including the scan operation would expand the number of use cases covered by functional methods.

If you like the functional style of programming, though, you’ll find a lot more facilities for it in Rust, because Rust has a lot more facilities than Go in general.

Another option is the use the functional library Ramda, while the syntax may be a bit different from the Ruby and Pure JS version, I find it to be more declarive: list = [null, "say", "kenglish", "co", null] R.reject(R.isNil, list) // return new array [ 'say', 'kenglish', 'co' ]

We can also define these properties for data types that we do not control, for example providing a custom way of hashing a data type implemented by someone else

However, there is a definite trade off in these three snippets. The first one is overly specific but is understandable to any Scala programmer. The last one is beautiful and elegant if you understand the necessary concepts but incomprehensible otherwise.

ZIO ecosystem libraries generally do not directly expose any functional abstractions but still expose a highly compositional interface because their design is based on algebraic properties like this. Users don't have to learn about these abstractions unless they want to, they just get to benefit from better library design.

The keyword data tells us this is an inductive definition, that is, that we are defining a new datatype with constructors

Adding Object Oriented Principles (OOP) to a functional codebase adds yet another way of writing code, reducing consistency and clarity.

you want to pass a function as an argument to higher-order functions

Put another way, it’s become clear to me over time that the problems with data races and memory safety arise when you have both aliasing and mutability. The functional approach to solving this problem is to remove mutability. Rust’s approach would be to remove aliasing. This gives us a story to tell and helps to set us apart. A note on terminology: I think we should refer to aliasing as sharing. In the past, we’ve avoided this because of its multithreaded connotations. However, if/when we implement the data parallelism plans I have proposed, then this connotation is not at all inappropriate. In fact, given the close relationship between memory safety and data races, I actually want to promote this connotation.

multi-paradigm: functional, imperative

in functional programming, the terms "conditional expression" or "conditional construct" are preferred, because these terms all have distinct meanings

But now, you can do the same thing in functional style!

Brings functional programming to Python land

The latter are important examples which usually also exist in "purely" functional programming languages.

Railway Oriented Programming comes from functional programming, so it is tightly related to the usual FP concepts like monads, composition, and many others.

This stuff is intoxicating once you get into it.

So every program starts in the IO monad. From here you can get any input you need, call into relatively "pure" code with the inputs, and then output the result in some way. The reverse does not work. You cannot call into IO code from pure code like you can call into a Maybe function from pure code.

Purely functional programming may also be defined by forbidding state changes and mutable data.

purely functional programming usually designates a programming paradigm—a style of building the structure and elements of computer programs—that treats all computation as the evaluation of mathematical functions.

Purely functional data structures are persistent. Persistency is required for functional programming; without it, the same computation could return different results.

Whatever language or default programming paradigm a developer uses, following the monad pattern brings many of the benefits of purely functional programming.

To emphasize how Just acts on the underlying value by wrapping it, it can be redefined as a function too, called eta for now

Research beginning in the late 1980s and early 1990s established that monads could bring seemingly disparate computer-science problems under a unified, functional model.

The central ideas of this design pattern closely mirror the semantics of first-class functions and higher-order functions in functional programming languages. Specifically, the invoker object is a higher-order function of which the command object is a first-class argument.

“Functional programming language” is not a clearly defined term. From the various properties that are typically associated with functional programming I only want to focus on one: “Immutability” and referential transparency.

The changes we needed to make to main to reassign post mean that this implementation doesn’t quite follow the object-oriented state pattern anymore: the transformations between the states are no longer encapsulated entirely within the Post implementation. However, our gain is that invalid states are now impossible because of the type system and the type checking that happens at compile time! This ensures that certain bugs, such as display of the content of an unpublished post, will be discovered before they make it to production.

{ item1: "hello", item2: "world" }

Note: The examples in Listings 10-17, 10-18, and 10-24 declare variables without giving them an initial value, so the variable name exists in the outer scope. At first glance, this might appear to be in conflict with Rust’s having no null values. However, if we try to use a variable before giving it a value, we’ll get a compile-time error, which shows that Rust indeed does not allow null values.

My frustration is mainly from Svelte's choices that are very un-JavaScript-like. It doesn't have to be "like React/Vue". React is React because it doesn't restrict what you can do with JavaScript for the most part. It's just common FP practice to fold/map.

In practice, functional programming is all about hiding for loops, which are abstracted away by the mapper functions that automate the iteration.

The lodash/fp module promotes a more functional programming (FP) friendly style by exporting an instance of lodash with its methods wrapped to produce immutable auto-curried iteratee-first data-last methods.

All validators can be used independently. Inspried by functional programming paradigm, all built in validators are just functions.

FormValidation.validators.creditCard().validate({

FormValidation.formValidation(formElement

functional-dominant hybrid style of programming

A paradigm is a model or pattern. In JavaScript, there are a number of popular paradigms including object-oriented programming (OOP) and functional programming (FP). Paradigms are more important than is sometimes recognized. They help form mental models for solving problems. Becoming well-versed in the principles of a given paradigm can help accelerate development by providing mental shortcuts for solving the challenges that arise while building applications. They can also help produce higher quality software.

We wanted a library designed specifically for a functional programming style, one that makes it easy to create functional pipelines, one that never mutates user data.

Nix is a purely functional package manager. This means that it treats packages like values in purely functional programming languages such as Haskell — they are built by functions that don’t have side-effects, and they never change after they have been built.

We might have some dirty mutable objects for performance - but our high-level API should be purely functional. You should be able to follow the React model of modelling your UI as a pure function of application state -> UI.

the abstraction I wished to have was a sort of a pure functional Vim, completely decoupled from terminal UI - where 'vim' is a function of (editor state, input) => (new editor state)

after the terminal operation of the stream pipeline commences.

That is using a specific tool for a specific use case. You don’t actually have a table view of your data. Once it’s in a table, man, you’re good. That is the modeling. A sequel database table, you have this amazing high-level language for doing all sorts of cool operations with it.To turn this into some class hierarchy, it’s almost criminal. There, I said it. It’s like you’re throwing away the power that you have.

(== 10)

Since Clojure uses the Java calling conventions, it cannot, and does not, make the same tail call optimization guarantees. Instead, it provides the recur special operator, which does constant-space recursive looping by rebinding and jumping to the nearest enclosing loop or function frame. While not as general as tail-call-optimization, it allows most of the same elegant constructs, and offers the advantage of checking that calls to recur can only happen in a tail position.

Keeping unpure functions clearly named and organized in such a way that they can be easily identified versus pure functions is a common goal of modularizing and organizing Scala applications.

Much like a Unix power user will compose multiple single-purpose tools into a complex piped command, a functional programmer will combine single-purpose function invocations into chains of operations (think Map/Reduce).