Functional programming is a programming paradigm that emphasizes the use of pure functions to create maintainable software. In functional programming, programs are constructed by applying and composing functions. It is a declarative programming paradigm in which functions are used to the best effect for creating clean and maintainable software. Here are some key concepts associated with functional programming:
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Pure functions: These are functions that always return the same output given the same input, and have no side effects. They are deterministic mathematical functions that cannot be affected by any mutable state or other side effects.
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Immutable data: In functional programming, data is immutable, meaning it cannot be changed once it is created. This is in contrast to object-oriented programming, which uses mutable data and shared states.
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Higher-order functions: These are functions that take other functions as arguments or return functions as output. They are a key feature of functional programming and allow for the creation of more modular and reusable code.
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Recursion: This is a technique used in functional programming to perform repetitive tasks by calling a function from within itself.
Functional programming has its roots in academia, evolving from the lambda calculus, a formal system of computation based only on functions. While functional programming has historically been less popular than imperative programming, many functional languages are seeing use today in industry and education, including Haskell, JavaScript, Python, Scala, Erlang, Lisp, ML, Clojure, OCaml, Common Lisp, Racket, and F# . Functional programming is an active area of research in the field of programming language theory, with several peer-reviewed publication venues focusing on functional programming.
Functional programming offers clear benefits in certain cases, such as data analysis workflows and tasks, where it is easier to analyze, test, and maintain using the functional programming paradigm. It is also notable for its ability to efficiently parallelize pure functions, making it useful for big data and machine learning applications. Additionally, functional programming is useful for breaking down large and complex projects into simpler modules, which can be tested separately, lessening the amount of time spent on unit testing and debugging.
