Take lazy evaluation, which is the ability to delay the evaluation of an expression until its value is needed. And when you can be sure your functions won’t have any unintended side effects, it opens the door to more powerful techniques. There’s a hidden power in composing pure functions into higher-order functions-you create safe, modular code by default. Common examples of higher-order functions include filter, map, and reduce. Higher-order functions (sometimes called functionals) take in functions as arguments and may return functions as results. This opens the door for higher-order functions, which receive functions as inputs and produce functions as outputs. First-class functions can be passed as arguments and returned from functions like any other data type. In the world of programming languages, designating a programming feature with first-class citizenship means that you can perform on that feature all the operations generally available to other entities in that language. And it’s this natural affinity for algorithms that makes functional programming popular for machine learning and AI. The mathematical predictability, independence, and modularity of pure functions makes them sturdy building blocks for computer algorithms. Always return the same output for a given identical input argumentĪs true mathematical analogs, you can apply all the rules of mathematics to pure functions (e.g., the associative property).Be deterministic-have no dependencies on out-of-scope variables.Pure functions are the computational analog to a mathematical function. Instead the output will return a new value that reflects the work done. In practice this means that when a function receives an input argument, it does not change that argument. In functional programming all data is immutable. Let’s take a closer look at the programming features that make this a viable programming paradigm. In functional programming, functions serve as the basic building blocks with which you compose computer programs.
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