Explain the concept of function purity in functional programming.

Function purity in functional programming refers to functions that do not have side effects and always produce the same output for the same input.

In more detail, a pure function is a function where the return value is only determined by its input values, without any observable side effects. This is how functions in mathematics work: for example, the function of adding two numbers together is pure because it will always produce the same result given the same pair of numbers.

In functional programming, side effects are seen as something to be avoided. Side effects could be anything that alters the state of the program outside the function, such as modifying a global variable, changing the value of a parameter, or performing input/output operations. These actions can make a program harder to understand and debug, because the behaviour of a function can depend on the history of the entire program, rather than just on the values of its inputs.

Pure functions, on the other hand, are much easier to reason about and test, because they don't depend on the state of the rest of the program. If a function is pure, you can be confident that it won't unexpectedly change the state of your program or interfere with other functions. This makes your code more predictable and easier to debug.

Moreover, pure functions are also easier to parallelise, because they don't need to access shared memory and can't interfere with each other. This makes them particularly useful in multi-threaded and distributed systems.

In summary, function purity is a key concept in functional programming that helps to make your code more understandable, predictable, and easier to test. It's all about reducing side effects and making sure that functions only depend on their inputs.