This is very important for efficiency: if you grow The output: output <- vector("double", length(x)).īefore you start the loop, you must always allocate sufficient spaceįor the output. Once you master the vocabulary of FP, you can solve many common iteration problems with less code, more ease, and fewer errors. Functional programming (FP) offers tools to extract out this duplicated code, so each common for loop pattern gets its own function. However, for loops are quite verbose, and require quite a bit of bookkeeping code that is duplicated for every for loop.
On the imperative side you have tools like for loops and while loops, which are a great place to start because they make iteration very explicit, so it’s obvious what’s happening. In this chapter you’ll learn about two important iteration paradigms: imperative programming and functional programming. Another tool for reducing duplication is iteration, which helps you when you need to do the same thing to multiple inputs: repeating the same operation on different columns, or on different datasets. One tool for reducing duplication is functions, which reduce duplication by identifying repeated patterns of code and extract them out into independent pieces that can be easily reused and updated. You’re likely to have fewer bugs because each line of code is Remembering to change every place that you copied-and-pasted the As your needsĬhange, you only need to make changes in one place, rather than It’s easier to respond to changes in requirements.
It’s easier to see the intent of your code, because your eyes areĭrawn to what’s different, not what stays the same. Reducing code duplication has three main benefits: In functions, we talked about how important it is to reduce duplication in your code by creating functions instead of copying-and-pasting.
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