15-wrap-up.Rmd

---
layout: page
title: R for reproducible scientific analysis
subtitle: Wrapping up
minutes: 15
---

> ## Learning Objectives {.objectives}
>
> * To review the best practices for using R for
>   scientific analysis.
>

## Best practices for writing nice code

## Make code readable

The most important part of writing code is making it readable and understandable.
You want someone else to be able to pick up your code and be able to understand
what it does: more often than not this someone will be you 6 months down the line,
who will otherwise be cursing past-self.

## Documentation: tell us what and why, not how

When you first start out, your comments will often describe what a command does,
since you're still learning yourself and it can help to clarify concepts and
remind you later. However, these comments aren't particularly useful later on
when you don't remember what problem your code is trying to solve. Try to also
include comments that tell you *why* you're solving a problem, and *what* problem
that is. The *how* can come after that: it's an implementation detail you ideally
shouldn't have to worry about.

## Keep your code modular

Our recommendation is that you should separate your functions from your analysis
scripts, and store them in a separate file that you `source` when you open the R
session in your project. This approach is nice because it leaves you with an
uncluttered analysis script, and a repository of useful functions that can be
loaded into any analysis script in your project. It also lets you group related
functions together easily.

## Break down problem into bite size pieces

When you first start out, problem solving and function writing can be daunting
tasks, and hard to separate from code inexperience. Try to break down your
problem into digestible chunks and worry about the implementation details later:
keep breaking down the problem into smaller and smaller functions until you
reach a point where you can code a solution, and build back up from there.

## Know that your code is doing the right thing

Make sure to test your functions!

## Don't repeat yourself

Functions enable easy reuse within a project. If you see blocks of similar
lines of code through your project, those are usually candidates for being
moved into functions.

If your calculations are performed through a series of functions, then the
project becomes more modular and easier to change. This is especially the case
for which a particular input always gives a particular output.

## Remember to be stylish

Apply consistent style to your code.