"Always code as if the guy who ends up maintaining your code will be a violent psychopath who knows where you live."
Here are 6 coding practices that I've adopted in the past 10 years to ensure that my future self has fewer sins to forgive.
Any codebase is read a lot more than it is written. Code with consistent formatting is easily readable and comprehensible for everyone in the team. Standard formatting ensures that your eye, and your subconscious, can look for variables, braces, functions, etc seamlessly. Golang does a great job by providing the gofmt command in the standard library. This ended all formatting discussions that come up so often in code reviews in the Golang community.
DRY (Don't Repeat Yourself) is almost a mantra for developers. But if applied indiscriminately, it leads to abstract code that’s hard to read & understand. It also stops different parts of the code to evolve to their full potential. Do not follow the DRY principle blindly.
It is a good idea to copy-paste the same function a minimum two times in the codebase. Only when you see the same requirement a third time, should you refactor the code and apply DRY. Doing this ensures that you are not prematurely assuming that two problems that looked the same initially, are still going to remain the same after a period of time. When you come across a similar requirement a third time, you have some data on what parts of the code are common. You also have three instances of repeated code to create a good abstraction.
Practice debugging code on your local machine via logs instead of a debugger. Debugging on your local machine ensures that logs are added at the right place. This, in turn, makes sure that you can debug production issues quickly because you would have gone through this cycle on your local machine before. Remember to not get too excited and add unnecessary logs everywhere. It will clutter your log file in production.
Too much logging == no logging.
A primary goal of code optimisation is to improve performance. More often than not, performance issues are not where you think they are. Always benchmark your code before starting to optimize for performance. Without benchmarking, how will you ever know whether the code changes you make have any real impact on efficiency or not? Premature optimization, especially micro-optimization, is not a good idea because you don’t know whether you are working on removing a performance bottle-neck or not.
As a corollary, this doesn't give you the license to code like the wild west. Don't get the computer to do work that it doesn’t need to do just because you got lazy and didn't think of the most efficient way of solving a problem.
Don’t complicate the codebase with features that no user has asked for. This is a problem you need to avoid in early product lifecycles. Startup teams tend to assume that building more features will help them find product-market fit faster. This is an anti-pattern. Adding unnecessary features makes the code harder to read & debug. When new developers come on board, they will find it difficult to differentiate important code paths from the ones that were added on a whim. Eventually this technical debt slows the entire team down.
Even if it’s a one-wo/man show, a CI/CD pipeline reduces the overhead of remembering (& doing) the build & deployment of a particular codebase. The common assumption is that CI/CD pipelines are important only in teams that are pushing a lot of code into production every day. In my experience, CI/CD pipelines are even more important for codebases that are rarely touched because you won’t remember how & where the code was deployed. This is especially true if you are updating the code only once a year. Plus, having a CI/CD pipeline ensures that you have a version-controlled script telling you exactly what you were thinking X months ago.
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