You've decided it's time to learn how to code, so the next step is to find some resources and start programming your first masterpiece. Hopefully, you've decided that my advice on which language to choose was useful, and you're going to start with either Python, Go or PowerShell. There are a number of ways to learn, and a number of approaches to take. In this post, I'll share my thoughts on different ways to achieve success, and I'll link to some learning resources that I feel are pretty good.
How I Began Coding
When I was a young lad, my first foray into programming was using Sinclair BASIC on a Sinclair ZX81 (which in the United States was sold as the Timex Sinclair 1000). BASIC was the only language available on that particular powerhouse of computing excellence, so my options were limited. I continued by using BBC BASIC on the Acorn BBC Micro Model B, where I learned to use functions and procedures to avoid repetition of code. On the PC I got interested in what could be accomplished by scripting in MS-DOS. On Macintosh, I rediscovered a little bit of C (via MPW). When I was finally introduced to NetBSD, things got interesting.
I wanted to automate activities that manipulated text files, and UNIX is just an amazing platform for that. I learned to edit text in vi (aka vim, these days) because it was one tool that I could pretty much guarantee was installed on every installation I got my hands on. I began writing shell scripts which looped around calling various instantiations of text processing utilities like grep, sed, awk, sort, uniq, fmt and more, just to get the results I wanted. I found that often, awk was the only tool with the power to extract and process the data I needed, so I ended up writing more and more little awk scripts to fill in. To be honest, some of the pipelines I was creating for my poor old text files were tricky at best. Finally, somebody with more experience than me looked at it and said, Have you considered doing this in Perl instead?
Challenge accepted! At that point, my mission became to create the same functionality in Perl as I had created from my shell scripts. Once I did so, I never looked back. Those and other scripts that I wrote at the time are still running. Periodically, I may go back and refactor some code, or extract it into a module so I can use the same code in multiple related scripts, but I have fully converted to using a proper scripting language, leaving shell scripts to history.
How I Learned Perl
With my extensive experience with BASIC and my shallow knowledge of C, I was not prepared to take on Perl. I knew what strings and arrays were, but what was a hash? I'd heard of references but didn't really understand them. In the end—and try not to laugh because this was in the very early days of the internet—I bought a book (Learn Perl in 21 Days), and started reading. As I learned something, I'd try it in a script, I'd play with it, and I'd keep using it until I found a problem it didn't solve. Then back to the book, and I'd continue. I used the book as more as a reference than I did as a true training guide (I don't think I read much beyond about Day 10 in a single stretch; after that was on an as-needed basis).
The point is, I did not learn Perl by working through a series of 100 exercises on a website. Nor did I learn Perl by reading through the 21 Days book, and then the ubiquitous Camel book. I can't learn by reading theory and then applying it. And in any case, I didn't necessarily want to learn Perl as such; what I really wanted was to solve my text processing problems at that time. And then as new problems arose, I would use Perl to solve those, and if I found something I didn't now how to do, I'd go back to the books as a reference to find out what the language could do for me. As a result, I did not always do things the most efficient way, and I look back at my early code and think, Oh, yuck. If I did that now I'd take a completely different approach. But that's okay, because learning means getting better over time and — this is the real kicker — my scripts worked. This might matter more if I were writing code to be used in a high-performance environment where every millisecond counts, but for my purposes, "It works" was more than enough for me to feel that I had met my goals.
In my research, I stumbled across a great video which put all of that more succinctly than I did:
In the video, (spoiler alert!) CheersKevin states that you don't want to learn a language; you want to solve problems, and that's exactly it. My attitude is that I need to learn enough about a language to be dangerous, and over time I will hone that skill so that I'm dangerous in the right direction, but my focus has always been on producing an end product that satisfies me in some way. To that end, I simply cannot sit through 30 progressive exercises teaching me to program a poker game simulator bit by bit. I don't want to play poker; I don't have any motivation to engage with the problem.
A Few Basics
Having said that you don't want to learn a language, it is nonetheless important to understand the ways in which data can be stored and some basic code structure. Here are a few things I believe it's important to understand as you start programming, regardless of which language you choose to learn:
a way to store data by associating a unique key to a value, e.g. the key might be "red", and the value might be the html hex value for that color, "#ff0000". Many key/value pairs can be stored in the same object, e.g. colors=("red"=>"#ff0000", "blue"=>"#00ff00", "green"=>"#0000ff")
the number (or index) of the first element in a list (array) is zero; the second element is 1, and so on. Each element in a list is typically accessed by putting the index (the position in the list) in square brackets after the name. In our previously defined array colors=("red", "blue", "green") the elements in the list are colors = "red", colors="blue", and colors="green".
a way to group a set of commands together so that the whole block can be called with a single command. This avoids repetition within the code.
objects, properties and methods
an object can have properties (which are information about, or characteristics of, the object), and methods (which are actually properties which execute a function when called). The properties and methods are usually accessed using dot notation. For example, I might have an object mycircle which has a property called radius; this would be accessed as mycircle.radius. I could then have a method called area which will calculate the area of the circle (πr²) based on the current value of mycircle.radius; the result would access as mycircle.area() where parentheses are conventionally used to indicate that this is a method rather than a property.
All three languages here (and indeed most other modern languages) use data types and structures like the above to store and access information. It's, therefore, important to have just a basic understanding before diving in too far. This is in some ways the same logic as gaining an understanding of IP before trying to configure a router; each router may have a different configuration syntax for routing protocols and IP addresses, but they're all fundamentally configuring IP ... so it's important to understand IP!
Some Training Resources
This section is really the impossible part, because we all learn things in different ways, at different speeds, and have different tolerances. However, I will share some resource which either I have personally found useful, or that others have recommended as being among the best:
The last course is a great example of learning in order to accomplish a goal, although perhaps only useful to network engineers as the title suggests. Kirk is the author of the NetMiko Python Library and uses it in his course to allow new programmers to jump straight into connecting to network devices, extracting information and executing commands.
Go is not, as I think I indicated previously, a good language for a total beginner. However, if you have some experience of programming, these resources will get you going fairly quickly:
As a relatively new, and still changing, language, Go does not have a wealth of training resources available. However, there is a strong community supporting it, and the online documentation is a good resource even though it's more a statement of fact than a learning experience.
Satisfaction with learning resources is so subjective, it's hard to be sure if I'm offering a helpful list or not, but I've tried to recommend courses which have a reputation for being good for complete beginners. Whether these resources appeal may depend on your learning style and your tolerance for repetition. Additionally, if you have previous programming experience you may find that they move too slowly or are too low level; that's okay because there are other resources out there aimed at people with more experience. There are many resources I haven't mentioned which you may think are amazing, and if so I would encourage you to share those in the comments because if it worked for you, it will almost certainly work for somebody else where other resources will fail.
Coincidentally a few days ago I was listening to Scott Lowe's Full Stack Journey podcast (now part of the Packet Pushers network), and as he interviewed Brent Salisbury in Episode 4, Brent talked about those lucky people who can simply read a book about a technology (or in this case a programming language) and understand it, but his own learning style requires a lot of hands-on, and the repetition is what drills home his learning. Those two categories of people are going to succeed in quite different ways.
Since it's fresh in my mind, I'd also like to recommend listening to Episode 8 with Ivan Pepelnjak. As I listened, I realized that Ivan had stolen many of the things I wanted to say, and said them to Scott late in 2016. In the spirit that everything old is new again, I'll leave you with some of the axioms from RFC1925 (The Twelve Networking Truths) (one of Ivan's favorites) seem oddly relevant to this post, and to the art of of programming too:
(6a) (corollary). It is always possible to add another level of indirection. (8) It is more complicated than you think. (9) For all resources, whatever it is, you need more. (10) One size never fits all. (11) Every old idea will be proposed again with a different name and a different presentation, regardless of whether it works. (11a) (corollary). See rule 6a.
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