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I focused on one at at time, making steady

This week I've been deep in an epic coding session, worthy of the rousing soundtrack you get in Hollywood hacker movies. It's fun. And something interesting: In working on this application (doesn't matter what it is), I was stuck on an important subsystem. It had to do with how my application integrates with a complex vendor API - but again, that detail doesn't matter. What matters is that, when I started, I could see four possible ways to implement it. And it wasn't clear which was best. So I invested a good chunk of time spec'ing them all out. Reasoning how each would fit in the app's architecture... And after, I still couldn't tell if ANY of them would work. Or all of them. Or only one. (Which one)? As you get better at coding, you encounter dilemmas like this less often. Like a master chess player, you get better at "pattern matching" increasingly complex coding situations, and able to reckon which choice has the best chance of work
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programming languages offer a good utility

p { margin-bottom: 0.25cm; line-height: 120%; }a:link { } The purpose of this article is to make you understand the role of two programming languages namely Python and Java, such that making a choice would be easier for you. Before we move on to the comparison between these two languages, we will first take a look at the basic characteristics of both Java vs Python. * Java: Java happens to be a high-level programming language. It is based on the OOPS methodology. The "write once, run anywhere" design philosophy adopted by Java makes it unique in nature. In addition, it is extremely scalable making it the numero-uno choice for enterprise level development. Read More: Career in Java: * Python: Python on the other hand is a high level, interpreted programming language with easy to understand and use syntax. Python adopts the design philosophy that enables writing less code for the same measure of work along with easy readability, when contrasted with other programming l
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enhancing readability is a never-ending process

Have you ever looked at code you wrote six months or three years ago, and ask yourself, "what in the world was I thinking?" We all have. Pondering my own Pythonic abominations, I've noticed a few trends. I don't want to say they're my "favorites", but I seem to do them a lot: Overly Complex Algorithms This is a big one. I look at the code I wrote - the classes, modules, etc. - and can see it works just fine. But it could be WAY simpler. Simpler often means more readable, more maintainable, and - surprisingly often - less fragile. I mean, the code still has to work correctly. But correct, simple code is nearly always better than correct, complex code. When I step away for a while, and look at the code base again later with fresh eyes, often I see a much cleaner solution. "Accidentally Working" Code This one is kind of funny. Reading the code, I can see what I was thinking at the time. And it actually works - meaning, it meets the requi
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