Also, make sure to avoid caffeinated drinks in the afternoon so that your body can get rid of the caffeine until bedtime

Being on your phone or laptop late at night, keeps your brain alert and harms the quality of your sleep. Even though watching your favorite movie or typing a few messages might not seem like a big deal, that’s what it is.

Late-night snacks or a big, delicious dinner can be pretty tempting after a long and exhausting day. And even though there’s nothing wrong with treating yourself with good food, overeating in the evening can lead to numerous negative effects.

The art of writing bad commit messages. We’ve probably all committed this one before. “Fixed a bug” or “WIP” are not great commit messages. Having good commit messages is important and you should take the time to write a good commit message. A good commit message provides useful information about what has changed and why. When things really go south, the revision history is a great resource to quickly find out where exactly things went wrong.

Having magic numbers in your code. Magic numbers are unique values with unexplained meaning or multiple occurrences that can and should be replaced with named constants. The thing with magic numbers is that they’re not readable and don’t provide any context for the developer. On top of that, magic numbers are often used multiple times in different places within a program, which makes it error-prone.

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he qualities of an ideal data pipeline. This list could be broken up into many more points but it’s pointed to the right direction. If you follow these principles when designing a pipeline, it’d result in the absolute minimum number of sleepless nights fixing bugs, scaling up and data privacy issues.

Not writing automated tests. Initially, it will cost you a little bit more time than doing manual tests when you start writing automated tests. In the long run, you’ll be glad you took the time to write these automated tests. Having to test everything manually is boring, time-consuming, and the human factor makes it more prone to errors.

Making things unnecessarily complex (aka over-engineering). Implementing certain design patterns for the heck of it is something that most developers have done. Just because you see an opportunity to implement a design pattern doesn’t mean you should. All this accomplishes is adding more technical debt to the code base.

If you really can’t stop using your devices, install a blue light blocker on your screens (e.g., f.lux). By doing so, the blue light of your screens will turn into a red light, which is less harmful to your body and sleep. Most phones already have a “night feature”. Alternatively, you can also grab a pair of blue light blocking glasses.

Too many things going on in one function. Try to let your functions do one thing and one thing only. Don’t let a function fetch, process, and output the data. Split all of these responsibilities up into different functions. One for fetching, one for processing, and another one to output the data. Keeping a function focused on a single concern is what makes it more robust.

Even if it might satisfy your cravings, eating carb-loaded or fatty meals before going to bed harms your sleep quality and should be avoided. Additionally, eating late can cause inflammation and impairments in blood sugar regulation and weight gain.

Starting to code without knowing the solution. This might seem exciting at first, but it will come back and bite you. Planning and organizing your code is an essential part of coding. You shouldn’t start coding without a plan. Think about problems that you might find along the way and how can you tackle them. This makes you more aware of the fact that there’s a lot to think about before writing code.

Python is one of the world’s most popular and in-demand programming languages. Indeed, if you are in the hot field of Data Science, Python is, most probably, your daily driver. But why?

Making things unnecessarily complex (aka over-engineering). Implementing certain design patterns for the heck of it is something that most developers have done. Just because you see an opportunity to implement a design pattern doesn’t mean you should. All this accomplishes is adding more technical debt to the code base.

Reinventing the wheel as a lack of knowledge. This mistake happens when a developer doesn’t know what’s already available in the framework. As a result of this lack of knowledge, new methods get implemented by the developer that are almost identical to a method that’s already available in the framework.

preface: are you ready to take your Python skills to the next level? Can you walk through the examples in this story without squinting? Functional programming in Python might be daunting for some, but still, very fulfilling.