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One of the major advantages of Python over other programming languages is its concise, readable code. Even within the Python language itself, though, there are ways to write code that is more elegant and achieves the same end result more efficiently. List comprehensions, dictionary comprehensions, and generator expressions are three powerful examples of such elegant expressions. In this post, we will take a look at for-loops, list comprehensions, dictionary comprehensions, and generator expressions to demonstrate how each of them can save you time and make development easier.
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Asynchronous Coding in Python

Asynchronous coding is not an entirely new concept - it has been a big topic over the last few years, but is just now being used on a wider scale. As opposed to traditional, linear programming - where things follow a precise order and every step must be completed before the next one can even begin - in asynchronous processes, none of the steps have to be finished before moving forward. So, how does it work, exactly?
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 If you’re a parent, maybe you’d find it convenient to be able to know if everything is alright with your baby, even when you’re not in the same room. I participated in a project which had a goal to enable parents to do exactly that. We created a mobile app intended to give parents the ability to monitor their babies remotely.
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Machine Learning (ML) and Deep Learning (DL) are evolving at a faster pace than ever. There is now a vast selection of different competitions, many of which are hosted on Kaggle, where thousands of data scientists and ML engineers compete to obtain higher positions on the scoreboard. Don't get me wrong - I am very fond of Kaggle. It is a great place to start and enhance your machine learning adventure. Also, competitions are places where science thrives - we all remember the space race, don’t we?
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Debugging Python Applications with pdb

Nobody likes to spend time on debugging when working under a tight deadline. But we all want our applications to work, so debugging code is a must in every project. Developers often turn to debuggers in such situations, and Python offers a solution like that.
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If you live in the world of tech, there is an excellent chance that you’ve heard the buzz surrounding Docker, along with the claims that it is set to change the face of programming. There’s no denying that the powerful container platform is making waves, but what is behind its meteoric rise to popularity, and should you be jumping on the bandwagon?
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What is graphQL? GraphQL is an open source data query and manipulation language. It was created by Facebook in 2012 and publicly released in 2015.
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Netguru Codestories | Python