9 Amazing Articles on Python Programming

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9 Amazing Articles on Python Programming

A collection of our favorite pieces from the last year

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A lot is happening in the world of Python. Support for Python 2 is ending and more and more companies are referencing Python in job descriptions as it continues to gain new libraries and more support.

Since there is so much changing so fast, we gathered some of our favorite pieces. We hope they help you with your Python programming journey!

Python 2 EOL: How to Survive the End of Python 2

By Serdar Yegulalp

On January 1, 2020, the 2.x branch of the Python programming language will no longer be supported by its creators, the Python Software Foundation.

Here’s what you can do if you’re stuck with Python 2 in what is fast becoming a Python 3 world.

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What Do Companies Expect From Python Devs In 2019?

By Andrew Stetsenko

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What skills do you need to succeed as a Python dev in 2019?

Our team took 300 job specs for Python developers, scrapped from StackOverflow, AngelList, LinkedIn, and some fast-growing tech companies worldwide.

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Asynchronous Programming in Python: A Walkthrough

by David Bolton

When we talk about program execution, “asynchronous” means that the program doesn’t wait for a particular process to complete, but carries on regardless.

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Buggy Python Code: The 10 Most Common Mistakes That Python Developers Make

By Martin Chikilian

Python’s simple, easy-to-learn syntax can mislead Python developers, especially those new to the language, into missing some of its subtleties and underestimating the power of the diverse Python language.

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Creating a Heatmap From Scratch in Python

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Heatmaps are frequently used to visualize event occurrence or density. There are some Python libraries or GIS software/tools that can be used to create a heatmap, such as QGIS, ArcGIS, and Google Table Fusion. Unfortunately, this piece doesn’t discuss how to create a heatmap using those software/tools, but more than that, we will write our own code to create a heatmap in Python 3 from scratch.

The algorithm which will be used to create a heatmap in Python is Kernel Density Estimation (KDE). Please refer to QGIS Heatmap Using KDE Explained for more explanation about KDE and Heatmap Calculation Tutorial which gives an example of how to calculate intensity for a point from a reference point using KDE.

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How to Build Your Own Neural Network From Scratch in Python

By James Loy

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Most introductory texts to Neural Networks brings up brain analogies when describing them. Without delving into brain analogies, I find it easier to simply describe Neural Networks as a mathematical function that maps a given input to the desired output.

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What Exactly Can You Do With Python? Here Are Python’s 3 Main Applications

by YK Sugi

“What exactly can I use Python for?”

Well, that’s a tricky question to answer because there are so many applications for Python.

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Python Programming Language Gets Speed Boost From Latest PyPy Interpreter

By Nick Heath

Good news for Python developers, thanks to a new release of the already speedy PyPy interpreter that promises to be the fastest version yet.

If you’re programming using Python, an important choice is whether to run your code using the main CPython interpreter or an alternative such as PyPy, with each option having pros and cons.

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How to Collect, Customize, and Centralize Python Logs

By Emily Chang and Nils Bunge

The logging module is included in Python’s standard library, which means that you can start using it without installing anything. The logging module’s basicConfig() method is the quickest way to configure the desired behavior of your logger.

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