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. Read More Here What Do Companies Expect From Python Devs In 2019? By Andrew Stetsenko Image for post Image for post 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. Read More Here 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. Read More Here 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. Read More Here Creating a Heatmap From Scratch in Python Image for post Image for post 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. Read More Here How to Build Your Own Neural Network From Scratch in Python By James Loy Image for post Image for post 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. Read More Here 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. Read More Here 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. Read More Here 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.
John Maeda created quite a stir with his montage of the Yahoo and Google homepages from 1996 to 2006 in simple is about staying simple:
There’s an interesting anecdote about Google’s absolute focus on minimalism in Seth Godin’s book Purple Cow:
It turns out that the folks at Google are obsessed with the email they get criticizing the service. They take it very seriously. One person writes in every once and a while and he never signs his name. According to Marissa Meyer at Google, “Every time he writes, the e-mail contains only a two-digit number. It took us a while to figure out what he was doing. He’s counting the number of words on the home page. When the number goes up, he gets irritated, and e-mails us the new word count. As crazy as it sounds, his emails are helpful, because they put an interesting discipline on the UI team not to introduce too many links. It’s like a scale that tells you that you’ve gained two pounds.”
Conventional wisdom says to beat your competitors you need to one-up them. If they have 4 features, you need 5. Or 15. Or 25. If they’re spending X, you need to spend XX. If they have 20, you need 30.While this strategy may still work for some, it’s expensive, resource intensive, difficult, defensive, and not very satisfying. And I don’t think it’s good for customers either. It’s a very Cold War mentality — always trying to one-up. When everyone tries to one-up, we all end up with too much. There’s already too much “more” — what we need are simple solutions to simple, common problems, not huger solutions to huger problems.
What I’d like to suggest is a different approach. Instead of one-upping, try one-downing. Instead of outdoing, try underdoing. Do less than your competitors to beat them.
Usability guru Donald Norman thinks the comparison between Google and Yahoo is misleading, and offers the truth about Google’s so-called “simplicity”:
Is Google simple? No. Google is deceptive. It hides all the complexity by simply showing one search box on the main page. The main difference, is that if you want to do anything else, the other search engines let you do it from their home pages, whereas Google makes you search through other, much more complex pages. Why aren’t many of these just linked together? Why isn’t Google a unified application? Why are there so many odd, apparently free-standing services?
I think this is a completely wrongheaded analysis, because I don’t want to do anything else. All I want is to find what I’m searching for. Like Damien Katz, I believe features don’t matter:
These people don’t care about your flexible, brilliant architecture. They don’t wish to tweak settings. They don’t want to spend more than 10 consecutive seconds confused. They just want simple, they want to get their task done and move on. They don’t want to spend time learning anything because they know they’ll probably just forget it long before they’ll need to do it again anyway.
We should always be in pursuit of simplicity, in whatever form it takes.