Python 3.9.9 hotfix release is now available

Python 3.9.9 hotfix release is now available

Python 3.9.9 is the eighth maintenance release of the legacy 3.9 series. Python 3.10 is now the latest feature release series of Python 3. Get the latest release of 3.10.x here.

3.9.9 was released out of schedule as a hotfix for an argparse regression in Python 3.9.8 which caused complex command-line tools to fail recognizing sub-commands properly. Details in BPO-45235. There are only three other bugfixes in this release compared to 3.9.8. See the changelog for details on what changed.

Upgrading to 3.9.9 is highly recommended if you’re running Python 3.9.8.

The next Python 3.9 maintenance release will be 3.9.10, currently scheduled for 2022-01-03.

Get it here:

We apologize for the inconvenience

…and still hope you’ll enjoy the new release!

Your friendly release team,
Ned Deily @nad
Steve Dower @steve.dower
Łukasz Langa @ambv

Bamboolib: One of the Most Useful Python Libraries You Have Ever Seen

Bamboolib: One of the Most Useful Python Libraries You Have Ever Seen

I love writing about Python libraries. If you have read any of my blogs, you might know I have written about multiple libraries. Before writing, I test some Python libraries, check their most remarkable features, and, if I like, I write about them. Usually, I try to include a few libraries in the same blog to make it more informative. However, once in a while, I find libraries that are so cool that deserve their own blog. That’s the case for Bamboolib!

Bamboolib is one of those libraries that makes you think: How didn’t I know this before? Yeah, it sounds a little dramatic, but believe me, you will be surprised. Bamboolib can build the code for things that take a while to write, such as complex group by clauses. Let’s jump right in because I’m very excited to show you how it works.

Bamboolib — for beginners and for pros

Bamboolib sells itself as making any person do Data Analysis in Python without becoming a programmer or googling syntax. Based on my tests, that’s true! It requires zero coding skills. However, I see how it could be handy for people running short in time or for someone who doesn’t want to type long codes for simple tasks. I can also see how people learning Python can take advantage of it. For example, if you want to learn how to do something in Python, you can use Bamboolib, check the code it generates, and learn from it.

Either way, let’s explore how you can use it, and you can decide if it can be helpful for you or not. Let’s get started!

Read the full article here

How to Analyze Data Using Mito in Python

How to Analyze Data Using Mito in Python

Spreadsheet and Programming on your Jupyter Notebook, Why Not?


Data contains so many meaningful insights. Data Analysis is the way for getting those insights. Sometimes, we get confused about choosing which tools we want to use, whether using spreadsheet software like Excel. Or we can use a programming language like Python.

And for some people, they prefer to use the spreadsheet tool. One of the reasons for that is because they cannot do programming yet.

Using the spreadsheet tool is not recommended for big data. Therefore, we need programming for analyzing big data. But thankfully, there’s a tool for connecting both. It’s called Mito.

Mito is a library that has capabilities for analyzing the data. Unlike the Pandas library, Mito has an interface like the spreadsheet software. Therefore, we can explore and process the data without interfering with codes.

In this article, I will show you how to analyze data using Mito. Also, I will show you the features that are included in this tool. Without further, let’s get started!


Install and load the library

Before we can use the library, we need to install it first. We need to install the mitoinstaller library for installing Mito with the ‘pip’ command. Here is the command for doing that:

Read the full article here