Python Weekly (Issue 432 January 16 2020)

Python Weekly - Issue 432

January 16, 2020

Python Weekly

Welcome to issue 432 of Python Weekly. Let's get straight to the links this week.

From Our Sponsor 

Monitor your Python applications in real time with Datadog. Trace requests across service boundaries (and identify latency and other potential errors) with detailed flame graphs.

Articles, Tutorials and Talks

Mercurial 5.2 was released on November 5, 2019. It is the first version of Mercurial that supports Python 3. This milestone comes nearly 11 years after Python 3.0 was first released on December 3, 2008. This post is logically divided into two sections: a mostly factual recount of Mercurial's Python 3 porting effort and a more opinionated commentary of the transition to Python 3 and the Python language ecosystem as a whole. 

If you're not careful, your Python environment can quickly become a disaster.  We'll walk through the available tools to be more (code) environmentally friendly and establish some (highly opinionated) preferences for setting up Python.

One of the more hair-raising facts we learn in my introductory Python trainings is that you can pass functions into other functions. You can pass functions around because in Python, functions are objects. You likely don’t need to know about this in your first week of using Python, but as you dive deeper into Python you’ll find that it can be quite convenient to understand how to pass a function into another function. This is part 1 of what I expect to be a series on the various properties of “function objects”. This article focuses on what a new Python programmer should know and appreciate about the object-nature of Python’s functions.

A gentle introduction to Visual Question Answering (VQA) using neural networks.

Whether you are working on some machine learning/AI stuff, building web apps in Flask or just writing some quick Python script, it's always useful to have some template for your project that satisfies all your needs, namely: predefined directory structure, all necessary config files like pytest.ini or requirements.txt, Testing, linting and static code analysis setup, CI/CD tooling, Dockerization of your app and on top of that automation with Makefile. So, here I bring you exactly that in this "Ultimate" all-purpose setup for your Python projects.

Django helps you build websites in Python. How does it work? In this series, we'll explore Django from top to bottom to show you how to build the website you've wanted. We'll start from the beginning with the browser.

Django 3 is released with full async support! In this tutorial, we’ll see by example how to create a CRUD application from scratch and step by step. We’ll see how to configure a MySQL database, enable the admin interface, and create the django views.

A Python script to help you find your ideal EuroTrip.

How open source programming can offer opportunities after incarceration.

Interesting Projects, Tools and Libraries

A high-performance, high-precision CPU and memory profiler for Python.

The First Python Selfbot for Slack Workspaces. Slacky was created as way to automate and make Slack more fun to use. It comes with many commands by default and even allows for custom plugins to be built and imported easily.

Render images as a set of continuous lines representing each horizontal (or vertical) line of pixels.

A light weight Python library for the Spotify Web API.

A static analysis tool for Python that blurs the line between testing and type systems.

CleverCSV provides a drop-in replacement for the Python csv package with improved dialect detection for messy CSV files. It also provides a handy command line tool that can standardize a messy file or generate Python code to import it.

Visualize an array, using common sorting algorithms to visualize how this algorithms are working.

AutoGluon enables easy-to-use and easy-to-extend AutoML with a focus on deep learning and real-world applications spanning image, text, or tabular data.

Another terminal-based Spotify client.

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