Python Weekly - Python Weekly - Issue 559

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Welcome to issue 559 of Python Weekly. Let's get straight to the links this week.
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Articles, Tutorials and Talks

3 Simple Ideas From Functional Programming To Improve Your Code 
Functional programming is a complex topic to dive into. However, there are 3 simple ideas from functional/declarative code that you can apply to your own code today - without becoming a Haskell expert! This video dives into the details and show you a few examples in Python of how you can use these ideas in both object-oriented and functional/procedural code.

Build a Passwordless Authentication System Using Django, Twilio Verify, and SendGrid
In this tutorial, you will learn how to create a passwordless authentication system using Twilio Verify, SendGrid, Django, and Python. The proposed authentication system will require users to verify their identity using a one-time password.

4 Pandas Anti-Patterns to Avoid and How to Fix Them
pandas is a powerful data analysis library with a rich API that offers multiple ways to perform any given data manipulation task. Some of these approaches are better than others, and pandas users often learn suboptimal coding practices that become their default workflows.

Logging in Python: A Developer’s Guide
In this tutorial, you’ll learn how to set up logging in Python using the built-in logging module. You’ll learn the basics of logging, logging variable values and exceptions, configuring custom loggers and formatters, and more.

Implementing a Toy Optimizer
This post shows the complete code (in Python3) of how a very simple optimizer for sequences of operations can work. These algorithms could be part of a (really simple) compiler, or a JIT. The architecture of the code in this post is very similar to that of the trace optimizer of the PyPy JIT: After a trace is produced, is is optimized before being sent to the machine code backend that produces binary instructions for the CPU architecture that PyPy is running on.

Building an authenticated Python CLI
Learn how to build a persistently authenticated Python CLI using Click, Rich and more.

Code From Anywhere: Dev Containers and Github Codespaces
Because VS Code can run in the browser, Dev Containers, along with Github Codespaces, also allow you to develop from almost anywhere. They’re great for standardizing development across a team. They can also make working on several repos at once much easier because each repo can have its own specific environment for development.

Interesting Projects, Tools and Libraries

An open-source Python library supporting popular model compression techniques on all mainstream deep learning frameworks (TensorFlow, PyTorch, ONNX Runtime, and MXNet)

Blazing fast bulk data transfers between any cloud.

The open-source data-centric IDE for NLP. Combining programmatic labeling, extensive data management and neural search capabilities.

Opportunity for researching x86 platforms. You can understand how Intel mitigated spectre vulnerability, explore the implementation of Intel TXT, SGX,VT-x technologies!

A Greybox and Coverage-based library to fuzz Python applications.

The tiny time series database optimized for your happiness.

A lightweight function-oriented toolkit for better organisation of business logic and efficient selection and projection of data in Django projects.

Pinkerton is an JavaScript file crawler and secret finder developed in Python.

PRegEx is a Python package that can be used in order to construct Regular Expression patterns in a more human-friendly way.

This Food Does Not Exist
We have trained four StyleGAN2 models to generate food pictures. The images are purely synthetic!

A typing application to level up your fingers!

A new python library to create UI (or UI toolkit), which can be rendered in anything which can render html/js/css.

Tell the story of your Git project by creating video animations (.mp4) of your commit history directly from your Git repo.

Solve puzzles. Learn CUDA.

New Releases

Django 4.1 release candidate 1 released

Upcoming Events and Webinars

Virtual: PyMC Meetup July 2022
A panel discussion on the topic, Bayesian Modeling in Biotech: Using PyMC to Analyze Agricultural Data.

PyData Lancaster Meetup July 2022 
There will be following talks
  • How tech makes my life easier: memoirs of a data analyst
  • Blue pill, or red pill? Why not both!

Virtual: PyData Chicago Meetup July 2022
There will be a talk, Running Notebooks in Production? Blessing or Curse? Let's Find out!
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