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Articles, Tutorials and Talks

These Bored Apes Do Not Exist
What’s worse than 10,000 Bored Ape Yacht Club NFTs? 100,000. In this blog post, we’ll attempt to train a GAN + super-resolution model to produce 100,000 Bored Ape Yacht Club ape images that do not actually exist.

How vectorization speeds up your Python code
Vectorization allows you to speed up the processing of homogeneous data in Python. Learn what it means, when it applies, and how to do it.

Go Fast With Django
How do you make your Django app fast? You measure what is slow, scale your system when necessary, and use a combination of fast database queries and strategic caching. In this Understand Django article, we'll explore those topics and more to help you get a performant Django app.

ThreadPoolExecutor in Python: The Complete Guide
The ThreadPoolExecutor allows you to create and manage thread pools in Python. This guide provides a detailed and comprehensive review of the ThreadPoolExecutor in Python, including how it works, how to use it, common questions, and best practices.

Django / Tailwind Tutorial - Code a Netflix Clone

Improve your Django and Tailwind CSS skills by building a Netflix clone. The clone focuses on simulating the front end of Netflix.

Python on z/OS – creating a C extension
The porting the MQ Python interface pymqi to z/OS exposed many of the challenges of running Python on z/OS. This post covers some of the lessons learned during the process.

Sentiment Analysis Using Python
Learn how to use sentiment analysis to mine insights from tweets and news articles.

SymPy Tutorial (2022): For Physicists, Engineers, and Mathematicians

This from-scratch tutorial on SymPy is designed specifically for those in physics, mathematics, and engineering.

Sockets for dummies
Dive into the world of socket programming with this Python tutorial that assumes 0 prior experience.

Analyzing stock data near events with pandas
Stock market returns are heavily impacted by some events, like FOMC announcements, and we can use pandas to understand this impact.

A probabilistic programming language in 70 lines of Python
This post explains how Probabilistic Programming Languages (PPLs) work by showing step-by-step how to build a simple one in Python.

Python bytecode explained

Problems with testing Python pre-releases and pip caching

Unravelling subscriptions in Python

Don't Wrap Instance Methods with 'functools.lru_cache' Decorator in Python

Books

Humanities Data Analysis: Case Studies with Python
A practical guide to data-intensive humanities research using the Python programming language.

Interesting Projects, Tools and Libraries

orbit
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

Mercury
Easily convert your Python notebooks into interactive web apps by adding parameters in YAML.

Brownie
A Python-based development and testing framework for smart contracts targeting the Ethereum Virtual Machine.

legodnn
A block-grained scaling tool for the mobile vision system.

ANCS4Linux
iOS/iPadOS notification service client for Linux desktop (notifications on your desktop, over Bluetooth Low Energy)

Hitomi-Downloader
Desktop utility to download images/videos/music/text from various websites, and more.

tolerance_interval_py
A small Python library for one-sided tolerance bounds and two-sided tolerance intervals.

Robusta
Robusta is a troubleshooting and automation platform for Kubernetes.

red-mail
Red Mail is an advanced email sender library. It makes sending emails trivial and has a lot of advanced features.

XManager
A framework for managing machine learning experiments.

wordle-tui
Play WORDLE game in your terminal.

mureq
Single-file replacement for python-requests.

coltrane
A simple content site framework that harnesses the power of Django without the hassle.

New Releases

Python 3.10.2, 3.9.10, and 3.11.0a4 are now available

Upcoming Events and Webinars

Virtual: Orlando Python Meetup January 2022
We're going to walk through an introduction to RocketPy, a Python library that lets you design and tests hobby rockets all in code. We'll run some simulations and provide the context to understand all of the components of this powerful library.

Virtual: PyData Chicago January 2022
There will be a talk, Scale EDA & ML Workloads To Clusters & Back With Dask.

Virtual: Salt Lake City PyData January 2022
There will be a talk, Model Review: improve transparency, reproducibility, & info sharing with MLflow.

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Python Weekly - Issue 533

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