Python Weekly (Issue 498 May 6 2021)

Python Weekly - Issue 498

May 06, 2021

Python Weekly

Welcome to issue 498 of Python Weekly. Let's get straight to the links this week.

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News

Everything you know and love about the TI-84 Plus CE, now with the power of Python. Introduce students to coding with Python using TI technology. Available fall 2021.

The Python standard library ipaddress also suffers from the critical IP address validation vulnerability identical to the flaw that was reported in the "netmask" library earlier this year. The researchers who had discovered the critical flaw in netmask, also discovered the same flaw in this Python module and have procured a vulnerability identifier: CVE-2021-29921. The regression bug crept into Python 3.x's ipaddress module as a result of a change made in 2019 by Python maintainers.

The Scientific Python Working Group considers funding proposals that advance the scientific use of Python. Our most recent call for proposals has closed, and we are excited to announce six grants.

Articles, Tutorials and Talks

Learn how to use a combination of numpy, scipy, and sympy to solve for the magnetic field for current carrying wires of any shape or size, provided they can be parametrized. All symbolic math is done in sympy so no paper or pencil is required.

Here's how we implemented multi-tenancy on a recent Python / Django app build. This article describes our approach, shares some code and compares it with an earlier project we did using a different method.

To explore SQLite along with Python, we are going to build a simple tic-tac-toe game. So buckle up and get your machines ready!

Learn how to use OpenCV in the cloud with Python. OpenCV is a library of programming functions mainly aimed at real-time computer vision. You will learn how to create computer vision applications in the cloud on Google Colab. You will use AI and machine learning.

This article covers the basics of sequence slicing in Python and teaches you some idiomatic slicing patterns to write more elegant code.

The PyTorch Developer Podcast is a place for the PyTorch dev team to do bite sized (10-20 min) topics about all sorts of internal development topics in PyTorch.

Although Bodywork is focused on deploying machine learning projects, it is flexible enough to deploy almost any type of Python project. We're going to demonstrate this by using Bodywork to deploy a production-ready instance of MLflow (a Flask app), to Kubernetes, in only a few minutes.

This talk will discuss the approaches taken in the past to support async/await in Flask, where they struggled, and the challenges in general. It will then show how inspiration has been taken from Django to introduce support in the upcoming Flask-2.0 release.

This post introduces a new Python package to generate clustergrams from clustering solutions. It is compatible with scikit-learn and GPU-enabled libraries such as cuML or cuDF within RAPIDS.AI. Let us look at some examples to understand how clustergram looks and what to do with it.

Interesting Projects, Tools and Libraries

Instagram's performance oriented fork of CPython.

PDM is a modern Python package manager with PEP 582 support. It installs and manages packages in a similar way to npm that doesn't need to create a virtualenv at all!

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO.

Fearless interactivity for Jupyter notebooks.

AWS Auto Inventory allows you to quickly and easily generate inventory reports of your AWS resources. 

PyMongoArrow is a companion library to PyMongo that contains tools for loading MongoDB query result sets as Pandas DataFrames, NumPy arrays, or Apache Arrow tables. It can also easily generate parquet files, csv files, etc. 

One Stop Anomaly Shop: Anomaly detection using two-phase approach: (a) pre-labeling using statistics, Natural Language Processing and static rules; (b) anomaly scoring using supervised and unsupervised machine learning.

New Releases

Upcoming Events and Webinars

The largest annual gathering for the community using and developing the Python programming language.

There will be following talks

  • Executable storytelling with rule-based models

  • Python vs. the pandemic: writing high-performance models in a jiffy

There will be a talk, Scraping Wikipedia using SPARQL and DBPedia.

There will be a talk, Accessibility Awareness in Tech.

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