Python Weekly (Issue 441 March 19 2020)

Python Weekly - Issue 441

March 19, 2020

Python Weekly

Welcome to issue 441 of Python Weekly. Let's get straight to the links this week.

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Articles, Tutorials and Talks

In this article, I’ll show you how to write Python with no runtime exceptions. This’ll get you partway to writing code that never breaks and mostly does what it’s supposed to do. We’ll do this by learning how to apply functional programming to Python.

In this tutorial, you will learn how to automatically detect COVID-19 in a hand-created X-ray image dataset using Keras, TensorFlow, and Deep Learning.

A simple guide to Django 3.0 and ASGI with performance implications told with quirky illustrations.

This is the second of a three-part blog post on the Jupyter Notebook ecosystem. Here, I’ll discuss various tools that I use alongside Notebooks, and how I incorporate them in my day-to-day work.

Towards neural net frameworks that purify stateful code.

Financial Institutions require a ton of man power to do simple tasks like data entry. This not only consumes resources, but also is a bottleneck for following processes. Modern techniques like deep learning to perform OCR can help automate the process.

My life in a Python package.

This article shows the main differences between Django ORM and SQLAlchemy with examples of how to do something in Django and how to do the same in SQLAlchemy. 

A beginner's guide to asynchronous API calls with Python's Twisted package.

How inappropriate data access patterns massively slow down programs and how the same problems arise with RESTful APIs.

Interesting Projects, Tools and Libraries

A powerful yet lean wrapper over Flask to massively speed up API creations and enable super fast module-to-API transformations.

Tweet locator using Python, Flask and Twitter API.

Self-hosted email marketing solution. Compatible with any SMTP email service.

A collection of my generative artwork, mostly with Processing in Python mode.

Advanced Pandas Vault — Utilities, Functions and Snippets.

A pytorch adversarial library for attack and defense methods on images and graphs.

Pytest plugin for analyzing resource usage during test sessions.

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