- Python Weekly
- Posts
- Python Weekly (Issue 471 October 22 2020)
Python Weekly (Issue 471 October 22 2020)
Python Weekly - Issue 471
Python Weekly
Welcome to issue 471 of Python Weekly. Let's get straight to the links this week.
From Our Sponsor
A weekly newsletter featuring the best hand curated news, articles, tutorials, talks, tools and libraries etc for programmers.
News
A proposal to speed up CPython by a factor of 5 over the next four releases.
Articles, Tutorials and Talks
Learn how you can improve performance of Sklearn, PyTorch, TensorFlow, Pandas etc using Intel Python.
A first part of a 4-part series on gevent. Check out
,
, and
as well.
How I develop software using dictation and eye-tracking.
In this first Python Core Developers Q&A, several core developers answer questions sent in by the broader Python community.
This post is a comprehensive overview of techniques for structured key-value pair information extraction from invoices. We review the latest research papers that explore this topic and towards the end touch upon how you can get started implementing these methods.
Learn about two options we have in Python to terminate threads.
This tutorial walks you through the process of setting up a Docker Compose file to create a Django, Redis, Celery and PostgreSQL environment. Starting from a new Django project the outcome of this tutorial you will have a development setup which will allow you to work with the named tools without having to install them in your OS environment.
In an interview with Evrone, Armin talks about his work at Sentry, shares his thoughts on handling errors in the backend, speaks about the differences between Rust and Python, the “gradual typing” approach, and, of course, the secrets of his work-life balance.
This article describes how to use pandas and openpyxl to read ranges of data from poorly structured Excel files.
A series of talks that gives you an overview of the basics concepts of the Django ORM and covers a range of common functions that you will perform on a database with Django.
Few helpful libraries which aim to simplify the data science process for beginners.
Previous posts covered writing a Django application in a single file, for both synchronous and asynchronous use cases. This post covers the angle of creating a REST API using Django in a single file.
In this post you’ll see what a fractal is, how to generate an image of a fractal, and how to animate a fractal. We’ll do all of this locally, and then when we’ve found something interesting to focus on we’ll move the rendering to a more powerful cloud computer.
Interesting Projects, Tools and Libraries
MicroK8s is a small, fast, single-package Kubernetes for developers, IoT and edge.
Implementation of LambdaNetworks, a new approach to image recognition that reaches SOTA with less compute.
A GUI for Pandas DataFrames.
A Tool for Scanning the Python Package Index for Typosquatters.
A pretty simple and fully asynchronous framework for Telegram Bot API written in Python 3.7 with asyncio and aiohttp.
A simple Python text editor for programming and note taking.
A command-line bound implementation of secure synchronous lightweight chatroom with zero logging and total transience built using WebSockets, Fernet Cryptography, Asyncio and Prompt Toolkit.
Silvera is a tool for acceleration of development of microservice architectures.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Allows you to whitelist Spotify users for your collaborative playlists.
Upcoming Events and Webinars
There will be a talk, Long Story Short: Using BERT for abstractive text summarization on a small, curated corpusLong Story Short: Using BERT for abstractive text summarization on a small, curated corpus.
There will be following talks
4 Tips to Visualize Behavior With Python Matplotlib
Exploration of Geospatial data and how to visualize it with Kepler
Comparing Snakes and Gems
Join us as we hear from the Code for Philly (CFP) Team and their project leaders about opportunities to use your Python skills to improve the city.
There will be following talks
Breaking down data silos with collective machine learning
ML Flow and managing the distributed end-to-end machine learning life-cycle
There will be following talks
Best Practices for Data Augmentation
Explaining ML models in 2020
Our Other Newsletters
- A free weekly newsletter for programmers.
- A free weekly newsletter for entrepreneurs featuring best curated content, must read articles, how to guides, tips and tricks, resources, events and more.