Python Weekly (Issue 370 October 25 2018)

Python Weekly - Issue 370

October 25, 2018

Python Weekly

Welcome to issue 370 of Python Weekly. Let's get straight to the links this week.

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News

With this second iteration of the official Python Developers Survey, we aim to identify how the Python development world looks today and how it compares to last year. The results of the survey will serve as a major source of knowledge about the current state of the Python community, so we encourage you to participate and make an invaluable contribution to the community knowledge. The survey takes about 10 minutes to complete.

Articles, Tutorials and Talks

Uber developed Michelangelo PyML to run identical copies of machine learning models locally in both real time experiments and large-scale offline prediction jobs.

In this tutorial you will learn how to perform object tracking using dlib, enabling you to track objects in real-time video.

Fascinated by robots? Follow this simple guide and learn how to use a robot simulator for programming a robot.

Altair is a declarative statistical visualization library for Python, based on Vega and Vega-Lite. In this post we’ll be digging deeper into one of altair's less known features: themes.

Linear regression is a great start to the journey of machine learning, given that it is a pretty straightforward problem and can be solved by popular modules such as the scikit-learn package. In this article, we shall discuss a line-by-line approach on we implement linear regression using TensorFlow.

Practical Tips for 1-GPU, Multi-GPU & Distributed setups.

In this tutorial, we will be learning about iterators and iterables. There is a lot of confusion around these terms and exactly what they mean. We're also going to learn how to make an object ourselves that is both an iterable and an iterator. This video isn't only about understanding these definitions. It's also about understanding the concepts of iterators so that you can write better code. Understanding these underlying concepts is going to help you write code that is more efficient and will also help you see solutions to certain problems in a way you might not have thought of before. 

Hadoop ships with a feature-rich and robust JVM-based HDFS client. For many that interact with HDFS directly it is the go-to tool for any given task. That said, there is a growing population of alternative HDFS clients. Some optimise for responsiveness while others make it easier to utilise HDFS in Python applications. In this post I'll walk through a few of these offerings.

This post article aims to show you how to call Rust from Python and has a few benchmarks to motivate why you may want to do so.

The Case, Investigation, and Results.

Interesting Projects, Tools and Libraries

Collection of flashcards for Python language, frameworks, libraries, etc.

Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet.

An open source framework for deep learning on satellite and aerial imagery. 

Automatically update running docker containers with latest image.

Readable regular expressions for Python 3.6 and up.

Celery Async Task Management App for Django.

eNMS is a vendor-agnostic NMS designed for building workflow-based network automation solutions.

A markdown renderer focusing on security first.

Proximal Meta-Policy Search.

A penetration testing framework for UNIX systems.

New Releases

Upcoming Events and Webinars

There will be following talks

  • Beyond Moore's Law: What happens to Pythonistas when the greatest truth of our lives ends

  • Astronomical data analysis using Python

  • iPython extensions!

If you’ve heard about testing and unit tests but are not sure where they fit in the development process, you are at the right place. Learn the basics of unit testing which will give you the tools to validate the correctness of your code. You will also find out how a startup uses the deployment tool Kubernetes to improve their testing pipeline and code quality.

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