Python Weekly (Issue 454 June 18 2020)

Python Weekly - Issue 454

June 18, 2020

Python Weekly

Welcome to issue 454 of Python Weekly. Let's get straight to the links this week.

From Our Sponsor 

Troubleshoot your app's performance with Datadog's end-to-end tracing and in one click correlate those Python traces with related logs and metrics. Use their detailed flame graphs to identify bottlenecks and latency in that app of yours.

News

The results of the fourth annual JetBrains Developer Ecosystem Survey 2020 based on the insights of almost 20,000 developers. Python has overtaken Java in the list of languages used in the last 12 months. It is the most studied language. In the last 12 months 30% of respondents have started or continued to learn Python — even more than last year

The free LEGO Mindstorms Robot Inventor coding app for kids uses coding language based on Scratch and supports Python for more advanced coders.

The virtual conference will take place on September 18-19 and open for everyone free of charge.

This year the conference will be online. So you can submit the proposal irrespective of where you are based and join remotely.

Articles, Tutorials and Talks

Dipping toes into the realm of structural design patterns.

Async Python is slower than "sync" Python under a realistic benchmark. A bigger worry is that async frameworks go a bit wobbly under load.

GitHub REST API allows you to manage issues, branches, repos, commits and more, so let’s see how you can do that using Python!

Automatic differentiation is the foundation upon which deep learning frameworks lie. Deep learning models are typically trained using gradient based techniques, and autodiff makes it easy to get gradients, even from enormous, complex models. ‘Reverse-mode autodiff’ is the autodiff method used by most deep learning frameworks, due to its efficiency and accuracy. Let’s: Look at how reverse-mode autodiff works and Create a minimal autodiff framework in Python.

Have you thought about contributing to an open source project, but you're too confused (or intimidated) by the process to even try? This step-by-step guide shows you the exact process you can use when contributing to a project on GitHub. If you follow this guide exactly, you can make your first open source contribution today!

A quick tour of the library and how it stands out from the old guard.

Exploring golang - can we ditch Python for go? And have we finally found a use case for go? Part 1 explores high-level differences between Python and go and gives specific examples on the two languages, aiming to answer the question based on Apache Beam and Google Dataflow as a real-world example.

In Python, Integers are not iterables but we can make them iterable by implementing __iter__ function. In this essay, we change Python's source code and implement iter function for integers.

This unique algorithm using Python and Shamir's Secret Sharing protects your master password from hackers and your own forgetfulness.

In this Django and Vue.js tutorial, we'll be building a todo app. This is a trivial thing to do when you know a language, but it's also a great way to learn many of the key concepts of programming.

Math to Code is an interactive Python tutorial to teach engineers how to read and implement math using the NumPy library.

Looking for a rapid way to pull down unstructured data from the Web?  Here’s a 5-minute analytics workout across two simple approaches to how to scrape the same set of real-world web data using either Excel or Python.  All of this is done with 13 lines of Python code or one filter and 5 formulas in Excel.

An introduction to property-based testing in Python.

In this post, we will walk though the steps in resolving these conversion headaches in order to get our example Pytorch model to do inferencing on iPhones via Core ML. At the end of the process, we’d build and iOS app for doing live inferencing with our Pytorch model, going from microphone input into visualized melspectrograms.

Learn HTTP cookies in this guide, complete of practical examples with JavaScript and Python, plus useful resources.

In this Pandas tutorial, we will learn how to import data from JSON to Excel in Python. This guide will cover 4 simple steps making use of Python’s json module, and the Python packages requests and Pandas.

In this article you will learn about: Common exceptions, Handling exceptions, Raising exceptions, Examining exception objects, Using the finally statement and Using the else statement.

Interesting Projects, Tools and Libraries

audino is an open source audio annotation tool. It provides features such as transcription and labeling which enables annotation for Voice Activity Detection (VAD), Diarization, Speaker Identification, Automated Speech Recognition, Emotion Recognition tasks and more.

High-Resolution 3D Human Digitization from A Single Image.

A simple OpenAI Gym environment for single and multi-agent reinforcement learning

Write, in pure Python, web apps that are automagically accessible from all the Internet. 

An HTTP Request Smuggling / Desync testing tool written in Python 3.

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models. 

Rethinking the Truly Unsupervised Image-to-Image Translation 

An optimized re-implementation for 2D-TAN: Learning 2D Temporal Localization Networks for Moment Localization with Natural Language.

Eric is a full featured Python editor and IDE, written in Python. It is based on the cross platform Qt UI toolkit, integrating the highly flexible Scintilla editor control. It is designed to be usable as everdays' quick and dirty editor as well as being usable as a professional project management tool integrating many advanced features Python offers the professional coder. 

Monitor Python web apps using Spring Boot Admin. Pyctuator supports Flask and FastAPI. Django support is planned as well.

Threat Hunting tool about Sysmon and graphs.

New Releases

In this release we worked on new features such as run by line and a start page, in addition to addressing 53 issues. You can check the full list of improvements in our changelog. 

Upcoming Events and Webinars

Moshe Zadka shows how to write unit tests like a pro in this hands-on free training course! Unit testing is an in-demand skill set used by software testers and QA engineers alike.

There will be following talks

  • Why does my NLP model (which got 96.72% accuracy during validation) suck in production?

  • When Product Management meets Machine Learning.

  • A bibliometric study of a research field

  • gentest: Automatic Test Generation for Arbitrary (1) Programs with TDDA

  • Introducing Elyra : Extending JupyterLab for AI

Extensive evidence has shown that AI can embed human and societal bias and deploy them at scale. And many algorithms are now being reexamined due to illegal bias. So how do you remove bias & discrimination in the machine learning pipeline? In this talk, you'll learn the debiasing techniques that can be implemented by using the open source toolkit AI Fairness 360.

In this talk, we will have Anton Biryukov and Jules LaPrairie discuss strategies employed and lessons learned from building and running a distributed, AI powered IoT solution.

There will be following talks

  • Choosing a Tech Recruiter 

  • Because Mocking Objects is Still Hard 

  • PyCharm tricks for productivity 

  • Testing with Nox and GitHub 

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