Python Weekly (Issue 467 September 24 2020)

Python Weekly - Issue 467

September 24, 2020

Python Weekly

Welcome to issue 467 of Python Weekly. Let's get straight to the links this week.

From Our Sponsor 

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News

The pandemic negatively affected the PSF’s finances with the cancellation of PyCon 2020’s in-person conference and lower donations. Thanks to PyCon 2020 Online sponsors, donors, and our financial reserve, we are able to continue to support the Python community! 

Articles, Tutorials and Talks

This post shows you how to make an auto 35mm film scanner where a roll of 35mm film is scanned by a DIY cardboard film carrier, which is driven by Arduino Nano and controlled by Python using computer vision.

In this tutorial we build an interactive deep learning app with Streamlit and PyTorch to apply style transfer. This tutorial should demonstrate how easy interactive web applications can be built with Streamlit. Streamlit lets you create beautiful apps for your machine learning projects with simple Python scripts.

Jacob Kaplan-Moss's post about understanding and preventing DoS in web applications. The primary focus of this post is on the big picture, and should apply to any kind of web app. But to make things concrete, he has added a few specific Django-related examples.

Although Dependency Conflict (DC) issues are common in Python projects, developers lack tool support to gain a comprehensive knowledge for diagnosing the root causes of these issues. This paper presents the findings after conducting an empirical study on 235 real-world DC issues.

How far can a pure Numpy-based vector index go? Turns out by using memmap, correct batching, & simple math tricks, it can go pretty far. 

State-of-the-art forecasting with neural networks made simple.

A Step by Step Tutorial To Create Stunning Visualizations

A post that shows how to create a visualization to understand how gzip performs on a particular file and more specifically, understand which parts of a file compressed well, and which ones did not.

This tutorial shows you how to use gradient ascent to figure out how to misclassify an input.

A story about an esoteric feature of Python 3, and how the author spent some time reviving it and bringing it into the limelight.

Interesting Projects, Tools and Libraries

Automated Driving in NFS using CNN.

With a little help from deep learning, now you too can create your own happy accidents.

Learn Git Internals by Building Git in Python.

A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.

An Intelligent file organizer module that reads your pattern.

A Usable Library for (Extractive) Question Answering on Large Datasets with BERT.

git-cu helps keep your local git repositories organized by cloning them into a directory structure based on their URL.

Opytimizer is a Python library consisting of meta-heuristic optimization techniques.

Typing speed test right in your terminal.

Lightweight Python library for adding real-time 2D object tracking to any detector.

A python parametric CAD scripting framework based on OCCT.

Upcoming Events and Webinars

There will be following talks

  • Using deep learning to count albatrosses from space

  • From Jupyter notebooks to production code, a Kedro introduction

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