Python Weekly (Issue 407 July 25 2019)

Python Weekly - Issue 407

July 25, 2019

Python Weekly

Welcome to issue 407 of Python Weekly. Let's get straight to the links this week.

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Articles, Tutorials and Talks

A simple walkthrough of what RNNs are, how they work, and how to build one from scratch in Python.

Scrapy is a popular open-source Python framework for writing scalable web scrapers. In this tutorial, we’ll take you step by step through using Scrapy to gather a list of Oscar-winning movies from Wikipedia.

In a previous post, we discussed how to automate some of the more tedious parts of debugging firmware using Python in GDB Scripts. To make these commands more powerful, one could use third-party packages from Python’s PyPi repository. In this post, we will discuss how to properly setup GDB and Python and then modify the uuid_list_dump command from the post mentioned above to make use of a third party package installed through PyPi.

In this post, we walk through setting up a virtual environment for our python packages and then scrape data from basketball-reference.com with beautifulsoup.

Deploying Scalable, Production-Ready Web-Services in Python 3 on Kubernetes.

How to tweak the Babel library for large i18n projects to enable pseudotranslation and iterative localization.

MIDI is an extremely popular and versatile format for music data, whether you're using it as a digital musical instrument interface or just transcribing music in it to show your bandmates new songs. Mido is a Python library you can use to interact with MIDI in your code. Let's walk through the basics of working with MIDI data using the Mido Python library.

In Part 1, we will complete the setup of Django rest framework and Vue.js and connect them by the help of Django webpack loader. 

  • Part 2 - In the second part, we will go deep in vue and create our application for uploading, listing and deleting any files with an eye-catching ui.

In this post we will learn how to create a binder so that our data analysis, for instance, can be fully reproduced by other researchers. That is, in this post we will learn how to use binder for reproducible research.

This is part 1 of a two-part series post about automating report generation using python, jupyter, papermill, and a couple of other tools.

Interesting Projects, Tools and Libraries

Tartiflette is a GraphQL Engine, built on top of Python 3.6 and above. Focused on building GraphQL APIs using the awesome Schema Definition Language.

Semi-automated, feedback-driven tool to rapidly search through troves of public data on GitHub for sensitive secrets.

3D printer / slicing GUI built on top of the Uranium framework.

A curated list of applied machine learning and data science notebooks and libraries across different industries.

Pylustrator is a program to style your matplotlib plots for publication. Subplots can be resized and dragged around by the mouse, text and annotations can be added. The changes can be saved to the initial plot file as python code.

A cli tool to convert and manage jupyter notebook blogs. Proudly host your notebooks even as a static site.

Data ETL & Analysis on the dataset 'Baby Names from Social Security Card Applications - National Data'.

pytorch implementation for "Deep Flow-Guided Video Inpainting"(CVPR'19) 

Non-blocking, high-performance Web API Framework.

New Releases

PyCharm 2019.2 is out now: improved Jupyter Notebook experience, syntax highlighting for many more languages out of the box, initial Python 3.8 support, and much more. 

It includes some exciting new features and changes, including a switch to “offline” mode by default, the inclusion of Plotly Express as the recommended entry point into the library, and a new rendering framework compatible with not only Jupyter notebooks but other notebook systems such as Colab, Azure and Kaggle notebooks, as well as popular IDEs such as PyCharm, VSCode, Spyder and others.

Upcoming Events and Webinars

The Python Web Conf is a virtual event that features international tech experts presenting on 24 topics such as microservices, identity management, machine learning and CI/CD. The talks are split into 3 exciting tracks: “App Dev”, “Cloud Native” and “Automate & Deploy”. Each track is accessible live via Zoom and participants can chat via Slack channels. Access to presentations and post-event recordings will be available exclusively to registered attendees.

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