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- Python Weekly (Issue 426 December 5 2019)
Python Weekly (Issue 426 December 5 2019)
Python Weekly - Issue 426
Python Weekly
Welcome to issue 426 of Python Weekly. We have a packed issue this week. Enjoy it!
From Our Sponsor
Monitor your Python applications in real time by pinpointing bottlenecks with detailed flame graphs and tracing requests as they travel across service boundaries.
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News
The Python Software Foundation is receiving $407,000 USD to support work on pip in 2020. This foundational, transformational work will release Python developers and users to concentrate on the tools they're making and using, instead of troubleshooting dependency conflicts. Specifically, CZI and Mozilla are funding user experience, communications/publicity, and testing work (including developing robust testing infrastructure) as well as core feature development and review.
The Python security team removed two trojanized Python libraries from PyPI (Python Package Index) that were caught stealing SSH and GPG keys from the projects of infected developers. The two libraries were created by the same developer and mimicked other more popular libraries -- using a technique called typosquatting to register similarly-looking names. The first is "python3-dateutil," which imitated the popular "dateutil" library. The second is "jeIlyfish" (the first L is an I), which mimicked the "jellyfish" library.
Articles, Tutorials and Talks
In this post, we'll go through the necessary steps to build and deploy a machine learning application. This starts from data collection to deployment and the journey, as you'll see it, is exciting and fun.
A practical and applied introduction to quantum computer programming, using IBM's free cloud-based quantum machines and Qiskit.
There are many ways to configure a framework. Each approach has its own trade-offs. This post describes some of these framework configuration patterns here, with brief examples and mention of some of the trade-offs.
How to tune and optimize Prophet using domain knowledge to add greater control to your forecasts.
Django just released their next major version, django 3.0. How does it impact you and what the hell is an ASGI? Let's talk.
A look at how to write performant Python code in simple ways and how much each improvement is effective.
In this tutorial, you will learn how to use OpenCV and Deep Learning to detect vehicles in video streams, track them, and apply speed estimation to detect the MPH/KPH of the moving vehicle.
Learn how to build an Indeed bot with Python.
What's the difference between Excel and Python? In this tutorial, we'll compare by looking at how to perform basic analysis tasks across both platforms.
In this episode, Tyreke White shows us how to get started with Python development using Visual Studio Code. He covers what you need to install and how to configure your environment, as well as sharing tips on how to debug your Python code.
If you use Jupyter Notebook to run long-running processes, such as machine learning training, then you would probably like to know when the cell finishes executing. There is a neat browser plugin that you can use to help solve this issue called jupyter-notify. It will allow you to have your browser send a pop-up message when the cell finishes executing.
A quick, easy introduction to the Bag-of-Words model and how to implement it in Python.
This is a great way to sample starting to get further and further into the internals of CPython, the de facto Python Reference Implementation. Don't let prior misconceptions or a perceived sense of topics you should be covering hold you back. If you want to learn more about Python, this is 10 minutes well spent!
Learn how to explore, visualise and analyse 100s of Gigabytes of tabular data with the Vaex open-source dataframe library in Python.
In this tutorial, we are going to learn how to push application logs from our Django application to Elasticsearch storage and have the ability to display it in a readable way in Kibana web tool. The main aim of this article is to establish a connection between our Django server and ELK stack (Elasticsearch, Kibana, Logstash) using another tool provided by Elastic - Filebeat. We will also briefly cover all preceding steps, such as the reasoning behind logging, configuring logging in Django and installing ELK stack.
Use python to build a Windows shortcut for launching conda environments.
Interesting Projects, Tools and Libraries
A framework, developed at Netflix, for real-life data science. Metaflow makes it quick and easy to build and manage real-life data science projects.
A managed TensorBoard experience that lets you upload and share your ML experiment results with anyone.
A Pythonic Object-Oriented Web Framework built on Flask.
How emojis are used on Twitter.
Lightbus allows your backend processes to communicate, run background tasks, and expose internal APIs. Lightbus uses Redis as its underlying transport, although support for other platforms may eventually be added.
cuSignal GPU-accelerates the popular SciPy Signal library with CuPy (GPU-accelerated NumPy) and custom Numba CUDA kernels.
Jupyter kernel for TLA⁺ and Pluscal specification languages.
Emacs Application Framework (EAF) is an application framework that extend GNU Emacs to an entire new universe of powerful GUI PyQt applications.
Aimed at Python beginners: replacing standard traceback by something easier to understand, translatable into various languages.
Simple, single-file deploy Django to an Ubuntu host.
A simple Python 3.5+ multitasking library.
A webapp for automatically managing a members and friends only Minecraft server.
Generate a network graph of connections from your WhatsApp groups data.
A simple library for writing and printing exam in Python.
New Releases
The release notes cover the raft of new features in detail, but a few highlights are:
Django 3.0 begins our journey to making Django fully async-capable by providing support for running as an ASGI application.
Django now officially supports MariaDB 10.1 and higher.
Custom enumeration types TextChoices, IntegerChoices, and Choices are now available as a way to define model field choices.
Upcoming Events and Webinars
There will be following talks
Setting up a simple Python server in AWS
Writing a Programming Language with Python
Data Visualization with Altair
There will be following talks
Go For Pythonistas
Python slice object
There will be following talks
Analyzing Housing First
Building microservices with Python and gRPC
NLP approach to extracting clinical findings from radiology reports using Python
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