Python Weekly (Issue 391 April 4 2019)

Python Weekly - Issue 391

April 04, 2019

Python Weekly

Welcome to issue 391 of Python Weekly. Let's get straight to the links this week.

From Our Sponsor 

Datadog's Service Map helps you visualize interdependencies between services so you can quickly understand the architecture of your Python applications.

 

Articles, Tutorials and Talks

In this article I'll develop Python code that will take me from an idea for a protein all the way to expression of the protein in a bacterial cell, all without touching a pipette or talking to a human. The total cost will only be a few hundred dollars! Using Vijay Pande from A16Z's terminology, this is Bio 2.0.

There are many ways to share a static Jupyter notebook with others, such as posting it on GitHub or sharing an nbviewer link. However, the recipient can only interact with the notebook file if they already have the Jupyter Notebook environment installed. But what if you want to share a fully interactive Jupyter notebook that doesn't require any installation? Or, you want to create your own Jupyter notebooks without installing anything on your local machine? In this post, I'm going to review six services you can use to easily run your Jupyter notebook in the cloud.

Over the last few weeks, I have been curious on how I could use data within my own life. On my day job, I use data to help make better decisions in a corporate setting so I figured, why not use data currently available to me to set metrics and targets for a healthier living? In these series, I will go through A. Introduction, B. Exploring the Data C. Analysis & Plotting, D. Testing, and E. Conclusion.

This can be useful to anyone looking to host a Flask app on AWS with Docker, but more specifically this will deal with many of the hurdles involved with putting this app into production while analyzing Google Analytics API data, visualizing with Plotly Dash, and version controlled with Amazon Elastic Container Registry (ECR).

In this post we explain the basic concept and general usage of RoI (Region of Interest) pooling and provide an implementation using Keras layers and the TensorFlow backend.

Scaling Interactive Pandas Workflows with Modin.

In this video we'll be looking into how we can use pyqt5 designer to create quick gui application with the drag and drop interface. The example will be a registration form with some event handling.

Interesting Projects, Tools and Libraries

PyTorch-BigGraph (PBG) is a distributed system for learning graph embeddings for large graphs, particularly big web interaction graphs with up to billions of entities and trillions of edges.

Cartography is a Python tool that consolidates infrastructure assets and the relationships between them in an intuitive graph view powered by a Neo4j database.

Visualize ROS topics inside a terminal with Unicode/ASCII art.

Audio visualizer using the MacBook keyboard lights.

Python library for Representation Learning on Knowledge Graphs.

Computer generated photomontage from video.

A Unified Panoptic Segmentation Network.

A fun and simple Python package that allows you to work with highly detailed nutrition data.

socialscan offers accurate and fast checks for email address and username usage on online platforms. Given an email address or username, socialscan returns whether it is available, taken or invalid on online platforms. Its speed also makes it suitable for bulk queries involving hundreds of usernames and email addresses.

A Wake-on-LAN tool written in Python.

New Releases

All-new direct Jupyter Notebook editing and running, a keymap for Sublime Text, and much more.

Django 2.2 is designated as a long-term support release. It will receive security updates for at least three years after its release. Support for the previous LTS, Django 1.11, will end in April 2020.

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