Python Weekly (Issue 355 - July 12 2018)

Python Weekly - Issue 355Â

July 12, 2018

Python Weekly

Welcome to issue 355 of Python Weekly. Let's get straight to the links this week.

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Articles, Tutorials and Talks

This tutorial covers face clustering, the process of finding the unique faces in an unlabeled set of images. We accomplish our face clustering and identity recognition task using OpenCV, Python, and deep learning.

In this tutorial you'll learn how to use Python's rich set of operators, functions, and methods for working with strings. You'll learn how to access and extract portions of strings, and also become familiar with the methods that are available to manipulate and modify string data in Python 3.

DLTK, the Deep Learning Toolkit for Medical Imaging extends TensorFlow to enable deep learning on biomedical images. It provides specialty ops and functions, implementations of models, tutorials and code examples for typical applications. This post serves as a quick introduction to deep learning with biomedical images, where we will demonstrate a few issues and solutions to current engineering problems and show you how to get up and running with a prototype for your problem.

Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values. Time series are widely used for non-stationary data, like economic, weather, stock price, and retail sales in this post. We will demonstrate different approaches for forecasting retail sales time series. Let’s get started!

In our last post, we introduced Pandas on Ray with some preliminary progress for making Pandas workflows faster by requiring only a single line of code change. Since then, we have received a lot of feedback from the community and in response we worked to significantly improve the functionality and performance. In this blog post, we will go over a few of the lessons we learned along the way and talk about performance and how we plan to continue improving the library moving forward.

Let’s look at how to spin up a Docker Swarm cluster on Digital Ocean and then configure a microservice, powered by Flask and Postgres, to run on it.

Why you should use Django for e-commerce and the different tools available to do so. Bonus: a full Wagtail tutorial for a lean, mean e-commerce set up! Live demo and code repo included.

Randy Olson uses data science to learn whether batting order matters in Major League Baseball.

In this Pandas tutorial we will learn how to work with Pandas dataframes. More specifically, we will learn how to read and write Excel (i.e., xlsx) and CSV files using Pandas. We will also learn how to add a column to Pandas dataframe object, and how to remove a column. Finally, we will also learn how to subset and group our dataframe.

In Part 1 we covered the serverless basics and got our feet wet with the Serverless Framework. In this post, we’ll introduce a library that allows you to plug any web framework that speaks WSGI into serverless (pretty much all of them); and we’ll take a look at AWS’ own Python web framework for creating web APIs.

In the first part I discussed the general usage of the new dataclasses. This post deals with another feature : dataclasses.field .

You'll cover a handful of different options for generating random data in Python, and then build up to a comparison of each in terms of its level of security, versatility, purpose, and speed.

Interesting Projects, Tools and Libraries

GlobaLeaks is open-source / free software intended to enable secure and anonymous whistleblowing initiatives developed by the Hermes Center for Transparency and Digital Human Rights.

Python sample codes for robotics algorithms.

A beautiful python framework "for humans", enabling you to deliver a REST enabled micro-services from zero to production within minutes (no kidding: literally within minutes).

The right way to check the weather

A context-preserving word cloud generator.

A small tool that generates 640x640 gif of chess pgn.

Like man pages, but for HTTP status codes.

Django Impersonate Auth is a simple drop in authentication backend that allows superusers to impersonate regular users in the system.

Switchable Normalization is a normalization technique that is able to learn different normalization operations for different normalization layers in a deep neural network in an end-to-end manner.

Upcoming Events and Webinars

When it comes to managing your Python app's dependencies, you have more options than vanilla pip. In this talk we take two Python packaging heavyweights - Conda (by Continuum Analytics) and Pipenv (by Kenneth Reitz) and pitch them against each other in a head-to-head showdown complete with live demonstrations and esoteric challenges.

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