Python Weekly (Issue 357 - July 26 2018)

Python Weekly - Issue 357

July 26, 2018

Python Weekly

Welcome to issue 357 of Python Weekly. Let's get straight to the links this week.

From Our Sponsor 

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News

Visual Studio has long been recognized for the quality of its IntelliSense (code analysis and suggestions) across all languages, and has had support for Python since 2011. We are pleased to announce that we are going to be making the Python support available to other tools as the Microsoft Python Language Server. It is available first in the July release of the Python Extension for Visual Studio Code, and we will later release it as a standalone component that you can use with any tool that works with the Language Server Protocol.

Articles, Tutorials and Talks

You will learn how to perform simple object tracking using OpenCV, Python, and the centroid tracking algorithm used to track objects in real-time.

What is it about Pandas that has data scientists, analysts, and engineers raving? This is a guide to using Pandas Pythonically to get the most out of its powerful and easy-to-use built-in features. Additionally, you will learn a couple of practical time-saving tips.

What if you could train and serve your object detection models even faster? We’ve heard your feedback, and today we’re excited to announce support for training an object detection model on Cloud TPUs, model quantization, and the addition of new models including RetinaNet and a MobileNet adaptation of RetinaNet. You can check out the announcement post on the AI blog. In this post, we’ll walk you through training a quantized pet breed detector on Cloud TPUs using transfer learning.

In this post, you will learn how to create a Celery task inside a Django project in a Docker container. Sounds awesome, right?

A complete guide to documenting Python code. Whether you're documenting a small script or a large project, whether you're a beginner or seasoned Pythonista, this guide will cover everything you need to know.

This video talks a little about how the annotate feature works in Django and show some examples.

This article illustrates how you can build your own Duplex-like agent to handle phone calls autonomously. We’re going to approach the problem at hand from the other direction — calling a business and talking with a machine (rather than a machine calling a business).

A Gentle Introduction to Natural Language Processing.

The purpose of this post is to unpack to the layman the basic concepts of applied machine learning and to document how data scientists or data analysts would generally answer a question or solve a problem with data and machine learning algorithms.

Python Jobs of the Week

Quora is looking for a Machine Learning engineer to join their growing Engineering team. The ideal candidate will have 5+ years of experience in Machine Learning or a related field and be able to take end to end ownership of our Machine Learning systems - improving and identifying new opportunities. See if you're a good match for this role

(Make sure you select Quora as one of your desired companies)

Allume is an online styling service for busy professional women. We combine human connection and data science to provide a WOW experience that clients can’t get other places. Our overall tech-stack is mainly composed of Python/Django, Redis, Docker, Celery and is hosted on AWS. We are seeking a developer who is excited to join a small, early-stage team where he/she can be a critical part of designing and building out this critical infrastructure.

Interesting Projects, Tools and Libraries

Data Version Control or DVC is an open source tool for data science projects. It helps data scientists manage their code and data together in a simple form of Git-like commands.

Incredibly fast crawler which extracts urls, emails, files, website accounts and much more.

Diffy is a triage tool used during cloud-centric security incidents, to help digital forensics and incident response (DFIR) teams quickly identify suspicious hosts on which to focus their response.

An open source software framework for quantum computing.

Content aware image resizing.

MNE-Python software is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, and statistics.

Serialization / De-serialization support for the SQLAlchemy Declarative ORM.

Build a REST API with Flask and marshmallow.

Strawberry Fields is a full-stack Python library for designing, simulating, and optimizing continuous variable (CV) quantum optical circuits.

A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits.

Layer Linter checks that your project follows a layered architecture that you define.

New Releases

NumPy 1.15.0 is a release with an unusual number of cleanups, many deprecations of old functions, and improvements to many existing functions. Please read the detailed descriptions to see if you are affected.

Some highlights includes

  • python 3.7 support.

  • beta pypy support. See Are we pypy yet?.

  • pygame.draw fixes

  • pygame.math is not experimental anymore. Speedups and bugfixes.

  • Debian, Mac homebrew, mac virtualenv, manylinux and other platform fixes.

  • Documentation fixes, jedi support for type ahead in editors like VSCode and VIM.

  • Surface.blits for blitting many surfaces at once more quickly.

Upcoming Events and Webinars

You are invited to join 500+ devs to learn about Python, data, infrastructure, and performance from core Python devs such as Raymond Hettinger, Travis Oliphant, Yury Selivanov, Carol Willing, Brandon Rhodes, Simon Wilison. The speaker lineup also includes CTOs from up and coming startups and senior devs from Google, Linkedin, Facebook, Yelp, Twitter, Microsoft, Amazon. Make some new friends at the opening party and PyMaker Fest.  Share your knowledge and deliver a lightning talk and/or a meetup. See why past attendees say #mindblown and #AwesomeCommunity after PyBay :)

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