Python Weekly (Issue 386 February 28 2019)

Python Weekly - Issue 386

February 28, 2019

Python Weekly

Welcome to issue 386 of Python Weekly. Let's get straight to the links this week.

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Articles, Tutorials and Talks

Learn how to build a data analysis library from scratch in Python. Immerse yourself into a comprehensive project with 40 steps and 100 tests that you must pass in order to complete. We are building Pandas Cub, a library with similar functionality as the Pandas library.

Analyzing images with code can be difficult. How do you make your code "understand" the context of an image?

Making an open source Python package may sound daunting, but you don’t need to be a grizzled veteran. You also don’t need an elaborate product idea. You do need persistence and time. Hopefully this guide will help you need less of both.

Wondered how Google comes up with movies that are similar to the ones you like? After reading this post you will be able to build one such recommendation system for yourself.

Automatic setting-up, getting help effectively, collaborative programming, and version control. A one-stop solution to the pain points in Python beginners’ practice.

This is the first of the series where we will be writing our own Python framework just like Flask and Django. In this part, we will implement the features: WSGI compatible, Request Handlers and Routing: simple and parameterized

  • Part II - In the second part of the series, we will implement the features: Check for duplicate routes, Class Based Handlers and Unit tests.

In this article we are going to discuss the most important data structures in python. How they work, when to use them and how to use them. We will even cover a little bit of Big-O notation which helps to describe effectiveness of algorithms and data structures.

Let’s have a look at a simple piece of Python code that I have both accidentally written and seen in code reviews which does an entirely different thing than expected.

Python Jobs of the Week

You will work directly with the co-founders (CEO and CTO) to build out our backend systems. We are looking for an experienced python developer with production experience building and maintaining flask apps that use sqlalchemy and mysql. We are deployed to aws fargate and prefer managed services to our own infrastructure.

As a Data Engineer, you will be an essential part of our Data team, inspiring and sharing your expertise with your colleagues. You will be working closely with a number of other teams too, including data science, engineering, and game teams, to ensure that we can collect and action the data in the best possible way.

Interesting Projects, Tools and Libraries

privacyIDEA is an open solution for strong two-factor authentication like OTP tokens, SMS, smartphones or SSH keys. Using privacyIDEA you can enhance your existing applications like local login (PAM, Windows Credential Provider), VPN, remote access, SSH connections, access to web sites or web portals with a second factor during authentication.

Meltano is an open source convention-over-configuration product for the whole data lifecycle, all the way from loading data to analyzing it.

Beautiful Python prompts made simple. Build a prompt like stacking blocks. 

Face Editing Generative Adversarial Network with User's Sketch and Color.

Automagically synchronize subtitles with video.

Polystores is an abstraction and a collection of clients to interact with cloud storages.

An OwO based, stack-oriented programming language.

Download a single directory/folder from a GitHub repo.

An optimizer that trains as fast as Adam and as good as SGD.

Statistical analysis of VKontakte and Telegram message history.

New Releases

Upcoming Events and Webinars

There will be following talks

  • Copilot @ Xaxis: Using Python and Airflow to Enable AI on Ad Tech Data at Scale

  • Bringing state of the art NLP stack for conversational AI to production settings

  • Runway: Adding machine learning capabilities to design and creative platforms

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