Python Weekly (Issue 396 May 9 2019)

Python Weekly - Issue 396

May 09, 2019

Python Weekly

Welcome to issue 396 of Python Weekly. Let's get straight to the links this week.

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Articles, Tutorials and Talks

The goal of this project is to build a web scraper that will run and perform searches on flight prices with flexible dates (up to 3 days before and after the dates you select first), for a particular destination. It saves an excel with the results and sends an email with the quick stats. Obviously, the objective is to help us find the best deals!

In this video, Guido van Rossum, the creator of Python talk about the origin of the language and why he stepped down from the leadership of the very project he created.

Check out a cool project that leverages Stack Overflow Data and Google's Cloud AI to predict what tags would work best on Stack Overflow questions.

This Python 3 tutorial course aims to teach everyone the basics of programming computers using Python. The course has no pre-requisites and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course.

How Machine Learning Can Help You Charge Your E-Scooters.

Complete guide to Python package creation, automated testing and deployment.

Using fbprophet to predict the number of public Jupyter Notebooks on Github for the next 2 years.

Currently there are guides out there on how to deploy JupyterHub on Kubernetes using native cloud services. How about if you just wanted to just use a single cloud instance? Or even an on-premise solution? This guide will cover how to host your own JupyterHub on a single bare metal instance.

Many Python developers are unaware of the extent to which you can use functional programming in Python, which is a shame: with few exceptions, functional programming allows you to write more concise and efficient code. Moreover, Python’s support for functional programming is extensive.   Here I'd like to talk a bit about how you can actually have a functional approach to programming with our favorite language.

How to connect an SSL-enabled MongoDB replica set with self-signed certificates using PyMongo, and testing MongoDB failover behavior in your Python app code.

In this post, I will guide you through the main reasons why PyTorch makes it much easier and more intuitive to build a Deep Learning model in Python — autograd, dynamic computation graph, model classes and more — and I will also show you how to avoid some common pitfalls and errors along the way.

Interesting Projects, Tools and Libraries

ZFS, in Python, without reading the original C.

Building Your NLP DNN Models Like Playing Lego.

Geomancer is a geospatial feature engineering library. It leverages geospatial data such as OpenStreetMap (OSM) alongside a data warehouse like BigQuery. You can use this to create, share, and iterate geospatial features for your downstream tasks (analysis, modelling, visualization, etc.).

Declarative access policies/permissions modeled after AWS' IAM policies.

Algorithms for monitoring and explaining machine learning models.

A LiveView library for Django.

Neural Architecture Search Powered by Swarm Intelligence.

New Releases

Upcoming Events and Webinars

Dash is an annual conference about building and scaling the next generation of applications, infrastructure, and technical teams. The two-day conference brings together more than 1,200 engineers across dev and ops who are taking their systems and organizations to the next level of velocity, performance, reliability, and scale. Dash features a mix of speaking sessions, hands-on labs and trainings, and opportunities to make new connections and exchange ideas.

There will be following talks

  • Intro to Python: Building A Hangman Game

  • Discovering your purpose

  • Python for Kids, how to encourage your kid to problem solve with Python

Meet other PyLadies at Flatiron Health and learn about data analysis using Python! Using Jupyter notebook and Pandas we will explore oncology treatment data. You will not only get an introduction to data analysis using Pandas, but also get a glimpse of the kind of healthcare data that engineers at Flatiron wrangle on a daily basis.

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