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Python Weekly 231

News

PyData London 2016 Call For Proposals
PyData welcomes presentations focusing on Python as well as other languages used in data science (e.g. R, Julia). Presentation content can be at a novice, intermediate or advanced level. Talks will run 30-40 min and hands-on tutorials will run 90-120 min.

Announcing the Keynote Speakers for PyCon 2016


Articles, Tutorials and Talks

Python for Live Music
At Les Chemins de Traverse we explore ways of "augmenting" acoustical musical instruments with new possibilities offered by computers. For doing so, we need ultra-low latency real-time audio processing programs. Pretty much the typical situation where python should *not* be used, right? Wrong. We've recently included python (with a strong use of Olivier Bélanger's wonderful pyo module) in our set of tools for realizing the musical ideas we have in mind. This talk will expose why we came to consider python as a very interesting option for our realtime audio systems and how we use it on stage, with code and sound samples.

Raspberry Pi & Python I2C Deep Dive with TonyD! 
A video that does deep dive into the I2C protocol and how to use it from Python with a Raspberry Pi.

Episode #46: Python in Movies and Entertainment
What did you experience the last time you watched a movie in a theater? Were you captivated by fast-paced action and special effects? Deeply moved by the characters that came to life during those two hours when the outside world just melted away? Yeah, movies are still magical. What was likely not top of mind was all the work that went into that movie, from the editing of the audio and video, the special effects, renderings, and coordination of maybe 100's of creative professionals. It turns out that Python plays a key role in coordinating all of this production work and that's what this episode is all about. Join me as I talk with Rob Blau from Autodesk about Python in the movies and entertainment business.

Signal Processing with GW150914 Open Data
This ipython notebook (or associated python script GW150914_tutorial.py ) will go through some typical signal processing tasks on strain time-series data associated with the LIGO GW150914 data release from the LIGO Open Science Center (LOSC).

Calling C Libraries from Numba Using CFFI
The python CFFI library provides an easy and efficient way to call C code from within a function jitted (just-in-time compiled) by Numba. This makes it simple to produce fast code with functionality that is not yet available directly in Numba. As a simple demonstration, I wrap several statistical functions from the Rmath library.

Sense2vec with spaCy and Gensim
If you were doing text analytics in 2015, you were probably using word2vec. Sense2vec is a new twist on word2vec that lets you learn more interesting, detailed and context-sensitive word vectors. This post motivates the idea, explains our implementation, and comes with an interactive demo that we've found surprisingly addictive.

Episode 44 - Airflow with Maxime Beauchemin
Are you struggling with trying to manage a series of related, interdependent batch jobs? Then you should check out Airflow. In this episode we spoke with the project's creator Maxime Beauchemin about what inspired him to create it, how it works, and why you might want to use it. Airflow is a data pipeline management tool that will simplify how you build, deploy, and monitor your complex data processing tasks so that you can focus on getting the insights you need from your data.

A recommendation system for blogs: Content-based similarity (part 2)
In this second post in a series of posts about a content recommendation system for The Marketing Technologist (TMT) website we are going to elaborate on the concept of content-based recommendation systems. In the first post we described the benefits of recommendation systems and we roughly divided them in two different types of recommenders: content-based and collaborative filtering. The first post also described the prerequisites in order to set-up both types of recommenders. In this article we take our first steps in content-based recommendation systems by describing a quantified approach to express the similarity of articles.

Ian Cordasco - Betamax (PTP013)
Testing apps that use requests without using mock.

Making Python on Hadoop Easier with Anaconda and Cloudera
This post will show you how to install and configure the Anaconda parcel, as well as provide an example of training a scikit-learn model on a single node and then using the model to make predictions on data in a cluster.

Technical writing with sphinx

Python Mocking 101: Fake It Before You Make It

Introducing Dask distributed


Books

Spark for Python Developers


To begin with, you will learn the most effective way to install the Python development environment powered by Spark, Blaze, and Bookeh. You will then find out how to connect with data stores such as MySQL, MongoDB, Cassandra, and Hadoop. You'll expand your skills throughout, getting familiarized with the various data sources (Github, Twitter, Meetup, and Blogs), their data structures, and solutions to effectively tackle complexities. You'll explore datasets using iPython Notebook and will discover how to optimize the data models and pipeline. Finally, you'll get to know how to create training datasets and train the machine learning models.


Interesting Projects, Tools and Libraries

Laboratory
A Python library for carefully refactoring critical paths (and a port of Github's Scientist)

BigchainDB
A scalable blockchain database. It combines the key benefits of distributed DBs and traditional blockchains, with an emphasis on scale. It is built on top of an enterprise-grade distributed DB, from which BigchainDB inherits high throughput, high capacity, a full-featured NoSQL query language, efficient querying, and permissioning.

curses-menu


A simple Python menu-based GUI system on the terminal using curses. Perfect for those times when you need a GUI, but don't want the overhead or learning curve of a full-fledged GUI framework.

dynaconf
The dynamic configurator for your Python Project. It can read settings variables from a set of different data stores such as python settings files, environment variables, redis, memcached, ini files, json files, yaml files and you can customize dynaconf loaders to read from wherever you want.

Thunder


Thunder is a library for analyzing large-scale spatial and temporal data. It's fast to run, easy to extend, and designed for interactivity. It is built on Spark, a new framework for cluster computing. Thunder includes utilities for loading and saving different formats, classes for working with distributed spatial and temporal data, and modular functions for time series analysis, factorization, and model fitting. Analyses can easily be scripted or combined. It is written against Spark's Python API (Pyspark), making use of scipy, numpy, and scikit-learn.

watson-word-watcher
A proof of concept using IBM's Speech-to-Text API to do quick-and-dirty transcriptions.

GeosPy
Highly optimized geolocation inference package for spatial approximation.

isign
A tool and library to re-sign iOS applications, without proprietary Apple software. For example, an iOS app in development would probably only run on the developer's iPhone. isign can alter the app so that it can run on another developer's iPhone. Apple tools already exist to do this. But with isign, now you can do this on operating systems like Linux.

gwpy


Package for analysing and characterising gravitational wave data in python.

pocket-cli
Pocket-CLI is an application for reading / listing and managing your GetPocket.com articles from the terminal.

hyperop
hyperop is a small library for representing really, really, ridiculously large numbers in pure python. It does so using hyperoperations.

Js2Py
JavaScript to Python Translator & JavaScript interpreter written in 100% pure Python.

fam
A simple Python ORM for CouchDB and Couchbase Sync Gateway.

spellbook
Search and store command lines.

django-field-history
A Django app to track changes to a model field.

 

         
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