Python Weekly No 217

Articles, Tutorials and Talks

Podcast.__init__ Episode 29 - Anthony Scopatz on Xonsh
Anthony Scopatz is the creator of the Python shell Xonsh in addition to his work as a professor of nuclear physics. In this episode we talked to him about why he created Xonsh, how it works, and what his goals are for the project. It is definitely worth trying out Xonsh as it greatly simplifies the day-to-day use of your terminal environment by adding easily accessible python interoperability.

Advanced Jupyter Notebook Tricks -- Part I
The Part 1 describes how to use Jupyter to create pipelines and reports.

Teardown: Refactoring Search from Monolith to Microservice
This post explains the technical choices we made while refactoring our search feature from a component within a monolithic Django project into a microservice. It explores our efforts to break dependence on a shared database, use central authentication and plan for redundancy, among other things.

Building Data Pipelines with Python and Luigi
This post will discuss some experience in building data pipelines, e.g. extraction, cleaning, integration, pre-processing of data, in general all the steps that are necessary to prepare your data for your data-driven product. In particular, the focus in on data plumbing, and how a workflow manager like Luigi can come to the rescue, without getting in your way. With a minimal effort, the transition from prototype to production can be smoother.

The Geography of Basketball: Mapping NBA Shotcharts in ArcGIS
There are a lot of great blog posts out there about techniques to get and plot basketball data using the NBA stats API. This post shows how you can use Python to push this data into a Geographic Information System, ArcGIS. From there, you can leverage concepts, tools, and applications that are generally reserved for geography and geographers to make some great visuals from NBA player shot chart data.

Deep Learning for Visual Question Answering

This post talks about the Visual Question Answering problem, and also present neural network based approaches for same.

Five Hundred Deep Learning Papers, Graphviz and Python

Let's Build A Simple Interpreter. Part 6.

Getting Started with OpenCV and Python: Featuring The Martian

Building Simple Command Line Interfaces in Python


Books

Getting Started with Python and Raspberry Pi

Learn to design and implement reliable Python applications on the Raspberry Pi using a range of external libraries, the Raspberry Pis GPIO port, and the camera module.


Interesting Projects, Tools and Libraries

curio
Curio is a modern library for performing reliable concurrent I/O using Python coroutines and the explicit async/await syntax introduced in Python 3.5. Its programming model is based on cooperative multitasking and common system programming abstractions such as threads, sockets, files, subprocesses, locks, and queues. Under the covers, it is based on a task queuing system that is small, fast, and powerful.

confidant
Confidant is a open source secret management service that provides user-friendly storage and access to secrets in a secure way, from the developers at Lyft.

worldengine

World generator using simulation of plates, rain shadow, erosion, etc.

dive-into-machine-learning
Dive into Machine Learning with Jupyter and scikit-learn.

neural-storyteller
A recurrent neural network for generating little stories about images.

Harvey
Harvey is a command line legal expert who manages license for your open source project.

RemI
Python REMote Interface library. Platform indipendent. In less than 100 Kbytes, perfect for your diet.

aioodbc
A library for accessing a ODBC databases from the asyncio.

sklearn-deap
Use evolutionary algorithms instead of gridsearch in scikit-learn. This allows you to exponentially reduce the time required to find the best parameters for your estimator. Instead of trying out every possible combination of parameters, evolve only the combinations that give the best results.

oscrypto
Compilation-free, always-patched, Python crypto library for OS X, Windows and Linux/BSD.

sentimentAPI
A fast python scikit-learn text sentiment API server.

sops
sop is an editor of encrypted files that supports YAML, JSON and TEXT formats and encrypts with AWS KMS and PGP (via GnuPG). 


New Releases

PyCharm 5
PyCharm 5 brings an outstanding lineup of new features, including full Python 3.5 support, Docker integration, Thread Concurrency Visualization, code insight for Django ORM methods, Conda integration, and IPython Notebook v4 support, just to name a few.

Django 1.8.6
Django 1.8.6 adds official support for Python 3.5 and fixes several bugs in 1.8.5.

Anaconda 2.4

matplotlib-1.5