Python Weekly No 204

Python Weekly No 204

News

PEP 0501 -- Translation ready string interpolation
This PEP agrees with the basic motivation of PEP 498 , but proposes to focus both the syntax and the implementation on the il8n use case, drawing on the previous proposals in PEP 292 (which added string.Template) and its predecessor PEP 215 (which proposed syntactic support, rather than a runtime string manipulation based approach). 

PyCon Canada 2015 Call for Proposals
We want to host your talk! You are invited to present your latest Python related projects, work and experiences to fellow Pythonistas. 


Articles, Tutorials and Talks

Episode #20: Interactive Python and Teaching Python: Beyond Text Books
What if your computer science textbooks could run their python code samples and that code ran directly in your browser, kinda like JavaScript but better, because: Python. It is possible and Brad Miller is making it happen! This episode is all about Brad Miller's work at Runestone Interactive where they are building the next generation of interactive textbooks for computer science students and the rest of us. As a cool side-effect, Brad is now maintaining Skulpt, one of the leading implementations of Python that runs in your browser! 

Episode 18 - Liza Avramenko Talks About CheckIO
In this episode we talked to Liza Avramenko, the CEO of CheckIO, about Empire of Code and CheckIO. We discussed what differentiates them from each other and from the other coding games that have been spreading on the internet. One of the main differentiators for CheckIO in particular is the strong focus on community. The bottom line is that if you use Python then you should check out CheckIO and Empire of Code as a great way to practice your skills.

Speeding up non-vectorizable code with Cython
Most people know that when working with numeric arrays in Python, it is almost always faster to use vectorized operations instead of loops. But what happens when there's no obvious way to vectorize a slow function? There are many approaches for speeding up code, and plenty of other great posts on the subject. This is just a simple example with Cython.

Bayesian optimisation for smart hyperparameter search
Fitting a single classifier does not take long, fitting hundreds takes a while. To find the best hyperparameters you need to fit a lot of classifiers. What to do? This post explores the inner workings of an algorithm you can use to reduce the number of hyperparameter sets you need to try before finding the best set. 

Ibis Design: Modeling high level analytics tasks
Outside of scalability and high performance on large data sets with Python, Ibis is focused on simplifying analytics tasks for end users. By designing a rich pandas-like domain specific language (DSL) embedded in Python code, we can hide away the complexities normally associated with expressing analytical concepts in SQL or some other tool. This post gives some specific examples and shows how we're solving them in Ibis.

Let's Build A Simple Interpreter. Part 3.
This part talks about how to parse (recognize) and interpret arithmetic expressions that have any number of plus or minus operators in it.

Composing Music With Recurrent Neural Networks

PyData Seattle Videos

Data Science with Python & R: Sentiment Classification Using Linear Methods

Building a Dynamic Static Website with Pelican & IFTTT

Google’s Deep Dream in PyCharm 

Books

Learning Data Mining with Python
This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. Next, we move on to more complex data types including text, images, and graphs. In every chapter, we create models that solve real-world problems.


Interesting Projects, Tools and Libraries

nolearn
nolearn contains a number of wrappers and abstractions around existing neural network libraries, most notably Lasagne, along with a few machine learning utility modules. All code is written to be compatible with scikit-learn.

Batavia
Tools to run Python bytecode in the browser.

Flake8Lint
Python Flake8 Lint is a Sublime Text 2/3 plugin for check Python files against some of the style conventions in PEP8, PEP257, PyFlakes, mccabe and pep8-naming.

Shoop
Shoop is an open source e-commerce platform based on django and python.

subuser
Run programs in linux with selectively restricted permissions. 

krill
Krill are filter feeders. It aggregates feed items from all sources you specify, filters out those that interest you, and displays them as a live stream :fire: of clean, legible command line output.

django-js-reverse
Django JS Reverse is a small django app that makes url handling of named urls in javascript easy and non-annoying.

ScratchABit
Easily retargetable and hackable interactive disassembler with IDAPython-compatible plugin API.

Hug
Hug aims to make developing Python driven APIs as simple as possible, but no simpler. As a result, it drastically simplifies Python API development.

CredCrack
CredCrack is a fast and stealthy credential harvester. It exfiltrates credentials in memory and in the clear without ever touching disk. Upon obtaining credentials, CredCrack will parse and output the credentials while identifying any domain administrators obtained. CredCrack also comes with the ability to list and enumerate share access and yes, it is threaded!

angr 
Angr is a platform-agnostic binary analysis framework developed by the Computer Security Lab at UC Santa Barbara and their associated CTF team, Shellphis.

netimpair
An easy-to-use network impairment script for Linux written in Python.

wharfee
A CLI with autocompletion and syntax highlighting for Docker commands.


New Releases

Cython 0.23
This is a major feature release. Highlights include, in addition to several important bug fixes: 

• PEP 492 (async/await) and PEP 448 (star-unpacking generalizations) 
• inlined generator expressions 
• support for the C++ assignment and bool() operators 
• support for coverage analysis 

IPython 4.0 Released

Python 3.5.0rc1


Upcoming Events and Webinars

Webinar: Automate boring keyboard and mouse tasks with Python GUI
Sometimes an application or service doesn't support an API or batch processing. But you can still automate tasks with code that directly controls the mouse and keyboard. In this webcast, Al Sweigart covers the Python GUI automation techniques described in his latest book, Automate the Boring Stuff with Python. 

Webinar: Explore algorithms in Python with a GUI-based app 
Algorithms are at the heart of Computer Science and they have a very real practical impact for Software Engineers. Too often, textbooks and Internet resources contain just the final code that implements an algorithm without any explanation or guidelines on how it was designed and implemented. In this webcast, I will demonstrate the principles behind kd-trees and how they can be used to solve a number of interesting problems, such as nearest neighbor and range queries. I will implement a GUI-based application that draws the kd-tree as points are inserted and performs nearest neighbor queries.