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[] Today we'll look at performing parallel computations with IPython.

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Much of this material will draw from resources available online, including Parallel computing is generally very difficult, and IPython provides primitives for a number of scenarios, including: Single program, multiple data (SPMD) parallelismMultiple program, multiple data (MPMD) parallelismTask farmingData parallel computationCoordination of distributed processesCombinations of these approachesCustom user defined approaches In addition, IPython parallel includes tools for executing parallel jobs interactively (this is the "I" in "IPython"). First... One common complaint levied against IPython is that it's too bloated. More about interactive graphs using Python, d3.js, R, shiny, IPython, vincent, d3py, python-nvd3. I recently found this url The Big List of D3.js Examples.

More about interactive graphs using Python, d3.js, R, shiny, IPython, vincent, d3py, python-nvd3

As d3.js is getting popular - their website is pretty nice -, I was curious if I could easily use it through Python. After a couple of searches (many in fact), I discovered vincent and some others. It ended up doing a quick review. Every script was tested with Python 3. Contents: If you want to easily produce a html file including javascript (to publish it on your website for example), you only need to look at sections Graphs with Python and d3py, Graphs with IPython and nvd3. Use of IPython (qt)console The QtConsole looks like a command line window but is able to display images inline using matplotlib: You can enable it by using the following steps: Install pyqt (only once, Windows users can go there)Go to <Python folder>/Scripts and type ipython3 qtconsoleIn the console, type %matplotlib inline To test it is working, you can type and press enter: %load Use of IPython notebook.

Pylab_examples example code: gradient_bar.py — Matplotlib 1.4.3 documentation. (Source code, png, hires.png, pdf)

pylab_examples example code: gradient_bar.py — Matplotlib 1.4.3 documentation

Web Applications. As a powerful scripting language adapted to both fast prototyping and bigger projects, Python is widely used in web application development.

Web Applications

Context The Web Server Gateway Interface (or “WSGI” for short) is a standard interface between web servers and Python web application frameworks. By standardizing behavior and communication between web servers and Python web frameworks, WSGI makes it possible to write portable Python web code that can be deployed in any WSGI-compliant web server. WSGI is documented in PEP 3333. Frameworks Broadly speaking, a web framework consists of a set of libraries and a main handler within which you can build custom code to implement a web application (i.e. an interactive web site).

URL Routing Matches an incoming HTTP request to a particular piece of Python code to be invoked Request and Response Objects Encapsulate the information received from or sent to a user’s browser Template Engine Development Web Server Django Flask. WebFrameworks. A Web framework is a collection of packages or modules which allow developers to write Web applications (see WebApplications) or services without having to handle such low-level details as protocols, sockets or process/thread management.

WebFrameworks

The majority of Web frameworks are exclusively server-side technology, although, with the increased prevalence of AJAX, some Web frameworks are beginning to include AJAX code that helps developers with the particularly tricky task of programming (client-side) the user's browser. At the extreme end of the client-side Web Frameworks is technology that can use the web browser as a full-blown application execution environment (a la gmail for example): see Web Browser Programming for details. Generally, frameworks provide support for a number of activities such as interpreting requests (getting form parameters, handling cookies and sessions), producing responses (presenting data as HTML or in other formats), storing data persistently, and so on.

Développer une WebApp en Python. Python: It's a Trap - The Hiltmon. TL;DR: Python is the best language for quantitative scripting (because of its libraries).

Python: It's a Trap - The Hiltmon

But it’s a trap. Almost all programmers and libraries require Python 2 when Python 3 is out and way better. Choosing to use an old language for new project traps us into supporting old languages, libraries and platforms. Python 3 Is Killing Python - the zero bit stream. Python 3 is easily the worst thing to happen to the Python community.

Python 3 Is Killing Python - the zero bit stream

I remember when I first used Python, I had been spending a lot of time in C++ land, and Python was like a revelation. I could open up a text editor and have a working program in seconds or minutes, not hours or days. I remember when Python 2.5 came out with a lot of neat new language features. Python 3 is killing Python. TL;DR Imo specific evidence directly contradicts chromatic's assertions about the intentions, plans and actions of the Rakudo dev leads (Patrick and jnthn).

Python 3 is killing Python

My assessment, and chromatic's too I think, is there was a growing breakdown in trust that blew up in 2011 with serious consequences for both Rakudo and Parrot. > When Rakudo announced it wanted to rewrite NQP to run on multiple backends. 18.5. asyncio – Asynchronous I/O, event loop, coroutines and tasks — Python 3.4.2 documentation. Source code: Lib/asyncio/ This module provides infrastructure for writing single-threaded concurrent code using coroutines, multiplexing I/O access over sockets and other resources, running network clients and servers, and other related primitives.

18.5. asyncio – Asynchronous I/O, event loop, coroutines and tasks — Python 3.4.2 documentation

Here is a more detailed list of the package contents: Asynchronous programming is more complex than classical “sequential” programming: see the Develop with asyncio page which lists common traps and explains how to avoid them. Enable the debug mode during development to detect common issues. Table of contents: Twisted 14.0.2. Twisted is an event-driven networking engine for Python.

Twisted 14.0.2

Twisted implements a variety of networking and communication protocols and exposes them all as method-calls on your Python objects. Client and server implementations are provided for various standard protocols, including: HTTP (twisted.web)IMAP, POP, SMTP (twisted.mail)DNS (twisted.names)TLS (core)SSH, Telnet (twisted.conch)IRC, XMPP, OSCAR (twisted.words)Ethernet, IP, TUN/TAP (twisted.pair)NMEA (twisted.positioning) Downloads (All Versions): 7736 downloads in the last day 50155 downloads in the last week 153251 downloads in the last month. Testing Your Code. Testing your code is very important. Getting used to writing the testing code and the running code in parallel is now considered a good habit. Used wisely, this method helps you define more precisely your code’s intent and have a more decoupled architecture. Some general rules of testing: A testing unit should focus on one tiny bit of functionality and prove it correct.Each test unit must be fully independent.

Each of them must be able to run alone, and also within the test suite, regardless of the order they are called. The Basics Unittest unittest is the batteries-included test module in the Python standard library. Pip 1.5.6. Package Index > pip > 7.1.2 Not Logged In Status Nothing to report pip 7.1.2 Downloads ↓ The PyPA recommended tool for installing Python packages. The PyPA recommended tool for installing Python packages. Downloads (All Versions): 135127 downloads in the last day 908543 downloads in the last week 3055229 downloads in the last month Website maintained by the Python community Real-time CDN by Fastly / hosting by Rackspace / design by Tim Parkin. Jinja2 (The Python Template Engine) Online Python Tutor - Learn programming by visualizing code execution. The IPython Notebook — IPython.

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