Free Mac Downloads VirSCAN.org-多引擎在线病毒扫描网 v1.02，当前支持 37 款杀毒引擎 Redis 网易 CSDN.NET - 全球最大中文IT社区，为IT专业技术人员提供最全面的信息传播和服务平台 Twisted Twisted is an event-driven networking engine written in Python and licensed under the open source MIT license. Twisted runs on Python 2 and an ever growing subset also works with Python 3. Twisted makes it easy to implement custom network applications. from twisted.internet import protocol, reactor, endpoints class Echo(protocol.Protocol): def dataReceived(self, data): self.transport.write(data) class EchoFactory(protocol.Factory): def buildProtocol(self, addr): return Echo() endpoints.serverFromString(reactor, "tcp:1234").listen(EchoFactory()) reactor.run() Learn more about writing servers, writing clients and the core networking libraries , including support for SSL, UDP, scheduled events, unit testing infrastructure, and much more. Twisted includes an event-driven web server. Learn more about web application development, templates and Twisted's HTTP client. Here's a simple publish/subscribe server, where clients see all messages posted by other clients:
50 Great Examples of Data Visualization Wrapping your brain around data online can be challenging, especially when dealing with huge volumes of information. And trying to find related content can also be difficult, depending on what data you’re looking for. But data visualizations can make all of that much easier, allowing you to see the concepts that you’re learning about in a more interesting, and often more useful manner. Below are 50 of the best data visualizations and tools for creating your own visualizations out there, covering everything from Digg activity to network connectivity to what’s currently happening on Twitter. Music, Movies and Other Media Narratives 2.0 visualizes music. Liveplasma is a music and movie visualization app that aims to help you discover other musicians or movies you might enjoy. Tuneglue is another music visualization service. MusicMap is similar to TuneGlue in its interface, but seems slightly more intuitive. Digg, Twitter, Delicious, and Flickr Internet Visualizations
域名注册|域名查询|域名交易-Oray全球顶级域名注册服务商 Stackless Python An introduction for newcomers Stackless Python is an enhanced version of the Python programming language. It allows programmers to reap the benefits of thread-based programming without the performance and complexity problems associated with conventional threads. Improved program structure.More readable code.Increased programmer productivity. Features For all the convenience gained through using Stackless, there is really only a minimal amount of functionality exposed through the stackless module. Microthreads: tasklets wrap functions allowing them to be launched as microthreads.Channels channels can be used for bidirectional communication between tasklets.Scheduling a round robin scheduler is built in. Further reading material FAQ frequently asked questions.Examples: useful or descriptive pieces of code that shows Stackless functionality in use.Idioms common patterns in using Stackless Python in code.Applications some of the businesses and projects that Stackless Python has been used by.
About Twingly Twingly is a data mining company from Linköping that was founded in 2006. We focus on indexing blogs and strive towards the best coverage, quality and support of mainly European languages. Today we are indexing about 55M blogs from all over the world. Apart from the data mining business we also provide companies with solutions to encourage bloggers to blog more about their brand and products. We currently have over 100 customers in 16 countries, most of them in the sectors of Media, Ecommerce and Media Monitoring. Contact Twingly Short facts about Twingly Founded 2006 Headquartered in Linköping, Sweden Indexing about 55M blogs, mainly from Europe Offering blog data in over 30 different languages Have over 100 customers in 16 different countries Strong market penetration in the sectors of Media, Ecommerce and Media Monitoring Was ranked as one of the fastest growing technology companies in November 2011 by Deloitte Twingly office
Timing and Profiling in IPython Timing and profiling code is all sorts of useful, and it’s also just good ol’ fashioned fun (and sometimes surprising!). In this post, I’ll introduce how to do the following through IPython magic functions: %time & %timeit: See how long a script takes to run (one time, or averaged over a bunch of runs). %prun: See how long it took each function in a script to run. Please make sure you’re running IPython 0.11 or greater. $ pip install ipython $ ipython --version 0.13.1 Most of the functionality we’ll work with is included in the standard library, but if you’re interested in line-by-line or memory profiling, go ahead and run through this setup. $ pip install line-profiler $ pip install psutil $ pip install memory_profiler Next, create an IPython profile and extensions directory where we’ll configure a couple of missing magic functions: Create the following IPython extention files with the contents below to define the magic functions: ~/.ipython/extensions/line_profiler_ext.py And that’s it!
Fidg't: Your Social Networking Address Book Explore your network with the Fidg't Visualizer* The Fidg't Visualizer allows you to play around with your network. You interface with the Visualizer through Flickr and LastFM tags, using any tag to create a Magnet. Once a Tag Magnet is created, members of the network will gravitate towards it if they have photos or music with that same Tag. This simple mechanic lets you visualize your Network in a unique way, demonstrating its Predisposition towards certain things. For good measure, you can also search through the network for certain users, and check out their recent photos and music. The Fidg't Visualizer is in an alpha release. Windows users might need to download Java, which can be done here . *You can download and play with the Fidg't Visualizer even if you haven't created a Fidg't account. 8.1.07 Thanks to Casey Reas for putting our Visualizer up on the Processing Home Page.