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• Python ThreadedTCPServer : "Name or service not known"

  11 avril 2014, par Hal

  I was developing a ThreadedTCPServer to communicate with a PHP application also residing in this same machine. This is suppose to receive requests from this PHP app and to convert some videos locally using ffmpeg.

  Here's the code :

  # -*- coding: utf-8 -*- 
  
  import os
  
  import socket
  
  import threading
  
  import logging.config
  
  import SocketServer, time
  
  from queuev2 import QueueServer
  
  
  
  logging.basicConfig(format='[%(asctime)s.%(msecs).03d] %(message)s', datefmt='%Y-%m-%d %H:%M:%S', filename=os.path.join(os.path.dirname(os.path.realpath(__file__)), 'converter.log'), level=logging.INFO)
  
  
  
  class ThreadedTCPRequestHandler(SocketServer.BaseRequestHandler):
  
  
  
      def handle(self):
  
          data = self.request.recv(1024)
  
          cur_thread = threading.current_thread()
  
          response = "{}: {}".format(cur_thread.name, data)
  
          videoPool.add(data)
  
          print "Output! %s" % data
  
          self.request.sendall(response)
  
  
  
  class ThreadedTCPServer(SocketServer.ThreadingMixIn, SocketServer.TCPServer):
  
      pass
  
  
  
  if __name__ == "__main__":
  
  
  
      logging.info("Initializing...")
  
      videoPool = QueueServer()
  
      HOST, PORT = "localhost", 6666
  
  
  
      server = ThreadedTCPServer((HOST, PORT), ThreadedTCPRequestHandler)
  
      ip, port = server.server_address
  
  
  
      # Start a thread with the server -- that thread will then start one
  
      # more thread for each request
  
      server_thread = threading.Thread(target=server.serve_forever)
  
  
  
      # Exit the server thread when the main thread terminates
  
      server_thread.daemon = True
  
      server_thread.start()
  
  
  
      print("Server loop running in thread: %s" % server_thread.name)
  
  
  
      # "Groundhog day" time
  
      while True:
  
          time.sleep(999)
  
          pass
  
  
  
      #server.shutdown()

  This works well in my development laptop, but on the server i'm getting the following error :

  Traceback (most recent call last):
  
    File "server.py", line 31, in <module>
  
      server = ThreadedTCPServer((HOST, PORT), ThreadedTCPRequestHandler)
  
    File "/usr/lib/python2.7/SocketServer.py", line 408, in __init__
  
      self.server_bind()
  
    File "/usr/lib/python2.7/SocketServer.py", line 419, in server_bind
  
      self.socket.bind(self.server_address)
  
    File "/usr/lib/python2.7/socket.py", line 224, in meth
  
      return getattr(self._sock,name)(*args)
  
  socket.gaierror: [Errno -2] Name or service not known
  
  </module>

  I'm guessing it has to do with the port I'm using (6666), but I've tried others and it hasn't been working. Would Unix Domain Sockets be of use here ? Can you give me an example ?

• Playing With Emscripten and ASM.js

  1er mars 2014, par Multimedia Mike — General

  The last 5 years or so have provided a tremendous amount of hype about the capabilities of JavaScript. I think it really kicked off when Google announced their Chrome web browser in September, 2008 along with its V8 JS engine. This seemed to spark an arms race in JS engine performance along with much hyperbole that eventually all software could, would, and/or should be written in straight JavaScript for maximum portability and future-proofing, perhaps aided by Emscripten, a tool which magically transforms C and C++ code into JS. The latest round of rhetoric comes courtesy of something called asm.js which purports to narrow the gap between JS and native code performance.

  I haven’t been a believer, to express it charitably. But I wanted to be certain, so I set out to devise my own experiment to test modern JS performance.

  Up Front Summary
  I was extremely surprised that my experiment demonstrated JS performance FAR beyond my expectations. There might be something to these claims of magnficent JS speed in numerical applications. Basically, here were my thoughts during the process :

  • There’s no way that JavaScript can come anywhere close to C performance for a numerically intensive operation ; a simple experiment should demonstrate this.
  • Here’s a straightforward C program to perform a simple yet numerically intensive operation.
  • Let’s compile the C program on gcc and get some baseline performance numbers.
  • Let’s use Emscripten to convert the C program to JavaScript and run it under Chrome.
  • Ha ! Pitiful JS performance, just as I expected !
  • Try the same program under Firefox, since Firefox is supposed to have some crazy optimization for asm.js code, allegedly emitted by Emscripten.
  • LOL ! Firefox performs even worse than Chrome !
  • Wait a minute… the Emscripten documentation mentioned using optimization levels for generating higher performance JS, so try ‘-O1′.
  • Umm… wow : Chrome’s performance increased dramatically ! What about Firefox ? Not only is Firefox faster than Chrome, it’s faster than the gcc-generated code !
  • As my faith in C is suddenly shaken to its core, I remembered to compile the gcc version with an explicit optimization level. The native C version pulled ahead of Firefox again, but the Firefox code is still close.
  • Aha ! This is just desktop– but what about mobile ? One of the leading arguments for converting everything to pure JavaScript is that such programs will magically run perfectly in mobile browsers. So I wager that this is where the experiment will fall over.
  • I proceed to try the same converted program on a variety of mobile platforms.
  • The mobile platforms perform rather admirably as well.
  • I am surprised.

  The Experiment
  I wanted to run a simple yet numerically-intensive and relevant benchmark, and something I am familiar with. I settled on JPEG image decoding. Again, I wanted to keep this simple, ideally in a single file because I didn’t know how hard it might be to deal with Emscripten. I found NanoJPEG, which is a straightforward JPEG decoder contained in a single C file.
  

  I altered nanojpeg.c (to a new file called nanojpeg-static.c) such that the main() program would always load a 1920×1080 (a.k.a. 1080p) JPEG file (“bbb-1080p-title.jpg”, the Big Buck Bunny title), rather than requiring a command line argument. Then I used gettimeofday() to profile the core decoding function (njDecode()).

  Compiling with gcc and profiling execution :

  gcc -Wall nanojpeg-static.c -o nanojpeg-static
  ./nanojpeg-static
  

  Optimization levels such as -O0, -O3, or -Os can be applied to the compilation command.

  For JavaScript conversion, I installed Emscripten and converted using :

  /path/to/emscripten/emcc nanojpeg-static.c -o nanojpeg.html \
    —preload-file bbb-1080p-title.jpg -s TOTAL_MEMORY=32000000
  

  The ‘–preload-file’ option makes the file available to the program via standard C-style file I/O functions. The ‘-s TOTAL_MEMORY’ was necessary because the default of 16 MB wasn’t enough. Again, the -O optimization levels can be sent in.

  For running, the .html file is loaded (via webserver) in a web browser.

  Want To Try It Yourself ?
  I put the files here : http://multimedia.cx/emscripten/. The .c file, the JPEG file, and the Emscripten-converted files using -O0, -O1, -O2, -O3, -Os, and no optimization switch.

  Results and Charts
  Here is the spreadsheet with the raw results.

  I ran this experiment using Ubuntu Linux 12.04 on an Intel Atom N450-based netbook. For this part, I was able to compare the Chrome and Firefox browser results against the C results :

  
  
  

  These are the results for a 2nd generation Android Nexus 7 using both Chrome and Firefox :

  
  
  

  Here is the result for an iPad 2 running iOS 7 and Safari– there is no Firefox for iOS and while there is a version of Chrome for iOS, it apparently isn’t able to leverage an optimized JS engine. Chrome takes so long to complete this experiment that there’s no reason to muddy the graph with the results :
  

  
  
  

  Interesting that -O1 tends to provide better optimization than levels 2 or 3, and that -Os (optimize for size) seems to be a good all-around choice.

  Don’t Get Too Smug
  JavaScript can indeed get amazing performance in this day and age. Please be advised, however, that this isn’t the best that a C decoder implementation can possibly do. This version doesn’t leverage any SIMD extensions. According to profiling (using gprof against the C code), sample saturation in color conversion dominates followed by inverse DCT functions, common cases for SIMD ASM or intrinsics. Allegedly, there will be some support for JS SIMD optimizations some day. We’ll see.

  Implications For Development
  I’m still not especially motivated to try porting the entire Native Client game music player codebase to JavaScript. I’m still wondering about the recommended development flow. How are you supposed to develop for Emscripten and asm.js ? From what I can tell, Emscripten is not designed as a simple aide for porting C/C++ code to JS. No, it reduces the code into JS code you can’t possibly maintain. This seems to imply that the C/C++ code needs to be developed and debugged in its entirety and then converted to JS, which seems arduous.

• [Aug-Sept 2013] Piwik 2.0 Development Update !

  3 octobre 2013, par Fabian Becker — Development

  This Development Update is the first in a new series of posts we’ll be writing to keep you, our loyal users, informed of our efforts. We hope these updates keep you excited about Piwik’s future, and if you’re a developer, we hope they inspire and challenge you to accomplish more yourself !

  Despite this being our first update, it will probably be one of our biggest. We’ve gotten a lot done as we race towards the Piwik 2.0 release ! Just see for yourself :

  What we’ve accomplished

  Theming

  Piwik now supports theming, a feature that was requested often in the past. Because of our switch to the Twig template engine and other major code changes it is now possible to change the way Piwik looks. Additionally, developers can use the dynamic stylesheet language LESS, instead of CSS. Piwik will automatically transform the LESS code into CSS.

  Piwik 2.0 will ship with a new dark theme called PleineLune (french for Full Moon) that makes use of the new theming feature. Another theme with a left-aligned menu was created during the Piwik Meetup in Paris. Both of these themes were created by Thomas Zilliox, a very talented designer and CSS expert.

  

  PHP 5.3 Namespaces

  For Piwik 2.0 we decided to make use of namespaces, a feature introduced in PHP 5.3. The usage of namespaces makes our code more readable and allows us to better modularize the platform. This is in part why we are raising the required minimum PHP version to 5.3 for Piwik 2.0. (Remember to update your server !)

  Translations in JSON

  All translations are now stored in JSON files which makes storing translations in Piwik a lot cleaner that the giant PHP array we previously used.

  Side note : if you’d like to make Piwik available to more languages, please sign up at translations.piwik.org. We’d love to have your help !

  UI Tests

  We now use UI tests to make sure that changes to the code don’t break the UI. UI tests use PhantomJS and CutyCapt and are automatically executed on Travis CI. Whenever an integration test fails the script produces a screenshot diff that shows the difference. Learn more.

  

  AnonymizeIP supports IPv6

  The AnonymizeIP plugin now masks IPv6 addresses. The concept of the config option ‘ip_address_mask_length’ has now changed to reflect the level of masking that should be applied to the IP. With a masking level of 1 Piwik will mask the last octet of an IPv4 address and the last 80 bits of an IPv6 address.

  All Websites Dashboard usable with 20,000+ Websites

  The All Websites Dashboard is now usable even if you track many thousands of websites in your Piwik instance. We rewrote parts of the archiving process in order to make this possible. Making Piwik fast and memory efficient is a constant concern for core developers.

  Plugins can now add new Visualizations

  Piwik Plugins and Themes can now create new visualizations for your report data. They can also specify their own ViewDataTable footer icons or modify existing ones. This will allow plugin developers to create new ways for you to view your data, customize existing reports so they look great in new visualizations and provide extra analytics functionality accessible in each of your reports.

  The new TreemapVisualization plugin makes use of this feature to let you view your reports as treemaps. It serves as an example of this new functionality.

  Piwik Marketplace

  The Piwik Marketplace is a new platform developers can use to publish their plugins and themes so all Piwik users can easily access them. The marketplace is hosted at plugins.piwik.org and is currently in an early development state, but we’re already able to host plugins !

  Developers can easily publish their plugins by adding a commit hook to their Github repositories. Every time you push a new tag, the marketplace will make a new version of your plugin available. The marketplace will provide a centralized platform to search for plugins and also provide statistics on plugin usage.

  Install Plugins and Themes in one click from within Piwik

  Piwik has offered since the beginning the much-loved “one click update” feature. We are bringing the same functionnality to the Marketplace : you will be able to install Plugins and Themes in one click directly within the Piwik interface ! Similarly to WordPress or Firefox, Piwik will let you extend the functionnality of your analytics platform.

  Conclusion

  In Piwik 2.0 you will be able to install plugins and themes from the marketplace. And, if you’re so inclined, you will be able to create and host your own plugins/themes on the marketplace so everyone can use them. This is by far the accomplishment we are most excited by… the possibilities it opens up for Piwik’s future are truly unlimited. We hope you share our excitement !

  Au revoir, until next time !

  PS : our mission is to liberate web analytics ; thank you for sharing the word about Piwik 2.0 !