Search Results

Search found 15224 results on 609 pages for 'parallel python'.

Page 303/609 | < Previous Page | 299 300 301 302 303 304 305 306 307 308 309 310  | Next Page >

  • strange(?) module import syntax

    - by morpheous
    I've come across the following code in a Python script from pprint import pprint why not simply import pprint? Unless the module pprint contains a function called pprint which is being aliased as pprint (surely, this must be the definition of madness?)

    Read the article

  • Iterating over key/value pairs in a dict sorted by keys

    - by Helper Method
    I have the following code, which just print the key/value pairs in a dict (the pairs are sorted by keys): for word, count in sorted(count_words(filename).items()): print word, count However, calling iteritems() instead of items() produces the same output for word, count in sorted(count_words(filename).iteritems()): print word, count Now, which one should I choose in this situation? I consulted the Python tutorial but it doesn't really answer my question.

    Read the article

  • Convert list of dicts to string

    - by John
    I'm very new to Python, so forgive me if this is easier than it seems to me. I'm being presented with a list of dicts as follows: [{'directMember': 'true', 'memberType': 'User', 'memberId': '[email protected]'}, {'directMember': 'true', 'memberType': 'User', 'memberId': '[email protected]'}, {'directMember': 'true', 'memberType': 'User', 'memberId': '[email protected]'}] I would like to generate a simple string of memberIds, such as [email protected], [email protected], [email protected] but every method of converting a list to a string that I have tried fails because dicts are involved. Any advice?

    Read the article

  • Django Deploy trouble

    - by i-Malignus
    Well, i've walking around this for a couples of days now... I think is time to ask for some help, i think my installation is ok... Server OS: Centos 5 Python -v 2.6.5 Django -v (1, 1, 1, 'final', 0) my apache conf: <VirtualHost *:80> DocumentRoot /opt/workshop ServerName taller.antell.com.py WSGIScriptAlias / /opt/workshop/workshop.wsgi WSGIDaemonProcess taller.antell.com.py user=ignacio group=ignacio processes=2 threads=25 ErrorLog /opt/workshop/apache.error.log CustomLog /opt/workshop/apache.custom.log combined <Directory "/opt/workshop"> Options +ExecCGI +FollowSymLinks -Indexes -MultiViews AllowOverride All Order allow,deny Allow from all </Directory> </VirtualHost> my mod_wsgi conf: import os import sys sys.path.append('/opt/workshop') os.environ['DJANGO_SETTINGS_MODULE'] = 'workshop.settings' os.environ['PYTHON_EGG_CACHE'] = '/tmp/.python-eggs' import django.core.handlers.wsgi application = django.core.handlers.wsgi.WSGIHandler( ) the error that i'm getting on my apache error log is: [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] mod_wsgi (pid=11459): Exception occurred processing WSGI script '/opt/workshop/workshop.wsgi'. [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] Traceback (most recent call last): [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/core/handlers/wsgi.py", line 241, in __call__ [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] response = self.get_response(request) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/core/handlers/base.py", line 134, in get_response [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] return self.handle_uncaught_exception(request, resolver, exc_info) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/core/handlers/base.py", line 154, in handle_uncaught_exception [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] return debug.technical_500_response(request, *exc_info) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/views/debug.py", line 40, in technical_500_response [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] html = reporter.get_traceback_html() [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/views/debug.py", line 114, in get_traceback_html [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] return t.render(c) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/template/__init__.py", line 178, in render [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] return self.nodelist.render(context) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/template/__init__.py", line 779, in render [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] bits.append(self.render_node(node, context)) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/template/debug.py", line 81, in render_node [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] raise wrapped [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] TemplateSyntaxError: Caught an exception while rendering: No module named vehicles [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] Original Traceback (most recent call last): [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/template/debug.py", line 71, in render_node [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] result = node.render(context) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/template/debug.py", line 87, in render [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] output = force_unicode(self.filter_expression.resolve(context)) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/template/__init__.py", line 572, in resolve [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] new_obj = func(obj, *arg_vals) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/template/defaultfilters.py", line 687, in date [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] return format(value, arg) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/utils/dateformat.py", line 269, in format [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] return df.format(format_string) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/utils/dateformat.py", line 30, in format [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] pieces.append(force_unicode(getattr(self, piece)())) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/utils/dateformat.py", line 175, in r [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] return self.format('D, j M Y H:i:s O') [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/utils/dateformat.py", line 30, in format [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] pieces.append(force_unicode(getattr(self, piece)())) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/utils/encoding.py", line 71, in force_unicode [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] s = unicode(s) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/utils/functional.py", line 201, in __unicode_cast [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] return self.__func(*self.__args, **self.__kw) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/utils/translation/__init__.py", line 62, in ugettext [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] return real_ugettext(message) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/utils/translation/trans_real.py", line 286, in ugettext [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] return do_translate(message, 'ugettext') [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/utils/translation/trans_real.py", line 276, in do_translate [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] _default = translation(settings.LANGUAGE_CODE) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/utils/translation/trans_real.py", line 194, in translation [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] default_translation = _fetch(settings.LANGUAGE_CODE) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/utils/translation/trans_real.py", line 180, in _fetch [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] app = import_module(appname) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/utils/importlib.py", line 35, in import_module [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] __import__(name) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] ImportError: No module named vehicles [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] mod_wsgi (pid=11463): Exception occurred processing WSGI script '/opt/workshop/workshop.wsgi'. [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] Traceback (most recent call last): [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/core/handlers/wsgi.py", line 241, in __call__ [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] response = self.get_response(request) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/core/handlers/base.py", line 73, in get_response [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] response = middleware_method(request) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/middleware/common.py", line 56, in process_request [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] if (not _is_valid_path(request.path_info) and [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/middleware/common.py", line 142, in _is_valid_path [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] urlresolvers.resolve(path) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/core/urlresolvers.py", line 303, in resolve [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] return get_resolver(urlconf).resolve(path) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/core/urlresolvers.py", line 218, in resolve [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] sub_match = pattern.resolve(new_path) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/core/urlresolvers.py", line 216, in resolve [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] for pattern in self.url_patterns: [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/core/urlresolvers.py", line 245, in _get_url_patterns [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] patterns = getattr(self.urlconf_module, "urlpatterns", self.urlconf_module) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/core/urlresolvers.py", line 240, in _get_urlconf_module [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] self._urlconf_module = import_module(self.urlconf_name) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] File "/opt/python2.6/lib/python2.6/site-packages/django/utils/importlib.py", line 35, in import_module [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] __import__(name) [Wed Apr 21 15:17:48 2010] [error] [client 190.128.226.122] ImportError: No module named vehicles.urls Please give my a hand, i stuck... Obviously is a problem with my vehicle module (the only one in the app), another thing is that when i try: [root@localhost workshop]# python manage.py runserver 0:8000 The app runs perfectly, i think that the problem is something near the wsgi conf, something is not clicking.... Tks... Update: workshop dir looks like... [root@localhost workshop]# ls -l total 504 -rw-r--r-- 1 root root 22706 Apr 21 15:17 apache.custom.log -rw-r--r-- 1 root root 408141 Apr 21 15:17 apache.error.log -rw-r--r-- 1 root root 0 Apr 17 10:56 __init__.py -rw-r--r-- 1 root root 124 Apr 21 11:09 __init__.pyc -rw-r--r-- 1 root root 542 Apr 17 10:56 manage.py -rw-r--r-- 1 root root 3326 Apr 17 10:56 settings.py -rw-r--r-- 1 root root 2522 Apr 21 11:09 settings.pyc drw-r--r-- 4 root root 4096 Apr 17 10:56 templates -rw-r--r-- 1 root root 381 Apr 21 13:42 urls.py -rw-r--r-- 1 root root 398 Apr 21 13:00 urls.pyc drw-r--r-- 2 root root 4096 Apr 21 13:44 vehicles -rw-r--r-- 1 root root 38912 Apr 17 10:56 workshop.db -rw-r--r-- 1 root root 263 Apr 21 15:30 workshop.wsgi vehicles dir [root@localhost vehicles]# ls -l total 52 -rw-r--r-- 1 root root 390 Apr 17 10:56 admin.py -rw-r--r-- 1 root root 967 Apr 21 13:00 admin.pyc -rw-r--r-- 1 root root 732 Apr 17 10:56 forms.py -rw-r--r-- 1 root root 2086 Apr 21 13:00 forms.pyc -rw-r--r-- 1 root root 0 Apr 17 10:56 __init__.py -rw-r--r-- 1 root root 133 Apr 21 11:36 __init__.pyc -rw-r--r-- 1 root root 936 Apr 17 10:56 models.py -rw-r--r-- 1 root root 1827 Apr 21 11:36 models.pyc -rw-r--r-- 1 root root 514 Apr 17 10:56 tests.py -rw-r--r-- 1 root root 989 Apr 21 13:44 tests.pyc -rw-r--r-- 1 root root 1035 Apr 17 10:56 urls.py -rw-r--r-- 1 root root 1935 Apr 21 13:00 urls.pyc -rw-r--r-- 1 root root 3164 Apr 17 10:56 views.py -rw-r--r-- 1 root root 4081 Apr 21 13:00 views.pyc Update 2: this is my settings.py # Django settings for workshop project. DEBUG = True TEMPLATE_DEBUG = DEBUG ADMINS = ( ('Ignacio Rojas', '[email protected]'), ('Fabian Biedermann', '[email protected]'), ) MANAGERS = ADMINS DATABASE_ENGINE = 'sqlite3' DATABASE_NAME = '/opt/workshop/workshop.db' DATABASE_USER = '' DATABASE_PASSWORD = '' DATABASE_HOST = '' DATABASE_PORT = '' # Local time zone for this installation. Choices can be found here: # http://en.wikipedia.org/wiki/List_of_tz_zones_by_name # although not all choices may be available on all operating systems. # If running in a Windows environment this must be set to the same as your # system time zone. TIME_ZONE = 'America/Asuncion' # Language code for this installation. All choices can be found here: # http://www.i18nguy.com/unicode/language-identifiers.html LANGUAGE_CODE = 'es-py' SITE_ID = 1 # If you set this to False, Django will make some optimizations so as not # to load the internationalization machinery. USE_I18N = True # Absolute path to the directory that holds media. # Example: "/home/media/media.lawrence.com/" MEDIA_ROOT = '' # URL that handles the media served from MEDIA_ROOT. Make sure to use a # trailing slash if there is a path component (optional in other cases). # Examples: "http://media.lawrence.com", "http://example.com/media/" MEDIA_URL = '' # URL prefix for admin media -- CSS, JavaScript and images. Make sure to use a # trailing slash. # Examples: "http://foo.com/media/", "/media/". ADMIN_MEDIA_PREFIX = '/media/' # Make this unique, and don't share it with anybody. SECRET_KEY = '11y0_jb=+b4^nq@2-fo#g$-ihk5*v&d5-8hg_y0i@*9$w8jalp' MIDDLEWARE_CLASSES = ( 'django.middleware.common.CommonMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', ) ROOT_URLCONF = 'workshop.urls' TEMPLATE_DIRS = ( # Put strings here, like "/home/html/django_templates" or "C:/www/django/templates". # Always use forward slashes, even on Windows. # Don't forget to use absolute paths, not relative paths. "/opt/workshop/templates" ) INSTALLED_APPS = ( 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.sites', 'workshop.vehicles', ) TEMPLATE_CONTEXT_PROCESSORS = ( 'django.core.context_processors.auth', 'django.core.context_processors.debug', 'django.core.context_processors.i18n', 'django.core.context_processors.media', )

    Read the article

  • Upload File to Windows Azure Blob in Chunks through ASP.NET MVC, JavaScript and HTML5

    - by Shaun
    Originally posted on: http://geekswithblogs.net/shaunxu/archive/2013/07/01/upload-file-to-windows-azure-blob-in-chunks-through-asp.net.aspxMany people are using Windows Azure Blob Storage to store their data in the cloud. Blob storage provides 99.9% availability with easy-to-use API through .NET SDK and HTTP REST. For example, we can store JavaScript files, images, documents in blob storage when we are building an ASP.NET web application on a Web Role in Windows Azure. Or we can store our VHD files in blob and mount it as a hard drive in our cloud service. If you are familiar with Windows Azure, you should know that there are two kinds of blob: page blob and block blob. The page blob is optimized for random read and write, which is very useful when you need to store VHD files. The block blob is optimized for sequential/chunk read and write, which has more common usage. Since we can upload block blob in blocks through BlockBlob.PutBlock, and them commit them as a whole blob with invoking the BlockBlob.PutBlockList, it is very powerful to upload large files, as we can upload blocks in parallel, and provide pause-resume feature. There are many documents, articles and blog posts described on how to upload a block blob. Most of them are focus on the server side, which means when you had received a big file, stream or binaries, how to upload them into blob storage in blocks through .NET SDK.  But the problem is, how can we upload these large files from client side, for example, a browser. This questioned to me when I was working with a Chinese customer to help them build a network disk production on top of azure. The end users upload their files from the web portal, and then the files will be stored in blob storage from the Web Role. My goal is to find the best way to transform the file from client (end user’s machine) to the server (Web Role) through browser. In this post I will demonstrate and describe what I had done, to upload large file in chunks with high speed, and save them as blocks into Windows Azure Blob Storage.   Traditional Upload, Works with Limitation The simplest way to implement this requirement is to create a web page with a form that contains a file input element and a submit button. 1: @using (Html.BeginForm("About", "Index", FormMethod.Post, new { enctype = "multipart/form-data" })) 2: { 3: <input type="file" name="file" /> 4: <input type="submit" value="upload" /> 5: } And then in the backend controller, we retrieve the whole content of this file and upload it in to the blob storage through .NET SDK. We can split the file in blocks and upload them in parallel and commit. The code had been well blogged in the community. 1: [HttpPost] 2: public ActionResult About(HttpPostedFileBase file) 3: { 4: var container = _client.GetContainerReference("test"); 5: container.CreateIfNotExists(); 6: var blob = container.GetBlockBlobReference(file.FileName); 7: var blockDataList = new Dictionary<string, byte[]>(); 8: using (var stream = file.InputStream) 9: { 10: var blockSizeInKB = 1024; 11: var offset = 0; 12: var index = 0; 13: while (offset < stream.Length) 14: { 15: var readLength = Math.Min(1024 * blockSizeInKB, (int)stream.Length - offset); 16: var blockData = new byte[readLength]; 17: offset += stream.Read(blockData, 0, readLength); 18: blockDataList.Add(Convert.ToBase64String(BitConverter.GetBytes(index)), blockData); 19:  20: index++; 21: } 22: } 23:  24: Parallel.ForEach(blockDataList, (bi) => 25: { 26: blob.PutBlock(bi.Key, new MemoryStream(bi.Value), null); 27: }); 28: blob.PutBlockList(blockDataList.Select(b => b.Key).ToArray()); 29:  30: return RedirectToAction("About"); 31: } This works perfect if we selected an image, a music or a small video to upload. But if I selected a large file, let’s say a 6GB HD-movie, after upload for about few minutes the page will be shown as below and the upload will be terminated. In ASP.NET there is a limitation of request length and the maximized request length is defined in the web.config file. It’s a number which less than about 4GB. So if we want to upload a really big file, we cannot simply implement in this way. Also, in Windows Azure, a cloud service network load balancer will terminate the connection if exceed the timeout period. From my test the timeout looks like 2 - 3 minutes. Hence, when we need to upload a large file we cannot just use the basic HTML elements. Besides the limitation mentioned above, the simple HTML file upload cannot provide rich upload experience such as chunk upload, pause and pause-resume. So we need to find a better way to upload large file from the client to the server.   Upload in Chunks through HTML5 and JavaScript In order to break those limitation mentioned above we will try to upload the large file in chunks. This takes some benefit to us such as - No request size limitation: Since we upload in chunks, we can define the request size for each chunks regardless how big the entire file is. - No timeout problem: The size of chunks are controlled by us, which means we should be able to make sure request for each chunk upload will not exceed the timeout period of both ASP.NET and Windows Azure load balancer. It was a big challenge to upload big file in chunks until we have HTML5. There are some new features and improvements introduced in HTML5 and we will use them to implement our solution.   In HTML5, the File interface had been improved with a new method called “slice”. It can be used to read part of the file by specifying the start byte index and the end byte index. For example if the entire file was 1024 bytes, file.slice(512, 768) will read the part of this file from the 512nd byte to 768th byte, and return a new object of interface called "Blob”, which you can treat as an array of bytes. In fact,  a Blob object represents a file-like object of immutable, raw data. The File interface is based on Blob, inheriting blob functionality and expanding it to support files on the user's system. For more information about the Blob please refer here. File and Blob is very useful to implement the chunk upload. We will use File interface to represent the file the user selected from the browser and then use File.slice to read the file in chunks in the size we wanted. For example, if we wanted to upload a 10MB file with 512KB chunks, then we can read it in 512KB blobs by using File.slice in a loop.   Assuming we have a web page as below. User can select a file, an input box to specify the block size in KB and a button to start upload. 1: <div> 2: <input type="file" id="upload_files" name="files[]" /><br /> 3: Block Size: <input type="number" id="block_size" value="512" name="block_size" />KB<br /> 4: <input type="button" id="upload_button_blob" name="upload" value="upload (blob)" /> 5: </div> Then we can have the JavaScript function to upload the file in chunks when user clicked the button. 1: <script type="text/javascript"> 1: 2: $(function () { 3: $("#upload_button_blob").click(function () { 4: }); 5: });</script> Firstly we need to ensure the client browser supports the interfaces we are going to use. Just try to invoke the File, Blob and FormData from the “window” object. If any of them is “undefined” the condition result will be “false” which means your browser doesn’t support these premium feature and it’s time for you to get your browser updated. FormData is another new feature we are going to use in the future. It could generate a temporary form for us. We will use this interface to create a form with chunk and associated metadata when invoked the service through ajax. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: if (window.File && window.Blob && window.FormData) { 4: alert("Your brwoser is awesome, let's rock!"); 5: } 6: else { 7: alert("Oh man plz update to a modern browser before try is cool stuff out."); 8: return; 9: } 10: }); Each browser supports these interfaces by their own implementation and currently the Blob, File and File.slice are supported by Chrome 21, FireFox 13, IE 10, Opera 12 and Safari 5.1 or higher. After that we worked on the files the user selected one by one since in HTML5, user can select multiple files in one file input box. 1: var files = $("#upload_files")[0].files; 2: for (var i = 0; i < files.length; i++) { 3: var file = files[i]; 4: var fileSize = file.size; 5: var fileName = file.name; 6: } Next, we calculated the start index and end index for each chunks based on the size the user specified from the browser. We put them into an array with the file name and the index, which will be used when we upload chunks into Windows Azure Blob Storage as blocks since we need to specify the target blob name and the block index. At the same time we will store the list of all indexes into another variant which will be used to commit blocks into blob in Azure Storage once all chunks had been uploaded successfully. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10:  11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: var blockSizeInKB = $("#block_size").val(); 14: var blockSize = blockSizeInKB * 1024; 15: var blocks = []; 16: var offset = 0; 17: var index = 0; 18: var list = ""; 19: while (offset < fileSize) { 20: var start = offset; 21: var end = Math.min(offset + blockSize, fileSize); 22:  23: blocks.push({ 24: name: fileName, 25: index: index, 26: start: start, 27: end: end 28: }); 29: list += index + ","; 30:  31: offset = end; 32: index++; 33: } 34: } 35: }); Now we have all chunks’ information ready. The next step should be upload them one by one to the server side, and at the server side when received a chunk it will upload as a block into Blob Storage, and finally commit them with the index list through BlockBlobClient.PutBlockList. But since all these invokes are ajax calling, which means not synchronized call. So we need to introduce a new JavaScript library to help us coordinate the asynchronize operation, which named “async.js”. You can download this JavaScript library here, and you can find the document here. I will not explain this library too much in this post. We will put all procedures we want to execute as a function array, and pass into the proper function defined in async.js to let it help us to control the execution sequence, in series or in parallel. Hence we will define an array and put the function for chunk upload into this array. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4:  5: // start to upload each files in chunks 6: var files = $("#upload_files")[0].files; 7: for (var i = 0; i < files.length; i++) { 8: var file = files[i]; 9: var fileSize = file.size; 10: var fileName = file.name; 11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: ... ... 14:  15: // define the function array and push all chunk upload operation into this array 16: blocks.forEach(function (block) { 17: putBlocks.push(function (callback) { 18: }); 19: }); 20: } 21: }); 22: }); As you can see, I used File.slice method to read each chunks based on the start and end byte index we calculated previously, and constructed a temporary HTML form with the file name, chunk index and chunk data through another new feature in HTML5 named FormData. Then post this form to the backend server through jQuery.ajax. This is the key part of our solution. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: blocks.forEach(function (block) { 15: putBlocks.push(function (callback) { 16: // load blob based on the start and end index for each chunks 17: var blob = file.slice(block.start, block.end); 18: // put the file name, index and blob into a temporary from 19: var fd = new FormData(); 20: fd.append("name", block.name); 21: fd.append("index", block.index); 22: fd.append("file", blob); 23: // post the form to backend service (asp.net mvc controller action) 24: $.ajax({ 25: url: "/Home/UploadInFormData", 26: data: fd, 27: processData: false, 28: contentType: "multipart/form-data", 29: type: "POST", 30: success: function (result) { 31: if (!result.success) { 32: alert(result.error); 33: } 34: callback(null, block.index); 35: } 36: }); 37: }); 38: }); 39: } 40: }); Then we will invoke these functions one by one by using the async.js. And once all functions had been executed successfully I invoked another ajax call to the backend service to commit all these chunks (blocks) as the blob in Windows Azure Storage. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.series(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); That’s all in the client side. The outline of our logic would be - Calculate the start and end byte index for each chunks based on the block size. - Defined the functions of reading the chunk form file and upload the content to the backend service through ajax. - Execute the functions defined in previous step with “async.js”. - Commit the chunks by invoking the backend service in Windows Azure Storage finally.   Save Chunks as Blocks into Blob Storage In above we finished the client size JavaScript code. It uploaded the file in chunks to the backend service which we are going to implement in this step. We will use ASP.NET MVC as our backend service, and it will receive the chunks, upload into Windows Azure Bob Storage in blocks, then finally commit as one blob. As in the client side we uploaded chunks by invoking the ajax call to the URL "/Home/UploadInFormData", I created a new action under the Index controller and it only accepts HTTP POST request. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: } 8: catch (Exception e) 9: { 10: error = e.ToString(); 11: } 12:  13: return new JsonResult() 14: { 15: Data = new 16: { 17: success = string.IsNullOrWhiteSpace(error), 18: error = error 19: } 20: }; 21: } Then I retrieved the file name, index and the chunk content from the Request.Form object, which was passed from our client side. And then, used the Windows Azure SDK to create a blob container (in this case we will use the container named “test”.) and create a blob reference with the blob name (same as the file name). Then uploaded the chunk as a block of this blob with the index, since in Blob Storage each block must have an index (ID) associated with so that finally we can put all blocks as one blob by specifying their block ID list. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var index = int.Parse(Request.Form["index"]); 9: var file = Request.Files[0]; 10: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 11:  12: var container = _client.GetContainerReference("test"); 13: container.CreateIfNotExists(); 14: var blob = container.GetBlockBlobReference(name); 15: blob.PutBlock(id, file.InputStream, null); 16: } 17: catch (Exception e) 18: { 19: error = e.ToString(); 20: } 21:  22: return new JsonResult() 23: { 24: Data = new 25: { 26: success = string.IsNullOrWhiteSpace(error), 27: error = error 28: } 29: }; 30: } Next, I created another action to commit the blocks into blob once all chunks had been uploaded. Similarly, I retrieved the blob name from the Request.Form. I also retrieved the chunks ID list, which is the block ID list from the Request.Form in a string format, split them as a list, then invoked the BlockBlob.PutBlockList method. After that our blob will be shown in the container and ready to be download. 1: [HttpPost] 2: public JsonResult Commit() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var list = Request.Form["list"]; 9: var ids = list 10: .Split(',') 11: .Where(id => !string.IsNullOrWhiteSpace(id)) 12: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 13: .ToArray(); 14:  15: var container = _client.GetContainerReference("test"); 16: container.CreateIfNotExists(); 17: var blob = container.GetBlockBlobReference(name); 18: blob.PutBlockList(ids); 19: } 20: catch (Exception e) 21: { 22: error = e.ToString(); 23: } 24:  25: return new JsonResult() 26: { 27: Data = new 28: { 29: success = string.IsNullOrWhiteSpace(error), 30: error = error 31: } 32: }; 33: } Now we finished all code we need. The whole process of uploading would be like this below. Below is the full client side JavaScript code. 1: <script type="text/javascript" src="~/Scripts/async.js"></script> 2: <script type="text/javascript"> 3: $(function () { 4: $("#upload_button_blob").click(function () { 5: // assert the browser support html5 6: if (window.File && window.Blob && window.FormData) { 7: alert("Your brwoser is awesome, let's rock!"); 8: } 9: else { 10: alert("Oh man plz update to a modern browser before try is cool stuff out."); 11: return; 12: } 13:  14: // start to upload each files in chunks 15: var files = $("#upload_files")[0].files; 16: for (var i = 0; i < files.length; i++) { 17: var file = files[i]; 18: var fileSize = file.size; 19: var fileName = file.name; 20:  21: // calculate the start and end byte index for each blocks(chunks) 22: // with the index, file name and index list for future using 23: var blockSizeInKB = $("#block_size").val(); 24: var blockSize = blockSizeInKB * 1024; 25: var blocks = []; 26: var offset = 0; 27: var index = 0; 28: var list = ""; 29: while (offset < fileSize) { 30: var start = offset; 31: var end = Math.min(offset + blockSize, fileSize); 32:  33: blocks.push({ 34: name: fileName, 35: index: index, 36: start: start, 37: end: end 38: }); 39: list += index + ","; 40:  41: offset = end; 42: index++; 43: } 44:  45: // define the function array and push all chunk upload operation into this array 46: var putBlocks = []; 47: blocks.forEach(function (block) { 48: putBlocks.push(function (callback) { 49: // load blob based on the start and end index for each chunks 50: var blob = file.slice(block.start, block.end); 51: // put the file name, index and blob into a temporary from 52: var fd = new FormData(); 53: fd.append("name", block.name); 54: fd.append("index", block.index); 55: fd.append("file", blob); 56: // post the form to backend service (asp.net mvc controller action) 57: $.ajax({ 58: url: "/Home/UploadInFormData", 59: data: fd, 60: processData: false, 61: contentType: "multipart/form-data", 62: type: "POST", 63: success: function (result) { 64: if (!result.success) { 65: alert(result.error); 66: } 67: callback(null, block.index); 68: } 69: }); 70: }); 71: }); 72:  73: // invoke the functions one by one 74: // then invoke the commit ajax call to put blocks into blob in azure storage 75: async.series(putBlocks, function (error, result) { 76: var data = { 77: name: fileName, 78: list: list 79: }; 80: $.post("/Home/Commit", data, function (result) { 81: if (!result.success) { 82: alert(result.error); 83: } 84: else { 85: alert("done!"); 86: } 87: }); 88: }); 89: } 90: }); 91: }); 92: </script> And below is the full ASP.NET MVC controller code. 1: public class HomeController : Controller 2: { 3: private CloudStorageAccount _account; 4: private CloudBlobClient _client; 5:  6: public HomeController() 7: : base() 8: { 9: _account = CloudStorageAccount.Parse(CloudConfigurationManager.GetSetting("DataConnectionString")); 10: _client = _account.CreateCloudBlobClient(); 11: } 12:  13: public ActionResult Index() 14: { 15: ViewBag.Message = "Modify this template to jump-start your ASP.NET MVC application."; 16:  17: return View(); 18: } 19:  20: [HttpPost] 21: public JsonResult UploadInFormData() 22: { 23: var error = string.Empty; 24: try 25: { 26: var name = Request.Form["name"]; 27: var index = int.Parse(Request.Form["index"]); 28: var file = Request.Files[0]; 29: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 30:  31: var container = _client.GetContainerReference("test"); 32: container.CreateIfNotExists(); 33: var blob = container.GetBlockBlobReference(name); 34: blob.PutBlock(id, file.InputStream, null); 35: } 36: catch (Exception e) 37: { 38: error = e.ToString(); 39: } 40:  41: return new JsonResult() 42: { 43: Data = new 44: { 45: success = string.IsNullOrWhiteSpace(error), 46: error = error 47: } 48: }; 49: } 50:  51: [HttpPost] 52: public JsonResult Commit() 53: { 54: var error = string.Empty; 55: try 56: { 57: var name = Request.Form["name"]; 58: var list = Request.Form["list"]; 59: var ids = list 60: .Split(',') 61: .Where(id => !string.IsNullOrWhiteSpace(id)) 62: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 63: .ToArray(); 64:  65: var container = _client.GetContainerReference("test"); 66: container.CreateIfNotExists(); 67: var blob = container.GetBlockBlobReference(name); 68: blob.PutBlockList(ids); 69: } 70: catch (Exception e) 71: { 72: error = e.ToString(); 73: } 74:  75: return new JsonResult() 76: { 77: Data = new 78: { 79: success = string.IsNullOrWhiteSpace(error), 80: error = error 81: } 82: }; 83: } 84: } And if we selected a file from the browser we will see our application will upload chunks in the size we specified to the server through ajax call in background, and then commit all chunks in one blob. Then we can find the blob in our Windows Azure Blob Storage.   Optimized by Parallel Upload In previous example we just uploaded our file in chunks. This solved the problem that ASP.NET MVC request content size limitation as well as the Windows Azure load balancer timeout. But it might introduce the performance problem since we uploaded chunks in sequence. In order to improve the upload performance we could modify our client side code a bit to make the upload operation invoked in parallel. The good news is that, “async.js” library provides the parallel execution function. If you remembered the code we invoke the service to upload chunks, it utilized “async.series” which means all functions will be executed in sequence. Now we will change this code to “async.parallel”. This will invoke all functions in parallel. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallel(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); In this way all chunks will be uploaded to the server side at the same time to maximize the bandwidth usage. This should work if the file was not very large and the chunk size was not very small. But for large file this might introduce another problem that too many ajax calls are sent to the server at the same time. So the best solution should be, upload the chunks in parallel with maximum concurrency limitation. The code below specified the concurrency limitation to 4, which means at the most only 4 ajax calls could be invoked at the same time. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallelLimit(putBlocks, 4, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: });   Summary In this post we discussed how to upload files in chunks to the backend service and then upload them into Windows Azure Blob Storage in blocks. We focused on the frontend side and leverage three new feature introduced in HTML 5 which are - File.slice: Read part of the file by specifying the start and end byte index. - Blob: File-like interface which contains the part of the file content. - FormData: Temporary form element that we can pass the chunk alone with some metadata to the backend service. Then we discussed the performance consideration of chunk uploading. Sequence upload cannot provide maximized upload speed, but the unlimited parallel upload might crash the browser and server if too many chunks. So we finally came up with the solution to upload chunks in parallel with the concurrency limitation. We also demonstrated how to utilize “async.js” JavaScript library to help us control the asynchronize call and the parallel limitation.   Regarding the chunk size and the parallel limitation value there is no “best” value. You need to test vary composition and find out the best one for your particular scenario. It depends on the local bandwidth, client machine cores and the server side (Windows Azure Cloud Service Virtual Machine) cores, memory and bandwidth. Below is one of my performance test result. The client machine was Windows 8 IE 10 with 4 cores. I was using Microsoft Cooperation Network. The web site was hosted on Windows Azure China North data center (in Beijing) with one small web role (1.7GB 1 core CPU, 1.75GB memory with 100Mbps bandwidth). The test cases were - Chunk size: 512KB, 1MB, 2MB, 4MB. - Upload Mode: Sequence, parallel (unlimited), parallel with limit (4 threads, 8 threads). - Chunk Format: base64 string, binaries. - Target file: 100MB. - Each case was tested 3 times. Below is the test result chart. Some thoughts, but not guidance or best practice: - Parallel gets better performance than series. - No significant performance improvement between parallel 4 threads and 8 threads. - Transform with binaries provides better performance than base64. - In all cases, chunk size in 1MB - 2MB gets better performance.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

    Read the article

  • Incremental PCA

    - by smichak
    Hi, Lately, I've been looking into an implementation of an incremental PCA algorithm in python - I couldn't find something that would meet my needs so I did some reading and implemented an algorithm I found in some paper. Here is the module's code - the relevant paper on which it is based is mentioned in the module's documentation. I would appreciate any feedback from people who are interested in this. Micha #!/usr/bin/env python """ Incremental PCA calculation module. Based on P.Hall, D. Marshall and R. Martin "Incremental Eigenalysis for Classification" which appeared in British Machine Vision Conference, volume 1, pages 286-295, September 1998. Principal components are updated sequentially as new observations are introduced. Each new observation (x) is projected on the eigenspace spanned by the current principal components (U) and the residual vector (r = x - U(U.T*x)) is used as a new principal component (U' = [U r]). The new principal components are then rotated by a rotation matrix (R) whose columns are the eigenvectors of the transformed covariance matrix (D=U'.T*C*U) to yield p + 1 principal components. From those, only the first p are selected. """ __author__ = "Micha Kalfon" import numpy as np _ZERO_THRESHOLD = 1e-9 # Everything below this is zero class IPCA(object): """Incremental PCA calculation object. General Parameters: m - Number of variables per observation n - Number of observations p - Dimension to which the data should be reduced """ def __init__(self, m, p): """Creates an incremental PCA object for m-dimensional observations in order to reduce them to a p-dimensional subspace. @param m: Number of variables per observation. @param p: Number of principle components. @return: An IPCA object. """ self._m = float(m) self._n = 0.0 self._p = float(p) self._mean = np.matrix(np.zeros((m , 1), dtype=np.float64)) self._covariance = np.matrix(np.zeros((m, m), dtype=np.float64)) self._eigenvectors = np.matrix(np.zeros((m, p), dtype=np.float64)) self._eigenvalues = np.matrix(np.zeros((1, p), dtype=np.float64)) def update(self, x): """Updates with a new observation vector x. @param x: Next observation as a column vector (m x 1). """ m = self._m n = self._n p = self._p mean = self._mean C = self._covariance U = self._eigenvectors E = self._eigenvalues if type(x) is not np.matrix or x.shape != (m, 1): raise TypeError('Input is not a matrix (%d, 1)' % int(m)) # Update covariance matrix and mean vector and centralize input around # new mean oldmean = mean mean = (n*mean + x) / (n + 1.0) C = (n*C + x*x.T + n*oldmean*oldmean.T - (n+1)*mean*mean.T) / (n + 1.0) x -= mean # Project new input on current p-dimensional subspace and calculate # the normalized residual vector g = U.T*x r = x - (U*g) r = (r / np.linalg.norm(r)) if not _is_zero(r) else np.zeros_like(r) # Extend the transformation matrix with the residual vector and find # the rotation matrix by solving the eigenproblem DR=RE U = np.concatenate((U, r), 1) D = U.T*C*U (E, R) = np.linalg.eigh(D) # Sort eigenvalues and eigenvectors from largest to smallest to get the # rotation matrix R sorter = list(reversed(E.argsort(0))) E = E[sorter] R = R[:,sorter] # Apply the rotation matrix U = U*R # Select only p largest eigenvectors and values and update state self._n += 1.0 self._mean = mean self._covariance = C self._eigenvectors = U[:, 0:p] self._eigenvalues = E[0:p] @property def components(self): """Returns a matrix with the current principal components as columns. """ return self._eigenvectors @property def variances(self): """Returns a list with the appropriate variance along each principal component. """ return self._eigenvalues def _is_zero(x): """Return a boolean indicating whether the given vector is a zero vector up to a threshold. """ return np.fabs(x).min() < _ZERO_THRESHOLD if __name__ == '__main__': import sys def pca_svd(X): X = X - X.mean(0).repeat(X.shape[0], 0) [_, _, V] = np.linalg.svd(X) return V N = 1000 obs = np.matrix([np.random.normal(size=10) for _ in xrange(N)]) V = pca_svd(obs) print V[0:2] pca = IPCA(obs.shape[1], 2) for i in xrange(obs.shape[0]): x = obs[i,:].transpose() pca.update(x) U = pca.components print U

    Read the article

  • One letter game problem?

    - by Alex K
    Recently at a job interview I was given the following problem: Write a script capable of running on the command line as python It should take in two words on the command line (or optionally if you'd prefer it can query the user to supply the two words via the console). Given those two words: a. Ensure they are of equal length b. Ensure they are both words present in the dictionary of valid words in the English language that you downloaded. If so compute whether you can reach the second word from the first by a series of steps as follows a. You can change one letter at a time b. Each time you change a letter the resulting word must also exist in the dictionary c. You cannot add or remove letters If the two words are reachable, the script should print out the path which leads as a single, shortest path from one word to the other. You can /usr/share/dict/words for your dictionary of words. My solution consisted of using breadth first search to find a shortest path between two words. But apparently that wasn't good enough to get the job :( Would you guys know what I could have done wrong? Thank you so much. import collections import functools import re def time_func(func): import time def wrapper(*args, **kwargs): start = time.time() res = func(*args, **kwargs) timed = time.time() - start setattr(wrapper, 'time_taken', timed) return res functools.update_wrapper(wrapper, func) return wrapper class OneLetterGame: def __init__(self, dict_path): self.dict_path = dict_path self.words = set() def run(self, start_word, end_word): '''Runs the one letter game with the given start and end words. ''' assert len(start_word) == len(end_word), \ 'Start word and end word must of the same length.' self.read_dict(len(start_word)) path = self.shortest_path(start_word, end_word) if not path: print 'There is no path between %s and %s (took %.2f sec.)' % ( start_word, end_word, find_shortest_path.time_taken) else: print 'The shortest path (found in %.2f sec.) is:\n=> %s' % ( self.shortest_path.time_taken, ' -- '.join(path)) def _bfs(self, start): '''Implementation of breadth first search as a generator. The portion of the graph to explore is given on demand using get_neighboors. Care was taken so that a vertex / node is explored only once. ''' queue = collections.deque([(None, start)]) inqueue = set([start]) while queue: parent, node = queue.popleft() yield parent, node new = set(self.get_neighbours(node)) - inqueue inqueue = inqueue | new queue.extend([(node, child) for child in new]) @time_func def shortest_path(self, start, end): '''Returns the shortest path from start to end using bfs. ''' assert start in self.words, 'Start word not in dictionnary.' assert end in self.words, 'End word not in dictionnary.' paths = {None: []} for parent, child in self._bfs(start): paths[child] = paths[parent] + [child] if child == end: return paths[child] return None def get_neighbours(self, word): '''Gets every word one letter away from the a given word. We do not keep these words in memory because bfs accesses a given vertex only once. ''' neighbours = [] p_word = ['^' + word[0:i] + '\w' + word[i+1:] + '$' for i, w in enumerate(word)] p_word = '|'.join(p_word) for w in self.words: if w != word and re.match(p_word, w, re.I|re.U): neighbours += [w] return neighbours def read_dict(self, size): '''Loads every word of a specific size from the dictionnary into memory. ''' for l in open(self.dict_path): l = l.decode('latin-1').strip().lower() if len(l) == size: self.words.add(l) if __name__ == '__main__': import sys if len(sys.argv) not in [3, 4]: print 'Usage: python one_letter_game.py start_word end_word' else: g = OneLetterGame(dict_path = '/usr/share/dict/words') try: g.run(*sys.argv[1:]) except AssertionError, e: print e

    Read the article

  • Why doesn't my QsciLexerCustom subclass work in PyQt4 using QsciScintilla?

    - by Jon Watte
    My end goal is to get Erlang syntax highlighting in QsciScintilla using PyQt4 and Python 2.6. I'm running on Windows 7, but will also need Ubuntu support. PyQt4 is missing the necessary wrapper code for the Erlang lexer/highlighter that "base" scintilla has, so I figured I'd write a lightweight one on top of QsciLexerCustom. It's a little bit problematic, because the Qsci wrapper seems to really want to talk about line+index rather than offset-from-start when getting/setting subranges of text. Meanwhile, the lexer gets arguments as offset-from-start. For now, I get a copy of the entire text, and split that up as appropriate. I have the following lexer, and I apply it with setLexer(). It gets all the appropriate calls when I open a new file and sets this as the lexer, and prints a bunch of appropriate lines based on what it's doing... but there is no styling in the document. I tried making all the defined styles red, and the document is still stubbornly black-on-white, so apparently the styles don't really "take effect" What am I doing wrong? If nobody here knows, what's the appropriate discussion forum where people might actually know these things? (It's an interesting intersection between Python, Qt and Scintilla, so I imagine the set of people who would know is small) Let's assume prefs.declare() just sets up a dict that returns the value for the given key (I've verified this -- it's not the problem). Let's assume scintilla is reasonably properly constructed into its host window QWidget. Specifically, if I apply a bundled lexer (such as QsciLexerPython), it takes effect and does show styled text. prefs.declare('font.name.margin', "MS Dlg") prefs.declare('font.size.margin', 8) prefs.declare('font.name.code', "Courier New") prefs.declare('font.size.code', 10) prefs.declare('color.editline', "#d0e0ff") class LexerErlang(Qsci.QsciLexerCustom): def __init__(self, obj = None): Qsci.QsciLexerCustom.__init__(self, obj) self.sci = None self.plainFont = QtGui.QFont() self.plainFont.setPointSize(int(prefs.get('font.size.code'))) self.plainFont.setFamily(prefs.get('font.name.code')) self.marginFont = QtGui.QFont() self.marginFont.setPointSize(int(prefs.get('font.size.code'))) self.marginFont.setFamily(prefs.get('font.name.margin')) self.boldFont = QtGui.QFont() self.boldFont.setPointSize(int(prefs.get('font.size.code'))) self.boldFont.setFamily(prefs.get('font.name.code')) self.boldFont.setBold(True) self.styles = [ Qsci.QsciStyle(0, QtCore.QString("base"), QtGui.QColor("#000000"), QtGui.QColor("#ffffff"), self.plainFont, True), Qsci.QsciStyle(1, QtCore.QString("comment"), QtGui.QColor("#008000"), QtGui.QColor("#eeffee"), self.marginFont, True), Qsci.QsciStyle(2, QtCore.QString("keyword"), QtGui.QColor("#000080"), QtGui.QColor("#ffffff"), self.boldFont, True), Qsci.QsciStyle(3, QtCore.QString("string"), QtGui.QColor("#800000"), QtGui.QColor("#ffffff"), self.marginFont, True), Qsci.QsciStyle(4, QtCore.QString("atom"), QtGui.QColor("#008080"), QtGui.QColor("#ffffff"), self.plainFont, True), Qsci.QsciStyle(5, QtCore.QString("macro"), QtGui.QColor("#808000"), QtGui.QColor("#ffffff"), self.boldFont, True), Qsci.QsciStyle(6, QtCore.QString("error"), QtGui.QColor("#000000"), QtGui.QColor("#ffd0d0"), self.plainFont, True), ] print("LexerErlang created") def description(self, ix): for i in self.styles: if i.style() == ix: return QtCore.QString(i.description()) return QtCore.QString("") def setEditor(self, sci): self.sci = sci Qsci.QsciLexerCustom.setEditor(self, sci) print("LexerErlang.setEditor()") def styleText(self, start, end): print("LexerErlang.styleText(%d,%d)" % (start, end)) lines = self.getText(start, end) offset = start self.startStyling(offset, 0) print("startStyling()") for i in lines: if i == "": self.setStyling(1, self.styles[0]) print("setStyling(1)") offset += 1 continue if i[0] == '%': self.setStyling(len(i)+1, self.styles[1]) print("setStyling(%)") offset += len(i)+1 continue self.setStyling(len(i)+1, self.styles[0]) print("setStyling(n)") offset += len(i)+1 def getText(self, start, end): data = self.sci.text() print("LexerErlang.getText(): " + str(len(data)) + " chars") return data[start:end].split('\n') Applied to the QsciScintilla widget as follows: _lexers = { 'erl': (Q.SCLEX_ERLANG, LexerErlang), 'hrl': (Q.SCLEX_ERLANG, LexerErlang), 'html': (Q.SCLEX_HTML, Qsci.QsciLexerHTML), 'css': (Q.SCLEX_CSS, Qsci.QsciLexerCSS), 'py': (Q.SCLEX_PYTHON, Qsci.QsciLexerPython), 'php': (Q.SCLEX_PHP, Qsci.QsciLexerHTML), 'inc': (Q.SCLEX_PHP, Qsci.QsciLexerHTML), 'js': (Q.SCLEX_CPP, Qsci.QsciLexerJavaScript), 'cpp': (Q.SCLEX_CPP, Qsci.QsciLexerCPP), 'h': (Q.SCLEX_CPP, Qsci.QsciLexerCPP), 'cxx': (Q.SCLEX_CPP, Qsci.QsciLexerCPP), 'hpp': (Q.SCLEX_CPP, Qsci.QsciLexerCPP), 'c': (Q.SCLEX_CPP, Qsci.QsciLexerCPP), 'hxx': (Q.SCLEX_CPP, Qsci.QsciLexerCPP), 'tpl': (Q.SCLEX_CPP, Qsci.QsciLexerCPP), 'xml': (Q.SCLEX_XML, Qsci.QsciLexerXML), } ... inside my document window class ... def addContentsDocument(self, contents, title): handler = self.makeScintilla() handler.title = title sci = handler.sci sci.append(contents) self.tabWidget.addTab(sci, title) self.tabWidget.setCurrentWidget(sci) self.applyLexer(sci, title) EventBus.bus.broadcast('command.done', {'text': 'Opened ' + title}) return handler def applyLexer(self, sci, title): (language, lexer) = language_and_lexer_from_title(title) if lexer: l = lexer() print("making lexer: " + str(l)) sci.setLexer(l) else: print("setting lexer by id: " + str(language)) sci.SendScintilla(Qsci.QsciScintillaBase.SCI_SETLEXER, language) linst = sci.lexer() print("lexer: " + str(linst)) def makeScintilla(self): sci = Qsci.QsciScintilla() sci.setUtf8(True) sci.setTabIndents(True) sci.setIndentationsUseTabs(False) sci.setIndentationWidth(4) sci.setMarginsFont(self.smallFont) sci.setMarginWidth(0, self.smallFontMetrics.width('00000')) sci.setFont(self.monoFont) sci.setAutoIndent(True) sci.setBraceMatching(Qsci.QsciScintilla.StrictBraceMatch) handler = SciHandler(sci) self.handlers[sci] = handler sci.setMarginLineNumbers(0, True) sci.setCaretLineVisible(True) sci.setCaretLineBackgroundColor(QtGui.QColor(prefs.get('color.editline'))) return handler Let's assume the rest of the application works, too (because it does :-)

    Read the article

  • wxPthon problems with Wrapping StaticText

    - by Scott B
    Hello. I am having an issue with wxPython. A simplified version of the code is posted below (white space, comments, etc removed to reduce size - but the general format to my program is kept roughly the same). When I run the script, the static text correctly wraps as it should, but the other items in the panel do not move down (they act as if the statictext is only one line and thus not everything is visible). If I manually resize the window/frame, even just a tiny amount, everything gets corrected and displays as it is should. I took screen shots to show this behavior, but I just created this account and thus don't have the required 10 reputation points to be allowed to post pictures. Why does it not display correctly to begin with? I've tried all sorts of combination's of GetParent().Refresh() or Update() and GetTopLevelParent().Update() or Refresh(). I've tried everything I can think of but cannot get it to display correctly without manually resizing the frame/window. Once re-sized, it works exactly as I want it to. Information: Windows XP Python 2.5.2 wxPython 2.8.11.0 (msw-unicode) Any suggestions? Thanks! Code: #! /usr/bin/python import wx class StaticWrapText(wx.PyControl): def __init__(self, parent, id=wx.ID_ANY, label='', pos=wx.DefaultPosition, size=wx.DefaultSize, style=wx.NO_BORDER, validator=wx.DefaultValidator, name='StaticWrapText'): wx.PyControl.__init__(self, parent, id, pos, size, style, validator, name) self.statictext = wx.StaticText(self, wx.ID_ANY, label, style=style) self.wraplabel = label #self.wrap() def wrap(self): self.Freeze() self.statictext.SetLabel(self.wraplabel) self.statictext.Wrap(self.GetSize().width) self.Thaw() def DoGetBestSize(self): self.wrap() #print self.statictext.GetSize() self.SetSize(self.statictext.GetSize()) return self.GetSize() class TestPanel(wx.Panel): def __init__(self, *args, **kwargs): # Init the base class wx.Panel.__init__(self, *args, **kwargs) self.createControls() def createControls(self): # --- Panel2 ------------------------------------------------------------- self.Panel2 = wx.Panel(self, -1) msg1 = 'Below is a List of Files to be Processed' staticBox = wx.StaticBox(self.Panel2, label=msg1) Panel2_box1_v1 = wx.StaticBoxSizer(staticBox, wx.VERTICAL) Panel2_box2_h1 = wx.BoxSizer(wx.HORIZONTAL) Panel2_box3_v1 = wx.BoxSizer(wx.VERTICAL) self.wxL_Inputs = wx.ListBox(self.Panel2, wx.ID_ANY, style=wx.LB_EXTENDED) sz = dict(size=(120,-1)) wxB_AddFile = wx.Button(self.Panel2, label='Add File', **sz) wxB_DeleteFile = wx.Button(self.Panel2, label='Delete Selected', **sz) wxB_ClearFiles = wx.Button(self.Panel2, label='Clear All', **sz) Panel2_box3_v1.Add(wxB_AddFile, 0, wx.TOP, 0) Panel2_box3_v1.Add(wxB_DeleteFile, 0, wx.TOP, 0) Panel2_box3_v1.Add(wxB_ClearFiles, 0, wx.TOP, 0) Panel2_box2_h1.Add(self.wxL_Inputs, 1, wx.ALL|wx.EXPAND, 2) Panel2_box2_h1.Add(Panel2_box3_v1, 0, wx.ALL|wx.EXPAND, 2) msg = 'This is a long line of text used to test the autowrapping ' msg += 'static text message. ' msg += 'This is a long line of text used to test the autowrapping ' msg += 'static text message. ' msg += 'This is a long line of text used to test the autowrapping ' msg += 'static text message. ' msg += 'This is a long line of text used to test the autowrapping ' msg += 'static text message. ' staticMsg = StaticWrapText(self.Panel2, label=msg) Panel2_box1_v1.Add(staticMsg, 0, wx.ALL|wx.EXPAND, 2) Panel2_box1_v1.Add(Panel2_box2_h1, 1, wx.ALL|wx.EXPAND, 0) self.Panel2.SetSizer(Panel2_box1_v1) # --- Combine Everything ------------------------------------------------- final_vbox = wx.BoxSizer(wx.VERTICAL) final_vbox.Add(self.Panel2, 1, wx.ALL|wx.EXPAND, 2) self.SetSizerAndFit(final_vbox) class TestFrame(wx.Frame): def __init__(self, *args, **kwargs): # Init the base class wx.Frame.__init__(self, *args, **kwargs) panel = TestPanel(self) self.SetClientSize(wx.Size(500,500)) self.Center() class wxFileCleanupApp(wx.App): def __init__(self, *args, **kwargs): # Init the base class wx.App.__init__(self, *args, **kwargs) def OnInit(self): # Create the frame, center it, and show it frame = TestFrame(None, title='Test Frame') frame.Show() return True if __name__ == '__main__': app = wxFileCleanupApp() app.MainLoop() EDIT: See my post below for a solution that works!

    Read the article

  • Data munging and data import scripting

    - by morpheous
    I need to write some scripts to carry out some tasks on my server (running Ubuntu server 8.04 TLS). The tasks are to be run periodically, so I will be running the scripts as cron jobs. I have divided the tasks into "group A" and "group B" - because (in my mind at least), they are a bit different. Task Group A import data from a file and possibly reformat it - by reformatting, I mean doing things like santizing the data, possibly normalizing it and or running calculations on 'columns' of the data Import the munged data into a database. For now, I am mostly using mySQL for the vast majority of imports - although some files will be imported into a sqlLite database. Note: The files will be mostly text files, although some of the files are in a binary format (my own proprietary format, written by a C++ application I developed). Task Group B Extract data from the database Perform calculations on the data and either insert or update tables in the database. My coding experience is is primarily as a C/C++ developer, although I have been using PHP as well for the last 2 years or so. I am from a windows background so I am still finding my feet in the linux environment. My question is this - I need to write scripts to perform the tasks I described above. Although I suppose I could write a few C++ applications to be used in the shell scripts, I think it may be better to write them in a scripting language (maybe this is a flawed assumption?). My thinking is that it would be easier to modify thins in a script - no need to rebuild etc for changes to functionality. Additionally, C++ data munging in C++ tends to involve more lines of code than "natural" scripting languages such as Perl, Python etc. Assuming that the majority of people on here agree that scripting is the way to go, herein lies my dilema. Which scripting language to use to perform the tasks above (giving my background). My gut instinct tells me that Perl (shudder) would be the most obvious choice for performing all of the above tasks. BUT (and that is a big BUT). The mere mention of Perl makes my toes curl, as I had a very, very bag experience with it a while back. The syntax seems quite unnatural to me - despite how many times I have tried to learn it - so if possible, I would really like to give it a miss. PHP (which I already know), also am not sure is a good candidate for scripting on the CLI (I have not seen many examples on how to do this etc - so I may be wrong). The last thing I must mention is that IF I have to learn a new language in order to do this, I cannot afford (time constraint) to spend more than a day, in learning the key commands/features required in order to do this (I can always learn the details of the language later, once I have actually deployed the scripts). So, which scripting language would you recommend (PHP, Python, Perl, [insert your favorite here]) - and most importantly WHY?. Or, should I just stick to writing little C++ applications that I call in a shell script?. Lastly, if you have suggested a scripting language, can you please show with a FEW lines (Perl mongers - I'm looking in your direction [nothing to cryptic!] ;) ) how I can use the language you suggested to do what I want to do. Hopefully, the lines you present will convince me that it can be done easily and elegantly in the language you suggested.

    Read the article

  • TDD - beginner problems and stumbling blocks

    - by Noufal Ibrahim
    While I've written unit tests for most of the code I've done, I only recently got my hands on a copy of TDD by example by Kent Beck. I have always regretted certain design decisions I made since they prevented the application from being 'testable'. I read through the book and while some of it looks alien, I felt that I could manage it and decided to try it out on my current project which is basically a client/server system where the two pieces communicate via. USB. One on the gadget and the other on the host. The application is in Python. I started off and very soon got entangled in a mess of rewrites and tiny tests which I later figured didn't really test anything. I threw away most of them and and now have a working application for which the tests have all coagulated into just 2. Based on my experiences, I have a few questions which I'd like to ask. I gained some information from http://stackoverflow.com/questions/1146218/new-to-tdd-are-there-sample-applications-with-tests-to-show-how-to-do-tdd but have some specific questions which I'd like answers to/discussion on. Kent Beck uses a list which he adds to and strikes out from to guide the development process. How do you make such a list? I initially had a few items like "server should start up", "server should abort if channel is not available" etc. but they got mixed and finally now, it's just something like "client should be able to connect to server" (which subsumed server startup etc.). How do you handle rewrites? I initially selected a half duplex system based on named pipes so that I could develop the application logic on my own machine and then later add the USB communication part. It them moved to become a socket based thing and then moved from using raw sockets to using the Python SocketServer module. Each time things changed, I found that I had to rewrite considerable parts of the tests which was annoying. I'd figured that the tests would be a somewhat invariable guide during my development. They just felt like more code to handle. I needed a client and a server to communicate through the channel to test either side. I could mock one of the sides to test the other but then the whole channel wouldn't be tested and I worry that I'd miss that. This detracted from the whole red/green/refactor rhythm. Is this just lack of experience or am I doing something wrong? The "Fake it till you make it" left me with a lot of messy code that I later spent a lot of time to refactor and clean up. Is this the way things work? At the end of the session, I now have my client and server running with around 3 or 4 unit tests. It took me around a week to do it. I think I could have done it in a day if I were using the unit tests after code way. I fail to see the gain. I'm looking for comments and advice from people who have implemented large non trivial projects completely (or almost completely) using this methodology. It makes sense to me to follow the way after I have something already running and want to add a new feature but doing it from scratch seems to tiresome and not worth the effort. P.S. : Please let me know if this should be community wiki and I'll mark it like that. Update 0 : All the answers were equally helpful. I picked the one I did because it resonated with my experiences the most. Update 1: Practice Practice Practice!

    Read the article

  • Disco/MapReduce: Using results of previous iteration as input to new iteration

    - by muckabout
    Currently am implementing PageRank on Disco. As an iterative algorithm, the results of one iteration are used as input to the next iteration. I have a large file which represents all the links, with each row representing a page and the values in the row representing the pages to which it links. For Disco, I break this file into N chunks, then run MapReduce for one round. As a result, I get a set of (page, rank) tuples. I'd like to feed this rank to the next iteration. However, now my mapper needs two inputs: the graph file, and the pageranks. I would like to "zip" together the graph file and the page ranks, such that each line represents a page, it's rank, and it's out links. Since this graph file is separated into N chunks, I need to split the pagerank vector into N parallel chunks, and zip the regions of the pagerank vectors to the graph chunks This all seems more complicated than necessary, and as a pretty straightforward operation (with the quintessential mapreduce algorithm), it seems I'm missing something about Disco that could really simplify the approach. Any thoughts?

    Read the article

  • Sphinx Error Unknow directive type "automodule" or "autoclass"

    - by user1130381
    I need document my python project using Sphinx. But I can't use autodoc. When I config my project I select the option "extension autodoc", but now if I use .. autoclass:: Class, I have a ERROR: ERROR: Unknown directive type "autoclass" I configure the PYTHONPATH, and now it's good. But I already have this problem. My index file is: .. ATOM documentation master file, created by sphinx-quickstart on Thu Nov 22 15:24:42 2012. You can adapt this file completely to your liking, but it should at least contain the root toctree directive. Welcome to ATOM's documentation! Contents: .. toctree:: :maxdepth: 2 .. automodule:: atom Indices and tables :ref:genindex :ref:modindex :ref:search Thank you, I need that someone say me how I find the problem, or how i can fix this! Sorry for my English, I start now to learn English.

    Read the article

  • Adaptive Threshold in OpenCV (Version 1 - the swig version)

    - by Neil Benn
    Hello I'm trying to get adaptive thresholding working in the python binding to opencv (the swig one - cannot get opencv 2.0 working as I am using a beagleboard as the cross compiling is not working yet). I have a greyscale image (ccg.jpg) and the following code import opencv from opencv import highgui img = highgui.cvLoadImage("ccg.png") img_bw = opencv.cvCreateImage(opencv.cvGetSize(img), opencv.IPL_DEPTH_8U, 1) opencv.cvAdaptiveThreshold(img, img_bw, 125, opencv.CV_ADAPTIVE_THRESH_MEAN_C, opencv.CV_THRESH_BINARY, 7, 10) When I run this I get the error: RuntimeError: openCV Error: Status=Formats of input arguments do not match function name=cvAdaptiveThreshold error messgae= file_name=cvadapthresh.cpp line=122 I've also tried having both the source and dest arguments both the same (greyscale) and I get the error 'Unsupported format or combination of formats'. Does anyone have any clues as to where I could be going wrong? Cheers, Neil

    Read the article

  • Redirect logging output using custom logging handler

    - by mridang
    Hi Guys, I'm using a module in my python app that writes a lot a of messages using the logging module. Initially I was using this in a console application and it was pretty easy to get the logging output to display on the console using a console handler. Now I've developed a GUI version of my app using wxPython and I'd like to display all the logging output to a custom control — a multi-line textCtrl. Is there a way i could create a custom logging handler so i can redirect all the logging output there and display the logging messages wherever/however I want — in this case, a wxPython app. Thanks

    Read the article

  • PHP Frameworks (CodeIgnitor, Yii, CakePHP) vs. Django

    - by niting
    I have to develop a site which has to accomodate around 2000 users a day and speed is a criterion for it. Moreover, the site is a user oriented one where the user will be able to log in and check his profile, register for specific events he/she wants to participate in. The site is to be hosted on a VPS server.Although I have pretty good experience with python and PHP but I have no idea how to use either of the framework. We have plenty of time to experiment and learn one of the above frameworks.Could you please specify which one would be preferred for such a scenario considering speed, features, and security of the site. Thanks, niting

    Read the article

  • Easy_install of wxpython has "setup script" error.

    - by vgm64
    I have an install of python 2.5 that fink placed in /sw/bin/. I use the easy install command sudo /sw/bin/easy_install wxPython to try to install wxpython and I get an error while trying to process wxPython-src-2.8.9.1.tab.bz2 that there is not setup script. Easy-install has worked for several other installations until this one. Any help on why it's busting now? EDIT: The error occurs before dumping back to shell prompt. Reading http://wxPython.org/download.php Best match: wxPython src-2.8.9.1 Downloading http://downloads.sourceforge.net/wxpython/wxPython-src-2.8.9.1.tar.bz2 Processing wxPython-src-2.8.9.1.tar.bz2 error: Couldn't find a setup script in /tmp/easy_install-tNg6FG/wxPython-src-2.8.9.1.tar.bz2

    Read the article

  • urlencode an array of values

    - by Ikke
    I'm trying to urlencode an dictionary in python with urllib.urlencode. The problem is, I have to encode an array. The result needs to be: criterias%5B%5D=member&criterias%5B%5D=issue #unquoted: criterias[]=member&criterias[]=issue But the result I get is: criterias=%5B%27member%27%2C+%27issue%27%5D #unquoted: criterias=['member',+'issue'] I have tried several things, but I can't seem to get the right result. import urllib criterias = ['member', 'issue'] params = { 'criterias[]': criterias, } print urllib.urlencode(params) If I use cgi.parse_qs to decode a correct query string, I get this as result: {'criterias[]': ['member', 'issue']} But if I encode that result, I get a wrong result back. Is there a way to produce the expected result?

    Read the article

  • Why allow concatenation of string literals?

    - by Caspin
    I recently got bit by a subtle bug. char ** int2str = { "zero", // 0 "one", // 1 "two" // 2 "three",// 3 nullptr }; assert( values[1] == "one"_s ); // passes assert( values[2] == "two"_s ); // fails If you have godlike code review powers you'll notice I forgot the , after "two". After the considerable effort to find that bug I've got to ask why would anyone ever want this behavior? I can see how this might be useful for macro magic, but then why is this a "feature" in a modern language like python? Have you ever used string literal concatenation in production code?

    Read the article

  • Any task-control algorithms programming practices?

    - by NumberFour
    Hi, I was just wondering if there's any field which concerns the task-control programming (or at least that's the way I call it). For a better explanation of task-control consider the following scenario: An application (master-thread) waits for a command - which might be a particular action or a set of actions the application should perform. When a command is received the master-thread creates a task (= spawns an independent thread which actually does the action) and adds a record in it's task-list - thus keeping track of the time of execution, thread handle, task priority...etc. The master-thread awaits for any other incoming commands while taking care of all the tasks - e.g: kills tasks running too long, prioritizes tasks with higher priorities, kills a task on a request of another task, limits the number of currently running tasks, allows task scheduling, cleans finished tasks (threads) and so on. The model is pretty similar to what we can see in OS dealing with running processes. Are there any good practices programming such task-models or is there some theoretical work done in this field? Maybe my question is too generalized, but at least I wanted to know whether there are any experiences working on such models or if there's a better approach. Thanks for any answers.

    Read the article

  • django admin: Add a "remove file" field for Image- or FileFields

    - by w-
    I was hunting around the net for a way to easily allow users to blank out imagefield/filefields they have set in the admin. I found this http://www.djangosnippets.org/snippets/894/ What was really interesting to me here was the code posted in the comment by rfugger remove_the_file = forms.BooleanField(required=False) def save(self, *args, **kwargs): object = super(self.__class__, self).save(*args, **kwargs) if self.cleaned_data.get('remove_the_file'): object.the_file = '' return object When i try to use this in my own form I basically added this to my admin.py which already had a BlahAdmin class BlahModelForm(forms.ModelForm): class Meta: model = Blah remove_img01 = forms.BooleanField(required=False) def save(self, *args, **kwargs): object = super(self.__class__, self).save(*args, **kwargs) if self.cleaned_data.get('remove_img01'): object.img01 = '' return object when i run it I get this error maximum recursion depth exceeded while calling a Python object at this line object = super(self.__class__, self).save(*args, **kwargs) When i think about it for a bit, it seems obvious that it is just infinitely calling itself causing the error. My problem is i can't figure out what is the correct way i should be doing this. Any suggestions? thanks

    Read the article

  • User management API

    - by Akshey
    Hi, I am developing an application suite where users will need to connect to a server and depending on their account type they will be given some services. The server will run Linux. Can you please suggest me some user management API which I can use to develop the server program? By user management I mean user authentication and other related functionalities. I prefer to work in C++ or python, but any other language should not be a problem. Please note that this application suite is not web based. Due to security issues, I do not want to give each user a separate account on the linux server. Thanks, Akshey

    Read the article

  • Why aren't we programming on the GPU???

    - by Chris
    So I finally took the time to learn CUDA and get it installed and configured on my computer and I have to say, I'm quite impressed! Here's how it does rendering the Mandelbrot set at 1280 x 678 pixels on my home PC with a Q6600 and a GeForce 8800GTS (max of 1000 iterations): Maxing out all 4 CPU cores with OpenMP: 2.23 fps Running the same algorithm on my GPU: 104.7 fps And here's how fast I got it to render the whole set at 8192 x 8192 with a max of 1000 iterations: Serial implemetation on my home PC: 81.2 seconds All 4 CPU cores on my home PC (OpenMP): 24.5 seconds 32 processors on my school's super computer (MPI with master-worker): 1.92 seconds My home GPU (CUDA): 0.310 seconds 4 GPUs on my school's super computer (CUDA with static domain decomposition): 0.0547 seconds So here's my question - if we can get such huge speedups by programming the GPU instead of the CPU, why is nobody doing it??? I can think of so many things we could speed up like this, and yet I don't know of many commercial apps that are actually doing it. Also, what kinds of other speedups have you seen by offloading your computations to the GPU?

    Read the article

< Previous Page | 299 300 301 302 303 304 305 306 307 308 309 310  | Next Page >