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	<title>Comments for Laurent Luce&#039;s Blog</title>
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	<link>http://www.laurentluce.com</link>
	<description>Technical blog on web technologies</description>
	<lastBuildDate>Thu, 19 Jan 2012 04:18:25 +0000</lastBuildDate>
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		<title>Comment on Upload to Django with progress bar using Ajax and jQuery by Laurent Luce</title>
		<link>http://www.laurentluce.com/posts/upload-to-django-with-progress-bar-using-ajax-and-jquery/comment-page-1/#comment-10885</link>
		<dc:creator>Laurent Luce</dc:creator>
		<pubDate>Thu, 19 Jan 2012 04:18:25 +0000</pubDate>
		<guid isPermaLink="false">http://www.laurentluce.com/?p=93#comment-10885</guid>
		<description>@Josh. I added examples for showRequest() and showResponse(). In my case, I return some xml in upload() containing a status value which is parsed in showResponse().

You are correct that you need to add url patterns in urls.py for upload(), get_upload_progress() and the upload form. I build the upload form using javascript and display it as a dialog box to avoid page navigation so I don&#039;t have a form url.

Regarding handling multiple files, HttpRequest.FILES in Django contains the list of files posted. upload() should be modified to handle multiple files. The rest can stay the same.</description>
		<content:encoded><![CDATA[<p>@Josh. I added examples for showRequest() and showResponse(). In my case, I return some xml in upload() containing a status value which is parsed in showResponse().</p>
<p>You are correct that you need to add url patterns in urls.py for upload(), get_upload_progress() and the upload form. I build the upload form using javascript and display it as a dialog box to avoid page navigation so I don&#8217;t have a form url.</p>
<p>Regarding handling multiple files, HttpRequest.FILES in Django contains the list of files posted. upload() should be modified to handle multiple files. The rest can stay the same.</p>
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		<title>Comment on Upload to Django with progress bar using Ajax and jQuery by Josh</title>
		<link>http://www.laurentluce.com/posts/upload-to-django-with-progress-bar-using-ajax-and-jquery/comment-page-1/#comment-10831</link>
		<dc:creator>Josh</dc:creator>
		<pubDate>Tue, 17 Jan 2012 23:01:00 +0000</pubDate>
		<guid isPermaLink="false">http://www.laurentluce.com/?p=93#comment-10831</guid>
		<description>Thanks for this basic intro, I have learned a lot already. I&#039;m trying to implement this (just a test for now), but I am missing some key bits of info. The main problems I&#039;m having:
- I know that I will need to supply a function/handler for &#039;showRequest&#039; and &#039;showResponse&#039; but I don&#039;t know what should go into these. Could you update your examples above with something simple?

- I know you said that it is app dependent, but for purposes of filling out this tutorial, could you post more of your &#039;upload&#039; view routine, specifically the return?

- could you discuss more about how to map the &#039;upload&#039; and &#039;get_upload_progress&#039; in urls.py, and how that relates to the view containing the upload form? Do I need 3 entries in urls.py? (one for the form, one for &#039;upload&#039;, and one for &#039;get_upload_progress&#039;?

- any idea how this might be modified for handling multiple files in a Django-friendly manner?</description>
		<content:encoded><![CDATA[<p>Thanks for this basic intro, I have learned a lot already. I&#8217;m trying to implement this (just a test for now), but I am missing some key bits of info. The main problems I&#8217;m having:<br />
- I know that I will need to supply a function/handler for &#8216;showRequest&#8217; and &#8216;showResponse&#8217; but I don&#8217;t know what should go into these. Could you update your examples above with something simple?</p>
<p>- I know you said that it is app dependent, but for purposes of filling out this tutorial, could you post more of your &#8216;upload&#8217; view routine, specifically the return?</p>
<p>- could you discuss more about how to map the &#8216;upload&#8217; and &#8216;get_upload_progress&#8217; in urls.py, and how that relates to the view containing the upload form? Do I need 3 entries in urls.py? (one for the form, one for &#8216;upload&#8217;, and one for &#8216;get_upload_progress&#8217;?</p>
<p>- any idea how this might be modified for handling multiple files in a Django-friendly manner?</p>
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		<title>Comment on Twitter sentiment analysis using Python and NLTK by Elliott</title>
		<link>http://www.laurentluce.com/posts/twitter-sentiment-analysis-using-python-and-nltk/comment-page-1/#comment-10700</link>
		<dc:creator>Elliott</dc:creator>
		<pubDate>Sun, 15 Jan 2012 05:48:19 +0000</pubDate>
		<guid isPermaLink="false">http://www.laurentluce.com/?p=321#comment-10700</guid>
		<description>@Laurent Luce Pour les liens en français, je sais que ça peut sembler un peu arbitraire, mais prendre un corpus en anglais et le faire passer par Google Translate, je vois pas de raison pour que ça marche pas!</description>
		<content:encoded><![CDATA[<p>@Laurent Luce Pour les liens en français, je sais que ça peut sembler un peu arbitraire, mais prendre un corpus en anglais et le faire passer par Google Translate, je vois pas de raison pour que ça marche pas!</p>
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		<title>Comment on Twitter sentiment analysis using Python and NLTK by Laurent Luce</title>
		<link>http://www.laurentluce.com/posts/twitter-sentiment-analysis-using-python-and-nltk/comment-page-1/#comment-10677</link>
		<dc:creator>Laurent Luce</dc:creator>
		<pubDate>Sat, 14 Jan 2012 19:12:36 +0000</pubDate>
		<guid isPermaLink="false">http://www.laurentluce.com/?p=321#comment-10677</guid>
		<description>@Elliott Thanks for the link to that pre-classified test corpus. Here is another one using emoticons: http://www.stanford.edu/~alecmgo/cs224n/twitterdata.2009.05.25.c.zip
I had to manually classified the tweets on my side because they are in French and I didn&#039;t find a pre-classified corpus in French.</description>
		<content:encoded><![CDATA[<p>@Elliott Thanks for the link to that pre-classified test corpus. Here is another one using emoticons: <a href="http://www.stanford.edu/~alecmgo/cs224n/twitterdata.2009.05.25.c.zip" rel="nofollow">http://www.stanford.edu/~alecmgo/cs224n/twitterdata.2009.05.25.c.zip</a><br />
I had to manually classified the tweets on my side because they are in French and I didn&#8217;t find a pre-classified corpus in French.</p>
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		<title>Comment on Python string objects implementation by Laurent Luce</title>
		<link>http://www.laurentluce.com/posts/python-string-objects-implementation/comment-page-1/#comment-10676</link>
		<dc:creator>Laurent Luce</dc:creator>
		<pubDate>Sat, 14 Jan 2012 18:55:56 +0000</pubDate>
		<guid isPermaLink="false">http://www.laurentluce.com/?p=307#comment-10676</guid>
		<description>@pythonee I used Dia.</description>
		<content:encoded><![CDATA[<p>@pythonee I used Dia.</p>
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	<item>
		<title>Comment on Python string objects implementation by pythonee</title>
		<link>http://www.laurentluce.com/posts/python-string-objects-implementation/comment-page-1/#comment-10568</link>
		<dc:creator>pythonee</dc:creator>
		<pubDate>Thu, 12 Jan 2012 21:39:13 +0000</pubDate>
		<guid isPermaLink="false">http://www.laurentluce.com/?p=307#comment-10568</guid>
		<description>How did you draw the diagram</description>
		<content:encoded><![CDATA[<p>How did you draw the diagram</p>
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		<title>Comment on Twitter sentiment analysis using Python and NLTK by Elliott</title>
		<link>http://www.laurentluce.com/posts/twitter-sentiment-analysis-using-python-and-nltk/comment-page-1/#comment-10335</link>
		<dc:creator>Elliott</dc:creator>
		<pubDate>Sat, 07 Jan 2012 23:53:21 +0000</pubDate>
		<guid isPermaLink="false">http://www.laurentluce.com/?p=321#comment-10335</guid>
		<description>@Laurent Luce The web interface is quite a good idea. If anyone is looking for a pre-classified test corpus, I found one here: http://sandersanalytics.com/lab/twitter-sentiment/.</description>
		<content:encoded><![CDATA[<p>@Laurent Luce The web interface is quite a good idea. If anyone is looking for a pre-classified test corpus, I found one here: <a href="http://sandersanalytics.com/lab/twitter-sentiment/" rel="nofollow">http://sandersanalytics.com/lab/twitter-sentiment/</a>.</p>
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		<title>Comment on Twitter sentiment analysis using Python and NLTK by Laurent Luce</title>
		<link>http://www.laurentluce.com/posts/twitter-sentiment-analysis-using-python-and-nltk/comment-page-1/#comment-10331</link>
		<dc:creator>Laurent Luce</dc:creator>
		<pubDate>Sat, 07 Jan 2012 19:13:43 +0000</pubDate>
		<guid isPermaLink="false">http://www.laurentluce.com/?p=321#comment-10331</guid>
		<description>@ Hywel I fixed the call to get_word_features. I am trimming the number of word features in the real application but I keep it simpler for the post.</description>
		<content:encoded><![CDATA[<p>@ Hywel I fixed the call to get_word_features. I am trimming the number of word features in the real application but I keep it simpler for the post.</p>
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	<item>
		<title>Comment on Twitter sentiment analysis using Python and NLTK by Laurent Luce</title>
		<link>http://www.laurentluce.com/posts/twitter-sentiment-analysis-using-python-and-nltk/comment-page-1/#comment-10330</link>
		<dc:creator>Laurent Luce</dc:creator>
		<pubDate>Sat, 07 Jan 2012 19:08:39 +0000</pubDate>
		<guid isPermaLink="false">http://www.laurentluce.com/?p=321#comment-10330</guid>
		<description>@Hywel You are correct. The same can apply to other languages. I am actually using that method to classify tweets written in French. I am not satisfied with the results yet because the sample I classified manually is too small. An issue with other languages than English is that it is difficult to find a large corpus of classified tweets.</description>
		<content:encoded><![CDATA[<p>@Hywel You are correct. The same can apply to other languages. I am actually using that method to classify tweets written in French. I am not satisfied with the results yet because the sample I classified manually is too small. An issue with other languages than English is that it is difficult to find a large corpus of classified tweets.</p>
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	<item>
		<title>Comment on Twitter sentiment analysis using Python and NLTK by Laurent Luce</title>
		<link>http://www.laurentluce.com/posts/twitter-sentiment-analysis-using-python-and-nltk/comment-page-1/#comment-10329</link>
		<dc:creator>Laurent Luce</dc:creator>
		<pubDate>Sat, 07 Jan 2012 18:55:52 +0000</pubDate>
		<guid isPermaLink="false">http://www.laurentluce.com/?p=321#comment-10329</guid>
		<description>@Elliott I built a simple web interface to help me classifying the tweets. I also stored the tweets in a Redis DB in 2 different lists: positive and negative. For the article, I am using hard coded list to simplify things.</description>
		<content:encoded><![CDATA[<p>@Elliott I built a simple web interface to help me classifying the tweets. I also stored the tweets in a Redis DB in 2 different lists: positive and negative. For the article, I am using hard coded list to simplify things.</p>
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