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<channel>
	<title>Huy Nguyen</title>
	
	<link>http://www.huyng.com</link>
	<description>occasionally prolific</description>
	<lastBuildDate>Sun, 29 May 2011 17:59:15 +0000</lastBuildDate>
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		<title>Could testing in Python be simplified?</title>
		<link>http://feedproxy.google.com/~r/huyng/~3/T_qdLD4YRr0/</link>
		<comments>http://www.huyng.com/archives/could-testing-in-python-be-simplified/792/#comments</comments>
		<pubDate>Sat, 28 May 2011 23:00:23 +0000</pubDate>
		<dc:creator>Huy</dc:creator>
				<category><![CDATA[python]]></category>

		<guid isPermaLink="false">http://www.huyng.com/?p=792</guid>
		<description>Edited on May 29 : After writing this article, Christian Heimes pointed out to me that the debug method on unttest.TestCase allows you to run tests interactively. The idiot in me didn&amp;#8217;t do enough research before writing this rant. I&amp;#8217;m leaving this post up to provide some context for future visitors/googlers who are looking for [...]&lt;img src="http://feeds.feedburner.com/~r/huyng/~4/T_qdLD4YRr0" height="1" width="1"/&gt;</description>
		<wfw:commentRss>http://www.huyng.com/archives/could-testing-in-python-be-simplified/792/feed/</wfw:commentRss>
		<slash:comments>10</slash:comments>
		<feedburner:origLink>http://www.huyng.com/archives/could-testing-in-python-be-simplified/792/</feedburner:origLink></item>
		<item>
		<title>Textmate hack: A keyboard shortcut for opening files in a new window</title>
		<link>http://feedproxy.google.com/~r/huyng/~3/9XMmrlpngDA/</link>
		<comments>http://www.huyng.com/archives/textmate-hack-a-keyboard-shortcut-for-opening-files-in-a-new-window/781/#comments</comments>
		<pubDate>Wed, 11 May 2011 16:26:34 +0000</pubDate>
		<dc:creator>Huy</dc:creator>
				<category><![CDATA[misc]]></category>

		<guid isPermaLink="false">http://www.huyng.com/?p=781</guid>
		<description>Textmate has no split windows, and you can&amp;#8217;t open the same file within a project in a new window without resorting to using the mouse. Here&amp;#8217;s what I mean: Situations often arise where you have to refrence one file while editing another. Maybe you want to view a header file while editing its implementation code. [...]&lt;img src="http://feeds.feedburner.com/~r/huyng/~4/9XMmrlpngDA" height="1" width="1"/&gt;</description>
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		<slash:comments>0</slash:comments>
		<feedburner:origLink>http://www.huyng.com/archives/textmate-hack-a-keyboard-shortcut-for-opening-files-in-a-new-window/781/</feedburner:origLink></item>
		<item>
		<title>A poorman’s Excel using sqlite, apsw, and csv2sql</title>
		<link>http://feedproxy.google.com/~r/huyng/~3/m0ZVaR_VooA/</link>
		<comments>http://www.huyng.com/archives/a-poormans-excel-using-sqlite-apsw-and-csv2sql/744/#comments</comments>
		<pubDate>Fri, 15 Apr 2011 11:19:40 +0000</pubDate>
		<dc:creator>Huy</dc:creator>
				<category><![CDATA[python]]></category>

		<guid isPermaLink="false">http://www.huyng.com/?p=744</guid>
		<description>Excel has always been my go-to tool for exploring the abundance of csv-formatted data that I often find on the internet. However, every once in awhile large datasets like these H1B salary figures show up1, where the shear amount of records exceeds Excel&amp;#8217;s 65k row limit. In these scenarios I turn to sqlite and a [...]&lt;img src="http://feeds.feedburner.com/~r/huyng/~4/m0ZVaR_VooA" height="1" width="1"/&gt;</description>
		<wfw:commentRss>http://www.huyng.com/archives/a-poormans-excel-using-sqlite-apsw-and-csv2sql/744/feed/</wfw:commentRss>
		<slash:comments>2</slash:comments>
		<feedburner:origLink>http://www.huyng.com/archives/a-poormans-excel-using-sqlite-apsw-and-csv2sql/744/</feedburner:origLink></item>
		<item>
		<title>So that’s how tracing JITs work …</title>
		<link>http://feedproxy.google.com/~r/huyng/~3/ET2S8ffF0bc/</link>
		<comments>http://www.huyng.com/archives/so-thats-how-tracing-jits-work/731/#comments</comments>
		<pubDate>Thu, 07 Apr 2011 19:05:34 +0000</pubDate>
		<dc:creator>Huy</dc:creator>
				<category><![CDATA[misc]]></category>

		<guid isPermaLink="false">http://www.huyng.com/?p=731</guid>
		<description>From PyPy&amp;#8217;s blog: Adding a JIT to your interpreter When it (the jit compiler) detects a loop of code in the target language that is executed often, the loop is considered &amp;#8220;hot&amp;#8221; and marked to be traced. The next time that loop is entered, the interpreter gets put in tracing mode where every executed instruction [...]&lt;img src="http://feeds.feedburner.com/~r/huyng/~4/ET2S8ffF0bc" height="1" width="1"/&gt;</description>
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		<slash:comments>0</slash:comments>
		<feedburner:origLink>http://www.huyng.com/archives/so-thats-how-tracing-jits-work/731/</feedburner:origLink></item>
		<item>
		<title>Sane color scheme for Matplotlib</title>
		<link>http://feedproxy.google.com/~r/huyng/~3/pWljVTv2ZQQ/</link>
		<comments>http://www.huyng.com/archives/sane-color-scheme-for-matplotlib/691/#comments</comments>
		<pubDate>Tue, 08 Feb 2011 16:01:27 +0000</pubDate>
		<dc:creator>Huy</dc:creator>
				<category><![CDATA[python]]></category>

		<guid isPermaLink="false">http://www.huyng.com/?p=691</guid>
		<description>What Python&amp;#8217;s MatPlotlib allows for in flexibility, it majorly lacks in aesthetics. Compared to graphs produced using ggplot2, the graphs I make using matplotlib strain my eyes. For the most part, this is caused by its default color scheme which the creator, John Hunter, optimized for display in publications rather than the web. I spent [...]&lt;img src="http://feeds.feedburner.com/~r/huyng/~4/pWljVTv2ZQQ" height="1" width="1"/&gt;</description>
		<wfw:commentRss>http://www.huyng.com/archives/sane-color-scheme-for-matplotlib/691/feed/</wfw:commentRss>
		<slash:comments>5</slash:comments>
		<feedburner:origLink>http://www.huyng.com/archives/sane-color-scheme-for-matplotlib/691/</feedburner:origLink></item>
		<item>
		<title>Under the hood: An HTTP request with multipart/form-data</title>
		<link>http://feedproxy.google.com/~r/huyng/~3/wpAh8iRz1XE/</link>
		<comments>http://www.huyng.com/archives/under-the-hood-an-http-request-with-multipartform-data/681/#comments</comments>
		<pubDate>Sun, 06 Feb 2011 11:22:43 +0000</pubDate>
		<dc:creator>Huy</dc:creator>
				<category><![CDATA[python]]></category>

		<guid isPermaLink="false">http://www.huyng.com/?p=681</guid>
		<description>Check yourself, do you know what an HTTP request looks like coming over the wire? No, not the raw bits or the flowing electrons. Just try to picture the actual HTTP request body as text. Now imagine what it looks like if the HTTP request has an image attached. Here it is. This is what [...]&lt;img src="http://feeds.feedburner.com/~r/huyng/~4/wpAh8iRz1XE" height="1" width="1"/&gt;</description>
		<wfw:commentRss>http://www.huyng.com/archives/under-the-hood-an-http-request-with-multipartform-data/681/feed/</wfw:commentRss>
		<slash:comments>2</slash:comments>
		<feedburner:origLink>http://www.huyng.com/archives/under-the-hood-an-http-request-with-multipartform-data/681/</feedburner:origLink></item>
		<item>
		<title>Django custom form widget for dictionary and tuple key-value pairs</title>
		<link>http://feedproxy.google.com/~r/huyng/~3/UrJGmuj3ouo/</link>
		<comments>http://www.huyng.com/archives/django-custom-form-widget-for-dictionary-and-tuple-key-value-pairs/661/#comments</comments>
		<pubDate>Mon, 20 Dec 2010 15:56:22 +0000</pubDate>
		<dc:creator>Huy</dc:creator>
				<category><![CDATA[django]]></category>
		<category><![CDATA[python]]></category>

		<guid isPermaLink="false">http://www.huyng.com/?p=661</guid>
		<description>Here&amp;#8217;s a code snippet to ease your pains when asking for user input in the form of key-value pairs of data. I&amp;#8217;ve been using this widget in more and more applications as Redis and other lightweight databases displace some of my traditional SQL storage solutions. I had to create this widget because none of the [...]&lt;img src="http://feeds.feedburner.com/~r/huyng/~4/UrJGmuj3ouo" height="1" width="1"/&gt;</description>
		<wfw:commentRss>http://www.huyng.com/archives/django-custom-form-widget-for-dictionary-and-tuple-key-value-pairs/661/feed/</wfw:commentRss>
		<slash:comments>1</slash:comments>
		<feedburner:origLink>http://www.huyng.com/archives/django-custom-form-widget-for-dictionary-and-tuple-key-value-pairs/661/</feedburner:origLink></item>
		<item>
		<title>Gathering Leads using MTurk</title>
		<link>http://feedproxy.google.com/~r/huyng/~3/k3dLyoIcstY/</link>
		<comments>http://www.huyng.com/archives/gathering-leads-using-mturk/583/#comments</comments>
		<pubDate>Sun, 13 Jun 2010 16:00:57 +0000</pubDate>
		<dc:creator>Huy</dc:creator>
				<category><![CDATA[hacks]]></category>

		<guid isPermaLink="false">http://www.huyng.com/?p=583</guid>
		<description>I want to share a technique with you that I have been using to streamline my customer development process. It&amp;#8217;s experimental, but so far it&amp;#8217;s saving me a lot of time and producing good results. At the core, my technique involves using MTurk to collect targeted leads for some business ideas that have been brewing [...]&lt;img src="http://feeds.feedburner.com/~r/huyng/~4/k3dLyoIcstY" height="1" width="1"/&gt;</description>
		<wfw:commentRss>http://www.huyng.com/archives/gathering-leads-using-mturk/583/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		<feedburner:origLink>http://www.huyng.com/archives/gathering-leads-using-mturk/583/</feedburner:origLink></item>
		<item>
		<title>Daily Signal (May 10, 2010)</title>
		<link>http://feedproxy.google.com/~r/huyng/~3/QnRC23R5uxc/</link>
		<comments>http://www.huyng.com/archives/daily-signal-may-10-2010/578/#comments</comments>
		<pubDate>Tue, 11 May 2010 05:00:03 +0000</pubDate>
		<dc:creator>Huy</dc:creator>
				<category><![CDATA[misc]]></category>

		<guid isPermaLink="false">http://www.huyng.com/?p=578</guid>
		<description>Pandas &amp;#8211; R&amp;#8217;s dataframes in Python Pandas is a python package for working with timeseries data. I&amp;#8217;ve been looking a long time for an equivalent to R&amp;#8217;s dataframe functionality within python and this is it. What makes these dataframe structures so special is their ability to quickly slice and dice a table of data. node.js, [...]&lt;img src="http://feeds.feedburner.com/~r/huyng/~4/QnRC23R5uxc" height="1" width="1"/&gt;</description>
		<wfw:commentRss>http://www.huyng.com/archives/daily-signal-may-10-2010/578/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		<feedburner:origLink>http://www.huyng.com/archives/daily-signal-may-10-2010/578/</feedburner:origLink></item>
		<item>
		<title>Exceptions are your Friends</title>
		<link>http://feedproxy.google.com/~r/huyng/~3/sAuX5uUsj-o/</link>
		<comments>http://www.huyng.com/archives/exceptions-are-your-friends/537/#comments</comments>
		<pubDate>Tue, 09 Feb 2010 15:00:39 +0000</pubDate>
		<dc:creator>Huy</dc:creator>
				<category><![CDATA[python]]></category>

		<guid isPermaLink="false">http://www.huyng.com/?p=537</guid>
		<description>Robust code cries often and loudly as soon as something is not right. It does not cower away in corners of obscurity hoping that no one will notice, until one day, shit hits the fan. Any serious python code contains proper use of exceptions, errors, and asserts. In fact, I would argue that their presence [...]&lt;img src="http://feeds.feedburner.com/~r/huyng/~4/sAuX5uUsj-o" height="1" width="1"/&gt;</description>
		<wfw:commentRss>http://www.huyng.com/archives/exceptions-are-your-friends/537/feed/</wfw:commentRss>
		<slash:comments>4</slash:comments>
		<feedburner:origLink>http://www.huyng.com/archives/exceptions-are-your-friends/537/</feedburner:origLink></item>
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