atom.xml

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  <title><![CDATA[yet another blog]]></title>
  <link href="http://Fruiter.github.com/atom.xml" rel="self"/>
  <link href="http://Fruiter.github.com/"/>
  <updated>2013-01-25T16:44:43+08:00</updated>
  <id>http://Fruiter.github.com/</id>
  <author>
    <name><![CDATA[fruiter]]></name>
    
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  <entry>
    <title type="html"><![CDATA[Install PhantomJS with NPM in Windows]]></title>
    <link href="http://Fruiter.github.com/blog/2013/01/25/install-phantomjs-with-npm-in-windows/"/>
    <updated>2013-01-25T14:38:00+08:00</updated>
    <id>http://Fruiter.github.com/blog/2013/01/25/install-phantomjs-with-npm-in-windows</id>
    <content type="html"><![CDATA[<p>When we install phantomjs(1.8.0) with npm in Windows by <code>npm install phantomjs</code>, the process may fail and throw out an error like this:</p>

<pre><code>Error with http request { connection: 'close',
  location: 'http://124.29.1.238/download/20544659/21242686/3/zip/156/114/1359054422428_370/phantomjs-1.8.0-windows.zip'
 }
</code></pre>

<p>The error is due to a defective network handling in phantomjs&#8217; <code>install.js</code> script, since it requests a zip file in <code>phantomjs.googlecode.com</code> but doesn&#8217;t handle the http redirection correctely.</p>

<p>What&#8217;s worse, the npm won&#8217;t allow us to install a package if one of its dependencies fail to install, so if we can&#8217;t install phantomjs, we can&#8217;t install other packages depend on it independently.</p>

<p>So here come the following method, but this is not a general way to handle similiar problems. At least it works in this case.</p>

<h2>Try First</h2>

<p>Let&#8217;s try to install <code>svg2png</code>(which depends on phantomjs) by</p>

<p><code>npm install -g svg2png</code></p>

<p>As expected it will fail, but now npm has downloaded the phantomjs package into its cache dir. The default cache dir is</p>

<p><code>%USERPROFILE%\appdata\Roaming\npm-cache</code></p>

<p>And we can change it by</p>

<p><code>npm config set cache=xxx</code></p>

<p>Now there must be a <code>phantomjs</code> dir, and it may contain these files:</p>

<pre><code>phantomjs\1.8.0-1\package\xxx
phantomjs\1.8.0-1\package\install.js
phantomjs\1.8.0-1\package.tgz
phantomjs\.cache.json
</code></pre>

<p>The <code>package.tgz</code> is the archive that npm will extract it every time when it needs to install phantomjs. And the <code>package\xxx</code> are the contents of the archive. So we need to modify the code, repack a new package.tgz, replace the original one, and install again.</p>

<h2>Download Zip</h2>

<p>There is a <code>downloadUrl</code> variable in the <code>package\install.js</code> file, which points to a archive file, we need to download it manually and save it in some convenient place.</p>

<p>In my case, this url is</p>

<p><code>http://phantomjs.googlecode.com/files/phantomjs-1.8.0-windows.zip</code></p>

<p>And I save it in</p>

<p><code>d:\node\phantomjs-1.8.0-windows.zip</code></p>

<h2>Modify Package</h2>

<p>Modify <code>phantomjs\1.8.0-1\package\install.js</code> in the cache dir. Skip the network process and directly extract the archive file. The patch:</p>

<div><script src='https://gist.github.com/4632657.js?file=installjs.patch'></script>
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Hello future GitHubber! I bet you're here to remove those nasty inline styles,
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Please, don't. https://github.com/styleguide/templates/2.0

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&quot; 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      &lt;div id=&quot;parallax_illustration&quot;&gt;

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kf4sl2gv/7tMfyHNlstD4AIgHc6rdHUgQ5X3zX9PnHICTE3ERLvA12MBjnuBFB6UkuJ2fco0A+eETfI4rkCHCbFOCj+ryijey+D4w0tcFzfAnQjjLOi9rA1s1GXZSk9oxN/Jbzq/6W8kvaI2LollymH2D3ftyiMkeYLoZviwSpRElyP7l47EXsQOGi+EVEaG8Jbjz692OR77GY/chRWsv+SxsipFb7hikkwar+WjAqXEqVyrfY4HMZfrUNGoYh1yMAX8hLP8S45Hltv1K1H0jJXCD5R9nd3heBDYaKOc8yzBFZ1lFxhkPWX6RQwg45k2XyYlO1YkfXKWkhgZHli2JVI4kfT9cvzzWyzHv6CAC/rtIimBgdPK4LOEh8hNrocIDUW/dqg0j5RVAkFJQsuCUl1PFpANuxgDsz7juEt4cMxiDwIpFZU1t3bsORYNnswnJUgG4ROtB4v2klDxF7+PIFXWDzqiRSeEnQv+kQ0AYiy2/VI9b44HNwrxIt39jbnd8ny7sK/PbeqUclmTWLVuhRTwwJ2jYRV6SSQkNog1/FpskK9wEWOfxmFRnohEosIlwyckZZ0rUEHM5ZUoxvpejseXsLAqNtGkHTElolNYu4j1Un3Uitin+bjH8PjNrtUE/jAXsd97XD/kMctMWEeOCSeUjQIYxAPkP6TLAv9YlEzY5NCEEL3AK0b3XoaHQFgLd9M17/ST7vtSuoIKZJIriX2hlsoA6bMWROJk9WVijLTES5wlllB1vlgpoYkIBtFK+NtayGQiYaKGv7s9s3sIDzw2RJm5AL9lyO5h/cgnIcoWMZGyGRLOugXnFlq01WRFuR+k7K0Zrt3D8XpZx5j3UGrWtm09yWvJiirJJoOZydvhog0PTTPZrIv2JpOxSBfmIH3TNPbvumnPHR7tBHepG3SDx7mTpm0ECJaKc4eGIhsKR+e8qeErtwlyRbGKJDvi3HtkPSfpkKFsgGgtHjX8NdPqdG7wmZCKpsqkoJmAR73qYVNlOk4/aGDGgXB6BUOA1U0Ssqy1qTJRwXthvU+sk7jRmYUDVAMAaWZWfMsW8jkNwwPb2KQBmVbzOUOjBlhzz5NSAMnN+5x76R+QyOvaMmvad6NqalCpqmFbz+BHozJUPyaTyUgU2NyozI9F/5TrJrHukUEeV58lu4wmyrRS/poE47tDrMKAzreppv9bGzzMHaP0wFgT8KgnCb+yPhZMUOAbDyDaPZkwPJCfMpozIf5gIwuMgz90PKpvv74dVQqUHhRXvR2+gXvJn37izTKKh7Z+ystnrHciU1tjs8zAUX6lhq9kRTGMNUkg61/N/2fWSMDFBD7HH1rrf9vQ68g6Y3vx03TufmtC3zBTXb4/Mz3N3vvexxe2ysXYNKl8X62nO/OO3Y6Fc/NNc1Z5PqFl3c6nR1jsfgs9gGMrq8a+244mbe1FhP8tGDDjtGO4nrV2sCxsVt7a2pjtorIzNXTy07yGORuECP2f214sts3YEgM9tLXAGKrW/+4ZOfd0bdzhfDx051tCPABN56+SAP0CvoNttH4RXL9OnVrFjVUMYSdEPf/ZXJ5+bJyDfQ1Q2CFsgwm/OYeZCfCYthao2mAXuDi9bBMir6GD0LP581q9mV36zlz901nAw1w49YC6V9DyZ6965s4UjSOTqHPtaLUDvdAafQYYIngTHAiA/5hW1QiGxPkRN55gVfVkWI18ZUfcmpopxlg+jEZVFVyC9j01Z6PhqQtg1MTAOamGI1BHe206fouYA2mP3JWBdWp6mzS+pdGOibm+MPgka0B2Qdx/Zi9KBThKrxihtUH0dFVHG/ZhhwtIbK0ja0BNah6gNLKcwqfR+rSqNA0gotG1i65ADXUEGPBxyhGKF14j2t6fBNRP29Si1+ZTgGOL20pEEHfn55cwqj78sp8wvbQuOHpv9ON88oaOi4vHlLown9OTnyg/MGtqJH9QHm+A/joZqh8IHXhQCQ9D5ecxxEkXHAQV/SrDBd2NcEgvgOeeV6dAwONRW58GWm2b+3FTH60v/DitUOswcmMb77ezyU+xW6W9xVlcVFBDHTUwqqUfpMYu4lTEwaumtvbSXNbWf4xd/WAlmgyPHyTsN3TyHcRekmHRTzu/NGkKNVIEXQ3+I0yCx3M77TTNaWpumwLNqfOG9eXbhHbjpeL6EfxJdKYOEDcQkSS6NbF9J3daMAydwMUFwSH9gzXcgIIhYynsnBfiMq/eSr8+vbQRA0yCHrxJXfvZZnxmJ472Mno4HVYhAY8QbMCKQON4zA0MWih4jxuRg8mmaechHMlGlhWyUMBwLPdq4OAE7B0dzCPoh44Bq6kdjdjrOJmqhxODV3sSqQXL8yvm5D8a2GHRAZ8w30WCyUSbOrY8mxyn8cylCB/E2cJfByTncqnmdBMjxETenyY/17R2fXPaxhjUL32sAHZt/KpNPtF5IOtHnAVG/ai9P609Wc+9VRvPQ+1stqnt3tTY1KxUr0Qp5Xsm2kHOo1AlhIy1l9YH3Voh8aP6hsVE214NhyYIaJt5HATTtHYuYl6Z3ybBEdrfWzRzm3snxq9OTaWpofAOpDQUpqPhq8DYpen4pDq2pPzU63k4umrrD++qkSHxS1L2aJfINzJAmHbwV86KqI7PIfK7PHV3bFTZnB+ffrTzhb1htHd2bJXYRfLg1Sx6x3Z30TRV4Ze2rl/7nk9t/Dl7C06nraGDyxj6Wifz6speVH6QIF5rG0cS4vqZ48Eq3sSvZ0JIVBpZemH+otpB4g9dyAmaOB85cz/NWrvGqM7d6sqGX/D70BqQ20m7fOXZGbW29sxOoa3behwrHzW7+LupZi7Irwx8Vz5cnx9bfsY2CB8GRl5BEAN8zBy01czNZ8DY1G1qOjx6HLFv5XhwzeCQTJwkM+XxgIVkM5q5u3bLyDJn7QbE94tM6GZkWYRtE7eYM0H7iQrK7Ncjw5ldiFixf5nOTa359LUnPTxzPXurPgJ/PPM81C3wAE2trCdnjo9JbhNIrmzAOR6SQij1m0sDUtKKHz4zPAp8JihIP8z1yuT5z1qpzqVlzj/V1qwG8o8q9q0Kux2pliaN3Z8iHuUmcsH4eYHFKl0dELELs6I4LmoTTwNZDrrw6NIrnaTG/WZCaMQtZVmTFp9047Xcc5bZUfAfn8d4vwCQBTwIBh1DQ6xDRUZF604VMi0V+15Oji7mwt2eE4FoLzr7G0mV9pSQ0Wr0PyYSx6vLqPF46nQn44L4CC7XhvIJCv6Dm9XvJmEqt5cv1rQFabDyruY/+UB32IvQ1W8/JivNL7xDZmaa6iInPHSxO1PQJZZTAteiTek4HpIu5ffELgRyUvyxASbcudPSTEQNSG5Fk37jaIRhYJ4M81IcwwVXSrQX7BwCOfa1s0t3t2rdWhcJy1oHfSX0xD41lb1oolJXUncZ7qQs0I98xZ+bXOI5DqF6NQ2bYsibkDbUvUZamvdHe1aRN2aLtFeF1LlYg4nqruX5dn3vD3t9RPSNeP8I4Seb5iU8Ev/UikvySOtPvOXMDXmd9WeHmNjfSEzKzBOuC3gIrdhQLIyB8F54cSCxAiG1cASwUpOhSfT8XcGENWnr6yMFy7gI5ArzLWIo9gJf3LlGq3xygbJphk4Txhf2yMNnXPhNRXMd9grdpFPDjtnlqatk89Da5uK9pzm+CPkO7cx3aTq/8l0qtxFm/h/aLcW6GWq7hQbbYFfTn5XbqzR9xi1HDF2GEAWxhAdHmha7N2jkd3uTLRw9wZav9ruIcHt+5PSjdrunzUWQpvI3AMgP9qbbGAybvvrUnWFaRM59lzYD5OqVl8PJW8NmLfRj5D2aN35nen7kck8sXo6VKgw8c0lMNHyZz7eisQTXfz6HMZ+p2VVb1/OZNp9NMz+HXI3W7RW39RRIQo6CFbX2m+vKba7bHdV0QFP7VjC4r60Qtg/YvTdd+j3yJiRxKLv1Dpv5div+/FhBHokfG6h0+hHUw260w1b9MVOOJeLlkj/FbgEb2lHrjogn/nNsPo+UPbJrJqNhPGwB/zEcjdLhCzSHU4BRNXx/aUwGro24NnEkHU9CusfUn4bC0fekgiSOeH6jlK/rj7i1umrbi2oUDnl0yC0Ag6ZJ09KsKNhOIf5QWYMw6Zy17Zn5BpZuPtWZ+4hni6c+LnW5Gy6VKKpsONyHTBm4VTc4YTNMSf4YX4dUkdNwTKc8Hg6XZoLxCSlt4VCsaUOuHS2L5oXcXhiWBENtjwKNQry2VnukjmqnJo6f1ynjwgujg3AKg4byJfQv42nAo3VH/xE1wAe6bFESB0v0CEec8QiVJudwIDSPdjOkcv3A07j7Rmb+V/a43ma6NWNtzUU7IdpLZ/5j5fXC4ZESCDEe7mY1vXTW747vm4bVaj/G/ICAh8VO21QRraOexLPehuDBhFiiZPqxcJI+A8/1wc63Z8pZj3LCNNY/Tv11TUUPF8GY4BoO0ez8RI7z/VBbe3Guchp7cHjYs2F6aDyp3blwSFaK/oNFInhBtQweFADJ5YxhajPsnBthXrdNGxIcW5dxMXT1g/EbXGqMh5fYasLYTjfzs9amM8SsRYeaTQUAJbyKSRzeBWO/4XDRLoNOpfsxKaVvdCf6DyUvhVw5Ak9qBPnFkJ5ZJxLkP5u8waLbXKcJdoZeWYKnND75avw26HhUef9pU83OJscKjzFPMcP+1DaufU5I0BudYklSdPgt+BV/vxyP8dax1ZnVYrCVxn7aMrbhUaIb+DORYnKGYbKZwYF9TOvQPnljbMb+TWoK13CoTZnwub4jrB/OBN2zD5DjqSH288koXbogRfoyHtJkHa+smrfv1IkNJJ256FcmMPtwYgKBqvo5+Hvz/Qw/G2RH3sQkACRkS1w17eVJNRqFpA2Iw06qaupn459MIH7x3nQygiQOz4dpczGsxvMwj0Dc8a6q3s39JDS3fYznDXroQpSjsErriD/40IRyBHPt3NKO5uK024aKwMdbn4EAl/OUVDlpQ677FTQ7a5qwXGkg1jz12Q2wAPBzRuPSAJJoUx+dN86v+sGxf8Ywz01dvA/52y4+VUlBcgCCh01Fnm8xFNT8/AzTgMuHyOBMhS6nXhhgflS7rBCYMd+k3iAPz96/spwez13OCPxdD0030wBI64W34X0Q3XZzNPcwe3uxTPiYHiq8+uABgdujyFwORGGTMsODzC5K3AMGwzZLUsiwR5GBOjlzkgEerZfsYnIUW7uMZeMA4s3jM48I2JHt2SePhOy0d2dOoSaxC/UaUkIuU3K4Hn8AdbgYe/6OpmaN83Fi10+VSsMb4wg03pnWCPaC97EoNnknmvWo0zlNPiAqOdniXG5vhew0TC9jxK1T4h0edvowSie2ctPg/sD+VfSnpLbYFH1Q/5stCsJ3kmypRd60j04ErEjtJnvIVRoCOfKSReuYX3RWX55wuNzCaOOvmgQj4Qfu5/VF45Z54XfSoSf03qccpl7QQDGl5cOH72dwSfHYupvr1NTQrxEP4sgSrbdmbh2eNXUzztsGmV7BnD6eQ5AswZ8MWdIwYsrcgor2IiG6AUVx+0EfTwuWAE8r+kn6IjTC/HvYR34DzZlLFkSsqyiy/yCCrAt5+D50ws6or8QA+gzDiyMkCPfZI/sgWO2n14wVfiGwnBRY8NlL4+Eu1zkpqFwsNstlCFzNIG3yQo4rAyH7GB0sG4l06Yr5LCbxQte/AA9FtUILPgUzW/rkl8j3cC0OGw6SLmYjIBw4ynR17DpQ0ZpXtRQ78MBKm81LgusQGCn8JDshWluvkFxRDYdHUqWcD4lrSyzHQ/SFnHjGfa4JrvLILk/kSRPddLa0ni+cQCg/5D9zRaMWlY1MKR5bWsEy+pGM/Wtol15CFcpRZQ8niIdr08q4QAUxp9yzg/EIKlbrq99C/CHIrfOmQodCLfXmoo7Lsw79evuhSdVcrQa9wmKhfrlHbk0JS5YV9MuWQvxB+8jYJ3xlP6RLuGZBKTe/cB02XFWYvNhrZzKwNf0b1gInEYSVD4IFPKRhZu3pcGV3kdvX6SlJHatJffOHSeGtGRUy2UVBc3jYMNxEUjAckJ0RSe39hfMt7aCIksBicHNYUDSbMlxitS4SHb9Z2MU1Ylp0Y9WgaqIDc0U8ZGdBuVtqTpz4R/QDxaI8yKyo8SMWPh2eHpHS/FJwP1q5fa/mg3sq0q4mJtN56x8TdEkPNkMhOgZ4YxA0/Xlqd3+upnY3FDZ2XELEa18N5he/Pwb70LV7hBSi/Hoy+di2l+G5ItfSnYv7+aRyCRBuyh5/sJtMF3avCtYAH0/gTAMOJKRRJvcW6kdoFIC3Hbs9Te1ecWQ4D+mEE/daoba5OoojFQzb7vTZI3t4B4U+mvs9tNrupcJeYg14+Ey886Z1Jyt21eM3TS9sLskv85An0TQRj9ZvEyrYT6r9vizgOfPf2bQfhKM2s+D5lxwWpVu/AexeSXHsyTV2j+91G1mZxkg8nKxO6/ierqn2G8NOLtiL9Qe9Z3Z79Nw+IujkeeNzOSxJu4ibtqmcv3F6/nZ26Z/f07/UfmfbKNAv7ilF99wanubSKDMZC3gwv4RaQMrCcDSJ5whwUHhxUs3hON++bmJUVR9ckoPXDz/fwonAEDIiXPrCvK1tosIHe+kTAeym9IddFYEYAAAHAklEQVRXtm0bnkSFXfn5uDq59HkPc5viMBr6IwXv7UEr3lpgbdrEqIosAuhno2qO39GRiRkmPikeo2AwH+gXqAkPGxTqc4gewsu0IFSMAW14uN2fRAfHFw5aXaKCdgeORmkav9qP8an2FILh6Sa89cC/T0IR2FNmYxvxgAcY7Ws3iFvOnKusH11nlb6RS0IIeLjX4QRs3I/NBfIfDcXDMd74BA50attOjc6f+TechJM47U97zad/9B+NOwrYwG0HdXLrpdYdbeqa1FNRo7Kzyi7/kQMYghebo9AkPOKz624EL52pj0P1+MaP1j9d7gEg8EC12p70p6P8FmtgRM7/AB2Fp9sdoZjgGTfx+RGvvRnYCpCkwdedeLC2qUxb96qeBmlz+A1kq+3P00QpZDw06SS+QVxC4p37tOkS6cC2QfZSJ0G1e0uIwcEf9QezjPZi8dbOAWmVFkIlncc+tRyf6gQJfpwFEmCaen4Wz4sdHzpMJVDmKEMhpbl4AMLhfoP9h297FZ/EtsPbIItEwIahiK/1sn/g4XXLq31DQKqnlcOPzCQKK4XCU0aXfqRWqZ8Lw/L4ODFFEl5AJpehgDqx/g3U2528B/FiIosPT0DfxzHGSPih1BqvATFlKrxPwvKH/akz4JAqUtfiux4jHGTQRTw4lqiXJr5IgVk3FDhcrrheBnEoAFEq+DnCBLoU3hXiK2iNNQg+L/2pMTrn1tRe6gSoToSTYGF8MzlL//5LACDfgJ7XJvqthpV/xY+NBltfx2UonJi5f1S9jpbt39qhISh5P6xOrky8opyinQyr9yFRwflDiNK8S00UUv4lOAYFr+M6NSy0bH7x/vS9cUPTyr4lo7FHVuHo2wgzm52fZiIRRGR7KefSn7m40DqK2THEpzVkz8YJt4F1BxoRd+gC6bXjJqYm2MTVeFmPlY7VzPqnvjoNb804fwsUGsjwPvZv2dAmXo8B/CRw+iaSsfrj41F4S4Z7y9v5OKgMOvqLPgQZUUk/kGWR82D3jqTWBe0VrBtgrjkPvbukh5DMpv1b9lwMN3XnDbVXgGnI9YDLoVuSnKufPjqezx1YlXvloUFmmE4rjq/CkiT6Bf8yPyvs2yu/EJjDC3PgLYBNetOTe00HdiH0CEWKx2iMErF0DY7PrmIGSmX3PQno7yAjqKnjayaqICioxAUsLS5CigRk77fthzH0O3LJ3ecuKWSm3Ytn4V0fkBllBnsGn+bLDMbo5+llE/MgdMTDvr9Yh5WzXTi7lPfwdiHtWCXaQURcKn9Mr7L1v1TJ/RnpQNrmiNU0i0/zTjpIan4n0FmwP5bvJJPodhmxuXqWuF7s+jn7LU8R28TR2YL4Q7YbgUhyMclLaSJEBCa4p5LkJERgcKKr9y2ctohKLzJO2S+NMMdj3UGTGVhz0Fi1o2oEKYb2LUsMdGJqOaE4U2B+SBH0o9sBF8zkOp92gwet7Hx6EoQq981/T5xyAu57If7Iuenh6MplDUfnf4XPyk017Vhsvd7LAxbNLwz6HNuC3mQDrIXbkfF+x0dDmEDn0+OcHu458afTnYwLIpAWzys/u7zht08hLyZFvI9vIeqHZCmMjaAtOquTlTiZkINX3BDZQxHjDLi8WvYzuyE5Pq7/OR5fhIsIv3JwNuEiMoXEZVE8htGXRggNtcoglETHVZiCZ0qT6iYSCbplpBRYToYlaHcxPs1PagTquMoXNytn6pXpGu4k/F6IP6QecWMyaKK7iT8Sm5DGJBcJo5A6kRUiViBaqvhlgVL2k4hHHLovfDIoSsVvSJjI7cv6kQ+gQEro9HOsZaQrdKMIHUdGPm9AHP7a/3XO3lZU8KefS10F0jq/qzGe8VPHaoucBL5O6lrwH0x1dWiUg5FqdoKzmUBJ818+TeBc8h9Uf3stEXOjIPUQSOVxFP2VBKusDASOgo1Qywq3OuMx3+AL2/7AXza9/VF8P8zv1FwWvB+XMZWzTW0n1MSV+YDkN/2NBDqFn2sAud9tcWyoaIgqKXrpfUq/s0kWFcFeeCcaS5sjJJqpbCU6DmqXF+ICsi4EchsMADkeh78r75nT5Xi8DDUk3Spa6+eNoQTcc2ZURCfqCVEo9+clx2Nfkd+TIkrKKsuATSpJKqy3xdCAC0a1tTzAyzkJikGuL/scj13cyW/SIiKs0jJtl+Pxhx8okUL/zH5+Kz73cJvjsXUPk8GKII6QxAbZ4hDYVVFiyjxqRgXN1+X4go9dh1Fr4WfPsrt9L4Nja+uxKCRhtUjhV75r+FiAY2tr71em5EmxELAZGW7HjCBc7YlwbG398eBT7ujLGufHXkKQd51Y0fSGQtCE+5k+oJqUysFOAQ5wIvsHvhFCpItJTDLjQBAxOI/SaHJgCtqDfl9vpjt4JrmOra3/B72L99CCrFH3AAAAAElFTkSuQmCC&quot; /&gt;

        &lt;img alt=&quot;Octobi Wan Catnobi&quot; class=&quot;js-plaxify&quot; data-xrange=&quot;10&quot; data-yrange=&quot;10&quot; height=&quot;230&quot; id=&quot;parallax_octocat&quot; width=&quot;188&quot;
        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&quot; /&gt;

        &lt;img alt=&quot;land speeder&quot; class=&quot;js-plaxify&quot; data-xrange=&quot;10&quot; data-yrange=&quot;10&quot; height=&quot;156&quot; id=&quot;parallax_speeder&quot; width=&quot;440&quot;
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&quot; /&gt;

        &lt;img alt=&quot;Octobi Wan Catnobi's shadow&quot; class=&quot;js-plaxify&quot; data-xrange=&quot;10&quot; data-yrange=&quot;10&quot; height=&quot;49&quot; id=&quot;parallax_octocatshadow&quot; width=&quot;166&quot;
        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&quot; /&gt;

        &lt;img alt=&quot;land speeder's shadow&quot; class=&quot;js-plaxify&quot; data-xrange=&quot;10&quot; data-yrange=&quot;10&quot; height=&quot;75&quot; id=&quot;parallax_speedershadow&quot; width=&quot;430&quot;
        src=&quot;data:image/png;base64,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&quot; /&gt;

        &lt;img alt=&quot;building&quot; class=&quot;js-plaxify&quot; data-invert=&quot;true&quot; data-xrange=&quot;50&quot; data-yrange=&quot;20&quot; height=&quot;123&quot; id=&quot;parallax_building_1&quot; width=&quot;304&quot;
        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&quot; /&gt;

        &lt;img alt=&quot;building&quot; class=&quot;js-plaxify&quot; data-invert=&quot;true&quot; data-xrange=&quot;75&quot; data-yrange=&quot;30&quot; height=&quot;50&quot; id=&quot;parallax_building_2&quot; width=&quot;116&quot;
        src=&quot;data:image/png;base64,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&quot; /&gt;
      &lt;/div&gt;

    &lt;/div&gt;

    &lt;div class=&quot;container&quot;&gt;
      &lt;ul id=&quot;next-steps&quot;&gt;
        &lt;li&gt;&lt;a href=&quot;/explore&quot;&gt;Explore&lt;/a&gt; projects and code.&lt;/li&gt;
        &lt;li&gt;&lt;a href=&quot;/login&quot;&gt;Sign in&lt;/a&gt; if you're trying to access a private repository.&lt;/li&gt;
        &lt;li&gt;&lt;a href=&quot;/search&quot;&gt;Search&lt;/a&gt; for a project on GitHub.&lt;/li&gt;
      &lt;/ul&gt;

      &lt;div class=&quot;divider&quot;&gt;&lt;/div&gt;

      &lt;ul id=&quot;error-suggestions&quot;&gt;
          &lt;li&gt;&lt;a href=&quot;https://github.com/contact&quot;&gt;Contact Support&lt;/a&gt;&lt;/li&gt;
          &lt;li&gt;&lt;a href=&quot;http://status.github.com&quot;&gt;Status Site&lt;/a&gt;&lt;/li&gt;
          &lt;li&gt;&lt;a href=&quot;http://twitter.com/github&quot;&gt;@github&lt;/a&gt;&lt;/li&gt;
      &lt;/ul&gt;

      &lt;p&gt;&lt;img width=&quot;109&quot; height=&quot;48&quot; title=&quot;&quot; alt=&quot;&quot; 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    &lt;script type=&quot;text/javascript&quot;&gt;
      /* Plax version 1.3.1 */

      /*
        Copyright (c) 2011 Cameron McEfee

        Permission is hereby granted, free of charge, to any person obtaining
        a copy of this software and associated documentation files (the
        &quot;Software&quot;), to deal in the Software without restriction, including
        without limitation the rights to use, copy, modify, merge, publish,
        distribute, sublicense, and/or sell copies of the Software, and to
        permit persons to whom the Software is furnished to do so, subject to
        the following conditions:

        The above copyright notice and this permission notice shall be
        included in all copies or substantial portions of the Software.

        THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND,
        EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
        MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
        NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
        LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
        OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
        WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
      */

      (function ($) {

        var maxfps             = 25,
            delay              = 1 / maxfps * 1000,
            lastRender         = new Date().getTime(),
            layers             = [],
            plaxActivityTarget = $(window),
            motionEnabled      = false,
            motionMax          = 1,
            motionAllowance    = .05,
            movementCycles     = 0,
            motionLowPassFilter= 0.05,
            motionLastX        = 1,
            motionLastY        = 1,
            motionData         = {
              &quot;xArray&quot;  : [0,0,0,0,0],
              &quot;yArray&quot;  : [0,0,0,0,0],
              &quot;xMotion&quot; : 0,
              &quot;yMotion&quot; : 0
            }

        // Public Methods
        $.fn.plaxify = function (params){

          return this.each(function () {
            var layerExistsAt = -1
            var layer         = {
              &quot;xRange&quot;: $(this).data('xrange') || 0,
              &quot;yRange&quot;: $(this).data('yrange') || 0,
              &quot;invert&quot;: $(this).data('invert') || false,
              &quot;background&quot;: $(this).data('background') || false
            }

            for (var i=0;i&lt;layers.length;i++){
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                layerExistsAt = i
              }
            }

            for (var param in params) {
              if (layer[param] == 0) {
                layer[param] = params[param]
              }
            }

            layer.inversionFactor = (layer.invert ? -1 : 1) // inversion factor for calculations

            // Add an object to the list of things to parallax
            layer.obj    = $(this)
            if(layer.background) {
              // animate using the element's background
              pos = (layer.obj.css('background-position') || &quot;0px 0px&quot;).split(/ /)
              if(pos.length != 2) {
                return
              }
              x = pos[0].match(/^((-?\d+)\s*px|0+\s*%|left)$/)
              y = pos[1].match(/^((-?\d+)\s*px|0+\s*%|top)$/)
              if(!x || !y) {
                // no can-doesville, babydoll, we need pixels or top/left as initial values (it mightbe possible to construct a temporary image from the background-image property and get the dimensions and run some numbers, but that'll almost definitely be slow)
                return
              }
              layer.startX = x[2] || 0
              layer.startY = y[2] || 0
            } else {

              // Figure out where the element is positioned, then reposition it from the top/left
              var position = layer.obj.position()
              layer.obj.css({
                'top'   : position.top,
                'left'  : position.left,
                'right' :'',
                'bottom':''
              })
              layer.startX = this.offsetLeft
              layer.startY = this.offsetTop
            }

            layer.startX -= layer.inversionFactor * Math.floor(layer.xRange/2)
            layer.startY -= layer.inversionFactor * Math.floor(layer.yRange/2)
            if(layerExistsAt &gt;= 0){
              layers.splice(layerExistsAt,1,layer)
            } else {
              layers.push(layer)
            }

          })
        }


        // Get minimum value of an array
        //
        // arr - array to be tested
        //
        // returns the smallest value in the array

        function getMin(arr){
          return Math.min.apply({}, arr)
        }


        // Get maximum value of an array
        //
        // arr - array to be tested
        //
        // returns the largest value in the array

        function getMax(arr){
          return Math.max.apply({}, arr)
        }


        // Determine if the device has an accelerometer
        //
        // returns true if the browser has window.DeviceMotionEvent (mobile)

        function moveable(){
          return window.DeviceMotionEvent != undefined
        }


        // Determine if the device is actually moving. If it is, enable motion based parallaxing.
        // Otherwise, use the mouse to parallax
        //
        // Parameters
        //
        //  e - devicemotion event
        //
        // returns nothing

        function detectMotion(e){
          if (new Date().getTime() &lt; lastRender + delay) return

          if(moveable()){
            var accel= e.accelerationIncludingGravity,
                x = accel.x,
                y = accel.y

            x = (x * motionLowPassFilter) + (motionLastX * (1.0 - motionLowPassFilter));
            y = (y * motionLowPassFilter) + (motionLastY * (1.0 - motionLowPassFilter));

            motionLastX = x;
            motionLastY = y;

            if(motionData.xArray.length &gt;= 5){
              motionData.xArray.shift()
            }
            if(motionData.yArray.length &gt;= 5){
              motionData.yArray.shift()
            }
            motionData.xArray.push(x)
            motionData.yArray.push(y)

            motionData.xMotion = Math.round((getMax(motionData.xArray) - getMin(motionData.xArray))*1000)/1000
            motionData.yMotion = Math.round((getMax(motionData.yArray) - getMin(motionData.yArray))*1000)/1000

            if((motionData.xMotion &gt; 1.5 || motionData.yMotion &gt; 1.5)) {
              if(motionMax!=10){
                motionMax = 10
              }
            }

            // test for sustained motion
            if(motionData.xMotion &gt; motionAllowance || motionData.yMotion &gt; motionAllowance){
              movementCycles++;
            } else {
              movementCycles = 0;
            }

            if(movementCycles &gt;= 5){
              motionEnabled = true
              $(document).unbind('mousemove.plax')
              //window.ondevicemotion = function(e){plaxifier(e)}

              $(window).bind('devicemotion', plaxifier(e))
            } else {
              motionEnabled = false
              $(window).unbind('devicemotion')
              $(document).bind('mousemove.plax', function (e) {
                plaxifier(e)
              })
            }
          }
        }


        // Move the elements in the `layers` array within their ranges,
        // based on mouse or motion input
        //
        // Parameters
        //
        //  e - mousemove or devicemotion event
        //
        // returns nothing

        function plaxifier(e) {
          if (new Date().getTime() &lt; lastRender + delay) return
            lastRender = new Date().getTime()
          var leftOffset = (plaxActivityTarget.offset() != null) ? plaxActivityTarget.offset().left : 0,
              topOffset  = (plaxActivityTarget.offset()  != null) ? plaxActivityTarget.offset().top : 0,
              x          = e.pageX-leftOffset,
              y          = e.pageY-topOffset
          if (
            x &lt; 0 || x &gt; plaxActivityTarget.width() ||
            y &lt; 0 || y &gt; plaxActivityTarget.height()
          ) return


          if(motionEnabled == true){
                // portrait(%2==0) or landscape
            var i = window.orientation ? (window.orientation + 180) % 360 / 90 : 2,
                accel= e.accelerationIncludingGravity,
                tmp_x = i%2==0 ? -accel.x : accel.y,
                tmp_y = i%2==0 ? accel.y : accel.x
            // facing up(&gt;=2) or down
            x = i&gt;=2 ? tmp_x : -tmp_x
            y = i&gt;=2 ? tmp_y : -tmp_y

            // change value from a range of -x to x =&gt; 0 to 1
            x = (x+motionMax)/2
            y = (y+motionMax)/2

            // keep values within range
            if(x &lt; 0 ){
              x = 0
            } else if( x &gt; motionMax ) {
              x = motionMax
            }

            if(y &lt; 0 ){
              y = 0
            } else if( y &gt; motionMax ) {
              y = motionMax
            }
          }

          var hRatio = x/((motionEnabled == true) ? motionMax : plaxActivityTarget.width()),
              vRatio = y/((motionEnabled == true) ? motionMax : plaxActivityTarget.height()),
              layer, i

          for (i = layers.length; i--;) {
            layer = layers[i]
            newX = layer.startX + layer.inversionFactor*(layer.xRange*hRatio)
            newY = layer.startY + layer.inversionFactor*(layer.yRange*vRatio)
            if(layer.background) {
              layer.obj.css('background-position', newX+'px '+newY+'px')
            } else {
              layer.obj
                .css('left', newX)
                .css('top', newY)
            }
          }
        }

        $.plax = {

          // Begin parallaxing
          //
          // Parameters
          //
          //  opts - options for plax
          //    activityTarget - optional; plax will only work within the bounds of this element, if supplied.
          //
          //  Examples
          //
          //    $.plax.enable({ &quot;activityTarget&quot;: $('#myPlaxDiv')})
          //    # plax only happens when the mouse is over #myPlaxDiv
          //
          // returns nothing
          enable: function(opts){
            $(document).bind('mousemove.plax', function (e) {
              if(opts){
                plaxActivityTarget = opts.activityTarget || $(window)
              }
              plaxifier(e)
            })

            if(moveable()){
              window.ondevicemotion = function(e){detectMotion(e)}
            }

          },

          // Stop parallaxing
          //
          //  Examples
          //
          //    $.plax.disable()
          //    # plax no longer runs
          //
          // returns nothing
          disable: function(){
            $(document).unbind('mousemove.plax')
            window.ondevicemotion = undefined
          }
        }

        if (typeof ender !== 'undefined') {
          $.ender($.fn, true)
        }

      })(function () {
        return typeof jQuery !== 'undefined' ? jQuery : ender
      }())
    &lt;/script&gt;

    &lt;script type=&quot;text/javascript&quot;&gt;
      // Plaxify all `js-plaxify` element layers
      var layers = $('.js-plaxify')

      $.each(layers, function(index, layer){
        $(layer).plaxify({
          xRange: $(layer).data('xrange') || 0,
          yRange: $(layer).data('yrange') || 0,
          invert: $(layer).data('invert') || false
        })
      })

      $.plax.enable()

    &lt;/script&gt;
  &lt;/body&gt;
&lt;/html&gt;
</code></pre></noscript></div>


<p>Be careful with the slash&#8217;s direction in the code</p>

<pre><code>var zipPath = path.normalize('d:/node/phantomjs-1.8.0-windows.zip')
</code></pre>

<p>Remove original <code>package.tgz</code>, then create a new one by <code>tar cxzf package.tgz package</code>.</p>

<h2>Install Again</h2>

<p>Run again</p>

<p><code>npm install -g svg2png</code></p>

<p>If everything is fine, this time it will succeed.</p>
]]></content>
  </entry>
  
  <entry>
    <title type="html"><![CDATA[Python Encoding Misc]]></title>
    <link href="http://Fruiter.github.com/blog/2012/12/04/python-encoding-misc/"/>
    <updated>2012-12-04T14:55:00+08:00</updated>
    <id>http://Fruiter.github.com/blog/2012/12/04/python-encoding-misc</id>
    <content type="html"><![CDATA[<h2>Intro</h2>

<p>There are several common problems about the encoding in Python. Here are my notes for them. All experiments are carried out in <code>Windows</code>.</p>

<h2>Interpreter</h2>

<p>Python&#8217;s interpreter cannot automatically detect source files&#8217; encoding, so any Non-ASCII characters will break the execution even they are just in comment.</p>

<figure class='code'><figcaption><span>cp936.py  </span></figcaption>
 <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
</pre></td><td class='code'><pre><code class='python'><span class='line'><span class="c"># This will fail</span>
</span><span class='line'><span class="c"># 你好</span>
</span></code></pre></td></tr></table></div></figure>


<p>We have to explicitly declare the encoding. The following is an example for <code>cp936</code>.</p>

<figure class='code'><figcaption><span>cp936.py  </span></figcaption>
 <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
<span class='line-number'>3</span>
</pre></td><td class='code'><pre><code class='python'><span class='line'><span class="c"># coding=cp936</span>
</span><span class='line'><span class="c"># This is ok</span>
</span><span class='line'><span class="c"># 你好</span>
</span></code></pre></td></tr></table></div></figure>


<p>One exception is that the interpreter can handle the <code>utf-8</code> file with the <code>BOM</code> header correctly, even without the specific declaration.
The interpreter cannot handle the <code>unicode</code> files such as those created by <code>Notepad</code> in Windows, even with the declaration.
If the file&#8217;s encoding is not consistent with the declaration, there may be other encoding/decoding problems.</p>

<h2>Print</h2>

<p>We usually use Python&#8217;s <code>Print</code> function to output strings to <code>sys.stdout</code>, but this function cannot handle the string&#8217;s encoding properly either. If the paramater is an <code>unicode PyString</code>, <code>Print</code> can encode it into the system&#8217;s local encoding and output correctly. Here are two examples.</p>

<figure class='code'><figcaption><span>cp936.py  </span></figcaption>
 <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
<span class='line-number'>3</span>
<span class='line-number'>4</span>
</pre></td><td class='code'><pre><code class='python'><span class='line'><span class="c"># coding=cp936</span>
</span><span class='line'><span class="c"># unicode string, this is ok</span>
</span><span class='line'><span class="n">s</span><span class="o">=</span><span class="s">u&quot;你好&quot;</span>
</span><span class='line'><span class="k">print</span> <span class="n">s</span>
</span></code></pre></td></tr></table></div></figure>




<figure class='code'><figcaption><span>utf8.py  </span></figcaption>
 <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
<span class='line-number'>3</span>
<span class='line-number'>4</span>
</pre></td><td class='code'><pre><code class='python'><span class='line'><span class="c"># coding=utf-8</span>
</span><span class='line'><span class="c"># unicode string, this is ok</span>
</span><span class='line'><span class="n">s</span><span class="o">=</span><span class="s">u&quot;你好&quot;</span>
</span><span class='line'><span class="k">print</span> <span class="n">s</span>
</span></code></pre></td></tr></table></div></figure>


<p>If the parameter is not a <code>unicode PyString</code>, <code>Print</code> just treat it as <code>ASCII</code> and send to <code>sys.stdout</code>. This will be fine if the parameter use the same as the system&#8217;s local encoding, but if it will cause error in other circumstances.</p>

<figure class='code'><figcaption><span>cp936.py  </span></figcaption>
 <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
<span class='line-number'>3</span>
<span class='line-number'>4</span>
</pre></td><td class='code'><pre><code class='python'><span class='line'><span class="c"># coding=cp936</span>
</span><span class='line'><span class="c"># same as local encoding, this is ok on my machine</span>
</span><span class='line'><span class="n">s</span><span class="o">=</span><span class="s">&quot;你好&quot;</span>
</span><span class='line'><span class="k">print</span> <span class="n">s</span>
</span></code></pre></td></tr></table></div></figure>




<figure class='code'><figcaption><span>utf8.py  </span></figcaption>
 <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
<span class='line-number'>3</span>
<span class='line-number'>4</span>
<span class='line-number'>5</span>
<span class='line-number'>6</span>
<span class='line-number'>7</span>
</pre></td><td class='code'><pre><code class='python'><span class='line'><span class="c"># coding=utf-8</span>
</span><span class='line'><span class="c"># This will be wrong</span>
</span><span class='line'><span class="n">s</span><span class="o">=</span><span class="s">&quot;你好&quot;</span>
</span><span class='line'><span class="k">print</span> <span class="n">s</span>
</span><span class='line'><span class="c"># This will be wrong too</span>
</span><span class='line'><span class="n">s</span><span class="o">=</span><span class="s">&quot;</span><span class="se">\xE4\xBD\xA0\xE5\xA5\xBD</span><span class="s">&quot;</span> <span class="c"># the same sequence</span>
</span><span class='line'><span class="k">print</span> <span class="n">s</span>
</span></code></pre></td></tr></table></div></figure>


<p>We must decode the parameter into <code>unicode</code> to solve this problem.</p>

<figure class='code'><figcaption><span>utf8.py  </span></figcaption>
 <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
<span class='line-number'>3</span>
<span class='line-number'>4</span>
<span class='line-number'>5</span>
<span class='line-number'>6</span>
<span class='line-number'>7</span>
</pre></td><td class='code'><pre><code class='python'><span class='line'><span class="c"># coding=utf-8</span>
</span><span class='line'><span class="c"># This will be ok</span>
</span><span class='line'><span class="n">s</span><span class="o">=</span><span class="s">&quot;你好&quot;</span>
</span><span class='line'><span class="k">print</span> <span class="n">s</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span><span class="s">&quot;utf-8&quot;</span><span class="p">)</span>
</span><span class='line'><span class="c"># This will be ok too</span>
</span><span class='line'><span class="n">s</span><span class="o">=</span><span class="s">&quot;</span><span class="se">\xE4\xBD\xA0\xE5\xA5\xBD</span><span class="s">&quot;</span> <span class="c"># the same sequence</span>
</span><span class='line'><span class="k">print</span> <span class="nb">unicode</span><span class="p">(</span><span class="n">s</span><span class="p">,</span> <span class="s">&quot;utf-8&quot;</span><span class="p">)</span>
</span></code></pre></td></tr></table></div></figure>


<h2>Embedded Python</h2>

<p>In some tasks we need to do some interaciton between <code>C</code> and <code>Python</code>, there are also some tricky encoding problems. The following is a <code>C</code> program calling the <code>Print</code> function.</p>

<figure class='code'><figcaption><span>print.c  </span></figcaption>
 <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
<span class='line-number'>3</span>
<span class='line-number'>4</span>
<span class='line-number'>5</span>
<span class='line-number'>6</span>
<span class='line-number'>7</span>
<span class='line-number'>8</span>
<span class='line-number'>9</span>
<span class='line-number'>10</span>
</pre></td><td class='code'><pre><code class='python'><span class='line'><span class="c">#include &lt;Python.h&gt;</span>
</span><span class='line'>
</span><span class='line'><span class="nb">int</span> <span class="n">main</span><span class="p">(</span><span class="nb">int</span> <span class="n">argc</span><span class="p">,</span> <span class="n">char</span><span class="o">*</span> <span class="n">argv</span><span class="p">[])</span>
</span><span class='line'><span class="p">{</span>
</span><span class='line'>    <span class="n">const</span> <span class="n">char</span><span class="o">*</span> <span class="nb">str</span> <span class="o">=</span> <span class="s">&quot;# coding=utf-8</span><span class="se">\n</span><span class="s">&quot;</span> <span class="s">&quot;s=&#39;你好&#39;</span><span class="se">\n</span><span class="s">&quot;</span> <span class="s">&quot;print unicode(s, &#39;utf-8&#39;)&quot;</span><span class="p">;</span>
</span><span class='line'>    <span class="n">Py_Initialize</span><span class="p">();</span>
</span><span class='line'>    <span class="n">PyRun_SimpleString</span><span class="p">(</span><span class="nb">str</span><span class="p">);</span>
</span><span class='line'>    <span class="n">Py_Finalize</span><span class="p">();</span>
</span><span class='line'>    <span class="k">return</span> <span class="mi">0</span><span class="p">;</span>
</span><span class='line'><span class="p">}</span>
</span></code></pre></td></tr></table></div></figure>


<p>If we save this source file as <code>utf-8</code> and compile it with <code>Visual C++</code>, the result of the program will be wrong. But the following program will be right.</p>

<figure class='code'><figcaption><span>print.c  </span></figcaption>
 <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
<span class='line-number'>3</span>
<span class='line-number'>4</span>
<span class='line-number'>5</span>
<span class='line-number'>6</span>
<span class='line-number'>7</span>
<span class='line-number'>8</span>
<span class='line-number'>9</span>
<span class='line-number'>10</span>
<span class='line-number'>11</span>
</pre></td><td class='code'><pre><code class='python'><span class='line'><span class="c">#include &lt;Python.h&gt;</span>
</span><span class='line'>
</span><span class='line'><span class="nb">int</span> <span class="n">main</span><span class="p">(</span><span class="nb">int</span> <span class="n">argc</span><span class="p">,</span> <span class="n">char</span><span class="o">*</span> <span class="n">argv</span><span class="p">[])</span>
</span><span class='line'><span class="p">{</span>
</span><span class='line'>    <span class="o">//</span> <span class="n">even</span> <span class="n">the</span> <span class="nb">file</span> <span class="ow">is</span> <span class="n">saved</span> <span class="k">as</span> <span class="n">utf</span><span class="o">-</span><span class="mi">8</span><span class="p">,</span> <span class="n">the</span> <span class="n">string</span> <span class="n">here</span> <span class="n">will</span> <span class="n">be</span> <span class="n">compiled</span> <span class="n">into</span> <span class="n">local</span> <span class="n">encoding</span>
</span><span class='line'>    <span class="n">const</span> <span class="n">char</span><span class="o">*</span> <span class="nb">str</span> <span class="o">=</span> <span class="s">&quot;# coding=cp936</span><span class="se">\n</span><span class="s">&quot;</span> <span class="s">&quot;s=&#39;你好&#39;</span><span class="se">\n</span><span class="s">&quot;</span> <span class="s">&quot;print unicode(s, &#39;cp936&#39;)&quot;</span><span class="p">;</span>
</span><span class='line'>    <span class="n">Py_Initialize</span><span class="p">();</span>
</span><span class='line'>    <span class="n">PyRun_SimpleString</span><span class="p">(</span><span class="nb">str</span><span class="p">);</span>
</span><span class='line'>    <span class="n">Py_Finalize</span><span class="p">();</span>
</span><span class='line'>    <span class="k">return</span> <span class="mi">0</span><span class="p">;</span>
</span><span class='line'><span class="p">}</span>
</span></code></pre></td></tr></table></div></figure>


<p>The problem is that the compiler will convert the string into local encoding without caring about the encoding of the file. What&#8217;s worse, I cannot find any way to change this setting. So to solve this problem, we should convert strings to sepcial encoding manually but not let the compiler do it.</p>

<h2>Conclusion</h2>

<p>In conclusion, to avoid other similar problems, we should only use <code>unicode</code> strings in Python, and use resource files instead of writing strings directly in the source files.</p>
]]></content>
  </entry>
  
  <entry>
    <title type="html"><![CDATA[Understand ArraySizeHelper]]></title>
    <link href="http://Fruiter.github.com/blog/2012/10/07/understand-arraysizehelper/"/>
    <updated>2012-10-07T16:14:00+08:00</updated>
    <id>http://Fruiter.github.com/blog/2012/10/07/understand-arraysizehelper</id>
    <content type="html"><![CDATA[<h2>Intro</h2>

<p>In Chrome&#8217;s source code, <code>arraysize</code> is a macro used to calculate the number of elements in one array. It can be applied to different kinds of arrays without indicate the arrays&#8217; type explicitly. The code is shown as below.</p>

<figure class='code'><figcaption><span>ArraySizeHelper  </span></figcaption>
 <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
<span class='line-number'>3</span>
</pre></td><td class='code'><pre><code class='cpp'><span class='line'><span class="k">template</span> <span class="o">&lt;</span><span class="k">typename</span> <span class="n">T</span><span class="p">,</span> <span class="n">size_t</span> <span class="n">N</span><span class="o">&gt;</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">ArraySizeHelper</span><span class="p">(</span><span class="n">T</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">array</span><span class="p">)[</span><span class="n">N</span><span class="p">]))[</span><span class="n">N</span><span class="p">];</span>
</span><span class='line'><span class="cp">#define arraysize(array) (sizeof(ArraySizeHelper(array)))</span>
</span></code></pre></td></tr></table></div></figure>


<p>The code is short, but it seems not very easy for C++ beginner to learn how it works. In order to understand this tircky macro, first we need to understand 3 special language features respectively.</p>

<h2>Reference</h2>

<p>Normally Reference is used in C++ to substitute Pointer in C in function call, so the function can have a clearer declaration and better data abstraction. But sometimes, the syntax of Reference is little complicated.</p>

<figure class='code'> <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
<span class='line-number'>3</span>
<span class='line-number'>4</span>
<span class='line-number'>5</span>
<span class='line-number'>6</span>
<span class='line-number'>7</span>
<span class='line-number'>8</span>
<span class='line-number'>9</span>
<span class='line-number'>10</span>
<span class='line-number'>11</span>
<span class='line-number'>12</span>
<span class='line-number'>13</span>
<span class='line-number'>14</span>
<span class='line-number'>15</span>
<span class='line-number'>16</span>
<span class='line-number'>17</span>
<span class='line-number'>18</span>
<span class='line-number'>19</span>
<span class='line-number'>20</span>
<span class='line-number'>21</span>
<span class='line-number'>22</span>
<span class='line-number'>23</span>
<span class='line-number'>24</span>
<span class='line-number'>25</span>
<span class='line-number'>26</span>
<span class='line-number'>27</span>
<span class='line-number'>28</span>
<span class='line-number'>29</span>
<span class='line-number'>30</span>
<span class='line-number'>31</span>
<span class='line-number'>32</span>
</pre></td><td class='code'><pre><code class='cpp'><span class='line'><span class="c1">// cliche</span>
</span><span class='line'><span class="kt">char</span> <span class="n">c</span><span class="p">;</span>
</span><span class='line'><span class="kt">char</span><span class="o">*</span> <span class="n">p</span><span class="p">;</span>
</span><span class='line'><span class="kt">char</span><span class="o">&amp;</span> <span class="n">r</span> <span class="o">=</span> <span class="n">c</span><span class="p">;</span>
</span><span class='line'>
</span><span class='line'><span class="c1">// dizzy code</span>
</span><span class='line'><span class="kt">char</span> <span class="n">s</span><span class="p">[</span><span class="mi">10</span><span class="p">];</span>
</span><span class='line'><span class="kt">char</span><span class="o">*</span> <span class="n">pp</span><span class="p">[</span><span class="mi">10</span><span class="p">];</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">*</span><span class="n">ps</span><span class="p">)[</span><span class="mi">10</span><span class="p">];</span>
</span><span class='line'><span class="c1">// ?</span>
</span><span class='line'><span class="c1">// char&amp; rr[10]; //error</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">rs</span><span class="p">)[</span><span class="mi">10</span><span class="p">]</span> <span class="o">=</span> <span class="n">s</span><span class="p">;</span>
</span><span class='line'>
</span><span class='line'><span class="c1">// how about this</span>
</span><span class='line'><span class="kt">char</span> <span class="n">fc</span><span class="p">()</span> <span class="p">{</span> <span class="k">return</span> <span class="sc">&#39;a&#39;</span><span class="p">;</span> <span class="p">}</span>
</span><span class='line'><span class="kt">char</span><span class="o">*</span> <span class="n">fp</span><span class="p">()</span> <span class="p">{</span> <span class="k">return</span> <span class="mi">0</span><span class="p">;</span> <span class="p">}</span>
</span><span class='line'><span class="c1">// char fs()[10]; //error</span>
</span><span class='line'><span class="kt">char</span><span class="o">&amp;</span> <span class="n">fr</span><span class="p">()</span> <span class="p">{</span> <span class="kt">char</span> <span class="n">c</span><span class="o">=</span><span class="sc">&#39;a&#39;</span><span class="p">;</span> <span class="k">return</span> <span class="n">c</span><span class="p">;</span> <span class="p">}</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">fr_decl</span><span class="p">());</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">fr_impl</span><span class="p">())</span> <span class="p">{</span> <span class="kt">char</span> <span class="n">c</span><span class="o">=</span><span class="sc">&#39;a&#39;</span><span class="p">;</span> <span class="k">return</span> <span class="n">c</span><span class="p">;</span> <span class="p">}</span>
</span><span class='line'>
</span><span class='line'><span class="c1">// tricky</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">*</span><span class="n">pfc</span><span class="p">)()</span> <span class="o">=</span> <span class="n">fc</span><span class="p">;</span>
</span><span class='line'><span class="kt">char</span><span class="o">*</span> <span class="p">(</span><span class="o">*</span><span class="n">pfp</span><span class="p">)()</span> <span class="o">=</span> <span class="n">fp</span><span class="p">;</span>
</span><span class='line'><span class="c1">// ??</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">rfc</span><span class="p">)()</span> <span class="o">=</span> <span class="n">fc</span><span class="p">;</span>
</span><span class='line'><span class="kt">char</span><span class="o">&amp;</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">rfr</span><span class="p">)()</span> <span class="o">=</span> <span class="n">fr</span><span class="p">;</span>
</span><span class='line'><span class="c1">// ???</span>
</span><span class='line'><span class="c1">// char (&amp;rfs)()[10]; //error</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">frs</span><span class="p">())[</span><span class="mi">10</span><span class="p">];</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">frs_impl</span><span class="p">())[</span><span class="mi">10</span><span class="p">]</span> <span class="p">{</span> <span class="kt">char</span> <span class="n">s</span><span class="p">[</span><span class="mi">10</span><span class="p">];</span> <span class="k">return</span> <span class="n">s</span><span class="p">;</span> <span class="p">}</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="p">(</span><span class="o">&amp;</span><span class="n">rfrs</span><span class="p">)())[</span><span class="mi">10</span><span class="p">]</span> <span class="o">=</span> <span class="n">frs</span><span class="p">;</span>
</span></code></pre></td></tr></table></div></figure>


<p>Through above examples, we can understand that <code>ArraySizeHelper</code> part involved in the macro code is actually a function declaration. For example, <code>ArraySizeHelper</code> in the code <code>int arr[10]; ArraySizeHelper(arr);</code> is equal with <code>char (&amp;ArraySizeHelper(int (&amp;array)[10]))[10]</code>, which is a function accepts a reference of an int array(size 10) as an parameter, and returns a reference of a char array(size 10) as result.</p>

<h2>Template</h2>

<p>As we already know <code>ArraySizeHelper</code> is a function declaration, the template part in the macro is not hard to understand. According to the macro, the template for <code>ArraySizeHelper</code> can only accept <code>array type</code> as its parameter. It will generate specific declaration corresponding the parameter&#8217;s type automatically.</p>

<figure class='code'> <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
<span class='line-number'>3</span>
<span class='line-number'>4</span>
<span class='line-number'>5</span>
<span class='line-number'>6</span>
<span class='line-number'>7</span>
<span class='line-number'>8</span>
<span class='line-number'>9</span>
<span class='line-number'>10</span>
<span class='line-number'>11</span>
<span class='line-number'>12</span>
</pre></td><td class='code'><pre><code class='cpp'><span class='line'><span class="c1">// simulate</span>
</span><span class='line'><span class="kt">float</span> <span class="n">f</span><span class="p">[</span><span class="mi">5</span><span class="p">];</span>
</span><span class='line'><span class="kt">float</span> <span class="n">f2</span><span class="p">[</span><span class="mi">5</span><span class="p">]</span>
</span><span class='line'><span class="n">foo</span> <span class="n">o</span><span class="p">[</span><span class="mi">8</span><span class="p">];</span>
</span><span class='line'>
</span><span class='line'><span class="n">ArraySizeHelper</span><span class="p">(</span><span class="n">f</span><span class="p">);</span>
</span><span class='line'><span class="n">ArraySizeHelper</span><span class="p">(</span><span class="n">f2</span><span class="p">);</span>
</span><span class='line'><span class="n">ArraySizeHelper</span><span class="p">(</span><span class="n">o</span><span class="p">);</span>
</span><span class='line'>
</span><span class='line'><span class="c1">// Template Instantiation...</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">ArraySizeHelper</span><span class="p">(</span><span class="kt">float</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">array</span><span class="p">)[</span><span class="mi">5</span><span class="p">]))[</span><span class="mi">5</span><span class="p">];</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">ArraySizeHelper</span><span class="p">(</span><span class="n">foo</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">array</span><span class="p">)[</span><span class="mi">8</span><span class="p">]))[</span><span class="mi">8</span><span class="p">];</span>
</span></code></pre></td></tr></table></div></figure>


<p>One point worth mention is that directly call <code>ArraySizeHelper</code> will cause error in the program, because <code>ArraySizeHelper</code> has no implement code.</p>

<h2>Sizeof</h2>

<p><code>sizeof</code> is a very interesting keyword. We usually use it to compute the size of special user-defined structure, or use it in the bit operation. It is natural to think it acts like a function, but actually it will return the computed result during compiling time instead of runing time, so we must consider it separately as a special language feature.</p>

<p>The way <code>sizeof</code> used in the macro is very tricky, and I have not seen this usage in any other articles or codes before.</p>

<figure class='code'> <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
<span class='line-number'>3</span>
<span class='line-number'>4</span>
<span class='line-number'>5</span>
<span class='line-number'>6</span>
<span class='line-number'>7</span>
<span class='line-number'>8</span>
<span class='line-number'>9</span>
<span class='line-number'>10</span>
<span class='line-number'>11</span>
<span class='line-number'>12</span>
<span class='line-number'>13</span>
<span class='line-number'>14</span>
<span class='line-number'>15</span>
<span class='line-number'>16</span>
<span class='line-number'>17</span>
<span class='line-number'>18</span>
<span class='line-number'>19</span>
<span class='line-number'>20</span>
<span class='line-number'>21</span>
<span class='line-number'>22</span>
<span class='line-number'>23</span>
<span class='line-number'>24</span>
<span class='line-number'>25</span>
<span class='line-number'>26</span>
<span class='line-number'>27</span>
<span class='line-number'>28</span>
<span class='line-number'>29</span>
<span class='line-number'>30</span>
<span class='line-number'>31</span>
<span class='line-number'>32</span>
<span class='line-number'>33</span>
</pre></td><td class='code'><pre><code class='cpp'><span class='line'><span class="c1">// sizeof reference</span>
</span><span class='line'><span class="kt">char</span> <span class="n">c</span><span class="p">;</span>
</span><span class='line'><span class="kt">int</span> <span class="n">i</span><span class="p">;</span>
</span><span class='line'><span class="kt">char</span> <span class="n">s</span><span class="p">[</span><span class="mi">7</span><span class="p">];</span>
</span><span class='line'><span class="kt">int</span> <span class="n">a</span><span class="p">[</span><span class="mi">9</span><span class="p">];</span>
</span><span class='line'>
</span><span class='line'><span class="kt">char</span><span class="o">&amp;</span> <span class="n">rc</span> <span class="o">=</span> <span class="n">c</span><span class="p">;</span>
</span><span class='line'><span class="kt">int</span><span class="o">&amp;</span> <span class="n">ri</span> <span class="o">=</span> <span class="n">i</span><span class="p">;</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">rs</span><span class="p">)[</span><span class="mi">7</span><span class="p">]</span> <span class="o">=</span> <span class="n">s</span><span class="p">;</span>
</span><span class='line'><span class="kt">int</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">ra</span><span class="p">)[</span><span class="mi">9</span><span class="p">]</span> <span class="o">=</span> <span class="n">a</span><span class="p">;</span>
</span><span class='line'>
</span><span class='line'><span class="kt">int</span> <span class="n">src</span> <span class="o">=</span> <span class="k">sizeof</span><span class="p">(</span><span class="n">rc</span><span class="p">);</span>
</span><span class='line'><span class="kt">int</span> <span class="n">sri</span> <span class="o">=</span> <span class="k">sizeof</span><span class="p">(</span><span class="n">ri</span><span class="p">);</span>
</span><span class='line'>
</span><span class='line'><span class="kt">int</span> <span class="n">ss</span> <span class="o">=</span> <span class="k">sizeof</span><span class="p">(</span><span class="n">s</span><span class="p">);</span>
</span><span class='line'><span class="kt">int</span> <span class="n">srs</span> <span class="o">=</span> <span class="k">sizeof</span><span class="p">(</span><span class="n">rs</span><span class="p">);</span>
</span><span class='line'><span class="kt">int</span> <span class="n">sa</span> <span class="o">=</span> <span class="k">sizeof</span><span class="p">(</span><span class="n">a</span><span class="p">);</span>
</span><span class='line'><span class="kt">int</span> <span class="n">sra</span> <span class="o">=</span> <span class="k">sizeof</span><span class="p">(</span><span class="n">ra</span><span class="p">);</span>
</span><span class='line'>
</span><span class='line'><span class="c1">// sizeof function call</span>
</span><span class='line'><span class="kt">int</span> <span class="n">fi</span><span class="p">();</span>
</span><span class='line'><span class="kt">char</span> <span class="n">fc</span><span class="p">(</span><span class="kt">int</span> <span class="n">arg</span><span class="p">);</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">frs</span><span class="p">(</span><span class="kt">double</span> <span class="n">arg</span><span class="p">))[</span><span class="mi">3</span><span class="p">]</span> <span class="p">{</span>
</span><span class='line'>    <span class="kt">char</span> <span class="n">s</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span> <span class="o">=</span> <span class="p">{</span><span class="sc">&#39;h&#39;</span><span class="p">,</span> <span class="sc">&#39;i&#39;</span><span class="p">,</span> <span class="sc">&#39;\0&#39;</span><span class="p">};</span>
</span><span class='line'>    <span class="n">std</span><span class="o">::</span><span class="n">cout</span><span class="o">&lt;&lt;</span><span class="n">s</span><span class="p">;</span>
</span><span class='line'>    <span class="k">return</span> <span class="n">s</span><span class="p">;</span>
</span><span class='line'><span class="p">}</span>
</span><span class='line'>
</span><span class='line'><span class="c1">// what will happen?</span>
</span><span class='line'><span class="c1">// int sfi = sizeof(fi); // error</span>
</span><span class='line'><span class="kt">int</span> <span class="n">sfi</span> <span class="o">=</span> <span class="k">sizeof</span><span class="p">(</span><span class="n">fi</span><span class="p">());</span>
</span><span class='line'><span class="kt">int</span> <span class="n">sfc</span> <span class="o">=</span> <span class="k">sizeof</span><span class="p">(</span><span class="n">fc</span><span class="p">(</span><span class="mi">7</span><span class="p">));</span>
</span><span class='line'><span class="kt">int</span> <span class="n">sfrs</span> <span class="o">=</span> <span class="k">sizeof</span><span class="p">(</span><span class="n">fs</span><span class="p">(</span><span class="mf">2.2</span><span class="p">));</span>
</span></code></pre></td></tr></table></div></figure>


<p>From above examples, we can find out that <code>sizeof</code> will treat reference types the same as their referring types, and it will treat function calls the same as their return types. As mentioned above, <code>sizeof</code> is executed during compiling time, so it can accept function calls as its parameter without caring about the implement of those functions because it will not really call them.</p>

<h2>Last Shot</h2>

<p>Now we can give an example to show how the ArraySizeHelper macro works.</p>

<figure class='code'> <div class="highlight"><table><tr><td class="gutter"><pre class="line-numbers"><span class='line-number'>1</span>
<span class='line-number'>2</span>
<span class='line-number'>3</span>
<span class='line-number'>4</span>
<span class='line-number'>5</span>
<span class='line-number'>6</span>
<span class='line-number'>7</span>
<span class='line-number'>8</span>
<span class='line-number'>9</span>
<span class='line-number'>10</span>
<span class='line-number'>11</span>
<span class='line-number'>12</span>
</pre></td><td class='code'><pre><code class='cpp'><span class='line'><span class="kt">float</span> <span class="n">f</span><span class="p">[</span><span class="mi">5</span><span class="p">];</span>
</span><span class='line'>
</span><span class='line'><span class="n">arraysize</span><span class="p">(</span><span class="n">f</span><span class="p">);</span>
</span><span class='line'>
</span><span class='line'><span class="c1">// equal with...</span>
</span><span class='line'><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">ArraySizeHelper</span><span class="p">(</span><span class="kt">float</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">array</span><span class="p">)[</span><span class="mi">5</span><span class="p">]))[</span><span class="mi">5</span><span class="p">];</span>
</span><span class='line'><span class="k">sizeof</span><span class="p">(</span><span class="n">ArraySizeHelper</span><span class="p">(</span><span class="n">f</span><span class="p">));</span>
</span><span class='line'>
</span><span class='line'><span class="c1">// equal with...</span>
</span><span class='line'><span class="k">sizeof</span><span class="p">(</span><span class="kt">char</span> <span class="p">(</span><span class="o">&amp;</span><span class="n">array</span><span class="p">)[</span><span class="mi">5</span><span class="p">]);</span>
</span><span class='line'>
</span><span class='line'><span class="c1">// return 5</span>
</span></code></pre></td></tr></table></div></figure>



]]></content>
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