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Frequently asked questions |
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What is character encoding? |
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When you think of “text”, you probably think of “characters and symbols |
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I see on my computer screen”. But computers don’t deal in characters and |
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symbols; they deal in bits and bytes. Every piece of text you’ve ever |
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seen on a computer screen is actually stored in a particular *character |
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encoding*. There are many different character encodings, some optimized |
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for particular languages like Russian or Chinese or English, and others |
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that can be used for multiple languages. Very roughly speaking, the |
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character encoding provides a mapping between the stuff you see on your |
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screen and the stuff your computer actually stores in memory and on |
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disk. |
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In reality, it’s more complicated than that. Many characters are common |
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to multiple encodings, but each encoding may use a different sequence of |
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bytes to actually store those characters in memory or on disk. So you |
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can think of the character encoding as a kind of decryption key for the |
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text. Whenever someone gives you a sequence of bytes and claims it’s |
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“text”, you need to know what character encoding they used so you can |
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decode the bytes into characters and display them (or process them, or |
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whatever). |
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What is character encoding auto-detection? |
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It means taking a sequence of bytes in an unknown character encoding, |
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and attempting to determine the encoding so you can read the text. It’s |
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like cracking a code when you don’t have the decryption key. |
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Isn’t that impossible? |
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In general, yes. However, some encodings are optimized for specific |
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languages, and languages are not random. Some character sequences pop up |
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all the time, while other sequences make no sense. A person fluent in |
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English who opens a newspaper and finds “txzqJv 2!dasd0a QqdKjvz” will |
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instantly recognize that that isn’t English (even though it is composed |
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entirely of English letters). By studying lots of “typical” text, a |
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computer algorithm can simulate this kind of fluency and make an |
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educated guess about a text’s language. |
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In other words, encoding detection is really language detection, |
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combined with knowledge of which languages tend to use which character |
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encodings. |
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Who wrote this detection algorithm? |
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This library is a port of `the auto-detection code in |
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Mozilla <https://www-archive.mozilla.org/projects/intl/chardet.html>`__. |
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I have attempted to maintain as much of the original structure as |
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possible (mostly for selfish reasons, to make it easier to maintain the |
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port as the original code evolves). I have also retained the original |
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authors’ comments, which are quite extensive and informative. |
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You may also be interested in the research paper which led to the |
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Mozilla implementation, `A composite approach to language/encoding |
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detection <http://www-archive.mozilla.org/projects/intl/UniversalCharsetDetection.html>`__. |
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Yippie! Screw the standards, I’ll just auto-detect everything! |
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Don’t do that. Virtually every format and protocol contains a method for |
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specifying character encoding. |
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- HTTP can define a ``charset`` parameter in the ``Content-type`` |
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header. |
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- HTML documents can define a ``<meta http-equiv="content-type">`` |
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element in the ``<head>`` of a web page. |
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- XML documents can define an ``encoding`` attribute in the XML prolog. |
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If text comes with explicit character encoding information, you should |
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use it. If the text has no explicit information, but the relevant |
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standard defines a default encoding, you should use that. (This is |
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harder than it sounds, because standards can overlap. If you fetch an |
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XML document over HTTP, you need to support both standards *and* figure |
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out which one wins if they give you conflicting information.) |
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Despite the complexity, it’s worthwhile to follow standards and `respect |
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explicit character encoding |
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information <http://www.w3.org/2001/tag/doc/mime-respect>`__. It will |
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almost certainly be faster and more accurate than trying to auto-detect |
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the encoding. It will also make the world a better place, since your |
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program will interoperate with other programs that follow the same |
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standards. |
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Why bother with auto-detection if it’s slow, inaccurate, and non-standard? |
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Sometimes you receive text with verifiably inaccurate encoding |
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information. Or text without any encoding information, and the specified |
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default encoding doesn’t work. There are also some poorly designed |
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standards that have no way to specify encoding at all. |
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If following the relevant standards gets you nowhere, *and* you decide |
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that processing the text is more important than maintaining |
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interoperability, then you can try to auto-detect the character encoding |
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as a last resort. An example is my `Universal Feed |
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Parser <https://pythonhosted.org/feedparser/>`__, which calls this auto-detection |
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library `only after exhausting all other |
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options <https://pythonhosted.org/feedparser/character-encoding.html>`__. |
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