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xml_objectify

xml_objectifyxml_objectify

xml_objectify

例句：
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To support this, I created a little recursive traversal function that walks all the nodes of a gnosis. xml. objectify object.
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gnosis. xml. objectify attaches subelement nodes directly as attributes of nodes (every node is of a custom class named after the tag name).
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In contrast, a gnosis. xml. objectify node has no built-in method to step through all of its subelements.
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From time to time, users have been bothered by the fact that gnosis. xml. objectify does not reserialize its objects to XML.
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There appears to be a complexity order effect going on that renders xml_objectify unusable for large documents.
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Two tools that simplify working with XML in an object-oriented manner (in Python) are David Mertz' xml_objectify and xml_pickle.
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In several previous articles, I have advocated the clarity and simplicity of my own Python xml_objectify module.
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I have produced my own set of high-level modules for dealing with XML called xml_pickle and xml_objectify.
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The limits imposed in this regard are essentially identical to the limits imposed by the xml_objectify library that xml2sql utilizes.
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When accessing a gnosis. xml. objectify object, the simplest thing that could possibly work almost always does work.
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I think beginning users of gnosis. xml. objectify have been intimidated by the idea of specializing classes per-tagname.
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I present a simple task that contrasts the ElementTree and gnosis. xml. objectify APIs.
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The node objects in gnosis. xml. objectify trees are, by design, quite dumb.
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In order to avoid a sloppy conflict in the first module version, xml_objectify now "mangles" the names of the class templates for XML nodes.
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The first step for xml2sql is to create a "Pythonic" object using xml_objectify.
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Probably the most powerful feature of xml_objectify is also a subtle one.
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In this article, I will remedy that, in part, relative to gnosis. xml. objectify.

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