https://github.com/dcwatson/drill

A small python library for quickly traversing XML data.
https://github.com/dcwatson/drill

Last synced: about 1 year ago
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A small python library for quickly traversing XML data.

• Host: GitHub
• URL: https://github.com/dcwatson/drill
• Owner: dcwatson
• License: bsd-2-clause
• Created: 2012-07-03T15:30:09.000Z (almost 14 years ago)
• Default Branch: master
• Last Pushed: 2018-12-03T00:30:54.000Z (over 7 years ago)
• Last Synced: 2025-03-21T19:04:56.947Z (about 1 year ago)
• Language: Python
• Size: 40 KB
• Stars: 2
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
## Basic Usage

    import drill

    doc = drill.parse(path_or_url_or_string)

    

    # Drill down to a specific element.

    print unicode(doc.book.title)

    

    # Iterate through all "title" tags in the document.

    for t in doc.iter('title'):

        print t.attrs, t.data

    

    # Find all "bar" nodes with a "baz" child and a "foo" parent.

    q = doc.find('//foo/bar[baz]')

    # Easily access the first and last elements of matching results.

    print q.first(), q.last()

    # Iterate over results.

    for e in q:

        do_something(e)

    

    # Parse only elements matching some path

    for e in drill.iterparse(filelike, xpath='root/*/something'):

        print e.tagname, e.data

## Features

* Runnable test suite

* Python 3 support

## Advantages

* Pure python

* Faster, more efficient parsing than ElementTree

    * Using ElementTree, a ~150 MB XML file (~3,000,000 elements) took ~46 seconds to parse, consuming ~1.3 GB of RAM

    * Parsing the same file using drill took ~24 seconds and consumed ~950 MB of RAM

    * Very unscientific benchmarks performed on a Core i5 @ 2.8 GHz, running Windows 7. YMMV.

* Lots of convenience methods for accessing elements quickly:

    * doc.response.resultCode.data

    * root[2].child['attr']

    * first/last/prev/next methods for traversing siblings