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Python module that makes working with XML feel like you are working with JSON

License: MIT License

Python 99.88% Shell 0.12%

xmltodict's Introduction

xmltodict

xmltodict is a Python module that makes working with XML feel like you are working with JSON, as in this "spec":

Build Status

>>> print(json.dumps(xmltodict.parse("""
...  <mydocument has="an attribute">
...    <and>
...      <many>elements</many>
...      <many>more elements</many>
...    </and>
...    <plus a="complex">
...      element as well
...    </plus>
...  </mydocument>
...  """), indent=4))
{
    "mydocument": {
        "@has": "an attribute", 
        "and": {
            "many": [
                "elements", 
                "more elements"
            ]
        }, 
        "plus": {
            "@a": "complex", 
            "#text": "element as well"
        }
    }
}

Namespace support

By default, xmltodict does no XML namespace processing (it just treats namespace declarations as regular node attributes), but passing process_namespaces=True will make it expand namespaces for you:

>>> xml = """
... <root xmlns="http://defaultns.com/"
...       xmlns:a="http://a.com/"
...       xmlns:b="http://b.com/">
...   <x>1</x>
...   <a:y>2</a:y>
...   <b:z>3</b:z>
... </root>
... """
>>> xmltodict.parse(xml, process_namespaces=True) == {
...     'http://defaultns.com/:root': {
...         'http://defaultns.com/:x': '1',
...         'http://a.com/:y': '2',
...         'http://b.com/:z': '3',
...     }
... }
True

It also lets you collapse certain namespaces to shorthand prefixes, or skip them altogether:

>>> namespaces = {
...     'http://defaultns.com/': None, # skip this namespace
...     'http://a.com/': 'ns_a', # collapse "http://a.com/" -> "ns_a"
... }
>>> xmltodict.parse(xml, process_namespaces=True, namespaces=namespaces) == {
...     'root': {
...         'x': '1',
...         'ns_a:y': '2',
...         'http://b.com/:z': '3',
...     },
... }
True

Streaming mode

xmltodict is very fast (Expat-based) and has a streaming mode with a small memory footprint, suitable for big XML dumps like Discogs or Wikipedia:

>>> def handle_artist(_, artist):
...     print(artist['name'])
...     return True
>>> 
>>> xmltodict.parse(GzipFile('discogs_artists.xml.gz'),
...     item_depth=2, item_callback=handle_artist)
A Perfect Circle
Fantômas
King Crimson
Chris Potter
...

It can also be used from the command line to pipe objects to a script like this:

import sys, marshal
while True:
    _, article = marshal.load(sys.stdin)
    print(article['title'])
$ bunzip2 enwiki-pages-articles.xml.bz2 | xmltodict.py 2 | myscript.py
AccessibleComputing
Anarchism
AfghanistanHistory
AfghanistanGeography
AfghanistanPeople
AfghanistanCommunications
Autism
...

Or just cache the dicts so you don't have to parse that big XML file again. You do this only once:

$ bunzip2 enwiki-pages-articles.xml.bz2 | xmltodict.py 2 | gzip > enwiki.dicts.gz

And you reuse the dicts with every script that needs them:

$ gunzip enwiki.dicts.gz | script1.py
$ gunzip enwiki.dicts.gz | script2.py
...

Roundtripping

You can also convert in the other direction, using the unparse() method:

>>> mydict = {
...     'response': {
...             'status': 'good',
...             'last_updated': '2014-02-16T23:10:12Z',
...     }
... }
>>> print(unparse(mydict, pretty=True))
<?xml version="1.0" encoding="utf-8"?>
<response>
	<status>good</status>
	<last_updated>2014-02-16T23:10:12Z</last_updated>
</response>

Text values for nodes can be specified with the cdata_key key in the python dict, while node properties can be specified with the attr_prefix prefixed to the key name in the python dict. The default value for attr_prefix is @ and the default value for cdata_key is #text.

>>> import xmltodict
>>> 
>>> mydict = {
...     'text': {
...         '@color':'red',
...         '@stroke':'2',
...         '#text':'This is a test'
...     }
... }
>>> print(xmltodict.unparse(mydict, pretty=True))
<?xml version="1.0" encoding="utf-8"?>
<text stroke="2" color="red">This is a test</text>

Lists that are specified under a key in a dictionary use the key as a tag for each item. But if a list does have a parent key, for example if a list exists inside another list, it does not have a tag to use and the items are converted to a string as shown in the example below. To give tags to nested lists, use the expand_iter keyword argument to provide a tag as demonstrated below. Note that using expand_iter will break roundtripping.

>>> mydict = {
...     "line": {
...         "points": [
...             [1, 5],
...             [2, 6],
...         ]
...     }
... }
>>> print(xmltodict.unparse(mydict, pretty=True))
<?xml version="1.0" encoding="utf-8"?>
<line>
        <points>[1, 5]</points>
        <points>[2, 6]</points>
</line>
>>> print(xmltodict.unparse(mydict, pretty=True, expand_iter="coord"))
<?xml version="1.0" encoding="utf-8"?>
<line>
        <points>
                <coord>1</coord>
                <coord>5</coord>
        </points>
        <points>
                <coord>2</coord>
                <coord>6</coord>
        </points>
</line>

Ok, how do I get it?

Using pypi

You just need to

$ pip install xmltodict

RPM-based distro (Fedora, RHEL, …)

There is an official Fedora package for xmltodict.

$ sudo yum install python-xmltodict

Arch Linux

There is an official Arch Linux package for xmltodict.

$ sudo pacman -S python-xmltodict

Debian-based distro (Debian, Ubuntu, …)

There is an official Debian package for xmltodict.

$ sudo apt install python-xmltodict

FreeBSD

There is an official FreeBSD port for xmltodict.

$ pkg install py36-xmltodict

openSUSE/SLE (SLE 15, Leap 15, Tumbleweed)

There is an official openSUSE package for xmltodict.

# Python2
$ zypper in python2-xmltodict

# Python3
$ zypper in python3-xmltodict

xmltodict's People

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