How to parse XML and get instances of a particular node attribute?
Question:
I have many rows in XML and I’m trying to get instances of a particular node attribute.
<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>
How do I access the values of the attribute foobar? In this example, I want "1" and "2".
Answers:
You can use BeautifulSoup:
from bs4 import BeautifulSoup
x="""<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>"""
y=BeautifulSoup(x)
>>> y.foo.bar.type["foobar"]
u'1'
>>> y.foo.bar.findAll("type")
[<type foobar="1"></type>, <type foobar="2"></type>]
>>> y.foo.bar.findAll("type")[0]["foobar"]
u'1'
>>> y.foo.bar.findAll("type")[1]["foobar"]
u'2'
I suggest ElementTree. There are other compatible implementations of the same API, such as lxml, and cElementTree in the Python standard library itself; but, in this context, what they chiefly add is even more speed — the ease of programming part depends on the API, which ElementTree defines.
First build an Element instance root from the XML, e.g. with the XML function, or by parsing a file with something like:
import xml.etree.ElementTree as ET
root = ET.parse('thefile.xml').getroot()
Or any of the many other ways shown at ElementTree. Then do something like:
for type_tag in root.findall('bar/type'):
value = type_tag.get('foobar')
print(value)
Output:
1
2
Python has an interface to the expat XML parser.
xml.parsers.expat
It’s a non-validating parser, so bad XML will not be caught. But if you know your file is correct, then this is pretty good, and you’ll probably get the exact info you want and you can discard the rest on the fly.
stringofxml = """<foo>
<bar>
<type arg="value" />
<type arg="value" />
<type arg="value" />
</bar>
<bar>
<type arg="value" />
</bar>
</foo>"""
count = 0
def start(name, attr):
global count
if name == 'type':
count += 1
p = expat.ParserCreate()
p.StartElementHandler = start
p.Parse(stringofxml)
print count # prints 4
minidom is the quickest and pretty straight forward.
XML:
<data>
<items>
<item name="item1"></item>
<item name="item2"></item>
<item name="item3"></item>
<item name="item4"></item>
</items>
</data>
Python:
from xml.dom import minidom
dom = minidom.parse('items.xml')
elements = dom.getElementsByTagName('item')
print(f"There are {len(elements)} items:")
for element in elements:
print(element.attributes['name'].value)
Output:
There are 4 items:
item1
item2
item3
item4
lxml.objectify is really simple.
Taking your sample text:
from lxml import objectify
from collections import defaultdict
count = defaultdict(int)
root = objectify.fromstring(text)
for item in root.bar.type:
count[item.attrib.get("foobar")] += 1
print dict(count)
Output:
{'1': 1, '2': 1}
Here a very simple but effective code using cElementTree.
try:
import cElementTree as ET
except ImportError:
try:
# Python 2.5 need to import a different module
import xml.etree.cElementTree as ET
except ImportError:
exit_err("Failed to import cElementTree from any known place")
def find_in_tree(tree, node):
found = tree.find(node)
if found == None:
print "No %s in file" % node
found = []
return found
# Parse a xml file (specify the path)
def_file = "xml_file_name.xml"
try:
dom = ET.parse(open(def_file, "r"))
root = dom.getroot()
except:
exit_err("Unable to open and parse input definition file: " + def_file)
# Parse to find the child nodes list of node 'myNode'
fwdefs = find_in_tree(root,"myNode")
This is from “python xml parse“.
There are many options out there. cElementTree looks excellent if speed and memory usage are an issue. It has very little overhead compared to simply reading in the file using readlines.
The relevant metrics can be found in the table below, copied from the cElementTree website:
library time space
xml.dom.minidom (Python 2.1) 6.3 s 80000K
gnosis.objectify 2.0 s 22000k
xml.dom.minidom (Python 2.4) 1.4 s 53000k
ElementTree 1.2 1.6 s 14500k
ElementTree 1.2.4/1.3 1.1 s 14500k
cDomlette (C extension) 0.540 s 20500k
PyRXPU (C extension) 0.175 s 10850k
libxml2 (C extension) 0.098 s 16000k
readlines (read as utf-8) 0.093 s 8850k
cElementTree (C extension) --> 0.047 s 4900K <--
readlines (read as ascii) 0.032 s 5050k
As pointed out by @jfs, cElementTree comes bundled with Python:
- Python 2:
from xml.etree import cElementTree as ElementTree.
- Python 3:
from xml.etree import ElementTree (the accelerated C version is used automatically).
I suggest xmltodict for simplicity.
It parses your XML to an OrderedDict;
>>> e = '<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo> '
>>> import xmltodict
>>> result = xmltodict.parse(e)
>>> result
OrderedDict([(u'foo', OrderedDict([(u'bar', OrderedDict([(u'type', [OrderedDict([(u'@foobar', u'1')]), OrderedDict([(u'@foobar', u'2')])])]))]))])
>>> result['foo']
OrderedDict([(u'bar', OrderedDict([(u'type', [OrderedDict([(u'@foobar', u'1')]), OrderedDict([(u'@foobar', u'2')])])]))])
>>> result['foo']['bar']
OrderedDict([(u'type', [OrderedDict([(u'@foobar', u'1')]), OrderedDict([(u'@foobar', u'2')])])])
import xml.etree.ElementTree as ET
data = '''<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>'''
tree = ET.fromstring(data)
lst = tree.findall('bar/type')
for item in lst:
print item.get('foobar')
This will print the value of the foobar attribute.
Just to add another possibility, you can use untangle, as it is a simple xml-to-python-object library. Here you have an example:
Installation:
pip install untangle
Usage:
Your XML file (a little bit changed):
<foo>
<bar name="bar_name">
<type foobar="1"/>
</bar>
</foo>
Accessing the attributes with untangle:
import untangle
obj = untangle.parse('/path_to_xml_file/file.xml')
print obj.foo.bar['name']
print obj.foo.bar.type['foobar']
The output will be:
bar_name
1
More information about untangle can be found in “untangle“.
Also, if you are curious, you can find a list of tools for working with XML and Python in “Python and XML“. You will also see that the most common ones were mentioned by previous answers.
I might suggest declxml.
Full disclosure: I wrote this library because I was looking for a way to convert between XML and Python data structures without needing to write dozens of lines of imperative parsing/serialization code with ElementTree.
With declxml, you use processors to declaratively define the structure of your XML document and how to map between XML and Python data structures. Processors are used to for both serialization and parsing as well as for a basic level of validation.
Parsing into Python data structures is straightforward:
import declxml as xml
xml_string = """
<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>
"""
processor = xml.dictionary('foo', [
xml.dictionary('bar', [
xml.array(xml.integer('type', attribute='foobar'))
])
])
xml.parse_from_string(processor, xml_string)
Which produces the output:
{'bar': {'foobar': [1, 2]}}
You can also use the same processor to serialize data to XML
data = {'bar': {
'foobar': [7, 3, 21, 16, 11]
}}
xml.serialize_to_string(processor, data, indent=' ')
Which produces the following output
<?xml version="1.0" ?>
<foo>
<bar>
<type foobar="7"/>
<type foobar="3"/>
<type foobar="21"/>
<type foobar="16"/>
<type foobar="11"/>
</bar>
</foo>
If you want to work with objects instead of dictionaries, you can define processors to transform data to and from objects as well.
import declxml as xml
class Bar:
def __init__(self):
self.foobars = []
def __repr__(self):
return 'Bar(foobars={})'.format(self.foobars)
xml_string = """
<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>
"""
processor = xml.dictionary('foo', [
xml.user_object('bar', Bar, [
xml.array(xml.integer('type', attribute='foobar'), alias='foobars')
])
])
xml.parse_from_string(processor, xml_string)
Which produces the following output
{'bar': Bar(foobars=[1, 2])}
XML:
<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>
Python code:
import xml.etree.cElementTree as ET
tree = ET.parse("foo.xml")
root = tree.getroot()
root_tag = root.tag
print(root_tag)
for form in root.findall("./bar/type"):
x=(form.attrib)
z=list(x)
for i in z:
print(x[i])
Output:
foo
1
2
xml.etree.ElementTree vs. lxml
These are some pros of the two most used libraries I would have benefit to know before choosing between them.
xml.etree.ElementTree:
- From the standard library: no needs of installing any module
lxml
- Easily write XML declaration: for instance do you need to add
standalone="no"?
- Pretty printing: you can have a nice indented XML without extra code.
- Objectify functionality: It allows you to use XML as if you were dealing with a normal Python object hierarchy
.node.
sourceline allows to easily get the line of the XML element you are using.- you can use also a built-in XSD schema checker.
There’s no need to use a lib specific API if you use python-benedict. Just initialize a new instance from your XML and manage it easily since it is a dict subclass.
Installation is easy: pip install python-benedict
from benedict import benedict as bdict
# data-source can be an url, a filepath or data-string (as in this example)
data_source = """
<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>"""
data = bdict.from_xml(data_source)
t_list = data['foo.bar'] # yes, keypath supported
for t in t_list:
print(t['@foobar'])
It supports and normalizes I/O operations with many formats: Base64, CSV, JSON, TOML, XML, YAML and query-string.
It is well tested and open-source on GitHub. Disclosure: I am the author.
#If the xml is in the form of a string as shown below then
from lxml import etree, objectify
'''sample xml as a string with a name space {http:// encoding="UTF-8"?>rn<pa:Process >rnt<pa:firsttag>SAMPLE</pa:firsttag></pa:Process>rn' # this is a sample xml which is a string
print('************message coversion and parsing starts*************')
message=message.decode('utf-8')
message=message.replace('<?xml version="1.0" encoding="UTF-8"?>rn','') #replace is used to remove unwanted strings from the 'message'
message=message.replace('pa:Process>rn','pa:Process>')
print (message)
print ('******Parsing starts*************')
parser = etree.XMLParser(remove_blank_text=True) #the name space is removed here
root = etree.fromstring(message, parser) #parsing of xml happens here
print ('******Parsing completed************')
dict={}
for child in root: # parsed xml is iterated using a for loop and values are stored in a dictionary
print(child.tag,child.text)
print('****Derving from xml tree*****')
if child.tag =="{http://>
<pa:firsttag>SAMPLE</pa:firsttag></pa:Process>
******Parsing starts*************
******Parsing completed************
{http://>
<pa:firsttag>SAMPLE</pa:firsttag>
</pa:Process>
you may try the following code
from lxml import etree, objectify
metadata = 'C:\Users\PROCS.xml' # this is sample xml file the contents are shown above
parser = etree.XMLParser(remove_blank_text=True) # this line removes the name space from the xml in this sample the name space is --> http://sssss
tree = etree.parse(metadata, parser) # this line parses the xml file which is PROCS.xml
root = tree.getroot() # we get the root of xml which is process and iterate using a for loop
for elem in root.getiterator():
if not hasattr(elem.tag, 'find'): continue # (1)
i = elem.tag.find('}')
if i >= 0:
elem.tag = elem.tag[i+1:]
dict={} # a python dictionary is declared
for elem in tree.iter(): #iterating through the xml tree using a for loop
if elem.tag =="firsttag": # if the tag name matches the name that is equated then the text in the tag is stored into the dictionary
dict["FIRST_TAG"]=str(elem.text)
print(dict)
Output would be
{'FIRST_TAG': 'SAMPLE'}
If you don’t want to use any external libraries or 3rd party tools, Please try below code.
- This will parse
xml into python dictionary
- This will parse xml attrbutes as well
- This will also parse empty tags like
<tag/> and tags with only attributes like <tag var=val/>
Code
import re
def getdict(content):
res=re.findall("<(?P<var>S*)(?P<attr>[^/>]*)(?:(?:>(?P<val>.*?)</(?P=var)>)|(?:/>))",content)
if len(res)>=1:
attreg="(?P<avr>S+?)(?:(?:=(?P<quote>['"])(?P<avl>.*?)(?P=quote))|(?:=(?P<avl1>.*?)(?:s|$))|(?P<avl2>[s]+)|$)"
if len(res)>1:
return [{i[0]:[{"@attributes":[{j[0]:(j[2] or j[3] or j[4])} for j in re.findall(attreg,i[1].strip())]},{"$values":getdict(i[2])}]} for i in res]
else:
return {res[0]:[{"@attributes":[{j[0]:(j[2] or j[3] or j[4])} for j in re.findall(attreg,res[1].strip())]},{"$values":getdict(res[2])}]}
else:
return content
with open("test.xml","r") as f:
print(getdict(f.read().replace('n','')))
Sample input
<details class="4b" count=1 boy>
<name type="firstname">John</name>
<age>13</age>
<hobby>Coin collection</hobby>
<hobby>Stamp collection</hobby>
<address>
<country>USA</country>
<state>CA</state>
</address>
</details>
<details empty="True"/>
<details/>
<details class="4a" count=2 girl>
<name type="firstname">Samantha</name>
<age>13</age>
<hobby>Fishing</hobby>
<hobby>Chess</hobby>
<address current="no">
<country>Australia</country>
<state>NSW</state>
</address>
</details>
Output (Beautified)
[
{
"details": [
{
"@attributes": [
{
"class": "4b"
},
{
"count": "1"
},
{
"boy": ""
}
]
},
{
"$values": [
{
"name": [
{
"@attributes": [
{
"type": "firstname"
}
]
},
{
"$values": "John"
}
]
},
{
"age": [
{
"@attributes": []
},
{
"$values": "13"
}
]
},
{
"hobby": [
{
"@attributes": []
},
{
"$values": "Coin collection"
}
]
},
{
"hobby": [
{
"@attributes": []
},
{
"$values": "Stamp collection"
}
]
},
{
"address": [
{
"@attributes": []
},
{
"$values": [
{
"country": [
{
"@attributes": []
},
{
"$values": "USA"
}
]
},
{
"state": [
{
"@attributes": []
},
{
"$values": "CA"
}
]
}
]
}
]
}
]
}
]
},
{
"details": [
{
"@attributes": [
{
"empty": "True"
}
]
},
{
"$values": ""
}
]
},
{
"details": [
{
"@attributes": []
},
{
"$values": ""
}
]
},
{
"details": [
{
"@attributes": [
{
"class": "4a"
},
{
"count": "2"
},
{
"girl": ""
}
]
},
{
"$values": [
{
"name": [
{
"@attributes": [
{
"type": "firstname"
}
]
},
{
"$values": "Samantha"
}
]
},
{
"age": [
{
"@attributes": []
},
{
"$values": "13"
}
]
},
{
"hobby": [
{
"@attributes": []
},
{
"$values": "Fishing"
}
]
},
{
"hobby": [
{
"@attributes": []
},
{
"$values": "Chess"
}
]
},
{
"address": [
{
"@attributes": [
{
"current": "no"
}
]
},
{
"$values": [
{
"country": [
{
"@attributes": []
},
{
"$values": "Australia"
}
]
},
{
"state": [
{
"@attributes": []
},
{
"$values": "NSW"
}
]
}
]
}
]
}
]
}
]
}
]
simplified_scrapy: a new lib, I fell in love with it after I used it. I recommend it to you.
from simplified_scrapy import SimplifiedDoc
xml = '''
<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>
'''
doc = SimplifiedDoc(xml)
types = doc.selects('bar>type')
print (len(types)) # 2
print (types.foobar) # ['1', '2']
print (doc.selects('bar>type>foobar()')) # ['1', '2']
Here are more examples. This lib is easy to use.
I am wounder, that no one suggest pandas. Pandas have a function read_xml(), what is perfect for such flat xml structures.
import pandas as pd
xml = """<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>"""
df = pd.read_xml(xml, xpath=".//type")
print(df)
Output:
foobar
0 1
1 2
I have many rows in XML and I’m trying to get instances of a particular node attribute.
<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>
How do I access the values of the attribute foobar? In this example, I want "1" and "2".
You can use BeautifulSoup:
from bs4 import BeautifulSoup
x="""<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>"""
y=BeautifulSoup(x)
>>> y.foo.bar.type["foobar"]
u'1'
>>> y.foo.bar.findAll("type")
[<type foobar="1"></type>, <type foobar="2"></type>]
>>> y.foo.bar.findAll("type")[0]["foobar"]
u'1'
>>> y.foo.bar.findAll("type")[1]["foobar"]
u'2'
I suggest ElementTree. There are other compatible implementations of the same API, such as lxml, and cElementTree in the Python standard library itself; but, in this context, what they chiefly add is even more speed — the ease of programming part depends on the API, which ElementTree defines.
First build an Element instance root from the XML, e.g. with the XML function, or by parsing a file with something like:
import xml.etree.ElementTree as ET
root = ET.parse('thefile.xml').getroot()
Or any of the many other ways shown at ElementTree. Then do something like:
for type_tag in root.findall('bar/type'):
value = type_tag.get('foobar')
print(value)
Output:
1
2
Python has an interface to the expat XML parser.
xml.parsers.expat
It’s a non-validating parser, so bad XML will not be caught. But if you know your file is correct, then this is pretty good, and you’ll probably get the exact info you want and you can discard the rest on the fly.
stringofxml = """<foo>
<bar>
<type arg="value" />
<type arg="value" />
<type arg="value" />
</bar>
<bar>
<type arg="value" />
</bar>
</foo>"""
count = 0
def start(name, attr):
global count
if name == 'type':
count += 1
p = expat.ParserCreate()
p.StartElementHandler = start
p.Parse(stringofxml)
print count # prints 4
minidom is the quickest and pretty straight forward.
XML:
<data>
<items>
<item name="item1"></item>
<item name="item2"></item>
<item name="item3"></item>
<item name="item4"></item>
</items>
</data>
Python:
from xml.dom import minidom
dom = minidom.parse('items.xml')
elements = dom.getElementsByTagName('item')
print(f"There are {len(elements)} items:")
for element in elements:
print(element.attributes['name'].value)
Output:
There are 4 items:
item1
item2
item3
item4
lxml.objectify is really simple.
Taking your sample text:
from lxml import objectify
from collections import defaultdict
count = defaultdict(int)
root = objectify.fromstring(text)
for item in root.bar.type:
count[item.attrib.get("foobar")] += 1
print dict(count)
Output:
{'1': 1, '2': 1}
Here a very simple but effective code using cElementTree.
try:
import cElementTree as ET
except ImportError:
try:
# Python 2.5 need to import a different module
import xml.etree.cElementTree as ET
except ImportError:
exit_err("Failed to import cElementTree from any known place")
def find_in_tree(tree, node):
found = tree.find(node)
if found == None:
print "No %s in file" % node
found = []
return found
# Parse a xml file (specify the path)
def_file = "xml_file_name.xml"
try:
dom = ET.parse(open(def_file, "r"))
root = dom.getroot()
except:
exit_err("Unable to open and parse input definition file: " + def_file)
# Parse to find the child nodes list of node 'myNode'
fwdefs = find_in_tree(root,"myNode")
This is from “python xml parse“.
There are many options out there. cElementTree looks excellent if speed and memory usage are an issue. It has very little overhead compared to simply reading in the file using readlines.
The relevant metrics can be found in the table below, copied from the cElementTree website:
library time space
xml.dom.minidom (Python 2.1) 6.3 s 80000K
gnosis.objectify 2.0 s 22000k
xml.dom.minidom (Python 2.4) 1.4 s 53000k
ElementTree 1.2 1.6 s 14500k
ElementTree 1.2.4/1.3 1.1 s 14500k
cDomlette (C extension) 0.540 s 20500k
PyRXPU (C extension) 0.175 s 10850k
libxml2 (C extension) 0.098 s 16000k
readlines (read as utf-8) 0.093 s 8850k
cElementTree (C extension) --> 0.047 s 4900K <--
readlines (read as ascii) 0.032 s 5050k
As pointed out by @jfs, cElementTree comes bundled with Python:
- Python 2:
from xml.etree import cElementTree as ElementTree. - Python 3:
from xml.etree import ElementTree(the accelerated C version is used automatically).
I suggest xmltodict for simplicity.
It parses your XML to an OrderedDict;
>>> e = '<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo> '
>>> import xmltodict
>>> result = xmltodict.parse(e)
>>> result
OrderedDict([(u'foo', OrderedDict([(u'bar', OrderedDict([(u'type', [OrderedDict([(u'@foobar', u'1')]), OrderedDict([(u'@foobar', u'2')])])]))]))])
>>> result['foo']
OrderedDict([(u'bar', OrderedDict([(u'type', [OrderedDict([(u'@foobar', u'1')]), OrderedDict([(u'@foobar', u'2')])])]))])
>>> result['foo']['bar']
OrderedDict([(u'type', [OrderedDict([(u'@foobar', u'1')]), OrderedDict([(u'@foobar', u'2')])])])
import xml.etree.ElementTree as ET
data = '''<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>'''
tree = ET.fromstring(data)
lst = tree.findall('bar/type')
for item in lst:
print item.get('foobar')
This will print the value of the foobar attribute.
Just to add another possibility, you can use untangle, as it is a simple xml-to-python-object library. Here you have an example:
Installation:
pip install untangle
Usage:
Your XML file (a little bit changed):
<foo>
<bar name="bar_name">
<type foobar="1"/>
</bar>
</foo>
Accessing the attributes with untangle:
import untangle
obj = untangle.parse('/path_to_xml_file/file.xml')
print obj.foo.bar['name']
print obj.foo.bar.type['foobar']
The output will be:
bar_name
1
More information about untangle can be found in “untangle“.
Also, if you are curious, you can find a list of tools for working with XML and Python in “Python and XML“. You will also see that the most common ones were mentioned by previous answers.
I might suggest declxml.
Full disclosure: I wrote this library because I was looking for a way to convert between XML and Python data structures without needing to write dozens of lines of imperative parsing/serialization code with ElementTree.
With declxml, you use processors to declaratively define the structure of your XML document and how to map between XML and Python data structures. Processors are used to for both serialization and parsing as well as for a basic level of validation.
Parsing into Python data structures is straightforward:
import declxml as xml
xml_string = """
<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>
"""
processor = xml.dictionary('foo', [
xml.dictionary('bar', [
xml.array(xml.integer('type', attribute='foobar'))
])
])
xml.parse_from_string(processor, xml_string)
Which produces the output:
{'bar': {'foobar': [1, 2]}}
You can also use the same processor to serialize data to XML
data = {'bar': {
'foobar': [7, 3, 21, 16, 11]
}}
xml.serialize_to_string(processor, data, indent=' ')
Which produces the following output
<?xml version="1.0" ?>
<foo>
<bar>
<type foobar="7"/>
<type foobar="3"/>
<type foobar="21"/>
<type foobar="16"/>
<type foobar="11"/>
</bar>
</foo>
If you want to work with objects instead of dictionaries, you can define processors to transform data to and from objects as well.
import declxml as xml
class Bar:
def __init__(self):
self.foobars = []
def __repr__(self):
return 'Bar(foobars={})'.format(self.foobars)
xml_string = """
<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>
"""
processor = xml.dictionary('foo', [
xml.user_object('bar', Bar, [
xml.array(xml.integer('type', attribute='foobar'), alias='foobars')
])
])
xml.parse_from_string(processor, xml_string)
Which produces the following output
{'bar': Bar(foobars=[1, 2])}
XML:
<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>
Python code:
import xml.etree.cElementTree as ET
tree = ET.parse("foo.xml")
root = tree.getroot()
root_tag = root.tag
print(root_tag)
for form in root.findall("./bar/type"):
x=(form.attrib)
z=list(x)
for i in z:
print(x[i])
Output:
foo
1
2
xml.etree.ElementTree vs. lxml
These are some pros of the two most used libraries I would have benefit to know before choosing between them.
xml.etree.ElementTree:
- From the standard library: no needs of installing any module
lxml
- Easily write XML declaration: for instance do you need to add
standalone="no"? - Pretty printing: you can have a nice indented XML without extra code.
- Objectify functionality: It allows you to use XML as if you were dealing with a normal Python object hierarchy
.node. sourcelineallows to easily get the line of the XML element you are using.- you can use also a built-in XSD schema checker.
There’s no need to use a lib specific API if you use python-benedict. Just initialize a new instance from your XML and manage it easily since it is a dict subclass.
Installation is easy: pip install python-benedict
from benedict import benedict as bdict
# data-source can be an url, a filepath or data-string (as in this example)
data_source = """
<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>"""
data = bdict.from_xml(data_source)
t_list = data['foo.bar'] # yes, keypath supported
for t in t_list:
print(t['@foobar'])
It supports and normalizes I/O operations with many formats: Base64, CSV, JSON, TOML, XML, YAML and query-string.
It is well tested and open-source on GitHub. Disclosure: I am the author.
#If the xml is in the form of a string as shown below then
from lxml import etree, objectify
'''sample xml as a string with a name space {http:// encoding="UTF-8"?>rn<pa:Process >rnt<pa:firsttag>SAMPLE</pa:firsttag></pa:Process>rn' # this is a sample xml which is a string
print('************message coversion and parsing starts*************')
message=message.decode('utf-8')
message=message.replace('<?xml version="1.0" encoding="UTF-8"?>rn','') #replace is used to remove unwanted strings from the 'message'
message=message.replace('pa:Process>rn','pa:Process>')
print (message)
print ('******Parsing starts*************')
parser = etree.XMLParser(remove_blank_text=True) #the name space is removed here
root = etree.fromstring(message, parser) #parsing of xml happens here
print ('******Parsing completed************')
dict={}
for child in root: # parsed xml is iterated using a for loop and values are stored in a dictionary
print(child.tag,child.text)
print('****Derving from xml tree*****')
if child.tag =="{http://>
<pa:firsttag>SAMPLE</pa:firsttag></pa:Process>
******Parsing starts*************
******Parsing completed************
{http://>
<pa:firsttag>SAMPLE</pa:firsttag>
</pa:Process>
you may try the following code
from lxml import etree, objectify
metadata = 'C:\Users\PROCS.xml' # this is sample xml file the contents are shown above
parser = etree.XMLParser(remove_blank_text=True) # this line removes the name space from the xml in this sample the name space is --> http://sssss
tree = etree.parse(metadata, parser) # this line parses the xml file which is PROCS.xml
root = tree.getroot() # we get the root of xml which is process and iterate using a for loop
for elem in root.getiterator():
if not hasattr(elem.tag, 'find'): continue # (1)
i = elem.tag.find('}')
if i >= 0:
elem.tag = elem.tag[i+1:]
dict={} # a python dictionary is declared
for elem in tree.iter(): #iterating through the xml tree using a for loop
if elem.tag =="firsttag": # if the tag name matches the name that is equated then the text in the tag is stored into the dictionary
dict["FIRST_TAG"]=str(elem.text)
print(dict)
Output would be
{'FIRST_TAG': 'SAMPLE'}
If you don’t want to use any external libraries or 3rd party tools, Please try below code.
- This will parse
xmlinto pythondictionary - This will parse xml attrbutes as well
- This will also parse empty tags like
<tag/>and tags with only attributes like<tag var=val/>
Code
import re
def getdict(content):
res=re.findall("<(?P<var>S*)(?P<attr>[^/>]*)(?:(?:>(?P<val>.*?)</(?P=var)>)|(?:/>))",content)
if len(res)>=1:
attreg="(?P<avr>S+?)(?:(?:=(?P<quote>['"])(?P<avl>.*?)(?P=quote))|(?:=(?P<avl1>.*?)(?:s|$))|(?P<avl2>[s]+)|$)"
if len(res)>1:
return [{i[0]:[{"@attributes":[{j[0]:(j[2] or j[3] or j[4])} for j in re.findall(attreg,i[1].strip())]},{"$values":getdict(i[2])}]} for i in res]
else:
return {res[0]:[{"@attributes":[{j[0]:(j[2] or j[3] or j[4])} for j in re.findall(attreg,res[1].strip())]},{"$values":getdict(res[2])}]}
else:
return content
with open("test.xml","r") as f:
print(getdict(f.read().replace('n','')))
Sample input
<details class="4b" count=1 boy>
<name type="firstname">John</name>
<age>13</age>
<hobby>Coin collection</hobby>
<hobby>Stamp collection</hobby>
<address>
<country>USA</country>
<state>CA</state>
</address>
</details>
<details empty="True"/>
<details/>
<details class="4a" count=2 girl>
<name type="firstname">Samantha</name>
<age>13</age>
<hobby>Fishing</hobby>
<hobby>Chess</hobby>
<address current="no">
<country>Australia</country>
<state>NSW</state>
</address>
</details>
Output (Beautified)
[
{
"details": [
{
"@attributes": [
{
"class": "4b"
},
{
"count": "1"
},
{
"boy": ""
}
]
},
{
"$values": [
{
"name": [
{
"@attributes": [
{
"type": "firstname"
}
]
},
{
"$values": "John"
}
]
},
{
"age": [
{
"@attributes": []
},
{
"$values": "13"
}
]
},
{
"hobby": [
{
"@attributes": []
},
{
"$values": "Coin collection"
}
]
},
{
"hobby": [
{
"@attributes": []
},
{
"$values": "Stamp collection"
}
]
},
{
"address": [
{
"@attributes": []
},
{
"$values": [
{
"country": [
{
"@attributes": []
},
{
"$values": "USA"
}
]
},
{
"state": [
{
"@attributes": []
},
{
"$values": "CA"
}
]
}
]
}
]
}
]
}
]
},
{
"details": [
{
"@attributes": [
{
"empty": "True"
}
]
},
{
"$values": ""
}
]
},
{
"details": [
{
"@attributes": []
},
{
"$values": ""
}
]
},
{
"details": [
{
"@attributes": [
{
"class": "4a"
},
{
"count": "2"
},
{
"girl": ""
}
]
},
{
"$values": [
{
"name": [
{
"@attributes": [
{
"type": "firstname"
}
]
},
{
"$values": "Samantha"
}
]
},
{
"age": [
{
"@attributes": []
},
{
"$values": "13"
}
]
},
{
"hobby": [
{
"@attributes": []
},
{
"$values": "Fishing"
}
]
},
{
"hobby": [
{
"@attributes": []
},
{
"$values": "Chess"
}
]
},
{
"address": [
{
"@attributes": [
{
"current": "no"
}
]
},
{
"$values": [
{
"country": [
{
"@attributes": []
},
{
"$values": "Australia"
}
]
},
{
"state": [
{
"@attributes": []
},
{
"$values": "NSW"
}
]
}
]
}
]
}
]
}
]
}
]
simplified_scrapy: a new lib, I fell in love with it after I used it. I recommend it to you.
from simplified_scrapy import SimplifiedDoc
xml = '''
<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>
'''
doc = SimplifiedDoc(xml)
types = doc.selects('bar>type')
print (len(types)) # 2
print (types.foobar) # ['1', '2']
print (doc.selects('bar>type>foobar()')) # ['1', '2']
Here are more examples. This lib is easy to use.
I am wounder, that no one suggest pandas. Pandas have a function read_xml(), what is perfect for such flat xml structures.
import pandas as pd
xml = """<foo>
<bar>
<type foobar="1"/>
<type foobar="2"/>
</bar>
</foo>"""
df = pd.read_xml(xml, xpath=".//type")
print(df)
Output:
foobar
0 1
1 2