Extract and Parse ODF Files with Python

Use Python to demystify Open Document Format files.

A SAX program requires a class derived from ContentHandler and overriding functions to handle the start, middle and end of each node. The tagHandler class shown in Listing 4 is used primarily to track the start of each node and ignores the contents. Use the names found in the listing as keys in a dictionary. Then, use the keys() method to list the names into a list that you also can sort(). I use this technique quite often to get a sorting of unique members quickly, because the hashing functions in Python dictionaries are very fast. Here's the output from the program:


I sorted the list of keys and printed only the types of tags found. You will have many tags, and the order of the listed tags is not the way they are found in the XML file. The tag you most likely will be concerned with is <text:p>, which has the text in each paragraph. In this example, I want to search for keywords in the text for one or more paragraphs in a document.

Although I can use the SAX version of the program to search for the text, I use the DOM libraries, because the code will be a little easier to write (and subsequently, easier to maintain), and I promised an example of this earlier.

The xml.dom and xml.dom.minidom packages in Python allow for reading in XML files as DOM trees. Both packages come with a standard Python installation. Use the minidom package as it has a smaller footprint and is easier to use than the dom package. The minidom package is sufficient for almost all my XML work, and I have never really needed the heavyweight xml.dom package. See Resources for more information.

Use the minidom packages to read the elements of an XML file into a tree-like structure. The nodes of the tree are objects based on the Node class in Python. The output from Listing 4 provides the names of nodes.

Up to this point, you have been using simple programs to list and extract data from the archive. Now, the next example runs a search operation on the file you've just read in. Look at the program in Listing 5.

The program is designed to work as a class that reads and searches for text in an ODF file. Declaring a class for the ODF reader helps in organizing the code for searching text within a node. The showManifest() member function simply tells me what files exist in the ODF file. In this particular program, I collect all the text as a list of paragraphs, and then I search for the keywords passed in from the command line. If the searched word matches, the paragraph is printed out.

The text found in each <text:p> is Unicode text. You have to convert this to normal text in order to print correctly and/or use in a widget. The encode() command translates the Unicode to a printable string.

Unicode provides a unique number for every character, regardless of the platform, program and language being used. The ability to work seamlessly with the same text across multiple platforms is a great feature for Unicode-enabled applications. Such features do come with a price for some legacy operations. Each Unicode character can have flags as bits set for special printing and so on, which causes a normal print statement to interpret each character as a number instead of text. In Python, the encode() member function of a Unicode string returns a printable version of the string. Here is an example code snippet for that:

def findIt(self,name):
    for s in self.text_in_paras:
        if name in s:
            print s.encode('utf-8')

The code in Listing 5 is not limited to an ODT file. You can modify the code presented here to work with spreadsheet files with an .ods file. Run the program in Listing 3 to get the contents.xml file out, and then run the second program (shown in Listing 4) to list the types of nodes. Below is a sample .ods file; note that this file also has paragraphs in addition to the table tags:


Use the program in Listing 5 to extract and search text from paragraphs as before. A simple modification of changing the text:p to table:table-cell searches for text within cells instead of paragraphs.

To summarize, an ODF file is a zipped archive of several XML files. One of these files contains contents in known tags. Each type of ODF file can have different tags based on stored information. By using introspection and the XML parsing capabilities in Python, you can list the types of nodes in a file and read them into a tree structure. Once read, you can extract data only from those nodes in the tree that are of interest to you.



Comment viewing options


File is not a zip file

hypertex's picture


File "./odt.py", line 13, in __init__
self.m_odf = zipfile.ZipFile(filename)
raise BadZipfile, "File is not a zip file"
zipfile.BadZipfile: File is not a zip file

and yet . . .

>>> odfname = ('bill_of_rights.odt')
>>> zipfile.is_zipfile(odfname)



hypertex's picture

the __main__ block should have:

filename = sys.argv[1]
phrase = sys.argv[2]


LPOD Project

Anonymous's picture


Fail? What fail?

Anonymous's picture

(Windows NT/2000/XP/Vista/7)


Anonymous's picture

for more information.

however, very good tutorial doh! ;)



Nichoals's picture


uçak bileti

uçak bileti's picture


Plug-in For MS Office

W^L+'s picture

