>> homepage 

Desktop

 

Dig

   
   

Note that this script is currently not maintained, it may fail to work with current versions of PyQt/PyKDE.

DesktopDig is a search engine that is optimized for your personal files. It has a graphical user interface for KDE but it can also be used on the command line or as a CGI script. It has been tested under Linux, let me know if the command line version works on Windows, too (the GUI isn't supposed to work on Windows).

Download: DesktopDig 0.1 (.tar.gz, 36KB)

Installation: Install the required software listed below, then download and unpack DesktopDig. Start desktopdig.py for the graphical user interface or use index.py and search.py on the command line.

Requirements:

  • externer Link zu PythonPython 2.2 (older versions might work)
  • externer Link zu eGenix.com mx BASE Extensions 2.1.0b5eGenix.com mx BASE Extensions 2.1.0b5 (externer Link zu src RPMsrc RPM, externer Link zu .tar.gz.tar.gz, )
    If you get the message that the mx.BeeBase.BeeDict package cannot be found after you have installed the RPM, you should try to build the source RPM with rpm --rebuild egenix-mx-bse-2.1.0b5-py2.2_1.src.rpm and install the generated RPM.
    If you cannot install the eGenix.com extension as root you can install it like this:
    ./setup.py install --prefix=/home/username/egenix
    Then add /home/username/egenix/lib/python2.2/site-packages/ to the path in Config.py.
  • If you want to use the graphical user interface: I suggest to download the RPMs for PyQt, SIP (required by PyQt) and PyKDE from externer Link zu SourceforgeSourceforge.

License: DesktopDig is freely available under the GPL.

Screenshots

Screenshot: searching Screenshot: indexing files

Features in comparison to externer Link zu Perlfect SearchPerlfect Search:

DesktopDig 0.1 Perlfect Search 3.30
Online Demo externer Link zu KDE DocumentationKDE Documentation externer Link zu Perlfect Search mailing list archivePerlfect Search mailing list archive
Incremental indexing Yes No, complete re-indexing necessary
Index files via http No Yes
Unicode support Yes (all encodings supported by Python, e.g. UTF-8) No
Phrase search support Yes Not by default (patch necessary)
+/- syntax for keyword forcing/exclusion No Yes
Support for several independant indexes Yes No
Supported file types
  • HTML
  • TXT
  • PDF (requires pdftotext)
  • MS-Word (requires externer Link zu AntiwordAntiword)
  • KWord >=1.2
  • StarOffice >= 6.0, OpenOffice.org
  • HTML
  • TXT
  • PDF (requires pdftotext)

The following values were measured on a Athlon 900 with 256MB RAM, with 460 HTML files whose average file size was 8 kb. The search was a one-word query which resulted in 18 matches. This is only an example, other document collections will give different results:

DesktopDig 0.1 Perlfect Search 3.30
Index speed 15 documents/second 15 documents/second (up to 45 documents/second if you accept much more memory usage)
RAM usage during indexing 10 MB 7 MB
Index size, compared to size of all documents 50-100% 10-20%
Search speed 0.1 seconds 0.1 seconds
 
 
Last updated: 2003-02-07
URL: http://www.danielnaber.de/desktopdig/