Niklas Saers' blog

In Scott Larsons blogpost referenced in my last post he gives a short but important note: his favourite MDX resource. And I agree: a 62 article series in learning MDX. Since I’ve worked with SQL “all my life” I’ve not bothered to much with MDX, but with this series I’m really looking forward to learning it better. To do the tutorials you’ll need the free MS-SQL 2000 samples (that unfortunately aren’t bundled with neither MS-SQL 2005 nor MS-SQL 2008). You can download them from here. I should note that while it compiles fine with VB6, using it with Visual Studio 2005 left me with a pretty large debugging job. But don’t worry, the data sources are included and that really is all you need to work through the tutorials. For the interface, you’ve got BIDS

One of my main gripes with Microsoft SSIS is that there is no way to reuse logic. In my data integration task I needed to do the same lookup and translation tasks (typically convert to upper case, replace ” with ‘N/A’, look up column in side table and use the IDs from that table instead) many times, in my case when importing data from an Axapta database. CozyRoc got back to me and told me that they have released an SSIS component that includes new components for reusability of code and flows. Being a coder I had given up on SSIS and rewritten my work in C#/SQL, but next time I’m very much looking forward to using it.

Not quite happy with any of the programs I found to identify iTunes duplicates, I spent an hour making my own (beats tracking down duplicates. ) I thought I’d share it with you. It’s my first attempt at using OS X’ ScriptingBridge and written in Python. I have no clue if it runs out of the box, I suppose you should have Developer Tools installed. It’s not the fastest beast either, and Python and iTunes both use 50% CPU. But it gets the job done. If you wonder why I give so many parameters to the track class I should say that I plan on reusing it to do some more iTunes housekeeping. The script will mark all the duplicates with one star. Then I can round them up and delete them afterwards.

import struct
from ScriptingBridge import *

class Track:
   def __init__(self, name, album, artist, size, length, track, path):
     self.name= self.str(name)
     self.album= self.str(album)
     self.artist= self.str(artist)
     self.size = size
     self.length= self.str(length)
     self.track = track
     self.path= self.str(path)

   def str(self, s):
     try:
       return s.encode('utf-8')
     except:
       return "N/A"

   def equals(self, t):
     test = t.name == self.name
     test = test and t.album == self.album
     test = test and t.artist == self.artist
     test = test and t.size == self.size
     test = test and t.length == self.length
     test = test and t.track == self.track
     return test

   def __eq__(self, t):
     return self.equals(t)

iTunes = SBApplication.applicationWithBundleIdentifier_("com.apple.iTunes")
lib = iTunes.sources()[0].playlists()[0]
tracks = lib.tracks()
filetracks = lib.elementArrayWithCode_(struct.unpack('>L', 'cFlT')[0])

Tracks = []
Duplicates = []
duplicates = []
for track in filetracks:
  t = Track(track.name(), track.album(), track.artist(), track.size(), track.time(), track.trackNumber(),track.location())
  if(Tracks.__contains__(t)):
    Duplicates.append(t)
    duplicates.append(track)
  else:
    Tracks.append(t)

print len(duplicates)

# Deal with duplicates
for track in duplicates:
   track.setRating_(20)