The result of the analysis is made up of a Struct, i.e. an associative array similar to Java’s HashMap or Perl’s Hash, that maps block names to blocks.
Each block is a rectangular data container made up of an Array of Arrays of Strings. The outer Array contains the rows while the inner ones will hold column values.
In the response, you get all the requested blocks as of parameter #9 of the call, plus a block named response. The block response will contain:
All other blocks will follow the convention that the inner Array #0 (the first row) will contain table headers, while actual data will be present from row 1 onwards. The table headers are the same you can see in the on-screen representation.
The following Python code will run a simple dump of all the results in a readable form:
for t in res.keys():
print "===== Block " + t + ": ========"
for r in range( len(res[t]) ):
for c in range( len( res[t][r] )):
print res[t][r][c] ,
print "\t" ,
printThe output will look like the following one:
===== Block result: ======== Status OK Description Time elapsed (ms) 3008 QM Version 1.3.1 ===== Block KoDO.DiscCauses: ======== Cause N. Calls ... Caller abandon 46 83.6% Agent dump 1 1.8% Timeout (voicemail) 8 14.5%
As you can see, the block KoDO.DiscCauses has one full line of header on its first row.