Python Script to Extract Call Record from Cisco CDR

There is a python script written by Steve Campbell which extracts Call Detailed Record (CDR) for an extension using Python Script.  Extraction of the record is quite simple and faster. The only drawback i see at this time is it can run the script against one extension only at a time which means you can search only one extension number in the whole CDR Report.
 

The script will pull out Data/Time, Duration, Calling Number and Called Number from raw CDR Report.

Procedure:

• To start using the Python Script, you need to have Python installed in your PC. You can download python from official website (“https://www.python.org/downloads/“).
• Once the software is downloaded, you need to install the application in your PC.
• Download Python Script from https://github.com/sdcampbell/PyCDR site and copy the files from the folder PyCDR-master to  Python Directory.
  To Find Python Directory, follow either of the below steps:
  OPTION 1
  “C:\Users\USERNAME\AppData\Local\Programs\Python\Python36-32\”(Replace USERNAME with your actual Username of Windows Machine)
  OPTION 2
  Click on Start Menu
  Type Python in the Search Program and File box
  
  Right Click on Python 3.6 (32 bit) or (64 bit) and click on Open file location
  A window will open; click on the address bar and copy the location from the address bar
• Also download CDR Raw Data from Cisco Unified Communications Manager and copy it in the python directory as shown in the above step
• Now open Command Prompt and execute the command
  

  C:\>    CD C:\Users\USERNAME\AppData\Local\Programs\Python\Python36-32\
  OR
  C:\> CD(Paste the location from the address bar as shown in the option 2)
  
  ——————————————————–
  C:\….\Python36-32>   python.exe PyCDR.py “CDR Raw Report.txt” “Output.csv” 10000             >>> Execute this command
  

  Once the command is executed, you will see a file “Output.csv” in the same folder that would have the CDR Records inside the fil

Sample Output

Hope this helps!

Published by Team UC Collabing