#Tableau prep install install#
#Tableau prep install code#

#Tableau prep install install#

Modified on: Wed, 31 Jul, 2019 at 5:13 AMįollow the Step-by-Step Installation Guide for BI Connector Desktop Edition to install and configure BI Connector on your PC.įollow these few simple mantras to quickly become an Expert in the report creation for OBIEE data using Tableau and BI Connector. Solution home Tableau Prep + OBIEE User Guides Connect Tableau Prep Builder to OBIEE Reports - BI connector Desktop Edition - Step-by-Step User Guide If you need further info just reach out to me on LinkedIn or Twitter.

#Tableau prep install code#

Using Tableau Server Client you need only few lines of Python code but, obviously, you can use REST APIs with any other programming language. Otherwise, in more limited contexts of use or to start using Tableau Prep on the web, you can create a script to run and monitor your flows. If you extensively use Tableau Prep to manage data preparation processes in your organization, the adoption of Tableau Data Management Add-on is recommended to orchestrate your flows. Run Flow “flow demo” Now Job finished with status: Success Run Flow “flow demo 2” Now Job finished with status: SuccessĪt this point, you should have everything you need to run and monitor programmatically your Tableau Prep flows execution. # job completion status types job_status = # loop until job is in pending/in progress status polling2.poll( lambda: _by_id(job.id).finish_code != -1, step=30, poll_forever= True) # print the completion status print( 'Job finished with status: ' + job_status) The polling execution will ends with finish_code different from -1. finish_code indicates the current status of the job and may assume the value: -1 for pending/in progress, 0 for success, 1 for error or 2 for cancelled.

In this example we use the Python polling2 utility, to test every 30 seconds ( step=30) the finish_code attribute of the JobItem instance returned by the method _by_id(job.id). You can monitor every job execution using, for example, a polling utility to wait for a function to return when the specified condition is met. To execute every flow in list, create a loop and use the () method (this method maps the Rest API endpoint Run Flow Now ) for flow in all_flow_items: print( 'Run Flow', flow.name, 'Now') # run the flow and get the JobItem job = (flow) Rest API version: 3.10 There are 2 flows on site:, ] My Tableau Server has two demo flows in this site, the result will be: format(pagination_item.total_available)) print( for flow in all_flow_items]) Use the _in()method to authenticate, and the () method to get the flow names and ids list (this method maps the Rest API endpoint Query Flows for a site ) with _in(tableau_auth): all_flow_items, pagination_item = () print( 'There are flows on site:'. tableau_auth = TSC.PersonalAccessTokenAuth( 'TSC', 'oe4S0kYrQfaVAatBFupHVg=:DmCHTwgrTqhkiWnU0yW2EURhNBhZmKkE', 'DemoSite') For the default site on Tableau Server you can use an empty string '' (with single quotes, no spaces). Initialize a PersonalAccessTokenAuth instance using the Token Name, the Token Secret and the site_id you want to connect, where the site_id is the portion of the URL that follows the /site/ string. import tableauserverclient as TSC server = TSC.Server( '',use_server_version= True) print( 'Rest API version:', server.version) Remember to use the attribute use_server_version=Trueto make sure to use the latest version of the REST API supported by the instance of Tableau Server or Tableau Online you are connecting to Flow methods are supported with API version 3.3 and later). Using the tableauserverclient, create a connection to your Tableau Server. Create a sample Python App to refresh the flow