#Create0 debatiendo

@Thea Baldewein​ 

Hi, as you cannot share your code, use tableau server client:

https://tableau.github.io/server-client-python/

import tableauserverclient as TSC
import csv
from datetime import datetime,timezone
 
# server admin creds
HOST = "https://prod-useast-b.online.tableau.com/"
TOKEN_NAME = "Python"
TOKEN_VALUE = "b5iXybhg==:lc65QDPxx6M"
CONTENT_URL = "yoursitename"
 
tableau_auth = TSC.PersonalAccessTokenAuth(TOKEN_NAME, TOKEN_VALUE, site_id=CONTENT_URL)
server = TSC.Server(HOST, use_server_version=True)
 
#Create the csv file and open it in write mode
f = open('usuarios.csv', 'w', encoding='UTF8', newline='')
 
#delimiter with semicolon if need change to comma, and write header
writer = csv.writer(f, delimiter=";")
header = ['User','Site Role','Last Login','Difference']
writer.writerow(header)
 
today_date = datetime.now(timezone.utc)
 
with server.auth.sign_in(tableau_auth):
    for user in TSC.Pager(server.users):
        if user.last_login is None:
            row=[user.name,user.site_role,"NA","NA"]
            print(user.name, user.site_role, "NA", "NA")
            #write the row
            writer.writerow(row)
        else:
            last_login = user.last_login
            difference = (today_date - last_login).total_seconds() / (60 * 60 * 24) 
            row=[user.name,user.site_role,user.last_login,difference]
            print(user.name, user.site_role, user.last_login, difference)
            writer.writerow(row)
#Close file connection and sign out
f.close()
server.auth.sign_out()

If this post resolves the question, would you be so kind to "Select as Best"?. This will help other users find the same answer/resolution and help community keep track of answered questions. Thank you.

Regards,

Diego Martinez

Tableau Visionary and Forums Ambassador

Hi Justin,

This might gain more attention in the Server Administration area.

I do not believe there is a 'supported' way to have write access to the PostGres Repository on Tableau Server. You are able to have read access though, build a query against it, and then write a tabcmd command to remove the users.

*There is a yml file with the superuser tblwgadmin account which is explained here but it is not supported: null

You could export the list though from Tableau PostGres to a csv and use the 'tabcmd deleteusers "user.csv"  ' which is referenced here: tabcmd Commands

One other note, you will not be able to remove users that currently are listed as owners so you would need to get a list of users that are attached to content on the server. You can also get this information from the PostGres repository though. If you run the deleteusers command and a user still has content it will leave them as 'unlicensed'

If you haven't enabled access to the PostGres Repository, here is a link:Collect Data with the Tableau Server Repository

Andrew

Hello!

The problem is, that temporary tables are only allowed to be in a temporary schema. However, your code tries to place them in the non-temporary "Extract" schema.

I would suggest you still use temporary tables but instead of:

TableName("Extract", "sales")

you just use:

TableName("sales")

Then, the temporary table is automatically placed in the temp-schema.

Also, you might want to take a look at pantab, which is a python library written by tableau users for easy and fast pandas <-> hyper conversions.

It uses a bunch of tricks under the hood which should make it quite a bit faster than the usual approach you took in your program.

Let me know if you have further questions.

Cheers,

Jonas

OK, explanations for the last two views and the dashboard.

Highway Spending per Capita for Selected Areas

This builds on a lot of the things we did in the previous view, but has one extra twist which I'll explain first before the detailed instructions.

The table calculation for the field [Amount Spent per Capita] uses the expression:

[Selected Amount Spent] / [Selected Population]

where both of those are themselves table calculation, but with different addressing: [Selected Amount Spent] is calculated over all roadnames whereas [Selected Population] is calculated over all dissemination blocks. This means we can't just use the 'Compute Using' menu option for [Amount Spent per Capita] to set the addressing, because that only allows us to pick one field, so only one of the two component calculations would be correct. Instead we need to use the 'Edit Table Calculation' option which gives the option to set the addressing individually for each component calculation:

The dialog has a drop-down list allowing you to choose each component calculation in turn.

At first sight you would think that for 'Selected Population' you should just check [dbuid] (meaning the calculation would be performed over all [dbuid] values for each combination of [Highway Roadname] and [Population Center]) and for [Selected Amount Spent] you should check [Highway Roadname] (meaning the calculation would be performed over all [Highway Roadname] values for each combination of [dbuid] and [Population Center]). But that results in [Amount Spent per Capita] being null. This screenshot of the 'show data' window hopefully explain what is happening here: [Selected Population] is always null for highway rows and [Selected Amount Spent] is null for all dissemination block rows - so [Amount Spent per Capita] is always null (because one or other of the two fields used to calculate it is always null).

So actually what we need to do is perform both calculations over all values of both [Highway Roadname] and [dbuid] for each [Population Center], by setting both like this:

That means that both components calculations and hence the [Amount Spent per Capita] are evaluated correctly for every row, as shown here:

We will again want to filter the view down to a single row, using the [First Row?] field, as we did previously.

Step by step instructions.

1) Create a new sheet and call it 'Highway Spending per Capita for Selected Areas'.

2) Drag [Population Center] from datasource 'Pop Centre Dissemination Block Highway' onto the Rows shelf.

3) Switch to sheet 'Dissemination Blocks and Highways around Population Centers' and for both the population and population center filters select 'Apply to Worksheets' and select 'Highway Spending per Capita for Selected Areas' to apply those filters to our new sheet.

4) Switch back to 'Highway Spending per Capita for Selected Areas' and drag [dbuid] and [Highway Roadname] onto the detail shelf.

5) Drag [Amount Spent per Capita] onto the Columns shelf, and set the addressing using the 'Edit Table Calculation' option from the drop-down menu on the field. Select both [dbuid] and [Highway Roadname] for each of the two component calculated fields, as per the explanation above.

6) Drag [Is First?] onto the filter shelf and select 'True' when prompted (the reason it only offers 'True' is because with the default addressing there is only one row per partition - so that row is always the first row in its partition). Now use 'Edit Table Calculation' to set the addressing to use both [dbuid] and [Highway Roadname] as above. Finally select 'True' when offered 'True' or 'False' to filter to just the first row.

7) From the Label shelf select 'Show mark labels'.

8) Optionally format the [Amount Spent per Capita] field and axis to use currency format.

Your view should now look like this for Saskatoon.

Highway Spending by Population Center and Route

Last sheet. This one is very straightforward, no new techniques or concepts, so just brief step-by-step instructions should do.

1) Create a new sheet and call it 'Highway Spending by Population Center and Route'.

2) Drag [Population Center] from datasource 'Pop Centre Dissemination Block Highway' onto the Rows shelf.

3) Switch to sheet 'Dissemination Blocks and Highways around Population Centers' and for both the population and population center filters select 'Apply to Worksheets' and select 'Highway Spending by Population Center and Route' to apply those filters to our new sheet.

4) Switch back to 'Highway Spending by Population Center and Route', drag [Highway Roadname] onto the Detail shelf and [Highway Route Number1] onto the Rows shelf.

5) Drag [Selected Amount Spent] onto the Columns shelf, and set the addressing using the 'Compute Using' option from the drop-down menu on the field. Select [Highway Roadname].

6) Drag [Is First?] onto the filter shelf and select 'True' when prompted. Now use the 'Compute Using' menu option to set the addressing to use [Highway Roadname] as above. Finally select 'True' when offered 'True' or 'False'.

7) From the Label shelf select 'Show mark labels'.

8) Optionally format the [Selected Amount Spent] field and axis to use currency format.

Your view should now look like this for Saskatoon.

One thing that is worth pointing out is that the calculated field [Selected Amount Spent] is the same field as we used on sheet 'Population and Highway Spending for Selected Areas', but gives a different answer this time because we have the route number dimension as well as population center on this sheet, so the result is broken down further.

Finally create a dashboard, drag all the sheets on and arrange as you see fit.

The filters should all just work on all sheets because of the way that we applied the filters from the first sheet to all of the other sheets.

You will probably want to edit the titles and alias some of the entries in the legends and do various other bits of tidy up. Here's what mine looks like:

For extra bonus points you can do things like adding highlight actions to the dashboard so that you can click on route numbers in the bar chart and highlight the routes on the map:

I noticed that you had created extracts for both the census CSV file and the expenditure spreadsheet. That is definitely a good thing to do - after seeing that I've done it for mine and although I haven't timed it the workbook seems quicker - it is certainly really responsive. One thing you could do is recreate the census extract with a filter on province, so that you only include dissemination blocks for Saskatchewan. I don't think that will make a measurable difference to performance, but it saves a bit of space - and it's a good habit to get into, I think - no point in carrying around lots of excess data that is unrelated to what you are doing.

So that's all there is to it.

It has certainly turned into a much bigger exercise than I was expecting and we have covered an awful lot of ground and lots of different Tableau concepts and techniques. It's actually been really useful for me - I've been right out of the Tableau world for a long time so it's been a great chance to refresh my knowledge and get up to date on all the changes that have been happening since I was last using it regularly.

As I say, I'm fully expecting some more questions (including working through the one you are stuck on at the moment). I'll get to those as and when I'm around.

Good luck!

Hey everyone,

Enable Ask Data for Data Sources - Tableau

This throttle is limited to the data source. However, we are actively working on the broader enable/disable settings (at the server and site level). I will share an update in a few weeks but we are targeting 2019.4 with this added capability.

Thanks,

Ruhaab Markas

Sr. Product Manager - Ask Data

@Wes Patton​ 

Hi, I think you may Tableau Server Client to generate a PDF (I currently don't have a PPT code).

import tableauserverclient as TSC
import os
import numpy as np
from io import BytesIO
import PyPDF2
 
# source information
SOURCE_SERVER_NAME = "https://www.yourserver.com"
SOURCE_SITE_NAME = 'yoursite'
SOURCE_WORKBOOK_NAME = "RestApi2"
PROJECT_NAME = "RestApi"
 
# destination info
TMPDIR = "PDF Merged"
PREVIEW_FOLDER_LOCATION = os.getcwd() + "/" + TMPDIR + "/"
PREVIEW_FILE_EXTENSION = ".pdf"
 
⌗Login info
TOKEN_NAME = 'Test'
TOKEN = 'neOMFA+Tyvw==:p48kScoLBZQILB'
#Each element in the filter array will generate a PDF. in the element, separate with comma the values e.g. 'Material de oficina,Mobiliario'. if you want to filter several values at the same time. This will generate two PDFs, one with Material de oficina and Mobiliario, and other, filtered with Tecnologia
FILTERS = np.array(['Material de oficina,Mobiliario', 'Tecnología'])
 
source_server = TSC.Server(SOURCE_SERVER_NAME, use_server_version=True)
 
⌗Use the following to sign in with PAT
source_tableau_auth = TSC.PersonalAccessTokenAuth(TOKEN_NAME,TOKEN,SOURCE_SITE_NAME)
 
with source_server.auth.sign_in(source_tableau_auth):
    print('Logged in to source server successfully')
    all_workbooks = source_server.workbooks.filter(name=SOURCE_WORKBOOK_NAME, project_name=PROJECT_NAME)
    print(len(all_workbooks))
    ⌗Download workbook to a temp directory
    if len(all_workbooks) == 0:
        print('No workbook named {} found.'.format(SOURCE_WORKBOOK_NAME))
        exit()
    elif len(all_workbooks) >= 2:
        print('Several workbooks named {} found.'.format(SOURCE_WORKBOOK_NAME))
        exit()
    elif len(all_workbooks) == 1:
        isExist = os.path.exists(TMPDIR)
        print(isExist)
        if not isExist:
            # Create a new directory because it does not exist
            os.makedirs(TMPDIR)
            print("The new directory is created!")          
        try:
            for j in all_workbooks:
                ##create a pdf merger object 
                PDFMerger = PyPDF2.PdfMerger()
                for k in FILTERS:
                    try:
                        source_server.workbooks.populate_views(j)  
                        print("Connected to wb")
                        for i in j.views:
                            # set the image request option
                            pdf_req_option = TSC.PDFRequestOptions(page_type=TSC.PDFRequestOptions.PageType.Unspecified)
                            # (optional) set a view filter
                            print("Setting filters")
                            pdf_req_option.vf('Categoría', k)
                            #pdf_req_option.vf('Parameters.Year', '2018')
                            source_server.views.populate_pdf(i, pdf_req_option)
                            stream = BytesIO(i.pdf)
                            PDFMerger.append(stream)
                    except:
                        pass
                PDFMerger.write(PREVIEW_FOLDER_LOCATION+PREVIEW_FILE_NAME)
                print(PREVIEW_FOLDER_LOCATION+PREVIEW_FILE_NAME)
        except:
            pass
# Sign out
source_server.auth.sign_out()         

If working with default site use:

SOURCE_SITE_NAME = ''

Note this approach needs the workbook published in Tableau Server or Tableau Cloud. Also, note this code uses PAT (Personal Access Token authentication).

https://help.tableau.com/current/online/en-us/security_personal_access_tokens.htm

If this post resolves the question, would you be so kind to "Select as Best"?. This will help other users find the same answer/resolution and help community keep track of answered questions. Thank you.

Regards,

Diego Martinez

Tableau Visionary and Forums Ambassador

@mursid rahman​ 

Hi, currently you can't do it using the Rest API or TSC.

As a workaround, you may use a combination of the REST API, and the Document API to make those changes. I have never done it, but I think it is possible. My suggested steps would be.

a. Download the tdsx or tds using TSC.

b. Edit the required connection fields using the document api:

https://tableau.github.io/document-api-python/docs/

However, the schema property is not documented, but taking a closer look from the source code, it seems it is supported:

https://github.com/tableau/document-api-python/blob/master/tableaudocumentapi/connection.py

This may be something like the following code, but like I said, I have not tested it. Also,

from tableaudocumentapi import Datasource
DS_FILENAME = "Ventas Test.tdsx"
DS_DIRECTORY = "D:\\Tableau Server\\Document API\\"
DS_PATH = DS_DIRECTORY + DS_FILENAME
NEW_DS_FILENAME = "New Ventas.tdsx"
sourceDS = Datasource.from_file(DS_PATH)
 
#Create a loop if neccesary if several connections in the TDSX/TDS
#sourceDS.connections[0].server = "MY-NEW-SERVER"
#sourceDS.connections[0].dbname = "NEW-DATABASE"
sourceDS.connections[0].schema = "NEW-SCHEMA"
#sourceDS.connections[0].service = "NEW-SERVICE"
#sourceDS.connections[0].port = "8040"
#sourceDS.connections[0].username = "NEW-USER"
sourceDS.save_as(DS_DIRECTORY + NEW_DS_FILENAME)

c. Once the file is saved, you may publish again your datasource using Rest API or Tableau Server Client. As always, before replacing your current datasource, do some tests.

I would like to have a complete code, however, I currently don't have it.

If this post resolves the question, would you be so kind to "Select as Best"?. This will help other users find the same answer/resolution and help community keep track of answered questions. Thank you.

Regards,

Diego Martinez

Tableau Visionary and Forums Ambassador

Hi @Lilian Castro I am a member of Trailhead Help, We have created a case on your behalf. We will reach out to you via email to investigate further.

++CreateTrailheadCase

You can ignore the above command, it is a tool used by our Agents to tell the system to create your case. Thank you!

@Serkan Arslan​ 

Hi, in this case you may use Tableau Server Client:

import tableauserverclient as TSC
import csv
 
# server admin creds
HOST = "https://prod-useast-b.online.tableau.com/"
TOKEN_NAME = "Test"
TOKEN_VALUE = "cjcvCg==:45pE9"
CONTENT_URL = "yoursite"
 
tableau_auth = TSC.PersonalAccessTokenAuth(TOKEN_NAME, TOKEN_VALUE, site_id=CONTENT_URL)
server = TSC.Server(HOST, use_server_version=True)
 
 
#Create the csv file and open it in write mode
f = open('views.csv', 'w', encoding='UTF8', newline='')
 
#delimiter with semicolon if need change to comma, and write header
writer = csv.writer(f, delimiter=";")
header = ['content URL','name','Owner_id','total_views']
writer.writerow(header)
 
today_date = datetime.now(timezone.utc)
 
with server.auth.sign_in(tableau_auth):
    for view in TSC.Pager(server.views,usage=True):
        row=[view.content_url,view.name,view.owner_id,view.total_views]
        #print(view.conten_url,view.name,view.owner_id,view.total_views)
        #write the row
        writer.writerow(row)
#Close file connection and sign out
f.close()
server.auth.sign_out()

To use this code, you will need a PAT:

https://help.tableau.com/current/pro/desktop/en-us/useracct.htm#create-a-personal-access-token

If this post resolves the question, would you be so kind to "Select as Best"?. This will help other users find the same answer/resolution and help community keep track of answered questions. Thank you.

Regards,

Diego Martinez

Tableau Visionary and Forums Ambassador