Column with None values becomes "All" when publishing a workbook using the TSC Python client

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Assessment

Difficulty
3/5
Estimated time
1-2 days
Newbie friendliness
48/100
Issue type
Bug
Clarity
Mostly clear
Activity status
Quiet
Tech stack
python
Domain
api

Research direction

Start at the reported server.workbooks.publish(wb_item, file_path, mode) entry point and reproduce the issue with a workbook containing None values. Compare the published data with the manually published workbook, then verify that None values remain unchanged after the fix.

Written by the indexing model from the issue text.

Description

bug needs investigation

Describe the bug

When publishing a workbook to Tableau Server using the Tableau Server Client (TSC) Python library, a column in the underlying table that contains None values is being converted to the string "All".
This happens only when publishing via TSC.
Publishing the same workbook manually to Tableau Server preserves the None values correctly.

Expected behavior
When publishing a workbook using the TSC client, column values that are None should remain unchanged—exactly as they do when publishing manually to Tableau Server.

Actual behavior
A datasource table includes a column with None values.
When publishing the workbook using TSC (server.workbooks.publish()), the None values in that column are changed to "All".
No transformation or custom handling of values is applied in the Python script.

Versions
Details of your environment, including:

  • Tableau Server version - 2025.1.7 (20251.25.0825.1650) 64-bit Linux
  • Python version - 3.9
  • TSC library version - 0.15.0

To Reproduce

  • Create a workbook with a datasource table containing at least one column with None values.
  • Publish the workbook using TSC:
  • server.workbooks.publish(wb_item, file_path, mode)
  • Open the published workbook on Tableau Server.
  • Observe that the original None values have been replaced with "All".

Results

This issue leads to incorrect data representation in the published workbook and may cause:

  • Misleading data displays
  • Filters not behaving as expected
  • Broken calculations relying on None values
  • Confusion or incorrect interpretation for end users

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Dominant language
Python
Stars
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Forks
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Avg merge
8d 8h
Merged PRs (30d)
2

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