If you export an SBDF from Python (for example, as outputs for a data function), and your output contains an empty column, then you can encounter the following error:

spotfire.sbdf.SBDFError: cannot determine type for column 'EmptyString'; all values are missing

This error occurs because the Spotfire data function environment cannot determine the proper Spotfire type to export the data as if all values in the column are missing (in other words, Python's None, NumPy's nan, or Panda's NA or NaT values).  To resolve this issue, edit your data function to use the helper function set_spotfire_types.

In your Python data function, if you export data containing a column with the data type Integer (32-bit) and manipulate the data so that the column grows by over 2 billion, Spotfire does not promote the column to the data type LongInteger (64-bit).

The documentation does not provide enough information on how to address issues with memory allocation for Spotfire Service for Python.

An interrupted engine is not destroyed (java.exe continues to run), consuming resources.

When you build Python packages into a Spotfire package (SPK), you cannot include Python packages that start with the same name as a Python package included with the Python interpreter SPK package. For example, you cannot include the package 'pandas_flavor' because the 'pandas' package is included with the interpreter.

The TERR service and Python Service for Spotfire fail to start when the property disable.java.core.dump is set to false.

A timing issue for fetching data function output on small or fast execution times can cause the job response to fail.