Python Testing Specification

Notes

TTB Stands for TabToolBar.
Import Scripts via TTB/Model/Import PythonScript.
Return State != OK will be displayed in the Frontend output.
To run a pipeline, first create one by selecting the Create Pipeline button in the Data Processing tab.
Then create a solver by selecting the corresping button in the Data Processing tab.
Select the pipeline that shall be executed in the solver’s properties.
Select a solver and start it by selecting the Run button in the Data Processing tab.

Error Handling Tests

For the following tests, no environment shall be selected.

#

Setup

Execution

Expectation

1
Import script: TestScript_Abort.py
Datapipeline: Python block with script set
Connect Python block out with Display block

Run Data pipeline
Message from the DataProcessingService that the execution failed because abort was called.
Subprocess is still alive.

2
Import script: TestScript_Exit.py
Datapipeline: Python block with script set
Connect Python block out with Display block

Run Data pipeline
Message from the DataProcessingService that the execution failed because a SystemExit occurred.
Subprocess is still alive.

3
Import script: TestScript_Throw.py
Datapipeline: Python block with script set
Connect Python block out with Display block

Run Data pipeline
Message from the DataProcessingService that the execution failed because an exception was thrown.
Exception content: (‘spam’, ‘eggs’)

4
Import script: TestScript_ExtensionException.py
Datapipeline: Python block with script set
Connect Python block out with Display block

Run Data pipeline

Message from the DataProcessingService that the execution failed because the property does not exist.

5
Import script: TestScript_ModuleNotFound.py
Datapipeline: Python block with script set
Connect Python block out with Display block

Run Data pipeline

Message from the DataProcessingService that the execution failed because the module could not be found.

9
Import script: TestScript_NoMain.py
Datapipeline: Python block with script set
Connect Python block out with Display block

Run Data pipeline

Message from the DataProcessingService that the execution failed because the main function is missing.

Misc Tests

For the following tests, no environment shall be selected.

#

Target

Setup

Execution

Expectation

1
Print redirection
Import script: TestScript_HelloWorld.py
Datapipeline: Python block with script set
Connect Python block out with Display block
Run Data pipeline
In the output box is a “Hello World” written

2
Accessing entity properties
Import Prüfmatrix_S8_Ausschnitt.csv, change Column delimiter to ‘,’
Import script: TestScript_TableCell.py
Datapipeline: Python block with script set
Connect Python block out with Display block

Run Data pipeline
Successful with UI message:

Data: 329

Metadata:

{
    "Selected Campaign": null,
    "Selected Series label": null
}

3
Executing another script from within a script
Import Prüfmatrix_S8_Ausschnitt.csv, change Column delimiter to ‘,’
Import script 1: TestScript_TableCell.py
Import script 2: TestScript_ExecuteOtherScript.py
Datapipeline: Python block with script 2 set
Connect Python block out with Display block

Run Data pipeline
Successful with UI message:

Data: 329

Metadata:

{
    "Selected Campaign": null,
    "Selected Series label": null
}

Environment Tests

Restart OpenTwin before proceeding with the following tests.

#

Target

Setup

Execution

Expectation

1
Protection of default environment
Import script: TestScript_Numpy.py
Datapipeline: Python block with script set
Connect Python block out with Display block

Run Data pipeline
Error message in output window, stating that packages cannot be added to the default environment.

2
Creation of new environment by script analysis
Import script: TestScript_Numpy.py
Datapipeline: Python block with script set
Connect Python block out with Display block
Create a new manifest and select it in the python block properties.

Run Data pipeline
Successful with UI message:

Installing package: numpy Installing completed Numpy Matrix is:

[[ 6.  -1.7]
 [30.  44. ]]

Determinant of given 2X2 matrix: 315

In the navigation tree in the Python folder, an Installation log entity appeared. It contains a timestamp and details about the installed packages.
The Environment entity in the Python/Manifest folder has an entry for the installed numpy version, e.g.: “numpy==2.4.0”

3
Change of environment package version
After finishing test 2, change the numpy version noted in the environment entity.
E.g.: “numpy==2.4.0” -> “numpy==2.2.0”

Run Data pipeline
Successful with UI message:

Installing package: numpy==2.2.0 Installing completed Numpy Matrix is:

[[ 6.  -1.7]
 [30.  44. ]]

Determinant of given 2X2 matrix: 315

In the navigation tree in the Python folder, an Installation log entity appeared. It contains a timestamp and details about the installed packages.
The Environment entity in the Python/Manifest folder has an entry for the installed numpy version, e.g.: “numpy==2.4.0”

4
Change of environment package version
After finishing test 3, change the numpy version noted in the environment entity. E.g.: “numpy==2.4.0” -> “numpy==2.2.0”

Run Data pipeline
Successful with UI message:

Installing package: numpy==2.2.0 Installing completed Numpy Matrix is:

[[ 6.  -1.7]
 [30.  44. ]]

Determinant of given 2X2 matrix: 315

In the navigation tree in the Python folder, an Installation log entity appeared. It contains a timestamp and details about the installed packages.
The Environment entity in the Python/Manifest folder has an entry for the installed numpy version, e.g.: “numpy==2.4.0”

5
Invalid manifest
After finishing test 4, change the entry into an invalid form.
E.g.: “numpy==2.4.0” -> “numpy 2.2.0”

Run Data pipeline
Fail with UI message:
Failed to initialize environment: Invalid manifest

6
Environment garbage collector
Repeatedly change the version of numpy until there are seven folders named with numbers in the Deployment/PythonEnvironments folder.
Alter the last-access-date of three folders to four days before. This can be done for the folder 1234 for instance in a powershell with:
$file=Get-Item “1234”
$file.LastAccessTime = “2026-01-01 12:00:00”

Select a new environment variable for the python block and run the Data pipeline. Keep an eye on the Deployment/PythonEnvironments folder.
First, the three folders are renamed by appending “_remove” to each name. Afterwards they are deleted one by one. Finally, only three folders with numbers as name should remain.