Data

BPMN Model

We’ll be using the following files from spiff-example-cli.

• bpmn-spiff/events workflow
• bpmn-spiff/call_activity workflow
• bpmn-spiff/data_output workflow
• product_prices DMN table
• shipping_costs DMN table

Data Objects

Data Objects exist at the process level and are not visible in the diagram, but when you create a Data Object Reference, you can choose what Data Object it points to.

Configuring a Data Object Reference

When a Data Output association (a line) is drawn from a task to a Data Object Reference, the value is copied from the task data to the workflow data and removed from the task. If a Data Input Association is created from a Data Object Reference, the value is temporarily copied into the task data while the task is being executed, and immediate removed afterwards.

This allows sensitive data to be removed from individual tasks (in our example, the customer’s credit card number). It can also be used to prevent large objects from being repeatedly copied from task to task.

Multiple Data Object References can point to the same underlying data. In our example, we use two references to the same Data Object to pass the credit card info to both tasks that require it. On the right panel, we can see that only one data object exists in the process.

Data objects in a process

If you step through this workflow, you’ll see that the card number is not contained in the task data after the ‘Enter Payment Info’ has been completed but is available to the ‘Charge Customer’ task later on.

Running The Model

If you have set up our example repository, this model can be run with the following command:

./spiff-bpmn-runner.py -c order_collaboration \
     -d bpmn/tutorial/product_prices.dmn bpmn/tutorial/shipping_costs.dmn \
     -b bpmn/tutorial/events.bpmn bpmn/tutorial/call_activity.bpmn

Data Inputs and Outputs

In complex workflows, it is useful to be able to specify required Data Inputs and Outputs, especially for Call Activities given that they are external and might be shared across many different processes.

When you add a Data Input to a Call Activity, SpiffWorkflow will check that a variable with that name is available to be copied into the activity and copy only the variables you’ve specified as inputs. When you add a Data Output, SpiffWorkflow will copy only the variables you’ve specified from the Call Activity at the end of the process. If any of the variables are missing, SpiffWorkflow will raise an error.

Our product customization Call Activity does not require any input, but the output of the process is the product name and quantity. We can add corresponding Data Outputs for those. .. figure:: figures/data/data_output.png

scale:30% align:center

Data Outputs in a Call Activity

If you use this version of the Call Activity and choose a product that has customizations, when you inspect the data after the Call Activity completes, you’ll see that the cutomizations have been removed. We won’t continue to use this version of the Call Activity, because we want to preserve all the data.

Note

The BPMN spec allows any task to have Data Inputs and Outputs. Our modeler does not provide a way to add them to arbitrary tasks, but SpiffWorkflow will recognize them on any task if they are present in the BPMN XML.

Running The Model

If you have set up our example repository, this model can be run with the following command:

./spiff-bpmn-runner.py -p order_product \
     -d bpmn/tutorial/product_prices.dmn bpmn/tutorial/shipping_costs.dmn \
     -b bpmn/tutorial/top_level.bpmn bpmn/tutorial/data_output.bpmn