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Merge commit '05e226fcabf9bbe6d9ca9816cd2df827926b619a' into main

This commit is contained in:
Dan 2023-02-14 16:51:09 -05:00
parent 829212dec9 05e226fcab
commit 929d04af5f
14 changed files with 137 additions and 139 deletions
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4
SpiffWorkflow/SpiffWorkflow/bpmn/parser/node_parser.py
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@ -46,7 +46,7 @@ class NodeParser:
if ref is not None and ref.get('dataObjectRef') in self.process_parser.spec.data_objects:
specs.append(self.process_parser.spec.data_objects[ref.get('dataObjectRef')])
else:
raise ValidationException(f'Cannot resolve dataInputAssociation {name}', self.node, self.file_name)
raise ValidationException(f'Cannot resolve dataInputAssociation {name}', self.node, self.filename)
return specs
def parse_outgoing_data_references(self):
@ -56,7 +56,7 @@ class NodeParser:
if ref is not None and ref.get('dataObjectRef') in self.process_parser.spec.data_objects:
specs.append(self.process_parser.spec.data_objects[ref.get('dataObjectRef')])
else:
raise ValidationException(f'Cannot resolve dataOutputAssociation {name}', self.node, self.file_name)
raise ValidationException(f'Cannot resolve dataOutputAssociation {name}', self.node, self.filename)
return specs
def parse_extensions(self, node=None):

18
SpiffWorkflow/doc/bpmn/advanced.rst
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@ -7,7 +7,7 @@ Filtering Tasks
In our earlier example, all we did was check the lane a task was in and display
it along with the task name and state.
Lets take a look at a sample workflow with lanes:
Let's take a look at a sample workflow with lanes:
.. figure:: figures/lanes.png
:scale: 30%
@ -15,7 +15,7 @@ Lets take a look at a sample workflow with lanes:
Workflow with lanes
To get all of the tasks that are ready for the 'Customer' workflow, we could
To get all the tasks that are ready for the 'Customer' workflow, we could
specify the lane when retrieving ready user tasks:
.. code:: python
@ -50,14 +50,14 @@ Logging
Spiff provides several loggers:
- the :code:`spiff` logger, which emits messages when a workflow is initialized and when tasks change state
- the :code:`spiff.metrics` logger, which emits messages containing the elapsed duration of tasks
- the :code:`spiff.data` logger, which emits message when task or workflow data is updated.
- the :code:`spiff.data` logger, which emits a message when task or workflow data is updated.
Log level :code:`INFO` will provide reasonably detailed information about state changes.
As usual, log level :code:`DEBUG` will probably provide more logs than you really want
to see, but the logs will contain the task and task internal data.
Data can be included at any level less than :code:`INFO`. In our exmple application,
Data can be included at any level less than :code:`INFO`. In our example application,
we define a custom log level
.. code:: python
@ -76,7 +76,7 @@ Serialization
Serialization Changed in Version 1.1.7.
Support for pre-1.1.7 serialization will be dropped in a future release.
The old serialization method still works but it is deprecated.
The old serialization method still works, but it is deprecated.
To migrate your system to the new version, see "Migrating between
serialization versions" below.
@ -131,7 +131,7 @@ To restore the workflow:
with open(args.restore) as state:
wf = serializer.deserialize_json(state.read())
The workflow serializer is designed to be flexible and modular and as such is a little complicated. It has
The workflow serializer is designed to be flexible and modular, and as such is a little complicated. It has
two components:
- a workflow spec converter (which handles workflow and task specs)
@ -141,7 +141,7 @@ The default workflow spec converter likely to meet your needs, either on its own
:code:`UserTask` and :code:`BusinessRuleTask` in the :code:`camnuda` or :code:`spiff` and :code:`dmn` subpackages
of this library, and all you'll need to do is add them to the list of task converters, as we did above.
However, he default data converter is very simple, adding only JSON-serializable conversions of :code:`datetime`
However, the default data converter is very simple, adding only JSON-serializable conversions of :code:`datetime`
and :code:`timedelta` objects (we make these available in our default script engine) and UUIDs. If your
workflow or task data contains objects that are not JSON-serializable, you'll need to extend ours, or extend
its base class to create one of your own.
@ -245,7 +245,7 @@ The code would then look more like this:
Because the serializer is highly customizable, we've made it possible for you to manage your own versions of the
serialization. You can do this by passing a version number into the serializer, which will be embedded in the
json of all workflows. This allow you to modify the serialization and customize it over time, and still manage
json of all workflows. This allows you to modify the serialization and customize it over time, and still manage
the different forms as you make adjustments without leaving people behind.
Versioned Serializer
@ -273,7 +273,7 @@ security reasons.
and :code:`exec`! If you have security concerns, you should definitely investigate
replacing the default with your own implementation.
We'll cover a simple extension of custom script engine here. There is also an examples of
We'll cover a simple extension of custom script engine here. There is also an example of
a similar engine based on `RestrictedPython <https://restrictedpython.readthedocs.io/en/latest/>`_
included alongside this example.

6
SpiffWorkflow/doc/bpmn/events.rst
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@ -31,7 +31,7 @@ We'll include examples of all of these types in this section.
Transactions
^^^^^^^^^^^^
We also need to introduce the concept of a Transaction, bceause certain events
We also need to introduce the concept of a Transaction because certain events
can only be used in that context. A Transaction is essentially a subprocess, but
it must fully complete before it affects its outer workflow.
@ -147,7 +147,7 @@ this tutorial.
We ask the Employee to verify that they were able to retrieve the product; if they
were unable to do so, then we generate an Error End Event, which we will handle
with an Interrupting Error Boundary Event (Error events are *always* Interrupting).
with an Interrupting Error Boundary Event (Error events are *always* interrupting).
If the product is unavailable, our Manager will notify the customer, issue a refund,
and cancel the order.
@ -161,7 +161,7 @@ Event, you'll have to use Escalation, because BPMN does not allow Intermediate E
and that Error Events cannot be Non-Interrupting.
In our example, we'll assume that if we failed to ship the product, we can try again later,
so we will not end the Subprocess (Escalation events can be either Interrupting or
so, we will not end the Subprocess (Escalation events can be either Interrupting or
Non-Interrupting).
However, we still want to notify our customer of a delay, so we use a Non-Interrupting

2
SpiffWorkflow/doc/bpmn/gateways.rst
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@ -23,7 +23,7 @@ Exclusive Gateway
Exclusive gateways are used when exactly one alternative can be selected.
Suppose our products are T-shirts and we offer product C in several colors. After
the user selects a product, we check to see it if is customizable. Our default
the user selects a product, we check to see it if is customizable. Our default
branch will be 'Not Customizable', but we'll direct the user to a second form
if they select 'C'; our condition for choosing this branch is a simple python
expression.

8
SpiffWorkflow/doc/bpmn/index.rst
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@ -1,7 +1,7 @@
BPMN Workflows
==============
The basic idea of SpiffWorkflow is that you can use it to write an interpreter
The basic idea of SpiffWorkflow is that you can use it to write an interpreter
in Python that creates business applications from BPMN models. In this section,
we'll develop a model of an example process and as well as a
simple workflow runner.
@ -11,8 +11,8 @@ We expect that readers will fall into two general categories:
- People with a background in BPMN who might not be very familiar Python
- Python developers who might not know much about BPMN
This section of the documentation provides an example that (hopefully) serves
the needs of both groups. We will introduce the BPMN elements that SpiffWorkflow
This section of the documentation provides an example that (hopefully) serves
the needs of both groups. We will introduce the BPMN elements that SpiffWorkflow
supports and show how to build a simple workflow runner around them.
SpiffWorkflow does heavy-lifting such as keeping track of task dependencies and
@ -29,7 +29,7 @@ Quickstart
Check out the code in `spiff-example-cli <https://github.com/sartography/spiff-example-cli>`_
and follow the instructions to set up an environment to run it in.
Run the sample workflow we built up using our example application with the following
Run the sample workflow we built up using our example application with the following
command:
.. code-block:: console

2
SpiffWorkflow/doc/bpmn/multiinstance.rst
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@ -28,7 +28,7 @@ selections in a collection.
Selecting more than one product
We'll also need to update our element docmentation to display all products.
We'll also need to update our element documentation to display all products.
.. figure:: figures/documentation_multi.png
:scale: 30%

26
SpiffWorkflow/doc/bpmn/organization.rst
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@ -1,4 +1,4 @@
Organizing More Complex Workflows
Organizing More Complex Workflows
=================================
BPMN Model
@ -43,20 +43,20 @@ For a simple code example of displaying a tasks lane, see `Handling Lanes`_
Subprocesses
^^^^^^^^^^^^
In general, subprocesses are a way of grouping work into smaller units. This, in
theory, will help us to re-use sections of business logic, but it will also allow
In general, subprocesses are a way of grouping work into smaller units. This, in
theory, will help us to re-use sections of business logic, but it will also allow
us to treat groups of work as a unit.
Subprocesses come in two different flavors. In this workflow we see an Expanded
Subprocess. Unfortunately, we can't collapse an expanded subprocess within BPMN.js,
Subprocesses come in two different flavors. In this workflow we see an Expanded
Subprocess. Unfortunately, we can't collapse an expanded subprocess within BPMN.js,
so expanded subprocesses are mainly useful for conceptualizing a group of tasks as
a unit.
a unit.
It also possible to refer to external subprocesses via a Call Activity Task. This
allows us to 'call' a separate workflow in a different file by referencing the ID of
It also possible to refer to external subprocesses via a Call Activity Task. This
allows us to 'call' a separate workflow in a different file by referencing the ID of
the called workflow, which can simplify business logic and make it re-usable.
We'll expand 'Fulfill Order' into sub tasks -- retrieving the product and shipping
We'll expand 'Fulfill Order' into sub tasks -- retrieving the product and shipping
the order -- and create an Expanded Subprocess.
We'll also expand our selection of products, adding several new products and the ability
@ -68,14 +68,14 @@ to customize certain products by size and style in addition to color.
Updated Product List
.. note::
.. note::
I've added what customizations are available for each product in the 'Annotations'
column of the DMN table. This is not actually used by Spiff; it simply provides
the option of documenting the decisions contained in the table.
Since adding gateways for navigating the new options will add a certain amount of
clutter to our diagram, we'll create a separate workflow around selecting and
Since adding gateways for navigating the new options will add a certain amount of
clutter to our diagram, we'll create a separate workflow around selecting and
customizing products and refer to that in our main workflow.
.. figure:: figures/call_activity.png
@ -116,7 +116,7 @@ our sample application, we'll simply display which lane a task belongs to.
.. code:: python
if hasattr(task.task_spec, 'lane') and task.task_spec.lane is not None:
lane = f'[{task.task_spec.lane}]'
lane = f'[{task.task_spec.lane}]'
else:
lane = ''

10
SpiffWorkflow/doc/bpmn/spiff-extensions.rst
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@ -17,7 +17,7 @@ instead of the `run.py <https://github.com/sartography/spiff-example-clie/blob/m
Camunda's BPMN editor does not handle data objects in the expected way. You can create data object
references, but there is no way to re-use data objects.
It also does not support Message Correlations, and the inteface for generating a message payload doesn't work
It also does not support Message Correlations, and the interface for generating a message payload doesn't work
well in a Python environment.
We have extended BPMN.js to correct some of these issues. The examples in this section were created using our
@ -25,7 +25,7 @@ custom BPMN editor, `bpmn-js-spiffworkflow <https://github.com/sartography/bpmn-
Data Objects
^^^^^^^^^^^^
Data objects exist at a 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.
@ -35,8 +35,8 @@ Data Objects
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
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.
@ -59,7 +59,7 @@ the 'Enter Payment Info' has been completed.
Configuring Messages
^^^^^^^^^^^^^^^^^^^^
Messages are handled slightly differently in Spiff Message Events. On an Message Throw Event or Send Task,
Messages are handled slightly differently in Spiff Message Events. On a Message Throw Event or Send Task,
we define a payload, which is simply a bit of python code that will be evaluated against the task data and
sent along with the message. In the corresponding Message Catch Event or Receive Task, we define a
variable name where we'll store the result.

32
SpiffWorkflow/doc/bpmn/synthesis.rst
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@ -4,13 +4,13 @@ Putting it All Together
In this section we'll be discussing the overall structure of the workflow
runner we developed in `spiff-example-cli <https://github.com/sartography/spiff-example-cli>`_.
Our example application contains two different workflow runners, one that uses tasks with
Our example application contains two different workflow runners, one that uses tasks with
Camunda extensions
(`run.py <https://github.com/sartography/spiff-example-cli/blob/main/run.py>`_) and one
that uses tasks with Spiff extensions
that uses tasks with Spiff extensions
(`run-spiff.py <https://github.com/sartography/spiff-example-cli/blob/main/run.py>`_).
Most of the workflow operations will not change, so shared functions are defined in
Most of the workflow operations will not change, so shared functions are defined in
`utils.py <https://github.com/sartography/spiff-example-cli/blob/main/utils.py>`_.
The primary difference is handling user tasks. Spiff User Tasks define an extensions
@ -23,7 +23,7 @@ Loading a Workflow
-------------------
The :code:`CamundaParser` extends the base :code:`BpmnParser`, adding functionality for
parsing forms defined in Camunda User Tasks and decision tables defined in Camunda
parsing forms defined in Camunda User Tasks and decision tables defined in Camunda
Business Rule Tasks. (There is a similar :code:`SpiffBpmnParser` used by the alternate
runner.)
@ -52,23 +52,23 @@ Our workflow parser looks like this;
We'll obtain the workflow specification from the parser for the top level process
using :code:`parser.get_spec()`.
We have two options for finding subprocess specs. The method :code:`parser.find_all_specs()`
will create specs for all executable processes found in every file supplied. The method
:code:`parser.get_subprocess_specs(process)` will create specs only for processes used by
the specified process. Both search recursively for subprocesses; the only difference is
We have two options for finding subprocess specs. The method :code:`parser.find_all_specs()`
will create specs for all executable processes found in every file supplied. The method
:code:`parser.get_subprocess_specs(process)` will create specs only for processes used by
the specified process. Both search recursively for subprocesses; the only difference is
the latter method limits the search start to the specified process.
Our examples are pretty simple and we're not loading any extraneous stuff, so we'll
Our examples are pretty simple, and we're not loading any extraneous stuff, so we'll
just always load everything. If your entire workflow is contained in your top-level
process, you can omit the :code:`subprocess` argument, but if your workflow contains
call activities, you'll need to use one of these methods to find the models for any
process, you can omit the :code:`subprocess` argument, but if your workflow contains
call activities, you'll need to use one of these methods to find the models for any
called processes.
We also provide an enhanced script engine to our workflow. More information about how and
why you might want to do this is covered in :doc:`advanced`. The :code:`script_engine`
argument is optional and the default will be used if none is supplied.
We return :code:`BpmnWorkflow` that runs our top-level workflow and contains specs for any
We return :code:`BpmnWorkflow` that runs our top-level workflow and contains specs for any
subprocesses defined by that workflow.
Defining Task Handlers
@ -91,7 +91,7 @@ We create a mapping of task type to handler, which we'll pass to our workflow ru
This might not be a step you would need to do in an application you build, since
you would likely have only one set of task specs that need to be parsed, handled, and
serialized; however our `run` method is an awful lot of code to maintain in two separate
serialized; however, our `run` method is an awful lot of code to maintain in two separate
files.
Running a Workflow
@ -180,10 +180,10 @@ Examining the Workflow State
----------------------------
When this application is run and we want to present steps to the user, we'll need
to be able to examine the workflow and task states and associated data. We'll cover
to be able to examine the workflow and task states and associated data. We'll cover
the basics of this in this section.
The code below is a simple method for displaying information about a task. We use
The code below is a simple method for displaying information about a task. We use
this in two ways
- presenting a list of tasks to a user (in this case the state will always be ready, so we won't include it)
@ -233,7 +233,7 @@ We'll print information about our task as described above, as well as a dump of
We can get a list of all tasks regardless of type or state with :code:`workflow.get_tasks()`.
The actual list of tasks will get quite long (some tasks are expanded internally by Spiff into
multiple tasks, and all gateways and events are also treated as "tasks"). So we're filtering
multiple tasks, and all gateways and events are also treated as "tasks"). So we're filtering
the tasks to only display the ones that would have salience to a user here.
We'll further filter those tasks for :code:`READY` and :code:`WAITING` tasks for a more

3
SpiffWorkflow/doc/bpmn/tasks.rst
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@ -171,7 +171,7 @@ Our :code:`select_option` function simply repeats the prompt until the user
enters a value contained in the option list.
For other fields, we'll just store whatever the user enters, although in the case
where they data type was specified to be a :code:`long`, we'll convert it to a
where the data type was specified to be a :code:`long`, we'll convert it to a
number.
Finally, we need to explicitly store the user-provided response in a variable
@ -219,4 +219,3 @@ The template string can be obtained from :code:`task.task_spec.documentation`.
As noted above, our template class comes from Jinja. We render the template
using the task data, which is just a dictionary.

5
SpiffWorkflow/doc/intro.rst
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@ -64,7 +64,7 @@ The following example also has one task, represented by the rectangle with curve
The sequence flow is represented with a solid line connector. When the node at
the tail of a sequence flow completes, the node at the arrowhead is enabled to start.
the tail of a sequence flow completes, the node at the arrowhead is enabled to start.
A More Complicated Workflow
@ -78,7 +78,7 @@ A More Complicated Workflow
In this example, the diamond shape is called a gateway. It represents a branch
point in our flow. This gateway is an exclusive data-based gateway (also
point in our flow. This gateway is an exclusive data-based gateway (also
called an XOR gateway). With an exclusive gateway, you must take one path or
the other based on some data condition. BPMN has other gateway types.
@ -122,4 +122,3 @@ attached to will be cancelled if the event is received) or Non-Interrupting (in
which case the task will continue). In both cases, flows may emanate from the
Boundary Event, which will trigger those paths if the events occur while the task
is being executed.

2
SpiffWorkflow/doc/non-bpmn/custom-tasks/index.rst
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@ -4,7 +4,7 @@ Implementing Custom Tasks
Introduction
------------
In this second tutorial we are going to implement our own task, and
In this second tutorial, we are going to implement our own task, and
use serialization and deserialization to store and restore it.
If you haven't already, you should complete the first

4
SpiffWorkflow/doc/non-bpmn/index.rst
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@ -1,7 +1,7 @@
Non-BPMN support
================
We have maintained support for legacy non-BPMN workflows, but we recommend using
We have maintained support for legacy non-BPMN workflows, but we recommend using
SpiffWorkflow with BPMN, as this is where current development is focused.
.. toctree::
@ -9,4 +9,4 @@ SpiffWorkflow with BPMN, as this is where current development is focused.
tutorial/index
custom-tasks/index
patterns
patterns

154
SpiffWorkflow/doc/non-bpmn/patterns.rst
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@ -1,77 +1,77 @@
.. _patterns:
Supported Workflow Patterns
===========================
.. HINT::
All examples are located
`here <https://github.com/knipknap/SpiffWorkflow/blob/master/tests/SpiffWorkflow/data/spiff/>`_.
Control-Flow Patterns
---------------------
1. Sequence [control-flow/sequence.xml]
2. Parallel Split [control-flow/parallel_split.xml]
3. Synchronization [control-flow/synchronization.xml]
4. Exclusive Choice [control-flow/exclusive_choice.xml]
5. Simple Merge [control-flow/simple_merge.xml]
6. Multi-Choice [control-flow/multi_choice.xml]
7. Structured Synchronizing Merge [control-flow/structured_synchronizing_merge.xml]
8. Multi-Merge [control-flow/multi_merge.xml]
9. Structured Discriminator [control-flow/structured_discriminator.xml]
10. Arbitrary Cycles [control-flow/arbitrary_cycles.xml]
11. Implicit Termination [control-flow/implicit_termination.xml]
12. Multiple Instances without Synchronization [control-flow/multi_instance_without_synch.xml]
13. Multiple Instances with a Priori Design-Time Knowledge [control-flow/multi_instance_with_a_priori_design_time_knowledge.xml]
14. Multiple Instances with a Priori Run-Time Knowledge [control-flow/multi_instance_with_a_priori_run_time_knowledge.xml]
15. Multiple Instances without a Priori Run-Time Knowledge [control-flow/multi_instance_without_a_priori.xml]
16. Deferred Choice [control-flow/deferred_choice.xml]
17. Interleaved Parallel Routing [control-flow/interleaved_parallel_routing.xml]
18. Milestone [control-flow/milestone.xml]
19. Cancel Task [control-flow/cancel_task.xml]
20. Cancel Case [control-flow/cancel_case.xml]
21. *NOT IMPLEMENTED*
22. Recursion [control-flow/recursion.xml]
23. Transient Trigger [control-flow/transient_trigger.xml]
24. Persistent Trigger [control-flow/persistent_trigger.xml]
25. Cancel Region [control-flow/cancel_region.xml]
26. Cancel Multiple Instance Task [control-flow/cancel_multi_instance_task.xml]
27. Complete Multiple Instance Task [control-flow/complete_multiple_instance_activity.xml]
28. Blocking Discriminator [control-flow/blocking_discriminator.xml]
29. Cancelling Discriminator [control-flow/cancelling_discriminator.xml]
30. Structured Partial Join [control-flow/structured_partial_join.xml]
31. Blocking Partial Join [control-flow/blocking_partial_join.xml]
32. Cancelling Partial Join [control-flow/cancelling_partial_join.xml]
33. Generalized AND-Join [control-flow/generalized_and_join.xml]
34. Static Partial Join for Multiple Instances [control-flow/static_partial_join_for_multi_instance.xml]
35. Cancelling Partial Join for Multiple Instances [control-flow/cancelling_partial_join_for_multi_instance.xml]
36. Dynamic Partial Join for Multiple Instances [control-flow/dynamic_partial_join_for_multi_instance.xml]
37. Acyclic Synchronizing Merge [control-flow/acyclic_synchronizing_merge.xml]
38. General Synchronizing Merge [control-flow/general_synchronizing_merge.xml]
39. Critical Section [control-flow/critical_section.xml]
40. Interleaved Routing [control-flow/interleaved_routing.xml]
41. Thread Merge [control-flow/thread_merge.xml]
42. Thread Split [control-flow/thread_split.xml]
43. Explicit Termination [control-flow/explicit_termination.xml]
Workflow Data Patterns
----------------------
1. Task Data [data/task_data.xml]
2. Block Data [data/block_data.xml]
3. *NOT IMPLEMENTED*
4. *NOT IMPLEMENTED*
5. *NOT IMPLEMENTED*
6. *NOT IMPLEMENTED*
7. *NOT IMPLEMENTED*
8. *NOT IMPLEMENTED*
9. Task to Task [data/task_to_task.xml]
10. Block Task to Sub-Workflow Decomposition [data/block_to_subworkflow.xml]
11. Sub-Workflow Decomposition to Block Task [data/subworkflow_to_block.xml]
Specs that have no corresponding workflow pattern on workflowpatterns.com
-------------------------------------------------------------------------
- Execute - spawns a subprocess and waits for the results
- Transform - executes commands that can be used for data transforms
- Celery - executes a Celery task (see http://celeryproject.org/)
.. _patterns:
Supported Workflow Patterns
===========================
.. HINT::
All examples are located
`here <https://github.com/knipknap/SpiffWorkflow/blob/master/tests/SpiffWorkflow/data/spiff/>`_.
Control-Flow Patterns
---------------------
1. Sequence [control-flow/sequence.xml]
2. Parallel Split [control-flow/parallel_split.xml]
3. Synchronization [control-flow/synchronization.xml]
4. Exclusive Choice [control-flow/exclusive_choice.xml]
5. Simple Merge [control-flow/simple_merge.xml]
6. Multi-Choice [control-flow/multi_choice.xml]
7. Structured Synchronizing Merge [control-flow/structured_synchronizing_merge.xml]
8. Multi-Merge [control-flow/multi_merge.xml]
9. Structured Discriminator [control-flow/structured_discriminator.xml]
10. Arbitrary Cycles [control-flow/arbitrary_cycles.xml]
11. Implicit Termination [control-flow/implicit_termination.xml]
12. Multiple Instances without Synchronization [control-flow/multi_instance_without_synch.xml]
13. Multiple Instances with a Priori Design-Time Knowledge [control-flow/multi_instance_with_a_priori_design_time_knowledge.xml]
14. Multiple Instances with a Priori Run-Time Knowledge [control-flow/multi_instance_with_a_priori_run_time_knowledge.xml]
15. Multiple Instances without a Priori Run-Time Knowledge [control-flow/multi_instance_without_a_priori.xml]
16. Deferred Choice [control-flow/deferred_choice.xml]
17. Interleaved Parallel Routing [control-flow/interleaved_parallel_routing.xml]
18. Milestone [control-flow/milestone.xml]
19. Cancel Task [control-flow/cancel_task.xml]
20. Cancel Case [control-flow/cancel_case.xml]
21. *NOT IMPLEMENTED*
22. Recursion [control-flow/recursion.xml]
23. Transient Trigger [control-flow/transient_trigger.xml]
24. Persistent Trigger [control-flow/persistent_trigger.xml]
25. Cancel Region [control-flow/cancel_region.xml]
26. Cancel Multiple Instance Task [control-flow/cancel_multi_instance_task.xml]
27. Complete Multiple Instance Task [control-flow/complete_multiple_instance_activity.xml]
28. Blocking Discriminator [control-flow/blocking_discriminator.xml]
29. Cancelling Discriminator [control-flow/cancelling_discriminator.xml]
30. Structured Partial Join [control-flow/structured_partial_join.xml]
31. Blocking Partial Join [control-flow/blocking_partial_join.xml]
32. Cancelling Partial Join [control-flow/cancelling_partial_join.xml]
33. Generalized AND-Join [control-flow/generalized_and_join.xml]
34. Static Partial Join for Multiple Instances [control-flow/static_partial_join_for_multi_instance.xml]
35. Cancelling Partial Join for Multiple Instances [control-flow/cancelling_partial_join_for_multi_instance.xml]
36. Dynamic Partial Join for Multiple Instances [control-flow/dynamic_partial_join_for_multi_instance.xml]
37. Acyclic Synchronizing Merge [control-flow/acyclic_synchronizing_merge.xml]
38. General Synchronizing Merge [control-flow/general_synchronizing_merge.xml]
39. Critical Section [control-flow/critical_section.xml]
40. Interleaved Routing [control-flow/interleaved_routing.xml]
41. Thread Merge [control-flow/thread_merge.xml]
42. Thread Split [control-flow/thread_split.xml]
43. Explicit Termination [control-flow/explicit_termination.xml]
Workflow Data Patterns
----------------------
1. Task Data [data/task_data.xml]
2. Block Data [data/block_data.xml]
3. *NOT IMPLEMENTED*
4. *NOT IMPLEMENTED*
5. *NOT IMPLEMENTED*
6. *NOT IMPLEMENTED*
7. *NOT IMPLEMENTED*
8. *NOT IMPLEMENTED*
9. Task to Task [data/task_to_task.xml]
10. Block Task to Sub-Workflow Decomposition [data/block_to_subworkflow.xml]
11. Sub-Workflow Decomposition to Block Task [data/subworkflow_to_block.xml]
Specs that have no corresponding workflow pattern on workflowpatterns.com
-------------------------------------------------------------------------
- Execute - spawns a subprocess and waits for the results
- Transform - executes commands that can be used for data transforms
- Celery - executes a Celery task (see http://celeryproject.org/)