Task Dependencies

Task dependencies work the same way in the API as they do in the UI. You can filter and sort on any of the fields. For information about Task Dependencies in Flow Production Tracking, check out the main documentation page on our support site

Create Tasks

Let’s create a couple of Tasks and create dependencies between them. First we’ll create a “Layout” Task for our Shot:

data = {
    'project': {'type':'Project', 'id':65},
    'content': 'Layout',
    'start_date': '2010-04-28',
    'due_date': '2010-05-05',
    'entity': {'type':'Shot', 'id':860}
    }
result = sg.create(Task, data)

Returns:

{'content': 'Layout',
 'due_date': '2010-05-05',
 'entity': {'id': 860, 'name': 'bunny_010_0010', 'type': 'Shot'},
 'id': 556,
 'project': {'id': 65, 'name': 'Demo Animation Project', 'type': 'Project'},
 'start_date': '2010-04-28',
 'type': 'Task'}

Now let’s create an “Anm” Task for our Shot:

data = {
    'project': {'type':'Project', 'id':65},
    'content': 'Anm',
    'start_date': '2010-05-06',
    'due_date': '2010-05-12',
    'entity': {'type':'Shot', 'id':860}
    }
result = sg.create(Task, data)

Returns:

{'content': 'Anm',
 'due_date': '2010-05-12',
 'entity': {'id': 860, 'name': 'bunny_010_0010', 'type': 'Shot'},
 'id': 557,
 'project': {'id': 65, 'name': 'Demo Animation Project', 'type': 'Project'},
 'start_date': '2010-05-06,
 'type': 'Task'}

Create A Dependency

Tasks each have an upstream_tasks field and a downstream_tasks field. Each field is a list [] type and can contain zero, one, or multiple Task entity dictionaries representing the dependent Tasks. There are four dependency types from which you can choose: finish-to-start-next-day, start-to-finish-next-day, start-to-start, finish-to-finish. If no dependency type is provided the default finish-to-start-next-day will be used. Here is how to create a dependency between our “Layout” and “Anm” Tasks:

# make 'Layout' an upstream Task to 'Anm'. (aka, make 'Anm' dependent on 'Layout') with finish-to-start-next-day dependency type
data = {
    'upstream_tasks':[{'type':'Task','id':556, 'dependency_type': 'finish-to-start-next-day'}]
}
result = sg.update('Task', 557, data)

Returns:

[{'id': 557,
  'type': 'Task',
  'upstream_tasks': [{'id': 556, 'name': 'Layout', 'type': 'Task'}]}]

This will also automatically update the downstream_tasks field on ‘Layout’ to include the ‘Anm’ Task.

Query Task Dependencies

Task Dependencies each have a dependent_task_id and a task_id fields. They correspond to upstream_task and downstream_task ids of the dependency accordingly. Here is how to get a TaskDependency using a dependent_task_id and a task_id fields:

filters = [["dependent_task_id", "is", 72], ["task_id", "is", 75]]
result = sg.find_one('TaskDependency', filters)

Returns:

{'type': 'TaskDependency', 'id': 128}

Updating the Dependency type

When updating the dependency type for the existing dependencies, update the dependency_type field of the TaskDependency directly:

result = sg.update('TaskDependency', 128, {'dependency_type': 'start-to-start'})

Returns:

{'dependency_type': 'start-to-start', 'type': 'TaskDependency', 'id': 128}

Query Tasks with Dependency Fields

So now lets look at the Tasks we’ve created and their dependency-related fields:

filters = [
    ['entity', 'is', {'type':'Shot', 'id':860}]
]
fields = [
    'content',
    'start_date',
    'due_date',
    'upstream_tasks',
    'downstream_tasks',
    'dependency_violation',
    'pinned'
    ]
result = sg.find("Task", filters, fields)

Returns:

[{'content': 'Layout',
  'dependency_violation': False,
  'downstream_tasks': [{'type': 'Task', 'name': 'Anm', 'id': 557}],
  'due_date': '2010-05-05',
  'id': 556,
  'pinned': False,
  'start_date': '2010-04-28',
  'type': 'Task',
  'upstream_tasks': []},
 {'content': 'Anm',
  'dependency_violation': False,
  'downstream_tasks': [{'type': 'Task', 'name': 'FX', 'id': 558}],
  'due_date': '2010-05-12',
  'id': 557,
  'pinned': False,
  'start_date': '2010-05-06',
  'type': 'Task',
  'upstream_tasks': [{'type': 'Task', 'name': 'Layout', 'id': 556}]},
...

Note that we have also created additional Tasks for this Shot but we’re going to focus on these first two for simplicity.

Updating the End Date on a Task with Downstream Task Dependencies

If we update the due_date field on our “Layout” Task, we’ll see that the “Anm” Task dates will automatically get pushed back to keep the dependency satisfied:

result = sg.update('Task', 556, {'due_date': '2010-05-07'})

Returns:

[{'due_date': '2010-05-07', 'type': 'Task', 'id': 556}]

Our Tasks now look like this (notice the new dates on the “Anm” Task):

[{'content': 'Layout',
  'dependency_violation': False,
  'downstream_tasks': [{'type': 'Task', 'name': 'Anm', 'id': 557}],
  'due_date': '2010-05-07',
  'id': 556,
  'pinned': False,
  'start_date': '2010-04-28',
  'type': 'Task',
  'upstream_tasks': []},
 {'content': 'Anm',
  'dependency_violation': False,
  'downstream_tasks': [{'type': 'Task', 'name': 'FX', 'id': 558}],
  'due_date': '2010-05-14',
  'id': 557,
  'pinned': False,
  'start_date': '2010-05-10',
  'type': 'Task',
  'upstream_tasks': [{'type': 'Task', 'name': 'Layout', 'id': 556}]},
...

Creating a Dependency Violation by pushing up a Start Date

Task Dependencies can work nicely if you are pushing out an end date for a Task as it will just recalculate the dates for all of the dependent Tasks. But what if we push up the Start Date of our “Anm” Task to start before our “Layout” Task is scheduled to end?

result = sg.update('Task', 557, {'start_date': '2010-05-06'})

Returns:

[{'type': 'Task', 'start_date': '2010-05-06', 'id': 557}]

Our Tasks now look like this:

[{'content': 'Layout',
  'dependency_violation': False,
  'downstream_tasks': [{'type': 'Task', 'name': 'Anm', 'id': 557}],
  'due_date': '2010-05-07',
  'id': 556,
  'pinned': False,
  'start_date': '2010-04-28',
  'type': 'Task',
  'upstream_tasks': []},
 {'content': 'Anm',
  'dependency_violation': True,
  'downstream_tasks': [{'type': 'Task', 'name': 'FX', 'id': 558}],
  'due_date': '2010-05-12',
  'id': 557,
  'pinned': True,
  'start_date': '2010-05-06',
  'type': 'Task',
  'upstream_tasks': [{'type': 'Task', 'name': 'Layout', 'id': 556}]},
 ...

Because the “Anm” Task start_date depends on the due_date of the “Layout” Task, this change creates a dependency violation. The update succeeds, but Flow Production Tracking has also set the dependency_violation field to True and has also updated the pinned field to True.

The pinned field simply means that if the upstream Task(s) are moved, the “Anm” Task will no longer get moved with it. The dependency is still there (in upstream_tasks) but the Task is now “pinned” to those dates until the Dependency Violation is resolved.

Resolving a Dependency Violation by updating the Start Date

We don’t want that violation there. Let’s revert that change so the Start Date for “Anm” is after the End Date of “Layout”:

result = sg.update('Task', 557, {'start_date': '2010-05-10'})

Returns:

[{'type': 'Task', 'start_date': '2010-05-10', 'id': 557}]

Our Tasks now look like this:

[{'content': 'Layout',
  'dependency_violation': False,
  'downstream_tasks': [{'type': 'Task', 'name': 'Anm', 'id': 557}],
  'due_date': '2010-05-07',
  'id': 556,
  'pinned': False,
  'start_date': '2010-04-28',
  'type': 'Task',
  'upstream_tasks': []},
 {'content': 'Anm',
  'dependency_violation': False,
  'downstream_tasks': [{'type': 'Task', 'name': 'FX', 'id': 558}],
  'due_date': '2010-05-14',
  'id': 557,
  'pinned': True,
  'start_date': '2010-05-10',
  'type': 'Task',
  'upstream_tasks': [{'type': 'Task', 'name': 'Layout', 'id': 556}]},
 ...

The dependency_violation field has now been set back to False since there is no longer a violation. But notice that the pinned field is still True. We will have to manually update that if we want the Task to travel with its dependencies again:

result = sg.update('Task', 557, {'pinned': False})

Returns:

[{'pinned': False, 'type': 'Task', 'id': 557}]

Our Tasks now look like this:

[{'content': 'Layout',
  'dependency_violation': False,
  'downstream_tasks': [{'type': 'Task', 'name': 'Anm', 'id': 557}],
  'due_date': '2010-05-07',
  'id': 556,
  'pinned': False,
  'start_date': '2010-04-28',
  'type': 'Task',
  'upstream_tasks': []},
 {'content': 'Anm',
  'dependency_violation': False,
  'downstream_tasks': [{'type': 'Task', 'name': 'FX', 'id': 558}],
  'due_date': '2010-05-14',
  'id': 557,
  'pinned': False,
  'start_date': '2010-05-10',
  'type': 'Task',
  'upstream_tasks': [{'type': 'Task', 'name': 'Layout', 'id': 556}]},
 ...

Looks great. But that’s an annoying manual process. What if we want to just reset a Task so that it automatically gets updated so that the Start Date is after its dependent Tasks?

Updating the pinned field on a Task with a Dependency Violation

Let’s go back a couple of steps to where our “Anm” Task had a Dependency Violation because we had moved the Start Date up before the “Layout” Task End Date. Remember that the pinned field was also True. If we simply update the pinned field to be False, Flow Production Tracking will also automatically update the Task dates to satisfy the upstream dependencies and reset the dependency_violation value to False:

result = sg.update('Task', 557, {'pinned': False})

Returns:

[{'pinned': False, 'type': 'Task', 'id': 557}]

Our Tasks now look like this:

[{'content': 'Layout',
  'dependency_violation': False,
  'downstream_tasks': [{'type': 'Task', 'name': 'Anm', 'id': 557}],
  'due_date': '2010-05-07',
  'id': 556,
  'pinned': False,
  'start_date': '2010-04-28',
  'type': 'Task',
  'upstream_tasks': []},
 {'content': 'Anm',
  'dependency_violation': False,
  'downstream_tasks': [{'type': 'Task', 'name': 'FX', 'id': 558}],
  'due_date': '2010-05-14',
  'id': 557,
  'pinned': False,
  'start_date': '2010-05-10',
  'type': 'Task',
  'upstream_tasks': [{'type': 'Task', 'name': 'Layout', 'id': 556}]},
...

Notice by updating pinned to False, Flow Production Tracking also updated the start_date and due_date fields of our “Anm” Task so it will satisfy the upstream Task dependencies. And since that succeeded, the dependency_violation field has also been set to False

dependency_violation field is read-only

The dependency_violation field is the only dependency-related field that is read-only. Trying to modify it will generate a Fault:

result = sg.update('Task', 557, {'dependency_violation': False})

Returns:

# --------------------------------------------------------------------------------
# XMLRPC Fault 103:
# API update() Task.dependency_violation is read only:
# {"value"=>false, "field_name"=>"dependency_violation"}
# --------------------------------------------------------------------------------
# Traceback (most recent call last):
# ...