def affected_wf_module_delta_ids(
cls, workflow: Workflow, old_slugs: List[str],
new_slugs: List[str]) -> List[Tuple[int, int]]:
"""
Find WfModule+Delta IDs whose output may change with this reordering.
Reordering tabs changes the ordering of 'Multitab' params. Any WfModule
with a 'Multitab' param can change as a result of this delta.
There are very few 'Multitab' params in the wild: as of 2019-02-12, the
only one is in "concattabs". TODO optimize this method to look one
level deep for _only_ 'Multitab' params that depend on the changed
ordering, not 'Tab' params, essentially making ReorderTabsCommand _not_
change any WfModules unless there's a "concattabs" module.
"""
# Calculate `moved_slugs`: just the slugs whose `position` changed.
#
# There's no need to re-render a WfModule that only depends on tabs
# whose `position`s _haven't_ changed: its input tab order certainly
# hasn't changed.
first_change_index = None
last_change_index = None
for i, old_slug_and_new_slug in enumerate(zip(old_slugs, new_slugs)):
old_slug, new_slug = old_slug_and_new_slug
if old_slug != new_slug:
if first_change_index is None:
first_change_index = i
last_change_index = i
moved_slugs = set(old_slugs[first_change_index:last_change_index + 1])
# Figure out which params depend on those.
graph = DependencyGraph.load_from_workflow(workflow)
wf_module_ids = graph.get_step_ids_depending_on_tab_slugs(moved_slugs)
q = models.Q(id__in=wf_module_ids)
return cls.q_to_wf_module_delta_ids(q)
def test_read_graph_happy_path(self):
workflow = Workflow.objects.create()
tab1 = workflow.tabs.create(position=0, slug="tab-1")
tab2 = workflow.tabs.create(position=1, slug="tab-2")
ModuleVersion.create_or_replace_from_spec(
{
"id_name": "simple",
"name": "Simple",
"category": "Add data",
"parameters": [{"id_name": "str", "type": "string"}],
}
)
ModuleVersion.create_or_replace_from_spec(
{
"id_name": "tabby",
"name": "Tabby",
"category": "Add data",
"parameters": [{"id_name": "tab", "type": "tab"}],
}
)
wfm1 = tab1.wf_modules.create(
order=0, slug="step-1", module_id_name="simple", params={"str": "A"}
)
wfm2 = tab1.wf_modules.create(
order=1, slug="step-2", module_id_name="tabby", params={"tab": "tab-2"}
)
wfm3 = tab2.wf_modules.create(
order=0, slug="step-3", module_id_name="simple", params={"str": "B"}
)
graph = DependencyGraph.load_from_workflow(workflow)
self.assertEqual(
graph.tabs,
[
DependencyGraph.Tab("tab-1", [wfm1.id, wfm2.id]),
DependencyGraph.Tab("tab-2", [wfm3.id]),
],
)
self.assertEqual(
graph.steps,
{
wfm1.id: DependencyGraph.Step(set()),
wfm2.id: DependencyGraph.Step(set(["tab-2"])),
wfm3.id: DependencyGraph.Step(set()),
},
)
def test_read_graph_happy_path(self):
workflow = Workflow.objects.create()
tab1 = workflow.tabs.create(position=0, slug="tab-1")
tab2 = workflow.tabs.create(position=1, slug="tab-2")
create_module_zipfile(
"simple",
spec_kwargs={"parameters": [{
"id_name": "str",
"type": "string"
}]})
create_module_zipfile(
"tabby",
spec_kwargs={"parameters": [{
"id_name": "tab",
"type": "tab"
}]})
step1 = tab1.wf_modules.create(order=0,
slug="step-1",
module_id_name="simple",
params={"str": "A"})
step2 = tab1.wf_modules.create(order=1,
slug="step-2",
module_id_name="tabby",
params={"tab": "tab-2"})
step3 = tab2.wf_modules.create(order=0,
slug="step-3",
module_id_name="simple",
params={"str": "B"})
self.kernel.migrate_params.side_effect = lambda m, p: p # return input
with self.assertLogs(level=logging.INFO):
graph = DependencyGraph.load_from_workflow(workflow)
self.assertEqual(
graph.tabs,
[
DependencyGraph.Tab("tab-1", [step1.id, step2.id]),
DependencyGraph.Tab("tab-2", [step3.id]),
],
)
self.assertEqual(
graph.steps,
{
step1.id: DependencyGraph.Step(set()),
step2.id: DependencyGraph.Step(set(["tab-2"])),
step3.id: DependencyGraph.Step(set()),
},
)
def affected_steps_from_tab(self, tab: "Tab") -> Q:
"""Filter for Steps depending on `tab`.
In other words: all Steps that use `tab` in a 'tab' parameter, plus
all Steps that depend on them.
This uses the tab's workflow's `DependencyGraph`.
"""
graph = DependencyGraph.load_from_workflow(tab.workflow)
tab_slug = tab.slug
step_ids = graph.get_step_ids_depending_on_tab_slug(tab_slug)
# You'd _think_ a Delta could change the dependency graph in a way we
# can't detect. But [adamhooper, 2019-02-07] I don't think it can. In
# particular, if this Delta is about to create or fix a cycle, then all
# the nodes in the cycle are there both before _and_ after the change.
#
# So assume `step_ids` is complete here. If we notice some modules
# not updating correctly, we'll have to revisit this. I haven't proved
# anything, and I don't know whether future Deltas might break this
# assumption.
return Q(id__in=step_ids)