def test_instance_yaml(docs_snippets_folder):
intance_yaml_folder = os.path.join(
docs_snippets_folder,
"deploying",
"concurrency_limits",
)
assert isinstance(
InstanceRef.from_dir(intance_yaml_folder).run_coordinator,
QueuedRunCoordinator)
def test_unique_value_instance_yaml(docs_snippets_folder):
intance_yaml_folder = os.path.join(
docs_snippets_folder,
"deploying",
"concurrency_limits",
)
assert isinstance(
InstanceRef.from_dir(
intance_yaml_folder,
config_filename="per-unique-value-dagster.yaml").run_coordinator,
QueuedRunCoordinator,
)
def test_nothing_new(mock_event_records):
mock_event_records.side_effect = get_mock_event_records([("comments", 1),
("stories", 2)])
with tempfile.TemporaryDirectory() as tmpdir_path:
context = SensorEvaluationContext(
instance_ref=InstanceRef.from_dir(tmpdir_path),
last_run_key="1|2",
last_completion_time=None,
cursor=None,
repository_name=None,
)
requests = story_recommender_on_hn_table_update.evaluate_tick(
context).run_requests
assert len(requests) == 0
def test_execution_plan_snapshot_backcompat():
src_dir = file_relative_path(__file__, "test_execution_plan_snapshots/")
snapshot_dirs = [
f for f in os.listdir(src_dir)
if not os.path.isfile(os.path.join(src_dir, f))
]
for snapshot_dir_path in snapshot_dirs:
print(f"Executing a saved run from {snapshot_dir_path}") # pylint: disable=print-call
with copy_directory(os.path.join(src_dir,
snapshot_dir_path)) as test_dir:
with DagsterInstance.from_ref(
InstanceRef.from_dir(test_dir)) as instance:
runs = instance.get_runs()
assert len(runs) == 1
run = runs[0]
assert run.status == PipelineRunStatus.NOT_STARTED
the_pipeline = InMemoryPipeline(dynamic_pipeline)
# First create a brand new plan from the pipeline and validate it
new_plan = create_execution_plan(the_pipeline,
run_config=run.run_config)
_validate_execution_plan(new_plan)
# Create a snapshot and rebuild it, validate the rebuilt plan
new_plan_snapshot = snapshot_from_execution_plan(
new_plan, run.pipeline_snapshot_id)
rebuilt_plan = ExecutionPlan.rebuild_from_snapshot(
"dynamic_pipeline", new_plan_snapshot)
_validate_execution_plan(rebuilt_plan)
# Then validate the plan built from the historical snapshot on the run
stored_snapshot = instance.get_execution_plan_snapshot(
run.execution_plan_snapshot_id)
rebuilt_plan = ExecutionPlan.rebuild_from_snapshot(
"dynamic_pipeline", stored_snapshot)
_validate_execution_plan(rebuilt_plan)
# Finally, execute the run (using the historical execution plan snapshot)
result = execute_run(the_pipeline,
run,
instance,
raise_on_error=True)
assert result.success
def dagster_instance(helm_postgres_url): # pylint: disable=redefined-outer-name
with tempfile.TemporaryDirectory() as tempdir:
with environ({"DAGSTER_HOME": tempdir}):
with DagsterInstance(
instance_type=InstanceType.PERSISTENT,
local_artifact_storage=LocalArtifactStorage(tempdir),
run_storage=PostgresRunStorage(helm_postgres_url),
event_storage=PostgresEventLogStorage(helm_postgres_url),
compute_log_manager=NoOpComputeLogManager(),
run_coordinator=DefaultRunCoordinator(),
run_launcher=ExplodingRunLauncher(), # use graphql to launch any runs
ref=InstanceRef.from_dir(tempdir),
) as instance:
yield instance
check_export_runs(instance)
def test_queued_runs(tmpdir, foo_pipeline_handle):
dagster_home_path = tmpdir.strpath
setup_instance(dagster_home_path)
with start_daemon():
instance_ref = InstanceRef.from_dir(dagster_home_path)
with DagsterInstance.from_ref(instance_ref) as instance:
run = create_run(instance, foo_pipeline_handle)
with external_pipeline_from_run(run) as external_pipeline:
instance.submit_run(run.run_id, external_pipeline)
poll_for_finished_run(instance, run.run_id)
logs = instance.all_logs(run.run_id)
assert_events_in_order(
logs,
["PIPELINE_ENQUEUED", "PIPELINE_DEQUEUED", "PIPELINE_SUCCESS"],
)
def dagster_instance_for_k8s_run_launcher(
helm_postgres_url_for_k8s_run_launcher,
): # pylint: disable=redefined-outer-name
tempdir = DagsterInstance.temp_storage()
instance_ref = InstanceRef.from_dir(tempdir)
with DagsterInstance(
instance_type=InstanceType.PERSISTENT,
local_artifact_storage=LocalArtifactStorage(tempdir),
run_storage=PostgresRunStorage(helm_postgres_url_for_k8s_run_launcher),
event_storage=PostgresEventLogStorage(helm_postgres_url_for_k8s_run_launcher),
schedule_storage=PostgresScheduleStorage(helm_postgres_url_for_k8s_run_launcher),
compute_log_manager=NoOpComputeLogManager(),
run_coordinator=DefaultRunCoordinator(),
run_launcher=ExplodingRunLauncher(),
ref=instance_ref,
) as instance:
yield instance
check_export_runs(instance)