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113 lines
4.7 KiB
Python
113 lines
4.7 KiB
Python
"""Integration tests for the Pulsar embedded runner."""
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import os
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from sqlalchemy import select
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from galaxy import model
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from galaxy_test.base.populators import DatasetPopulator
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from galaxy_test.driver import integration_util
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SCRIPT_DIRECTORY = os.path.abspath(os.path.dirname(__file__))
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EMBEDDED_PULSAR_JOB_CONFIG_FILE = os.path.join(SCRIPT_DIRECTORY, "embedded_pulsar_job_conf.yml")
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class TestEmbeddedPulsarIntegrationInstance(integration_util.IntegrationTestCase):
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"""Describe a Galaxy test instance with embedded pulsar configured."""
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framework_tool_and_types = True
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dataset_populator: DatasetPopulator
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def setUp(self) -> None:
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super().setUp()
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self.dataset_populator = DatasetPopulator(self.galaxy_interactor)
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@classmethod
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def handle_galaxy_config_kwds(cls, config):
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super().handle_galaxy_config_kwds(config)
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config["job_config_file"] = EMBEDDED_PULSAR_JOB_CONFIG_FILE
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config["enable_celery_tasks"] = False
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config["metadata_strategy"] = "directory"
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config["cleanup_job"] = "never"
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def test_tool_eval_failure(self):
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with self.dataset_populator.test_history() as history_id:
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dataset = self.dataset_populator.new_dataset(history_id=history_id, content="ABC", ext="tabular")
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self.dataset_populator.run_tool(
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"gx_data_column",
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inputs={"ref_parameter": {"src": "hda", "id": dataset["id"]}, "parameter": 2},
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history_id=history_id,
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)
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failed_dataset = self.dataset_populator.get_history_dataset_details(history_id, wait=True, assert_ok=False)
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assert failed_dataset["state"] == "error"
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assert failed_dataset["misc_info"] == "Parameter 'parameter': requires a value, but no legal values defined"
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def test_collection_directory_discovery_does_not_collect_working_dir_files(self):
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"""Test that collection discovery with directory attribute doesn't collect files from working directory root."""
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with self.dataset_populator.test_history() as history_id:
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# Create input dataset
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input_content = "101\t1\n101\t2\n101\t3\n1334\t1\n1334\t10\n1334\t11\n1334\t12\n1334\t13\n1334\t2\n"
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dataset = self.dataset_populator.new_dataset(history_id=history_id, content=input_content, ext="tabular")
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# Run the tool
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run_response = self.dataset_populator.run_tool(
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"collection_split_on_column",
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inputs={"input1": {"src": "hda", "id": dataset["id"]}},
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history_id=history_id,
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)
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# Wait for job to complete
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self.dataset_populator.wait_for_job(run_response["jobs"][0]["id"])
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# Get the job from the database
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job_id = run_response["jobs"][0]["id"]
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job_id_decoded = self._app.security.decode_id(job_id)
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sa_session = self._app.model.session
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job = sa_session.scalars(select(model.Job).filter_by(id=job_id_decoded)).one()
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# Get the job working directory using the object store
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job_working_directory = self._app.object_store.get_filename(
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job, base_dir="job_work", dir_only=True, obj_dir=True
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)
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assert job_working_directory is not None, "Could not determine job working directory"
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# Verify that do_not_collect_me.txt does NOT exist in the Galaxy job working directory
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# This file is created in the working directory but should not be staged back because
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# the collection discovery specifies directory="outputs"
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do_not_collect_path = os.path.join(job_working_directory, "working", "do_not_collect_me.txt")
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assert not os.path.exists(do_not_collect_path), (
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f"File {do_not_collect_path} should not have been collected from Pulsar, "
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"but it exists in Galaxy's job working directory"
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)
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instance = integration_util.integration_module_instance(TestEmbeddedPulsarIntegrationInstance)
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test_tools = integration_util.integration_tool_runner(
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[
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"cat_default",
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"cat_user_defined",
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"collection_nested_default",
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"collection_creates_dynamic_nested_from_json",
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"composite",
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"simple_constructs",
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"multi_data_param",
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"output_filter",
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"vcf_bgzip_test",
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"environment_variables",
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"multi_output_assign_primary_ext_dbkey",
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"job_properties",
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"strict_shell",
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"tool_provided_metadata_9",
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"simple_constructs_y",
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"composite_output",
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"composite_output_tests",
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"detect_errors",
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"tool_directory_copy",
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"metadata_columns",
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"create_directory_index",
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"collection_split_on_column",
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]
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)
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