def test_ix_attach_to(self, pipeline_settings, example_pipelines, tmpdir):
sparcc_params = setup_external(
pipeline_settings,
example_pipelines,
module="network_inference",
pipeline="network_inference.correlation.sparcc",
)
json_params = setup_internal(pipeline_settings, example_pipelines)
to_remove = []
for io_elem in json_params.input:
if io_elem.datatype in {"interaction_table"}:
to_remove.append(io_elem)
for remove in to_remove:
json_params.input.remove(remove)
json_params.input.add(
Input(datatype=remove.datatype, format=remove.format))
sparcc_process = Process(sparcc_params,
profile="local",
output_location=".")
json_process = Process(json_params,
profile="local",
output_location=".")
output_dir = pathlib.Path.cwd() / "tests/data"
sparcc_process.update_location(str(output_dir), "input")
sparcc_process.build(tmpdir)
json_process.attach_to(sparcc_process)
json_process.update_location(str(output_dir), "input")
with pytest.raises(FileNotFoundError):
json_process.build(tmpdir)
sparcc_process.run()
sparcc_process.wait()
json_process.build(tmpdir)
json_process.run()
json_process.wait()
def test_attach_to(self, pipeline_settings, example_pipelines, tmpdir):
previous_params = setup_internal(
pipeline_settings,
example_pipelines,
module="otu_processing",
pipeline="otu_processing.transform.normalize",
)
previous_process = Process(previous_params,
profile="local",
output_location=".")
curr_params = setup_internal(
pipeline_settings,
example_pipelines,
module="otu_processing",
pipeline="otu_processing.filter.group",
)
curr_process = Process(curr_params,
profile="local",
output_location=".")
output_dir = pathlib.Path.cwd() / "tests/data"
previous_process.update_location(str(output_dir), "input")
previous_process.build(tmpdir)
curr_process.attach_to(previous_process)
with pytest.raises(FileNotFoundError):
curr_process.build(tmpdir)
previous_process.run()
previous_process.output
curr_process.update_location(str(output_dir), "input")
curr_process.build(tmpdir)
curr_process.run()
def test_clean(self, pipeline_settings, example_pipelines, tmpdir):
params = setup_internal(
pipeline_settings,
example_pipelines,
module="otu_processing",
pipeline="otu_processing.filter.group",
)
process = Process(params, profile="local", output_location=".")
process_dir = tmpdir.mkdir("test_process_clean")
output_dir = pathlib.Path.cwd() / "tests/data"
process.update_location(str(output_dir), "input")
process.build(process_dir)
cmd = process.cmd
paths = [
p for p in str(cmd).split(" ")
if not p.startswith("-") and "/" in p
]
process.run()
process.wait()
for path in paths:
assert pathlib.Path(path).exists()
process.clean("all")
for path in paths:
assert not pathlib.Path(path).exists()
process.build(process_dir)
process.clean("work_dir")
for path in paths:
if "work" in path:
assert not pathlib.Path(path).exists()
else:
if not path.endswith(".log"):
assert pathlib.Path(path).exists()
def test_run(self, pipeline_settings, example_pipelines, tmpdir):
params = setup_external(
pipeline_settings,
example_pipelines,
module="network_inference",
pipeline="network_inference.correlation.sparcc",
)
process = Process(params, profile="local", output_location=".")
process_dir = tmpdir.mkdir("test_process_run")
output_dir = pathlib.Path.cwd() / "tests/data"
process.update_location(str(output_dir), "input")
process.build(process_dir)
process.run()
assert process.output
assert not process.error
process.log()
for output in process.params.output:
if "*" in str(output.location):
str_loc = str(output.location)
ind = str_loc.find("*")
files = list(pathlib.Path(str_loc[:ind]).glob(str_loc[ind:]))
assert len(files) > 0
else:
assert output.location.exists()