def test_report_invalid_file(invalid_filepath):
# verify appropriate error handling for
# provision of an invalid file path to
# DarshanReport
with pytest.raises(RuntimeError, match='Failed to open file'):
darshan.DarshanReport(invalid_filepath)
def test_metadata():
"""Sample for an expected property in counters."""
report = darshan.DarshanReport("tests/input/sample.darshan")
# check a metadata field
assert 4478544 == report.metadata['job']['jobid']
def test_load_records():
"""Test if loaded records match."""
report = darshan.DarshanReport("tests/input/sample.darshan")
report.mod_read_all_records("POSIX")
assert 1 == len(report.data['records']['POSIX'])
def test_modules():
"""Sample for an expected number of modules."""
report = darshan.DarshanReport("tests/input/sample.darshan")
# check if number of modules matches
assert 4 == len(report.modules)
assert 154 == report.modules['MPI-IO']['len']
def test_unsupported_record_load(caplog, unsupported_record):
# check for appropriate logger warning when attempting to
# load unsupported record
report = darshan.DarshanReport("tests/input/sample.darshan")
report.mod_read_all_records(mod=unsupported_record)
for record in caplog.records:
assert 'Currently unsupported' in record.message
assert unsupported_record in record.message
def test_internal_references():
"""
Test if the reference ids match. This tests mainly serves to make
regressions verbose when the behavior is changed.
"""
report = darshan.DarshanReport()
# check the convienience refs are working fine
check = id(report.records) == id(report.data['records'])
assert check is True
def main(args=None):
if args is None:
parser = argparse.ArgumentParser(description='')
setup_parser(parser)
args = parser.parse_args()
if args.debug:
print(args)
report = darshan.DarshanReport(args.input,
read_all=True) # Default behavior
print(report.to_json())
def main(args=None):
parser = argparse.ArgumentParser(description='')
parser.add_argument('input',
help='darshan log file',
nargs='?',
default='ior_hdf5_example.darshan')
parser.add_argument('--debug', help='', action='store_true')
args = parser.parse_args()
if args.debug:
print(args)
report = darshan.DarshanReport(args.input, read_all=True, dtype="numpy")
print(report.to_json())
def main(args=None):
if args is None:
parser = argparse.ArgumentParser(description='')
setup_parser(parser)
args = parser.parse_args()
if args.debug:
print(args)
report = darshan.DarshanReport(args.input, read_all=True) # Default behavior
for nrec, path in report.name_records.items():
print("{:<20} => {}".format(nrec, path))
def test_deepcopy_fidelity_darshan_report(key, subkey):
# regression guard for the __deepcopy__() method
# of DarshanReport class
# note that to_numpy() also performs a deepcopy
report = darshan.DarshanReport("tests/input/sample.darshan")
report_deepcopy = copy.deepcopy(report)
# the deepcopied records should be identical
# within floating point tolerance
assert_allclose(report_deepcopy.data['records'][key].to_numpy()[0][subkey],
report.data['records'][key].to_numpy()[0][subkey])
# a deepcopy should not share memory bounds
# with the original object (or deepcopies thereof)
assert not np.may_share_memory(
report_deepcopy.data['records'][key].to_numpy()[0][subkey],
report.data['records'][key].to_numpy()[0][subkey])
def test_info_contents(capsys):
# regression guard for the output from the info()
# method of DarshanReport
report = darshan.DarshanReport("tests/input/sample.darshan")
report.info()
captured = capsys.readouterr()
expected_keys = [
'Times', 'Executable', 'Processes', 'JobID', 'UID', 'Modules in Log',
'Loaded Records', 'Name Records', 'Darshan/Hints', 'DarshanReport'
]
expected_values = ['2048', '4478544', '69615']
expected_strings = expected_keys + expected_values
for expected_string in expected_strings:
assert expected_string in captured.out
def test_json_fidelity():
# regression test for provision of appropriate
# data by to_json() method of DarshanReport class
report = darshan.DarshanReport("tests/input/sample.darshan")
actual_json = report.to_json()
for expected_key in [
"version", "metadata", "job", "uid", "start_time", "end_time",
"nprocs"
]:
assert expected_key in actual_json
for expected_value in [
'69615', '1490000867', '1490000983', '2048', 'lustre', 'dvs',
'rootfs'
]:
assert expected_value in actual_json
#!/usr/bin/env python3
import darshan
r = darshan.DarshanReport("ior_hdf5_example.darshan")
r.info()
#!/usr/bin/env python3
import darshan
from darshan.experimental.plots.matplotlib import *
darshan.enable_experimental()
r = darshan.DarshanReport("ior_hdf5_example.darshan", dtype="numpy")
plot_opcounts(r).show()
