# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# Copyright (C) 2014-2020 GEM Foundation
#
# OpenQuake is free software: you can redistribute it and/or modify it
# under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# OpenQuake is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with OpenQuake. If not, see <http://www.gnu.org/licenses/>.
import collections
import tempfile
import logging
import os.path
import cProfile
import pstats
from openquake.baselib import performance, general, sap, datastore, parallel
from openquake.hazardlib import valid
from openquake.commonlib import readinput, oqvalidation, logs
from openquake.calculators import base, views
from openquake.server import dbserver
calc_path = None # set only when the flag --slowest is given
PStatData = collections.namedtuple(
'PStatData', 'ncalls tottime percall cumtime percall2 path')
oqvalidation.OqParam.calculation_mode.validator.choices = tuple(
base.calculators)
[docs]def get_pstats(pstatfile, n):
"""
Return profiling information as an RST table.
:param pstatfile: path to a .pstat file
:param n: the maximum number of stats to retrieve
"""
with tempfile.TemporaryFile(mode='w+') as stream:
ps = pstats.Stats(pstatfile, stream=stream)
ps.sort_stats('cumtime')
ps.print_stats(n)
stream.seek(0)
lines = list(stream)
for i, line in enumerate(lines):
if line.startswith(' ncalls'):
break
data = []
for line in lines[i + 2:]:
columns = line.split()
if len(columns) == 6:
data.append(PStatData(*columns))
rows = [(rec.ncalls, rec.cumtime, rec.path) for rec in data]
# here is an example of the expected output table:
# ====== ======= ========================================================
# ncalls cumtime path
# ====== ======= ========================================================
# 1 33.502 commands/run.py:77(_run)
# 1 33.483 calculators/base.py:110(run)
# 1 25.166 calculators/classical.py:115(execute)
# 1 25.104 baselib.parallel.py:249(apply_reduce)
# 1 25.099 calculators/classical.py:41(classical)
# 1 25.099 hazardlib/calc/hazard_curve.py:164(classical)
return views.rst_table(rows, header='ncalls cumtime path'.split())
[docs]def run2(job_haz, job_risk, calc_id, concurrent_tasks, pdb, loglevel,
exports, params):
"""
Run both hazard and risk, one after the other
"""
hcalc = base.calculators(readinput.get_oqparam(job_haz), calc_id)
hcalc.run(concurrent_tasks=concurrent_tasks, pdb=pdb,
exports=exports, **params)
hcalc.datastore.close()
hc_id = hcalc.datastore.calc_id
rcalc_id = logs.init(level=getattr(logging, loglevel.upper()))
oq = readinput.get_oqparam(job_risk, hc_id=hc_id)
rcalc = base.calculators(oq, rcalc_id)
rcalc.run(pdb=pdb, exports=exports, **params)
return rcalc
# run with processpool unless OQ_DISTRIBUTE is set to something else
def _run(job_inis, concurrent_tasks, calc_id, pdb, loglevel, hc, exports,
params):
global calc_path
assert len(job_inis) in (1, 2), job_inis
# set the logs first of all
calc_id = logs.init(calc_id, getattr(logging, loglevel.upper()))
# disable gzip_input
base.BaseCalculator.gzip_inputs = lambda self: None
with performance.Monitor('total runtime', measuremem=True) as monitor:
if os.environ.get('OQ_DISTRIBUTE') not in ('no', 'processpool'):
os.environ['OQ_DISTRIBUTE'] = 'processpool'
if len(job_inis) == 1: # run hazard or risk
if hc:
hc_id = hc[0]
rlz_ids = hc[1:]
else:
hc_id = None
rlz_ids = ()
oqparam = readinput.get_oqparam(job_inis[0], hc_id=hc_id)
# if not oqparam.csm_cache:
# oqparam.csm_cache = datastore.get_datadir()
if hc_id and hc_id < 0: # interpret negative calculation ids
calc_ids = datastore.get_calc_ids()
try:
hc_id = calc_ids[hc_id]
except IndexError:
raise SystemExit(
'There are %d old calculations, cannot '
'retrieve the %s' % (len(calc_ids), hc_id))
calc = base.calculators(oqparam, calc_id)
calc.run(concurrent_tasks=concurrent_tasks, pdb=pdb,
exports=exports, hazard_calculation_id=hc_id,
rlz_ids=rlz_ids)
else: # run hazard + risk
calc = run2(
job_inis[0], job_inis[1], calc_id, concurrent_tasks, pdb,
loglevel, exports, params)
logging.info('Total time spent: %s s', monitor.duration)
logging.info('Memory allocated: %s', general.humansize(monitor.mem))
print('See the output with silx view %s' % calc.datastore.filename)
calc_path, _ = os.path.splitext(calc.datastore.filename) # used below
return calc
[docs]@sap.script
def run(job_ini, slowest=False, hc=None, param='', concurrent_tasks=None,
exports='', loglevel='info', calc_id='nojob', pdb=None):
"""
Run a calculation bypassing the database layer
"""
dbserver.ensure_on()
if param:
params = oqvalidation.OqParam.check(
dict(p.split('=', 1) for p in param.split(',')))
else:
params = {}
if slowest:
prof = cProfile.Profile()
stmt = ('_run(job_ini, concurrent_tasks, calc_id, pdb, loglevel, hc, '
'exports, params)')
prof.runctx(stmt, globals(), locals())
pstat = calc_path + '.pstat'
prof.dump_stats(pstat)
print('Saved profiling info in %s' % pstat)
print(get_pstats(pstat, slowest))
return
try:
return _run(job_ini, concurrent_tasks, calc_id, pdb, loglevel,
hc, exports, params)
finally:
parallel.Starmap.shutdown()
run.arg('job_ini', 'calculation configuration file '
'(or files, space-separated)', nargs='+')
run.opt('slowest', 'profile and show the slowest operations', type=int)
run.opt('hc', 'previous calculation ID', type=valid.hazard_id)
run.opt('param', 'override parameter with the syntax NAME=VALUE,...')
run.opt('concurrent_tasks', 'hint for the number of tasks to spawn',
type=int)
run.opt('exports', 'export formats as a comma-separated string',
type=valid.export_formats)
run.opt('loglevel', 'logging level',
choices='debug info warn error critical'.split())
run.opt('calc_id', 'calculation ID (if "nojob" infer it)')
run.flg('pdb', 'enable post mortem debugging', '-d')