Source code for

# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# Copyright (C) 2014-2022 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
# 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 <>.

import collections
import tempfile
import logging
import os.path
import cProfile
import pstats

from openquake.baselib import performance, general
from openquake.hazardlib import valid
from openquake.commonlib import oqvalidation, logs, datastore, readinput
from openquake.calculators import base, views
from openquake.engine.engine import create_jobs, run_jobs
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(

[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) 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/ # 1 33.483 calculators/ # 1 25.166 calculators/ # 1 25.104 # 1 25.099 calculators/ # 1 25.099 hazardlib/calc/ return views.text_table(rows, header='ncalls cumtime path'.split())
# called when profiling def _run(job_ini, concurrent_tasks, pdb, reuse_input, loglevel, exports, params): global calc_path if 'hazard_calculation_id' in params: hc_id = int(params['hazard_calculation_id']) if hc_id < 0: # interpret negative calculation ids calc_ids = datastore.get_calc_ids() try: params['hazard_calculation_id'] = calc_ids[hc_id] except IndexError: raise SystemExit( 'There are %d old calculations, cannot ' 'retrieve the %s' % (len(calc_ids), hc_id)) else: params['hazard_calculation_id'] = hc_id dic = readinput.get_params(job_ini, params) # set the logs first of all log = logs.init("job", dic, getattr(logging, loglevel.upper())) # disable gzip_input base.BaseCalculator.gzip_inputs = lambda self: None with log, performance.Monitor('total runtime', measuremem=True) as monitor: calc = base.calculators(log.get_oqparam(), log.calc_id) if reuse_input: # enable caching calc.oqparam.cachedir = datastore.get_datadir(), pdb=pdb, exports=exports)'Total time spent: %s s', monitor.duration)'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]def main(job_ini, pdb=False, reuse_input=False, *, slowest: int = None, hc: int = None, param='', concurrent_tasks: int = None, exports: valid.export_formats = '', loglevel='info'): """ Run a calculation """ dbserver.ensure_on() if param: params = dict(p.split('=', 1) for p in param.split(',')) else: params = {} if hc: params['hazard_calculation_id'] = str(hc) if slowest: prof = cProfile.Profile() prof.runctx('_run(job_ini[0], 0, pdb, reuse_input, loglevel, ' 'exports, params)', globals(), locals()) pstat = calc_path + '.pstat' prof.dump_stats(pstat) print('Saved profiling info in %s' % pstat) print(get_pstats(pstat, slowest)) return if len(job_ini) == 1: return _run(job_ini[0], concurrent_tasks, pdb, reuse_input, loglevel, exports, params) jobs = create_jobs(job_ini, loglevel, hc_id=hc) for job in jobs: job.params.update(params) job.params['exports'] = ','.join(exports) run_jobs(jobs)
main.job_ini = dict(help='calculation configuration file ' '(or files, space-separated)', nargs='+') main.pdb = dict(help='enable post mortem debugging', abbrev='-d') main.reuse_input = dict(help='reuse source model and exposure') main.slowest = dict(help='profile and show the slowest operations') main.hc = dict(help='previous calculation ID') main.param = dict(help='override parameter with the syntax NAME=VALUE,...') main.concurrent_tasks = dict(help='hint for the number of tasks to spawn') main.exports = dict(help='export formats as a comma-separated string') main.loglevel = dict(help='logging level', choices='debug info warn error critical'.split())