def job_from_file_lite(cfg_file, username, log_level='info', exports='',
**extras):
"""
Create a full job profile from a job config file.
:param str cfg_file:
Path to the job.ini files.
:param str username:
The user who will own this job profile and all results.
:param str log_level:
Desired log level.
:param exports:
Comma-separated sting of desired export types.
:params extras:
Extra parameters (used only in the tests to override the params)
:returns:
:class:`openquake.engine.db.models.OqJob` object
:raises:
`RuntimeError` if the input job configuration is not valid
"""
from openquake.commonlib.calculators import base
# create the current job
job = create_job(user_name=username, log_level=log_level)
models.JobStats.objects.create(oq_job=job)
with logs.handle(job, log_level):
# read calculation params and create the calculation profile
params = readinput.get_params([cfg_file])
params.update(extras)
# build and validate an OqParam object
oqparam = readinput.get_oqparam(params, calculators=base.calculators)
job.save_params(vars(oqparam))
job.save()
return job
def run_calc(job, log_level, log_file, exports):
"""
Run a calculation.
:param job:
:class:`openquake.engine.db.model.OqJob` instance
:param str log_level:
The desired logging level. Valid choices are 'debug', 'info',
'progress', 'warn', 'error', and 'critical'.
:param str log_file:
Complete path (including file name) to file where logs will be written.
If `None`, logging will just be printed to standard output.
:param exports:
A comma-separated string of export types.
"""
# let's import the calculator classes here, when they are needed
# the reason is that the command `$ oq-engine --upgrade-db`
# does not need them and would raise strange errors during installation
# time if the PYTHONPATH is not set and commonlib is not visible
from openquake.engine.calculators import calculators
# first of all check the database version and exit if the db is outdated
upgrader.check_versions(django_db.connections['admin'])
calculator = calculators(job)
with logs.handle(job, log_level, log_file), job_stats(job): # run the job
_do_run_calc(calculator, exports)
return calculator
def wrapped(*args):
"""
Initialize logs, make sure the job is still running, and run the task
code surrounded by a try-except. If any error occurs, log it as a
critical failure.
"""
# the last argument is assumed to be a monitor
monitor = args[-1]
job = models.OqJob.objects.get(id=monitor.job_id)
if job.is_running is False:
# the job was killed, it is useless to run the task
raise JobNotRunning(monitor.job_id)
# it is important to save the task id soon, so that
# the revoke functionality can work
with monitor('storing task id', task=tsk, autoflush=True):
pass
with logs.handle(job):
check_mem_usage() # warn if too much memory is used
# run the task
try:
total = 'total ' + task_func.__name__
with monitor(total, task=tsk, autoflush=True):
return task_func(*args)
finally:
# save on the db
CacheInserter.flushall()
# the task finished, we can remove from the performance
# table the associated row 'storing task id'
models.Performance.objects.filter(
oq_job=job,
operation='storing task id',
task_id=tsk.request.id).delete()
def wrapped(*args):
"""
Initialize logs, make sure the job is still running, and run the task
code surrounded by a try-except. If any error occurs, log it as a
critical failure.
"""
# the last argument is assumed to be a monitor
monitor = args[-1]
job = models.OqJob.objects.get(id=monitor.job_id)
if job.is_running is False:
# the job was killed, it is useless to run the task
raise JobNotRunning(monitor.job_id)
# it is important to save the task id soon, so that
# the revoke functionality can work
with monitor("storing task id", task=tsk, autoflush=True):
pass
with logs.handle(job):
check_mem_usage() # warn if too much memory is used
# run the task
try:
total = "total " + task_func.__name__
with monitor(total, task=tsk):
with GroundShakingIntensityModel.forbid_instantiation():
return task_func(*args)
finally:
# save on the db
CacheInserter.flushall()
# the task finished, we can remove from the performance
# table the associated row 'storing task id'
models.Performance.objects.filter(
oq_job=job, operation="storing task id", task_id=tsk.request.id
).delete()
def run_calc(job_id,
oqparam,
log_level,
log_file,
exports,
hazard_calculation_id=None):
"""
Run a calculation.
:param job_id:
ID of the current job
:param oqparam:
:class:`openquake.commonlib.oqvalidation.OqParam` instance
:param str log_level:
The desired logging level. Valid choices are 'debug', 'info',
'progress', 'warn', 'error', and 'critical'.
:param str log_file:
Complete path (including file name) to file where logs will be written.
If `None`, logging will just be printed to standard output.
:param exports:
A comma-separated string of export types.
"""
monitor = Monitor('total runtime', measuremem=True)
with logs.handle(job_id, log_level, log_file): # run the job
if USE_CELERY and os.environ.get('OQ_DISTRIBUTE') == 'celery':
set_concurrent_tasks_default()
calc = base.calculators(oqparam, monitor, calc_id=job_id)
tb = 'None\n'
try:
_do_run_calc(calc, exports, hazard_calculation_id)
logs.dbcmd('finish', job_id, 'complete')
expose_outputs(calc.datastore)
records = views.performance_view(calc.datastore)
logs.dbcmd('save_performance', job_id, records)
calc.datastore.close()
logs.LOG.info('Calculation %d finished correctly in %d seconds',
job_id, calc.monitor.duration)
except:
tb = traceback.format_exc()
try:
logs.LOG.critical(tb)
logs.dbcmd('finish', job_id, 'failed')
except: # an OperationalError may always happen
sys.stderr.write(tb)
raise
finally:
# if there was an error in the calculation, this part may fail;
# in such a situation, we simply log the cleanup error without
# taking further action, so that the real error can propagate
try:
if USE_CELERY:
celery_cleanup(TERMINATE, parallel.TaskManager.task_ids)
except:
# log the finalization error only if there is no real error
if tb == 'None\n':
logs.LOG.error('finalizing', exc_info=True)
return calc
def run_calc(job_id, oqparam, log_level, log_file, exports,
hazard_calculation_id=None):
"""
Run a calculation.
:param job_id:
ID of the current job
:param oqparam:
:class:`openquake.commonlib.oqvalidation.OqParam` instance
:param str log_level:
The desired logging level. Valid choices are 'debug', 'info',
'progress', 'warn', 'error', and 'critical'.
:param str log_file:
Complete path (including file name) to file where logs will be written.
If `None`, logging will just be printed to standard output.
:param exports:
A comma-separated string of export types.
"""
monitor = Monitor('total runtime', measuremem=True)
with logs.handle(job_id, log_level, log_file): # run the job
if USE_CELERY and os.environ.get('OQ_DISTRIBUTE') == 'celery':
set_concurrent_tasks_default()
calc = base.calculators(oqparam, monitor, calc_id=job_id)
tb = 'None\n'
try:
logs.dbcmd('set_status', job_id, 'executing')
_do_run_calc(calc, exports, hazard_calculation_id)
expose_outputs(calc.datastore)
records = views.performance_view(calc.datastore)
logs.dbcmd('save_performance', job_id, records)
calc.datastore.close()
logs.LOG.info('Calculation %d finished correctly in %d seconds',
job_id, calc.monitor.duration)
logs.dbcmd('finish', job_id, 'complete')
except:
tb = traceback.format_exc()
try:
logs.LOG.critical(tb)
logs.dbcmd('finish', job_id, 'failed')
except: # an OperationalError may always happen
sys.stderr.write(tb)
raise
finally:
# if there was an error in the calculation, this part may fail;
# in such a situation, we simply log the cleanup error without
# taking further action, so that the real error can propagate
try:
if USE_CELERY:
celery_cleanup(TERMINATE, parallel.TaskManager.task_ids)
except:
# log the finalization error only if there is no real error
if tb == 'None\n':
logs.LOG.error('finalizing', exc_info=True)
return calc
def run_calc(job, log_level, log_file, exports, lite=False):
"""
Run a calculation.
:param job:
:class:`openquake.engine.db.model.OqJob` instance
:param str log_level:
The desired logging level. Valid choices are 'debug', 'info',
'progress', 'warn', 'error', and 'critical'.
:param str log_file:
Complete path (including file name) to file where logs will be written.
If `None`, logging will just be printed to standard output.
:param exports:
A comma-separated string of export types.
:param lite:
Flag set when the oq-lite calculators are used
"""
# let's import the calculator classes here, when they are needed;
# the reason is that the command `$ oq-engine --upgrade-db`
# does not need them and would raise strange errors during installation
# time if the PYTHONPATH is not set and commonlib is not visible
if lite:
calc_dir = os.path.join(datastore.DATADIR, 'calc_%d' % job.id)
if os.path.exists(calc_dir):
os.rename(calc_dir, calc_dir + '.bak')
print 'Generated %s.bak' % calc_dir
from openquake.commonlib.calculators import base
calculator = base.calculators(job.get_oqparam(), calc_id=job.id)
calculator.job = job
calculator.monitor = EnginePerformanceMonitor('', job.id)
else:
from openquake.engine.calculators import calculators
calculator = calculators(job)
# first of all check the database version and exit if the db is outdated
upgrader.check_versions(django_db.connections['admin'])
with logs.handle(job, log_level, log_file), job_stats(job): # run the job
try:
_do_run_calc(calculator, exports)
except:
tb = traceback.format_exc()
logs.LOG.critical(tb)
raise
return calculator
def job_from_files(cfg_files,
username,
log_level='info',
exports='',
**extras):
"""
Create a full job profile from a job config file.
:param str cfg_files_path:
Path to the job.ini files.
:param str username:
The user who will own this job profile and all results.
:param str log_level:
Desired log level.
:param exports:
Comma-separated sting of desired export types.
:params extras:
Extra parameters (used only in the tests to override the params)
:returns:
:class:`openquake.engine.db.models.OqJob` object
:raises:
`RuntimeError` if the input job configuration is not valid
"""
from openquake.commonlib.calculators import base
# create the current job
job = create_job(user_name=username, log_level=log_level)
models.JobStats.objects.create(oq_job=job)
with logs.handle(job, log_level):
# read calculation params and create the calculation profile
params = readinput.get_params(cfg_files)
params['hazard_output_id'] = None
params['hazard_calculation_id'] = None
params.update(extras)
# build and validate an OqParam object
oqparam = readinput.get_oqparam(params, calculators=base.calculators)
oqparam.concurrent_tasks = int(config.get('celery',
'concurrent_tasks'))
job.save_params(vars(oqparam))
job.save()
return job
def run_calc(job, log_level, log_file, exports, lite=False):
"""
Run a calculation.
:param job:
:class:`openquake.engine.db.model.OqJob` instance
:param str log_level:
The desired logging level. Valid choices are 'debug', 'info',
'progress', 'warn', 'error', and 'critical'.
:param str log_file:
Complete path (including file name) to file where logs will be written.
If `None`, logging will just be printed to standard output.
:param exports:
A comma-separated string of export types.
:param lite:
Flag set when the oq-lite calculators are used
"""
# let's import the calculator classes here, when they are needed
# the reason is that the command `$ oq-engine --upgrade-db`
# does not need them and would raise strange errors during installation
# time if the PYTHONPATH is not set and commonlib is not visible
if lite:
from openquake.commonlib.calculators import base
calculator = base.calculators(job.get_oqparam())
calculator.job = job
calculator.monitor = EnginePerformanceMonitor('', job.id)
else:
from openquake.engine.calculators import calculators
calculator = calculators(job)
# first of all check the database version and exit if the db is outdated
upgrader.check_versions(django_db.connections['admin'])
with logs.handle(job, log_level, log_file), job_stats(job): # run the job
try:
_do_run_calc(calculator, exports)
except:
tb = traceback.format_exc()
logs.LOG.critical(tb)
raise
return calculator
def job_from_file(cfg_file_path, username, log_level='info', exports='',
hazard_output_id=None, hazard_calculation_id=None, **extras):
"""
Create a full job profile from a job config file.
:param str cfg_file_path:
Path to the job.ini.
:param str username:
The user who will own this job profile and all results.
:param str log_level:
Desired log level.
:param exports:
Comma-separated sting of desired export types.
:param int hazard_output_id:
ID of a hazard output to use as input to this calculation. Specify
this xor ``hazard_calculation_id``.
:param int hazard_calculation_id:
ID of a complete hazard job to use as input to this
calculation. Specify this xor ``hazard_output_id``.
:params extras:
Extra parameters (used only in the tests to override the params)
:returns:
:class:`openquake.engine.db.models.OqJob` object
:raises:
`RuntimeError` if the input job configuration is not valid
"""
assert os.path.exists(cfg_file_path), cfg_file_path
from openquake.engine.calculators import calculators
# determine the previous hazard job, if any
if hazard_calculation_id:
haz_job = models.OqJob.objects.get(pk=hazard_calculation_id)
elif hazard_output_id: # extract the hazard job from the hazard_output_id
haz_job = models.Output.objects.get(pk=hazard_output_id).oq_job
else:
haz_job = None # no previous hazard job
# create the current job
job = prepare_job(user_name=username, log_level=log_level)
models.JobStats.objects.create(oq_job=job)
# read calculation params and create the calculation profile
with logs.handle(job, log_level):
oqparam = readinput.get_oqparam(cfg_file_path, calculators)
oqparam.hazard_calculation_id = \
haz_job.id if haz_job and not hazard_output_id else None
oqparam.hazard_output_id = hazard_output_id
vars(oqparam).update(extras)
if haz_job: # for risk calculations
check_hazard_risk_consistency(haz_job, oqparam.calculation_mode)
if haz_job.user_name != username:
logs.LOG.warn(
'You are using a hazard calculation ran by %s',
haz_job.user_name)
if oqparam.hazard_output_id and getattr(
oqparam, 'quantile_loss_curves', False):
logs.LOG.warn(
'quantile_loss_curves is on, but you passed a single hazard '
'output: the statistics will not be computed')
params = vars(oqparam).copy()
if 'quantile_loss_curves' not in params:
params['quantile_loss_curves'] = []
if 'poes_disagg' not in params:
params['poes_disagg'] = []
if 'sites_disagg' not in params:
params['sites_disagg'] = []
if 'specific_assets' not in params:
params['specific_assets'] = []
if 'conditional_loss_poes' not in params:
params['conditional_loss_poes'] = []
if haz_job:
params['hazard_calculation_id'] = haz_job.id
job.save_params(params)
if hazard_output_id is None and hazard_calculation_id is None:
# this is a hazard calculation, not a risk one
del params['hazard_calculation_id']
del params['hazard_output_id']
else: # this is a risk calculation
job.hazard_calculation = haz_job
job.save()
return job
def job_from_file(cfg_file_path, username, log_level='info', exports='',
hazard_output_id=None, hazard_calculation_id=None, **extras):
"""
Create a full job profile from a job config file.
:param str cfg_file_path:
Path to the job.ini.
:param str username:
The user who will own this job profile and all results.
:param str log_level:
Desired log level.
:param exports:
Comma-separated sting of desired export types.
:param int hazard_output_id:
ID of a hazard output to use as input to this calculation. Specify
this xor ``hazard_calculation_id``.
:param int hazard_calculation_id:
ID of a complete hazard job to use as input to this
calculation. Specify this xor ``hazard_output_id``.
:params extras:
Extra parameters (used only in the tests to override the params)
:returns:
:class:`openquake.engine.db.models.OqJob` object
:raises:
`RuntimeError` if the input job configuration is not valid
"""
assert os.path.exists(cfg_file_path), cfg_file_path
from openquake.engine.calculators import calculators
# determine the previous hazard job, if any
if hazard_calculation_id:
haz_job = models.OqJob.objects.get(pk=hazard_calculation_id)
elif hazard_output_id: # extract the hazard job from the hazard_output_id
haz_job = models.Output.objects.get(pk=hazard_output_id).oq_job
else:
haz_job = None # no previous hazard job
# create the current job
job = create_job(user_name=username, log_level=log_level)
models.JobStats.objects.create(oq_job=job)
with logs.handle(job, log_level):
# read calculation params and create the calculation profile
params = readinput.get_params([cfg_file_path])
# TODO: improve the logic before; it is very hackish we should
# change the call in server.views.submit_job to pass the temporary dir
if not exports: # when called from the engine server
# ignore the user-provided export_dir: the engine server will
# export on demand with its own mechanism on a temporary directory
params['export_dir'] = tempfile.gettempdir()
params.update(extras)
if haz_job: # for risk calculations
calcmode = params['calculation_mode']
check_hazard_risk_consistency(haz_job, calcmode)
if haz_job.user_name != username:
logs.LOG.warn(
'You are using a hazard calculation ran by %s',
haz_job.user_name)
if hazard_output_id and params.get('quantile_loss_curves'):
logs.LOG.warn(
'quantile_loss_curves is on, but you passed a single '
'hazard output: the statistics will not be computed')
# build and validate an OqParam object
oqparam = readinput.get_oqparam(params, calculators=calculators)
oqparam.hazard_calculation_id = \
haz_job.id if haz_job and not hazard_output_id else None
oqparam.hazard_output_id = hazard_output_id
params = vars(oqparam).copy()
if haz_job:
params['hazard_calculation_id'] = haz_job.id
if hazard_output_id is None and hazard_calculation_id is None:
# this is a hazard calculation, not a risk one
job.save_params(params)
del params['hazard_calculation_id']
del params['hazard_output_id']
else: # this is a risk calculation
if 'maximum_distance' in params:
raise NameError(
'The name of the parameter `maximum_distance` for risk '
'calculators has changed.\nIt is now `asset_hazard_distance`. '
'Please change your risk .ini file.\nNB: do NOT '
'change the maximum_distance in the hazard .ini file!')
job.hazard_calculation = haz_job
hc = haz_job.get_oqparam()
# copy the non-conflicting hazard parameters in the risk parameters
for name, value in hc:
if name not in params:
params[name] = value
params['hazard_investigation_time'] = hc.investigation_time
params['hazard_imtls'] = dict(hc.imtls)
cfd = hc.continuous_fragility_discretization
if cfd and cfd != oqparam.continuous_fragility_discretization:
raise RuntimeError(
'The hazard parameter continuous_fragility_discretization '
'was %d but the risk one is %d' % (
hc.continuous_fragility_discretization,
oqparam.continuous_fragility_discretization))
job.save_params(params)
job.save()
return job
def job_from_file(cfg_file_path,
username,
log_level='info',
exports='',
hazard_output_id=None,
hazard_calculation_id=None,
**extras):
"""
Create a full job profile from a job config file.
:param str cfg_file_path:
Path to the job.ini.
:param str username:
The user who will own this job profile and all results.
:param str log_level:
Desired log level.
:param exports:
Comma-separated sting of desired export types.
:param int hazard_output_id:
ID of a hazard output to use as input to this calculation. Specify
this xor ``hazard_calculation_id``.
:param int hazard_calculation_id:
ID of a complete hazard job to use as input to this
calculation. Specify this xor ``hazard_output_id``.
:params extras:
Extra parameters (used only in the tests to override the params)
:returns:
:class:`openquake.engine.db.models.OqJob` object
:raises:
`RuntimeError` if the input job configuration is not valid
"""
assert os.path.exists(cfg_file_path), cfg_file_path
from openquake.engine.calculators import calculators
# determine the previous hazard job, if any
if hazard_calculation_id:
haz_job = models.OqJob.objects.get(pk=hazard_calculation_id)
elif hazard_output_id: # extract the hazard job from the hazard_output_id
haz_job = models.Output.objects.get(pk=hazard_output_id).oq_job
else:
haz_job = None # no previous hazard job
# create the current job
job = create_job(user_name=username, log_level=log_level)
models.JobStats.objects.create(oq_job=job)
with logs.handle(job, log_level):
# read calculation params and create the calculation profile
params = readinput.get_params([cfg_file_path])
# TODO: improve the logic before; it is very hackish we should
# change the call in server.views.submit_job to pass the temporary dir
if not exports: # when called from the engine server
# ignore the user-provided export_dir: the engine server will
# export on demand with its own mechanism on a temporary directory
params['export_dir'] = tempfile.gettempdir()
params.update(extras)
if haz_job: # for risk calculations
calcmode = params['calculation_mode']
check_hazard_risk_consistency(haz_job, calcmode)
if haz_job.user_name != username:
logs.LOG.warn('You are using a hazard calculation ran by %s',
haz_job.user_name)
if hazard_output_id and params.get('quantile_loss_curves'):
logs.LOG.warn(
'quantile_loss_curves is on, but you passed a single '
'hazard output: the statistics will not be computed')
# build and validate an OqParam object
oqparam = readinput.get_oqparam(params, calculators=calculators)
oqparam.hazard_calculation_id = \
haz_job.id if haz_job and not hazard_output_id else None
oqparam.hazard_output_id = hazard_output_id
params = vars(oqparam).copy()
if haz_job:
params['hazard_calculation_id'] = haz_job.id
if hazard_output_id is None and hazard_calculation_id is None:
# this is a hazard calculation, not a risk one
job.save_params(params)
del params['hazard_calculation_id']
del params['hazard_output_id']
else: # this is a risk calculation
if 'maximum_distance' in params:
raise NameError(
'The name of the parameter `maximum_distance` for risk '
'calculators has changed.\nIt is now `asset_hazard_distance`. '
'Please change your risk .ini file.\nNB: do NOT '
'change the maximum_distance in the hazard .ini file!')
job.hazard_calculation = haz_job
hc = haz_job.get_oqparam()
# copy the non-conflicting hazard parameters in the risk parameters
for name, value in hc:
if name not in params:
params[name] = value
params['hazard_investigation_time'] = hc.investigation_time
params['hazard_imtls'] = dict(hc.imtls)
cfd = hc.continuous_fragility_discretization
if cfd and cfd != oqparam.continuous_fragility_discretization:
raise RuntimeError(
'The hazard parameter continuous_fragility_discretization '
'was %d but the risk one is %d' %
(hc.continuous_fragility_discretization,
oqparam.continuous_fragility_discretization))
job.save_params(params)
job.save()
return job