def submit_jobs():
"""
Submit all jobs in the TOSUBMIT state.
"""
from aiida.orm import JobCalculation, Computer, User
from aiida.utils.logger import get_dblogger_extra
from aiida.backends.utils import get_authinfo
computers_users_to_check = list(
JobCalculation._get_all_with_state(state=calc_states.TOSUBMIT,
only_computer_user_pairs=True,
only_enabled=True))
for computer, aiidauser in computers_users_to_check:
#~ user = User.search_for_users(id=dbuser_id)
#~ computer = Computer.get(dbcomputer_id)
execlogger.debug("({},{}) pair to submit".format(
aiidauser.email, computer.name))
try:
try:
authinfo = get_authinfo(computer.dbcomputer, aiidauser._dbuser)
except AuthenticationError:
# TODO!!
# Put each calculation in the SUBMISSIONFAILED state because
# I do not have AuthInfo to submit them
calcs_to_inquire = JobCalculation._get_all_with_state(
state=calc_states.TOSUBMIT,
computer=computer,
user=aiidauser)
for calc in calcs_to_inquire:
try:
calc._set_state(calc_states.SUBMISSIONFAILED)
except ModificationNotAllowed:
# Someone already set it, just skip
pass
logger_extra = get_dblogger_extra(calc)
execlogger.error("Submission of calc {} failed, "
"computer pk= {} ({}) is not configured "
"for aiidauser {}".format(
calc.pk, computer.pk,
computer.get_name(), aiidauser.email),
extra=logger_extra)
# Go to the next (dbcomputer,aiidauser) pair
continue
submitted_calcs = submit_jobs_with_authinfo(authinfo)
except Exception as e:
import traceback
msg = ("Error while submitting jobs "
"for aiidauser={} on computer={}, "
"error type is {}, traceback: {}".format(
aiidauser.email, computer.name, e.__class__.__name__,
traceback.format_exc()))
print msg
execlogger.error(msg)
# Continue with next computer
continue
def logger(self):
"""
Get the logger of the Workflow object, so that it also logs to the
DB.
:return: LoggerAdapter object, that works like a logger, but also has
the 'extra' embedded
"""
return logging.LoggerAdapter(logger=self._logger,
extra=get_dblogger_extra(self))
def logger(self):
"""
Return the logger, also with automatic extras of the associated
extras of the calculation
"""
import logging
from aiida.utils.logger import get_dblogger_extra
return logging.LoggerAdapter(logger=self._logger,
extra=get_dblogger_extra(self._calc))
def logger(self):
"""
Get the logger of the Calculation object, so that it also logs to the
DB.
:return: LoggerAdapter object, that works like a logger, but also has
the 'extra' embedded
"""
import logging
from aiida.utils.logger import get_dblogger_extra
return logging.LoggerAdapter(logger=self._logger,
extra=get_dblogger_extra(self))
def get_log_messages(obj):
from aiida.backends.djsite.db.models import DbLog
import json
extra = get_dblogger_extra(obj)
# convert to list, too
log_messages = list(DbLog.objects.filter(**extra).order_by('time').values(
'loggername', 'levelname', 'message', 'metadata', 'time'))
# deserialize metadata
for log in log_messages:
log.update({'metadata': json.loads(log['metadata'])})
return log_messages
def get_log_messages(obj):
"""
Get the log messages for the object.
"""
from aiida.backends.sqlalchemy.models.log import DbLog
from aiida.backends.sqlalchemy import session
extra = get_dblogger_extra(obj)
log_messages = []
for log_message in (session.query(DbLog).filter_by(
**extra).order_by('time').all()):
val_dict = log_message.__dict__
updated_val_dict = {
"loggername": val_dict["loggername"],
"levelname": val_dict["levelname"],
"message": val_dict["message"],
"metadata": val_dict["_metadata"],
"time": val_dict["time"]
}
log_messages.append(updated_val_dict)
return log_messages
def parse_from_calc(self):
"""
Parses the datafolder, stores results.
This parser for this code ...
"""
from aiida.common.exceptions import InvalidOperation
from aiida.common import aiidalogger
from aiida.utils.logger import get_dblogger_extra
parserlogger = aiidalogger.getChild('yamboparser')
logger_extra = get_dblogger_extra(self._calc)
# suppose at the start that the job is unsuccessful, unless proven otherwise
successful = False
# check whether the yambo calc was an initialisation (p2y)
try:
settings_dict = self._calc.inp.settings.get_dict()
settings_dict = _uppercase_dict(settings_dict,
dict_name='settings')
except AttributeError:
settings_dict = {}
initialise = settings_dict.pop('INITIALISE', None)
# select the folder object
out_folder = self._calc.get_retrieved_node()
# check what is inside the folder
list_of_files = out_folder.get_folder_list()
try:
input_params = self._calc.inp.parameters.get_dict()
except AttributeError:
if not initialise:
raise ParsingError("Input parameters not found!")
else:
input_params = {}
# retrieve the cell: if parent_calc is a YamboCalculation we must find the original PwCalculation
# going back through the graph tree.
parent_calc = self._calc.inp.parent_calc_folder.inp.remote_folder
cell = {}
if isinstance(parent_calc, YamboCalculation):
has_found_cell = False
while (not has_found_cell):
try:
cell = parent_calc.inp.structure.cell
has_found_cell = True
except AttributeError:
parent_calc = parent_calc.inp.parent_calc_folder.inp.remote_folder
elif isinstance(parent_calc, PwCalculation):
cell = self._calc.inp.parent_calc_folder.inp.remote_folder.inp.structure.cell
output_params = {'warnings': [], 'errors': [], 'yambo_wrote': False}
new_nodes_list = []
ndbqp = {}
ndbhf = {}
try:
results = YamboFolder(out_folder.get_abs_path())
except Exception, e:
success = False
raise ParsingError("Unexpected behavior of YamboFolder: %s" % e)
def retrieve_computed_for_authinfo(authinfo):
from aiida.orm import JobCalculation
from aiida.common.folders import SandboxFolder
from aiida.orm.data.folder import FolderData
from aiida.utils.logger import get_dblogger_extra
from aiida.orm import DataFactory
import os
if not authinfo.enabled:
return
calcs_to_retrieve = list(
JobCalculation._get_all_with_state(state=calc_states.COMPUTED,
computer=authinfo.dbcomputer,
user=authinfo.aiidauser))
retrieved = []
# I avoid to open an ssh connection if there are no
# calcs with state not COMPUTED
if len(calcs_to_retrieve):
# Open connection
with authinfo.get_transport() as t:
for calc in calcs_to_retrieve:
logger_extra = get_dblogger_extra(calc)
t._set_logger_extra(logger_extra)
try:
calc._set_state(calc_states.RETRIEVING)
except ModificationNotAllowed:
# Someone else has already started to retrieve it,
# just log and continue
execlogger.debug("Attempting to retrieve more than once "
"calculation {}: skipping!".format(
calc.pk),
extra=logger_extra)
continue # with the next calculation to retrieve
try:
execlogger.debug("Retrieving calc {}".format(calc.pk),
extra=logger_extra)
workdir = calc._get_remote_workdir()
retrieve_list = calc._get_retrieve_list()
retrieve_singlefile_list = calc._get_retrieve_singlefile_list(
)
execlogger.debug("[retrieval of calc {}] "
"chdir {}".format(calc.pk, workdir),
extra=logger_extra)
t.chdir(workdir)
retrieved_files = FolderData()
retrieved_files.add_link_from(
calc,
label=calc._get_linkname_retrieved(),
link_type=LinkType.CREATE)
# First, retrieve the files of folderdata
with SandboxFolder() as folder:
for item in retrieve_list:
# I have two possibilities:
# * item is a string
# * or is a list
# then I have other two possibilities:
# * there are file patterns
# * or not
# First decide the name of the files
if isinstance(item, list):
tmp_rname, tmp_lname, depth = item
# if there are more than one file I do something differently
if t.has_magic(tmp_rname):
remote_names = t.glob(tmp_rname)
local_names = []
for rem in remote_names:
to_append = rem.split(
os.path.sep
)[-depth:] if depth > 0 else []
local_names.append(
os.path.sep.join([tmp_lname] +
to_append))
else:
remote_names = [tmp_rname]
to_append = remote_names.split(
os.path.sep
)[-depth:] if depth > 0 else []
local_names = [
os.path.sep.join([tmp_lname] +
to_append)
]
if depth > 1: # create directories in the folder, if needed
for this_local_file in local_names:
new_folder = os.path.join(
folder.abspath,
os.path.split(this_local_file)[0])
if not os.path.exists(new_folder):
os.makedirs(new_folder)
else: # it is a string
if t.has_magic(item):
remote_names = t.glob(item)
local_names = [
os.path.split(rem)[1]
for rem in remote_names
]
else:
remote_names = [item]
local_names = [os.path.split(item)[1]]
for rem, loc in zip(remote_names, local_names):
execlogger.debug(
"[retrieval of calc {}] "
"Trying to retrieve remote item '{}'".
format(calc.pk, rem),
extra=logger_extra)
t.get(rem,
os.path.join(folder.abspath, loc),
ignore_nonexisting=True)
# Here I retrieved everything;
# now I store them inside the calculation
retrieved_files.replace_with_folder(folder.abspath,
overwrite=True)
# Second, retrieve the singlefiles
with SandboxFolder() as folder:
singlefile_list = []
for (linkname, subclassname,
filename) in retrieve_singlefile_list:
execlogger.debug(
"[retrieval of calc {}] Trying "
"to retrieve remote singlefile '{}'".format(
calc.pk, filename),
extra=logger_extra)
localfilename = os.path.join(
folder.abspath,
os.path.split(filename)[1])
t.get(filename,
localfilename,
ignore_nonexisting=True)
singlefile_list.append(
(linkname, subclassname, localfilename))
# ignore files that have not been retrieved
singlefile_list = [
i for i in singlefile_list if os.path.exists(i[2])
]
# after retrieving from the cluster, I create the objects
singlefiles = []
for (linkname, subclassname,
filename) in singlefile_list:
SinglefileSubclass = DataFactory(subclassname)
singlefile = SinglefileSubclass()
singlefile.set_file(filename)
singlefile.add_link_from(calc,
label=linkname,
link_type=LinkType.CREATE)
singlefiles.append(singlefile)
# Finally, store
execlogger.debug("[retrieval of calc {}] "
"Storing retrieved_files={}".format(
calc.pk, retrieved_files.dbnode.pk),
extra=logger_extra)
retrieved_files.store()
for fil in singlefiles:
execlogger.debug(
"[retrieval of calc {}] "
"Storing retrieved_singlefile={}".format(
calc.pk, fil.dbnode.pk),
extra=logger_extra)
fil.store()
# If I was the one retrieving, I should also be the only
# one parsing! I do not check
calc._set_state(calc_states.PARSING)
Parser = calc.get_parserclass()
# If no parser is set, the calculation is successful
successful = True
if Parser is not None:
# TODO: parse here
parser = Parser(calc)
successful, new_nodes_tuple = parser.parse_from_calc()
for label, n in new_nodes_tuple:
n.add_link_from(calc,
label=label,
link_type=LinkType.CREATE)
n.store()
if successful:
try:
calc._set_state(calc_states.FINISHED)
except ModificationNotAllowed:
# I should have been the only one to set it, but
# in order to avoid unuseful error messages, I
# just ignore
pass
else:
try:
calc._set_state(calc_states.FAILED)
except ModificationNotAllowed:
# I should have been the only one to set it, but
# in order to avoid unuseful error messages, I
# just ignore
pass
execlogger.error(
"[parsing of calc {}] "
"The parser returned an error, but it should have "
"created an output node with some partial results "
"and warnings. Check there for more information on "
"the problem".format(calc.pk),
extra=logger_extra)
retrieved.append(calc)
except Exception:
import traceback
tb = traceback.format_exc()
newextradict = logger_extra.copy()
newextradict['full_traceback'] = tb
if calc.get_state() == calc_states.PARSING:
execlogger.error("Error parsing calc {}. "
"Traceback: {}".format(calc.pk, tb),
extra=newextradict)
# TODO: add a 'comment' to the calculation
try:
calc._set_state(calc_states.PARSINGFAILED)
except ModificationNotAllowed:
pass
else:
execlogger.error("Error retrieving calc {}. "
"Traceback: {}".format(calc.pk, tb),
extra=newextradict)
try:
calc._set_state(calc_states.RETRIEVALFAILED)
except ModificationNotAllowed:
pass
raise
return retrieved
def submit_calc(calc, authinfo, transport=None):
"""
Submit a calculation
:note: if no transport is passed, a new transport is opened and then
closed within this function. If you want to use an already opened
transport, pass it as further parameter. In this case, the transport
has to be already open, and must coincide with the transport of the
the computer defined by the authinfo.
:param calc: the calculation to submit
(an instance of the aiida.orm.JobCalculation class)
:param authinfo: the authinfo for this calculation.
:param transport: if passed, must be an already opened transport. No checks
are done on the consistency of the given transport with the transport
of the computer defined in the authinfo.
"""
from aiida.orm import Code, Computer
from aiida.common.folders import SandboxFolder
from aiida.common.exceptions import (InputValidationError)
from aiida.orm.data.remote import RemoteData
from aiida.utils.logger import get_dblogger_extra
if not authinfo.enabled:
return
logger_extra = get_dblogger_extra(calc)
if transport is None:
t = authinfo.get_transport()
must_open_t = True
else:
t = transport
must_open_t = False
t._set_logger_extra(logger_extra)
if calc._has_cached_links():
raise ValueError("Cannot submit calculation {} because it has "
"cached input links! If you "
"just want to test the submission, use the "
"test_submit() method, otherwise store all links"
"first".format(calc.pk))
# Double check, in the case the calculation was 'killed' (and therefore
# put in the 'FAILED' state) in the meantime
# Do it as near as possible to the state change below (it would be
# even better to do it with some sort of transaction)
if calc.get_state() != calc_states.TOSUBMIT:
raise ValueError("Can only submit calculations with state=TOSUBMIT! "
"(state of calc {} is {} instead)".format(
calc.pk, calc.get_state()))
# I start to submit the calculation: I set the state
try:
calc._set_state(calc_states.SUBMITTING)
except ModificationNotAllowed:
raise ValueError("The calculation has already been submitted by "
"someone else!")
try:
if must_open_t:
t.open()
s = Computer(dbcomputer=authinfo.dbcomputer).get_scheduler()
s.set_transport(t)
computer = calc.get_computer()
with SandboxFolder() as folder:
calcinfo, script_filename = calc._presubmit(
folder, use_unstored_links=False)
codes_info = calcinfo.codes_info
input_codes = [
load_node(_.code_uuid, parent_class=Code) for _ in codes_info
]
for code in input_codes:
if not code.can_run_on(computer):
raise InputValidationError(
"The selected code {} for calculation "
"{} cannot run on computer {}".format(
code.pk, calc.pk, computer.name))
# After this call, no modifications to the folder should be done
calc._store_raw_input_folder(folder.abspath)
# NOTE: some logic is partially replicated in the 'test_submit'
# method of JobCalculation. If major logic changes are done
# here, make sure to update also the test_submit routine
remote_user = t.whoami()
# TODO Doc: {username} field
# TODO: if something is changed here, fix also 'verdi computer test'
remote_working_directory = authinfo.get_workdir().format(
username=remote_user)
if not remote_working_directory.strip():
raise ConfigurationError(
"[submission of calc {}] "
"No remote_working_directory configured for computer "
"'{}'".format(calc.pk, computer.name))
# If it already exists, no exception is raised
try:
t.chdir(remote_working_directory)
except IOError:
execlogger.debug(
"[submission of calc {}] "
"Unable to chdir in {}, trying to create it".format(
calc.pk, remote_working_directory),
extra=logger_extra)
try:
t.makedirs(remote_working_directory)
t.chdir(remote_working_directory)
except (IOError, OSError) as e:
raise ConfigurationError(
"[submission of calc {}] "
"Unable to create the remote directory {} on "
"computer '{}': {}".format(calc.pk,
remote_working_directory,
computer.name, e.message))
# Store remotely with sharding (here is where we choose
# the folder structure of remote jobs; then I store this
# in the calculation properties using _set_remote_dir
# and I do not have to know the logic, but I just need to
# read the absolute path from the calculation properties.
t.mkdir(calcinfo.uuid[:2], ignore_existing=True)
t.chdir(calcinfo.uuid[:2])
t.mkdir(calcinfo.uuid[2:4], ignore_existing=True)
t.chdir(calcinfo.uuid[2:4])
t.mkdir(calcinfo.uuid[4:])
t.chdir(calcinfo.uuid[4:])
workdir = t.getcwd()
# I store the workdir of the calculation for later file
# retrieval
calc._set_remote_workdir(workdir)
# I first create the code files, so that the code can put
# default files to be overwritten by the plugin itself.
# Still, beware! The code file itself could be overwritten...
# But I checked for this earlier.
for code in input_codes:
if code.is_local():
# Note: this will possibly overwrite files
for f in code.get_folder_list():
t.put(code.get_abs_path(f), f)
t.chmod(code.get_local_executable(), 0755) # rwxr-xr-x
# copy all files, recursively with folders
for f in folder.get_content_list():
execlogger.debug("[submission of calc {}] "
"copying file/folder {}...".format(
calc.pk, f),
extra=logger_extra)
t.put(folder.get_abs_path(f), f)
# local_copy_list is a list of tuples,
# each with (src_abs_path, dest_rel_path)
# NOTE: validation of these lists are done
# inside calc._presubmit()
local_copy_list = calcinfo.local_copy_list
remote_copy_list = calcinfo.remote_copy_list
remote_symlink_list = calcinfo.remote_symlink_list
if local_copy_list is not None:
for src_abs_path, dest_rel_path in local_copy_list:
execlogger.debug("[submission of calc {}] "
"copying local file/folder to {}".format(
calc.pk, dest_rel_path),
extra=logger_extra)
t.put(src_abs_path, dest_rel_path)
if remote_copy_list is not None:
for (remote_computer_uuid, remote_abs_path,
dest_rel_path) in remote_copy_list:
if remote_computer_uuid == computer.uuid:
execlogger.debug(
"[submission of calc {}] "
"copying {} remotely, directly on the machine "
"{}".format(calc.pk, dest_rel_path, computer.name))
try:
t.copy(remote_abs_path, dest_rel_path)
except (IOError, OSError):
execlogger.warning(
"[submission of calc {}] "
"Unable to copy remote resource from {} to {}! "
"Stopping.".format(calc.pk, remote_abs_path,
dest_rel_path),
extra=logger_extra)
raise
else:
# TODO: implement copy between two different
# machines!
raise NotImplementedError(
"[presubmission of calc {}] "
"Remote copy between two different machines is "
"not implemented yet".format(calc.pk))
if remote_symlink_list is not None:
for (remote_computer_uuid, remote_abs_path,
dest_rel_path) in remote_symlink_list:
if remote_computer_uuid == computer.uuid:
execlogger.debug(
"[submission of calc {}] "
"copying {} remotely, directly on the machine "
"{}".format(calc.pk, dest_rel_path, computer.name))
try:
t.symlink(remote_abs_path, dest_rel_path)
except (IOError, OSError):
execlogger.warning(
"[submission of calc {}] "
"Unable to create remote symlink from {} to {}! "
"Stopping.".format(calc.pk, remote_abs_path,
dest_rel_path),
extra=logger_extra)
raise
else:
raise IOError("It is not possible to create a symlink "
"between two different machines for "
"calculation {}".format(calc.pk))
remotedata = RemoteData(computer=computer, remote_path=workdir)
remotedata.add_link_from(calc,
label='remote_folder',
link_type=LinkType.CREATE)
remotedata.store()
job_id = s.submit_from_script(t.getcwd(), script_filename)
calc._set_job_id(job_id)
# This should always be possible, because we should be
# the only ones submitting this calculations,
# so I do not check the ModificationNotAllowed
calc._set_state(calc_states.WITHSCHEDULER)
## I do not set the state to queued; in this way, if the
## daemon is down, the user sees '(unknown)' as last state
## and understands that the daemon is not running.
# if job_tmpl.submit_as_hold:
# calc._set_scheduler_state(job_states.QUEUED_HELD)
#else:
# calc._set_scheduler_state(job_states.QUEUED)
execlogger.debug("submitted calculation {} on {} with "
"jobid {}".format(calc.pk, computer.name, job_id),
extra=logger_extra)
except Exception as e:
import traceback
try:
calc._set_state(calc_states.SUBMISSIONFAILED)
except ModificationNotAllowed:
# Someone already set it, just skip
pass
execlogger.error("Submission of calc {} failed, check also the "
"log file! Traceback: {}".format(
calc.pk, traceback.format_exc()),
extra=logger_extra)
raise
finally:
# close the transport, but only if it was opened within this function
if must_open_t:
t.close()
def submit_jobs_with_authinfo(authinfo):
"""
Submit jobs in TOSUBMIT status belonging
to user and machine as defined in the 'dbauthinfo' table.
"""
from aiida.orm import JobCalculation
from aiida.utils.logger import get_dblogger_extra
if not authinfo.enabled:
return
execlogger.debug("Submitting jobs for user {} "
"and machine {}".format(authinfo.aiidauser.email,
authinfo.dbcomputer.name))
# This returns an iterator over aiida JobCalculation objects
calcs_to_inquire = list(
JobCalculation._get_all_with_state(state=calc_states.TOSUBMIT,
computer=authinfo.dbcomputer,
user=authinfo.aiidauser))
# I avoid to open an ssh connection if there are
# no calcs with state WITHSCHEDULER
if len(calcs_to_inquire):
# Open connection
try:
# I do it here so that the transport is opened only once per computer
with authinfo.get_transport() as t:
for c in calcs_to_inquire:
logger_extra = get_dblogger_extra(c)
t._set_logger_extra(logger_extra)
try:
submit_calc(calc=c, authinfo=authinfo, transport=t)
except Exception as e:
# TODO: implement a counter, after N retrials
# set it to a status that
# requires the user intervention
execlogger.warning("There was an exception for "
"calculation {} ({}): {}".format(
c.pk, e.__class__.__name__,
e.message))
# I just proceed to the next calculation
continue
# Catch exceptions also at this level (this happens only if there is
# a problem opening the transport in the 'with t' statement,
# because any other exception is caught and skipped above
except Exception as e:
import traceback
from aiida.utils.logger import get_dblogger_extra
for calc in calcs_to_inquire:
logger_extra = get_dblogger_extra(calc)
try:
calc._set_state(calc_states.SUBMISSIONFAILED)
except ModificationNotAllowed:
# Someone already set it, just skip
pass
execlogger.error(
"Submission of calc {} failed, check also the "
"log file! Traceback: {}".format(calc.pk,
traceback.format_exc()),
extra=logger_extra)
raise
def update_running_calcs_status(authinfo):
"""
Update the states of calculations in WITHSCHEDULER status belonging
to user and machine as defined in the 'dbauthinfo' table.
"""
from aiida.orm import JobCalculation, Computer
from aiida.scheduler.datastructures import JobInfo
from aiida.utils.logger import get_dblogger_extra
if not authinfo.enabled:
return
execlogger.debug("Updating running calc status for user {} "
"and machine {}".format(authinfo.aiidauser.email,
authinfo.dbcomputer.name))
# This returns an iterator over aiida JobCalculation objects
calcs_to_inquire = list(
JobCalculation._get_all_with_state(state=calc_states.WITHSCHEDULER,
computer=authinfo.dbcomputer,
user=authinfo.aiidauser))
# NOTE: no further check is done that machine and
# aiidauser are correct for each calc in calcs
s = Computer(dbcomputer=authinfo.dbcomputer).get_scheduler()
t = authinfo.get_transport()
computed = []
# I avoid to open an ssh connection if there are
# no calcs with state WITHSCHEDULER
if len(calcs_to_inquire):
jobids_to_inquire = [str(c.get_job_id()) for c in calcs_to_inquire]
# Open connection
with t:
s.set_transport(t)
# TODO: Check if we are ok with filtering by job (to make this work,
# I had to remove the check on the retval for getJobs,
# because if the job has computed and is not in the output of
# qstat, it gives a nonzero retval)
# TODO: catch SchedulerError exception and do something
# sensible (at least, skip this computer but continue with
# following ones, and set a counter; set calculations to
# UNKNOWN after a while?
if s.get_feature('can_query_by_user'):
found_jobs = s.getJobs(user="******", as_dict=True)
else:
found_jobs = s.getJobs(jobs=jobids_to_inquire, as_dict=True)
# I update the status of jobs
for c in calcs_to_inquire:
try:
logger_extra = get_dblogger_extra(c)
t._set_logger_extra(logger_extra)
jobid = c.get_job_id()
if jobid is None:
execlogger.error("JobCalculation {} is WITHSCHEDULER "
"but no job id was found!".format(
c.pk),
extra=logger_extra)
continue
# I check if the calculation to be checked (c)
# is in the output of qstat
if jobid in found_jobs:
# jobinfo: the information returned by
# qstat for this job
jobinfo = found_jobs[jobid]
execlogger.debug("Inquirying calculation {} (jobid "
"{}): it has job_state={}".format(
c.pk, jobid, jobinfo.job_state),
extra=logger_extra)
# For the moment, FAILED is not defined
if jobinfo.job_state in [job_states.DONE
]: # , job_states.FAILED]:
computed.append(c)
try:
c._set_state(calc_states.COMPUTED)
except ModificationNotAllowed:
# Someone already set it, just skip
pass
## Do not set the WITHSCHEDULER state multiple times,
## this would raise a ModificationNotAllowed
# else:
# c._set_state(calc_states.WITHSCHEDULER)
c._set_scheduler_state(jobinfo.job_state)
c._set_last_jobinfo(jobinfo)
else:
execlogger.debug("Inquirying calculation {} (jobid "
"{}): not found, assuming "
"job_state={}".format(
c.pk, jobid, job_states.DONE),
extra=logger_extra)
# calculation c is not found in the output of qstat
computed.append(c)
c._set_scheduler_state(job_states.DONE)
except Exception as e:
# TODO: implement a counter, after N retrials
# set it to a status that
# requires the user intervention
execlogger.warning("There was an exception for "
"calculation {} ({}): {}".format(
c.pk, e.__class__.__name__,
e.message),
extra=logger_extra)
continue
for c in computed:
try:
logger_extra = get_dblogger_extra(c)
try:
detailed_jobinfo = s.get_detailed_jobinfo(
jobid=c.get_job_id())
except NotImplementedError:
detailed_jobinfo = (
u"AiiDA MESSAGE: This scheduler does not implement "
u"the routine get_detailed_jobinfo to retrieve "
u"the information on "
u"a job after it has finished.")
last_jobinfo = c._get_last_jobinfo()
if last_jobinfo is None:
last_jobinfo = JobInfo()
last_jobinfo.job_id = c.get_job_id()
last_jobinfo.job_state = job_states.DONE
last_jobinfo.detailedJobinfo = detailed_jobinfo
c._set_last_jobinfo(last_jobinfo)
except Exception as e:
execlogger.warning("There was an exception while "
"retrieving the detailed jobinfo "
"for calculation {} ({}): {}".format(
c.pk, e.__class__.__name__,
e.message),
extra=logger_extra)
continue
finally:
# Set the state to COMPUTED as the very last thing
# of this routine; no further change should be done after
# this, so that in general the retriever can just
# poll for this state, if we want to.
try:
c._set_state(calc_states.COMPUTED)
except ModificationNotAllowed:
# Someone already set it, just skip
pass
return computed
def _prepare_for_submission(self, tempfolder, inputdict):
"""
This is the routine to be called when you want to create
the input files and related stuff with a plugin.
:param tempfolder: a aiida.common.folders.Folder subclass where
the plugin should put all its files.
:param inputdict: a dictionary with the input nodes, as they would
be returned by get_inputs_dict (without the Code!)
"""
local_copy_list = []
remote_copy_list = []
remote_symlink_list = []
try:
parameters = inputdict.pop(self.get_linkname('parameters'))
except KeyError:
raise InputValidationError("No parameters specified for this calculation")
if not isinstance(parameters, ParameterData):
raise InputValidationError("parameters is not of type ParameterData")
try:
structure = inputdict.pop(self.get_linkname('structure'))
except KeyError:
raise InputValidationError("No structure specified for this calculation")
if not isinstance(structure, StructureData):
raise InputValidationError("structure is not of type StructureData")
if self._use_kpoints:
try:
kpoints = inputdict.pop(self.get_linkname('kpoints'))
except KeyError:
raise InputValidationError("No kpoints specified for this calculation")
if not isinstance(kpoints, KpointsData):
raise InputValidationError("kpoints is not of type KpointsData")
else:
kpoints = None
# Settings can be undefined, and defaults to an empty dictionary
settings = inputdict.pop(self.get_linkname('settings'), None)
if settings is None:
settings_dict = {}
else:
if not isinstance(settings, ParameterData):
raise InputValidationError("settings, if specified, must be of "
"type ParameterData")
# Settings converted to uppercase
settings_dict = _uppercase_dict(settings.get_dict(),
dict_name='settings')
pseudos = {}
# I create here a dictionary that associates each kind name to a pseudo
for link in inputdict.keys():
if link.startswith(self._get_linkname_pseudo_prefix()):
kindstring = link[len(self._get_linkname_pseudo_prefix()):]
kinds = kindstring.split('_')
the_pseudo = inputdict.pop(link)
if not isinstance(the_pseudo, UpfData):
raise InputValidationError("Pseudo for kind(s) {} is not of "
"type UpfData".format(",".join(kinds)))
for kind in kinds:
if kind in pseudos:
raise InputValidationError("Pseudo for kind {} passed "
"more than one time".format(kind))
pseudos[kind] = the_pseudo
parent_calc_folder = inputdict.pop(self.get_linkname('parent_folder'), None)
if parent_calc_folder is not None:
if not isinstance(parent_calc_folder, RemoteData):
raise InputValidationError("parent_calc_folder, if specified, "
"must be of type RemoteData")
vdw_table = inputdict.pop(self.get_linkname('vdw_table'), None)
if vdw_table is not None:
if not isinstance(vdw_table, SinglefileData):
raise InputValidationError("vdw_table, if specified, "
"must be of type SinglefileData")
try:
code = inputdict.pop(self.get_linkname('code'))
except KeyError:
raise InputValidationError("No code specified for this calculation")
# Here, there should be no more parameters...
if inputdict:
raise InputValidationError("The following input data nodes are "
"unrecognized: {}".format(inputdict.keys()))
# Check structure, get species, check peudos
kindnames = [k.name for k in structure.kinds]
if set(kindnames) != set(pseudos.keys()):
err_msg = ("Mismatch between the defined pseudos and the list of "
"kinds of the structure. Pseudos: {}; kinds: {}".format(
",".join(pseudos.keys()), ",".join(list(kindnames))))
raise InputValidationError(err_msg)
##############################
# END OF INITIAL INPUT CHECK #
##############################
# I create the subfolder that will contain the pseudopotentials
tempfolder.get_subfolder(self._PSEUDO_SUBFOLDER, create=True)
# I create the subfolder with the output data (sometimes Quantum
# Espresso codes crash if an empty folder is not already there
tempfolder.get_subfolder(self._OUTPUT_SUBFOLDER, create=True)
# If present, add also the Van der Waals table to the pseudo dir
# Note that the name of the table is not checked but should be the
# one expected by QE.
if vdw_table:
local_copy_list.append(
(
vdw_table.get_file_abs_path(),
os.path.join(self._PSEUDO_SUBFOLDER,
os.path.split(vdw_table.get_file_abs_path())[1])
)
)
input_filecontent, local_copy_pseudo_list = self._generate_PWCPinputdata(parameters,settings_dict,pseudos,
structure,kpoints)
local_copy_list += local_copy_pseudo_list
input_filename = tempfolder.get_abs_path(self._INPUT_FILE_NAME)
with open(input_filename, 'w') as infile:
infile.write(input_filecontent)
# operations for restart
symlink = settings_dict.pop('PARENT_FOLDER_SYMLINK',
self._default_symlink_usage) # a boolean
if symlink:
if parent_calc_folder is not None:
# I put the symlink to the old parent ./out folder
remote_symlink_list.append(
(parent_calc_folder.get_computer().uuid,
os.path.join(parent_calc_folder.get_remote_path(),
self._restart_copy_from),
self._restart_copy_to
))
else:
# copy remote output dir, if specified
if parent_calc_folder is not None:
remote_copy_list.append(
(parent_calc_folder.get_computer().uuid,
os.path.join(parent_calc_folder.get_remote_path(),
self._restart_copy_from),
self._restart_copy_to
))
# here we may create an aiida.EXIT file
create_exit_file = settings_dict.pop('ONLY_INITIALIZATION', False)
if create_exit_file:
exit_filename = tempfolder.get_abs_path(
'{}.EXIT'.format(self._PREFIX))
with open(exit_filename, 'w') as f:
f.write('\n')
# Check if specific inputs for the ENVIRON module where specified
environ_namelist = settings_dict.pop('ENVIRON', None)
if environ_namelist is not None:
if not isinstance(environ_namelist, dict):
raise InputValidationError(
"ENVIRON namelist should be specified as a dictionary")
# We first add the environ flag to the command-line options (if not already present)
try:
if '-environ' not in settings_dict['CMDLINE']:
settings_dict['CMDLINE'].append('-environ')
except KeyError:
settings_dict['CMDLINE'] = ['-environ']
# To create a mapping from the species to an incremental fortran 1-based index
# we use the alphabetical order as in the inputdata generation
mapping_species = {sp_name: (idx+1) for idx, sp_name in
enumerate(sorted([kind.name for kind in structure.kinds]))}
environ_input_filename = tempfolder.get_abs_path(
self._ENVIRON_INPUT_FILE_NAME)
with open(environ_input_filename, 'w') as environ_infile:
environ_infile.write("&ENVIRON\n")
for k, v in sorted(environ_namelist.iteritems()):
environ_infile.write(
get_input_data_text(k, v, mapping=mapping_species))
environ_infile.write("/\n")
# Check for the deprecated 'ALSO_BANDS' setting and if present fire a deprecation log message
also_bands = settings_dict.pop('ALSO_BANDS', None)
if also_bands:
import logging
from aiida.utils.logger import get_dblogger_extra
logger = logging.LoggerAdapter(logger=self.logger, extra=get_dblogger_extra(self))
logger.warning(
"The '{}' setting is deprecated as bands are now parsed by default. "
"If you do not want the bands to be parsed set the '{}' to True {}. "
"Note that the eigenvalue.xml files are also no longer stored in the repository"
.format('also_bands', 'no_bands', type(self))
)
calcinfo = CalcInfo()
calcinfo.uuid = self.uuid
# Empty command line by default
cmdline_params = settings_dict.pop('CMDLINE', [])
# we commented calcinfo.stin_name and added it here in cmdline_params
# in this way the mpirun ... pw.x ... < aiida.in
# is replaced by mpirun ... pw.x ... -in aiida.in
# in the scheduler, _get_run_line, if cmdline_params is empty, it
# simply uses < calcinfo.stin_name
calcinfo.cmdline_params = (list(cmdline_params) + ["-in", self._INPUT_FILE_NAME])
codeinfo = CodeInfo()
codeinfo.cmdline_params = (list(cmdline_params) + ["-in", self._INPUT_FILE_NAME])
codeinfo.stdout_name = self._OUTPUT_FILE_NAME
codeinfo.code_uuid = code.uuid
calcinfo.codes_info = [codeinfo]
calcinfo.local_copy_list = local_copy_list
calcinfo.remote_copy_list = remote_copy_list
calcinfo.remote_symlink_list = remote_symlink_list
# Retrieve by default the output file and the xml file
calcinfo.retrieve_list = []
calcinfo.retrieve_list.append(self._OUTPUT_FILE_NAME)
calcinfo.retrieve_list.append(self._DATAFILE_XML)
calcinfo.retrieve_list += settings_dict.pop('ADDITIONAL_RETRIEVE_LIST', [])
calcinfo.retrieve_list += self._internal_retrieve_list
# Retrieve the k-point directories with the xml files to the temporary folder
# to parse the band eigenvalues and occupations but not to have to save the raw files
# if and only if the 'no_bands' key was not set to true in the settings
no_bands = settings_dict.pop('NO_BANDS', False)
if no_bands is False:
xmlpaths = os.path.join(self._OUTPUT_SUBFOLDER, self._PREFIX + '.save', 'K*[0-9]', 'eigenval*.xml')
calcinfo.retrieve_temporary_list = [[xmlpaths, '.', 2]]
try:
Parserclass = self.get_parserclass()
parser = Parserclass(self)
parser_opts = parser.get_parser_settings_key().upper()
settings_dict.pop(parser_opts)
except (KeyError, AttributeError):
# the key parser_opts isn't inside the dictionary
pass
if settings_dict:
raise InputValidationError("The following keys have been found in "
"the settings input node, but were not understood: {}".format(
",".join(settings_dict.keys())))
return calcinfo
def parse_from_calc(self, manual=True, custom_instruct=None):
"""
Parses the datafolder, stores results.
"""
from aiida.common.exceptions import InvalidOperation
from aiida.common import aiidalogger
from aiida.utils.logger import get_dblogger_extra
parserlogger = aiidalogger.getChild('vaspparser')
logger_extra = get_dblogger_extra(self._calc)
# suppose at the start that the job is successful
successful = True
parser_warnings = {} # for logging non-critical events
# check that calculation is in the right state
if not manual:
state = self._calc.get_state()
if state != calc_states.PARSING:
raise InvalidOperation("Calculation not in {} state".format(
calc_states.PARSING))
# get parser instructions
# TODO: output parser should NOT interpret the input !!!
try:
instruct = self._calc.get_inputs_dict().pop(
self._calc.get_linkname('settings'))
instruct = instruct.get_dict()
instruct = instruct[u'PARSER_INSTRUCTIONS']
########## Abel Modification to test custom parsers
if custom_instruct is not None:
instruct = custom_instruct
##########
# check if structure, data, and error parsers are specified
# if not append defaults
itypes = [i['type'] for i in instruct]
# structure
if not 'structure' in itypes:
instruct.append({
'instr': 'default_structure_parser',
'type': 'structure',
'params': {}
})
parser_warnings.setdefault(
'Structure parser instruction not found!',
'default_structure_parser loaded.')
# error
if not 'error' in itypes:
instruct.append({
'instr': 'default_error_parser',
'type': 'error',
'params': {}
})
parser_warnings.setdefault(
'Error parser instruction not found!',
'default_error_parser loaded.')
# output
if not 'data' in itypes:
instruct.append({
'instr': 'default_vasprun_parser',
'type': 'data',
'params': {}
})
parser_warnings.setdefault(
'Data parser instruction not found!',
'default_data_parser_parser loaded.')
except:
parser_warnings.setdefault('Parser instructions not found',
'Default instructions were loaded.')
# don't crash, load default instructions instead
instruct = [
# output
{
'instr': 'default_vasprun_parser',
'type': 'data',
'params': {}
},
# error
{
'instr': 'default_error_parser',
'type': 'error',
'params': {}
},
# structure
{
'instr': 'default_structure_parser',
'type': 'structure',
'params': {}
}
]
# select the folder object
out_folder = self._calc.get_retrieved_node()
# check what is inside the folder
list_of_files = out_folder.get_folder_list()
# === check if mandatory files exist ===
# default output file should exist
if not self._calc._default_output in list_of_files:
successful = False
parserlogger.error("Standard output file ({}) not found".format(
self._calc._default_output),
extra=logger_extra)
return successful, ()
# output structure file should exist
if not self._calc._output_structure in list_of_files:
successful = False
parserlogger.error("Output structure file ({}) not found".format(
self._calc._output_structure),
extra=logger_extra)
return successful, ()
# stderr file should exist
if not self._calc._SCHED_ERROR_FILE in list_of_files:
successful = False
parserlogger.error("STDERR file ({}) not found".format(
self._calc._SCHED_ERROR_FILE),
extra=logger_extra)
return successful, ()
instr_node_list = []
errors_node_list = []
# === execute instructions ===
# print instruct
for instr in instruct:
# create an executable instruction
try:
# load instruction
itype = instr['type'].lower()
iname = instr['instr']
iparams = instr['params']
ifull_name = "{}.{}".format(itype, iname)
# append parameters
if itype == 'error':
iparams.setdefault('SCHED_ERROR_FILE',
self._calc._SCHED_ERROR_FILE)
elif itype == 'structure':
iparams.setdefault('OUTPUT_STRUCTURE',
self._calc._output_structure)
# instantiate
instr = ParserInstructionFactory(ifull_name)
instr_exe = instr(out_folder,
params=iparams if iparams else None)
except ValueError:
parser_warnings.setdefault(
'{}_instruction'.format(instr),
'Invalid parser instruction - could not be instantiated!')
instr_exe = None
# execute
if instr_exe:
try:
for item in instr_exe.execute(): # store the results
instr_node_list.append(item)
except Exception as e:
print instr, e
# parser_warnings['output'].setdefault( Modified by Abel
parser_warnings.setdefault(
'output', {
'{}_instruction'.format(instr),
'Failed to execute. Errors: {}'.format(e)
})
# add all parser warnings to the error list
parser_warnings = ParameterData(dict=parser_warnings)
errors_node_list.append(('parser_warnings', parser_warnings))
# === save the outputs ===
new_nodes_list = []
# save the errors/warrnings
for item in errors_node_list:
new_nodes_list.append(item)
# save vasp data
if instr_node_list:
for item in instr_node_list:
new_nodes_list.append(item)
return successful, new_nodes_list
