def upload_potcar_family(cls,
source,
group_name,
group_description=None,
stop_if_existing=True,
dry_run=False):
"""
Upload a set of POTCAR potentials as a family.
:param folder: a path containing all POTCAR files to be added.
:param group_name: the name of the group to create. If it exists and is
non-empty, a UniquenessError is raised.
:param group_description: a string to be set as the group description.
Overwrites previous descriptions, if the group was existing.
:param stop_if_existing: if True, check for the sha512 of the files and,
if the file already exists in the DB, raises a MultipleObjectsError.
If False, simply adds the existing UPFData node to the group.
:param dry_run: If True, do not change the database.
"""
group = cls._prepare_group_for_upload(group_name,
group_description,
dry_run=dry_run)
potcar_finder = PotcarWalker(source)
potcar_finder.walk()
num_files = len(potcar_finder.potcars)
family_nodes_uuid = [node.uuid
for node in group.nodes] if not dry_run else []
potcars_tried_upload = cls._try_upload_potcars(
potcar_finder.potcars,
stop_if_existing=stop_if_existing,
dry_run=dry_run)
new_potcars_added = [
(potcar, created, file_path)
for potcar, created, file_path in potcars_tried_upload
if potcar.uuid not in family_nodes_uuid
]
for potcar, created, file_path in new_potcars_added:
if created:
aiidalogger.debug(
'New PotcarData node %s created while uploading file %s for family %s',
potcar.uuid, file_path, group_name)
else:
aiidalogger.debug(
'PotcarData node %s used instead of uploading file %s to family %s',
potcar.uuid, file_path, group_name)
if not dry_run:
group.add_nodes(
[potcar for potcar, created, file_path in new_potcars_added])
num_added = len(new_potcars_added)
num_uploaded = len([item for item in new_potcars_added
if item[1]]) # item[1] refers to 'created'
return num_files, num_added, num_uploaded
def deserialize_dict(mainitem, subitems, sep, original_class, original_pk,
lesserrors):
"""Deserialize a Python dictionary."""
# pylint: disable=protected-access
# subitems contains all subitems, here I store only those of
# deepness 1, i.e. if I have subitems '0', '1' and '1.c' I
# store only '0' and '1'
from aiida.common import AIIDA_LOGGER
firstlevelsubdict = {k: v for k, v in subitems.items() if sep not in k}
if len(firstlevelsubdict) != mainitem['ival']:
if (original_class is not None
and original_class._subspecifier_field_name is not None):
subspecifier_string = '{}={} and '.format(
original_class._subspecifier_field_name, original_pk)
else:
subspecifier_string = ''
if original_class is None:
sourcestr = 'the data passed'
else:
sourcestr = original_class.__name__
msg = ('Wrong dict length stored in {} for '
"{}key='{}' ({} vs {})".format(sourcestr, subspecifier_string,
mainitem['key'],
len(firstlevelsubdict),
mainitem['ival']))
if lesserrors:
AIIDA_LOGGER.error(msg)
else:
raise DeserializationException(msg)
# I get the values in memory as a dictionary
tempdict = {}
for firstsubk, firstsubv in firstlevelsubdict.items():
# I call recursively the same function to get subitems
newsubitems = {
k[len(firstsubk) + len(sep):]: v
for k, v in subitems.items() if k.startswith(firstsubk + sep)
}
tempdict[firstsubk] = _deserialize_attribute(
mainitem=firstsubv,
subitems=newsubitems,
sep=sep,
original_class=original_class,
original_pk=original_pk)
return tempdict
def __init__(self, calculation):
"""Initialize the instance of YamboParser"""
from aiida.common import AIIDA_LOGGER
self._logger = AIIDA_LOGGER.getChild('parser').getChild(
self.__class__.__name__)
# check for valid input
if calculation.process_type == 'aiida.calculations:yambo.yambo':
yambo_parent = True
else:
raise OutputParsingError(
"Input calculation must be a YamboCalculation, not {}".format(
calculation.process_type))
self._calc = calculation
self.last_job_info = self._calc.get_last_job_info()
self._eels_array_linkname = 'array_eels'
self._eps_array_linkname = 'array_eps'
self._alpha_array_linkname = 'array_alpha'
self._qp_array_linkname = 'array_qp'
self._ndb_linkname = 'array_ndb'
self._ndb_QP_linkname = 'array_ndb_QP'
self._ndb_HF_linkname = 'array_ndb_HFlocXC'
self._lifetime_bands_linkname = 'bands_lifetime'
self._quasiparticle_bands_linkname = 'bands_quasiparticle'
self._parameter_linkname = 'output_parameters'
self._system_info_linkname = 'system_info'
super(YamboParser, self).__init__(calculation)
def __init__(self, **kwargs): # pylint: disable=unused-argument
super(BaseFileParser, self).__init__()
self._logger = aiidalogger.getChild(self.__class__.__name__)
self._exit_code = None
self._parsable_items = self.PARSABLE_ITEMS
self._parsed_data = {}
if 'file_path' in kwargs:
self._data_obj = SingleFile(path=kwargs['file_path'])
elif 'data' in kwargs:
self._data_obj = SingleFile(data=kwargs['data'])
else:
self._data_obj = None
def __init__(self, *args, **kwargs): # pylint: disable=unused-argument
"""
__init__ method of the Transport base class.
"""
from aiida.common import AIIDA_LOGGER
self._safe_open_interval = kwargs.pop('safe_interval',
self._DEFAULT_SAFE_OPEN_INTERVAL)
self._logger = AIIDA_LOGGER.getChild('transport').getChild(
self.__class__.__name__)
self._logger_extra = None
self._is_open = False
self._enters = 0
def __init__(self, calc_parser_cls=None, **kwargs): # pylint: disable=unused-argument
super(BaseFileParser, self).__init__()
self._logger = aiidalogger.getChild(self.__class__.__name__)
self._vasp_parser = calc_parser_cls
self.settings = None
if calc_parser_cls is not None:
calc_parser_cls.get_quantity.append(self.get_quantity)
self.settings = calc_parser_cls.settings
self.parsable_items = {}
self._parsed_data = {}
self._data_obj = None
def __init__(self, *args, **kwargs): # pylint: disable=unused-argument
"""
__init__ method of the Transport base class.
:param safe_interval: (optional, default self._DEFAULT_SAFE_OPEN_INTERVAL)
Minimum time interval in seconds between opening new connections.
:param use_login_shell: (optional, default True)
if False, do not use a login shell when executing command
"""
from aiida.common import AIIDA_LOGGER
self._safe_open_interval = kwargs.pop('safe_interval',
self._DEFAULT_SAFE_OPEN_INTERVAL)
self._use_login_shell = kwargs.pop('use_login_shell', True)
if self._use_login_shell:
self._bash_command_str = 'bash -l '
else:
self._bash_command_str = 'bash '
self._logger = AIIDA_LOGGER.getChild('transport').getChild(
self.__class__.__name__)
self._logger_extra = None
self._is_open = False
self._enters = 0
def upload_upf_family(folder,
group_label,
group_description,
stop_if_existing=True):
"""Upload a set of UPF files in a given group.
:param folder: a path containing all UPF files to be added.
Only files ending in .UPF (case-insensitive) are considered.
:param group_label: the name of the group to create. If it exists and is non-empty, a UniquenessError is raised.
:param group_description: string to be set as the group description. Overwrites previous descriptions.
:param stop_if_existing: if True, check for the md5 of the files and, if the file already exists in the DB, raises a
MultipleObjectsError. If False, simply adds the existing UPFData node to the group.
"""
# pylint: disable=too-many-locals,too-many-branches
import os
from aiida import orm
from aiida.common import AIIDA_LOGGER
from aiida.common.exceptions import UniquenessError
from aiida.common.files import md5_file
if not os.path.isdir(folder):
raise ValueError('folder must be a directory')
# only files, and only those ending with .upf or .UPF;
# go to the real file if it is a symlink
filenames = [
os.path.realpath(os.path.join(folder, i)) for i in os.listdir(folder)
if os.path.isfile(os.path.join(folder, i))
and i.lower().endswith('.upf')
]
nfiles = len(filenames)
automatic_user = orm.User.objects.get_default()
group, group_created = orm.Group.objects.get_or_create(
label=group_label, type_string=UPFGROUP_TYPE, user=automatic_user)
if group.user.email != automatic_user.email:
raise UniquenessError(
'There is already a UpfFamily group with label {}'
', but it belongs to user {}, therefore you '
'cannot modify it'.format(group_label, group.user.email))
# Always update description, even if the group already existed
group.description = group_description
# NOTE: GROUP SAVED ONLY AFTER CHECKS OF UNICITY
pseudo_and_created = []
for filename in filenames:
md5sum = md5_file(filename)
builder = orm.QueryBuilder()
builder.append(UpfData, filters={'attributes.md5': {'==': md5sum}})
existing_upf = builder.first()
if existing_upf is None:
# return the upfdata instances, not stored
pseudo, created = UpfData.get_or_create(filename,
use_first=True,
store_upf=False)
# to check whether only one upf per element exists
# NOTE: actually, created has the meaning of "to_be_created"
pseudo_and_created.append((pseudo, created))
else:
if stop_if_existing:
raise ValueError('A UPF with identical MD5 to '
' {} cannot be added with stop_if_existing'
''.format(filename))
existing_upf = existing_upf[0]
pseudo_and_created.append((existing_upf, False))
# check whether pseudo are unique per element
elements = [(i[0].element, i[0].md5sum) for i in pseudo_and_created]
# If group already exists, check also that I am not inserting more than
# once the same element
if not group_created:
for aiida_n in group.nodes:
# Skip non-pseudos
if not isinstance(aiida_n, UpfData):
continue
elements.append((aiida_n.element, aiida_n.md5sum))
elements = set(elements) # Discard elements with the same MD5, that would
# not be stored twice
elements_names = [e[0] for e in elements]
if not len(elements_names) == len(set(elements_names)):
duplicates = {x for x in elements_names if elements_names.count(x) > 1}
duplicates_string = ', '.join(i for i in duplicates)
raise UniquenessError('More than one UPF found for the elements: ' +
duplicates_string + '.')
# At this point, save the group, if still unstored
if group_created:
group.store()
# save the upf in the database, and add them to group
for pseudo, created in pseudo_and_created:
if created:
pseudo.store()
AIIDA_LOGGER.debug('New node {} created for file {}'.format(
pseudo.uuid, pseudo.filename))
else:
AIIDA_LOGGER.debug('Reusing node {} for file {}'.format(
pseudo.uuid, pseudo.filename))
# Add elements to the group all togetehr
group.add_nodes([pseudo for pseudo, created in pseudo_and_created])
nuploaded = len([_ for _, created in pseudo_and_created if created])
return nfiles, nuploaded
def parse_upf(fname, check_filename=True):
"""
Try to get relevant information from the UPF. For the moment, only the
element name. Note that even UPF v.2 cannot be parsed with the XML minidom!
(e.g. due to the & characters in the human-readable section).
If check_filename is True, raise a ParsingError exception if the filename
does not start with the element name.
"""
import os
from aiida.common.exceptions import ParsingError
from aiida.common import AIIDA_LOGGER
from aiida.orm.nodes.data.structure import _valid_symbols
parsed_data = {}
try:
upf_contents = fname.read()
fname = fname.name
except AttributeError:
with io.open(fname, encoding='utf8') as handle:
upf_contents = handle.read()
match = REGEX_UPF_VERSION.search(upf_contents)
if match:
version = match.group('version')
AIIDA_LOGGER.debug('Version found: {} for file {}'.format(
version, fname))
else:
AIIDA_LOGGER.debug('Assuming version 1 for file {}'.format(fname))
version = '1'
parsed_data['version'] = version
try:
version_major = int(version.partition('.')[0])
except ValueError:
# If the version string does not contain a dot, fallback
# to version 1
AIIDA_LOGGER.debug('Falling back to version 1 for file {}, '
"version string '{}' unrecognized".format(
fname, version))
version_major = 1
element = None
if version_major == 1:
match = REGEX_ELEMENT_V1.search(upf_contents)
if match:
element = match.group('element_name')
else: # all versions > 1
match = REGEX_ELEMENT_V2.search(upf_contents)
if match:
element = match.group('element_name')
if element is None:
raise ParsingError(
'Unable to find the element of UPF {}'.format(fname))
element = element.capitalize()
if element not in _valid_symbols:
raise ParsingError('Unknown element symbol {} for file {}'.format(
element, fname))
if check_filename:
if not os.path.basename(fname).lower().startswith(element.lower()):
raise ParsingError('Filename {0} was recognized for element '
'{1}, but the filename does not start '
'with {1}'.format(fname, element))
parsed_data['element'] = element
return parsed_data
import os
from six.moves import zip
from aiida.common import AIIDA_LOGGER, exceptions
from aiida.common.datastructures import CalcJobState
from aiida.common.folders import SandboxFolder
from aiida.common.links import LinkType
from aiida.orm import FolderData
from aiida.orm.utils.log import get_dblogger_extra
from aiida.plugins import DataFactory
from aiida.schedulers.datastructures import JobState
REMOTE_WORK_DIRECTORY_LOST_FOUND = 'lost+found'
execlogger = AIIDA_LOGGER.getChild('execmanager')
def upload_calculation(node,
transport,
calc_info,
script_filename,
dry_run=False):
"""Upload a `CalcJob` instance
:param node: the `CalcJobNode`.
:param transport: an already opened transport to use to submit the calculation.
:param calc_info: the calculation info datastructure returned by `CalcJobNode.presubmit`
:param script_filename: the job launch script returned by `CalcJobNode.presubmit`
:return: tuple of ``calc_info`` and ``script_filename``
"""
# For further information please visit http://www.aiida.net #
###########################################################################
"""Data structures used by `Scheduler` instances.
In particular, there is the definition of possible job states (job_states),
the data structure to be filled for job submission (JobTemplate), and
the data structure that is returned when querying for jobs in the scheduler
(JobInfo).
"""
import abc
import enum
from aiida.common import AIIDA_LOGGER
from aiida.common.extendeddicts import AttributeDict, DefaultFieldsAttributeDict
SCHEDULER_LOGGER = AIIDA_LOGGER.getChild('scheduler')
__all__ = (
'JobState', 'JobResource', 'JobTemplate', 'JobInfo', 'NodeNumberJobResource', 'ParEnvJobResource', 'MachineInfo'
)
class JobState(enum.Enum):
"""Enumeration of possible scheduler states of a CalcJob.
There is no FAILED state as every completed job is put in DONE, regardless of success.
"""
UNDETERMINED = 'undetermined'
QUEUED = 'queued'
QUEUED_HELD = 'queued held'
def __init__(self):
self._cache = {}
self._logger = AIIDA_LOGGER.getChild('plugin_version_provider')
def deserialize_list(mainitem, subitems, sep, original_class, original_pk,
lesserrors):
"""Deserialize a Python list."""
# pylint: disable=protected-access
# subitems contains all subitems, here I store only those of
# deepness 1, i.e. if I have subitems '0', '1' and '1.c' I
# store only '0' and '1'
from aiida.common import AIIDA_LOGGER
firstlevelsubdict = {k: v for k, v in subitems.items() if sep not in k}
# For checking, I verify the expected values
expected_set = {'{:d}'.format(i) for i in range(mainitem['ival'])}
received_set = set(firstlevelsubdict.keys())
# If there are more entries than expected, but all expected
# ones are there, I just issue an error but I do not stop.
if not expected_set.issubset(received_set):
if (original_class is not None
and original_class._subspecifier_field_name is not None):
subspecifier_string = '{}={} and '.format(
original_class._subspecifier_field_name, original_pk)
else:
subspecifier_string = ''
if original_class is None:
sourcestr = 'the data passed'
else:
sourcestr = original_class.__name__
raise DeserializationException('Wrong list elements stored in {} for '
"{}key='{}' ({} vs {})".format(
sourcestr, subspecifier_string,
mainitem['key'], expected_set,
received_set))
if expected_set != received_set:
if (original_class is not None
and original_class._subspecifier_field_name is not None):
subspecifier_string = '{}={} and '.format(
original_class._subspecifier_field_name, original_pk)
else:
subspecifier_string = ''
sourcestr = 'the data passed' if original_class is None else original_class.__name__
msg = ('Wrong list elements stored in {} for '
"{}key='{}' ({} vs {})".format(sourcestr, subspecifier_string,
mainitem['key'], expected_set,
received_set))
if lesserrors:
AIIDA_LOGGER.error(msg)
else:
raise DeserializationException(msg)
# I get the values in memory as a dictionary
tempdict = {}
for firstsubk, firstsubv in firstlevelsubdict.items():
# I call recursively the same function to get subitems
newsubitems = {
k[len(firstsubk) + len(sep):]: v
for k, v in subitems.items() if k.startswith(firstsubk + sep)
}
tempdict[firstsubk] = _deserialize_attribute(
mainitem=firstsubv,
subitems=newsubitems,
sep=sep,
original_class=original_class,
original_pk=original_pk)
# And then I put them in a list
retlist = [tempdict['{:d}'.format(i)] for i in range(mainitem['ival'])]
return retlist
def _deserialize_attribute(mainitem,
subitems,
sep,
original_class=None,
original_pk=None,
lesserrors=False):
"""
Deserialize a single attribute.
:param mainitem: the main item (either the attribute itself for base
types (None, string, ...) or the main item for lists and dicts.
Must contain the 'key' key and also the following keys:
datatype, tval, fval, ival, bval, dval.
NOTE that a type check is not performed! tval is expected to be a string,
dval a date, etc.
:param subitems: must be a dictionary of dictionaries. In the top-level dictionary,
the key must be the key of the attribute, stripped of all prefixes
(i.e., if the mainitem has key 'a.b' and we pass subitems
'a.b.0', 'a.b.1', 'a.b.1.c', their keys must be '0', '1', '1.c').
It must be None if the value is not iterable (int, str,
float, ...).
It is an empty dictionary if there are no subitems.
:param sep: a string, the separator between subfields (to separate the
name of a dictionary from the keys it contains, for instance)
:param original_class: if these elements come from a specific subclass
of DbMultipleValueAttributeBaseClass, pass here the class (note: the class,
not the instance!). This is used only in case the wrong number of elements
is found in the raw data, to print a more meaningful message (if the class
has a dbnode associated to it)
:param original_pk: if the elements come from a specific subclass
of DbMultipleValueAttributeBaseClass that has a dbnode associated to it,
pass here the PK integer. This is used only in case the wrong number
of elements is found in the raw data, to print a more meaningful message
:param lesserrors: If set to True, in some cases where the content of the
DB is not consistent but data is still recoverable,
it will just log the message rather than raising
an exception (e.g. if the number of elements of a dictionary is different
from the number declared in the ival field).
:return: the deserialized value
:raise aiida.backends.djsite.db.migrations.DeserializationException: if an error occurs
"""
from aiida.common import json
from aiida.common.timezone import (is_naive, make_aware,
get_current_timezone)
from aiida.common import AIIDA_LOGGER
if mainitem['datatype'] == 'none':
if subitems:
raise DeserializationException("'{}' is of a base type, "
'but has subitems!'.format(
mainitem.key))
return None
elif mainitem['datatype'] == 'bool':
if subitems:
raise DeserializationException("'{}' is of a base type, "
'but has subitems!'.format(
mainitem.key))
return mainitem['bval']
elif mainitem['datatype'] == 'int':
if subitems:
raise DeserializationException("'{}' is of a base type, "
'but has subitems!'.format(
mainitem.key))
return mainitem['ival']
elif mainitem['datatype'] == 'float':
if subitems:
raise DeserializationException("'{}' is of a base type, "
'but has subitems!'.format(
mainitem.key))
return mainitem['fval']
elif mainitem['datatype'] == 'txt':
if subitems:
raise DeserializationException("'{}' is of a base type, "
'but has subitems!'.format(
mainitem.key))
return mainitem['tval']
elif mainitem['datatype'] == 'date':
if subitems:
raise DeserializationException("'{}' is of a base type, "
'but has subitems!'.format(
mainitem.key))
if is_naive(mainitem['dval']):
return make_aware(mainitem['dval'], get_current_timezone())
else:
return mainitem['dval']
elif mainitem['datatype'] == 'list':
# subitems contains all subitems, here I store only those of
# deepness 1, i.e. if I have subitems '0', '1' and '1.c' I
# store only '0' and '1'
firstlevelsubdict = {k: v for k, v in subitems.items() if sep not in k}
# For checking, I verify the expected values
expected_set = set(['{:d}'.format(i) for i in range(mainitem['ival'])])
received_set = set(firstlevelsubdict.keys())
# If there are more entries than expected, but all expected
# ones are there, I just issue an error but I do not stop.
if not expected_set.issubset(received_set):
if (original_class is not None
and original_class._subspecifier_field_name is not None):
subspecifier_string = '{}={} and '.format(
original_class._subspecifier_field_name, original_pk)
else:
subspecifier_string = ''
if original_class is None:
sourcestr = 'the data passed'
else:
sourcestr = original_class.__name__
raise DeserializationException(
'Wrong list elements stored in {} for '
"{}key='{}' ({} vs {})".format(sourcestr, subspecifier_string,
mainitem['key'], expected_set,
received_set))
if expected_set != received_set:
if (original_class is not None
and original_class._subspecifier_field_name is not None):
subspecifier_string = '{}={} and '.format(
original_class._subspecifier_field_name, original_pk)
else:
subspecifier_string = ''
if original_class is None:
sourcestr = 'the data passed'
else:
sourcestr = original_class.__name__
msg = ('Wrong list elements stored in {} for '
"{}key='{}' ({} vs {})".format(sourcestr,
subspecifier_string,
mainitem['key'],
expected_set, received_set))
if lesserrors:
AIIDA_LOGGER.error(msg)
else:
raise DeserializationException(msg)
# I get the values in memory as a dictionary
tempdict = {}
for firstsubk, firstsubv in firstlevelsubdict.items():
# I call recursively the same function to get subitems
newsubitems = {
k[len(firstsubk) + len(sep):]: v
for k, v in subitems.items() if k.startswith(firstsubk + sep)
}
tempdict[firstsubk] = _deserialize_attribute(
mainitem=firstsubv,
subitems=newsubitems,
sep=sep,
original_class=original_class,
original_pk=original_pk)
# And then I put them in a list
retlist = [tempdict['{:d}'.format(i)] for i in range(mainitem['ival'])]
return retlist
elif mainitem['datatype'] == 'dict':
# subitems contains all subitems, here I store only those of
# deepness 1, i.e. if I have subitems '0', '1' and '1.c' I
# store only '0' and '1'
firstlevelsubdict = {k: v for k, v in subitems.items() if sep not in k}
if len(firstlevelsubdict) != mainitem['ival']:
if (original_class is not None
and original_class._subspecifier_field_name is not None):
subspecifier_string = '{}={} and '.format(
original_class._subspecifier_field_name, original_pk)
else:
subspecifier_string = ''
if original_class is None:
sourcestr = 'the data passed'
else:
sourcestr = original_class.__name__
msg = ('Wrong dict length stored in {} for '
"{}key='{}' ({} vs {})".format(sourcestr,
subspecifier_string,
mainitem['key'],
len(firstlevelsubdict),
mainitem['ival']))
if lesserrors:
AIIDA_LOGGER.error(msg)
else:
raise DeserializationException(msg)
# I get the values in memory as a dictionary
tempdict = {}
for firstsubk, firstsubv in firstlevelsubdict.items():
# I call recursively the same function to get subitems
newsubitems = {
k[len(firstsubk) + len(sep):]: v
for k, v in subitems.items() if k.startswith(firstsubk + sep)
}
tempdict[firstsubk] = _deserialize_attribute(
mainitem=firstsubv,
subitems=newsubitems,
sep=sep,
original_class=original_class,
original_pk=original_pk)
return tempdict
elif mainitem['datatype'] == 'json':
try:
return json.loads(mainitem['tval'])
except ValueError:
raise DeserializationException(
'Error in the content of the json field')
else:
raise DeserializationException(
"The type field '{}' is not recognized".format(
mainitem['datatype']))
def upload_psf_family(folder, group_label, group_description, stop_if_existing=True):
"""
Upload a set of PSF files in a given group.
:param folder: a path containing all PSF files to be added.
Only files ending in .PSF (case-insensitive) are considered.
:param group_label: the name of the group to create. If it exists and is
non-empty, a UniquenessError is raised.
:param group_description: a string to be set as the group description.
Overwrites previous descriptions, if the group was existing.
:param stop_if_existing: if True, check for the md5 of the files and,
if the file already exists in the DB, raises a MultipleObjectsError.
If False, simply adds the existing PsfData node to the group.
"""
import os
from aiida import orm
from aiida.common import AIIDA_LOGGER as aiidalogger
from aiida.common.exceptions import UniquenessError
from aiida.orm.querybuilder import QueryBuilder
from aiida_siesta.groups.pseudos import PsfFamily
message = ( #pylint: disable=invalid-name
'This function has been deprecated and will be removed in `v2.0.0`. ' +
'`upload_psf_family` is substitued by `fam.create_from_folder` ' +
'where `fam` is an instance of the families classes in `aiida_pseudo.groups.family`.'
)
warnings.warn(message, AiidaSiestaDeprecationWarning)
if not os.path.isdir(folder):
raise ValueError("folder must be a directory")
# only files, and only those ending with .psf or .PSF;
# go to the real file if it is a symlink
files = [
os.path.realpath(os.path.join(folder, i))
for i in os.listdir(folder)
if os.path.isfile(os.path.join(folder, i)) and i.lower().endswith('.psf')
]
nfiles = len(files)
automatic_user = orm.User.objects.get_default()
group, group_created = PsfFamily.objects.get_or_create(label=group_label, user=automatic_user)
if group.user.email != automatic_user.email:
raise UniquenessError(
"There is already a PsfFamily group with name {}"
", but it belongs to user {}, therefore you "
"cannot modify it".format(group_label, group.user.email)
)
# Always update description, even if the group already existed
group.description = group_description
# NOTE: GROUP SAVED ONLY AFTER CHECKS OF UNICITY
pseudo_and_created = []
for afile in files:
md5sum = md5_file(afile)
qb = QueryBuilder()
qb.append(PsfData, filters={'attributes.md5': {'==': md5sum}})
existing_psf = qb.first()
#existing_psf = PsfData.query(dbattributes__key="md5",
# dbattributes__tval = md5sum)
if existing_psf is None:
# return the psfdata instances, not stored
pseudo, created = PsfData.get_or_create(afile, use_first=True, store_psf=False)
# to check whether only one psf per element exists
# NOTE: actually, created has the meaning of "to_be_created"
pseudo_and_created.append((pseudo, created))
else:
if stop_if_existing:
raise ValueError(
"A PSF with identical MD5 to "
" {} cannot be added with stop_if_existing"
"".format(afile)
)
existing_psf = existing_psf[0]
pseudo_and_created.append((existing_psf, False))
# check whether pseudo are unique per element
elements = [(i[0].element, i[0].md5sum) for i in pseudo_and_created]
# If group already exists, check also that I am not inserting more than
# once the same element
if not group_created:
for aiida_n in group.nodes:
# Skip non-pseudos
if not isinstance(aiida_n, PsfData):
continue
elements.append((aiida_n.element, aiida_n.md5sum))
elements = set(elements) # Discard elements with the same MD5, that would
# not be stored twice
elements_names = [e[0] for e in elements]
if not len(elements_names) == len(set(elements_names)):
duplicates = {x for x in elements_names if elements_names.count(x) > 1}
duplicates_string = ", ".join(i for i in duplicates)
raise UniquenessError("More than one PSF found for the elements: " + duplicates_string + ".")
# At this point, save the group, if still unstored
if group_created:
group.store()
# save the psf in the database, and add them to group
for pseudo, created in pseudo_and_created:
if created:
pseudo.store()
aiidalogger.debug("New node {} created for file {}".format(pseudo.uuid, pseudo.filename))
else:
aiidalogger.debug("Reusing node {} for file {}".format(pseudo.uuid, pseudo.filename))
# Add elements to the group all togetehr
group.add_nodes([pseudo for pseudo, created in pseudo_and_created])
nuploaded = len([_ for _, created in pseudo_and_created if created])
return nfiles, nuploaded
from tempfile import NamedTemporaryFile
from typing import Any, List, Optional, Mapping as MappingType, Tuple, Union
from aiida.common import AIIDA_LOGGER, exceptions
from aiida.common.datastructures import CalcInfo
from aiida.common.folders import SandboxFolder
from aiida.common.links import LinkType
from aiida.orm import load_node, CalcJobNode, Code, FolderData, Node, RemoteData
from aiida.orm.utils.log import get_dblogger_extra
from aiida.plugins import DataFactory
from aiida.schedulers.datastructures import JobState
from aiida.transports import Transport
REMOTE_WORK_DIRECTORY_LOST_FOUND = 'lost+found'
EXEC_LOGGER = AIIDA_LOGGER.getChild('execmanager')
def _find_data_node(inputs: MappingType[str, Any],
uuid: str) -> Optional[Node]:
"""Find and return the node with the given UUID from a nested mapping of input nodes.
:param inputs: (nested) mapping of nodes
:param uuid: UUID of the node to find
:return: instance of `Node` or `None` if not found
"""
data_node = None
for input_node in inputs.values():
if isinstance(input_node, Mapping):
data_node = _find_data_node(input_node, uuid)
