def test_sniff_compressed_dynamic_datatypes_default_on():
# With auto sniffing on, verify the sniffers work and the files match what is expected
# when coming from guess_ext.
datatypes_registry = example_datatype_registry_for_sample(sniff_compressed_dynamic_datatypes_default=True)
fastqsangergz_datatype = datatypes_registry.get_datatype_by_extension('fastqsanger.gz')
fname = sniff.get_test_fname('1.fastqsanger.gz')
assert fastqsangergz_datatype.sniff(fname)
sniff_order = datatypes_registry.sniff_order
fname = sniff.get_test_fname('1.fastqsanger.gz')
assert sniff.guess_ext(fname, sniff_order) == 'fastqsanger.gz'
fname = sniff.get_test_fname('1.fastqsanger.bz2')
assert sniff.guess_ext(fname, sniff_order) == 'fastqsanger.bz2'
def test_sniff_compressed_dynamic_datatypes_default_off():
# Redo last tests with auto compressed sniffing disabled and they should not longer result from guess_ext.
datatypes_registry = example_datatype_registry_for_sample(sniff_compressed_dynamic_datatypes_default=False)
# sniffer still returns True for these files...
fastqsangergz_datatype = datatypes_registry.get_datatype_by_extension('fastqsanger.gz')
fname = sniff.get_test_fname('1.fastqsanger.gz')
assert fastqsangergz_datatype.sniff(fname)
# but they don't report as matching the specified sniff_order.
sniff_order = datatypes_registry.sniff_order
fname = sniff.get_test_fname('1.fastqsanger.gz')
assert 'fastq' not in sniff.guess_ext(fname, sniff_order)
fname = sniff.get_test_fname('1.fastqsanger.bz2')
assert 'fastq' not in sniff.guess_ext(fname, sniff_order)
def test_sniff_compressed_dynamic_datatypes_default_on():
# With auto sniffing on, verify the sniffers work and the files match what is expected
# when coming from guess_ext.
datatypes_registry = example_datatype_registry_for_sample(
sniff_compressed_dynamic_datatypes_default=True)
fastqsangergz_datatype = datatypes_registry.get_datatype_by_extension(
'fastqsanger.gz')
fname = sniff.get_test_fname('1.fastqsanger.gz')
assert fastqsangergz_datatype.sniff(fname)
sniff_order = datatypes_registry.sniff_order
fname = sniff.get_test_fname('1.fastqsanger.gz')
assert sniff.guess_ext(fname, sniff_order) == 'fastqsanger.gz'
fname = sniff.get_test_fname('1.fastqsanger.bz2')
assert sniff.guess_ext(fname, sniff_order) == 'fastqsanger.bz2'
def test_sniff_compressed_dynamic_datatypes_default_off():
# Redo last tests with auto compressed sniffing disabled and they should not longer result from guess_ext.
datatypes_registry = example_datatype_registry_for_sample(
sniff_compressed_dynamic_datatypes_default=False)
# sniffer still returns True for these files...
fastqsangergz_datatype = datatypes_registry.get_datatype_by_extension(
'fastqsanger.gz')
fname = sniff.get_test_fname('1.fastqsanger.gz')
assert fastqsangergz_datatype.sniff(fname)
# but they don't report as matching the specified sniff_order.
sniff_order = datatypes_registry.sniff_order
fname = sniff.get_test_fname('1.fastqsanger.gz')
assert 'fastq' not in sniff.guess_ext(fname, sniff_order)
fname = sniff.get_test_fname('1.fastqsanger.bz2')
assert 'fastq' not in sniff.guess_ext(fname, sniff_order)
def exec_after_process( app, inp_data, out_data, param_dict, tool=None, stdout=None, stderr=None ):
"""Verifies the data after the run"""
name, data = out_data.items()[0]
if data.state == data.states.OK:
data.info = data.name
if data.extension == 'txt':
data_type = sniff.guess_ext( data.file_name, sniff_order=app.datatypes_registry.sniff_order )
data = app.datatypes_registry.change_datatype( data, data_type )
data.set_peek()
data.set_size()
data.flush()
def sniff_and_handle_data_type(file_path, datatypes_registry):
"""
The sniff.handle_uploaded_dataset_file() method in Galaxy performs dual
functions: it sniffs the filetype and if it's a compressed archive for
a non compressed datatype such as fasta, it will be unpacked.
"""
ext = sniff.handle_uploaded_dataset_file(file_path, datatypes_registry)
if not ext or ext == "data":
is_binary = check_binary(file_path)
ext = sniff.guess_ext(file_path,
datatypes_registry.sniff_order,
is_binary=is_binary)
return ext
def handle_sniffable_binary_check(data_type, ext, path, registry):
"""Return modified values of data_type and ext if sniffable binary encountered.
Precondition: check_binary called returned True.
"""
# Sniff the data type
guessed_ext = sniff.guess_ext(path, registry.sniff_order)
# Set data_type only if guessed_ext is a binary datatype
datatype = registry.get_datatype_by_extension(guessed_ext)
if isinstance(datatype, Binary):
data_type = guessed_ext
ext = guessed_ext
return data_type, ext
def detect_datatype(self, trans, dataset_assoc):
"""Sniff and assign the datatype to a given dataset association (ldda or hda)"""
data = trans.sa_session.query(self.model_class).get(dataset_assoc.id)
if data.datatype.is_datatype_change_allowed():
if not data.ok_to_edit_metadata():
raise exceptions.ItemAccessibilityException('This dataset is currently being used as input or output. You cannot change datatype until the jobs have completed or you have canceled them.')
else:
path = data.dataset.file_name
is_binary = check_binary(path)
datatype = sniff.guess_ext(path, trans.app.datatypes_registry.sniff_order, is_binary=is_binary)
trans.app.datatypes_registry.change_datatype(data, datatype)
trans.sa_session.flush()
self.set_metadata(trans, dataset_assoc)
else:
raise exceptions.InsufficientPermissionsException(f'Changing datatype "{data.extension}" is not allowed.')
def add_file(self, trans, file_obj, file_name, file_type, dbkey, info ):
temp_name = sniff.stream_to_file(file_obj)
sniff.convert_newlines(temp_name)
if file_type == 'auto':
ext = sniff.guess_ext(temp_name)
else:
ext = file_type
data = trans.app.model.Dataset()
data.name = file_name
data.extension = ext
data.dbkey = dbkey
data.info = info
data.flush()
shutil.move(temp_name, data.file_name)
data.state = data.states.OK
data.init_meta()
data.set_peek()
if isinstance( data.datatype, datatypes.interval.Interval ):
if data.missing_meta():
data.extension = 'tabular'
trans.history.add_dataset( data )
trans.app.model.flush()
return data
def add_file(self, trans, file_obj, file_name, file_type, dbkey, info):
temp_name = sniff.stream_to_file(file_obj)
sniff.convert_newlines(temp_name)
if file_type == 'auto':
ext = sniff.guess_ext(temp_name)
else:
ext = file_type
data = trans.app.model.Dataset()
data.name = file_name
data.extension = ext
data.dbkey = dbkey
data.info = info
data.flush()
shutil.move(temp_name, data.file_name)
data.state = data.states.OK
data.init_meta()
data.set_peek()
if isinstance(data.datatype, datatypes.interval.Interval):
if data.missing_meta():
data.extension = 'tabular'
trans.history.add_dataset(data)
trans.app.model.flush()
return data
def add_file(dataset, registry, output_path):
ext = None
compression_type = None
line_count = None
converted_path = None
stdout = None
link_data_only_str = dataset.get('link_data_only', 'copy_files')
if link_data_only_str not in ['link_to_files', 'copy_files']:
raise UploadProblemException(
"Invalid setting '%s' for option link_data_only - upload request misconfigured"
% link_data_only_str)
link_data_only = link_data_only_str == 'link_to_files'
# run_as_real_user is estimated from galaxy config (external chmod indicated of inputs executed)
# If this is True we always purge supplied upload inputs so they are cleaned up and we reuse their
# paths during data conversions since this user already owns that path.
# Older in_place check for upload jobs created before 18.01, TODO remove in 19.XX. xref #5206
run_as_real_user = dataset.get('run_as_real_user', False) or dataset.get(
"in_place", False)
# purge_source defaults to True unless this is an FTP import and
# ftp_upload_purge has been overridden to False in Galaxy's config.
# We set purge_source to False if:
# - the job does not have write access to the file, e.g. when running as the
# real user
# - the files are uploaded from external paths.
purge_source = dataset.get(
'purge_source',
True) and not run_as_real_user and dataset.type not in ('server_dir',
'path_paste')
# in_place is True unless we are running as a real user or importing external paths (i.e.
# this is a real upload and not a path paste or ftp import).
# in_place should always be False if running as real user because the uploaded file will
# be owned by Galaxy and not the user and it should be False for external paths so Galaxy doesn't
# modify files not controlled by Galaxy.
in_place = not run_as_real_user and dataset.type not in ('server_dir',
'path_paste',
'ftp_import')
# Base on the check_upload_content Galaxy config option and on by default, this enables some
# security related checks on the uploaded content, but can prevent uploads from working in some cases.
check_content = dataset.get('check_content', True)
# auto_decompress is a request flag that can be swapped off to prevent Galaxy from automatically
# decompressing archive files before sniffing.
auto_decompress = dataset.get('auto_decompress', True)
try:
dataset.file_type
except AttributeError:
raise UploadProblemException(
'Unable to process uploaded file, missing file_type parameter.')
if dataset.type == 'url':
try:
dataset.path = sniff.stream_url_to_file(dataset.path)
except Exception as e:
raise UploadProblemException('Unable to fetch %s\n%s' %
(dataset.path, str(e)))
# See if we have an empty file
if not os.path.exists(dataset.path):
raise UploadProblemException(
'Uploaded temporary file (%s) does not exist.' % dataset.path)
if not os.path.getsize(dataset.path) > 0:
raise UploadProblemException('The uploaded file is empty')
# Does the first 1K contain a null?
is_binary = check_binary(dataset.path)
# Decompress if needed/desired and determine/validate filetype. If a keep-compressed datatype is explicitly selected
# or if autodetection is selected and the file sniffs as a keep-compressed datatype, it will not be decompressed.
if not link_data_only:
if is_zip(dataset.path) and not is_single_file_zip(dataset.path):
stdout = 'ZIP file contained more than one file, only the first file was added to Galaxy.'
try:
ext, converted_path, compression_type = sniff.handle_uploaded_dataset_file(
dataset.path,
registry,
ext=dataset.file_type,
tmp_prefix='data_id_%s_upload_' % dataset.dataset_id,
tmp_dir=output_adjacent_tmpdir(output_path),
in_place=in_place,
check_content=check_content,
is_binary=is_binary,
auto_decompress=auto_decompress,
uploaded_file_ext=os.path.splitext(
dataset.name)[1].lower().lstrip('.'),
convert_to_posix_lines=dataset.to_posix_lines,
convert_spaces_to_tabs=dataset.space_to_tab,
)
except sniff.InappropriateDatasetContentError as exc:
raise UploadProblemException(str(exc))
elif dataset.file_type == 'auto':
# Link mode can't decompress anyway, so enable sniffing for keep-compressed datatypes even when auto_decompress
# is enabled
os.environ['GALAXY_SNIFFER_VALIDATE_MODE'] = '1'
ext = sniff.guess_ext(dataset.path,
registry.sniff_order,
is_binary=is_binary)
os.environ.pop('GALAXY_SNIFFER_VALIDATE_MODE')
# The converted path will be the same as the input path if no conversion was done (or in-place conversion is used)
converted_path = None if converted_path == dataset.path else converted_path
# Validate datasets where the filetype was explicitly set using the filetype's sniffer (if any)
if dataset.file_type != 'auto':
datatype = registry.get_datatype_by_extension(dataset.file_type)
# Enable sniffer "validate mode" (prevents certain sniffers from disabling themselves)
os.environ['GALAXY_SNIFFER_VALIDATE_MODE'] = '1'
if hasattr(datatype, 'sniff') and not datatype.sniff(dataset.path):
stdout = (
"Warning: The file 'Type' was set to '{ext}' but the file does not appear to be of that"
" type".format(ext=dataset.file_type))
os.environ.pop('GALAXY_SNIFFER_VALIDATE_MODE')
# Handle unsniffable binaries
if is_binary and ext == 'binary':
upload_ext = os.path.splitext(dataset.name)[1].lower().lstrip('.')
if registry.is_extension_unsniffable_binary(upload_ext):
stdout = (
"Warning: The file's datatype cannot be determined from its contents and was guessed based on"
" its extension, to avoid this warning, manually set the file 'Type' to '{ext}' when uploading"
" this type of file".format(ext=upload_ext))
ext = upload_ext
else:
stdout = (
"The uploaded binary file format cannot be determined automatically, please set the file 'Type'"
" manually")
datatype = registry.get_datatype_by_extension(ext)
# Strip compression extension from name
if compression_type and not getattr(
datatype, 'compressed',
False) and dataset.name.endswith('.' + compression_type):
dataset.name = dataset.name[:-len('.' + compression_type)]
# Move dataset
if link_data_only:
# Never alter a file that will not be copied to Galaxy's local file store.
if datatype.dataset_content_needs_grooming(dataset.path):
err_msg = 'The uploaded files need grooming, so change your <b>Copy data into Galaxy?</b> selection to be ' + \
'<b>Copy files into Galaxy</b> instead of <b>Link to files without copying into Galaxy</b> so grooming can be performed.'
raise UploadProblemException(err_msg)
if not link_data_only:
# Move the dataset to its "real" path. converted_path is a tempfile so we move it even if purge_source is False.
if purge_source or converted_path:
try:
shutil.move(converted_path or dataset.path, output_path)
except OSError as e:
# We may not have permission to remove the input
if e.errno != errno.EACCES:
raise
else:
shutil.copy(dataset.path, output_path)
# Write the job info
stdout = stdout or 'uploaded %s file' % ext
info = dict(type='dataset',
dataset_id=dataset.dataset_id,
ext=ext,
stdout=stdout,
name=dataset.name,
line_count=line_count)
if dataset.get('uuid', None) is not None:
info['uuid'] = dataset.get('uuid')
# FIXME: does this belong here? also not output-adjacent-tmpdir aware =/
if not link_data_only and datatype and datatype.dataset_content_needs_grooming(
output_path):
# Groom the dataset content if necessary
datatype.groom_dataset_content(output_path)
return info
def run_job(self, job):
if job.params['type'] == 'init_transfer':
# TODO: don't create new downloads on restart.
if job.params['protocol'] in ['http', 'https']:
results = []
for result in job.params['results'].values():
result['transfer_job'] = self.app.transfer_manager.new(protocol=job.params['protocol'],
name=result['name'],
datatype=result['datatype'],
url=result['url'])
results.append(result)
elif job.params['protocol'] == 'scp':
results = []
result = {}
sample_datasets_dict = job.params['sample_datasets_dict']
# sample_datasets_dict looks something like the following. The outer dictionary keys are SampleDataset ids.
# {'7': {'status': 'Not started', 'name': '3.bed', 'file_path': '/tmp/library/3.bed', 'sample_id': 7,
# 'external_service_id': 2, 'error_msg': '', 'size': '8.0K'}}
for sample_dataset_id, sample_dataset_info_dict in sample_datasets_dict.items():
result = {}
result['transfer_job'] = self.app.transfer_manager.new(protocol=job.params['protocol'],
host=job.params['host'],
user_name=job.params['user_name'],
password=job.params['password'],
sample_dataset_id=sample_dataset_id,
status=sample_dataset_info_dict['status'],
name=sample_dataset_info_dict['name'],
file_path=sample_dataset_info_dict['file_path'],
sample_id=sample_dataset_info_dict['sample_id'],
external_service_id=sample_dataset_info_dict['external_service_id'],
error_msg=sample_dataset_info_dict['error_msg'],
size=sample_dataset_info_dict['size'])
results.append(result)
self.app.transfer_manager.run([r['transfer_job'] for r in results])
for result in results:
transfer_job = result.pop('transfer_job')
self.create_job(None,
transfer_job_id=transfer_job.id,
result=transfer_job.params,
sample_id=job.params['sample_id'])
# Update the state of the relevant SampleDataset
new_status = self.app.model.SampleDataset.transfer_status.IN_QUEUE
self._update_sample_dataset_status(protocol=job.params['protocol'],
sample_id=job.params['sample_id'],
result_dict=transfer_job.params,
new_status=new_status,
error_msg='')
job.state = self.app.model.DeferredJob.states.OK
self.sa_session.add(job)
self.sa_session.flush()
# TODO: Error handling: failure executing, or errors returned from the manager
if job.params['type'] == 'finish_transfer':
protocol = job.params['protocol']
# Update the state of the relevant SampleDataset
new_status = self.app.model.SampleDataset.transfer_status.ADD_TO_LIBRARY
if protocol in ['http', 'https']:
result_dict = job.params['result']
library_dataset_name = result_dict['name']
extension = result_dict['datatype']
elif protocol in ['scp']:
# In this case, job.params will be a dictionary that contains a key named 'result'. The value
# of the result key is a dictionary that looks something like:
# {'sample_dataset_id': '8', 'status': 'Not started', 'protocol': 'scp', 'name': '3.bed',
# 'file_path': '/data/library/3.bed', 'host': '127.0.0.1', 'sample_id': 8, 'external_service_id': 2,
# 'local_path': '/tmp/kjl2Ss4', 'password': '******', 'user_name': 'gvk', 'error_msg': '', 'size': '8.0K'}
try:
tj = self.sa_session.query(self.app.model.TransferJob).get(int(job.params['transfer_job_id']))
result_dict = tj.params
result_dict['local_path'] = tj.path
except Exception as e:
log.error("Updated transfer result unavailable, using old result. Error was: %s" % str(e))
result_dict = job.params['result']
library_dataset_name = result_dict['name']
# Determine the data format (see the relevant TODO item in the manual_data_transfer plugin)..
extension = sniff.guess_ext(result_dict['local_path'], sniff_order=self.app.datatypes_registry.sniff_order)
self._update_sample_dataset_status(protocol=job.params['protocol'],
sample_id=int(job.params['sample_id']),
result_dict=result_dict,
new_status=new_status,
error_msg='')
sample = self.sa_session.query(self.app.model.Sample).get(int(job.params['sample_id']))
ld = self.app.model.LibraryDataset(folder=sample.folder, name=library_dataset_name)
self.sa_session.add(ld)
self.sa_session.flush()
self.app.security_agent.copy_library_permissions(FakeTrans(self.app), sample.folder, ld)
ldda = self.app.model.LibraryDatasetDatasetAssociation(name=library_dataset_name,
extension=extension,
dbkey='?',
library_dataset=ld,
create_dataset=True,
sa_session=self.sa_session)
ldda.message = 'Transferred by the Data Transfer Plugin'
self.sa_session.add(ldda)
self.sa_session.flush()
ldda.state = ldda.states.QUEUED # flushed in the set property
ld.library_dataset_dataset_association_id = ldda.id
self.sa_session.add(ld)
self.sa_session.flush()
try:
# Move the dataset from its temporary location
shutil.move(job.transfer_job.path, ldda.file_name)
ldda.init_meta()
for name, spec in ldda.metadata.spec.items():
if name not in ['name', 'info', 'dbkey', 'base_name']:
if spec.get('default'):
setattr(ldda.metadata, name, spec.unwrap(spec.get('default')))
self.app.datatypes_registry.set_external_metadata_tool.tool_action.execute(self.app.datatypes_registry.set_external_metadata_tool,
FakeTrans(self.app,
history=sample.history,
user=sample.request.user),
incoming={'input1': ldda})
ldda.state = ldda.states.OK
# TODO: not sure if this flush is necessary
self.sa_session.add(ldda)
self.sa_session.flush()
except Exception as e:
log.exception('Failure preparing library dataset for finished transfer job (id: %s) via deferred job (id: %s):' %
(str(job.transfer_job.id), str(job.id)))
ldda.state = ldda.states.ERROR
if sample.workflow:
log.debug("\n\nLogging sample mappings as: %s" % sample.workflow['mappings'])
log.debug("job.params: %s" % job.params)
# We have a workflow. Update all mappings to ldda's, and when the final one is done
# execute_workflow with either the provided history, or a new one.
sub_done = True
rep_done = False
for k, v in sample.workflow['mappings'].items():
if 'hda' not in v and v['ds_tag'].startswith('hi|'):
sample.workflow['mappings'][k]['hda'] = self.app.security.decode_id(v['ds_tag'][3:])
for key, value in sample.workflow['mappings'].items():
if 'url' in value and value['url'] == job.params['result']['url']:
# DBTODO Make sure all ds| mappings get the URL of the dataset, for linking to later.
# If this dataset maps to what we just finished, update the ldda id in the sample.
sample.workflow['mappings'][key]['ldda'] = ldda.id
rep_done = True
# DBTODO replace the hi| mappings with the hda here. Just rip off the first three chars.
elif 'ldda' not in value and 'hda' not in value:
# We're not done if some mappings still don't have ldda or hda mappings.
sub_done = False
if sub_done and rep_done:
if not sample.history:
new_history = self.app.model.History(name="New History From %s" % sample.name, user=sample.request.user)
self.sa_session.add(new_history)
sample.history = new_history
self.sa_session.flush()
self._execute_workflow(sample)
# Check the workflow for substitution done-ness
self.sa_session.add(sample)
self.sa_session.flush()
elif sample.history:
# We don't have a workflow, but a history was provided.
# No processing, go ahead and chunk everything in the history.
if ldda.dataset.state in ['new', 'upload', 'queued', 'running', 'empty', 'discarded']:
log.error("Cannot import dataset '%s' to user history since its state is '%s'. " % (ldda.name, ldda.dataset.state))
elif ldda.dataset.state in ['ok', 'error']:
ldda.to_history_dataset_association(target_history=sample.history, add_to_history=True)
# Finished
job.state = self.app.model.DeferredJob.states.OK
self.sa_session.add(job)
self.sa_session.flush()
# Update the state of the relevant SampleDataset
new_status = self.app.model.SampleDataset.transfer_status.COMPLETE
self._update_sample_dataset_status(protocol=job.params['protocol'],
sample_id=int(job.params['sample_id']),
result_dict=job.params['result'],
new_status=new_status,
error_msg='')
if sample.datasets and not sample.untransferred_dataset_files:
# Update the state of the sample to the sample's request type's final state.
new_state = sample.request.type.final_sample_state
self._update_sample_state(sample.id, new_state)
# Update the state of the request, if possible
self._update_request_state(sample.request.id)
def run_job(self, job):
if job.params['type'] == 'init_transfer':
# TODO: don't create new downloads on restart.
if job.params['protocol'] in ['http', 'https']:
results = []
for result in job.params['results'].values():
result['transfer_job'] = self.app.transfer_manager.new(
protocol=job.params['protocol'],
name=result['name'],
datatype=result['datatype'],
url=result['url'])
results.append(result)
elif job.params['protocol'] == 'scp':
results = []
result = {}
sample_datasets_dict = job.params['sample_datasets_dict']
# sample_datasets_dict looks something like the following. The outer dictionary keys are SampleDataset ids.
# {'7': {'status': 'Not started', 'name': '3.bed', 'file_path': '/tmp/library/3.bed', 'sample_id': 7,
# 'external_service_id': 2, 'error_msg': '', 'size': '8.0K'}}
for sample_dataset_id, sample_dataset_info_dict in sample_datasets_dict.items(
):
result = {}
result['transfer_job'] = self.app.transfer_manager.new(
protocol=job.params['protocol'],
host=job.params['host'],
user_name=job.params['user_name'],
password=job.params['password'],
sample_dataset_id=sample_dataset_id,
status=sample_dataset_info_dict['status'],
name=sample_dataset_info_dict['name'],
file_path=sample_dataset_info_dict['file_path'],
sample_id=sample_dataset_info_dict['sample_id'],
external_service_id=sample_dataset_info_dict[
'external_service_id'],
error_msg=sample_dataset_info_dict['error_msg'],
size=sample_dataset_info_dict['size'])
results.append(result)
self.app.transfer_manager.run([r['transfer_job'] for r in results])
for result in results:
transfer_job = result.pop('transfer_job')
self.create_job(None,
transfer_job_id=transfer_job.id,
result=transfer_job.params,
sample_id=job.params['sample_id'])
# Update the state of the relevant SampleDataset
new_status = self.app.model.SampleDataset.transfer_status.IN_QUEUE
self._update_sample_dataset_status(
protocol=job.params['protocol'],
sample_id=job.params['sample_id'],
result_dict=transfer_job.params,
new_status=new_status,
error_msg='')
job.state = self.app.model.DeferredJob.states.OK
self.sa_session.add(job)
self.sa_session.flush()
# TODO: Error handling: failure executing, or errors returned from the manager
if job.params['type'] == 'finish_transfer':
protocol = job.params['protocol']
# Update the state of the relevant SampleDataset
new_status = self.app.model.SampleDataset.transfer_status.ADD_TO_LIBRARY
if protocol in ['http', 'https']:
result_dict = job.params['result']
library_dataset_name = result_dict['name']
extension = result_dict['datatype']
elif protocol in ['scp']:
# In this case, job.params will be a dictionary that contains a key named 'result'. The value
# of the result key is a dictionary that looks something like:
# {'sample_dataset_id': '8', 'status': 'Not started', 'protocol': 'scp', 'name': '3.bed',
# 'file_path': '/data/library/3.bed', 'host': '127.0.0.1', 'sample_id': 8, 'external_service_id': 2,
# 'local_path': '/tmp/kjl2Ss4', 'password': '******', 'user_name': 'gvk', 'error_msg': '', 'size': '8.0K'}
try:
tj = self.sa_session.query(self.app.model.TransferJob).get(
int(job.params['transfer_job_id']))
result_dict = tj.params
result_dict['local_path'] = tj.path
except Exception as e:
log.error(
"Updated transfer result unavailable, using old result. Error was: %s"
% str(e))
result_dict = job.params['result']
library_dataset_name = result_dict['name']
# Determine the data format (see the relevant TODO item in the manual_data_transfer plugin)..
extension = sniff.guess_ext(
result_dict['local_path'],
sniff_order=self.app.datatypes_registry.sniff_order)
self._update_sample_dataset_status(protocol=job.params['protocol'],
sample_id=int(
job.params['sample_id']),
result_dict=result_dict,
new_status=new_status,
error_msg='')
sample = self.sa_session.query(self.app.model.Sample).get(
int(job.params['sample_id']))
ld = self.app.model.LibraryDataset(folder=sample.folder,
name=library_dataset_name)
self.sa_session.add(ld)
self.sa_session.flush()
self.app.security_agent.copy_library_permissions(
FakeTrans(self.app), sample.folder, ld)
ldda = self.app.model.LibraryDatasetDatasetAssociation(
name=library_dataset_name,
extension=extension,
dbkey='?',
library_dataset=ld,
create_dataset=True,
sa_session=self.sa_session)
ldda.message = 'Transferred by the Data Transfer Plugin'
self.sa_session.add(ldda)
self.sa_session.flush()
ldda.state = ldda.states.QUEUED # flushed in the set property
ld.library_dataset_dataset_association_id = ldda.id
self.sa_session.add(ld)
self.sa_session.flush()
try:
# Move the dataset from its temporary location
shutil.move(job.transfer_job.path, ldda.file_name)
ldda.init_meta()
for name, spec in ldda.metadata.spec.items():
if name not in ['name', 'info', 'dbkey', 'base_name']:
if spec.get('default'):
setattr(ldda.metadata, name,
spec.unwrap(spec.get('default')))
self.app.datatypes_registry.set_external_metadata_tool.tool_action.execute(
self.app.datatypes_registry.set_external_metadata_tool,
FakeTrans(self.app,
history=sample.history,
user=sample.request.user),
incoming={'input1': ldda})
ldda.state = ldda.states.OK
# TODO: not sure if this flush is necessary
self.sa_session.add(ldda)
self.sa_session.flush()
except Exception as e:
log.exception(
'Failure preparing library dataset for finished transfer job (id: %s) via deferred job (id: %s):'
% (str(job.transfer_job.id), str(job.id)))
ldda.state = ldda.states.ERROR
if sample.workflow:
log.debug("\n\nLogging sample mappings as: %s" %
sample.workflow['mappings'])
log.debug("job.params: %s" % job.params)
# We have a workflow. Update all mappings to ldda's, and when the final one is done
# execute_workflow with either the provided history, or a new one.
sub_done = True
rep_done = False
for k, v in sample.workflow['mappings'].items():
if 'hda' not in v and v['ds_tag'].startswith('hi|'):
sample.workflow['mappings'][k][
'hda'] = self.app.security.decode_id(
v['ds_tag'][3:])
for key, value in sample.workflow['mappings'].items():
if 'url' in value and value['url'] == job.params['result'][
'url']:
# DBTODO Make sure all ds| mappings get the URL of the dataset, for linking to later.
# If this dataset maps to what we just finished, update the ldda id in the sample.
sample.workflow['mappings'][key]['ldda'] = ldda.id
rep_done = True
# DBTODO replace the hi| mappings with the hda here. Just rip off the first three chars.
elif 'ldda' not in value and 'hda' not in value:
# We're not done if some mappings still don't have ldda or hda mappings.
sub_done = False
if sub_done and rep_done:
if not sample.history:
new_history = self.app.model.History(
name="New History From %s" % sample.name,
user=sample.request.user)
self.sa_session.add(new_history)
sample.history = new_history
self.sa_session.flush()
self._execute_workflow(sample)
# Check the workflow for substitution done-ness
self.sa_session.add(sample)
self.sa_session.flush()
elif sample.history:
# We don't have a workflow, but a history was provided.
# No processing, go ahead and chunk everything in the history.
if ldda.dataset.state in [
'new', 'upload', 'queued', 'running', 'empty',
'discarded'
]:
log.error(
"Cannot import dataset '%s' to user history since its state is '%s'. "
% (ldda.name, ldda.dataset.state))
elif ldda.dataset.state in ['ok', 'error']:
ldda.to_history_dataset_association(
target_history=sample.history, add_to_history=True)
# Finished
job.state = self.app.model.DeferredJob.states.OK
self.sa_session.add(job)
self.sa_session.flush()
# Update the state of the relevant SampleDataset
new_status = self.app.model.SampleDataset.transfer_status.COMPLETE
self._update_sample_dataset_status(
protocol=job.params['protocol'],
sample_id=int(job.params['sample_id']),
result_dict=job.params['result'],
new_status=new_status,
error_msg='')
if sample.datasets and not sample.untransferred_dataset_files:
# Update the state of the sample to the sample's request type's final state.
new_state = sample.request.type.final_sample_state
self._update_sample_state(sample.id, new_state)
# Update the state of the request, if possible
self._update_request_state(sample.request.id)
file_err( 'Unable to fetch %s\n%s' % ( dataset.path, str( e ) ), dataset, json_file )
return
dataset.path = temp_name
dataset.is_multi_byte = is_multi_byte
# See if we have an empty file
if not os.path.exists( dataset.path ):
file_err( 'Uploaded temporary file (%s) does not exist. Please' % dataset.path, dataset, json_file )
return
if not os.path.getsize( dataset.path ) > 0:
file_err( 'The uploaded file is empty', dataset, json_file )
return
if 'is_multi_byte' not in dir( dataset ):
dataset.is_multi_byte = util.is_multi_byte( open( dataset.path, 'r' ).read( 1024 ) )
if dataset.is_multi_byte:
ext = sniff.guess_ext( dataset.path, is_multi_byte=True )
data_type = ext
else:
# See if we have a gzipped file, which, if it passes our restrictions, we'll uncompress
is_gzipped, is_valid = check_gzip( dataset.path )
if is_gzipped and not is_valid:
file_err( 'The uploaded file contains inappropriate content', dataset, json_file )
return
elif is_gzipped and is_valid:
# We need to uncompress the temp_name file
CHUNK_SIZE = 2**20 # 1Mb
fd, uncompressed = tempfile.mkstemp( prefix='data_id_%s_upload_gunzip_' % dataset.dataset_id, dir=os.path.dirname( dataset.path ) )
gzipped_file = gzip.GzipFile( dataset.path )
while 1:
try:
chunk = gzipped_file.read( CHUNK_SIZE )
def handle_upload(
registry,
path, # dataset.path
requested_ext, # dataset.file_type
name, # dataset.name,
tmp_prefix,
tmp_dir,
check_content,
link_data_only,
in_place,
auto_decompress,
convert_to_posix_lines,
convert_spaces_to_tabs,
):
stdout = None
converted_path = None
multi_file_zip = False
# Does the first 1K contain a null?
is_binary = check_binary(path)
# Decompress if needed/desired and determine/validate filetype. If a keep-compressed datatype is explicitly selected
# or if autodetection is selected and the file sniffs as a keep-compressed datatype, it will not be decompressed.
if not link_data_only:
if auto_decompress and is_zip(path) and not is_single_file_zip(path):
multi_file_zip = True
try:
ext, converted_path, compression_type = sniff.handle_uploaded_dataset_file_internal(
path,
registry,
ext=requested_ext,
tmp_prefix=tmp_prefix,
tmp_dir=tmp_dir,
in_place=in_place,
check_content=check_content,
is_binary=is_binary,
auto_decompress=auto_decompress,
uploaded_file_ext=os.path.splitext(name)[1].lower().lstrip('.'),
convert_to_posix_lines=convert_to_posix_lines,
convert_spaces_to_tabs=convert_spaces_to_tabs,
)
except sniff.InappropriateDatasetContentError as exc:
raise UploadProblemException(str(exc))
elif requested_ext == 'auto':
ext = sniff.guess_ext(path, registry.sniff_order, is_binary=is_binary)
else:
ext = requested_ext
# The converted path will be the same as the input path if no conversion was done (or in-place conversion is used)
converted_path = None if converted_path == path else converted_path
# Validate datasets where the filetype was explicitly set using the filetype's sniffer (if any)
if requested_ext != 'auto':
datatype = registry.get_datatype_by_extension(requested_ext)
# Enable sniffer "validate mode" (prevents certain sniffers from disabling themselves)
if check_content and hasattr(datatype, 'sniff') and not datatype.sniff(path):
stdout = ("Warning: The file 'Type' was set to '{ext}' but the file does not appear to be of that"
" type".format(ext=requested_ext))
# Handle unsniffable binaries
if is_binary and ext == 'binary':
upload_ext = os.path.splitext(name)[1].lower().lstrip('.')
if registry.is_extension_unsniffable_binary(upload_ext):
stdout = ("Warning: The file's datatype cannot be determined from its contents and was guessed based on"
" its extension, to avoid this warning, manually set the file 'Type' to '{ext}' when uploading"
" this type of file".format(ext=upload_ext))
ext = upload_ext
else:
stdout = ("The uploaded binary file format cannot be determined automatically, please set the file 'Type'"
" manually")
datatype = registry.get_datatype_by_extension(ext)
if multi_file_zip and not getattr(datatype, 'compressed', False):
stdout = 'ZIP file contained more than one file, only the first file was added to Galaxy.'
return stdout, ext, datatype, is_binary, converted_path
def add_file(dataset, registry, json_file, output_path):
data_type = None
line_count = None
converted_path = None
stdout = None
link_data_only = dataset.get('link_data_only', 'copy_files')
in_place = dataset.get('in_place', True)
purge_source = dataset.get('purge_source', True)
try:
ext = dataset.file_type
except AttributeError:
file_err(
'Unable to process uploaded file, missing file_type parameter.',
dataset, json_file)
return
if dataset.type == 'url':
try:
page = urlopen(
dataset.path) # page will be .close()ed by sniff methods
temp_name, dataset.is_multi_byte = sniff.stream_to_file(
page,
prefix='url_paste',
source_encoding=util.get_charset_from_http_headers(
page.headers))
except Exception as e:
file_err('Unable to fetch %s\n%s' % (dataset.path, str(e)),
dataset, json_file)
return
dataset.path = temp_name
# See if we have an empty file
if not os.path.exists(dataset.path):
file_err('Uploaded temporary file (%s) does not exist.' % dataset.path,
dataset, json_file)
return
if not os.path.getsize(dataset.path) > 0:
file_err('The uploaded file is empty', dataset, json_file)
return
if not dataset.type == 'url':
# Already set is_multi_byte above if type == 'url'
try:
dataset.is_multi_byte = multi_byte.is_multi_byte(
codecs.open(dataset.path, 'r', 'utf-8').read(100))
except UnicodeDecodeError as e:
dataset.is_multi_byte = False
# Is dataset an image?
i_ext = get_image_ext(dataset.path)
if i_ext:
ext = i_ext
data_type = ext
# Is dataset content multi-byte?
elif dataset.is_multi_byte:
data_type = 'multi-byte char'
ext = sniff.guess_ext(dataset.path,
registry.sniff_order,
is_multi_byte=True)
# Is dataset content supported sniffable binary?
else:
# FIXME: This ignores the declared sniff order in datatype_conf.xml
# resulting in improper behavior
type_info = Binary.is_sniffable_binary(dataset.path)
if type_info:
data_type = type_info[0]
ext = type_info[1]
if not data_type:
root_datatype = registry.get_datatype_by_extension(dataset.file_type)
if getattr(root_datatype, 'compressed', False):
data_type = 'compressed archive'
ext = dataset.file_type
else:
# See if we have a gzipped file, which, if it passes our restrictions, we'll uncompress
is_gzipped, is_valid = check_gzip(dataset.path)
if is_gzipped and not is_valid:
file_err(
'The gzipped uploaded file contains inappropriate content',
dataset, json_file)
return
elif is_gzipped and is_valid:
if link_data_only == 'copy_files':
# We need to uncompress the temp_name file, but BAM files must remain compressed in the BGZF format
CHUNK_SIZE = 2**20 # 1Mb
fd, uncompressed = tempfile.mkstemp(
prefix='data_id_%s_upload_gunzip_' %
dataset.dataset_id,
dir=os.path.dirname(output_path),
text=False)
gzipped_file = gzip.GzipFile(dataset.path, 'rb')
while 1:
try:
chunk = gzipped_file.read(CHUNK_SIZE)
except IOError:
os.close(fd)
os.remove(uncompressed)
file_err('Problem decompressing gzipped data',
dataset, json_file)
return
if not chunk:
break
os.write(fd, chunk)
os.close(fd)
gzipped_file.close()
# Replace the gzipped file with the decompressed file if it's safe to do so
if dataset.type in ('server_dir',
'path_paste') or not in_place:
dataset.path = uncompressed
else:
shutil.move(uncompressed, dataset.path)
os.chmod(dataset.path, 0o644)
dataset.name = dataset.name.rstrip('.gz')
data_type = 'gzip'
if not data_type and bz2 is not None:
# See if we have a bz2 file, much like gzip
is_bzipped, is_valid = check_bz2(dataset.path)
if is_bzipped and not is_valid:
file_err(
'The gzipped uploaded file contains inappropriate content',
dataset, json_file)
return
elif is_bzipped and is_valid:
if link_data_only == 'copy_files':
# We need to uncompress the temp_name file
CHUNK_SIZE = 2**20 # 1Mb
fd, uncompressed = tempfile.mkstemp(
prefix='data_id_%s_upload_bunzip2_' %
dataset.dataset_id,
dir=os.path.dirname(output_path),
text=False)
bzipped_file = bz2.BZ2File(dataset.path, 'rb')
while 1:
try:
chunk = bzipped_file.read(CHUNK_SIZE)
except IOError:
os.close(fd)
os.remove(uncompressed)
file_err(
'Problem decompressing bz2 compressed data',
dataset, json_file)
return
if not chunk:
break
os.write(fd, chunk)
os.close(fd)
bzipped_file.close()
# Replace the bzipped file with the decompressed file if it's safe to do so
if dataset.type in ('server_dir',
'path_paste') or not in_place:
dataset.path = uncompressed
else:
shutil.move(uncompressed, dataset.path)
os.chmod(dataset.path, 0o644)
dataset.name = dataset.name.rstrip('.bz2')
data_type = 'bz2'
if not data_type:
# See if we have a zip archive
is_zipped = check_zip(dataset.path)
if is_zipped:
if link_data_only == 'copy_files':
CHUNK_SIZE = 2**20 # 1Mb
uncompressed = None
uncompressed_name = None
unzipped = False
z = zipfile.ZipFile(dataset.path)
for name in z.namelist():
if name.endswith('/'):
continue
if unzipped:
stdout = 'ZIP file contained more than one file, only the first file was added to Galaxy.'
break
fd, uncompressed = tempfile.mkstemp(
prefix='data_id_%s_upload_zip_' %
dataset.dataset_id,
dir=os.path.dirname(output_path),
text=False)
if sys.version_info[:2] >= (2, 6):
zipped_file = z.open(name)
while 1:
try:
chunk = zipped_file.read(CHUNK_SIZE)
except IOError:
os.close(fd)
os.remove(uncompressed)
file_err(
'Problem decompressing zipped data',
dataset, json_file)
return
if not chunk:
break
os.write(fd, chunk)
os.close(fd)
zipped_file.close()
uncompressed_name = name
unzipped = True
else:
# python < 2.5 doesn't have a way to read members in chunks(!)
try:
outfile = open(uncompressed, 'wb')
outfile.write(z.read(name))
outfile.close()
uncompressed_name = name
unzipped = True
except IOError:
os.close(fd)
os.remove(uncompressed)
file_err(
'Problem decompressing zipped data',
dataset, json_file)
return
z.close()
# Replace the zipped file with the decompressed file if it's safe to do so
if uncompressed is not None:
if dataset.type in ('server_dir',
'path_paste') or not in_place:
dataset.path = uncompressed
else:
shutil.move(uncompressed, dataset.path)
os.chmod(dataset.path, 0o644)
dataset.name = uncompressed_name
data_type = 'zip'
if not data_type:
# TODO refactor this logic. check_binary isn't guaranteed to be
# correct since it only looks at whether the first 100 chars are
# printable or not. If someone specifies a known unsniffable
# binary datatype and check_binary fails, the file gets mangled.
if check_binary(dataset.path) or Binary.is_ext_unsniffable(
dataset.file_type):
# We have a binary dataset, but it is not Bam, Sff or Pdf
data_type = 'binary'
# binary_ok = False
parts = dataset.name.split(".")
if len(parts) > 1:
ext = parts[-1].strip().lower()
if not Binary.is_ext_unsniffable(ext):
file_err(
'The uploaded binary file contains inappropriate content',
dataset, json_file)
return
elif Binary.is_ext_unsniffable(
ext) and dataset.file_type != ext:
err_msg = "You must manually set the 'File Format' to '%s' when uploading %s files." % (
ext.capitalize(), ext)
file_err(err_msg, dataset, json_file)
return
if not data_type:
# We must have a text file
if check_html(dataset.path):
file_err(
'The uploaded file contains inappropriate HTML content',
dataset, json_file)
return
if data_type != 'binary':
if link_data_only == 'copy_files':
if dataset.type in ('server_dir',
'path_paste') and data_type not in [
'gzip', 'bz2', 'zip'
]:
in_place = False
# Convert universal line endings to Posix line endings, but allow the user to turn it off,
# so that is becomes possible to upload gzip, bz2 or zip files with binary data without
# corrupting the content of those files.
if dataset.to_posix_lines:
tmpdir = output_adjacent_tmpdir(output_path)
tmp_prefix = 'data_id_%s_convert_' % dataset.dataset_id
if dataset.space_to_tab:
line_count, converted_path = sniff.convert_newlines_sep2tabs(
dataset.path,
in_place=in_place,
tmp_dir=tmpdir,
tmp_prefix=tmp_prefix)
else:
line_count, converted_path = sniff.convert_newlines(
dataset.path,
in_place=in_place,
tmp_dir=tmpdir,
tmp_prefix=tmp_prefix)
if dataset.file_type == 'auto':
ext = sniff.guess_ext(dataset.path, registry.sniff_order)
else:
ext = dataset.file_type
data_type = ext
# Save job info for the framework
if ext == 'auto' and dataset.ext:
ext = dataset.ext
if ext == 'auto':
ext = 'data'
datatype = registry.get_datatype_by_extension(ext)
if dataset.type in ('server_dir',
'path_paste') and link_data_only == 'link_to_files':
# Never alter a file that will not be copied to Galaxy's local file store.
if datatype.dataset_content_needs_grooming(dataset.path):
err_msg = 'The uploaded files need grooming, so change your <b>Copy data into Galaxy?</b> selection to be ' + \
'<b>Copy files into Galaxy</b> instead of <b>Link to files without copying into Galaxy</b> so grooming can be performed.'
file_err(err_msg, dataset, json_file)
return
if link_data_only == 'copy_files' and dataset.type in (
'server_dir',
'path_paste') and data_type not in ['gzip', 'bz2', 'zip']:
# Move the dataset to its "real" path
if converted_path is not None:
shutil.copy(converted_path, output_path)
try:
os.remove(converted_path)
except:
pass
else:
# This should not happen, but it's here just in case
shutil.copy(dataset.path, output_path)
elif link_data_only == 'copy_files':
if purge_source:
shutil.move(dataset.path, output_path)
else:
shutil.copy(dataset.path, output_path)
# Write the job info
stdout = stdout or 'uploaded %s file' % data_type
info = dict(type='dataset',
dataset_id=dataset.dataset_id,
ext=ext,
stdout=stdout,
name=dataset.name,
line_count=line_count)
if dataset.get('uuid', None) is not None:
info['uuid'] = dataset.get('uuid')
json_file.write(dumps(info) + "\n")
if link_data_only == 'copy_files' and datatype.dataset_content_needs_grooming(
output_path):
# Groom the dataset content if necessary
datatype.groom_dataset_content(output_path)
def _resolve_src(item):
converted_path = None
name, path = _has_src_to_path(item)
dbkey = item.get("dbkey", "?")
requested_ext = item.get("ext", "auto")
info = item.get("info", None)
object_id = item.get("object_id", None)
link_data_only = upload_config.link_data_only
if "link_data_only" in item:
# Allow overriding this on a per file basis.
link_data_only = _link_data_only(item)
to_posix_lines = upload_config.get_option(item, "to_posix_lines")
space_to_tab = upload_config.get_option(item, "space_to_tab")
in_place = item.get("in_place", False)
purge_source = item.get("purge_source", True)
# Follow upload.py logic but without the auto-decompress logic.
registry = upload_config.registry
check_content = upload_config.check_content
data_type, ext = None, requested_ext
is_binary = check_binary(path)
if is_binary:
data_type, ext = handle_sniffable_binary_check(
data_type, ext, path, registry)
if data_type is None:
root_datatype = registry.get_datatype_by_extension(ext)
if getattr(root_datatype, 'compressed', False):
data_type = 'compressed archive'
ext = ext
elif is_binary:
data_type, ext = handle_unsniffable_binary_check(
data_type, ext, path, name, is_binary, requested_ext,
check_content, registry)
if not data_type and check_content and check_html(path):
raise UploadProblemException(
'The uploaded file contains inappropriate HTML content')
if data_type != 'binary':
if not link_data_only:
if to_posix_lines:
if space_to_tab:
line_count, converted_path = sniff.convert_newlines_sep2tabs(
path, in_place=in_place, tmp_dir=".")
else:
line_count, converted_path = sniff.convert_newlines(
path, in_place=in_place, tmp_dir=".")
else:
if space_to_tab:
line_count, converted_path = sniff.sep2tabs(
path, in_place=in_place, tmp_dir=".")
if requested_ext == 'auto':
ext = sniff.guess_ext(converted_path or path,
registry.sniff_order)
else:
ext = requested_ext
data_type = ext
if ext == 'auto' and data_type == 'binary':
ext = 'data'
if ext == 'auto' and requested_ext:
ext = requested_ext
if ext == 'auto':
ext = 'data'
datatype = registry.get_datatype_by_extension(ext)
if link_data_only:
# Never alter a file that will not be copied to Galaxy's local file store.
if datatype.dataset_content_needs_grooming(path):
err_msg = 'The uploaded files need grooming, so change your <b>Copy data into Galaxy?</b> selection to be ' + \
'<b>Copy files into Galaxy</b> instead of <b>Link to files without copying into Galaxy</b> so grooming can be performed.'
raise UploadProblemException(err_msg)
# If this file is not in the workdir make sure it gets there.
if not link_data_only and converted_path:
path = upload_config.ensure_in_working_directory(
converted_path, purge_source, in_place)
elif not link_data_only:
path = upload_config.ensure_in_working_directory(
path, purge_source, in_place)
if not link_data_only and datatype and datatype.dataset_content_needs_grooming(
path):
# Groom the dataset content if necessary
datatype.groom_dataset_content(path)
rval = {
"name": name,
"filename": path,
"dbkey": dbkey,
"ext": ext,
"link_data_only": link_data_only
}
if info is not None:
rval["info"] = info
if object_id is not None:
rval["object_id"] = object_id
return rval
def add_file( self, trans, temp_name, file_name, file_type, is_multi_byte, dbkey, info=None, space_to_tab=False, precreated_dataset=None ):
def dataset_no_data_error( data, message = 'there was an error uploading your file' ):
data.info = "No data: %s." % message
data.state = data.states.ERROR
if data.extension is None:
data.extension = 'data'
return data
data_type = None
if precreated_dataset is not None:
data = precreated_dataset
else:
data = trans.app.model.HistoryDatasetAssociation( history = trans.history, create_dataset = True )
trans.app.security_agent.set_all_dataset_permissions( data.dataset, trans.app.security_agent.history_get_default_permissions( trans.history ) )
# See if we have an empty file
if not os.path.getsize( temp_name ) > 0:
return dataset_no_data_error( data, message = 'you attempted to upload an empty file' )
#raise BadFileException( "you attempted to upload an empty file." )
if is_multi_byte:
ext = sniff.guess_ext( temp_name, is_multi_byte=True )
else:
if not data_type:
# See if we have a gzipped file, which, if it passes our restrictions,
# we'll decompress on the fly.
is_gzipped, is_valid = self.check_gzip( temp_name )
if is_gzipped and not is_valid:
return dataset_no_data_error( data, message = 'you attempted to upload an inappropriate file' )
#raise BadFileException( "you attempted to upload an inappropriate file." )
elif is_gzipped and is_valid:
# We need to uncompress the temp_name file
CHUNK_SIZE = 2**20 # 1Mb
fd, uncompressed = tempfile.mkstemp()
gzipped_file = gzip.GzipFile( temp_name )
while 1:
try:
chunk = gzipped_file.read( CHUNK_SIZE )
except IOError:
os.close( fd )
os.remove( uncompressed )
return dataset_no_data_error( data, message = 'problem decompressing gzipped data' )
#raise BadFileException( 'problem decompressing gzipped data.' )
if not chunk:
break
os.write( fd, chunk )
os.close( fd )
gzipped_file.close()
# Replace the gzipped file with the decompressed file
shutil.move( uncompressed, temp_name )
file_name = file_name.rstrip( '.gz' )
data_type = 'gzip'
ext = ''
if not data_type:
# See if we have a zip archive
is_zipped, is_valid, test_ext = self.check_zip( temp_name )
if is_zipped and not is_valid:
return dataset_no_data_error( data, message = 'you attempted to upload an inappropriate file' )
#raise BadFileException( "you attempted to upload an inappropriate file." )
elif is_zipped and is_valid:
# Currently, we force specific tools to handle this case. We also require the user
# to manually set the incoming file_type
if ( test_ext == 'ab1' or test_ext == 'scf' ) and file_type != 'binseq.zip':
return dataset_no_data_error( data, message = "Invalid 'File Format' for archive consisting of binary files - use 'Binseq.zip'" )
#raise BadFileException( "Invalid 'File Format' for archive consisting of binary files - use 'Binseq.zip'." )
elif test_ext == 'txt' and file_type != 'txtseq.zip':
return dataset_no_data_error( data, message = "Invalid 'File Format' for archive consisting of text files - use 'Txtseq.zip'" )
#raise BadFileException( "Invalid 'File Format' for archive consisting of text files - use 'Txtseq.zip'." )
if not ( file_type == 'binseq.zip' or file_type == 'txtseq.zip' ):
return dataset_no_data_error( data, message = "you must manually set the 'File Format' to either 'Binseq.zip' or 'Txtseq.zip' when uploading zip files" )
#raise BadFileException( "you must manually set the 'File Format' to either 'Binseq.zip' or 'Txtseq.zip' when uploading zip files." )
data_type = 'zip'
ext = file_type
if not data_type:
if self.check_binary( temp_name ):
parts = file_name.split( "." )
if len( parts ) > 1:
ext = parts[1].strip().lower()
if not( ext == 'ab1' or ext == 'scf' ):
return dataset_no_data_error( data, message = "you attempted to upload an inappropriate file" )
#raise BadFileException( "you attempted to upload an inappropriate file." )
if ext == 'ab1' and file_type != 'ab1':
return dataset_no_data_error( data, message = "you must manually set the 'File Format' to 'Ab1' when uploading ab1 files" )
#raise BadFileException( "you must manually set the 'File Format' to 'Ab1' when uploading ab1 files." )
elif ext == 'scf' and file_type != 'scf':
return dataset_no_data_error( data, message = "you must manually set the 'File Format' to 'Scf' when uploading scf files" )
#raise BadFileException( "you must manually set the 'File Format' to 'Scf' when uploading scf files." )
data_type = 'binary'
if not data_type:
# We must have a text file
if trans.app.datatypes_registry.get_datatype_by_extension( file_type ).composite_type != 'auto_primary_file' and self.check_html( temp_name ):
return dataset_no_data_error( data, message = "you attempted to upload an inappropriate file" )
#raise BadFileException( "you attempted to upload an inappropriate file." )
if data_type != 'binary' and data_type != 'zip':
if space_to_tab:
self.line_count = sniff.convert_newlines_sep2tabs( temp_name )
else:
self.line_count = sniff.convert_newlines( temp_name )
if file_type == 'auto':
ext = sniff.guess_ext( temp_name, sniff_order=trans.app.datatypes_registry.sniff_order )
else:
ext = file_type
data_type = ext
if info is None:
info = 'uploaded %s file' %data_type
data.extension = ext
data.name = file_name
data.dbkey = dbkey
data.info = info
data.flush()
shutil.move( temp_name, data.file_name )
data.state = data.states.OK
data.set_size()
data.init_meta()
if self.line_count is not None:
try:
if is_multi_byte:
data.set_multi_byte_peek( line_count=self.line_count )
else:
data.set_peek( line_count=self.line_count )
except:
if is_multi_byte:
data.set_multi_byte_peek()
else:
data.set_peek()
else:
if is_multi_byte:
data.set_multi_byte_peek()
else:
data.set_peek()
# validate incomming data
# Commented by greg on 3/14/07
# for error in data.datatype.validate( data ):
# data.add_validation_error(
# model.ValidationError( message=str( error ), err_type=error.__class__.__name__, attributes=util.object_to_string( error.__dict__ ) ) )
if data.missing_meta():
data.datatype.set_meta( data )
dbkey_to_store = dbkey
if type( dbkey_to_store ) == type( [] ):
dbkey_to_store = dbkey[0]
if precreated_dataset is not None:
trans.history.genome_build = dbkey_to_store
else:
trans.history.add_dataset( data, genome_build=dbkey_to_store )
trans.app.model.flush()
trans.log_event( "Added dataset %d to history %d" %( data.id, trans.history.id ), tool_id="upload" )
return data
try:
dataset.is_multi_byte = multi_byte.is_multi_byte( codecs.open( dataset.path, 'r', 'utf-8' ).read( 100 ) )
except UnicodeDecodeError, e:
dataset.is_multi_byte = False
# Is dataset an image?
image = check_image( dataset.path )
if image:
if not PIL:
image = None
# get_image_ext() returns None if nor a supported Image type
ext = get_image_ext( dataset.path, image )
data_type = ext
# Is dataset content multi-byte?
elif dataset.is_multi_byte:
data_type = 'multi-byte char'
ext = sniff.guess_ext( dataset.path, is_multi_byte=True )
# Is dataset content supported sniffable binary?
else:
# FIXME: This ignores the declared sniff order in datatype_conf.xml
# resulting in improper behavior
type_info = Binary.is_sniffable_binary( dataset.path )
if type_info:
data_type = type_info[0]
ext = type_info[1]
if not data_type:
root_datatype = registry.get_datatype_by_extension( dataset.file_type )
if getattr( root_datatype, 'compressed', False ):
data_type = 'compressed archive'
ext = dataset.file_type
else:
# See if we have a gzipped file, which, if it passes our restrictions, we'll uncompress
dataset, json_file)
return
if not os.path.getsize(dataset.path) > 0:
file_err('The uploaded file is empty', dataset, json_file)
return
if not dataset.type == 'url':
# Already set is_multi_byte above if type == 'url'
try:
dataset.is_multi_byte = util.is_multi_byte(
codecs.open(dataset.path, 'r', 'utf-8').read(100))
except UnicodeDecodeError, e:
dataset.is_multi_byte = False
# Is dataset content multi-byte?
if dataset.is_multi_byte:
data_type = 'multi-byte char'
ext = sniff.guess_ext(dataset.path, is_multi_byte=True)
# Is dataset content supported sniffable binary?
elif check_bam(dataset.path):
ext = 'bam'
data_type = 'bam'
elif check_sff(dataset.path):
ext = 'sff'
data_type = 'sff'
else:
# See if we have a gzipped file, which, if it passes our restrictions, we'll uncompress
is_gzipped, is_valid = check_gzip(dataset.path)
if is_gzipped and not is_valid:
file_err(
'The gzipped uploaded file contains inappropriate content',
dataset, json_file)
return
def add_file(dataset, registry, json_file, output_path):
data_type = None
line_count = None
converted_path = None
stdout = None
link_data_only = dataset.get('link_data_only', 'copy_files') != 'copy_files'
# run_as_real_user is estimated from galaxy config (external chmod indicated of inputs executed)
# If this is True we always purge supplied upload inputs so they are cleaned up and we reuse their
# paths during data conversions since this user already owns that path.
# Older in_place check for upload jobs created before 18.01, TODO remove in 19.XX. xref #5206
run_as_real_user = dataset.get('run_as_real_user', False) or dataset.get("in_place", False)
# purge_source defaults to True unless this is an FTP import and
# ftp_upload_purge has been overridden to False in Galaxy's config.
# We set purge_source to False if:
# - the job does not have write access to the file, e.g. when running as the
# real user
# - the files are uploaded from external paths.
purge_source = dataset.get('purge_source', True) and not run_as_real_user and dataset.type not in ('server_dir', 'path_paste')
# in_place is True unless we are running as a real user or importing external paths (i.e.
# this is a real upload and not a path paste or ftp import).
# in_place should always be False if running as real user because the uploaded file will
# be owned by Galaxy and not the user and it should be False for external paths so Galaxy doesn't
# modify files not controlled by Galaxy.
in_place = not run_as_real_user and dataset.type not in ('server_dir', 'path_paste', 'ftp_import')
# Base on the check_upload_content Galaxy config option and on by default, this enables some
# security related checks on the uploaded content, but can prevent uploads from working in some cases.
check_content = dataset.get('check_content' , True)
# auto_decompress is a request flag that can be swapped off to prevent Galaxy from automatically
# decompressing archive files before sniffing.
auto_decompress = dataset.get('auto_decompress', True)
try:
ext = dataset.file_type
except AttributeError:
raise UploadProblemException('Unable to process uploaded file, missing file_type parameter.')
if dataset.type == 'url':
try:
page = urlopen(dataset.path) # page will be .close()ed by sniff methods
temp_name = sniff.stream_to_file(page, prefix='url_paste', source_encoding=util.get_charset_from_http_headers(page.headers))
except Exception as e:
raise UploadProblemException('Unable to fetch %s\n%s' % (dataset.path, str(e)))
dataset.path = temp_name
# See if we have an empty file
if not os.path.exists(dataset.path):
raise UploadProblemException('Uploaded temporary file (%s) does not exist.' % dataset.path)
if not os.path.getsize(dataset.path) > 0:
raise UploadProblemException('The uploaded file is empty')
# Is dataset content supported sniffable binary?
is_binary = check_binary(dataset.path)
if is_binary:
# Sniff the data type
guessed_ext = sniff.guess_ext(dataset.path, registry.sniff_order)
# Set data_type only if guessed_ext is a binary datatype
datatype = registry.get_datatype_by_extension(guessed_ext)
if isinstance(datatype, Binary):
data_type = guessed_ext
ext = guessed_ext
if not data_type:
root_datatype = registry.get_datatype_by_extension(dataset.file_type)
if getattr(root_datatype, 'compressed', False):
data_type = 'compressed archive'
ext = dataset.file_type
else:
# See if we have a gzipped file, which, if it passes our restrictions, we'll uncompress
is_gzipped, is_valid = check_gzip(dataset.path, check_content=check_content)
if is_gzipped and not is_valid:
raise UploadProblemException('The gzipped uploaded file contains inappropriate content')
elif is_gzipped and is_valid and auto_decompress:
if not link_data_only:
# We need to uncompress the temp_name file, but BAM files must remain compressed in the BGZF format
CHUNK_SIZE = 2 ** 20 # 1Mb
fd, uncompressed = tempfile.mkstemp(prefix='data_id_%s_upload_gunzip_' % dataset.dataset_id, dir=os.path.dirname(output_path), text=False)
gzipped_file = gzip.GzipFile(dataset.path, 'rb')
while 1:
try:
chunk = gzipped_file.read(CHUNK_SIZE)
except IOError:
os.close(fd)
os.remove(uncompressed)
raise UploadProblemException('Problem decompressing gzipped data')
if not chunk:
break
os.write(fd, chunk)
os.close(fd)
gzipped_file.close()
# Replace the gzipped file with the decompressed file if it's safe to do so
if not in_place:
dataset.path = uncompressed
else:
shutil.move(uncompressed, dataset.path)
os.chmod(dataset.path, 0o644)
dataset.name = dataset.name.rstrip('.gz')
data_type = 'gzip'
if not data_type:
# See if we have a bz2 file, much like gzip
is_bzipped, is_valid = check_bz2(dataset.path, check_content)
if is_bzipped and not is_valid:
raise UploadProblemException('The gzipped uploaded file contains inappropriate content')
elif is_bzipped and is_valid and auto_decompress:
if not link_data_only:
# We need to uncompress the temp_name file
CHUNK_SIZE = 2 ** 20 # 1Mb
fd, uncompressed = tempfile.mkstemp(prefix='data_id_%s_upload_bunzip2_' % dataset.dataset_id, dir=os.path.dirname(output_path), text=False)
bzipped_file = bz2.BZ2File(dataset.path, 'rb')
while 1:
try:
chunk = bzipped_file.read(CHUNK_SIZE)
except IOError:
os.close(fd)
os.remove(uncompressed)
raise UploadProblemException('Problem decompressing bz2 compressed data')
if not chunk:
break
os.write(fd, chunk)
os.close(fd)
bzipped_file.close()
# Replace the bzipped file with the decompressed file if it's safe to do so
if not in_place:
dataset.path = uncompressed
else:
shutil.move(uncompressed, dataset.path)
os.chmod(dataset.path, 0o644)
dataset.name = dataset.name.rstrip('.bz2')
data_type = 'bz2'
if not data_type:
# See if we have a zip archive
is_zipped = check_zip(dataset.path)
if is_zipped and auto_decompress:
if not link_data_only:
CHUNK_SIZE = 2 ** 20 # 1Mb
uncompressed = None
uncompressed_name = None
unzipped = False
z = zipfile.ZipFile(dataset.path)
for name in z.namelist():
if name.endswith('/'):
continue
if unzipped:
stdout = 'ZIP file contained more than one file, only the first file was added to Galaxy.'
break
fd, uncompressed = tempfile.mkstemp(prefix='data_id_%s_upload_zip_' % dataset.dataset_id, dir=os.path.dirname(output_path), text=False)
if sys.version_info[:2] >= (2, 6):
zipped_file = z.open(name)
while 1:
try:
chunk = zipped_file.read(CHUNK_SIZE)
except IOError:
os.close(fd)
os.remove(uncompressed)
raise UploadProblemException('Problem decompressing zipped data')
if not chunk:
break
os.write(fd, chunk)
os.close(fd)
zipped_file.close()
uncompressed_name = name
unzipped = True
else:
# python < 2.5 doesn't have a way to read members in chunks(!)
try:
with open(uncompressed, 'wb') as outfile:
outfile.write(z.read(name))
uncompressed_name = name
unzipped = True
except IOError:
os.close(fd)
os.remove(uncompressed)
raise UploadProblemException('Problem decompressing zipped data')
z.close()
# Replace the zipped file with the decompressed file if it's safe to do so
if uncompressed is not None:
if not in_place:
dataset.path = uncompressed
else:
shutil.move(uncompressed, dataset.path)
os.chmod(dataset.path, 0o644)
dataset.name = uncompressed_name
data_type = 'zip'
if not data_type:
if is_binary or registry.is_extension_unsniffable_binary(dataset.file_type):
# We have a binary dataset, but it is not Bam, Sff or Pdf
data_type = 'binary'
parts = dataset.name.split(".")
if len(parts) > 1:
ext = parts[-1].strip().lower()
is_ext_unsniffable_binary = registry.is_extension_unsniffable_binary(ext)
if check_content and not is_ext_unsniffable_binary:
raise UploadProblemException('The uploaded binary file contains inappropriate content')
elif is_ext_unsniffable_binary and dataset.file_type != ext:
err_msg = "You must manually set the 'File Format' to '%s' when uploading %s files." % (ext, ext)
raise UploadProblemException(err_msg)
if not data_type:
# We must have a text file
if check_content and check_html(dataset.path):
raise UploadProblemException('The uploaded file contains inappropriate HTML content')
if data_type != 'binary':
if not link_data_only and data_type not in ('gzip', 'bz2', 'zip'):
# Convert universal line endings to Posix line endings if to_posix_lines is True
# and the data is not binary or gzip-, bz2- or zip-compressed.
if dataset.to_posix_lines:
tmpdir = output_adjacent_tmpdir(output_path)
tmp_prefix = 'data_id_%s_convert_' % dataset.dataset_id
if dataset.space_to_tab:
line_count, converted_path = sniff.convert_newlines_sep2tabs(dataset.path, in_place=in_place, tmp_dir=tmpdir, tmp_prefix=tmp_prefix)
else:
line_count, converted_path = sniff.convert_newlines(dataset.path, in_place=in_place, tmp_dir=tmpdir, tmp_prefix=tmp_prefix)
if dataset.file_type == 'auto':
ext = sniff.guess_ext(converted_path or dataset.path, registry.sniff_order)
else:
ext = dataset.file_type
data_type = ext
# Save job info for the framework
if ext == 'auto' and data_type == 'binary':
ext = 'data'
if ext == 'auto' and dataset.ext:
ext = dataset.ext
if ext == 'auto':
ext = 'data'
datatype = registry.get_datatype_by_extension(ext)
if dataset.type in ('server_dir', 'path_paste') and link_data_only:
# Never alter a file that will not be copied to Galaxy's local file store.
if datatype.dataset_content_needs_grooming(dataset.path):
err_msg = 'The uploaded files need grooming, so change your <b>Copy data into Galaxy?</b> selection to be ' + \
'<b>Copy files into Galaxy</b> instead of <b>Link to files without copying into Galaxy</b> so grooming can be performed.'
raise UploadProblemException(err_msg)
if not link_data_only and converted_path:
# Move the dataset to its "real" path
try:
shutil.move(converted_path, output_path)
except OSError as e:
# We may not have permission to remove converted_path
if e.errno != errno.EACCES:
raise
elif not link_data_only:
if purge_source:
shutil.move(dataset.path, output_path)
else:
shutil.copy(dataset.path, output_path)
# Write the job info
stdout = stdout or 'uploaded %s file' % data_type
info = dict(type='dataset',
dataset_id=dataset.dataset_id,
ext=ext,
stdout=stdout,
name=dataset.name,
line_count=line_count)
if dataset.get('uuid', None) is not None:
info['uuid'] = dataset.get('uuid')
json_file.write(dumps(info) + "\n")
if not link_data_only and datatype and datatype.dataset_content_needs_grooming(output_path):
# Groom the dataset content if necessary
datatype.groom_dataset_content(output_path)
dataset.is_multi_byte = util.is_multi_byte(
codecs.open(dataset.path, 'r', 'utf-8').read(100))
except UnicodeDecodeError, e:
dataset.is_multi_byte = False
# Is dataset an image?
image = check_image(dataset.path)
if image:
if not PIL:
image = None
# get_image_ext() returns None if nor a supported Image type
ext = get_image_ext(dataset.path, image)
data_type = ext
# Is dataset content multi-byte?
elif dataset.is_multi_byte:
data_type = 'multi-byte char'
ext = sniff.guess_ext(dataset.path, is_multi_byte=True)
# Is dataset content supported sniffable binary?
else:
type_info = Binary.is_sniffable_binary(dataset.path)
if type_info:
data_type = type_info[0]
ext = type_info[1]
if not data_type:
# See if we have a gzipped file, which, if it passes our restrictions, we'll uncompress
is_gzipped, is_valid = check_gzip(dataset.path)
if is_gzipped and not is_valid:
file_err(
'The gzipped uploaded file contains inappropriate content',
dataset, json_file)
return
elif is_gzipped and is_valid:
def run_job(self, job):
if job.params['type'] == 'init_transfer':
# TODO: don't create new downloads on restart.
if job.params['protocol'] in ['http', 'https']:
results = []
for result in job.params['results'].values():
result['transfer_job'] = self.app.transfer_manager.new(
protocol=job.params['protocol'],
name=result['name'],
datatype=result['datatype'],
url=result['url'])
results.append(result)
elif job.params['protocol'] == 'scp':
results = []
result = {}
sample_datasets_dict = job.params['sample_datasets_dict']
# sample_datasets_dict looks something like the following. The outer dictionary keys are SampleDataset ids.
# {'7': {'status': 'Not started', 'name': '3.bed', 'file_path': '/tmp/library/3.bed', 'sample_id': 7,
# 'external_service_id': 2, 'error_msg': '', 'size': '8.0K'}}
for sample_dataset_id, sample_dataset_info_dict in sample_datasets_dict.items(
):
result = {}
result['transfer_job'] = self.app.transfer_manager.new(
protocol=job.params['protocol'],
host=job.params['host'],
user_name=job.params['user_name'],
password=job.params['password'],
sample_dataset_id=sample_dataset_id,
status=sample_dataset_info_dict['status'],
name=sample_dataset_info_dict['name'],
file_path=sample_dataset_info_dict['file_path'],
sample_id=sample_dataset_info_dict['sample_id'],
external_service_id=sample_dataset_info_dict[
'external_service_id'],
error_msg=sample_dataset_info_dict['error_msg'],
size=sample_dataset_info_dict['size'])
results.append(result)
self.app.transfer_manager.run([r['transfer_job'] for r in results])
for result in results:
transfer_job = result.pop('transfer_job')
self.create_job(None,
transfer_job_id=transfer_job.id,
result=transfer_job.params,
sample_id=job.params['sample_id'])
# Update the state of the relevant SampleDataset
new_status = self.app.model.SampleDataset.transfer_status.IN_QUEUE
self._update_sample_dataset_status(
protocol=job.params['protocol'],
sample_id=job.params['sample_id'],
result_dict=transfer_job.params,
new_status=new_status,
error_msg='')
job.state = self.app.model.DeferredJob.states.OK
self.sa_session.add(job)
self.sa_session.flush()
# TODO: Error handling: failure executing, or errors returned from the manager
if job.params['type'] == 'finish_transfer':
protocol = job.params['protocol']
# Update the state of the relevant SampleDataset
new_status = self.app.model.SampleDataset.transfer_status.ADD_TO_LIBRARY
if protocol in ['http', 'https']:
result_dict = job.params['result']
library_dataset_name = result_dict['name']
extension = result_dict['datatype']
elif protocol in ['scp']:
# In this case, job.params will be a dictionary that contains a key named 'result'. The value
# of the result key is a dictionary that looks something like:
# {'sample_dataset_id': '8', 'status': 'Not started', 'protocol': 'scp', 'name': '3.bed',
# 'file_path': '/data/library/3.bed', 'host': '127.0.0.1', 'sample_id': 8, 'external_service_id': 2,
# 'local_path': '/tmp/kjl2Ss4', 'password': '******', 'user_name': 'gvk', 'error_msg': '', 'size': '8.0K'}
try:
tj = self.sa_session.query(self.app.model.TransferJob).get(
int(job.params['transfer_job_id']))
result_dict = tj.params
result_dict['local_path'] = tj.path
except Exception, e:
log.error(
"Updated transfer result unavailable, using old result. Error was: %s"
% str(e))
result_dict = job.params['result']
library_dataset_name = result_dict['name']
# Determine the data format (see the relevant TODO item in the manual_data_transfer plugin)..
extension = sniff.guess_ext(
result_dict['local_path'],
sniff_order=self.app.datatypes_registry.sniff_order)
self._update_sample_dataset_status(protocol=job.params['protocol'],
sample_id=int(
job.params['sample_id']),
result_dict=result_dict,
new_status=new_status,
error_msg='')
sample = self.sa_session.query(self.app.model.Sample).get(
int(job.params['sample_id']))
ld = self.app.model.LibraryDataset(folder=sample.folder,
name=library_dataset_name)
self.sa_session.add(ld)
self.sa_session.flush()
self.app.security_agent.copy_library_permissions(
FakeTrans(self.app), sample.folder, ld)
ldda = self.app.model.LibraryDatasetDatasetAssociation(
name=library_dataset_name,
extension=extension,
dbkey='?',
library_dataset=ld,
create_dataset=True,
sa_session=self.sa_session)
ldda.message = 'Transferred by the Data Transfer Plugin'
self.sa_session.add(ldda)
self.sa_session.flush()
ldda.state = ldda.states.QUEUED # flushed in the set property
ld.library_dataset_dataset_association_id = ldda.id
self.sa_session.add(ld)
self.sa_session.flush()
try:
# Move the dataset from its temporary location
shutil.move(job.transfer_job.path, ldda.file_name)
ldda.init_meta()
for name, spec in ldda.metadata.spec.items():
if name not in ['name', 'info', 'dbkey', 'base_name']:
if spec.get('default'):
setattr(ldda.metadata, name,
spec.unwrap(spec.get('default')))
self.app.datatypes_registry.set_external_metadata_tool.tool_action.execute(
self.app.datatypes_registry.set_external_metadata_tool,
FakeTrans(self.app,
history=sample.history,
user=sample.request.user),
incoming={'input1': ldda})
ldda.state = ldda.states.OK
# TODO: not sure if this flush is necessary
self.sa_session.add(ldda)
self.sa_session.flush()
except Exception, e:
log.exception( 'Failure preparing library dataset for finished transfer job (id: %s) via deferred job (id: %s):' % \
( str( job.transfer_job.id ), str( job.id ) ) )
ldda.state = ldda.states.ERROR
def handle_upload(
registry,
path, # dataset.path
requested_ext, # dataset.file_type
name, # dataset.name,
tmp_prefix,
tmp_dir,
check_content,
link_data_only,
in_place,
auto_decompress,
convert_to_posix_lines,
convert_spaces_to_tabs,
):
stdout = None
converted_path = None
# Does the first 1K contain a null?
is_binary = check_binary(path)
# Decompress if needed/desired and determine/validate filetype. If a keep-compressed datatype is explicitly selected
# or if autodetection is selected and the file sniffs as a keep-compressed datatype, it will not be decompressed.
if not link_data_only:
if auto_decompress and is_zip(path) and not is_single_file_zip(path):
stdout = 'ZIP file contained more than one file, only the first file was added to Galaxy.'
try:
ext, converted_path, compression_type = sniff.handle_uploaded_dataset_file_internal(
path,
registry,
ext=requested_ext,
tmp_prefix=tmp_prefix,
tmp_dir=tmp_dir,
in_place=in_place,
check_content=check_content,
is_binary=is_binary,
auto_decompress=auto_decompress,
uploaded_file_ext=os.path.splitext(name)[1].lower().lstrip(
'.'),
convert_to_posix_lines=convert_to_posix_lines,
convert_spaces_to_tabs=convert_spaces_to_tabs,
)
except sniff.InappropriateDatasetContentError as exc:
raise UploadProblemException(str(exc))
elif requested_ext == 'auto':
ext = sniff.guess_ext(path, registry.sniff_order, is_binary=is_binary)
else:
ext = requested_ext
# The converted path will be the same as the input path if no conversion was done (or in-place conversion is used)
converted_path = None if converted_path == path else converted_path
# Validate datasets where the filetype was explicitly set using the filetype's sniffer (if any)
if requested_ext != 'auto':
datatype = registry.get_datatype_by_extension(requested_ext)
# Enable sniffer "validate mode" (prevents certain sniffers from disabling themselves)
if check_content and hasattr(datatype,
'sniff') and not datatype.sniff(path):
stdout = (
"Warning: The file 'Type' was set to '{ext}' but the file does not appear to be of that"
" type".format(ext=requested_ext))
# Handle unsniffable binaries
if is_binary and ext == 'binary':
upload_ext = os.path.splitext(name)[1].lower().lstrip('.')
if registry.is_extension_unsniffable_binary(upload_ext):
stdout = (
"Warning: The file's datatype cannot be determined from its contents and was guessed based on"
" its extension, to avoid this warning, manually set the file 'Type' to '{ext}' when uploading"
" this type of file".format(ext=upload_ext))
ext = upload_ext
else:
stdout = (
"The uploaded binary file format cannot be determined automatically, please set the file 'Type'"
" manually")
datatype = registry.get_datatype_by_extension(ext)
return stdout, ext, datatype, is_binary, converted_path
def add_file( self, trans, folder_id, file_obj, name, file_format, dbkey, roles, info='no info', space_to_tab=False,
replace_dataset=None, library_item_info_template=None, template_elements={}, message=None ):
folder = trans.app.model.LibraryFolder.get( folder_id )
data_type = None
line_count = 0
temp_name, is_multi_byte = sniff.stream_to_file( file_obj )
# See if we have an empty file
if not os.path.getsize( temp_name ) > 0:
raise BadFileException( "you attempted to upload an empty file." )
if is_multi_byte:
ext = sniff.guess_ext( temp_name, is_multi_byte=True )
else:
if not data_type:
# See if we have a gzipped file, which, if it passes our restrictions, we'll uncompress on the fly.
is_gzipped, is_valid = self.check_gzip( temp_name )
if is_gzipped and not is_valid:
raise BadFileException( "you attempted to upload an inappropriate file." )
elif is_gzipped and is_valid:
# We need to uncompress the temp_name file
CHUNK_SIZE = 2**20 # 1Mb
fd, uncompressed = tempfile.mkstemp()
gzipped_file = gzip.GzipFile( temp_name )
while 1:
try:
chunk = gzipped_file.read( CHUNK_SIZE )
except IOError:
os.close( fd )
os.remove( uncompressed )
raise BadFileException( 'problem uncompressing gzipped data.' )
if not chunk:
break
os.write( fd, chunk )
os.close( fd )
gzipped_file.close()
# Replace the gzipped file with the decompressed file
shutil.move( uncompressed, temp_name )
name = name.rstrip( '.gz' )
data_type = 'gzip'
ext = ''
if not data_type:
# See if we have a zip archive
is_zipped, is_valid, test_ext = self.check_zip( temp_name )
if is_zipped and not is_valid:
raise BadFileException( "you attempted to upload an inappropriate file." )
elif is_zipped and is_valid:
# Currently, we force specific tools to handle this case. We also require the user
# to manually set the incoming file_format
if ( test_ext == 'ab1' or test_ext == 'scf' ) and file_format != 'binseq.zip':
raise BadFileException( "Invalid 'File Format' for archive consisting of binary files - use 'Binseq.zip'." )
elif test_ext == 'txt' and file_format != 'txtseq.zip':
raise BadFileException( "Invalid 'File Format' for archive consisting of text files - use 'Txtseq.zip'." )
if not ( file_format == 'binseq.zip' or file_format == 'txtseq.zip' ):
raise BadFileException( "you must manually set the 'File Format' to either 'Binseq.zip' or 'Txtseq.zip' when uploading zip files." )
data_type = 'zip'
ext = file_format
if not data_type:
if self.check_binary( temp_name ):
try:
ext = name.split( "." )[1].strip().lower()
except:
ext = ''
if not( ext == 'ab1' or ext == 'scf' ):
raise BadFileException( "you attempted to upload an inappropriate file." )
if ext == 'ab1' and file_format != 'ab1':
raise BadFileException( "you must manually set the 'File Format' to 'Ab1' when uploading ab1 files." )
elif ext == 'scf' and file_format != 'scf':
raise BadFileException( "you must manually set the 'File Format' to 'Scf' when uploading scf files." )
data_type = 'binary'
if not data_type:
# We must have a text file
if self.check_html( temp_name ):
raise BadFileException( "you attempted to upload an inappropriate file." )
if data_type != 'binary' and data_type != 'zip':
if space_to_tab:
line_count = sniff.convert_newlines_sep2tabs( temp_name )
elif os.stat( temp_name ).st_size < 262144000: # 250MB
line_count = sniff.convert_newlines( temp_name )
else:
if sniff.check_newlines( temp_name ):
line_count = sniff.convert_newlines( temp_name )
else:
line_count = None
if file_format == 'auto':
ext = sniff.guess_ext( temp_name, sniff_order=trans.app.datatypes_registry.sniff_order )
else:
ext = file_format
data_type = ext
if info is None:
info = 'uploaded %s file' % data_type
if file_format == 'auto':
data_type = sniff.guess_ext( temp_name, sniff_order=trans.app.datatypes_registry.sniff_order )
else:
data_type = file_format
if replace_dataset:
# The replace_dataset param ( when not None ) refers to a LibraryDataset that is being replaced with a new version.
library_dataset = replace_dataset
else:
# If replace_dataset is None, the Library level permissions will be taken from the folder and applied to the new
# LibraryDataset, and the current user's DefaultUserPermissions will be applied to the associated Dataset.
library_dataset = trans.app.model.LibraryDataset( folder=folder, name=name, info=info )
library_dataset.flush()
trans.app.security_agent.copy_library_permissions( folder, library_dataset )
ldda = trans.app.model.LibraryDatasetDatasetAssociation( name=name,
info=info,
extension=data_type,
dbkey=dbkey,
library_dataset=library_dataset,
user=trans.get_user(),
create_dataset=True )
ldda.message = message
ldda.flush()
# Permissions must be the same on the LibraryDatasetDatasetAssociation and the associated LibraryDataset
trans.app.security_agent.copy_library_permissions( library_dataset, ldda )
if replace_dataset:
# Copy the Dataset level permissions from replace_dataset to the new LibraryDatasetDatasetAssociation.dataset
trans.app.security_agent.copy_dataset_permissions( replace_dataset.library_dataset_dataset_association.dataset, ldda.dataset )
else:
# Copy the current user's DefaultUserPermissions to the new LibraryDatasetDatasetAssociation.dataset
trans.app.security_agent.set_all_dataset_permissions( ldda.dataset, trans.app.security_agent.user_get_default_permissions( trans.get_user() ) )
folder.add_library_dataset( library_dataset, genome_build=dbkey )
folder.flush()
library_dataset.library_dataset_dataset_association_id = ldda.id
library_dataset.flush()
# Handle any templates included in the upload form
if library_item_info_template:
user = trans.get_user()
library_item_info = trans.app.model.LibraryItemInfo( user=user )
library_item_info.library_item_info_template = library_item_info_template
library_item_info.flush()
trans.app.security_agent.copy_library_permissions( library_item_info_template, library_item_info )
for template_element in library_item_info_template.elements:
info_element_value = template_elements.get( "info_element_%s_%s" % ( library_item_info_template.id, template_element.id ), None )
info_element = trans.app.model.LibraryItemInfoElement()
info_element.contents = info_element_value
info_element.library_item_info_template_element = template_element
info_element.library_item_info = library_item_info
info_element.flush()
library_item_info_association = trans.app.model.LibraryDatasetDatasetInfoAssociation( user=user )
library_item_info_association.set_library_item( ldda )
library_item_info_association.library_item_info = library_item_info
library_item_info_association.flush()
# If roles were selected upon upload, restrict access to the Dataset to those roles
if roles:
for role in roles:
dp = trans.app.model.DatasetPermissions( RBACAgent.permitted_actions.DATASET_ACCESS.action, ldda.dataset, role )
dp.flush()
shutil.move( temp_name, ldda.dataset.file_name )
ldda.state = ldda.states.OK
ldda.init_meta()
if line_count:
try:
if is_multi_byte:
ldda.set_multi_byte_peek( line_count=line_count )
else:
ldda.set_peek( line_count=line_count )
except:
if is_multi_byte:
ldda.set_multi_byte_peek()
else:
ldda.set_peek()
else:
if is_multi_byte:
ldda.set_multi_byte_peek()
else:
ldda.set_peek()
ldda.set_size()
if ldda.missing_meta():
ldda.datatype.set_meta( ldda )
ldda.flush()
return ldda
def add_file(dataset, registry, json_file, output_path):
data_type = None
line_count = None
converted_path = None
stdout = None
link_data_only = dataset.get('link_data_only', 'copy_files')
run_as_real_user = in_place = dataset.get('in_place', True)
purge_source = dataset.get('purge_source', True)
# in_place is True if there is no external chmod in place,
# however there are other instances where modifications should not occur in_place:
# when a file is added from a directory on the local file system (ftp import folder or any other path).
if dataset.type in ('server_dir', 'path_paste', 'ftp_import'):
in_place = False
check_content = dataset.get('check_content' , True)
auto_decompress = dataset.get('auto_decompress', True)
try:
ext = dataset.file_type
except AttributeError:
file_err('Unable to process uploaded file, missing file_type parameter.', dataset, json_file)
return
if dataset.type == 'url':
try:
page = urlopen(dataset.path) # page will be .close()ed by sniff methods
temp_name, dataset.is_multi_byte = sniff.stream_to_file(page, prefix='url_paste', source_encoding=util.get_charset_from_http_headers(page.headers))
except Exception as e:
file_err('Unable to fetch %s\n%s' % (dataset.path, str(e)), dataset, json_file)
return
dataset.path = temp_name
# See if we have an empty file
if not os.path.exists(dataset.path):
file_err('Uploaded temporary file (%s) does not exist.' % dataset.path, dataset, json_file)
return
if not os.path.getsize(dataset.path) > 0:
file_err('The uploaded file is empty', dataset, json_file)
return
if not dataset.type == 'url':
# Already set is_multi_byte above if type == 'url'
try:
dataset.is_multi_byte = multi_byte.is_multi_byte(codecs.open(dataset.path, 'r', 'utf-8').read(100))
except UnicodeDecodeError as e:
dataset.is_multi_byte = False
# Is dataset an image?
i_ext = get_image_ext(dataset.path)
if i_ext:
ext = i_ext
data_type = ext
# Is dataset content multi-byte?
elif dataset.is_multi_byte:
data_type = 'multi-byte char'
ext = sniff.guess_ext(dataset.path, registry.sniff_order, is_multi_byte=True)
# Is dataset content supported sniffable binary?
else:
# FIXME: This ignores the declared sniff order in datatype_conf.xml
# resulting in improper behavior
type_info = Binary.is_sniffable_binary(dataset.path)
if type_info:
data_type = type_info[0]
ext = type_info[1]
if not data_type:
root_datatype = registry.get_datatype_by_extension(dataset.file_type)
if getattr(root_datatype, 'compressed', False):
data_type = 'compressed archive'
ext = dataset.file_type
else:
# See if we have a gzipped file, which, if it passes our restrictions, we'll uncompress
is_gzipped, is_valid = check_gzip(dataset.path, check_content=check_content)
if is_gzipped and not is_valid:
file_err('The gzipped uploaded file contains inappropriate content', dataset, json_file)
return
elif is_gzipped and is_valid and auto_decompress:
if link_data_only == 'copy_files':
# We need to uncompress the temp_name file, but BAM files must remain compressed in the BGZF format
CHUNK_SIZE = 2 ** 20 # 1Mb
fd, uncompressed = tempfile.mkstemp(prefix='data_id_%s_upload_gunzip_' % dataset.dataset_id, dir=os.path.dirname(output_path), text=False)
gzipped_file = gzip.GzipFile(dataset.path, 'rb')
while 1:
try:
chunk = gzipped_file.read(CHUNK_SIZE)
except IOError:
os.close(fd)
os.remove(uncompressed)
file_err('Problem decompressing gzipped data', dataset, json_file)
return
if not chunk:
break
os.write(fd, chunk)
os.close(fd)
gzipped_file.close()
# Replace the gzipped file with the decompressed file if it's safe to do so
if not in_place:
dataset.path = uncompressed
else:
shutil.move(uncompressed, dataset.path)
os.chmod(dataset.path, 0o644)
dataset.name = dataset.name.rstrip('.gz')
data_type = 'gzip'
if not data_type:
# See if we have a bz2 file, much like gzip
is_bzipped, is_valid = check_bz2(dataset.path, check_content)
if is_bzipped and not is_valid:
file_err('The gzipped uploaded file contains inappropriate content', dataset, json_file)
return
elif is_bzipped and is_valid and auto_decompress:
if link_data_only == 'copy_files':
# We need to uncompress the temp_name file
CHUNK_SIZE = 2 ** 20 # 1Mb
fd, uncompressed = tempfile.mkstemp(prefix='data_id_%s_upload_bunzip2_' % dataset.dataset_id, dir=os.path.dirname(output_path), text=False)
bzipped_file = bz2.BZ2File(dataset.path, 'rb')
while 1:
try:
chunk = bzipped_file.read(CHUNK_SIZE)
except IOError:
os.close(fd)
os.remove(uncompressed)
file_err('Problem decompressing bz2 compressed data', dataset, json_file)
return
if not chunk:
break
os.write(fd, chunk)
os.close(fd)
bzipped_file.close()
# Replace the bzipped file with the decompressed file if it's safe to do so
if not in_place:
dataset.path = uncompressed
else:
shutil.move(uncompressed, dataset.path)
os.chmod(dataset.path, 0o644)
dataset.name = dataset.name.rstrip('.bz2')
data_type = 'bz2'
if not data_type:
# See if we have a zip archive
is_zipped = check_zip(dataset.path)
if is_zipped and auto_decompress:
if link_data_only == 'copy_files':
CHUNK_SIZE = 2 ** 20 # 1Mb
uncompressed = None
uncompressed_name = None
unzipped = False
z = zipfile.ZipFile(dataset.path)
for name in z.namelist():
if name.endswith('/'):
continue
if unzipped:
stdout = 'ZIP file contained more than one file, only the first file was added to Galaxy.'
break
fd, uncompressed = tempfile.mkstemp(prefix='data_id_%s_upload_zip_' % dataset.dataset_id, dir=os.path.dirname(output_path), text=False)
if sys.version_info[:2] >= (2, 6):
zipped_file = z.open(name)
while 1:
try:
chunk = zipped_file.read(CHUNK_SIZE)
except IOError:
os.close(fd)
os.remove(uncompressed)
file_err('Problem decompressing zipped data', dataset, json_file)
return
if not chunk:
break
os.write(fd, chunk)
os.close(fd)
zipped_file.close()
uncompressed_name = name
unzipped = True
else:
# python < 2.5 doesn't have a way to read members in chunks(!)
try:
outfile = open(uncompressed, 'wb')
outfile.write(z.read(name))
outfile.close()
uncompressed_name = name
unzipped = True
except IOError:
os.close(fd)
os.remove(uncompressed)
file_err('Problem decompressing zipped data', dataset, json_file)
return
z.close()
# Replace the zipped file with the decompressed file if it's safe to do so
if uncompressed is not None:
if not in_place:
dataset.path = uncompressed
else:
shutil.move(uncompressed, dataset.path)
os.chmod(dataset.path, 0o644)
dataset.name = uncompressed_name
data_type = 'zip'
if not data_type:
# TODO refactor this logic. check_binary isn't guaranteed to be
# correct since it only looks at whether the first 100 chars are
# printable or not. If someone specifies a known unsniffable
# binary datatype and check_binary fails, the file gets mangled.
if check_binary(dataset.path) or Binary.is_ext_unsniffable(dataset.file_type):
# We have a binary dataset, but it is not Bam, Sff or Pdf
data_type = 'binary'
# binary_ok = False
parts = dataset.name.split(".")
if len(parts) > 1:
ext = parts[-1].strip().lower()
if check_content and not Binary.is_ext_unsniffable(ext):
file_err('The uploaded binary file contains inappropriate content', dataset, json_file)
return
elif Binary.is_ext_unsniffable(ext) and dataset.file_type != ext:
err_msg = "You must manually set the 'File Format' to '%s' when uploading %s files." % (ext.capitalize(), ext)
file_err(err_msg, dataset, json_file)
return
if not data_type:
# We must have a text file
if check_content and check_html(dataset.path):
file_err('The uploaded file contains inappropriate HTML content', dataset, json_file)
return
if data_type != 'binary':
if link_data_only == 'copy_files' and data_type not in ('gzip', 'bz2', 'zip'):
# Convert universal line endings to Posix line endings if to_posix_lines is True
# and the data is not binary or gzip-, bz2- or zip-compressed.
if dataset.to_posix_lines:
tmpdir = output_adjacent_tmpdir(output_path)
tmp_prefix = 'data_id_%s_convert_' % dataset.dataset_id
if dataset.space_to_tab:
line_count, converted_path = sniff.convert_newlines_sep2tabs(dataset.path, in_place=in_place, tmp_dir=tmpdir, tmp_prefix=tmp_prefix)
else:
line_count, converted_path = sniff.convert_newlines(dataset.path, in_place=in_place, tmp_dir=tmpdir, tmp_prefix=tmp_prefix)
if dataset.file_type == 'auto':
ext = sniff.guess_ext(dataset.path, registry.sniff_order)
else:
ext = dataset.file_type
data_type = ext
# Save job info for the framework
if ext == 'auto' and data_type == 'binary':
ext = 'data'
if ext == 'auto' and dataset.ext:
ext = dataset.ext
if ext == 'auto':
ext = 'data'
datatype = registry.get_datatype_by_extension(ext)
if dataset.type in ('server_dir', 'path_paste') and link_data_only == 'link_to_files':
# Never alter a file that will not be copied to Galaxy's local file store.
if datatype.dataset_content_needs_grooming(dataset.path):
err_msg = 'The uploaded files need grooming, so change your <b>Copy data into Galaxy?</b> selection to be ' + \
'<b>Copy files into Galaxy</b> instead of <b>Link to files without copying into Galaxy</b> so grooming can be performed.'
file_err(err_msg, dataset, json_file)
return
if link_data_only == 'copy_files' and converted_path:
# Move the dataset to its "real" path
try:
shutil.move(converted_path, output_path)
except OSError as e:
# We may not have permission to remove converted_path
if e.errno != errno.EACCES:
raise
elif link_data_only == 'copy_files':
if purge_source and not run_as_real_user:
# if the upload tool runs as a real user the real user
# can't move dataset.path as this path is owned by galaxy.
shutil.move(dataset.path, output_path)
else:
shutil.copy(dataset.path, output_path)
# Write the job info
stdout = stdout or 'uploaded %s file' % data_type
info = dict(type='dataset',
dataset_id=dataset.dataset_id,
ext=ext,
stdout=stdout,
name=dataset.name,
line_count=line_count)
if dataset.get('uuid', None) is not None:
info['uuid'] = dataset.get('uuid')
json_file.write(dumps(info) + "\n")
if link_data_only == 'copy_files' and datatype and datatype.dataset_content_needs_grooming(output_path):
# Groom the dataset content if necessary
datatype.groom_dataset_content(output_path)
def run_job( self, job ):
if job.params[ 'type' ] == 'init_transfer':
# TODO: don't create new downloads on restart.
if job.params[ 'protocol' ] in [ 'http', 'https' ]:
results = []
for result in job.params[ 'results' ].values():
result[ 'transfer_job' ] = self.app.transfer_manager.new( protocol=job.params[ 'protocol' ],
name=result[ 'name' ],
datatype=result[ 'datatype' ],
url=result[ 'url' ] )
results.append( result )
elif job.params[ 'protocol' ] == 'scp':
results = []
result = {}
sample_datasets_dict = job.params[ 'sample_datasets_dict' ]
# sample_datasets_dict looks something like the following. The outer dictionary keys are SampleDataset ids.
# {'7': {'status': 'Not started', 'name': '3.bed', 'file_path': '/tmp/library/3.bed', 'sample_id': 7,
# 'external_service_id': 2, 'error_msg': '', 'size': '8.0K'}}
for sample_dataset_id, sample_dataset_info_dict in sample_datasets_dict.items():
result = {}
result[ 'transfer_job' ] = self.app.transfer_manager.new( protocol=job.params[ 'protocol' ],
host=job.params[ 'host' ],
user_name=job.params[ 'user_name' ],
password=job.params[ 'password' ],
sample_dataset_id=sample_dataset_id,
status=sample_dataset_info_dict[ 'status' ],
name=sample_dataset_info_dict[ 'name' ],
file_path=sample_dataset_info_dict[ 'file_path' ],
sample_id=sample_dataset_info_dict[ 'sample_id' ],
external_service_id=sample_dataset_info_dict[ 'external_service_id' ],
error_msg=sample_dataset_info_dict[ 'error_msg' ],
size=sample_dataset_info_dict[ 'size' ] )
results.append( result )
self.app.transfer_manager.run( [ r[ 'transfer_job' ] for r in results ] )
for result in results:
transfer_job = result.pop( 'transfer_job' )
self.create_job( None,
transfer_job_id=transfer_job.id,
result=transfer_job.params,
sample_id=job.params[ 'sample_id' ] )
# Update the state of the relevant SampleDataset
new_status = self.app.model.SampleDataset.transfer_status.IN_QUEUE
self._update_sample_dataset_status( protocol=job.params[ 'protocol' ],
sample_id=job.params[ 'sample_id' ],
result_dict=transfer_job.params,
new_status=new_status,
error_msg='' )
job.state = self.app.model.DeferredJob.states.OK
self.sa_session.add( job )
self.sa_session.flush()
# TODO: Error handling: failure executing, or errors returned from the manager
if job.params[ 'type' ] == 'finish_transfer':
protocol = job.params[ 'protocol' ]
# Update the state of the relevant SampleDataset
new_status = self.app.model.SampleDataset.transfer_status.ADD_TO_LIBRARY
if protocol in [ 'http', 'https' ]:
result_dict = job.params[ 'result' ]
library_dataset_name = result_dict[ 'name' ]
extension = result_dict[ 'datatype' ]
elif protocol in [ 'scp' ]:
# In this case, job.params will be a dictionary that contains a key named 'result'. The value
# of the result key is a dictionary that looks something like:
# {'sample_dataset_id': '8', 'status': 'Not started', 'protocol': 'scp', 'name': '3.bed',
# 'file_path': '/data/library/3.bed', 'host': '127.0.0.1', 'sample_id': 8, 'external_service_id': 2,
# 'local_path': '/tmp/kjl2Ss4', 'password': '******', 'user_name': 'gvk', 'error_msg': '', 'size': '8.0K'}
try:
tj = self.sa_session.query( self.app.model.TransferJob ).get( int( job.params['transfer_job_id'] ) )
result_dict = tj.params
result_dict['local_path'] = tj.path
except Exception, e:
log.error( "Updated transfer result unavailable, using old result. Error was: %s" % str( e ) )
result_dict = job.params[ 'result' ]
library_dataset_name = result_dict[ 'name' ]
# Determine the data format (see the relevant TODO item in the manual_data_transfer plugin)..
extension = sniff.guess_ext( result_dict[ 'local_path' ], sniff_order=self.app.datatypes_registry.sniff_order )
self._update_sample_dataset_status( protocol=job.params[ 'protocol' ],
sample_id=int( job.params[ 'sample_id' ] ),
result_dict=result_dict,
new_status=new_status,
error_msg='' )
sample = self.sa_session.query( self.app.model.Sample ).get( int( job.params[ 'sample_id' ] ) )
ld = self.app.model.LibraryDataset( folder=sample.folder, name=library_dataset_name )
self.sa_session.add( ld )
self.sa_session.flush()
self.app.security_agent.copy_library_permissions( FakeTrans( self.app ), sample.folder, ld )
ldda = self.app.model.LibraryDatasetDatasetAssociation( name = library_dataset_name,
extension = extension,
dbkey = '?',
library_dataset = ld,
create_dataset = True,
sa_session = self.sa_session )
ldda.message = 'Transferred by the Data Transfer Plugin'
self.sa_session.add( ldda )
self.sa_session.flush()
ldda.state = ldda.states.QUEUED # flushed in the set property
ld.library_dataset_dataset_association_id = ldda.id
self.sa_session.add( ld )
self.sa_session.flush()
try:
# Move the dataset from its temporary location
shutil.move( job.transfer_job.path, ldda.file_name )
ldda.init_meta()
for name, spec in ldda.metadata.spec.items():
if name not in [ 'name', 'info', 'dbkey', 'base_name' ]:
if spec.get( 'default' ):
setattr( ldda.metadata, name, spec.unwrap( spec.get( 'default' ) ) )
self.app.datatypes_registry.set_external_metadata_tool.tool_action.execute( self.app.datatypes_registry.set_external_metadata_tool,
FakeTrans( self.app,
history=sample.history,
user=sample.request.user ),
incoming = { 'input1':ldda } )
ldda.state = ldda.states.OK
# TODO: not sure if this flush is necessary
self.sa_session.add( ldda )
self.sa_session.flush()
except Exception, e:
log.exception( 'Failure preparing library dataset for finished transfer job (id: %s) via deferred job (id: %s):' % \
( str( job.transfer_job.id ), str( job.id ) ) )
ldda.state = ldda.states.ERROR