def _get_galaxy_download_tasks(analysis):
"""Get file import tasks for Galaxy analysis results"""
logger.debug("Preparing to download analysis results from Galaxy")
task_list = []
# retrieving list of files to download for workflow
dl_files = analysis.workflow_dl_files
# creating dictionary based on files to download predetermined by workflow
# w/ keep operators
dl_dict = {}
for dl in dl_files.all():
temp_dict = {}
temp_dict['filename'] = dl.filename
temp_dict['pair_id'] = dl.pair_id
dl_dict[str(dl.step_id)] = temp_dict
galaxy_instance = analysis.workflow.workflow_engine.instance
try:
download_list = galaxy_instance.get_history_file_list(
analysis.history_id)
except galaxy.client.ConnectionError as exc:
error_msg = (
"Error downloading Galaxy history files for analysis '%s': %s")
logger.error(error_msg, analysis.name, exc.message)
analysis.set_status(Analysis.FAILURE_STATUS, error_msg)
analysis.galaxy_cleanup()
return task_list
# Iterating through files in current galaxy history
for results in download_list:
# download file if result state is "ok"
if results['state'] == 'ok':
file_type = results["type"]
curr_file_id = results['name']
if curr_file_id in dl_dict:
curr_dl_dict = dl_dict[curr_file_id]
result_name = curr_dl_dict['filename'] + '.' + file_type
# size of file defined by galaxy
file_size = results['file_size']
# Determining tag if galaxy results should be download through
# http or copying files directly to retrieve HTML files as zip
# archives via dataset URL
if galaxy_instance.local_download and file_type != 'html':
download_url = results['file_name']
else:
download_url = urlparse.urljoin(
galaxy_instance.base_url, '/'.join([
'datasets',
str(results['dataset_id']), 'display?to_ext=txt'
]))
# workaround to set the correct file type for zip archives of
# FastQC HTML reports produced by Galaxy dynamically
if file_type == 'html':
file_type = 'zip'
# TODO: when changing permanent=True, fix update of % download
# of file
filestore_uuid = create(source=download_url,
filetype=file_type)
# adding history files to django model
temp_file = AnalysisResult(analysis_uuid=analysis.uuid,
file_store_uuid=filestore_uuid,
file_name=result_name,
file_type=file_type)
temp_file.save()
analysis.results.add(temp_file)
analysis.save()
# downloading analysis results into file_store
# only download files if size is greater than 1
if file_size > 0:
task_id = import_file.subtask(
(filestore_uuid, False, file_size))
task_list.append(task_id)
return task_list
def _get_galaxy_download_task_ids(analysis):
"""Get file import tasks for Galaxy analysis results"""
logger.debug("Preparing to download analysis results from Galaxy")
task_id_list = []
# retrieving list of files to download for workflow
tool = _get_workflow_tool(analysis.uuid)
tool.create_analysis_output_node_connections()
galaxy_instance = analysis.workflow.workflow_engine.instance
try:
download_list = tool.get_galaxy_dataset_download_list()
except galaxy.client.ConnectionError as exc:
error_msg = (
"Error downloading Galaxy history files for analysis '%s': %s")
logger.error(error_msg, analysis.name, exc.message)
analysis.set_status(Analysis.FAILURE_STATUS, error_msg)
analysis.galaxy_cleanup()
return task_id_list
# Iterating through files in current galaxy history
for results in download_list:
# download file if result state is "ok"
if results['state'] == 'ok':
file_extension = results["type"]
result_name = "{}.{}".format(results['name'], file_extension)
# size of file defined by galaxy
file_size = results['file_size']
# Determining tag if galaxy results should be download through
# http or copying files directly to retrieve HTML files as zip
# archives via dataset URL
if galaxy_instance.local_download and file_extension != 'html':
download_url = results['file_name']
else:
download_url = urlparse.urljoin(
galaxy_instance.base_url, '/'.join([
'datasets',
str(results['dataset_id']), 'display?to_ext=txt'
]))
file_store_item = FileStoreItem(source=download_url)
# workaround to set the correct file type for zip archives of
# FastQC HTML reports produced by Galaxy dynamically
if file_extension == 'html':
file_extension = 'zip'
# assign file type manually since it cannot be inferred from source
try:
extension = FileExtension.objects.get(name=file_extension)
except (FileExtension.DoesNotExist,
FileExtension.MultipleObjectsReturned) as exc:
logger.warn(
"Could not assign type to file '%s' using "
"extension '%s': %s", file_store_item, file_extension, exc)
else:
file_store_item.filetype = extension.filetype
file_store_item.save()
# adding history files to django model
temp_file = AnalysisResult(analysis_uuid=analysis.uuid,
file_store_uuid=file_store_item.uuid,
file_name=result_name,
file_type=file_extension)
temp_file.save()
analysis.results.add(temp_file)
analysis.save()
# downloading analysis results into file_store
# only download files if size is greater than 1
if file_size > 0:
task_id = import_file.subtask(
(file_store_item.uuid, False, file_size))
task_id_list.append(task_id)
return task_id_list
def download_history_files(analysis):
"""Download entire histories from galaxy.
Getting files out of history to file store.
"""
logger.debug("analysis_manger.download_history_files called")
# retrieving list of files to download for workflow
#TODO: handle Django exceptions
analysis = Analysis.objects.get(uuid=analysis.uuid)
dl_files = analysis.workflow_dl_files
### creating dictionary based on files to download predetermined by workflow w/ keep operators
dl_dict = {}
for dl in dl_files.all():
temp_dict = {}
temp_dict['filename'] = dl.filename
temp_dict['pair_id'] = dl.pair_id
dl_dict[str(dl.step_id)] = temp_dict
task_list = []
# gets current galaxy connection
connection = analysis.get_galaxy_connection()
try:
download_list = connection.get_history_file_list(analysis.history_id)
except RuntimeError as exc:
error_msg = "Post-processing failed: " + \
"error downloading Galaxy history files for analysis '{}': {}" \
.format(analysis.name, exc.message)
logger.error(error_msg)
if not isinstance(exc, (ConnectionError, TimeoutError, AuthError)):
analysis.set_status(Analysis.FAILURE_STATUS, error_msg)
try:
analysis.delete_galaxy_library()
analysis.delete_galaxy_workflow()
analysis.delete_galaxy_history()
except RuntimeError:
logger.error("Cleanup failed for analysis '{}'".format(
analysis.name))
return task_list
# Iterating through files in current galaxy history
for results in download_list:
# download file if result state is "ok"
if results['state'] == 'ok':
file_type = results["type"]
curr_file_id = results['name']
if curr_file_id in dl_dict:
curr_dl_dict = dl_dict[curr_file_id]
result_name = curr_dl_dict['filename'] + '.' + file_type
# size of file defined by galaxy
file_size = results['file_size']
# Determing tag if galaxy results should be download through http or copying files directly
local_download = analysis.workflow.workflow_engine.instance.local_download
# to retrieve HTML files as zip archives via dataset URL
if local_download and file_type != 'html':
download_url = results['file_name']
else:
download_url = connection.make_url(str(
results['dataset_id']),
is_data=True,
key=False)
# workaround to set the correct file type for zip archives of
# reports produced by FASTQC
if file_type == 'html':
file_type = 'zip'
# getting file_store_uuid,
# TODO: when changing permanent=True, fix update of % download of file
filestore_uuid = create(source=download_url,
filetype=file_type,
permanent=False)
# adding history files to django model
temp_file = AnalysisResult(analysis_uuid=analysis.uuid,
file_store_uuid=filestore_uuid,
file_name=result_name,
file_type=file_type)
temp_file.save()
analysis.results.add(temp_file)
analysis.save()
# downloading analysis results into file_store
# only download files if size is greater than 1
if file_size > 0:
#task_id = import_file.subtask((filestore_uuid, True, False, file_size,))
# local download, force copying into the file_store instead of symlinking
if local_download:
task_id = import_file.subtask((
filestore_uuid,
False,
True,
file_size,
))
else:
task_id = import_file.subtask((
filestore_uuid,
False,
False,
file_size,
))
task_list.append(task_id)
return task_list
def get_galaxy_download_tasks(analysis):
"""Get file import tasks for Galaxy analysis results"""
logger.debug("Preparing to download analysis results from Galaxy")
# retrieving list of files to download for workflow
dl_files = analysis.workflow_dl_files
# creating dictionary based on files to download predetermined by workflow
# w/ keep operators
dl_dict = {}
for dl in dl_files.all():
temp_dict = {}
temp_dict['filename'] = dl.filename
temp_dict['pair_id'] = dl.pair_id
dl_dict[str(dl.step_id)] = temp_dict
task_list = []
galaxy_instance = analysis.workflow.workflow_engine.instance
try:
download_list = galaxy_instance.get_history_file_list(
analysis.history_id)
except galaxy.client.ConnectionError as exc:
error_msg = "Error downloading Galaxy history files for analysis " \
"'%s': %s"
logger.error(error_msg, analysis.name, exc.message)
analysis.set_status(Analysis.FAILURE_STATUS, error_msg)
analysis.galaxy_cleanup()
return task_list
# Iterating through files in current galaxy history
for results in download_list:
# download file if result state is "ok"
if results['state'] == 'ok':
file_type = results["type"]
curr_file_id = results['name']
if curr_file_id in dl_dict:
curr_dl_dict = dl_dict[curr_file_id]
result_name = curr_dl_dict['filename'] + '.' + file_type
# size of file defined by galaxy
file_size = results['file_size']
# Determining tag if galaxy results should be download through
# http or copying files directly to retrieve HTML files as zip
# archives via dataset URL
if galaxy_instance.local_download and file_type != 'html':
download_url = results['file_name']
else:
download_url = urlparse.urljoin(
galaxy_instance.base_url, '/'.join(
['datasets', str(results['dataset_id']),
'display?to_ext=txt']))
# workaround to set the correct file type for zip archives of
# FastQC HTML reports produced by Galaxy dynamically
if file_type == 'html':
file_type = 'zip'
# TODO: when changing permanent=True, fix update of % download
# of file
filestore_uuid = create(
source=download_url, filetype=file_type, permanent=False)
# adding history files to django model
temp_file = AnalysisResult(
analysis_uuid=analysis.uuid,
file_store_uuid=filestore_uuid,
file_name=result_name, file_type=file_type)
temp_file.save()
analysis.results.add(temp_file)
analysis.save()
# downloading analysis results into file_store
# only download files if size is greater than 1
if file_size > 0:
# local download, force copying into the file_store instead
# of symlinking
if galaxy_instance.local_download:
task_id = import_file.subtask(
(filestore_uuid, False, True, file_size,))
else:
task_id = import_file.subtask(
(filestore_uuid, False, False, file_size,))
task_list.append(task_id)
return task_list
def download_history_files(analysis) :
"""Download entire histories from galaxy.
Getting files out of history to file store.
"""
logger.debug("analysis_manger.download_history_files called")
# retrieving list of files to download for workflow
#TODO: handle Django exceptions
analysis = Analysis.objects.get(uuid=analysis.uuid)
dl_files = analysis.workflow_dl_files
### creating dictionary based on files to download predetermined by workflow w/ keep operators
dl_dict = {}
for dl in dl_files.all():
temp_dict = {}
temp_dict['filename'] = dl.filename
temp_dict['pair_id'] = dl.pair_id
dl_dict[str(dl.step_id)] = temp_dict
task_list = []
# gets current galaxy connection
connection = analysis.get_galaxy_connection()
try:
download_list = connection.get_history_file_list(analysis.history_id)
except RuntimeError as exc:
error_msg = "Post-processing failed: " + \
"error downloading Galaxy history files for analysis '{}': {}" \
.format(analysis.name, exc.message)
logger.error(error_msg)
if not isinstance(exc, (ConnectionError, TimeoutError, AuthError)):
analysis.set_status(Analysis.FAILURE_STATUS, error_msg)
try:
analysis.delete_galaxy_library()
analysis.delete_galaxy_workflow()
analysis.delete_galaxy_history()
except RuntimeError:
logger.error(
"Cleanup failed for analysis '{}'".format(analysis.name))
return task_list
# Iterating through files in current galaxy history
for results in download_list:
# download file if result state is "ok"
if results['state'] == 'ok':
file_type = results["type"]
curr_file_id = results['name']
if curr_file_id in dl_dict:
curr_dl_dict = dl_dict[curr_file_id]
result_name = curr_dl_dict['filename'] + '.' + file_type
# size of file defined by galaxy
file_size = results['file_size']
# Determing tag if galaxy results should be download through http or copying files directly
local_download = analysis.workflow.workflow_engine.instance.local_download
# to retrieve HTML files as zip archives via dataset URL
if local_download and file_type != 'html':
download_url = results['file_name']
else:
download_url = connection.make_url(
str(results['dataset_id']), is_data=True, key=False)
# workaround to set the correct file type for zip archives of
# reports produced by FASTQC
if file_type == 'html':
file_type = 'zip'
# getting file_store_uuid,
# TODO: when changing permanent=True, fix update of % download of file
filestore_uuid = create(
source=download_url,
filetype=file_type,
permanent=False
)
# adding history files to django model
temp_file = AnalysisResult(
analysis_uuid=analysis.uuid, file_store_uuid=filestore_uuid,
file_name=result_name, file_type=file_type)
temp_file.save()
analysis.results.add(temp_file)
analysis.save()
# downloading analysis results into file_store
# only download files if size is greater than 1
if file_size > 0:
#task_id = import_file.subtask((filestore_uuid, True, False, file_size,))
# local download, force copying into the file_store instead of symlinking
if local_download:
task_id = import_file.subtask(
(filestore_uuid, False, True, file_size,))
else:
task_id = import_file.subtask(
(filestore_uuid, False, False, file_size,))
task_list.append(task_id)
return task_list
