Warning
This document is for an in-development version of Galaxy. You can alternatively view this page in the latest release if it exists or view the top of the latest release's documentation.
Source code for galaxy_ext.metadata.set_metadata
"""
Execute an external process to set_meta() on a provided list of pickled datasets.
This was formerly scripts/set_metadata.py and expects these arguments:
%prog datatypes_conf.xml job_metadata_file metadata_in,metadata_kwds,metadata_out,metadata_results_code,output_filename_override,metadata_override... max_metadata_value_size
Galaxy should be importable on sys.path and output_filename_override should be
set to the path of the dataset on which metadata is being set
(output_filename_override could previously be left empty and the path would be
constructed automatically).
"""
import json
import logging
import os
import sys
# insert *this* galaxy before all others on sys.path
sys.path.insert(1, os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir, os.pardir)))
from six.moves import cPickle
from sqlalchemy.orm import clear_mappers
import galaxy.model.mapping # need to load this before we unpickle, in order to setup properties assigned by the mappers
from galaxy.model.custom_types import total_size
from galaxy.util import (
stringify_dictionary_keys,
unicodify,
)
from ._provided_metadata import parse_tool_provided_metadata
# ensure supported version
assert sys.version_info[:2] >= (2, 7), 'Python version must be at least 2.7, this is: %s' % sys.version
logging.basicConfig()
log = logging.getLogger(__name__)
galaxy.model.Job() # this looks REAL stupid, but it is REQUIRED in order for SA to insert parameters into the classes defined by the mappers --> it appears that instantiating ANY mapper'ed class would suffice here
[docs]def set_meta_with_tool_provided(dataset_instance, file_dict, set_meta_kwds, datatypes_registry, max_metadata_value_size):
# This method is somewhat odd, in that we set the metadata attributes from tool,
# then call set_meta, then set metadata attributes from tool again.
# This is intentional due to interplay of overwrite kwd, the fact that some metadata
# parameters may rely on the values of others, and that we are accepting the
# values provided by the tool as Truth.
extension = dataset_instance.extension
if extension == "_sniff_":
try:
from galaxy.datatypes import sniff
extension = sniff.handle_uploaded_dataset_file(dataset_instance.dataset.external_filename, datatypes_registry)
# We need to both set the extension so it is available to set_meta
# and record it in the metadata so it can be reloaded on the server
# side and the model updated (see MetadataCollection.{from,to}_JSON_dict)
dataset_instance.extension = extension
# Set special metadata property that will reload this on server side.
setattr(dataset_instance.metadata, "__extension__", extension)
except Exception:
log.exception("Problem sniffing datatype.")
for metadata_name, metadata_value in file_dict.get('metadata', {}).items():
setattr(dataset_instance.metadata, metadata_name, metadata_value)
dataset_instance.datatype.set_meta(dataset_instance, **set_meta_kwds)
for metadata_name, metadata_value in file_dict.get('metadata', {}).items():
setattr(dataset_instance.metadata, metadata_name, metadata_value)
if max_metadata_value_size:
for k, v in list(dataset_instance.metadata.items()):
if total_size(v) > max_metadata_value_size:
log.info("Key %s too large for metadata, discarding" % k)
dataset_instance.metadata.remove_key(k)
[docs]def set_metadata():
if len(sys.argv) == 1:
set_metadata_portable()
else:
set_metadata_legacy()
[docs]def set_metadata_portable():
import galaxy.model
tool_job_working_directory = os.path.abspath(os.getcwd())
galaxy.model.metadata.MetadataTempFile.tmp_dir = os.path.join(tool_job_working_directory, "metadata")
metadata_params_path = os.path.join("metadata", "params.json")
try:
with open(metadata_params_path, "r") as f:
metadata_params = json.load(f)
except IOError:
raise Exception("Failed to find metadata/params.json from cwd [%s]" % tool_job_working_directory)
datatypes_config = metadata_params["datatypes_config"]
job_metadata = metadata_params["job_metadata"]
max_metadata_value_size = metadata_params.get("max_metadata_value_size") or 0
outputs = metadata_params["outputs"]
datatypes_registry = validate_and_load_datatypes_config(datatypes_config)
tool_provided_metadata = load_job_metadata(job_metadata)
def set_meta(new_dataset_instance, file_dict):
set_meta_with_tool_provided(new_dataset_instance, file_dict, set_meta_kwds, datatypes_registry, max_metadata_value_size)
for output_name, output_dict in outputs.items():
filename_in = os.path.join("metadata/metadata_in_%s" % output_name)
filename_kwds = os.path.join("metadata/metadata_kwds_%s" % output_name)
filename_out = os.path.join("metadata/metadata_out_%s" % output_name)
filename_results_code = os.path.join("metadata/metadata_results_%s" % output_name)
override_metadata = os.path.join("metadata/metadata_override_%s" % output_name)
dataset_filename_override = output_dict["filename_override"]
# Same block as below...
set_meta_kwds = stringify_dictionary_keys(json.load(open(filename_kwds))) # load kwds; need to ensure our keywords are not unicode
try:
dataset = cPickle.load(open(filename_in, 'rb')) # load DatasetInstance
dataset.dataset.external_filename = dataset_filename_override
store_by = metadata_params.get("object_store_store_by", "id")
extra_files_dir_name = "dataset_%s_files" % getattr(dataset.dataset, store_by)
files_path = os.path.abspath(os.path.join(tool_job_working_directory, extra_files_dir_name))
dataset.dataset.external_extra_files_path = files_path
file_dict = tool_provided_metadata.get_dataset_meta(output_name, dataset.dataset.id)
if 'ext' in file_dict:
dataset.extension = file_dict['ext']
# Metadata FileParameter types may not be writable on a cluster node, and are therefore temporarily substituted with MetadataTempFiles
override_metadata = json.load(open(override_metadata))
for metadata_name, metadata_file_override in override_metadata:
if galaxy.datatypes.metadata.MetadataTempFile.is_JSONified_value(metadata_file_override):
metadata_file_override = galaxy.datatypes.metadata.MetadataTempFile.from_JSON(metadata_file_override)
setattr(dataset.metadata, metadata_name, metadata_file_override)
set_meta(dataset, file_dict)
dataset.metadata.to_JSON_dict(filename_out) # write out results of set_meta
json.dump((True, 'Metadata has been set successfully'), open(filename_results_code, 'wt+')) # setting metadata has succeeded
except Exception as e:
json.dump((False, unicodify(e)), open(filename_results_code, 'wt+')) # setting metadata has failed somehow
write_job_metadata(tool_job_working_directory, job_metadata, set_meta, tool_provided_metadata)
[docs]def set_metadata_legacy():
import galaxy.model
galaxy.model.metadata.MetadataTempFile.tmp_dir = tool_job_working_directory = os.path.abspath(os.getcwd())
# This is ugly, but to transition from existing jobs without this parameter
# to ones with, smoothly, it has to be the last optional parameter and we
# have to sniff it.
try:
max_metadata_value_size = int(sys.argv[-1])
sys.argv = sys.argv[:-1]
except ValueError:
max_metadata_value_size = 0
# max_metadata_value_size is unspecified and should be 0
# Set up datatypes registry
datatypes_config = sys.argv.pop(1)
datatypes_registry = validate_and_load_datatypes_config(datatypes_config)
job_metadata = sys.argv.pop(1)
tool_provided_metadata = load_job_metadata(job_metadata)
def set_meta(new_dataset_instance, file_dict):
set_meta_with_tool_provided(new_dataset_instance, file_dict, set_meta_kwds, datatypes_registry, max_metadata_value_size)
for filenames in sys.argv[1:]:
fields = filenames.split(',')
filename_in = fields.pop(0)
filename_kwds = fields.pop(0)
filename_out = fields.pop(0)
filename_results_code = fields.pop(0)
dataset_filename_override = fields.pop(0)
override_metadata = fields.pop(0)
set_meta_kwds = stringify_dictionary_keys(json.load(open(filename_kwds))) # load kwds; need to ensure our keywords are not unicode
try:
dataset = cPickle.load(open(filename_in, 'rb')) # load DatasetInstance
dataset.dataset.external_filename = dataset_filename_override
files_path = os.path.abspath(os.path.join(tool_job_working_directory, "dataset_%s_files" % (dataset.dataset.id)))
dataset.dataset.external_extra_files_path = files_path
file_dict = tool_provided_metadata.get_dataset_meta(None, dataset.dataset.id)
if 'ext' in file_dict:
dataset.extension = file_dict['ext']
# Metadata FileParameter types may not be writable on a cluster node, and are therefore temporarily substituted with MetadataTempFiles
override_metadata = json.load(open(override_metadata))
for metadata_name, metadata_file_override in override_metadata:
if galaxy.datatypes.metadata.MetadataTempFile.is_JSONified_value(metadata_file_override):
metadata_file_override = galaxy.datatypes.metadata.MetadataTempFile.from_JSON(metadata_file_override)
setattr(dataset.metadata, metadata_name, metadata_file_override)
set_meta(dataset, file_dict)
dataset.metadata.to_JSON_dict(filename_out) # write out results of set_meta
json.dump((True, 'Metadata has been set successfully'), open(filename_results_code, 'wt+')) # setting metadata has succeeded
except Exception as e:
json.dump((False, unicodify(e)), open(filename_results_code, 'wt+')) # setting metadata has failed somehow
write_job_metadata(tool_job_working_directory, job_metadata, set_meta, tool_provided_metadata)
[docs]def validate_and_load_datatypes_config(datatypes_config):
galaxy_root = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir, os.pardir, os.pardir))
if not os.path.exists(datatypes_config):
# Hack for Pulsar on usegalaxy.org, drop ASAP.
datatypes_config = "configs/registry.xml"
if not os.path.exists(datatypes_config):
print("Metadata setting failed because registry.xml [%s] could not be found. You may retry setting metadata." % datatypes_config)
sys.exit(1)
import galaxy.datatypes.registry
datatypes_registry = galaxy.datatypes.registry.Registry()
datatypes_registry.load_datatypes(root_dir=galaxy_root, config=datatypes_config)
galaxy.model.set_datatypes_registry(datatypes_registry)
return datatypes_registry
[docs]def write_job_metadata(tool_job_working_directory, job_metadata, set_meta, tool_provided_metadata):
for i, file_dict in enumerate(tool_provided_metadata.get_new_datasets_for_metadata_collection(), start=1):
filename = file_dict["filename"]
new_dataset_filename = os.path.join(tool_job_working_directory, "working", filename)
new_dataset = galaxy.model.Dataset(id=-i, external_filename=new_dataset_filename)
extra_files = file_dict.get('extra_files', None)
if extra_files is not None:
new_dataset._extra_files_path = os.path.join(tool_job_working_directory, "working", extra_files)
new_dataset.state = new_dataset.states.OK
new_dataset_instance = galaxy.model.HistoryDatasetAssociation(id=-i, dataset=new_dataset, extension=file_dict.get('ext', 'data'))
set_meta(new_dataset_instance, file_dict)
file_dict['metadata'] = json.loads(new_dataset_instance.metadata.to_JSON_dict()) # storing metadata in external form, need to turn back into dict, then later jsonify
tool_provided_metadata.rewrite()
clear_mappers()