Source code for galaxy.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
import traceback

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.tool_util.provided_metadata import parse_tool_provided_metadata
from galaxy.util import (
    stringify_dictionary_keys,
    unicodify,
)

logging.basicConfig()
log = logging.getLogger(__name__)


[docs]def set_validated_state(dataset_instance):
    from galaxy.datatypes.data import validate
    datatype_validation = validate(dataset_instance)

    dataset_instance.validated_state = datatype_validation.state
    dataset_instance.validated_state_message = datatype_validation.message

    # Set special metadata property that will reload this on server side.
    setattr(dataset_instance.metadata, "__validated_state__", datatype_validation.state)
    setattr(dataset_instance.metadata, "__validated_state_message__", datatype_validation.message)


[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())
    metadata_tmp_files_dir = os.path.join(tool_job_working_directory, "metadata")
    galaxy.model.metadata.MetadataTempFile.tmp_dir = metadata_tmp_files_dir

    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, "working", 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)
            if output_dict.get("validate", False):
                set_validated_state(dataset)
            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:
            json.dump((False, traceback.format_exc()), 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
            store_by = set_meta_kwds.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, "working", extra_files_dir_name))
            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, use_build_sites=False, use_converters=False, use_display_applications=False)
    galaxy.model.set_datatypes_registry(datatypes_registry)
    return datatypes_registry


[docs]def load_job_metadata(job_metadata):
    return parse_tool_provided_metadata(job_metadata)


[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()