comparison queue_genotype_workflow.py @ 1:d00c4cc7e8c2 draft

Uploaded

0:c80fae8c94c1

import sys
import threading
import time

from bioblend import galaxy
from six.moves import configparser

parser = argparse.ArgumentParser()
parser.add_argument('--affy_metadata', dest='affy_metadata', help='Input Affymetrix 96 well plate metadata file')
parser.add_argument('--annot', dest='annot', help='Probeset annotation file')

    new_library_dataset_dict = gi.libraries.copy_from_dataset(library_id, dataset_id)
    return new_library_dataset_dict


def copy_dataset_to_storage(src_path, dst_base_path, dataset_name, output_fh):
    # Copy a dataset via its file path to a storage directory on disk.
    if not os.path.isdir(dst_base_path):
        os.makedirs(dst_base_path)
    dst_path = os.path.join(dst_base_path, dataset_name)
    shutil.copyfile(src_path, dst_path)
    outputfh.write("Copied %s to storage.\n" % dataset_name)


def delete_history_dataset(gi, history_id, dataset_id, outputfh, purge=False):

            deleted_dataset_dict = delete_library_dataset(admin_gi, ags_library_id, ags_ldda_id, outputfh)
            # To save disk space, delete the all_genotyped_samples hda
            # in the current history to enable later purging by an admin.
            ags_hda_id = get_history_dataset_id_by_name(gi, args.history_id, "all_genotyped_samples", outputfh)
            delete_history_dataset(gi, args.history_id, ags_hda_id, outputfh)
    else:
        outputfh.write("\nProcessing ended in error...\n")
        outputfh.close()
        lock.release()
        sys.exit(1)

1:d00c4cc7e8c2

import sys
import threading
import time

from bioblend import galaxy
from datetime import datetime
from six.moves import configparser

parser = argparse.ArgumentParser()
parser.add_argument('--affy_metadata', dest='affy_metadata', help='Input Affymetrix 96 well plate metadata file')
parser.add_argument('--annot', dest='annot', help='Probeset annotation file')

    new_library_dataset_dict = gi.libraries.copy_from_dataset(library_id, dataset_id)
    return new_library_dataset_dict


def copy_dataset_to_storage(src_path, dst_base_path, dataset_name, output_fh):
    # Copy a dataset to a storage directory on disk.  Use the date
    # to name the storage directory to enable storing a file per day
    # (multiple runs per day will overwrite the existing file).
    date_str = datetime.now().strftime("%Y_%m_%d")
    dst_dir = os.path.join(dst_base_path, date_str)
    if not os.path.isdir(dst_dir):
        os.makedirs(dst_dir)
    dst_path = os.path.join(dst_dir, dataset_name)
    shutil.copyfile(src_path, dst_path)
    outputfh.write("Copied %s to storage.\n" % dataset_name)


def delete_history_dataset(gi, history_id, dataset_id, outputfh, purge=False):

            deleted_dataset_dict = delete_library_dataset(admin_gi, ags_library_id, ags_ldda_id, outputfh)
            # To save disk space, delete the all_genotyped_samples hda
            # in the current history to enable later purging by an admin.
            ags_hda_id = get_history_dataset_id_by_name(gi, args.history_id, "all_genotyped_samples", outputfh)
            delete_history_dataset(gi, args.history_id, ags_hda_id, outputfh)
        else:
            outputfh.write("\nProcessing ended in error...\n")
            outputfh.close()
            lock.release()
            sys.exit(1)
    else:
        outputfh.write("\nProcessing ended in error...\n")
        outputfh.close()
        lock.release()
        sys.exit(1)