import os.path from gcloud import storage from collections import Counter def frange(start, stop, step): i = start while i < stop: yield i i += step #-------------------------------------- # set default bucket #-------------------------------------- storage.set_default_bucket("isb-cgc") storage_conn = storage.get_connection() storage.set_default_connection(storage_conn) all_elements = {} df2 = pd.DataFrame() #-------------------------------------- # get the bucket contents #-------------------------------------- bucket = storage.get_bucket('ptone-experiments') for k in bucket.list_blobs(prefix="working-files/clinical_metadata/"): if 'counts.txt' in k.name: disease_type = k.name.split("/")[2].split(".")[0] data = StringIO()
def _callFUT(self, connection=None): from gcloud.storage import set_default_connection return set_default_connection(connection=connection)
def _callFUT(self, project=None, connection=None): from gcloud.storage import set_default_connection return set_default_connection(project=project, connection=connection)
from collections import Counter def frange(start, stop, step): i = start while i < stop: yield i i += step #-------------------------------------- # set default bucket #-------------------------------------- storage.set_default_bucket("isb-cgc") storage_conn = storage.get_connection() storage.set_default_connection(storage_conn) all_elements = {} df2 = pd.DataFrame() #-------------------------------------- # get the bucket contents #-------------------------------------- bucket = storage.get_bucket('ptone-experiments') for k in bucket.list_blobs(prefix="working-files/clinical_metadata/"): if 'counts.txt' in k.name: disease_type = k.name.split("/")[2].split(".")[0] data = StringIO()