def upload(filename, bucket):
client = storage.get_bucket(
bucket,
"tagtooadex2",
"*****@*****.**",
"tagtooadex2-9e2928ac0acf.p12"
)
for i in os.listdir('.'):
if '%s.' % filename in i and '.gz' not in i:
print 'start upload', i, bucket
ipath = './%s' % i
os.system('gzip %s' % ipath)
client.upload_file(ipath, ipath)
os.remove(ipath)
#!/usr/bin/python
import jinja2
import csv
import logging
import codecs
from collections import defaultdict
from gcloud import storage
from jinja2 import Template
template = Template(open('sponsor_page.html').read())
bucket = storage.get_bucket("pycon-apac-2015", "living-bio")
def upload_image(filename):
try:
key = bucket.upload_file(filename)
key.make_public()
return key.public_url
except:
return 'http://storage.googleapis.com/pycon-apac-2015/%s' % filename
def import_application():
level_orders = ["Gold", "Silver", "Bronze", "Media", "Other"]
sponsor_categories = defaultdict(list)
with open('application.csv') as ifile:
ireader = csv.DictReader(ifile)
for row in ireader:
if not row['Sponsor Package']: continue
def _callFUT(self, *args, **kw):
from gcloud.storage import get_bucket
return get_bucket(*args, **kw)
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()
k.download_to_file(data)
data.seek(0)
df = pd.read_csv(data, sep="\t")
df['disease_type'] = disease_type
if df2.empty:
def _callFUT(self, *args, **kw):
from gcloud.storage import get_bucket
return get_bucket(*args, **kw)
#!/usr/bin/python
import jinja2
import csv
import logging
import codecs
from collections import defaultdict
from gcloud import storage
from jinja2 import Template
template = Template(open('sponsor_page.html').read())
bucket = storage.get_bucket(
"pycon-apac-2015",
"living-bio"
)
def upload_image(filename):
try:
key = bucket.upload_file(filename)
key.make_public()
return key.public_url
except:
return 'http://storage.googleapis.com/pycon-apac-2015/%s' % filename
def import_application():
level_orders = ["Platinum", "Gold", "Silver", "Bronze", "Media", "Other"]
sponsor_categories = defaultdict(list)
with open('application.csv') as ifile:
ireader = csv.DictReader(ifile)
def _get_bucket():
try:
return storage.get_bucket(BUCKET_NAME)
except NotFound:
return storage.create_bucket(BUCKET_NAME)
#--------------------------------------
# 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()
k.download_to_file(data)
data.seek(0)
df = pd.read_csv(data, sep="\t")
df['disease_type'] = disease_type
if df2.empty:
def __init__(self, options):
self.bucket = storage.get_bucket('just_a_test')
self.bucket.make_public(recursive=True, future=True)
#--------------------------------------
# set default bucket
#--------------------------------------
storage.set_default_bucket("isb-cgc")
storage_conn = storage.get_connection()
storage.set_default_connection(storage_conn)
all_elements = {}
#--------------------------------------
# get the bucket contents
#--------------------------------------
bucket = storage.get_bucket('isb-cgc-open')
for k in bucket.list_blobs(prefix="tcga/"):
if '.xml' in k.name and 'clinical' in k.name:
print k.name
disease_type = k.name.split("/")[1]
maf_data = StringIO()
k.download_to_file(maf_data)
maf_data.seek(0)
tree = etree.parse(maf_data)
root = tree.getroot() #this is the root; we can use it to find elements
blank_elements = re.compile("^\\n\s*$")