pip install lxml
11/29/2020
11/27/2020
get parameter from parameter store of aws system manager, python example code
firstly create parameter in parameter store of AWS system manager
Then get the key from this code.
code
import boto3
ssm = boto3.client('ssm')
parameter = ssm.get_parameter(Name='/project/key_endpoint', WithDecryption=True)
print(parameter['Parameter']['Value'])
.
s3 bucket copy object to another bucket, python example
code
def copy_s3_object(s3_resource, source_bucket_name, source_key, target_bucket_name, target_key):
copy_source = {'Bucket': source_bucket_name, 'Key': source_key}
s3_resource.meta.client.copy(copy_source, target_bucket_name, target_key)
s3_resource = boto3.resource('s3')
copy_s3_object(s3_resource, source_bucket_name, source_key, target_bucket_name, target_key)
.
aws s3 get all object more than 1000 python example code
simply to use paginator instance
example code
paginator = s3_client.get_paginator('list_objects_v2')
pages = paginator.paginate(Bucket='bucket', Prefix='folder1/')
for page in pages:
for obj in page['Contents']:
print(obj['Key'])
.
11/02/2020
sci sparse -> tuple list -> sci sparse
refer to below source code
source code start
from scipy.sparse import csr_matrix
#sci sparse to tuple list
c = A2.tocoo() #A2 is scipy.sparse.csr.csr_matrix
in_edge_idx = list(zip(c.row, c.col)) #make tuple list
#tuple list to sci sparse
two_list = list(map(list, zip(*in_edge_idx))) #tuple 2 tow list of list [[1,2,3], [2,3,4]]
rows = np.array(two_list[0]) #rows
cols = np.array(two_list[1]) #cols
data_num = len(rows) #number of edge
data = np.ones( data_num ) #edge value
dim = len(x_data) #N x N adj
#sci sparse -> tuple list -> sci sparse
re_edge_idx = csr_matrix((data, (rows, cols)), shape=(dim, dim))
print('in', A2, type(A2))
print('re', re_edge_idx, type(re_edge_idx))
#origin A2 and re-generated edge index same?
print( (A2!=re_edge_idx).nnz==0 )
source code end
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