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.


import boto3
ssm = boto3.client('ssm')
parameter = ssm.get_parameter(Name='/project/key_endpoint', WithDecryption=True)


s3 bucket copy object to another bucket, python example


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']:



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