AWS Python Lambda Function - Upload File to S3 - python-2.7

I have an AWS Lambda function written in Python 2.7 in which I want to:
1) Grab an .xls file form an HTTP address.
2) Store it in a temp location.
3) Store the file in an S3 bucket.
My code is as follows:
from __future__ import print_function
import urllib
import datetime
import boto3
from botocore.client import Config
def lambda_handler(event, context):
"""Make a variable containing the date format based on YYYYYMMDD"""
cur_dt = datetime.datetime.today().strftime('%Y%m%d')
"""Make a variable containing the url and current date based on the variable
cur_dt"""
dls = "http://11.11.111.111/XL/" + cur_dt + ".xlsx"
urllib.urlretrieve(dls, cur_dt + "test.xls")
ACCESS_KEY_ID = 'Abcdefg'
ACCESS_SECRET_KEY = 'hijklmnop+6dKeiAByFluK1R7rngF'
BUCKET_NAME = 'my-bicket'
FILE_NAME = cur_dt + "test.xls";
data = open('/tmp/' + FILE_NAME, 'wb')
# S3 Connect
s3 = boto3.resource(
's3',
aws_access_key_id=ACCESS_KEY_ID,
aws_secret_access_key=ACCESS_SECRET_KEY,
config=Config(signature_version='s3v4')
)
# Uploaded File
s3.Bucket(BUCKET_NAME).put(Key=FILE_NAME, Body=data, ACL='public-read')
However, when I run this function, I receive the following error:
'IOError: [Errno 30] Read-only file system'
I've spent hours trying to address this issue but I'm falling on my face. Any help would be appreciated.

'IOError: [Errno 30] Read-only file system'
You seem to lack some write access right. If your lambda has another policy, try to attach this policy to your role:
arn:aws:iam::aws:policy/AWSLambdaFullAccess
It has full access on S3 as well, in case you can't write in your bucket. If it solves your issue, you'll remove some rights after that.

I have uploaded the image to s3 Bucket. In "Lambda Test Event", I have created one json test event which contains BASE64 of Image to be uploaded to s3 Bucket and Image Name.
Lambda Test JSON Event as fallows ======>
{
"ImageName": "Your Image Name",
"img64":"BASE64 of Your Image"
}
Following is the code to upload an image or any file to s3 ======>
import boto3
import base64
def lambda_handler(event, context):
s3 = boto3.resource(u's3')
bucket = s3.Bucket(u'YOUR-BUCKET-NAME')
path_test = '/tmp/output' # temp path in lambda.
key = event['ImageName'] # assign filename to 'key' variable
data = event['img64'] # assign base64 of an image to data variable
data1 = data
img = base64.b64decode(data1) # decode the encoded image data (base64)
with open(path_test, 'wb') as data:
#data.write(data1)
data.write(img)
bucket.upload_file(path_test, key) # Upload image directly inside bucket
#bucket.upload_file(path_test, 'FOLDERNAME-IN-YOUR-BUCKET /{}'.format(key)) # Upload image inside folder of your s3 bucket.
print('res---------------->',path_test)
print('key---------------->',key)
return {
'status': 'True',
'statusCode': 200,
'body': 'Image Uploaded'
}

change data = open('/tmp/' + FILE_NAME, 'wb') change the wb for "r"
also, I assume your IAM user has full access to S3 right?
or maybe the problem is in the request of that url...
try that cur_dt starts with "/tmp/"
urllib.urlretrieve(dls, "/tmp/" + cur_dt + "test.xls")

Related

NoCredentialError when trying to access head_object

I have the following code which runs as expected:
import boto3
session = boto3.Session(profile_name='default')
s3 = session.resource('s3')
bucketName = 'myBucketName'
bucket = s3.Bucket(bucketName)
for object_summary in bucket.objects.filter(Prefix="MainFolder/"):
s3_cli = boto3.client('s3')
if(object_summary.key[-1]!='/'):
print('FileName: '+object_summary.key)
# print(s3_cli.head_object(Bucket=bucketName,Key=str(object_summary.key)))
else:
s3obj='FolderName: '+object_summary.key
print(s3obj)
And lists the files and folders present in MainFolder on my S3 bucket. However, when I uncomment Line#12, I get this error:
NoCredentialsError: Unable to locate credentials
Any idea what I am doing wrong?
Instead of:
s3_cli = boto3.client('s3')
you should be using your session which loads the specific profile:
s3_cli = session.client('s3')

Creating a dmarc parser using parsedmarc in python3 for use in AWS s3

I am very new to programming. I am working on a pipeline to analyze DMARC report files that are sent to my email account, that I am manually placing in an s3 bucket. The goal of this task is to download, extract, and analyze files using parsedmarc: https://github.com/domainaware/parsedmarc The part I'm having difficulty with is setting a conditional statement to extract .gz files if the target file is not a .zip file. I'm assuming the gzip library will be sufficient for this purpose. Here is the code I have so far. I'm using python3 and the boto3 library for AWS. Any help is appreciated!
import parsedmarc
import pprint
import json
import boto3
import zipfile
import gzip
pp = pprint.PrettyPrinter(indent=2)
def main():
#Set default session profile and region for sandbox account. Access keys are pulled from /.aws/config and /.aws/credentials.
#The 'profile_name' value comes from the header for the account in question in /.aws/config and /.aws/credentials
boto3.setup_default_session(region_name="aws-region-goes-here")
boto3.setup_default_session(profile_name="aws-account-profile-name-goes-here")
#Define the s3 resource, the bucket name, and the file to download. It's hardcoded for now...
s3_resource = boto3.resource(s3)
s3_resource.Bucket('dmarc-parsing').download_file('source-dmarc-report-filename.zip' '/home/user/dmarc/parseme.zip')
#Use the zipfile python library to extract the file into its raw state.
with zipfile.ZipFile('/home/user/dmarc/parseme.zip', 'r') as zip_ref:
zip_ref.extractall('/home/user/dmarc')
#Ingest all locations for xml file source
dmarc_report_directory = '/home/user/dmarc/'
dmarc_report_file = 'parseme.xml'
"""I need an if statement here for extracting .gz files if the file type is not .zip. The contents of every archive are .xml files"""
#Set report output variables using functions in parsedmarc. Variable set to equal the output
pd_report_output=parsedmarc.parse_aggregate_report_file(_input=f"{dmarc_report_directory}{dmarc_report_file}")
#use jsonify to make the output in json format
pd_report_jsonified = json.loads(json.dumps(pd_report_output))
dkim_status = pd_report_jsonified['records'][0]['policy_evaluated']['dkim']
spf_status = pd_report_jsonified['records'][0]['policy_evaluated']['spf']
if dkim_status == 'fail' or spf_status == 'fail':
print(f"{dmarc_report_file} reports failure. oh crap. report:")
else:
print(f"{dmarc_report_file} passes. great. report:")
pp.pprint(pd_report_jsonified['records'][0]['auth_results'])
if __name__ == "__main__":
main()
Here is the code using the parsedmarc.parse_aggregate_report_xml method I found. Hope this helps others in parsing these reports:
import parsedmarc
import pprint
import json
import boto3
import zipfile
import gzip
pp = pprint.PrettyPrinter(indent=2)
def main():
#Set default session profile and region for account. Access keys are pulled from ~/.aws/config and ~/.aws/credentials.
#The 'profile_name' value comes from the header for the account in question in ~/.aws/config and ~/.aws/credentials
boto3.setup_default_session(profile_name="aws_profile_name_goes_here", region_name="region_goes_here")
source_file = 'filename_in_s3_bucket.zip'
destination_directory = '/tmp/'
destination_file = 'compressed_report_file'
#Define the s3 resource, the bucket name, and the file to download. It's hardcoded for now...
s3_resource = boto3.resource('s3')
s3_resource.Bucket('bucket-name-for-dmarc-report-files').download_file(source_file, f"{destination_directory}{destination_file}")
#Extract xml
outputxml = parsedmarc.extract_xml(f"{destination_directory}{destination_file}")
#run parse dmarc analysis & convert output to json
pd_report_output = parsedmarc.parse_aggregate_report_xml(outputxml)
pd_report_jsonified = json.loads(json.dumps(pd_report_output))
#loop through results and find relevant status info and pass fail status
dmarc_report_status = ''
for record in pd_report_jsonified['records']:
if False in record['alignment'].values():
dmarc_report_status = 'Failed'
#************ add logic for interpreting results
#if fail, publish to sns
if dmarc_report_status == 'Failed':
message = "Your dmarc report failed a least one check. Review the log for details"
sns_resource = boto3.resource('sns')
sns_topic = sns_resource.Topic('arn:aws:sns:us-west-2:112896196555:TestDMARC')
sns_publish_response = sns_topic.publish(Message=message)
if __name__ == "__main__":
main()

How to extract files in S3 on the fly with boto3?

I'm trying to find a way to extract .gz files in S3 on the fly, that is no need to download it to locally, extract and then push it back to S3.
With boto3 + lambda, how can i achieve my goal?
I didn't see any extract part in boto3 document.
You can use BytesIO to stream the file from S3, run it through gzip, then pipe it back up to S3 using upload_fileobj to write the BytesIO.
# python imports
import boto3
from io import BytesIO
import gzip
# setup constants
bucket = '<bucket_name>'
gzipped_key = '<key_name.gz>'
uncompressed_key = '<key_name>'
# initialize s3 client, this is dependent upon your aws config being done
s3 = boto3.client('s3', use_ssl=False) # optional
s3.upload_fileobj( # upload a new obj to s3
Fileobj=gzip.GzipFile( # read in the output of gzip -d
None, # just return output as BytesIO
'rb', # read binary
fileobj=BytesIO(s3.get_object(Bucket=bucket, Key=gzipped_key)['Body'].read())),
Bucket=bucket, # target bucket, writing to
Key=uncompressed_key) # target key, writing to
Ensure that your key is reading in correctly:
# read the body of the s3 key object into a string to ensure download
s = s3.get_object(Bucket=bucket, Key=gzip_key)['Body'].read()
print(len(s)) # check to ensure some data was returned
The above answers are for gzip files, for zip files, you may try
import boto3
import zipfile
from io import BytesIO
bucket = 'bucket1'
s3 = boto3.client('s3', use_ssl=False)
Key_unzip = 'result_files/'
prefix = "folder_name/"
zipped_keys = s3.list_objects_v2(Bucket=bucket, Prefix=prefix, Delimiter = "/")
file_list = []
for key in zipped_keys['Contents']:
file_list.append(key['Key'])
#This will give you list of files in the folder you mentioned as prefix
s3_resource = boto3.resource('s3')
#Now create zip object one by one, this below is for 1st file in file_list
zip_obj = s3_resource.Object(bucket_name=bucket, key=file_list[0])
print (zip_obj)
buffer = BytesIO(zip_obj.get()["Body"].read())
z = zipfile.ZipFile(buffer)
for filename in z.namelist():
file_info = z.getinfo(filename)
s3_resource.meta.client.upload_fileobj(
z.open(filename),
Bucket=bucket,
Key='result_files/' + f'{filename}')
This will work for your zip file and your result unzipped data will be in result_files folder. Make sure to increase memory and time on AWS Lambda to maximum since some files are pretty large and needs time to write.
Amazon S3 is a storage service. There is no in-built capability to manipulate the content of files.
However, you could use an AWS Lambda function to retrieve an object from S3, decompress it, then upload content back up again. However, please note that there is default limit of 500MB in temporary disk space for Lambda, so avoid decompressing too much data at the same time.
You could configure the S3 bucket to trigger the Lambda function when a new file is created in the bucket. The Lambda function would then:
Use boto3 to download the new file
Use the gzip Python library to extract files
Use boto3 to upload the resulting file(s)
Sample code:
import gzip
import io
import boto3
bucket = '<bucket_name>'
key = '<key_name>'
s3 = boto3.client('s3', use_ssl=False)
compressed_file = io.BytesIO(
s3.get_object(Bucket=bucket, Key=key)['Body'].read())
uncompressed_file = gzip.GzipFile(None, 'rb', fileobj=compressed_file)
s3.upload_fileobj(Fileobj=uncompressed_file, Bucket=bucket, Key=key[:-3])

Issue with uploading files from local directory to aws S3 using python 2.7 and boto 2

I’m doing simple operation to of downloading the gzip files from S3 bucket to the local directory. I’m extracting those into another local directory and then uploading them back to S3 bucket again into archive folder path. While doing this operation I want to make sure I am processing same set of files that I initially download from S3 bucket which is (f_name) in below code. Now, below code is not uploading those back to S3 , that’s where I’m stuck. But able to download from S3 and extract it into local directory. Can you please help me understand what is wrong with the _uploadFile function?
from boto.s3.connection import S3Connection
from boto.s3.key import *
import os
import os.path
aws_bucket= "event-logs-dev” ## S3 Bucket name
local_download_directory= "/Users/TargetData/Download/test_queue1/“ ## local directory to download the gzip files from S3.
Target_directory_to_extract = "/Users/TargetData/unzip” ##local directory to gunzip the downloaded files.
Target_s3_path_to_upload= "event-logs-dev/data/clean/xact/logs/archive/“ ## S3 bucket path to upload the files.
def decompressAllFilesFromNetfiler(self,aws_bucket,local_download_directory,Target_d irectory_to_extract,Target_s3_path_to_upload):
zipFiles = [f for f in os.listdir(local_download_directory) if re.match(r'.*\.tar\.gz', f)]
for f_name in zipFiles:
if os.path.exists(Target_directory_to_extract+"/"+f_name[:-len('.tar.gz')]) and os.access(Target_directory_to_extract+"/"+f_name[:-len('.tar.gz')], os.R_OK):
print ('File {} already exists!'.format(f_name))
else:
f_name_with_path = os.path.join(local_download_directory, f_name)
os.system('mkdir -p {} && tar vxzf {} -C {}'.format(Target_directory_to_extract, f_name_with_path, Target_directory_to_extract))
print ('Extracted file {}'.format(f_name))
self._uploadFile(aws_bucket,f_name,Target_s3_path_to_upload,Target_directory_to_extract)
def _uploadFile(self, aws_bucket, f_name,Target_s3_path_to_upload,Target_directory_to_extract):
full_key_name = os.path.expanduser(os.path.join(Target_s3_path_to_upload, f_name))
path = os.path.expanduser(os.path.join(Target_directory_to_extract, f_name))
try:
print "Uploaded extracted file to: %s" % (full_key_name)
key = aws_bucket.new_key(full_key_name)
key.set_contents_from_filename(path)
except:
if full_key_name is None:
print "Error uploading”
Currently, the output prints that Uploaded extracted file to: event-logs-dev/data/clean/xact/logs/archive/1442235602129200000.tar.gz, but nothing is uploaded to S3 bucket. Your help is greatly appreciated!! Thank you in advance!
It appears that you have cut and pasted parts of your code - and maybe formatting was lost as your code above will not work as pasted. I've taken the liberty to make it PEP8 (mostly) however there is still some missing code to create the S3 objects. Since your import the modules, I presume that you have that section of code and just didn't paste it.
here is a cleaned up version of your code formatted correctly. I also added a Exception code to your try: block to print out the error you get. You should update the Exception to be more specific to the Exceptions thrown for make_key or set_contents_... but the general Exception will get you started. If nothing more this is more readable, but you should include your S3 connection code too - and remove anything that is specific to your domain (e.g. keys, trade secrets, etc).
#!/usr/bin/env python
"""
do some download
some extract
and some upload
"""
from boto.s3.connection import S3Connection
from boto.s3.key import *
import os
import os.path
aws_bucket = 'event-logs-dev'
local_download_directory = '/Users/TargetData/Download/test_queue1/'
Target_directory_to_extract = '/Users/TargetData/unzip'
Target_s3_path_to_upload = 'event-logs-dev/data/clean/xact/logs/archive/'
'''
MUST BE SOME MAGIC HERE TO GET AN S3 CONNECTION ???
aws_bucket IS NOT A BUCKET OBJECT ...
'''
def decompressAllFilesFromNetfiler(self,
aws_bucket,
local_download_directory,
Target_directory_to_extract,
Target_s3_path_to_upload):
'''
decompress stuff
'''
zipFiles = [f for f in os.listdir(
local_download_directory) if re.match(r'.*\.tar\.gz', f)]
for f_name in zipFiles:
if os.path.exists(
"{}/{}".format(Target_directory_to_extract,
f_name[:len('.tar.gz')])) and os.access(
"{}/{}".format(Target_directory_to_extract,
f_name[:len('.tar.gz')])) and os.R_OK:
print ('File {} already exists!'.format(f_name))
else:
f_name_with_path = os.path.join(local_download_directory, f_name)
os.system('mkdir -p {} && tar vxzf {} -C {}'.format(
Target_directory_to_extract,
f_name_with_path,
Target_directory_to_extract))
print ('Extracted file {}'.format(f_name))
self._uploadFile(aws_bucket,
f_name,
Target_s3_path_to_upload,
Target_directory_to_extract)
def _uploadFile(self,
aws_bucket,
f_name,
Target_s3_path_to_upload,
Target_directory_to_extract):
full_key_name = os.path.expanduser(os.path.join(Target_s3_path_to_upload,
f_name))
path = os.path.expanduser(os.path.join(Target_directory_to_extract, f_name))
try:
S3CONN = S3Connection()
BUCKET = S3CONN.get_bucket(aws_bucket)
key = BUCKET.new_key(full_key_name)
key.set_contents_from_filename(path)
print "Uploaded extracted file to: {}".format(full_key_name)
except Exception as UploadERR:
if full_key_name is None:
print 'Error uploading'
else:
print "Error : {}".format(UploadERR)

upload a directory to s3 with boto

I am already connected to the instance and I want to upload the files that are generated from my python script directly to S3. I have tried this:
import boto
s3 = boto.connect_s3()
bucket = s3.get_bucket('alexandrabucket')
from boto.s3.key import Key
key = bucket.new_key('s0').set_contents_from_string('some content')
but this is rather creating a new file s0 with the context "same content" while I want to upload the directory s0 to mybucket.
I had a look also to s3put but I didn't manage to get what I want.
The following function can be used to upload directory to s3 via boto.
def uploadDirectory(path,bucketname):
for root,dirs,files in os.walk(path):
for file in files:
s3C.upload_file(os.path.join(root,file),bucketname,file)
Provide a path to the directory and bucket name as the inputs. The files are placed directly into the bucket. Alter the last variable of the upload_file() function to place them in "directories".
There is nothing in the boto library itself that would allow you to upload an entire directory. You could write your own code to traverse the directory using os.walk or similar and to upload each individual file using boto.
There is a command line utility in boto called s3put that could handle this or you could use the AWS CLI tool which has a lot of features that allow you to upload entire directories or even sync the S3 bucket with a local directory or vice-versa.
The s3fs package provides nice functionalities to handle such cases
s3_file = s3fs.S3FileSystem()
local_path = "some_dir_path/some_dir_path/"
s3_path = "bucket_name/dir_path"
s3_file.put(local_path, s3_path, recursive=True)
I built the function based on the feedback from #JDPTET, however,
I needed to remove the common entire local path from getting uploaded to the bucket!
Not sure how many path separators I encounter - so I had to use os.path.normpath
def upload_folder_to_s3(s3bucket, inputDir, s3Path):
print("Uploading results to s3 initiated...")
print("Local Source:",inputDir)
os.system("ls -ltR " + inputDir)
print("Dest S3path:",s3Path)
try:
for path, subdirs, files in os.walk(inputDir):
for file in files:
dest_path = path.replace(inputDir,"")
__s3file = os.path.normpath(s3Path + '/' + dest_path + '/' + file)
__local_file = os.path.join(path, file)
print("upload : ", __local_file, " to Target: ", __s3file, end="")
s3bucket.upload_file(__local_file, __s3file)
print(" ...Success")
except Exception as e:
print(" ... Failed!! Quitting Upload!!")
print(e)
raise e
s3 = boto3.resource('s3', region_name='us-east-1')
s3bucket = s3.Bucket("<<s3bucket_name>>")
upload_folder_to_s3(s3bucket, "<<Local Folder>>", "<<s3 Path>>")
You could do the following:
import os
import boto3
s3_resource = boto3.resource("s3", region_name="us-east-1")
def upload_objects():
try:
bucket_name = "S3_Bucket_Name" #s3 bucket name
root_path = 'D:/sample/' # local folder for upload
my_bucket = s3_resource.Bucket(bucket_name)
for path, subdirs, files in os.walk(root_path):
path = path.replace("\\","/")
directory_name = path.replace(root_path,"")
for file in files:
my_bucket.upload_file(os.path.join(path, file), directory_name+'/'+file)
except Exception as err:
print(err)
if __name__ == '__main__':
upload_objects()
This is the code I used which recursively upload files from the specified folder to the specified s3 path. Just add S3 credential and bucket details in the script:
https://gist.github.com/hari116/4ab5ebd885b63e699c4662cd8382c314/
#!/usr/bin/python
"""Usage: Add bucket name and credentials
script.py <source folder> <s3 destination folder >"""
import os
from sys import argv
import boto3
from botocore.exceptions import NoCredentialsError
ACCESS_KEY = ''
SECRET_KEY = ''
host = ''
bucket_name = ''
local_folder, s3_folder = argv[1:3]
walks = os.walk(local_folder)
# Function to upload to s3
def upload_to_aws(bucket, local_file, s3_file):
"""local_file, s3_file can be paths"""
s3 = boto3.client('s3', aws_access_key_id=ACCESS_KEY,
aws_secret_access_key=SECRET_KEY)
print(' Uploading ' +local_file + ' as ' + bucket + '/' +s3_file)
try:
s3.upload_file(local_file, bucket, s3_file)
print(' '+s3_file + ": Upload Successful")
print(' ---------')
return True
except NoCredentialsError:
print("Credentials not available")
return False
"""For file names"""
for source, dirs, files in walks:
print('Directory: ' + source)
for filename in files:
# construct the full local path
local_file = os.path.join(source, filename)
# construct the full Dropbox path
relative_path = os.path.relpath(local_file, local_folder)
s3_file = os.path.join(s3_folder, relative_path)
# Invoke upload function
upload_to_aws(bucket_name, local_file, s3_file)
For reading file form folder we can use
import boto
from boto.s3.key import Key
keyId = 'YOUR_AWS_ACCESS_KEY_ID'
sKeyId='YOUR_AWS_ACCESS_KEY_ID'
bucketName='your_bucket_name'
conn = boto.connect_s3(keyId,sKeyId)
bucket = conn.get_bucket(bucketName)
for key in bucket.list():
print ">>>>>"+key.name
pathV = key.name.split('/')
if(pathV[0] == "data"):
if(pathV[1] != ""):
srcFileName = key.name
filename = key.name
filename = filename.split('/')[1]
destFileName = "model/data/"+filename
k = Key(bucket,srcFileName)
k.get_contents_to_filename(destFileName)
elif(pathV[0] == "nlu_data"):
if(pathV[1] != ""):
srcFileName = key.name
filename = key.name
filename = filename.split('/')[1]
destFileName = "model/nlu_data/"+filename
k = Key(bucket,srcFileName)
k.get_contents_to_filename(destFileName)
Updated #user 923227's answer to (1) include newer boto3 interface (2) work with nuances of windows double backslash (3) cleaner tqdm progress bar:
import os
from tqdm import tqdm
def upload_folder_to_s3(s3_client, s3bucket, input_dir, s3_path):
pbar = tqdm(os.walk(input_dir))
for path, subdirs, files in pbar:
for file in files:
dest_path = path.replace(input_dir, "").replace(os.sep, '/')
s3_file = f'{s3_path}/{dest_path}/{file}'.replace('//', '/')
local_file = os.path.join(path, file)
s3_client.upload_file(local_file, s3bucket, s3_file)
pbar.set_description(f'Uploaded {local_file} to {s3_file}')
print(f"Successfully uploaded {input_dir} to S3 {s3_path}")
Usage example:
s3_client = boto3.client('s3', aws_access_key_id=AWS_ACCESS_KEY_ID, aws_secret_access_key=AWS_SECRET_ACCESS_KEY)
upload_folder_to_s3(s3_client, 'BUCKET-NAME', <local-directory>, <s3-directory>)
Somehow the other snippets did not really work for me, this is a modification of the snippet from user 923227 that does.
This code copies all files in a directory and maintains the directory in S3, e.g.2023/01/file.jpg will be in the bucket as 2023/01/file.jpg.
import os
import sys
import boto3
client = boto3.client('s3')
local_path = "your-path/data"
bucketname = "bucket-name"
for path, dirs, files in os.walk(local_path):
for file in files:
file_s3 = os.path.normpath(path + '/' + file)
file_local = os.path.join(path, file)
print("Upload:", file_local, "to target:", file_s3, end="")
client.upload_file(file_local, bucketname, file_s3)
print(" ...Success")
Another method that did not exist when this question was first asked is to use python-rclone (https://github.com/ddragosd/python-rclone/blob/master/README.md).
This requires a download of rclone and a working rclone config. Commonly used for AWS (https://rclone.org/s3/) but can be used for other providers as well.
install('python-rclone')
import rclone
cfg_path = r'(path to rclone config file here)'
with open(cfg_path) as f:
cfg = f.read()
# Implementation
# Local file to cloud server
result = rclone.with_config(cfg).run_cmd(command="sync", extra_args=["/home/demodir/", "AWS test:dummydir/etc/"])
# Cloud server to cloud server
result = rclone.with_config(cfg).run_cmd(command="sync", extra_args=["Gdrive:test/testing/", "AWS test:dummydir/etc/"
This allows you to run a "sync" command similar to the AWS CLI within your python code by reading in the config file and mapping your output via kwargs (extra_args)
This solution does not use boto, but I think it could do what the OP wants.
It uses awscli and Python.
import os
class AwsCredentials:
def __init__(self, access_key: str, secret_key: str):
self.access_key = access_key
self.secret_key = secret_key
def to_command(self):
credentials = f'AWS_ACCESS_KEY_ID={self.access_key} AWS_SECRET_ACCESS_KEY={self.secret_key}'
return credentials
def sync_s3_bucket(credentials: AwsCredentials, source_path: str, bucket: str) -> None:
command = f'{credentials.to_command()} aws s3 sync {source_path} s3://{bucket}'
result = os.system(command)
assert result == 0, f'The s3 sync was not successful, error code: {result}'
Please consider getting the AWS credentials from a file or from the environment.
The documentation for the s3 sync command is here.
Simply running terminal commands using os module with F string works
import os
ActualFolderName = "FolderToBeUploadedOnS3"
os.system(f'aws s3 cp D:\<PathToYourFolder>\{ActualFolderName} s3://<BucketName>/{ActualFolderName}/ --recursive')