Cannot Upload Multiple Files to AWS S3 using Python Script and wildcards - python

I am newer to working with python as well as AWS.
I am attempting to move various files "and usually" with specific formats from my local pc to an S3 AWS folder via a python script. I am having an issue with implementing a wildcard within the script to catch various files at once. I am able to move one file at a time using the string "data = open('file_example_here.csv', 'rb')" , though I am stuck on adjusting my python script to capture all (i.e. .csv or all .json files). An example set of files are detailed below, so if I wanted to move all .json files to my s3 instance using a wildcard in the script how could I go about adjusting my script to handle that ask if possible?.
Any help would really be appreciated , implementation is shared below.
/home/user/folder1/c_log_1-10-19.csv
/home/user/folder1/c_log_2-10-19.csv
/home/user/folder1/c_log_3-10-19.csv
/home/user/folder1/c_log_4-10-19.csv
/home/user/folder1/c_log_5-10-19.csv
/home/user/folder1/c_log_6-10-19.csv
/home/user/folder1/h_log_1-11-18.json
/home/user/folder1/h_log_2-11-18.json
/home/user/folder1/h_log_3-11-18.json
/home/user/folder1/h_log_4-11-18.json
/home/user/folder1/h_log_5-11-18.json
/home/user/folder1/h_log_6-11-18.json
import boto3
from botocore.client import Config
ACCESS_KEY_ID = 'key_id_here'
ACCESS_SECRET_KEY = 'secret_key_here'
BUCKET_NAME = 'bucket_name_here'
data = open('test_file.csv', 'rb')
s3 = boto3.resource(
's3',
aws_access_key_id=ACCESS_KEY_ID,
aws_secret_access_key=ACCESS_SECRET_KEY,
config=Config(signature_version='s3v4')
)
s3.Bucket(BUCKET_NAME).put_object(Key='folder_test/folder_test_2/test_file.csv', Body=data)
print ("All_Done")
````````````````````````````````````````````````````
################################################
############## UPDATED CODE BELOW ############
################################################
import glob
import boto3
from botocore.client import Config
ACCESS_KEY_ID = 'some_key'
ACCESS_SECRET_KEY = 'some_key'
BUCKET_NAME = 'some_bucket'
#session = boto3.Session(profile_name='default')
s3 = boto3.resource(
's3',
aws_access_key_id=ACCESS_KEY_ID,
aws_secret_access_key=ACCESS_SECRET_KEY,
config=Config(signature_version='s3v4')
)
csv_files = glob.glob("/home/user/Desktop/*.csv")
#json_files = glob.glob("/home/user/folder1/h_log_*.json")
for filename in csv_files:
print("Putting %s" % filename)
s3.upload_file(filename, BUCKET_NAME, filename)
#for filename in json_files:
# print("Putting %s" % filename)
# s3.upload_file(filename, BUCKET_NAME, filename)
s3.Bucket(BUCKET_NAME).put_object(Key='folder1/folder1', Body=csv_files)
print("All_Done")

You can use something as simple as Python's glob module to find all files matching a specified pattern as in this example below:
#!/usr/bin/env python
import glob
import boto3
import os
BUCKET_NAME = 'MyBucket'
FOLDER_NAME = 'folder1/folder1'
session = boto3.Session(profile_name='default')
s3 = session.client('s3')
csv_files = glob.glob("/home/user/folder1/c_log_*.csv")
json_files = glob.glob("/home/user/folder1/h_log_*.json")
for filename in csv_files:
key = "%s/%s" % (FOLDER_NAME, os.path.basename(filename))
print("Putting %s as %s" % (filename,key))
s3.upload_file(filename, BUCKET_NAME, key)
for filename in json_files:
key = "%s/%s" % (FOLDER_NAME, os.path.basename(filename))
print("Putting %s as %s" % (filename,key))
s3.upload_file(filename, BUCKET_NAME, key)
print("All_Done")
The above code assumes you have AWS CLI installed with an access key configured under the default profile. If not, you can use the various methods of authenticating with boto3.
There's probably a more pythonic way to do this but this simple script works.

Check out the glob module (https://docs.python.org/3/library/glob.html).
import glob
csv_files = glob.glob('/home/user/folder_1/*.csv')
json_files = glob.glob('/home/user/folder_1/*.json')
Then iterate over these lists and upload as you were doing.
Also, there's no need to read in the data from the file. Just use the upload_file method on the bucket: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/s3.html#S3.Bucket.upload_file

Related

unable to upload pdf containing only images to S3 bucket using python

I've images which have been converted into pdf and stored in a folder named 'test'.
I need to upload all files inside test folder to S3
Current situation : files get created in S3 but are empty. I'm assuming because the source pdf file only contains an image. I'm unable to figure out a way to ensure images of the pdf also get uploaded
Here's my code:
import os
import boto3
import botocore
import sys
SERVICE_NAME = 's3'
AWS_ACCESS_KEY_ID = 'XXXX'
AWS_SECRET_ACCESS_KEY = 'XXXXX+A'
AWS_S3_ENDPOINT_URL = 'https://s3.amazonaws.com'
AWS_STORAGE_BUCKET_NAME = 'resolution-medical/resolution_scanner'
AWS_STORAGE_BUCKET_NAME = 'resolution-medical'
source_folder = '/home/irfan/Downloads/test'
arr = os.listdir(source_folder)
for each in arr:
try:
arr2 = os.listdir(source_folder + '/' + each)
except:
arr2 = []
if len(arr2) == 0:
filepath = 'resolution_scanner/' + each
fileobject = source_folder+ '/' + each
conn = boto3.resource(
service_name=SERVICE_NAME,
aws_access_key_id=AWS_ACCESS_KEY_ID,
aws_secret_access_key=AWS_SECRET_ACCESS_KEY,
endpoint_url=AWS_S3_ENDPOINT_URL)
conn.Object(AWS_STORAGE_BUCKET_NAME, filepath).put(Body=fileobject, ACL='public-read', ContentType='application/pdf')
sys.exit()
It seems that the encoding issue occurs with put(). This SO Q&A solving with java. For me, just using upload_file() works like this:
import boto3
file = "PDF/aaaaa.pdf"
s3 = boto3.resource("s3")
s3.Object("my-bucket-test", "test.pdf").upload_file(file)

How to upload images to S3 bucket if it doesn't already exist

I have a python script running to upload images to s3 bucket every hour.
The images coming in are of three types and the script creates a specific folder based on name of image and then uploads images to that folder in S3 based on image name.
What's happening now is that every hour the same images are getting overwritten in the bucket, I need to upload images only if it doesn't exist already
How can I achieve this.
Please help through
import os.path, shutil
import os, time
import socket
import boto3
from botocore.exceptions import NoCredentialsError
import glob
import json
from apscheduler.schedulers.blocking import BlockingScheduler
id = id_of_file
def my_schedule():
s3 = boto3.client('s3', aws_access_key_id="Access_key",
aws_secret_access_key="Secret_key")
folder_path = "path"
images = [f for f in os.listdir(folder_path) if os.path.isfile(os.path.join(folder_path, f))]
for image in images:
print(image)
folder_name = image.split('-')[0]
print(folder_name)
print("folder created**********************************")
key = "%s/%s" % (id+ '/' + folder_name, os.path.basename(image))
objs = list(bucket.objects.filter(Prefix=key))
print("Putting %s as %s" % (image, key))
final_file = folder_path + image
s3.upload_file(final_file, Bucket, key)
print("ALL Images uploaded successfully to s3 bucket")
time.sleep(5)
scheduler = BlockingScheduler()
scheduler.add_job(my_schedule, 'interval', hours=1)
scheduler.start()

Upload files in a subdirectory in S3 with boto3 in python

I want to upload files in a a subdirectory in a bucket. When I try to upload it in the bucket only it works well but I don't know how to add the subdirectory (Prefix ?)
def dlImgs():
s3 = boto3.resource("s3")
if gmNew is not None:
reqImg = requests.get(gmNew, stream=True)
fileObj = reqImg.raw
reqData = fileObj.read()
#upload to S3
s3.Bucket(_BUCKET_NAME_IMG).put_object(Key=ccvName, Body=reqData)
dlImgs()
But how to add the Prefix ?
EDIT: I find the solution by creating a path directly in the ccvName variable.
I had written this long ago.
def upload_file(file_name,in_sub_folder,bucket_name):
client = boto3.client('s3')
fname = os.path.basename(file_name)
key = f'{in_sub_folder}/{fname}'
try:
client.upload_file(fname, Bucket=bucket_name ,Key=key)
except:
print(f'{file_name} not uploaded')

How to encrypt file from Python using AWS KMS server side encryption

I am fairly new to python. Need some help. This is what I need.
We want to look for the file in directory, if file exist and size of the file is not zero bytes, I want to encrypt the file using AWS KMS encryption and upload it to bucket.
If file doesn't exist then raise an exception
If file exist but the file is zero bytes then raise exception.
Below is the code I could come up with but I am sure there is better way to write this and need your help. One thing I couldn't achieve is the encryption.
import os
import sys
import boto3
from botocore.client import Config
import configparser
import re
import os.path
import glob
## Initialize the Parameters
def initconfig(input):
config = configparser.ConfigParser()
config.read_file(open( 'CONFIG_AIRBILLING.conf'))
print('Code Name is :'+ input)
global REMOTE_DIR,ACCESS_KEY_ID,ACCESS_SECRET_KEY,BUCKET_NAME,TARGET_DIR,FILENAME,SRC_DIR,File,FILEPATH
ACCESS_KEY_ID = config.get('ACCESS', 'ACCESS_KEY_ID')
print('ACCESS_ID_IS:'+ ACCESS_KEY_ID)
ACCESS_SECRET_KEY = config.get('ACCESS', 'ACCESS_SECRET_KEY')
BUCKET_NAME = config.get('ACCESS', 'BUCKET_NAME')
SRC_DIR = config.get(input, 'SRC_DIR')
FILENAME = config.get(input, 'FILENAME')
FILENAME=FILENAME+'*.txt'
FILEPATH=SRC_DIR+'\\'+FILENAME
print('File Path is:'+FILEPATH)
TARGET_DIR = config.get(input, 'TARGET_DIR')
File='demo.txt'
## This function will make sure file exist in Source directory
def readstatus():
print('Startibg')
try:
with open(FILEPATH,'r') as f:
f.closed
result='True'
movefiles(result)
except (Exception) as e:
print('***Error:File Not Found or Accessible***')
result='False*'
raise e
## This function will move the files to AWS S3 bucket
def movefiles(result):
if result=='True':
s3 = boto3.resource(
's3',
aws_access_key_id=ACCESS_KEY_ID,
aws_secret_access_key=ACCESS_SECRET_KEY,
config=Config(signature_version='s3v4')
)
s3.Bucket(BUCKET_NAME).put_object(Key=TARGET_DIR + '/' + File, Body=File)
print('***File Moved***')
print("Done")
if __name__ == '__main__':
print(len(sys.argv))
initconfig(sys.argv[1])
print(sys.argv)
readstatus()
#initconfig(input=input())
#readstatus()

Boto3 to download all files from a S3 Bucket

I'm using boto3 to get files from s3 bucket. I need a similar functionality like aws s3 sync
My current code is
#!/usr/bin/python
import boto3
s3=boto3.client('s3')
list=s3.list_objects(Bucket='my_bucket_name')['Contents']
for key in list:
s3.download_file('my_bucket_name', key['Key'], key['Key'])
This is working fine, as long as the bucket has only files.
If a folder is present inside the bucket, its throwing an error
Traceback (most recent call last):
File "./test", line 6, in <module>
s3.download_file('my_bucket_name', key['Key'], key['Key'])
File "/usr/local/lib/python2.7/dist-packages/boto3/s3/inject.py", line 58, in download_file
extra_args=ExtraArgs, callback=Callback)
File "/usr/local/lib/python2.7/dist-packages/boto3/s3/transfer.py", line 651, in download_file
extra_args, callback)
File "/usr/local/lib/python2.7/dist-packages/boto3/s3/transfer.py", line 666, in _download_file
self._get_object(bucket, key, filename, extra_args, callback)
File "/usr/local/lib/python2.7/dist-packages/boto3/s3/transfer.py", line 690, in _get_object
extra_args, callback)
File "/usr/local/lib/python2.7/dist-packages/boto3/s3/transfer.py", line 707, in _do_get_object
with self._osutil.open(filename, 'wb') as f:
File "/usr/local/lib/python2.7/dist-packages/boto3/s3/transfer.py", line 323, in open
return open(filename, mode)
IOError: [Errno 2] No such file or directory: 'my_folder/.8Df54234'
Is this a proper way to download a complete s3 bucket using boto3. How to download folders.
I have the same needs and created the following function that download recursively the files.
The directories are created locally only if they contain files.
import boto3
import os
def download_dir(client, resource, dist, local='/tmp', bucket='your_bucket'):
paginator = client.get_paginator('list_objects')
for result in paginator.paginate(Bucket=bucket, Delimiter='/', Prefix=dist):
if result.get('CommonPrefixes') is not None:
for subdir in result.get('CommonPrefixes'):
download_dir(client, resource, subdir.get('Prefix'), local, bucket)
for file in result.get('Contents', []):
dest_pathname = os.path.join(local, file.get('Key'))
if not os.path.exists(os.path.dirname(dest_pathname)):
os.makedirs(os.path.dirname(dest_pathname))
if not file.get('Key').endswith('/'):
resource.meta.client.download_file(bucket, file.get('Key'), dest_pathname)
The function is called that way:
def _start():
client = boto3.client('s3')
resource = boto3.resource('s3')
download_dir(client, resource, 'clientconf/', '/tmp', bucket='my-bucket')
When working with buckets that have 1000+ objects its necessary to implement a solution that uses the NextContinuationToken on sequential sets of, at most, 1000 keys. This solution first compiles a list of objects then iteratively creates the specified directories and downloads the existing objects.
import boto3
import os
s3_client = boto3.client('s3')
def download_dir(prefix, local, bucket, client=s3_client):
"""
params:
- prefix: pattern to match in s3
- local: local path to folder in which to place files
- bucket: s3 bucket with target contents
- client: initialized s3 client object
"""
keys = []
dirs = []
next_token = ''
base_kwargs = {
'Bucket':bucket,
'Prefix':prefix,
}
while next_token is not None:
kwargs = base_kwargs.copy()
if next_token != '':
kwargs.update({'ContinuationToken': next_token})
results = client.list_objects_v2(**kwargs)
contents = results.get('Contents')
for i in contents:
k = i.get('Key')
if k[-1] != '/':
keys.append(k)
else:
dirs.append(k)
next_token = results.get('NextContinuationToken')
for d in dirs:
dest_pathname = os.path.join(local, d)
if not os.path.exists(os.path.dirname(dest_pathname)):
os.makedirs(os.path.dirname(dest_pathname))
for k in keys:
dest_pathname = os.path.join(local, k)
if not os.path.exists(os.path.dirname(dest_pathname)):
os.makedirs(os.path.dirname(dest_pathname))
client.download_file(bucket, k, dest_pathname)
import os
import boto3
#initiate s3 resource
s3 = boto3.resource('s3')
# select bucket
my_bucket = s3.Bucket('my_bucket_name')
# download file into current directory
for s3_object in my_bucket.objects.all():
# Need to split s3_object.key into path and file name, else it will give error file not found.
path, filename = os.path.split(s3_object.key)
my_bucket.download_file(s3_object.key, filename)
Amazon S3 does not have folders/directories. It is a flat file structure.
To maintain the appearance of directories, path names are stored as part of the object Key (filename). For example:
images/foo.jpg
In this case, the whole Key is images/foo.jpg, rather than just foo.jpg.
I suspect that your problem is that boto is returning a file called my_folder/.8Df54234 and is attempting to save it to the local filesystem. However, your local filesystem interprets the my_folder/ portion as a directory name, and that directory does not exist on your local filesystem.
You could either truncate the filename to only save the .8Df54234 portion, or you would have to create the necessary directories before writing files. Note that it could be multi-level nested directories.
An easier way would be to use the AWS Command-Line Interface (CLI), which will do all this work for you, eg:
aws s3 cp --recursive s3://my_bucket_name local_folder
There's also a sync option that will only copy new and modified files.
I'm currently achieving the task, by using the following
#!/usr/bin/python
import boto3
s3=boto3.client('s3')
list=s3.list_objects(Bucket='bucket')['Contents']
for s3_key in list:
s3_object = s3_key['Key']
if not s3_object.endswith("/"):
s3.download_file('bucket', s3_object, s3_object)
else:
import os
if not os.path.exists(s3_object):
os.makedirs(s3_object)
Although, it does the job, I'm not sure its good to do this way.
I'm leaving it here to help other users and further answers, with better manner of achieving this
Better late than never:) The previous answer with paginator is really good. However it is recursive, and you might end up hitting Python's recursion limits. Here's an alternate approach, with a couple of extra checks.
import os
import errno
import boto3
def assert_dir_exists(path):
"""
Checks if directory tree in path exists. If not it created them.
:param path: the path to check if it exists
"""
try:
os.makedirs(path)
except OSError as e:
if e.errno != errno.EEXIST:
raise
def download_dir(client, bucket, path, target):
"""
Downloads recursively the given S3 path to the target directory.
:param client: S3 client to use.
:param bucket: the name of the bucket to download from
:param path: The S3 directory to download.
:param target: the local directory to download the files to.
"""
# Handle missing / at end of prefix
if not path.endswith('/'):
path += '/'
paginator = client.get_paginator('list_objects_v2')
for result in paginator.paginate(Bucket=bucket, Prefix=path):
# Download each file individually
for key in result['Contents']:
# Calculate relative path
rel_path = key['Key'][len(path):]
# Skip paths ending in /
if not key['Key'].endswith('/'):
local_file_path = os.path.join(target, rel_path)
# Make sure directories exist
local_file_dir = os.path.dirname(local_file_path)
assert_dir_exists(local_file_dir)
client.download_file(bucket, key['Key'], local_file_path)
client = boto3.client('s3')
download_dir(client, 'bucket-name', 'path/to/data', 'downloads')
A lot of the solutions here get pretty complicated. If you're looking for something simpler, cloudpathlib wraps things in a nice way for this use case that will download directories or files.
from cloudpathlib import CloudPath
cp = CloudPath("s3://bucket/product/myproject/2021-02-15/")
cp.download_to("local_folder")
Note: for large folders with lots of files, awscli at the command line is likely faster.
I have a workaround for this that runs the AWS CLI in the same process.
Install awscli as python lib:
pip install awscli
Then define this function:
from awscli.clidriver import create_clidriver
def aws_cli(*cmd):
old_env = dict(os.environ)
try:
# Environment
env = os.environ.copy()
env['LC_CTYPE'] = u'en_US.UTF'
os.environ.update(env)
# Run awscli in the same process
exit_code = create_clidriver().main(*cmd)
# Deal with problems
if exit_code > 0:
raise RuntimeError('AWS CLI exited with code {}'.format(exit_code))
finally:
os.environ.clear()
os.environ.update(old_env)
To execute:
aws_cli('s3', 'sync', '/path/to/source', 's3://bucket/destination', '--delete')
import boto3, os
s3 = boto3.client('s3')
def download_bucket(bucket):
paginator = s3.get_paginator('list_objects_v2')
pages = paginator.paginate(Bucket=bucket)
for page in pages:
if 'Contents' in page:
for obj in page['Contents']:
os.path.dirname(obj['Key']) and os.makedirs(os.path.dirname(obj['Key']), exist_ok=True)
try:
s3.download_file(bucket, obj['Key'], obj['Key'])
except NotADirectoryError:
pass
# Change bucket_name to name of bucket that you want to download
download_bucket(bucket_name)
This should work for all number of objects (also when there are more than 1000). Each paginator page can contain up to 1000 objects.Notice extra param in os.makedirs function - exist_ok=True which cause that it's not throwing error when path exist)
I've updated Grant's answer to run in parallel, it's much faster if anyone is interested:
from concurrent import futures
import os
import boto3
def download_dir(prefix, local, bucket):
client = boto3.client('s3')
def create_folder_and_download_file(k):
dest_pathname = os.path.join(local, k)
if not os.path.exists(os.path.dirname(dest_pathname)):
os.makedirs(os.path.dirname(dest_pathname))
print(f'downloading {k} to {dest_pathname}')
client.download_file(bucket, k, dest_pathname)
keys = []
dirs = []
next_token = ''
base_kwargs = {
'Bucket': bucket,
'Prefix': prefix,
}
while next_token is not None:
kwargs = base_kwargs.copy()
if next_token != '':
kwargs.update({'ContinuationToken': next_token})
results = client.list_objects_v2(**kwargs)
contents = results.get('Contents')
for i in contents:
k = i.get('Key')
if k[-1] != '/':
keys.append(k)
else:
dirs.append(k)
next_token = results.get('NextContinuationToken')
for d in dirs:
dest_pathname = os.path.join(local, d)
if not os.path.exists(os.path.dirname(dest_pathname)):
os.makedirs(os.path.dirname(dest_pathname))
with futures.ThreadPoolExecutor() as executor:
futures.wait(
[executor.submit(create_folder_and_download_file, k) for k in keys],
return_when=futures.FIRST_EXCEPTION,
)
Yet another parallel downloader using asyncio/aioboto
import os, time
import asyncio
from itertools import chain
import json
from typing import List
from json.decoder import WHITESPACE
import logging
from functools import partial
from pprint import pprint as pp
# Third Party
import asyncpool
import aiobotocore.session
import aiobotocore.config
_NUM_WORKERS = 50
bucket_name= 'test-data'
bucket_prefix= 'etl2/test/20210330/f_api'
async def save_to_file(s3_client, bucket: str, key: str):
response = await s3_client.get_object(Bucket=bucket, Key=key)
async with response['Body'] as stream:
content = await stream.read()
if 1:
fn =f'out/downloaded/{bucket_name}/{key}'
dn= os.path.dirname(fn)
if not isdir(dn):
os.makedirs(dn,exist_ok=True)
if 1:
with open(fn, 'wb') as fh:
fh.write(content)
print(f'Downloaded to: {fn}')
return [0]
async def go(bucket: str, prefix: str) -> List[dict]:
"""
Returns list of dicts of object contents
:param bucket: s3 bucket
:param prefix: s3 bucket prefix
:return: list of download statuses
"""
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger()
session = aiobotocore.session.AioSession()
config = aiobotocore.config.AioConfig(max_pool_connections=_NUM_WORKERS)
contents = []
async with session.create_client('s3', config=config) as client:
worker_co = partial(save_to_file, client, bucket)
async with asyncpool.AsyncPool(None, _NUM_WORKERS, 's3_work_queue', logger, worker_co,
return_futures=True, raise_on_join=True, log_every_n=10) as work_pool:
# list s3 objects using paginator
paginator = client.get_paginator('list_objects')
async for result in paginator.paginate(Bucket=bucket, Prefix=prefix):
for c in result.get('Contents', []):
contents.append(await work_pool.push(c['Key'], client))
# retrieve results from futures
contents = [c.result() for c in contents]
return list(chain.from_iterable(contents))
def S3_download_bucket_files():
s = time.perf_counter()
_loop = asyncio.get_event_loop()
_result = _loop.run_until_complete(go(bucket_name, bucket_prefix))
assert sum(_result)==0, _result
print(_result)
elapsed = time.perf_counter() - s
print(f"{__file__} executed in {elapsed:0.2f} seconds.")
It will fetch list of files from S3 first and then download using aioboto with _NUM_WORKERS=50 reading data in parallel from the network.
If you want to call a bash script using python, here is a simple method to load a file from a folder in S3 bucket to a local folder (in a Linux machine) :
import boto3
import subprocess
import os
###TOEDIT###
my_bucket_name = "your_my_bucket_name"
bucket_folder_name = "your_bucket_folder_name"
local_folder_path = "your_local_folder_path"
###TOEDIT###
# 1.Load thes list of files existing in the bucket folder
FILES_NAMES = []
s3 = boto3.resource('s3')
my_bucket = s3.Bucket('{}'.format(my_bucket_name))
for object_summary in my_bucket.objects.filter(Prefix="{}/".format(bucket_folder_name)):
# print(object_summary.key)
FILES_NAMES.append(object_summary.key)
# 2.List only new files that do not exist in local folder (to not copy everything!)
new_filenames = list(set(FILES_NAMES )-set(os.listdir(local_folder_path)))
# 3.Time to load files in your destination folder
for new_filename in new_filenames:
upload_S3files_CMD = """aws s3 cp s3://{}/{}/{} {}""".format(my_bucket_name,bucket_folder_name,new_filename ,local_folder_path)
subprocess_call = subprocess.call([upload_S3files_CMD], shell=True)
if subprocess_call != 0:
print("ALERT: loading files not working correctly, please re-check new loaded files")
From AWS S3 Docs (How do I use folders in an S3 bucket?):
In Amazon S3, buckets and objects are the primary resources, and objects are stored in buckets. Amazon S3 has a flat structure instead of a hierarchy like you would see in a file system. However, for the sake of organizational simplicity, the Amazon S3 console supports the folder concept as a means of grouping objects. Amazon S3 does this by using a shared name prefix for objects (that is, objects have names that begin with a common string). Object names are also referred to as key names.
For example, you can create a folder on the console named photos and store an object named myphoto.jpg in it. The object is then stored with the key name photos/myphoto.jpg, where photos/ is the prefix.
To download all files from "mybucket" into the current directory respecting the bucket's emulated directory structure (creating the folders from the bucket if they don't already exist locally):
import boto3
import os
bucket_name = "mybucket"
s3 = boto3.client("s3")
objects = s3.list_objects(Bucket = bucket_name)["Contents"]
for s3_object in objects:
s3_key = s3_object["Key"]
path, filename = os.path.split(s3_key)
if len(path) != 0 and not os.path.exists(path):
os.makedirs(path)
if not s3_key.endswith("/"):
download_to = path + '/' + filename if path else filename
s3.download_file(bucket_name, s3_key, download_to)
It is a very bad idea to get all files in one go, you should rather get it in batches.
One implementation which I use to fetch a particular folder (directory) from S3 is,
def get_directory(directory_path, download_path, exclude_file_names):
# prepare session
session = Session(aws_access_key_id, aws_secret_access_key, region_name)
# get instances for resource and bucket
resource = session.resource('s3')
bucket = resource.Bucket(bucket_name)
for s3_key in self.client.list_objects(Bucket=self.bucket_name, Prefix=directory_path)['Contents']:
s3_object = s3_key['Key']
if s3_object not in exclude_file_names:
bucket.download_file(file_path, download_path + str(s3_object.split('/')[-1])
and still if you want to get the whole bucket use it via CLI as #John Rotenstein mentioned as below,
aws s3 cp --recursive s3://bucket_name download_path
for objs in my_bucket.objects.all():
print(objs.key)
path='/tmp/'+os.sep.join(objs.key.split(os.sep)[:-1])
try:
if not os.path.exists(path):
os.makedirs(path)
my_bucket.download_file(objs.key, '/tmp/'+objs.key)
except FileExistsError as fe:
print(objs.key+' exists')
This code will download the content in /tmp/ directory. If you want you can change the directory.
I got the similar requirement and got help from reading few of the above solutions and across other websites, I have came up with below script, Just wanted to share if it might help anyone.
from boto3.session import Session
import os
def sync_s3_folder(access_key_id,secret_access_key,bucket_name,folder,destination_path):
session = Session(aws_access_key_id=access_key_id,aws_secret_access_key=secret_access_key)
s3 = session.resource('s3')
your_bucket = s3.Bucket(bucket_name)
for s3_file in your_bucket.objects.all():
if folder in s3_file.key:
file=os.path.join(destination_path,s3_file.key.replace('/','\\'))
if not os.path.exists(os.path.dirname(file)):
os.makedirs(os.path.dirname(file))
your_bucket.download_file(s3_file.key,file)
sync_s3_folder(access_key_id,secret_access_key,bucket_name,folder,destination_path)
Reposting #glefait 's answer with an if condition at the end to avoid os error 20. The first key it gets is the folder name itself which cannot be written in the destination path.
def download_dir(client, resource, dist, local='/tmp', bucket='your_bucket'):
paginator = client.get_paginator('list_objects')
for result in paginator.paginate(Bucket=bucket, Delimiter='/', Prefix=dist):
if result.get('CommonPrefixes') is not None:
for subdir in result.get('CommonPrefixes'):
download_dir(client, resource, subdir.get('Prefix'), local, bucket)
for file in result.get('Contents', []):
print("Content: ",result)
dest_pathname = os.path.join(local, file.get('Key'))
print("Dest path: ",dest_pathname)
if not os.path.exists(os.path.dirname(dest_pathname)):
print("here last if")
os.makedirs(os.path.dirname(dest_pathname))
print("else file key: ", file.get('Key'))
if not file.get('Key') == dist:
print("Key not equal? ",file.get('Key'))
resource.meta.client.download_file(bucket, file.get('Key'), dest_pathname)enter code here
I have been running into this problem for a while and with all of the different forums I've been through I haven't see a full end-to-end snip-it of what works. So, I went ahead and took all the pieces (add some stuff on my own) and have created a full end-to-end S3 Downloader!
This will not only download files automatically but if the S3 files are in subdirectories, it will create them on the local storage. In my application's instance, I need to set permissions and owners so I have added that too (can be comment out if not needed).
This has been tested and works in a Docker environment (K8) but I have added the environmental variables in the script just in case you want to test/run it locally.
I hope this helps someone out in their quest of finding S3 Download automation. I also welcome any advice, info, etc. on how this can be better optimized if needed.
#!/usr/bin/python3
import gc
import logging
import os
import signal
import sys
import time
from datetime import datetime
import boto
from boto.exception import S3ResponseError
from pythonjsonlogger import jsonlogger
formatter = jsonlogger.JsonFormatter('%(message)%(levelname)%(name)%(asctime)%(filename)%(lineno)%(funcName)')
json_handler_out = logging.StreamHandler()
json_handler_out.setFormatter(formatter)
#Manual Testing Variables If Needed
#os.environ["DOWNLOAD_LOCATION_PATH"] = "some_path"
#os.environ["BUCKET_NAME"] = "some_bucket"
#os.environ["AWS_ACCESS_KEY"] = "some_access_key"
#os.environ["AWS_SECRET_KEY"] = "some_secret"
#os.environ["LOG_LEVEL_SELECTOR"] = "DEBUG, INFO, or ERROR"
#Setting Log Level Test
logger = logging.getLogger('json')
logger.addHandler(json_handler_out)
logger_levels = {
'ERROR' : logging.ERROR,
'INFO' : logging.INFO,
'DEBUG' : logging.DEBUG
}
logger_level_selector = os.environ["LOG_LEVEL_SELECTOR"]
logger.setLevel(logger_level_selector)
#Getting Date/Time
now = datetime.now()
logger.info("Current date and time : ")
logger.info(now.strftime("%Y-%m-%d %H:%M:%S"))
#Establishing S3 Variables and Download Location
download_location_path = os.environ["DOWNLOAD_LOCATION_PATH"]
bucket_name = os.environ["BUCKET_NAME"]
aws_access_key_id = os.environ["AWS_ACCESS_KEY"]
aws_access_secret_key = os.environ["AWS_SECRET_KEY"]
logger.debug("Bucket: %s" % bucket_name)
logger.debug("Key: %s" % aws_access_key_id)
logger.debug("Secret: %s" % aws_access_secret_key)
logger.debug("Download location path: %s" % download_location_path)
#Creating Download Directory
if not os.path.exists(download_location_path):
logger.info("Making download directory")
os.makedirs(download_location_path)
#Signal Hooks are fun
class GracefulKiller:
kill_now = False
def __init__(self):
signal.signal(signal.SIGINT, self.exit_gracefully)
signal.signal(signal.SIGTERM, self.exit_gracefully)
def exit_gracefully(self, signum, frame):
self.kill_now = True
#Downloading from S3 Bucket
def download_s3_bucket():
conn = boto.connect_s3(aws_access_key_id, aws_access_secret_key)
logger.debug("Connection established: ")
bucket = conn.get_bucket(bucket_name)
logger.debug("Bucket: %s" % str(bucket))
bucket_list = bucket.list()
# logger.info("Number of items to download: {0}".format(len(bucket_list)))
for s3_item in bucket_list:
key_string = str(s3_item.key)
logger.debug("S3 Bucket Item to download: %s" % key_string)
s3_path = download_location_path + "/" + key_string
logger.debug("Downloading to: %s" % s3_path)
local_dir = os.path.dirname(s3_path)
if not os.path.exists(local_dir):
logger.info("Local directory doesn't exist, creating it... %s" % local_dir)
os.makedirs(local_dir)
logger.info("Updating local directory permissions to %s" % local_dir)
#Comment or Uncomment Permissions based on Local Usage
os.chmod(local_dir, 0o775)
os.chown(local_dir, 60001, 60001)
logger.debug("Local directory for download: %s" % local_dir)
try:
logger.info("Downloading File: %s" % key_string)
s3_item.get_contents_to_filename(s3_path)
logger.info("Successfully downloaded File: %s" % s3_path)
#Updating Permissions
logger.info("Updating Permissions for %s" % str(s3_path))
#Comment or Uncomment Permissions based on Local Usage
os.chmod(s3_path, 0o664)
os.chown(s3_path, 60001, 60001)
except (OSError, S3ResponseError) as e:
logger.error("Fatal error in s3_item.get_contents_to_filename", exc_info=True)
# logger.error("Exception in file download from S3: {}".format(e))
continue
logger.info("Deleting %s from S3 Bucket" % str(s3_item.key))
s3_item.delete()
def main():
killer = GracefulKiller()
while not killer.kill_now:
logger.info("Checking for new files on S3 to download...")
download_s3_bucket()
logger.info("Done checking for new files, will check in 120s...")
gc.collect()
sys.stdout.flush()
time.sleep(120)
if __name__ == '__main__':
main()
There are very minor differences in the way S3 organizes files and the way Windows does.
Here is a simple self-documenting example that accounts for those differences.
Also: Think of amazon file names as a normal string. They don't really represent a folder. Amazon SIMULATES folders, so if you try to just shove a file into a NAME of a folder that doesn't exist on your system, it cannot figure out where to place it. So you must MAKE a folder on your system for each simulated folder from S3. If you have a folder within a folder, don't use "mkdir(path)" it won't work. You have to use "makedirs(path)". ANOTHER THING! -> PC file paths are weirdly formatted. Amazon uses "/" and pc uses "\" and it MUST be the same for the whole file name. Check out my code block below (WHICH SHOWS AUTHENTICATION TOO).
In my example, I have a folder in my bucket called "iTovenGUIImages/gui_media". I want to put it in a folder on my system that MAY not exist yet. The folder on my system has it's own special prefix that can be whatever you want in your system as long as it's formatted like a folder path.
import boto3
import cred
import os
locale_file_Imagedirectory = r"C:\\Temp\\App Data\\iToven AI\\" # This is where all GUI files for iToven AI exist on PC
def downloadImageDirectoryS3(remoteDirectoryName, desired_parent_folder):
my_bucket = 'itovenbucket'
s3_resource = boto3.resource('s3', aws_access_key_id=cred.AWSAccessKeyId,
aws_secret_access_key=cred.AWSSecretKey)
bucket = s3_resource.Bucket(my_bucket)
for obj in bucket.objects.filter(Prefix=remoteDirectoryName):
pcVersionPrefix = remoteDirectoryName.replace("/", r"\\")
isolatedFileName = obj.key.replace(remoteDirectoryName, "")
clientSideFileName = desired_parent_folder+pcVersionPrefix+isolatedFileName
print(clientSideFileName) # Client-Side System File Structure
if not os.path.exists(desired_parent_folder+pcVersionPrefix): # CREATE DIRECTORIES FOR EACH FOLDER RECURSIVELY
os.makedirs(desired_parent_folder+pcVersionPrefix)
if obj.key not in desired_parent_folder+pcVersionPrefix:
bucket.download_file(obj.key, clientSideFileName) # save to new path
downloadImageDirectoryS3(r"iTovenGUIImagesPC/gui_media/", locale_file_Imagedirectory)

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