Develop Reference

How do I get a download link for an object I upload to an AWS bucket?

I'm using AWS S3 boto3 to upload files to my AWS bucket called uploadtesting. Here is an example implementation:
import boto3
...
s3 = boto3.resource('s3')
s3.meta.client.upload_file('files/report.pdf', 'uploadtesting', 'report.pdf')
Accessing the object from the AWS S3 console allows you to see the object URL, however it is not a downloadable link. What I wanted to know is how can I use python to print out a downloadable link to the file I just uploaded?

It appears you are asking how to generate a URL that allows a private object to be downloaded.
This can be done by generating an Amazon S3 pre-signed URL, which provides access to a private S3 object for a limited time.
Basically, using credentials that have access to the object, you can create a URL that is 'signed'. When Amazon S3 receives this URL, it verifies the signature and provides access to the object if the expiry period has not ended.
From Presigned URLs — Boto3 documentation:
response = s3_client.generate_presigned_url('get_object',
Params={'Bucket': bucket_name,
'Key': object_name},
ExpiresIn=expiration)
The ExpiresIn parameter is expressed in seconds.

The format is:
https://BUCKET-NAME.s3.amazonaws.com/OBJECT-KEY
So your object would be:
https://uploadtesting.s3.amazonaws.com/report.pdf
There is no supplied function to generate this string, so use:
url = f'https://{bucket_name}.s3.amazonaws.com/{key}'

Problems Enabling S3 Bucket Transfer Acceleration Using boto3

I am attempting to pull information about an S3 bucket using boto3. Here is the setup (bucketname is set to a valid S3 bucket name):
import boto3
s3 = boto3.client('s3')
result = s3.get_bucket_acl(Bucket=bucketname)
When I try, I get this error:
ClientError: An error occurred (InvalidRequest) when calling the
GetBucketAcl operation: S3 Transfer Acceleration is not configured on
this bucket
So, I attempt to enable transfer acceleration:
s3.put_bucket_accelerate_configuration(Bucket=bucketname, AccelerateConfiguration={'Status': 'Enabled'})
But, I get this error, which seems silly, since the line above is attempting to configure the bucket. I do have IAM rights (Allow: *) to modify the bucket too:
ClientError: An error occurred (InvalidRequest) when calling the
PutBucketAccelerateConfiguration operation: S3 Transfer Acceleration
is not configured on this bucket
Does anyone have any ideas on what I'm missing here?

Although I borrowed the code in the original question from the boto3 documentation, this construct is not complete and did not provide the connectivity that I expected:
s3 = boto3.client('s3')
What is really needed are fully-initialized session and client handlers, like this (assuming that the profile variable is set correctly in the ~/.aws/config file and bucketname is a valid S3 bucket):
from boto3 import Session
session = Session(profile_name=profile)
client = session.client('s3')
result = client.get_bucket_acl(Bucket=bucketname)
After doing this (duh), I was able to connect with or without transfer acceleration.
Thanks to the commenters, since those comments led me to the solution.

AWS S3 upload boto status

I am using Flask and Boto with AWS S3 to upload files. I would like to know the progress so I can show it to the user.
I am boto.s3client and
s3.put_object(Body=body, Bucket= BUCKET_NAME, Key=key, ContentType='image/png')
For example.
How can I know the progress of uploading?

How to execute bash commands in aws lambda

I am trying to schedule a job in AWS lambda where i get data fromm a Json API. I want to transfer JSON file to amazon S3 everytime.I have set up S3 bucket and aws lambda function with proper IAM roles. I am writing AWS lambda function in Python. Code works fine on an EC2 instance but It's not transferring file to S3 if I put it in AWS Lambda.
import os
def lambda_handler(event, context):
#changing the directory to /tmp
os.chdir("/tmp")
print "loading function"
#downloading file to
os.system("wget https://jsonplaceholder.typicode.com/posts/1 -P /tmp")
#using aws-cli to transfer file to amazon S3
os.system("aws s3 sync . s3://targetbucket")
I am new to aws lambda. I am not getting any error but it's not giving me expected output

AWS Lambda does not have the aws cli by default.
You can either Create a deployment package with awscli in it or Use python boto3 library.
import boto3
s3client = boto3.client('s3')
for filename in os.listdir('/tmp'): # assuming there will not be any sub-directories
fpath = os.path.join('/tmp',filename)
if os.path.isfile(fpath):
s3client.upload_file(fpath, 'targetbucket', filename)

Python Boto3 AWS Multipart Upload Syntax

I am successfully authenticating with AWS and using the 'put_object' method on the Bucket object to upload a file. Now I want to use the multipart API to accomplish this for large files. I found the accepted answer in this question:
How to save S3 object to a file using boto3
But when trying to implement I am getting "unknown method" errors. What am I doing wrong? My code is below. Thanks!
## Get an AWS Session
self.awsSession = Session(aws_access_key_id=accessKey,
aws_secret_access_key=secretKey,
aws_session_token=session_token,
region_name=region_type)
...
# Upload the file to S3
s3 = self.awsSession.resource('s3')
s3.Bucket('prodbucket').put_object(Key=fileToUpload, Body=data) # WORKS
#s3.Bucket('prodbucket').upload_file(dataFileName, 'prodbucket', fileToUpload) # DOESNT WORK
#s3.upload_file(dataFileName, 'prodbucket', fileToUpload) # DOESNT WORK

The upload_file method has not been ported over to the bucket resource yet. For now you'll need to use the client object directly to do this:
client = self.awsSession.client('s3')
client.upload_file(...)

Libcloud S3 wrapper transparently handles all the splitting and uploading of the parts for you.
Use upload_object_via_stream method to do so:
from libcloud.storage.types import Provider
from libcloud.storage.providers import get_driver
# Path to a very large file you want to upload
FILE_PATH = '/home/user/myfile.tar.gz'
cls = get_driver(Provider.S3)
driver = cls('api key', 'api secret key')
container = driver.get_container(container_name='my-backups-12345')
# This method blocks until all the parts have been uploaded.
extra = {'content_type': 'application/octet-stream'}
with open(FILE_PATH, 'rb') as iterator:
obj = driver.upload_object_via_stream(iterator=iterator,
container=container,
object_name='backup.tar.gz',
extra=extra)
For official documentation on S3 Multipart feature, refer to AWS Official Blog.