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Amazon S3 Cookbook (n)

You're reading from   Amazon S3 Cookbook (n) Over 30 hands-on recipes that will get you up and running with Amazon Simple Storage Service (S3) efficiently

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Product type Paperback
Published in Aug 2015
Publisher Packt
ISBN-13 9781785280702
Length 280 pages
Edition 1st Edition
Languages
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Author (1):
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Naoya Hashimoto Naoya Hashimoto
Author Profile Icon Naoya Hashimoto
Naoya Hashimoto
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Table of Contents (14) Chapters Close

Preface 1. Managing Common Operations with AWS SDKs FREE CHAPTER 2. Hosting a Static Website on Amazon S3 Bucket 3. Calculating Cost with the AWS Simple Monthly Calculator 4. Deploying a Static Website with CloudFormation 5. Distributing Your Contents via CloudFront 6. Securing Resources with Bucket Policies and IAM 7. Sending Authenticated Requests with AWS SDKs 8. Protecting Data Using Server-side and Client-side Encryption 9. Enabling Cross-origin Resource Sharing 10. Managing Object Lifecycle to Lower the Cost 11. S3 Performance Optimization 12. Creating Triggers and Notifying S3 Events to Lambda Index

Learning AWS SDK for Python and basic S3 operations with sample code

This section introduces you about how to install AWS SDK for Python and how to create S3 buckets, put objects, get objects using the sample code, and explains how the sample code runs as well.

Getting ready

Boto, a Python interface, is offered by Amazon Web Services and all of its features work with Python 2.6 and 2.7. The next major version to support Python 3.3 is underway.

To get started with AWS SDK for Python (Boto), it is necessary to install the following on your development machine:

How to do it…

Proceed with the following steps to install the packages and run the sample application:

  1. Download the sample SDK application:
    $ git clone https://github.com/awslabs/aws-python-sample.git
    $ cd aws-python-sample/
    
  2. Run the sample application:
    $ python s3_sample.py
    

How it works…

The sample code works as shown in the following diagram; initiating the credentials to allow access to Amazon S3, creating a bucket in a region, putting and getting objects into the bucket, and then finally deleting the objects and the bucket.

How it works…

Now, let's run the sample application and see the output of the preceding command, as shown in the following screenshot, and then follow the source code step by step:

How it works…

Now, let's examine the sample code; the path is aws-python-sample/s3-sample.py.

The connect_s3 method creates a connection for accessing S3:

s3 = boto.connect_s3()

The create_bucket method creates an S3 bucket with the specified name defined as the bucket_name variable in the standard US region by default:

bucket_name = "python-sdk-sample-%s" % uuid.uuid4()
print "Creating new bucket with name: " + bucket_name
bucket = s3.create_bucket(bucket_name)

By creating a new key object, it stores new data in the bucket:

from boto.s3.key import Key 
k = Key(bucket)
k.key = 'python_sample_key.txt'

The delete method deletes all the objects in the bucket:

k.delete()

The delete_bucket method deletes the bucket:

bucket.s3.delete_bucket(bucket_name)

The whole sample code is as follows:

import boto
import uuid
s3 = boto.connect_s3()
bucket_name = "python-sdk-sample-%s" % uuid.uuid4()
print "Creating new bucket with name: " + bucket_name
bucket = s3.create_bucket(bucket_name)
from boto.s3.key import Key
k = Key(bucket)
k.key = 'python_sample_key.txt'
print "Uploading some data to " + bucket_name + " with key: " + k.key
k.set_contents_from_string('Hello World!')
expires_in_seconds = 1800
print "Generating a public URL for the object we just uploaded. This URL will be active for %d seconds" % expires_in_seconds
print
print k.generate_url(expires_in_seconds)
print
raw_input("Press enter to delete both the object and the bucket...")
print "Deleting the object."
k.delete()
print "Deleting the bucket."
s3.delete_bucket(bucket_name)

See also

You have been reading a chapter from
Amazon S3 Cookbook (n)
Published in: Aug 2015
Publisher: Packt
ISBN-13: 9781785280702
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