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Python tutorial for AWS Cloud9

This tutorial shows you how to run Python code in an AWS Cloud9 development environment.

Following this tutorial might result in charges to your AWS account. These include possible charges for services such as Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Simple Storage Service (Amazon S3). For more information, see Amazon EC2 Pricing and Amazon S3 Pricing.

Prerequisites

Before you use this tutorial, be sure to meet the following requirements.

Step 1: Install Python

Step 2: Add code

In the AWS Cloud9 IDE, create a file with the following content and save the file with the name hello.py. (To create a file, on the menu bar choose File, New File. To save the file, choose File, Save.)

import sys

print('Hello, World!')

print('The sum of 2 and 3 is 5.')

sum = int(sys.argv[1]) + int(sys.argv[2])

print('The sum of {0} and {1} is {2}.'.format(sys.argv[1], sys.argv[2], sum))

Step 3: Run the code

Step 4: Install and configure the AWS SDK for Python (Boto3)

The AWS SDK for Python (Boto3) enables you to use Python code to interact with AWS services like Amazon S3. For example, you can use the SDK to create an Amazon S3 bucket, list your available buckets, and then delete the bucket you just created.

Install pip

In the AWS Cloud9 IDE, confirm whether pip is already installed for the active version of Python by running the python -m pip --version command. If pip is installed, skip to the next section.

To install pip, run the following commands. Because sudo is in a different environment from your user, you must specify the version of Python to use if it differs from the current aliased version.

curl -O https://bootstrap.pypa.io/get-pip.py # Get the install script.
sudo python3 get-pip.py                     # Install pip for Python 3.
python -m pip --version                      # Verify pip is installed.
rm get-pip.py                                # Delete the install script.

For more information, see Installation on the pip website.

Install the AWS SDK for Python (Boto3)

After you install pip, install the AWS SDK for Python (Boto3) by running the pip install command.

sudo python3 -m pip install boto3  # Install boto3 for Python 3.
python -m pip show boto3            # Verify boto3 is installed for the current version of Python.

For more information, see the "Installation" section of Quickstart in the AWS SDK for Python (Boto3).

Set up credentials in your environment

Each time you use the AWS SDK for Python (Boto3) to call an AWS service, you must provide a set of credentials with the call. These credentials determine whether the SDK has the necessary permissions to make the call. If the credentials don't cover the necessary permissions, the call fails.

To store your credentials within the environment, follow the instructions in Calling AWS services from an environment in AWS Cloud9, and then return to this topic.

For additional information, see Credentials in the AWS SDK for Python (Boto3).

Step 5: Add AWS SDK code

Add code that uses Amazon S3 to create a bucket, list your available buckets, and optionally delete the bucket you just created.

In the AWS Cloud9 IDE, create a file with the following content and save the file with the name s3.py.

import sys
import boto3
from botocore.exceptions import ClientError


def list_my_buckets(s3_resource):
    print("Buckets:\n\t", *[b.name for b in s3_resource.buckets.all()], sep="\n\t")


def create_and_delete_my_bucket(s3_resource, bucket_name, keep_bucket):
    list_my_buckets(s3_resource)

    try:
        print("\nCreating new bucket:", bucket_name)
        bucket = s3_resource.create_bucket(
            Bucket=bucket_name,
            CreateBucketConfiguration={
                "LocationConstraint": s3_resource.meta.client.meta.region_name
            },
        )
    except ClientError as e:
        print(
            f"Couldn't create a bucket for the demo. Here's why: "
            f"{e.response['Error']['Message']}"
        )
        raise

    bucket.wait_until_exists()
    list_my_buckets(s3_resource)

    if not keep_bucket:
        print("\nDeleting bucket:", bucket.name)
        bucket.delete()

        bucket.wait_until_not_exists()
        list_my_buckets(s3_resource)
    else:
        print("\nKeeping bucket:", bucket.name)


def main():
    import argparse

    parser = argparse.ArgumentParser()
    parser.add_argument("bucket_name", help="The name of the bucket to create.")
    parser.add_argument("region", help="The region in which to create your bucket.")
    parser.add_argument(
        "--keep_bucket",
        help="Keeps the created bucket. When not "
        "specified, the bucket is deleted "
        "at the end of the demo.",
        action="store_true",
    )

    args = parser.parse_args()
    s3_resource = (
        boto3.resource("s3", region_name=args.region)
        if args.region
        else boto3.resource("s3")
    )
    try:
        create_and_delete_my_bucket(s3_resource, args.bucket_name, args.keep_bucket)
    except ClientError:
        print("Exiting the demo.")


if __name__ == "__main__":
    main()

Step 6: Run the AWS SDK code

Step 7: Clean up

To prevent ongoing charges to your AWS account after you're done with this tutorial, delete the AWS Cloud9 environment. For instructions, see Deleting an environment in AWS Cloud9.