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Python Sample for AWS Cloud9

This sample enables you to run some Python scripts in an AWS Cloud9 development environment.

Note

This sample assumes you already have the AWS Cloud9 IDE for your AWS Cloud9 development environment open in your web browser, and that you're using an AWS Cloud9 EC2 development environment that is connected to an Amazon EC2 instance running Amazon Linux. In you're using a different operating system or using an AWS Cloud9 SSH development environment, you might need to adapt this sample's instructions to correctly install and configure this sample's required tools. To create an environment, see Creating an Environment.

When you're using this sample, be sure you're signed in to AWS with the AWS account ID and name and password of the user you created or identified in Team Setup.

Creating this sample may result in charges to your AWS account. These include possible charges for services such as Amazon EC2 and Amazon S3. For more information, see Amazon EC2 Pricing and Amazon S3 Pricing.

Step 1: Install Required Tools

In this step, you install Python, which is required to run this sample.

  1. In a terminal session in the AWS Cloud9 IDE, confirm whether Python is already installed by running the python --version command. (To start a new terminal session, on the menu bar, choose Window, New Terminal.) If successful, the output contains the Python version number. If Python is installed, skip ahead to Step 2: Add Code.

  2. Run the yum update command to help ensure the latest security updates and bug fixes are installed.

    sudo yum -y update
  3. Install Python by running the install command.

    sudo yum -y install python27 # Installs Python 2.7.

    For more information, see Download Python on the Python website and Installing Packages in the Python Packaging User Guide.

Step 2: Add Code

In the AWS Cloud9 IDE, create a file with this 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))

Note

The preceding code doesn't rely on any custom Python modules or packages. However, if you ever import custom Python modules or packages, and you want AWS Cloud9 to use those modules or pacakges to do code completion as you type, turn on the Project, Python Support, Enable Python code completion setting in Preferences, and then add the paths to those modules or packages to the Project, Python Support, PYTHONPATH setting. (To view and change your preferences, choose AWS Cloud9, Preferences on the menu bar.)

Step 3: Run the Code

  1. In the AWS Cloud9 IDE, on the menu bar, choose Run, Run Configurations, New Run Configuration.

  2. On the [New] - Idle tab, choose Runner: Auto, and then choose Python.

    Note

    If Python isn't available, you can create a custom runner for Python.

    1. On the [New] - Idle tab, choose Runner: Auto, and then choose New Runner.

    2. On the My Runner.run tab, replace the tab's contents with this code.

      { "cmd" : ["python", "$file", "$args"], "info" : "Running $project_path$file_name...", "selector" : "source.py" }
    3. Choose File, Save As on the menu bar, and save the file as Python.run in the /.c9/runners folder.

    4. On the [New] - Idle tab, choose Runner: Auto, and then choose Python.

    5. Choose the hello.py tab to make it active.

  3. For Command, type hello.py 5 9. In the code, 5 represents sys.argv[1], and 9 represents sys.argv[2].

  4. Choose the Run button, and compare your output.

    Hello, World! The sum of 2 and 3 is 5. The sum of 5 and 9 is 14.

Step 4: Install and Configure the AWS SDK for Python (Boto)

You can enhance this sample to use the AWS SDK for Python (Boto) to create an Amazon S3 bucket, list your available buckets, and then delete the bucket you just created.

In this step, you install and configure the AWS SDK for Python (Boto), which provides a convenient way to interact with AWS services, such as Amazon S3, from your Python code. Before you can install the AWS SDK for Python (Boto), you must install pip. After you install the AWS SDK for Python (Boto), you must set up credentials management in your environment. The AWS SDK for Python (Boto) needs these credentials to interact with AWS services.

To install pip

  1. In the AWS Cloud9 IDE, confirm whether pip is already installed by running the pip --version command. If successful, the output contains the pip version number. Otherwise, an error message should be output. If pip is installed, skip ahead to the next procedure, To install the |sdk-python|.

  2. To install pip, run these commands, one at a time.

    curl -O https://bootstrap.pypa.io/get-pip.py # Get the install script. sudo python get-pip.py # Install pip. rm get-pip.py # Delete the install script.

    For more information, see pip Installation on the pip website.

To install the AWS SDK for Python (Boto)

After you install pip, use Python to run the pip install command.

sudo python -m pip install boto3

For more information, see the "Installation" section of Quickstart in the AWS SDK for Python Developer Guide.

To set up credentials management in your environment

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

In this step, you store your credentials within the environment. To do this, follow the instructions in Call AWS Services from an Environment, and then return to this topic.

For additional information, see Credentials in the AWS SDK for Python Developer Guide.

Step 5: Add AWS SDK Code

In this step, you add some more code, this time to interact with Amazon S3 to create a bucket, list your available buckets, and then delete the bucket you just created. You will run this code later.

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

import boto3 import sys import botocore s3 = boto3.client( 's3', region_name = 'YOUR_REGION' ) bucket_name = sys.argv[1] # Lists all of your available buckets in this AWS Region. def list_my_buckets(s3): resp = s3.list_buckets() print('My buckets now are:\n') for bucket in resp['Buckets']: print(bucket['Name']) return list_my_buckets(s3) # Create a new bucket. try: print("\nCreating a new bucket named '" + bucket_name + "'...\n") s3.create_bucket(Bucket = bucket_name) except botocore.exceptions.ClientError as e: if e.response['Error']['Code'] == 'BucketAlreadyExists': print("Cannot create the bucket. A bucket with the name '" + bucket_name + "' already exists. Exiting.") sys.exit() list_my_buckets(s3) # Delete the bucket you just created. print("\nDeleting the bucket named '" + bucket_name + "'...\n") s3.delete_bucket(Bucket = bucket_name) list_my_buckets(s3)

In the preceding code, replace YOUR_REGION with the ID of an AWS Region. For example, for the US East (Ohio) Region, use us-east-2. For more IDs, see Amazon Simple Storage Service (Amazon S3) in the Amazon Web Services General Reference.

Step 6: Run the AWS SDK Code

  1. On the menu bar, choose Run, Run Configurations, New Run Configuration.

  2. On the [New] - Idle tab, choose Runner: Auto, and then choose Python.

  3. For Command, type s3.py YOUR_BUCKET_NAME , where YOUR_BUCKET_NAME is the name of the bucket you want to create and then delete.

    Note

    Amazon S3 bucket names must be unique across AWS—not just your AWS account.

  4. Choose the Run button, and compare your output.

    My buckets now are: Creating a new bucket named 'my-test-bucket'... My buckets now are: my-test-bucket Deleting the bucket named 'my-test-bucket'... My buckets now are:

Step 7: Clean Up

To prevent ongoing charges to your AWS account after you're done using this sample, you should delete the environment. For instructions, see Deleting an Environment.