Chapter 2. Creating an S3 client

Procedure

1. From the OpenShift AI dashboard, click Data science projects.
2. Click the name of the project that contains the workbench.
3. Click the Workbenches tab.

4. If the status of the workbench is Running, skip to the next step.

   If the status of the workbench is Stopped, in the Status column for the workbench, click Start.

   The Status column changes from Stopped to Starting when the workbench server is starting, and then to Running when the workbench has successfully started.

5. Click the open icon ( ) next to the workbench.

   Your Jupyter environment window opens.

6. On the toolbar, click the Git Clone icon and then select Clone a Repository.
7. In the Clone a repo dialog, enter the following URL https://github.com/opendatahub-io/odh-doc-examples.git and then click Clone.
8. In the file browser, select the newly-created odh-doc-examples folder.

9. Double-click the newly created storage folder.

   You see a Jupyter notebook named s3client_examples.ipynb.

10. Double-click the s3client_examples.ipynb file to launch the Jupyter notebook.

    The Jupyter notebook opens. You see code examples for the following tasks:

    • Installing Boto3 and required Boto3 libraries
    • Creating an S3 client session
    • Creating an S3 client connection
    • Listing files
    • Creating a bucket
    • Uploading a file to a bucket
    • Downloading a file from a bucket
    • Copying files between buckets
    • Deleting an object from a bucket
    • Deleting a bucket

11. In the Jupyter notebook, locate the following instructions to install Boto3 and its required libraries, and run the code cell:

    #Upgrade pip to the latest version
    !pip3 install --upgrade pip
    
    #Install Boto3
    !pip3 install boto3
    
    #Install Boto3 libraries
    import os
    import boto3
    from botocore.client import Config
    from boto3 import session
    
    #Check Boto3 version
    !pip3 show boto3

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    The instructions in the code cell update the Python Package Manager (pip) to the latest version, install Boto3 and its required libraries, and display the version of Boto3 installed.

12. Locate the following instructions to create an S3 client and session. Run the code cell.

    #Creating an S3 client
    #Define credentials
    key_id = os.environ.get('AWS_ACCESS_KEY_ID')
    secret_key = os.environ.get('AWS_SECRET_ACCESS_KEY')
    endpoint = os.environ.get('AWS_S3_ENDPOINT')
    region = os.environ.get('AWS_DEFAULT_REGION')
    
    #Define client session
    session = Boto3.session.Session(aws_access_key_id=key_id,
    aws_secret_access_key=secret_key)
    
    #Define client connection
    s3_client = Boto3.client('s3', aws_access_key_id=key_id,
    aws_secret_access_key=secret_key,aws_session_token=None,
        config=Boto3.session.Config(signature_version='s3v4'),
                            endpoint_url=endpoint,
                            region_name=region)

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    The instructions in the code cell configure an S3 client and establish a session to your S3-compatible object store.