Read the difference between boto3 session, client, and resource to understand its differences and when to use it. In this section, you’ll learn how to pass the credentials directly during the creation of the boto3 Session or boto3 client. Now, you can use it to access AWS resources.
You can use the % symbol before pip to install packages directly from the Jupyter notebook instead of launching the Anaconda Prompt. If you’ve not installed boto3 yet, you can install it by using the below snippet. This is necessary to create session with your AWS account. Generate the security credentials by clicking Your Profile Name -> My Security Credentials -> Access keys (access key ID and secret access key) option.In this tutorial, you’ll learn the different methods available to specify credentials when connecting to AWS services using boto3. If You Want to Understand Details, Read on…
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This is how you can specify credentials directly when creating a session to AWS S3. You can use the below code snippet to specify credentials when creating a boto3.Session. You can specify credentials in boto3 using session = boto3.Session(aws_access_key_id= '', aws_secret_access_key= '' ). You can interact with any AWS service using Boto3 when you’re programming with python if you have the access and the appropriate credentials.
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