It is frequently necessary to create and manage cloud infrastructure with the aid of some programming language in addition to creating and managing it using the AWS console. To help with this, AWS provides SDKs for a variety of programming languages. One such Python SDK for AWS is Boto3, which makes it easier to create and manage AWS resources through code. We will learn how to use Boto3 to communicate with various AWS cloud services in this article.
Introduction to AWS Boto3 (SDK)
AWS Boto3 is a Python SDK that facilitates using Python code to interact with AWS services. It makes it simple to integrate Python programs with AWS cloud services like Amazon EC2, S3, IAM, Lambda, etc.
Boto3 was created with the Python programming language, which simplifies the process of calling AWS APIs with Python code.
- Levels of APIs: Client-level and Resource level APIs are the two levels offered by AWS Boto3. About AWS services, these APIs offer a low-level and a high level of abstraction respectively.
- Python 2 and 3 support: Python 2.7+ and 3.4+ versions are both natively supported by AWS Boto3, making it simple to integrate existing applications with Boto3.
- Waiters: Waiter is a feature of AWS Boto3 that enables you to wait for a resource's status and pause code execution until the status is returned. For instance, a waiter can delay code execution until an EC2 instance is running.
- Credentials Configuration: AWS Boto3 offers several options for setting up AWS credentials to communicate with an AWS account. The credentials may be passed to client or resource APIs, kept in the configuration files, or kept in environment variables.
To install and configure AWS Boto3 on your computer, follow these steps:
- Visit here to download and install Python for your operating system.
- Using the terminal's provided command, install Boto3 pip3 install boto3
- Boto3 requires valid AWS credentials to connect to your AWS account and interact with AWS services:
- Create a new file, /.aws/credentials
- Enter your AWS IAM user credentials and a valid AWS Region where you want to interact with AWS services into the file.
Levels of APIs
Client API and Resource API are the two levels of APIs offered by AWS Boto3 for interacting with AWS services.
Client API: A low-level interface to the AWS service is provided by Boto3 clients. The client-provided methods and the AWS service APIs correspond exactly. Clients enable API response interaction using the built-in dictionary format of Python. The methods offered by clients map exactly to the AWS service APIs.
The following code can be used to create an AWS Boto3 S3 Client:
Resource API: High-level abstraction is provided by resource APIs for AWS services. In contrast to clients, resources offer an object-oriented interface for communicating with AWS services. Resources also offer the option of specifying identifiers and attributes within a resource.
The following code can be used to create an AWS Boto3 S3 Resource:
S3 Bucket System Details
AWS Simple Storage Service (S3) is an object storage service where data can be stored in the object format. S3 has a concept of buckets that can be created within an AWS Region and objects can be then uploaded to the S3 bucket.
AWS S3 allows data to be organized using folder structure (home/scaler/topics), but internally S3 does not follow a filesystem hierarchy, rather it is a flat structure. To organize the data, prefixes, and delimiters can be used, thus imitating the folder structure.
Basic S3 Commands and Steps in AWS Boto3
The following commands can be used to interact with and manage an AWS S3 bucket using Boto3, presuming the AWS credentials have already been set up in the terminal:
- Creating a bucket: The create_bucket() method is used to create an S3 bucket:
- Upload an object: The upload_file() method is used to upload an object to an S3 bucket:
- List object in a bucket: The list_objects() method can be used to list all objects within an S3 bucket:
- Deleting a bucket: The delete_bucket() method is used to delete an S3 bucket:
- AWS Boto3 is a Python SDK that facilitates using Python code to interact with Amazon Web Services.
- It offers two levels of API access - Client and Resource - which offer a low-level and high-level level of abstraction for data and services.
- AWS Boto3's Waiters feature allows you to pause code execution until an EC2 instance is running. A waiter can be used to delay code execution while a resource's status is checked and its value is recorded.
- A low-level interface to the AWS service is provided by Boto3 clients. Clients enable API response interaction using the built-in dictionary format of Python. The methods offered by clients map exactly to the Amazon Web Services (AWS) service APIs.
- High-level abstraction is provided by resource APIs for Amazon Web Services (AWS) services. Resources offer an object-oriented interface for communicating with AWS services. Resources also offer the option of specifying identifiers and attributes within a resource.