Research and analysis of the technical principle of 'Saws' Library in Python

AWS (Amazon Network Services) is a world -leading cloud computing platform that provides rich cloud services, including solutions such as computing, storage, database, artificial intelligence, machine learning and the Internet of Things.AWS provides a series of libraries to call and manage AWS services in Python development. The research and analysis of the technical principles of AWS libraries is a process of in -depth research and analysis of the underlying mechanism and principles of these class libraries.The following will be briefly introduced by the commonly used AWS library technology principles, including code examples and related configuration descriptions. 1. Boto3 library BOTO3 is a software development tool package for AWS for Python, which is used to access and manage AWS services.Its technical principle is based on the RESTFUL API of AWS, providing a more convenient Python interface through encapsulation and expansion of API.The following is a sample code for visiting the AWS S3 service using Boto3: python import boto3 # Create S3 resource object s3 = boto3.resource('s3') # Create a new storage bucket s3.create_bucket(Bucket='my-bucket') # Upload file to the storage barrel s3.Object('my-bucket', 'example.txt').put(Body=open('example.txt', 'rb')) By creating the S3 resource object, we can call the correlation method for the creation, deletion, uploading of the barrels and files. 2. Dynamodb library Dynamodb is a high -performance, scalable NOSQL database service provided by AWS.Use the Dynamodb library to easily operate Dynamodb.The following is a sample code for creating tables and inserting data using Dynamodb library library: python import boto3 # Create Dynamodb resource object dynamodb = boto3.resource('dynamodb') # 创 创 创 table = dynamodb.create_table( TableName='my-table', KeySchema=[ { 'AttributeName': 'id', 'KeyType': 'HASH' } ], AttributeDefinitions=[ { 'AttributeName': 'id', 'AttributeType': 'N' } ], ProvisionedThroughput={ 'ReadCapacityUnits': 5, 'WriteCapacityUnits': 5 } ) # Insert data table.put_item( Item={ 'id': 1, 'name': 'John', 'age': 30 } ) By creating Dynamodb resource objects, we can use the corresponding method to create, delete, read and write data and other operations in the table. 3. Lambda class library Lambda is a server -free service provided by AWS, which can run code fragments customized by users.Use Lambda libraries to simplify interaction with the Lambda function.The following is a sample code that uses Lambda libraries to call the LAMBDA function: python import boto3 # B Lambda client object lambda_client = boto3.client('lambda') # Call the lambda function response = lambda_client.invoke( FunctionName='my-lambda-function', InvocationType='RequestResponse', Payload='{}' ) # Get the execution result of the lambda function result = response['Payload'].read().decode('utf-8') By creating the LAMBDA client object, we can call the correlation method to trigger and manage the lambda function, and obtain the execution result of the function. The above is a brief introduction and example code for the commonly used libraries of the AWS library technology.When using these class libraries, we need to configure the AWS management console, such as creating access keys, configuration IAM permissions, etc.At the same time, we can also carry out secondary development and expansion of these class libraries according to specific application needs to provide more flexible and customized functions.