https://boto3.amazonaws.com/v1/documentation/api/latest/guide/quickstart.htmlboto3 安装pip install boto3 指定相应版本pip install boto3 The latest development version can always be found on GitHub.最新的开发版本
Configuration 配置
在开始使用Boto 3之前，应该设置身份验证凭据。您的AWS帐户的凭据可以在IAM控制台中找到。您可以创建或使用现有用户。转到管理访问键并生成一组新的键。
如果您已经安装了AWS CLI，那么您可以使用它来配置您的凭据文件:
aws configure
或者，您可以自己创建凭据文件。默认情况下，它的位置在 ~/.aws/credentials:
[default] aws_access_key_id = YOUR_ACCESS_KEY aws_secret_access_key = YOUR_SECRET_KEY
您可能还需要设置一个默认区域。这可以在配置文件中完成。默认情况下，它的位置在~/.aws/config:
[default] region=us-east-1 或者，您可以在创建客户机和资源时传递region_name。这将为创建连接时使用的默认配置文件和默认区域设置凭据。有关深入配置源和选项，请参见凭据。See Credentials
使用Boto 3
import boto3
s3 = boto3.resource('s3')#使用Amazon S3
现在您有了s3资源，就可以发出请求并处理来自服务的响应。下面使用bucket集合打印出所有桶名:
for bucket in s3.buckets.all():
print(bucket.name)
上传和下载二进制数据也很容易。例如，下面将一个新文件上传到S3。它假设bucket my-bucket已经存在:
# Upload a new file
data = open('test.jpg', 'rb')
s3.Bucket('my-bucket').put_object(Key='test.jpg', Body=data)
Resources and Collections will be covered in more detail in the following sections, so don't worry if you do not completely understand the examples.
资源和集合将在下面的部分中更详细地介绍，所以如果您没有完全理解这些示例，也不必担心。
A Sample Tutorial# 一个示例教程本教程将向您展示如何在AWS服务中使用Boto3。在本示例教程中，您将了解如何在Amazon Simple Queue Service (SQS)中使用Boto3This tutorial will show you how to use Boto3 with an AWS service. In this sample tutorial, you will learn how to use Boto3 with Amazon Simple Queue Service (SQS) SQS允许您排队，然后处理消息。本教程介绍如何创建新队列、获取和使用现有队列、将新消息推送到队列以及通过使用资源和集合处理来自队列的消息。SQS allows you to queue and then process messages. This tutorial covers how to create a new queue, get and use an existing queue, push new messages onto the queue, and process messages from the queue by using Resources and Collections. Creating a Queue创建一个队列 队列是用名称创建的。您还可以选择设置队列属性，例如在处理某项之前等待的秒数。下面的示例将使用队列名称测试。在创建队列之前，您必须首先获取SQS服务资源:
# Get the service resource
sqs = boto3.resource('sqs')
# Create the queue. This returns an SQS.Queue instance#创建队列。它返回一个SQS。队列实例
queue = sqs.create_queue(QueueName='test', Attributes={'DelaySeconds': '5'})
# You can now access identifiers and attributes
print(queue.url)
print(queue.attributes.get('DelaySeconds'))
Reference: SQS.ServiceResource.create_queue()
Warning
The code above may throw an exception if you already have a queue named test.
如果您已经有一个名为test的队列，那么上面的代码可能会抛出一个异常。
Using an Existing Queue# 使用现有队列
：可以根据队列的名称查找队列。如果队列不存在，则抛出异常:
# Get the service resource
sqs = boto3.resource('sqs')
# Get the queue. This returns an SQS.Queue instance
queue = sqs.get_queue_by_name(QueueName='test')
# You can now access identifiers and attributes
print(queue.url)
print(queue.attributes.get('DelaySeconds'))
It is also possible to list all of your existing queues:
#也可以列出所有现有的队列:
# Print out each queue name, which is part of its ARN#打印出每个队列名称，它是其ARN的一部分
for queue in sqs.queues.all():
print(queue.url)
Note
To get the name from a queue, you must use its ARN, which is available in the queue's attributesattribute.
要从队列中获取名称，必须使用它的ARN，该ARN在队列的attributes属性中可用。
Using queue.attributes['QueueArn'].split(':')[-1] will return its name.
Reference: SQS.ServiceResource.get_queue_by_name(), SQS.ServiceResource.queues
Sending Messages
发送消息将它添加到队列的末尾
# Get the service resource
sqs = boto3.resource('sqs')
# Get the queue
queue = sqs.get_queue_by_name(QueueName='test')
# Create a new message
response = queue.send_message(MessageBody='world')
# The response is NOT a resource, but gives you a message ID and MD5
print(response.get('MessageId'))
print(response.get('MD5OfMessageBody'))
You can also create messages with custom attributes:你可以创建带有自定义属性的消息
queue.send_message(MessageBody='boto3', MessageAttributes={
'Author': {
'StringValue': 'Daniel',
'DataType': 'String'
}
})消息也可以分批发送。例如，在一个请求中发送上面描述的两条消息如下所示:response = queue.send_messages(Entries=[
{
'Id': '1',
'MessageBody': 'world'
},
{
'Id': '2',
'MessageBody': 'boto3',
'MessageAttributes': {
'Author': {
'StringValue': 'Daniel',
'DataType': 'String'
}
}
}
])
# Print out any failures
print(response.get('Failed'))
在这种情况下，响应包含成功和失败消息的列表，因此如果需要，您可以重试失败。
In this case, the response contains lists of Successful and Failed messages, so you can retry failures if needed.
Reference: SQS.Queue.send_message(), SQS.Queue.send_messages()
Processing Messages 消息处理
Messages are processed in batches: 分批处理消息
# Get the service resource
sqs = boto3.resource('sqs')
# Get the queue
queue = sqs.get_queue_by_name(QueueName='test')
# Process messages by printing out body and optional author name#通过打印正文和可选作者名来处理消息
for message in queue.receive_messages(MessageAttributeNames=['Author']):
# Get the custom author message attribute if it was set#让队列知道消息已被处理
author_text = ''
if message.message_attributes is not None:
author_name = message.message_attributes.get('Author').get('StringValue')
if author_name:
author_text = ' ({0})'.format(author_name)
# Print out the body and author (if set)打印正文和作者(如果设置)
print('Hello, {0}!{1}'.format(message.body, author_text))
# Let the queue know that the message is processed 让队列知道消息已被处理
message.delete()
Given only the messages that were sent in a batch with SQS.Queue.send_messages() in the previous section, the above code will print out:
Hello, world! Hello, boto3! (Daniel)
Reference: SQS.Queue.receive_messages(), SQS.Message.delete()
Code Examples This section provides code examples that demonstrate common Amazon Web Services scenarios using the Amazon Web Services (AWS) SDK for Python.本节提供的代码示例演示了使用Python的Amazon Web Services (AWS) SDK的常见Amazon Web服务场景。
User Guides用户指南