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连接到boto3 S3时如何指定凭据？

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问题：连接到boto3 S3时如何指定凭据？
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回答 1
回答 2
回答 3
回答 4

问题：连接到boto3 S3时如何指定凭据？

在boto上，当以这种方式连接到S3时，我通常指定我的凭据：

import boto
from boto.s3.connection import Key, S3Connection
S3 = S3Connection( settings.AWS_SERVER_PUBLIC_KEY, settings.AWS_SERVER_SECRET_KEY )

然后，我可以使用S3执行操作（在我的情况下，从存储桶中删除对象）。

使用boto3，我发现的所有示例都是这样的：

import boto3
S3 = boto3.resource( 's3' )
S3.Object( bucket_name, key_name ).delete()

我无法指定我的凭据，因此所有尝试均因InvalidAccessKeyId错误而失败。

如何使用boto3指定凭据？

点击查看英文原文

On boto I used to specify my credentials when connecting to S3 in such a way:

import boto
from boto.s3.connection import Key, S3Connection
S3 = S3Connection( settings.AWS_SERVER_PUBLIC_KEY, settings.AWS_SERVER_SECRET_KEY )

I could then use S3 to perform my operations (in my case deleting an object from a bucket).

With boto3 all the examples I found are such:

import boto3
S3 = boto3.resource( 's3' )
S3.Object( bucket_name, key_name ).delete()

I couldn’t specify my credentials and thus all attempts fail with InvalidAccessKeyId error.

How can I specify credentials with boto3?

回答 0

您可以创建一个会话：

import boto3
session = boto3.Session(
    aws_access_key_id=settings.AWS_SERVER_PUBLIC_KEY,
    aws_secret_access_key=settings.AWS_SERVER_SECRET_KEY,
)

然后使用该会话获取S3资源：

s3 = session.resource('s3')
点击查看英文原文

You can create a session:

import boto3
session = boto3.Session(
    aws_access_key_id=settings.AWS_SERVER_PUBLIC_KEY,
    aws_secret_access_key=settings.AWS_SERVER_SECRET_KEY,
)

Then use that session to get an S3 resource:

s3 = session.resource('s3')

回答 1

您可以client像下面这样直接获得一个新会话。

 s3_client = boto3.client('s3', 
                      aws_access_key_id=settings.AWS_SERVER_PUBLIC_KEY, 
                      aws_secret_access_key=settings.AWS_SERVER_SECRET_KEY, 
                      region_name=REGION_NAME
                      )
点击查看英文原文

You can get a client with new session directly like below. 

 s3_client = boto3.client('s3', 
                      aws_access_key_id=settings.AWS_SERVER_PUBLIC_KEY, 
                      aws_secret_access_key=settings.AWS_SERVER_SECRET_KEY, 
                      region_name=REGION_NAME
                      )

回答 2

这是旧的，但也将其放在这里供我参考。boto3.resource只是实现默认的Session，可以通过boto3.resource会话详细信息。

Help on function resource in module boto3:

resource(*args, **kwargs)
    Create a resource service client by name using the default session.

    See :py:meth:`boto3.session.Session.resource`.

https://github.com/boto/boto3/blob/86392b5ca26da57ce6a776365a52d3cab8487d60/boto3/session.py#L265

您会看到它只接受与Boto3.Session相同的参数

import boto3
S3 = boto3.resource('s3', region_name='us-west-2', aws_access_key_id=settings.AWS_SERVER_PUBLIC_KEY, aws_secret_access_key=settings.AWS_SERVER_SECRET_KEY)
S3.Object( bucket_name, key_name ).delete()
点击查看英文原文

This is older but placing this here for my reference too. boto3.resource is just implementing the default Session, you can pass through boto3.resource session details.

Help on function resource in module boto3:

resource(*args, **kwargs)
    Create a resource service client by name using the default session.

    See :py:meth:`boto3.session.Session.resource`.

https://github.com/boto/boto3/blob/86392b5ca26da57ce6a776365a52d3cab8487d60/boto3/session.py#L265

you can see that it just takes the same arguments as Boto3.Session

import boto3
S3 = boto3.resource('s3', region_name='us-west-2', aws_access_key_id=settings.AWS_SERVER_PUBLIC_KEY, aws_secret_access_key=settings.AWS_SERVER_SECRET_KEY)
S3.Object( bucket_name, key_name ).delete()

回答 3

我想扩展@JustAGuy的答案。我更喜欢使用的方法是AWS CLI创建配置文件。原因是使用配置文件时，CLI或SDK会自动在~/.aws文件夹中查找凭据。好AWS CLI是用python编写的。

如果还没有，可以从pypi获取cli。这是从终端获取CLI的步骤

$> pip install awscli  #can add user flag 
$> aws configure
AWS Access Key ID [****************ABCD]:[enter your key here]
AWS Secret Access Key [****************xyz]:[enter your secret key here]
Default region name [us-west-2]:[enter your region here]
Default output format [None]:

之后，您boto无需指定键即可访问和任何api（除非您想使用其他凭据）。

点击查看英文原文

I’d like expand on @JustAGuy’s answer. The method I prefer is to use AWS CLI to create a config file. The reason is, with the config file, the CLI or the SDK will automatically look for credentials in the ~/.aws folder. And the good thing is that AWS CLI is written in python.

You can get cli from pypi if you don’t have it already. Here are the steps to get cli set up from terminal

$> pip install awscli  #can add user flag 
$> aws configure
AWS Access Key ID [****************ABCD]:[enter your key here]
AWS Secret Access Key [****************xyz]:[enter your secret key here]
Default region name [us-west-2]:[enter your region here]
Default output format [None]:

After this you can access boto and any of the api without having to specify keys (unless you want to use a different credentials).

回答 4

在仍然使用boto3.resource（）的情况下，有多种存储凭证的方法。我自己在使用AWS CLI方法。完美运作。

https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html?fbclid=IwAR2LlrS4O2gYH6xAF4QDVIH2Q2tzfF_VZ6loM3XfXsPAOR4qA-pX_qAILys

点击查看英文原文

There are numerous ways to store credentials while still using boto3.resource(). I’m using the AWS CLI method myself. It works perfectly.

https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html?fbclid=IwAR2LlrS4O2gYH6xAF4QDVIH2Q2tzfF_VZ6loM3XfXsPAOR4qA-pX_qAILys