Getting started with Boto3 is easy, but requires a few steps.
Prior to using Boto3, you need to install it and its dependencies.
Before installing Boto3, ensure that you're using an up-to-date version of Python. Unless you have specific reasons to use another version of Python, you should be using Python 3.7 or later. Boto3 support for Python 2.7 is deprecated and will end effective July 15, 2021. See Migrating from Python 2.7 to Python 3 for more details, including timeline information and guidance regarding how to transition to Python 3 if you haven't done so yet.
For more information on how to get the latest version of Python, please refer to the official Python documentation.
Before you can begin using Boto3, you should set up authentication credentials. Credentials for your AWS account can be found in the IAM Console. You can create or use an existing user. Go to manage access keys and generate a new set of keys.
If you have the AWS CLI installed, then you can use it to configure your credentials file:
aws configure
Alternatively, you can create the credential file yourself. By default, its location is at ~/.aws/credentials:
[default]
aws_access_key_id = YOUR_ACCESS_KEY
aws_secret_access_key = YOUR_SECRET_KEY
You may also want to set a default region. This can be done in the configuration file. By default, its location is at ~/.aws/config:
[default]
region=us-east-1
Alternatively, you can pass a region_name when creating clients and resources.
This sets up credentials for the default profile as well as a default region to use when creating connections. See Configuration for in-depth configuration sources and options.
To use Boto3, you must first import it and tell it what service you are going to use:
import boto3
# Let's use Amazon S3
s3 = boto3.resource('s3')
Now that you have an s3 resource, you can make requests and process responses from the service. The following uses the buckets collection to print out all bucket names:
# Print out bucket names
for bucket in s3.buckets.all():
print(bucket.name)
It's also easy to upload and download binary data. For example, the following uploads a new file to S3. It assumes that the bucket my-bucket already exists:
# 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.