Boto3 Resource vs Client – Do You Know the Difference?
Dear Reader, I hope you are doing well. As you know, Boto3 or AWS SDK for Python helps you to develop Python application that makes use of AWS services. There are mainly two ways or abstractions that boto3 provides you to be able to interact with AWS services and can you guess what they are?
Absolutely – they are Resource and Client
You can either use Resource or Client or both to interact with AWS services and you can achieve the same things by using any of these for example creating an s3 bucket. Hence it becomes really confusing on which one to use.
Today we are going to learn about the boto3 client and resource and figure out the difference between the two abstraction/interface.
Let’s discuss in detail about these so that it becomes easier to decide on which one to use among boto3 Client and Resource.
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Boto3 Resource vs Client – What’s the Difference between Boto3 Resource and Client?
Both Boto3 Resource and Client are the abstractions of Boto3 and more or less they can achieve the same task. The question then comes what both of these exist?
Why do we even need two and why not one?
What’s the purpose of one over the other or what criteria shall we think about before choosing one interface over the other for our requirement?
There must be some deeper details that make both of them unique and usable despite doing a similar job.
Let’s find out.
Boto3 Resource vs Client: Definition
Boto3 Client: Boto3 client is the low-level interface to AWS services that provides a direct mapping to the AWS API methods. You can use it to make direct API calls to the various AWS services and get the raw response as it is received from the service. The client is typically used when you need to call a specific AWS API, or when fine-grained control over the API parameters is required.
Boto3 Resource: Boto3 Resource on the other hand is a higher-level interface to AWS services that provides a simpler and more object-oriented way of interacting with them. It provides a set of methods that allows you to perform common operations on the AWS resources, such as creating or deleting a resource. The resource object is designed to abstract away the details of the AWS API and provide a more user-friendly interface.
Boto3 Resource vs Client: Example
Working with Boto3 resource:
While working with the resource interface, we import boto3 and create a service resource object. Then you can interact with the service using available methods and attributes.
for example – In the below example we have created an s3 service resource object and then use the buckets attribute of the s3 object to retrieve the list of all the S3 buckets in my AWS account. Then, I am looping through the list to print out the name of each bucket. As simple as that –
import boto3
# Create an S3 resource object
s3 = boto3.resource('s3')
# List of s3 buckets in the account
for bucket in s3.buckets.all():
print(bucket.name)
Working with Boto3 client:
While working with the client interface, we import boto3 and create a service client passing the service name you want to work with. After the client is created, you can interact with the service using the available methods of the client.
for example – In the below example we have created an s3 client and then used the method available to the client for example list_buckets to get the list of buckets for the account. After that, I am looping through the response to print out the name of each bucket. easy peasy?
import boto3
# Create an S3 client object
s3 = boto3.client('s3')
# List of s3 buckets in the account
response = s3.list_buckets()
for bucket in response['Buckets']:
print(bucket['Name'])
Boto3 Resource vs Client: Benefits
Let’s see the benefits of resource and client individually –
Benefits of Resource:
- Provides a more user-friendly and object-oriented way to work with AWS services.
- It Simplifies working with AWS by handling and hiding lots of underlying details
Benefits of Client:
- Provides fine-grained control over the input parameters and response
- Maps 1:1 with actual AWS APIs
- All API operations are supported
- Is lightweight compared to resource
Boto3 Resource vs Client: Performance
As a general rule of thumb, I would say, the client is more performant as it lets you interact with AWS API directly. When you use a client, you can call methods on the client object that map directly to the AWS APIs. And to say, those operations are mostly optimized for performance and efficiency, which means that client can provide better performance than resource.
On the other hand, resource provides a higher-level abstraction of AWS services that is more Pythonic and easier to use for someone who is already well-versed in the Python ecosystem. Even if it is less performant than a client, it can be easier to use as it abstracts away some of the complexity of the AWS API and provides a more natural way of working with AWS resources.
Boto3 Resource vs Client: Summary – Which one to Choose?
As we are here to summarise, both client and resource have their own pros and cons. Which one to choose among them depends on the use case and the level of control and performance required.
The best approach is to choose the interface that best suits your needs based on the specific use case. If you need fine-grained control over the AWS API and require maximum performance, client is likely the better choice. If you need a more Pythonic and higher-level interface and are willing to trade off some performance, resource may be the better choice.
Also one of the important points you can consider is Resource deprecation-
The Boto3 team has said that they will no longer add any new features to the resource interface, So we are bound to use the client for everything hereafter. You can still use the existing functionality if you want to but I feel a bit apprehensive using something that’s no longer supported or maintained.
Here are some more key parameters you on which boto3 resource and client can be differentiated:
Difference between Boto3 Resource and Client
| Resource Object | Client Object |
|---|---|
| Higher-level interface | Lower-level interface |
| Abstraction over AWS API | Maps 1:1 with AWS API |
| Easier to use, more object-oriented method calls | Fine-grained control over API parameters |
| Handles pagination for you | Needs you to handle pagination yourself |
| It is generated from an AWS resource description | it is generated from an AWS service description |
| Abstracts away details of AWS API | Direct calls to AWS services with appropriate parameters |
| Consistent API across different AWS services | Different API structures for different AWS services |
| Simplifies working with AWS services | Provides fine-grained control and flexibility |
| Suitable for common operations on AWS resources | Suitable for making specific API calls with specific parameters |
Conclusion
In this article on boto3 resource vs client, we discussed these two abstractions or ways boto3 provides us to be able to work with various AWS services.
We learned that the resource provides a higher-level, more abstracted interface to AWS services, while the client object provides a lower-level, more direct interface to the AWS API.
And when it comes to deciding which one to use, it really depends on the use case and what level of control we want while calling AWS API.
Last but not least we also talked about Resource deprecation and that they will not have any new features added to them. So it makes sense to think before using them.
Hope this post was useful to you. If so, don’t forget to tell me in the comment section.
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