Aws lambda python requests

Upcoming changes to the Python SDK in AWS Lambda

In response to customer feedback, we have decided to cancel the change described in this blog post. The version of the AWS SDK included in the AWS Lambda runtimes for Python 2.7, Python 3.6 and Python 3.7 will continue to include the ‘requests’ module in Botocore. No action is required for customers using these runtimes. The Lambda runtimes for Python 3.8 and later do not include the ‘requests’ module. Customers using ‘requests’ with these runtimes should package the ‘requests’ module with their function code or as a Lambda layer.

Update (November 11, 2021):

The deprecation date for the Lambda service to bundle the requests module in the AWS SDK is now March 31, 2022.

Update (March 29, 2021):

The deprecation date for the Lambda service to bundle the requests module in the AWS SDK is now December 1, 2021.

Update (January 19, 2021):

The deprecation date for the Lambda service to bundle the requests module in the AWS SDK is now March 31, 2021.

Update (November 23, 2020):

For customers using inline code in AWS CloudFormation templates that include the cfn-response module, we have recently removed this module’s dependency on botocore.requests. Customers will need to update their Lambda function to attach the updated cfn-response module. Change the Python version or trigger an update to the function code to attach the updated modules.

Update (March 10, 2020):

The deprecation date for the Lambda service to bundle the requests module in the AWS SDK is now January 30, 2021.

This blog post describes an upcoming change to the AWS SDK that affects Python developers using the requests module in Botocore. This post explains why the changes are happening, and describes what Python developers must do to continue using the requests library.

Please note that this change affects the Python 2.7, Python 3.6 and Python 3.7 runtimes. The Python 3.8 runtime is not affected.

The upcoming changes to AWS SDK

Botocore is a low-level interface to many services in the AWS Cloud. The package is the foundation for the AWS CLI and also Boto3, which is the AWS SDK for Python. In August 2018, Botocore was refactored to allow pluggable HTTP clients.

One of the main changes is that the requests library was replaced with urllib3. Additionally, the requests dependency was also unvendored, meaning Botocore can now support a range of versions of urllib3, instead of relying on a specific version. From version 1.13.0, the requests module is no longer part of the AWS SDK for Python. These changes create additional flexibility for Python developers, and can result in performance improvements for applications using Botocore.

Although the SDK has removed the requests module, the Lambda service continues to bundle the requests module in the AWS SDK until January 30, 2021. This is so builders have additional time to decide on the best course of action for their Python Lambda functions that rely on the requests module.

Best practices for using the AWS SDK

For convenience, the Lambda service includes the AWS SDK in its execution environment. This allows Lambda console users to easily use the SDK functionality within the integrated code window. It also allows Lambda to interoperate with the growing number of AWS services and features released to customers.

The best practice for Lambda development is to bundle all dependencies used by your Lambda function, including the AWS SDK. By doing this, your code uses the bundled version and is not affected when the version in the execution environment is upgraded. This is preferable to using the included version of the SDK, since this version can change, and in rare cases might affect compatibility with your code.

If you are currently bundling the SDK version in your Lambda version, you do not need to take any further action. Your code continues to use the bundled version and the upcoming changes do not affect you.

Importing the requests module directly into your code

If you are using the AWS SDK in the Lambda execution environment and do not want to bundle a version into your zipped deployment package, you have a couple of additional options.

First, you can install the requests module into your Python environment and import the module directly. Currently, you may be importing the library from Botocore in your Lambda function using this code:

from botocore.vendored import requests

First, to install the requests module, enter the following in a terminal window:

After the installation, update the import statement in your code as shown below:

This updates your dependency from the Botocore vendored version to a locally packaged version of the module. As a result, your code is unaffected after the requests module is no longer available via the AWS SDK in the execution environment.

Using AWS Lambda layers

AWS has also published Lambda layers containing version 1.12.221 of the AWS SDK, which includes the requests module in Botocore. To use this, first identify the layer ARN you need, using the Python runtime version and AWS Region.

Using this method, you do not need to change the code in the Lambda function. With the layer attached to the function, you can continue to use the requests module with:

from botocore.vendored import requests

To add this layer to your function in the Lambda console:

1. Select your function from the Functions list.
2. Locate the function’s ARN near the top of the display. In the ARN, note the AWS Region code after arn:aws:lambda: . In the Function code panel, note the Python version in the Runtime dropdown.
3. Using both the AWS Region code and Python version, find the ARN from the lists below. For Python versions 2.7, 3.6 and 3.7, locate the layer ARN for your Region:
   

   Region	ARN
   ap-northeast-1	arn:aws:lambda:ap-northeast-1:249908578461:layer:AWSLambda-Python-AWS-SDK:4
   us-east-1	arn:aws:lambda:us-east-1:668099181075:layer:AWSLambda-Python-AWS-SDK:4
   ap-southeast-1	arn:aws:lambda:ap-southeast-1:468957933125:layer:AWSLambda-Python-AWS-SDK:4
   eu-west-1	arn:aws:lambda:eu-west-1:399891621064:layer:AWSLambda-Python-AWS-SDK:4
   us-west-1	arn:aws:lambda:us-west-1:325793726646:layer:AWSLambda-Python-AWS-SDK:4
   ap-east-1	arn:aws:lambda:ap-east-1:118857876118:layer:AWSLambda-Python-AWS-SDK:4
   ap-northeast-2	arn:aws:lambda:ap-northeast-2:296580773974:layer:AWSLambda-Python-AWS-SDK:4
   ap-northeast-3	arn:aws:lambda:ap-northeast-3:961244031340:layer:AWSLambda-Python-AWS-SDK:4
   ap-south-1	arn:aws:lambda:ap-south-1:631267018583:layer:AWSLambda-Python-AWS-SDK:4
   ap-southeast-2	arn:aws:lambda:ap-southeast-2:817496625479:layer:AWSLambda-Python-AWS-SDK:4
   ca-central-1	arn:aws:lambda:ca-central-1:778625758767:layer:AWSLambda-Python-AWS-SDK:4
   eu-central-1	arn:aws:lambda:eu-central-1:292169987271:layer:AWSLambda-Python-AWS-SDK:4
   eu-north-1	arn:aws:lambda:eu-north-1:642425348156:layer:AWSLambda-Python-AWS-SDK:4
   eu-west-2	arn:aws:lambda:eu-west-2:142628438157:layer:AWSLambda-Python-AWS-SDK:4
   eu-west-3	arn:aws:lambda:eu-west-3:959311844005:layer:AWSLambda-Python-AWS-SDK:4
   sa-east-1	arn:aws:lambda:sa-east-1:640010853179:layer:AWSLambda-Python-AWS-SDK:4
   us-east-2	arn:aws:lambda:us-east-2:259788987135:layer:AWSLambda-Python-AWS-SDK:4
   us-west-2	arn:aws:lambda:us-west-2:420165488524:layer:AWSLambda-Python-AWS-SDK:5
   cn-north-1	arn:aws-cn:lambda:cn-north-1:683298794825:layer:AWSLambda-Python-AWS-SDK:4
   cn-northwest-1	arn:aws-cn:lambda:cn-northwest-1:382066503313:layer:AWSLambda-Python-AWS-SDK:4
   us-gov-west	arn:aws-us-gov:lambda:us-gov-west-1:556739011827:layer:AWSLambda-Python-AWS-SDK:4
   us-gov-east	arn:aws-us-gov:lambda:us-gov-east-1:138526772879:layer:AWSLambda-Python-AWS-SDK:4

   In this example, using Python 3.6 in us-west-2, the layer ARN is arn:aws:lambda:us-west-2:420165488524:layer:AWSLambda-Python-AWS-SDK:5 .

4. Select the Layers view in the Designer panel, then choose Add a layer.
5. Select the Provide a layer version ARN option, and then paste the relevant ARN from the list above into the Layer version ARN field. Choose Add.

The Lambda function is now using the layer.

Alternatively, you can use the CLI to add a Lambda Layer to your existing Lambda function. To do this, first identify the correct layer ARN using the procedure above. Next, execute the following command from a terminal window, replacing the layer parameter with the ARN:

aws lambda update-function-configuration --function-name yourFunctionName --layers arn:aws:lambda:xxxxxxxxxxxxxxxxxxxx

If you are using the AWS Serverless Application Model, you can add the layer to an existing function using the following YAML in the SAM template, replacing arn with the ARN:

To learn more, see our documentation describing how to add layers to Lambda functions.

Conclusion

The change to Botocore helps improve flexibility and performance for the AWS SDK. If you are bundling a fixed AWS SDK version with your Python version, you do not need to take any action. If you are using the AWS SDK included in the execution environment and want to continue using the requests module, you can include the Lambda Layer with the appropriate AWS SDK version, or include the requests module directly in your application package.

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How to use requests module in AWS Lambda

Python requests library is by default not avaialble in AWS Lambda Python environments. For using requests library in Lambda function a Lambda Layer needs to attached to the Lambda function. This tutorials lists the required steps for creating and attaching Lambda Layer for requests module.

Step 1: Create Python Virtual Environment

Step 2: Activate Virtual Environment

 # [On Ubuntu] source test_venv/bin/activate # [On Windows] .\test_venv\Scripts\activate 

Step 3: Check Python Version

Step 4: Create directory with name python

Step 5: Install requests package in python directory created in Step 4

 pip install requests -t python 

Step 6: Zip python directory

 # [On Ubuntu] zip -r requests.zip python # [On Windows] powershell Compress-Archive python requests.zip 

Step 7: Login to AWS account and Navigate to AWS Lambda Service.

Step 8: In AWS Lambda select Layers from Additional resources.

Step 9: Click on create layer, enter the required information.

• Name: requests_layer
• Description: Lambda layer for requests module
• Select Upload a .zip file, click on upload and choose requests.zip created in Step 6
• Compatible runtimes — Choose run time as per the python version from output of Step 3

Step 10: Click on Create

Step 11: Navigate to AWS Lambda function and select Functions

Step 12: Click on Create function

Step 13: Select Author from scratch

Step 14: Enter Below details in Basic information

• Function name: test_lambda_function
• Runtime: choose run time as per the python version from output of Step 3

Step 15: Click on create function

Step 16: In the Function overview pane click on Layers or Scroll down to select Layers section

Step 17: Click on Add a layer

Step 18: Select Custom layers , choose layer created in Step 9, select version 1 and click on Add.

Step 19: Write below code in lambda function and click on Deploy

 import json import logging import requests logger = logging.getLogger() logger.setLevel(logging.INFO) def lambda_handler(event, context): logger.info(requests.__version__) 

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Building Lambda functions with Python

You can run Python code in AWS Lambda. Lambda provides runtimes for Python that run your code to process events. Your code runs in an environment that includes the SDK for Python (Boto3), with credentials from an AWS Identity and Access Management (IAM) role that you manage.

Lambda supports the following Python runtimes.

The runtime information in this table undergoes continuous updates. For more information on using AWS SDKs in Lambda, see Managing AWS SDKs in Lambda functions in Serverless Land.

To create a Python function

• Function name: Enter a name for the function.
• Runtime: Choose Python 3.10.

The console creates a Lambda function with a single source file named lambda_function . You can edit this file and add more files in the built-in code editor. To save your changes, choose Save. Then, to run your code, choose Test.

Note

The Lambda console uses AWS Cloud9 to provide an integrated development environment in the browser. You can also use AWS Cloud9 to develop Lambda functions in your own environment. For more information, see Working with AWS Lambda functions using the AWS Toolkit in the AWS Cloud9 user guide.

Note

To get started with application development in your local environment, deploy one of the sample applications available in this guide’s GitHub repository.

Sample Lambda applications in Python

• blank-python – A Python function that shows the use of logging, environment variables, AWS X-Ray tracing, layers, unit tests and the AWS SDK.

Your Lambda function comes with a CloudWatch Logs log group. The function runtime sends details about each invocation to CloudWatch Logs. It relays any logs that your function outputs during invocation. If your function returns an error, Lambda formats the error and returns it to the invoker.

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