You can also write Lambda functions using Python.

Before you begin

You can reuse everything your learned from the previous topic and replace the Node.js code with a Lambda function written in Python.

Deploy Lambda function via Terraform

  1. Using a text editor, save the code below in a file called

This is the source code for the Lambda function.


            def lambda_handler(event, context):
    message = 'Hello {}{}!'.format(event['first_name'], event['last_name'])
    return {
      'message' : message

The Lambda function will simply print a message. The message adds the first_name and last_name inputs to the output string.

This example doesn’t place the Python source code in a subdirectory, leave it in the current directory.

  1. Using a text editor, save the code below in a file called

            provider "aws" {
  region = "us-east-1"

provider "archive" {}

data "archive_file" "lambda_zip_dir" {
  type        = "zip"
  output_path = ""
  source_file = ""
data "aws_iam_policy_document" "policy" {
  statement {
    sid    = ""
    effect = "Allow"

    principals {
      identifiers = [""]
      type        = "Service"

    actions = ["sts:AssumeRole"]

resource "aws_iam_role" "iam_for_lambda" {
  name               = "iam_for_lambda"
  assume_role_policy = data.aws_iam_policy_document.policy.json

resource "aws_lambda_function" "lambda" {
  function_name    = "python_lambda"
  filename         = data.archive_file.lambda_zip_dir.output_path
  source_code_hash = data.archive_file.lambda_zip_dir.output_base64sha256
  role             = aws_iam_role.iam_for_lambda.arn
  handler          = "python_lambda.lambda_handler"
  runtime          = "python3.8"
  architectures    = ["arm64"]

data "aws_lambda_invocation" "example" {
  function_name = aws_lambda_function.lambda.function_name

  input = <<JSON
  "first_name": "Arm-",
  "last_name": "user"

output "result" {
  value = data.aws_lambda_invocation.example.result
  1. Using a text editor, save the code below in a file called

            output "lambda" {
  value = aws_lambda_function.lambda.qualified_arn

You should have three files ready to deploy the Lambda function using Terraform. You have,, and in the current directory.

Running the Lambda function displays the ARN (Amazon Resource Names) of the Lambda resource and the output message from the code.

Terraform Commands

Use Terraform to deploy the file.

Create a Terraform execution plan

Run terraform plan to create an execution plan.


            terraform plan

A long output of resources to be created will be printed.

Any errors in the Terraform setup are usually identified by terraform plan.

Apply a Terraform execution plan

Run terraform apply to apply the execution plan and create all AWS resources:


            terraform apply

Answer yes to the prompt to confirm you want to create AWS resources.

The result should print output similar to:


        Apply complete! Resources: 0 added, 1 changed, 0 destroyed.


lambda = "arn:aws:lambda:us-east-1:200211127965:function:python_lambda:$LATEST"
result = "{\"message\": \"Hello Arm-user!\"}"


You have successfully created and executed the Python Lambda function on AWS.

Verify the Lambda function

To verify the creation of the Lambda function to to the AWS console and select AWS Lambda. Click on Functions and verify the Lambda function python_lambda is displayed.

Image Alt Text:python

You can use the Test tab of the Lambda console to run the function again.

Enter the text below in the Event JSON input area.


  "first_name": "Arm-",
  "last_name": "user"

Click the Test button to run the function.

You should see the same output as running the function with Terraform.


        "hello Arm_user, are you using Testing"


You have successfully deployed a Lambda function using Python on an AWS Graviton2 processor.

Clean up resources

Run terraform destroy to delete all resources created.


            terraform destroy

After you run terraform destroy the Lambda function is gone from the AWS console.