• Classes
  • 07 - Lambda Functions
  • Part 1

Lambda Function for Sentment Analysis (SA)

Let's create a lambda function that uses the textblob library to return the polarity of a text.

Example: list Lambda functions

In this and in the next classes, we will also use the AWS CLI to interact with AWS services.

You can use the AWS CLI to create, list, or remove resources. For example, to list the names of lambda functions:

$ aws lambda list-functions --query "Functions[*].FunctionName" --output text --profile mlops


From here on, you can research how to do with the AWS CLI what we did with boto3 library.

Create source code

Question 1

Create a file polarity.py containing a Lambda function get_polarity that receives a JSON in the request body and returns a JSON containing:

  • The received sentence itself
  • The polarity returned by TextBlob
  • The feeling of the sentence.
    • If the polarity is below -0.8, consider it as negative sentiment.
    • If the polarity is between -0.8 and 0.2, consider it neutral sentiment.
    • If the polarity is above 0.2, consider it as positive sentiment.

Once finished, check your code with the official answer provided below.

Official answer for polarity.py 
from textblob import TextBlob
import json


def get_polarity(event, context):
    # Provide a body for the request!
    if "body" not in event:
        return {"error": "No body provided"}

    # Get the raw posted JSON
    raw_json = event["body"]

    # Load it into a Python dict
    body = json.loads(raw_json)

    if "phrase" not in body:
        return {"error": "No phrase provided"}

    phrase = body["phrase"]

    # Create a TextBlob object of the phrase
    blob = TextBlob(phrase)

    # Get the polarity score
    polarity = blob.polarity

    # Create a response object with the phrase and polarity
    res = {"phrase": phrase, "polarity": str(polarity)}

    # Determine the sentiment
    if polarity > 0.2:
        res["sentiment"] = "Positive sentiment"
    elif polarity >= -0.8:
        res["sentiment"] = "Neutral sentiment"
    else:
        res["sentiment"] = "Negative sentiment"

    return res

Question 2

Do as in the last class, create a ZIP of your Python file to deploy to AWS Lambda.

Create Lambda function

Atention!

Change the function_name variable.

Provide a name in the pattern get_polarity_<YOUR_INSPER_USERNAME>

import boto3
import os
from dotenv import load_dotenv

load_dotenv()

# Lambda function name
# Provide a name in the pattern `get_polarity_<YOUR_INSPER_USERNAME>`
function_name = ""

# Lambda basic execution role
lambda_role_arn = os.getenv("AWS_LAMBDA_ROLE_ARN")

# Create a Boto3 client for AWS Lambda
session = boto3.Session(
    profile_name=os.getenv("AWS_PROFILE"), region_name=os.getenv("AWS_REGION")
)

lambda_client = session.client("lambda")

# Read the contents of the zip file that you want to deploy
with open("polarity.zip", "rb") as f:
    zip_to_deploy = f.read()

lambda_response = lambda_client.create_function(
    FunctionName=function_name,
    Runtime="python3.12", # Change the runtime if you want!
    Role=lambda_role_arn,
    Handler="polarity.get_polarity",  # function get_polarity inside polarity.py
    Code={"ZipFile": zip_to_deploy},
)

print("Function ARN:", lambda_response["FunctionArn"])

Check if worked

Before creating the API, let's check if the Lambda function works correctly!

To do this, let's make a direct call to the function with:

Atention!

Change the function_name variable with the same name as before.

import boto3
import os
import io
from dotenv import load_dotenv

load_dotenv()

# Lambda function name
function_name = ""

# Create a Boto3 client for AWS Lambda
session = boto3.Session(
    profile_name=os.getenv("AWS_PROFILE"), region_name=os.getenv("AWS_REGION")
)

lambda_client = session.client("lambda")


try:
    # Invoke the function
    response = lambda_client.invoke(
        FunctionName=function_name,
        InvocationType="RequestResponse",
    )

    payload = response["Payload"]

    txt = io.BytesIO(payload.read()).read().decode("utf-8")
    print(f"Response:\n{txt}")
except Exception as e:
    print(e)

Question 3

The call must not have worked. What error is returned?

Answer!

Among others: 

{
    "errorMessage": "Unable to import module 'polarity': No module named 'textblob'"
}

This occurred because our function depends on a library textblob that is not available in the environment where it is being executed.

Runtime dependencies

In AWS Lambda, when our Python code depends on another package or module, two options are:

  1. Include the dependencies in the ZIP
  2. Use Lambda layer

Let's work with the second option! Proceed to the next topic.