Connect python to MongoDB service of AWS using lambda

Introduction

This guide outlines the process of connecting a Python application running in AWS Lambda to a MongoDB database hosted on MongoDB Atlas. It covers obtaining the MongoDB URI, installing the pymongo library, creating a Lambda layer, and deploying your main code in AWS Lambda—all tailored for Windows users.

Step 1: Create a MongoDB Atlas Account

Visit MongoDB Atlas: Go to the MongoDB Atlas website.
Sign Up/Login: Create a new account or log in if you already have one.

Step 2: Set Up a MongoDB Cluster

Build a Cluster:
- Click on the "Build a Cluster" button.
- Select your preferred cloud provider and region. Choose the free tier for testing.
- Click "Create Cluster". Wait for the cluster to be provisioned.

Step 3: Configure Network Access

Network Access:
- In the left sidebar, go to the "Network Access" tab.
- Click on "Add IP Address."
- To allow access from anywhere for testing, enter 0.0.0.0/0. Be cautious as this is not recommended for production.
- Click "Confirm."
Database Access:
- Go to the "Database Access" tab.
- Click on "Add New Database User."
- Create a user with a username and password. Assign appropriate roles (e.g., Read and Write to any database).
- Click "Add User."

Step 4: Get the MongoDB URI

Obtain Connection String:
- Go to the "Database Deployments" section.
- Click "Connect" next to your cluster.
- Choose "Connect your application."
- Copy the provided connection string URI and replace <username> and <password> with your database user credentials:
```
  mongodb+srv://<username>:<password>@<cluster_name>.mongodb.net/test?retryWrites=true&w=majority
```

Step 5: Install Required Packages

To connect to MongoDB Atlas, you need to install the pymongo package.

Open Command Prompt:
- Launch the Command Prompt.
Install Pymongo:
- Run the following command:
```
  pip install pymongo
```

Step 6: Compress the Package for Lambda

AWS Lambda requires a zip file containing the necessary libraries.

Create Layer Directory:
- Create a new directory for the Lambda layer:
```
  mkdir pymongo-layer
  cd pymongo-layer
```
Set Up Virtual Environment:
- Create a virtual environment:
```
  python -m venv venv
```
Activate Virtual Environment:
- Activate the virtual environment:
```
  venv\Scripts\activate
```
Install Pymongo Again:
- Inside the activated environment, install pymongo:
```
  pip install pymongo
```

Prepare Package for Lambda:

Create the necessary directory structure:

  mkdir -p python/lib/python3.8/site-packages

Copy the installed packages into this directory:

  xcopy /s venv\Lib\site-packages\* python\lib\python3.8\site-packages\

Compress the directory into a zip file:

  powershell -command "Compress-Archive -Path python -DestinationPath pymongo-layer.zip"

Now, you have pymongo-layer.zip ready for upload to AWS Lambda.

AWS Lambda Setup

Step 1: Create a Lambda Layer for Pymongo

Access AWS Lambda:
- Open the AWS Management Console and navigate to the Lambda service.
Create Layer:
- In the left sidebar, go to Layers and click on "Create Layer."
- Upload the pymongo-layer.zip file.
- Select the appropriate runtime (e.g., Python 3.8).
- Click "Create."

Step 2: Create a Lambda Function

Create New Function:
- Return to the AWS Lambda console.
- Click "Create function."
- Select "Author from scratch."
- Fill in the details:
  - Function name: MongoDBConnectionFunction
  - Runtime: Python 3.8
  - Permissions: Choose an execution role with basic Lambda permissions or create a new one.
Create Function:
- Click "Create function." You will be redirected to the function configuration page.

Python Connection Code

Code Implementation:
- Scroll down to the Function code section in the AWS Lambda console.
- Copy and paste the following code into the code editor:

import json
import pymongo
import os

def lambda_handler(event, context):
    # MongoDB connection string from environment variables
    mongo_uri = os.getenv('MONGO_URI')

    # Connect to MongoDB
    client = pymongo.MongoClient(mongo_uri)

    # Select database and collection
    db = client['your_database_name']  # Replace with your database name
    collection = db['your_collection_name']  # Replace with your collection name

    # Example: Insert a document
    document = {
        "name": "Sample Document from Lambda",
        "type": "Demo"
    }
    result = collection.insert_one(document)

    # Example: Query the inserted document
    inserted_document = collection.find_one({"_id": result.inserted_id})

    return {
        'statusCode': 200,
        'body': json.dumps(f'Document inserted: {inserted_document}')
    }

Note

Make sure to replace your_database_name and your_collection_name with the actual names from your MongoDB Atlas setup.

Deploying the Code to Lambda

Set Environment Variables:
- In the Environment variables section, add a new variable:
  - Key: MONGO_URI
  - Value: Your MongoDB Atlas connection string (the URI you copied earlier).
Attach Layer:
- In the Layers section, click on "Add a layer," and select the pymongo layer you created earlier.
Deploy Function:
- Click on "Deploy" to save your changes.

Testing the Lambda Function

Create Test Event:
- Click on the "Test" button in the AWS Lambda console.
- Configure a test event using the default settings.
Invoke Function:
- Click on "Test" to invoke the Lambda function.
- Check the "Execution result" to confirm the document has been successfully inserted and retrieved from MongoDB.

Conclusion

This documentation provides a comprehensive guide for Windows users on connecting a Python application running in AWS Lambda to a MongoDB Atlas database. By following these steps, you will successfully deploy a serverless application capable of performing various database operations.

Feel free to modify any sections to better fit your specific project requirements!