Real-time occupants of a public room API

This project is a Flask-based API for tracking the registration and unregistration of people, along with logging their actions. The API is deployed on AWS Lambda, thus serverless, using the aws-wsgi package,

Features

• Register a Person: Add a person to the current list of occupants.
• Unregister a Person: Remove a person from the current list of occupants.
• Status Check: Get the current status of the location, including a list of occupants and their count.
• Logging: Actions are logged with timestamps and stored in an S3 bucket.

Endpoints

1. Register a Person

• URL: /people/register
• Method: POST
• Request Body:

  {
    "name": "Person Name"
  }

• Response
  • 200 OK

    {
      "status": "registered",
      "occupants": ["Person Name", ...]
    }

  • 400 Bad request

     {
       "error": "name is required",
     }

2. Unregister a Person

• URL: /people/unregister
• Method: POST
• Request Body:

  {
    "name": "Person Name"
  }

• Response
  • 200 OK

    {
      "status": "unregistered",
      "occupants": ["Remaining Occupants", ...]
    }

  • 400 Bad request

     {
       "error": "name is required",
     }

3. Get Status

• URL: /people/status
• Method: GET
• Response
  • 200 OK

    {
      "status": "open" or "closed",
      "occupants": ["Person Name", ...],
      "count": number
    }

AWS S3 Logging

• S3 Bucket: The log files are stored in an S3 bucket named ugo-people-tracker.
• Log Format: Each log entry contains the date, time, name of the person, and the action (register or unregister).
• File Naming: Logs are saved daily with the filename format YYYY-MM-DD-logs.csv.

Deployment

This application is deployed on AWS Lambda using aws-wsgi. Below are the deployment steps:

Prerequisites

1. Set Up AWS Lambda:
   • Create a new Lambda function in AWS Console.
   • the Python 3.x runtime.
   • Ensure the Lambda function has a role with permissions to access S3.
2. Package the Application:
   • Zip the application files including lambda_function.py and dependencies.
3. Upload and Deploy:
   • Upload the zipped package to AWS Lambda.
   • Set the handler to lambda_function.lambda_handler.
4. API Gateway Setup:
   • Create an API Gateway to expose the Lambda function as an HTTP API.
   • Configure CORS settings if needed.

Local Development

For local testing and development, you can run the Flask application using the built-in server:

python lambda_function.py

The application will be accessible at http://127.0.0.1:5000/.

Notes

• Ensure your Lambda function has the necessary permissions to read and write to the specified S3 bucket.

License

This project is licensed under the MIT License.