Receipt Processor

Overview

This project implements a web service for processing receipts and calculating points based on a specific ruleset from the Fetch Rewards Receipt Processor Challenge.

The service is built using FastAPI and includes endpoints for submitting receipts and retrieving points awarded for a given receipt ID. The project is designed to fulfill the requirements of a coding challenge, with a focus on in-memory data storage, efficient request handling, and comprehensive testing.

Key Features and Challenge Requirements

• Efficient Request Handling: Utilizes FastAPI's async capabilities for efficient request handling.
• In-Memory Storage: Stores receipt data in memory, ensuring no data persistence across application restarts.
• Comprehensive Testing: Includes both unit and integration tests to ensure the correctness of the implementation.
• Dockerized Setup: Provides a Dockerfile for easy containerization and deployment.
• Exception Handlers: Provides exception handler examples for ValidationError and HTTPException to return meaningful error responses.

API Endpoints

1. Process Receipts

• Endpoint: /receipts/process
• Method: POST
• Description: Submits a receipt for processing and returns a JSON object with an ID generated by the application.
• Request Body: JSON object representing the receipt.
• Response: JSON object containing the receipt ID.

Example Request

{
  "retailer": "Target",
  "purchaseDate": "2022-01-01",
  "purchaseTime": "13:01",
  "items": [
    {"shortDescription": "Mountain Dew 12PK", "price": "6.49"},
    {"shortDescription": "Emils Cheese Pizza", "price": "12.25"},
    {"shortDescription": "Knorr Creamy Chicken", "price": "1.26"},
    {"shortDescription": "Doritos Nacho Cheese", "price": "3.35"},
    {"shortDescription": "Klarbrunn 12-PK 12 FL OZ", "price": "12.00"}
  ],
  "total": "35.35"
}

Example Response

{
  "id": "7fb1377b-b223-49d9-a31a-5a02701dd310"
}

2. Get Points

• Endpoint: /receipts/{id}/points
• Method: GET
• Description: Retrieves the points awarded for the receipt with the given ID.
• Response: JSON object containing the number of points awarded.

Example Request

GET /receipts/7fb1377b-b223-49d9-a31a-5a02701dd310/points

Example Response

{
  "points": 28
}

Points Calculation Rules

1. One point for every alphanumeric character in the retailer name.
2. 50 points if the total is a round dollar amount with no cents.
3. 25 points if the total is a multiple of 0.25.
4. 5 points for every two items on the receipt.
5. If the trimmed length of the item description is a multiple of 3, multiply the price by 0.2 and round up to the nearest integer.
6. 6 points if the day in the purchase date is odd.
7. 10 points if the time of purchase is after 2:00pm and before 4:00pm.

Running the Application via Docker

Installation

Clone the repository

git clone https://github.com/ryanlevee/receipt-processor.git

Make sure you are in the root directory for the project (receipt-processor).

Build Docker image

docker build -t receipt-processor-image:1.0 .

Verify Docker image was successfully built

docker images

Run a container using the image

docker run -d --name receipt-processor -p 8000:8000 receipt-processor-image:1.0

Verify the container is running

docker ps

Verify the web service has started

docker logs receipt-processor

API documentation and UI can now be accessed at http://localhost:8000/docs.

Running Tests

1. Run the tests using pytest:

   pytest
   

Project Structure

receipt-processor/
├── main.py                # Main application code
├── tests/
│   ├── __init__.py        # Test package initializer
│   ├── test_integration.py# Integration tests
│   ├── test_unit.py       # Unit tests
├── requirements.txt       # Project dependencies
├── Dockerfile             # Dockerfile for containerization
└── README.md              # Project documentation

Running the Application Locally

1. Clone the repository:

   git clone https://github.com/ryanlevee/receipt-processor.git
   cd receipt-processor
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the application:

   uvicorn main:app --host 0.0.0.0 --port 8000
   

4. Access the API documentation and UI at http://localhost:8000/docs.