Flight Availability and Pricing Service

Scenario

Build a service that aggregates flight availability and pricing from multiple airlines and travel agencies. The service allows users to search for flights between two cities, specifying a date range and preferences. It recommends the best flights based on price and availability, considering factors like layovers and travel duration.

Requirements

1. Data Sources

AirlineConnect: A major airline providing availability and pricing through a RESTful API.
GlobalFlyer: A travel agency offering flight information via a GraphQL endpoint.
BudgetWings: A budget airline that uploads a CSV file daily with flight schedules and prices.

2. Features

Allow users to specify:
- Origin and Destination cities.
- A departure date range (e.g., Jan 10–15).
- Optional preferences such as shortest travel time or lowest cost.
Fetch flight availability and pricing from all sources.
Return:
- The best-priced flight(s) for the selected route and date range.
- Details like layovers, total travel time, and airline.

3. User Preferences

Include filters for:
- Direct flights only or allow layovers.
- Maximum layover duration (e.g., no more than 3 hours).
- Maximum travel time (e.g., no longer than 10 hours total).

4. Performance

Fetch data from all providers concurrently.
Cache frequently queried routes and date ranges to reduce latency.
Use a timeout to handle slow providers.

5. Notifications

If a flight matching a user's preferences drops below a certain price threshold, send an alert to their email or a notification service.

Simulation Details

1. AirlineConnect (REST API)

Simulate this provider with an asynchronous function that returns flight data in JSON format after a delay of 200ms.

Example Response:

[
    {
        "flight_number": "AC101",
        "origin": "JFK",
        "destination": "LAX",
        "price": 300,
        "departure": "2025-01-10T08:00:00",
        "arrival": "2025-01-10T11:00:00",
        "layovers": []
    },
    {
        "flight_number": "AC202",
        "origin": "JFK",
        "destination": "LAX",
        "price": 250,
        "departure": "2025-01-10T15:00:00",
        "arrival": "2025-01-10T19:00:00",
        "layovers": ["ORD"]
    }
]

2. GlobalFlyer (GraphQL Endpoint)

Simulate a GraphQL query returning flight data after a 300ms delay.

Example Query:

query {
    flights(origin: "JFK", destination: "LAX", dates: ["2025-01-10", "2025-01-15"]) {
        flightNumber
        price
        departure
        arrival
        layovers
    }
}

3. BudgetWings (CSV File):

flight_number,origin,destination,price,departure,arrival,layovers
BW303,JFK,LAX,200,2025-01-10T22:00:00,2025-01-11T02:00:00,""
BW404,JFK,LAX,180,2025-01-11T05:00:00,2025-01-11T09:00:00,"PHX"

Steps

Step 1: Basic Implementation

Fetch flight availability and pricing for a given route and date range from all providers.
Aggregate the results and return the best-priced flight(s).

Step 2: Handle Preferences

Add filters for:
- Direct flights only.
- Maximum layover duration.
- Maximum travel time.

Step 3: Performance Optimization

Fetch data concurrently using asynchronous calls.
Add caching for frequently searched routes and date ranges.
Implement timeouts for slow providers to avoid delays in the overall response.

Step 4: Notifications

Send a notification if a flight below a specific price threshold becomes available.

Step 5: Handle Failures

Simulate provider failures (e.g., API down, CSV file missing).
Ensure partial results are returned even if some providers fail.

Possible Extensions:

Multi-City Itineraries

Allow users to search for multi-city routes (e.g., JFK → LAX → SFO).

Real-Time Updates

Implement WebSocket or push notifications for price changes in real-time.

User Accounts

Add user-specific preferences and saved searches.

Pricing Trends

Include price trends over time for users to identify the best time to book flights.

ambersariya/Kata: Flight Availability and Pricing Service.md