Code Craft Practice Problems

Task: Write a function, calculate_pay_units(events), that takes a list of Dasher events. Each event has a timestamp and a status ('PICKUP' or 'DROPOFF'). Return the total "pay units", where pay units = (time elapsed in seconds × multiplier).

Logic:

• The multiplier starts at 0.
• PICKUP increases the multiplier by 1.
• DROPOFF decreases the multiplier by 1.

Rules & Constraints:

• The input list is not guaranteed to be in chronological order.
• The multiplier must never drop below 0.
• If a PICKUP and DROPOFF occur at the exact same timestamp, process the PICKUP first.

Example Input:

[
  (300, 'DROPOFF'),
  (100, 'PICKUP'),
  (350, 'DROPOFF'),
  (200, 'PICKUP')
]

Calculation Trace (after sorting):

1. Event (t=100, PICKUP):
   • Interval (0s to 100s) @ 0x multiplier = 0 units.
   • Multiplier becomes 1.
2. Event (t=200, PICKUP):
   • Interval (100s to 200s) @ 1x multiplier = 100 units.
   • Multiplier becomes 2.
3. Event (t=300, DROPOFF):
   • Interval (200s to 300s) @ 2x multiplier = 200 units.
   • Multiplier becomes 1.
4. Event (t=350, DROPOFF):
   • Interval (300s to 350s) @ 1x multiplier = 50 units.
   • Multiplier becomes 0.

Expected Output: 350

Task: Implement calculate_order_total(order_json). You must parse the messy JSON, calculate all line items (ignoring the unreliable subtotal_estimate), apply *only* valid promotions, and sum up all fees (ignoring null ones) and the tip to produce a single, final total.

Tricks:

• items.price and tip are strings that must be parsed.
• promotions is a dictionary; you must check is_active: true.
• adjustments is a list; some values might be null.

Input JSON:

{
  "order_id": "ord-123",
  "subtotal_estimate": "45.00",
  "items": [
    {"item_id": "i-1", "name": "Chicken Wings", "price": "14.99", "quantity": 1},
    {"item_id": "i-2", "name": "Coke Zero", "price": "2.50", "quantity": 2}
  ],
  "promotions": {
    "FALL20": {"type": "PERCENT", "value": 0.20, "is_active": true},
    "WELCOME5": {"type": "FIXED", "value": 5.00, "is_active": false}
  },
  "adjustments": [
    {"name": "Service Fee", "amount": 3.99},
    {"name": "Delivery Fee", "amount": 5.00},
    {"name": "Small Order Fee", "amount": null}
  ],
  "tip": "6.15"
}

Task: Design an OrderValidationService with a process_order(raw_json) method. It must parse the JSON, validate it, and return a "clean" Example [ ['X', ' ', ' ', 'D', ' ', ' ', 'X', ' ', 'X'], ['X', ' ', 'X', 'X', ' ', ' ', ' ', ' ', 'X'], [' ', ' ', ' ', 'D', 'X', 'X', ' ', 'X', ' '], [' ', ' ', ' ', 'D', 'X', 'X', ' ', 'X', ' '], [' ', ' ', ' ', ' ', ' ', 'X', ' ', ' ', 'X'], [' ', ' ', ' ', ' ', 'X', ' ', ' ', 'X', 'X'] ] Order object or a structured error message.

Rules: Must have customer_id, at least one item, a parsable delivery_address, and all item_ids must be integers.

Tricks:

• Field names are inconsistent (e.g., order_id vs orderId).
• items is a dictionary where the *key* is the item_id.
• item_ids in the keys might be strings (e.g., "1002").
• delivery_address is a single string to be parsed.

Input JSON:

{
  "orderId": "A-987",
  "custId": "user-554",
  "delivery_address": "123 Main St, Toronto, M5V 2K1",
  "items": {
    "1002": {"name": "Bag of Chips", "quantity": 2},
    "2005": {"name": "Energy Drink", "quantity": 1}
  }
}

Task: Write calculate_bonus(dasher_deliveries_json). Bonus is +$1.00 for on-time (dropoff_actual <= dropoff_estimated) and +$2.00 for 5-star ratings (rating == 5 or rating == "5").

Tricks:

• Timestamps are ISO 8601 strings and must be parsed to compare.
• customer_feedback object can be null or missing.
• rating can be an integer (5) or a string ("5").
• is_return: true deliveries are ineligible for any bonus.

Input JSON:

[
  {
    "delivery_id": "d-1", "is_return": false,
    "timestamps": {
      "dropoff_estimated": "2025-10-25T14:30:00Z",
      "dropoff_actual": "2025-10-25T14:28:00Z"
    },
    "customer_feedback": {"rating": 5}
  },
  {
    "delivery_id": "d-2", "is_return": false,
    "timestamps": {
      "dropoff_estimated": "2025-10-25T15:20:00Z",
      "dropoff_actual": "2025-10-25T15:22:00Z"
    },
    "customer_feedback": {"rating": "4"}
  },
  {
    "delivery_id": "d-3", "is_return": true,
    "timestamps": {"...": "..."},
    "customer_feedback": {"rating": 5}
  },
  {
    "delivery_id": "d-4", "is_return": false,
    "timestamps": {
      "dropoff_estimated": "2025-10-25T17:20:00Z",
      "dropoff_actual": "2025-10-25T17:19:00Z"
    },
    "customer_feedback": null
  }
]

Task: Design a MenuFilteringService that takes menu_json and filters_json. It must return a new, filtered menu JSON. Items that don't match are removed. If a category becomes empty, it must also be removed.

Tricks:

• Deeply nested JSON: categories -> items.
• Filters are optional (e.g., no max_price means don't filter by price).
• Filtering logic is *AND*: must be is_available, under max_price, AND match all dietary_tags.
• Items without a dietary_tags key should be treated as [].
• You must construct a new, valid JSON object, not modify the original.

Input Menu JSON:

{
  "categories": [
    {"category_name": "Appetizers", "items": [
      {"name": "Spring Rolls", "price": 8.00, "is_available": true, "dietary_tags": ["vegan"]},
      {"name": "Chicken Wings", "price": 14.00, "is_available": true, "dietary_tags": []}
    ]},
    {"category_name": "Main Courses", "items": [
      {"name": "Green Curry", "price": 18.00, "is_available": true, "dietary_tags": ["vegan", "gluten_free"]},
      {"name": "Pad Thai", "price": 16.00, "is_available": false, "dietary_tags": ["gluten_free"]}
    ]}
  ]
}

Input Filters JSON:

{
  "max_price": 15.00,
  "dietary_tags": ["vegan"]
}

Task: Write reconcile_transactions(transactions_json). Take the log and return a JSON object where each key is an order_id and the value is its "net profit".

Logic: CHARGE/ADJUSTMENT (positive) are revenue. DASHER_PAY, REFUND, ADJUSTMENT (negative) are expenses. Ignore other types.

Tricks:

• Heterogeneous list: type key determines structure.
• Some events (like DASHER_ONLINE) have no order_id and should be skipped.
• amount is always positive; use type to know if it's revenue or expense.
• ADJUSTMENT payload is a **double-encoded JSON string**! You must parse it to get its (positive or negative) amount.

Input JSON:

[
  { "event_id": "evt-1", "type": "CHARGE", "order_id": "A100", "amount": 45.50 },
  { "event_id": "evt-2", "type": "DASHER_PAY", "order_id": "A100", "amount": 8.00 },
  { "event_id": "evt-3", "type": "DASHER_ONLINE", "dasher_id": "D123" },
  { "event_id": "evt-4", "type": "CHARGE", "order_id": "B200", "amount": 22.00 },
  { "event_id": "evt-5",
    "type": "ADJUSTMENT",
    "order_id": "A100",
    "payload": "{\"reason\": \"Customer complaint\", \"amount\": -5.00}"
  },
  { "event_id": "evt-6", "type": "DASHER_PAY", "order_id": "B200", "amount": 6.50 },
  { "event_id": "evt-7", "type": "REFUND", "order_id": "B200", "amount": 22.00 }
]

Task: Design and implement a DeliveryAssignmentService. This service will be responsible for assigning a newly created order to the 'best' available Dasher.

Core Requirements:

1. Implement the main API method: assign_order(Order order).
2. The "best" Dasher is defined as the closest available Dasher to the restaurant.
3. When an order is assigned, the Dasher becomes unavailable, and the order's status should be updated to ASSIGNED.
4. If no Dashers are available, the service should throw a NoDashersAvailableException.

Provided Mocks (Assume these exist):

• DasherRepository with get_available_dashers() -> List[Dasher]
• OrderRepository with save(Order order)
• DasherRepository with save(Dasher dasher)
• DistanceService with calculate_distance(Location loc1, Location loc2) -> float

Data Models (You will need to define these):

• Location: (latitude, longitude)
• Order: (order_id, restaurant_location, customer_location, status)
• Dasher: (dasher_id, current_location, is_available)
• Delivery: (delivery_id, order_id, dasher_id, status)

Focus on: Your implementation of DeliveryAssignmentService and any supporting classes/enums. Show good OOD, error handling, and testability.