Shipping Cost: Calculate the Optimal Shipping Cost Across Multiple Carrier Rate Tables

Question

## Problem

You have multiple shipping carriers. Each carrier has a rate table: a list of `(max_weight, cost)` tiers. Given a package weight, each carrier charges the cost of the first tier whose `max_weight >= package_weight`, or is ineligible if the package exceeds all tiers.

Return the carrier name and minimum cost, or `"no carrier"` if none can handle the package.

```python
from typing import List, Tuple, Optional

def cheapest_carrier(
    carriers: List[dict],
    weight: float
) -> Tuple[Optional[str], Optional[float]]:
    # carrier: {"name": str, "tiers": [[max_weight, cost], ...] sorted asc by max_weight}
    # return: (carrier_name, cost) or (None, None)
    pass
```

**Example:**
```
carriers = [
  {"name": "FastShip", "tiers": [[5, 3.99],[20, 7.99],[50, 12.99]]},
  {"name": "BulkCo",   "tiers": [[10, 5.00],[100, 9.00]]}
]
weight = 8

FastShip: 8 > 5, fits tier [20,7.99] -> cost=$7.99
BulkCo:   8 <= 10 -> cost=$5.00

Output: ("BulkCo", 5.00)
```

## Follow-ups

1. How would you use binary search to find the applicable tier in O(log n) per carrier?
2. How would you handle dimensional weight (volumetric weight = L*W*H/divisor) as an additional input?
3. If carriers have time-of-day pricing, how do you incorporate that into the rate lookup?
4. How would you design a caching layer so repeated queries for the same weight return instantly?

Shipping Cost: Calculate the Optimal Shipping Cost Across Multiple Carrier Rate Tables

Question Details

Full Details

Topics

More from Stripe