shows how to use map_reduce to summarize specific properties on values

summarizing_orders_with_map_reduce.py

from dataclasses import dataclass
from typing import Iterable, Tuple, Dict, Set
from more_itertools import map_reduce


@dataclass(frozen=True, eq=True)
class Order:  # 1
    order_id: str  # 1
    price: int  # 1


def map_order_id_to_highest_price(orders: Iterable[Order]) -> Dict[str, int]:
    return map_reduce(
        orders,
        keyfunc=lambda order: order.order_id,  # 2
        valuefunc=lambda order: order.price,  # 3
        reducefunc=max,  # 4
    )


def test_group_edges_by_source_node():
    orders = {
        Order(order_id="123", price=4),
        Order(order_id="456", price=4),
        Order(order_id="123", price=3),
        Order(order_id="456", price=10),
        Order(order_id="123", price=6),
        Order(order_id="789", price=7),
    }

    order_id_to_higest_price = map_order_id_to_highest_price(orders)

    assert order_id_to_higest_price == {"123": 6, "456": 10, "789": 7}