Record aggregation exercise. From: https://twitter.com/zanfranceschi/status/1679497149732585472

aggregation.exs

records = [
  %{"data" => "2023-07-13", "qtd" => 12},
  %{"data" => "2023-07-14", "qtd" => 30},
  %{"data" => "2023-07-13", "qtd" => 4},
  %{"data" => "2023-07-14", "qtd" => 98},
  %{"data" => "2023-07-12", "qtd" => 4},
  %{"data" => "2023-07-12", "qtd" => 8},
  %{"data" => "2023-07-12", "qtd" => 31},
  %{"data" => "2023-07-15", "qtd" => 74},
  %{"data" => "2023-07-13", "qtd" => 12},
  %{"data" => "2023-07-12", "qtd" => 1},
  %{"data" => "2023-07-17", "qtd" => 3},
  %{"data" => "2023-07-16", "qtd" => 35}
]

records
  |> Enum.group_by(&Map.get(&1, "data"), &Map.get(&1, "qtd"))
  |> Map.new(fn {k, v} -> {k, Enum.sum(v)} end)
  |> IO.inspect()

aggregation.py

from functools import reduce


def aggregate(records):
    def f(acc, r):
        acc[r["data"]] = acc[r["data"]] + r["qtd"] if acc.get(r["data"]) is not None else r["qtd"]

        return acc
    
    return reduce(f, records, {})


records = [
    {"data": "2023-07-13", "qtd": 12},
    {"data": "2023-07-14", "qtd": 30},
    {"data": "2023-07-13", "qtd": 4},
    {"data": "2023-07-14", "qtd": 98},
    {"data": "2023-07-12", "qtd": 4},
    {"data": "2023-07-12", "qtd": 8},
    {"data": "2023-07-12", "qtd": 31},
    {"data": "2023-07-15", "qtd": 74},
    {"data": "2023-07-13", "qtd": 12},
    {"data": "2023-07-12", "qtd": 1},
    {"data": "2023-07-17", "qtd": 3},
    {"data": "2023-07-16", "qtd": 35},
]

result = aggregate(records)
print(result)