Data Traversal

Mix.install([
  {:jason, "~> 1.4"},
  {:kino, "~> 0.9", override: true},
  {:youtube, github: "brooklinjazz/youtube"},
  {:hidden_cell, github: "brooklinjazz/hidden_cell"}
])

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Data Traversal

Enum.reduce/3 is often useful for traversing complex or nested data structures.

You’re going to create a DataTraversal module that can perform some complex data traversal operations.

Example Solution

defmodule DataTraversal do
  def sum_keyword_list(keyword_list) do
    Enum.reduce(keyword_list, 0, fn {_key, value}, acc -> value + acc end)
  end

  def aggregate(keyword_list) do
    Enum.reduce(keyword_list, [], fn {key, value}, acc ->
      previous = acc[key] || 0
      Keyword.put(acc, key, previous + value)
    end)
    |> Enum.sort()
  end

  def merge_maps(maps) do
    Enum.reduce(maps, %{}, fn map, acc ->
      Map.merge(acc, map)
    end)
  end
end

Implement the DataTraversal module as documented below.

defmodule DataTraversal do
  @doc """
  Sum all of the integer values in a keyword list. The keys do not matter.

  iex> DataTraversal.sum([key: 10, key: 20, key: 30])
  60
  """
  def sum(keyword_list) do
  end

  @doc """
  Aggregate values with common keys in a keyword list.
  Ensure aggregated values are sorted with Enum.sort/1

  iex> DataTraversal.aggregate([key1: 10, key1: 20, key2: 30, key2: 20])
  [key1: 30, key2: 50]
  """
  def aggregate(keyword_list) do
  end

  @doc """
  Merge a list of maps together. New values will replace old values.

  iex> maps = [%{keya: "a"}, %{keyb: "b"}, %{keyc: "c"}, %{keyc: "c2"}]
  iex> DataTraversal.merge_maps(maps)
  %{keya: "a", keyb: "b", keyc: "c2"}
  """
  def merge_maps(maps) do
  end
end

Commit Your Progress

DockYard Academy now recommends you use the latest Release rather than forking or cloning our repository.

Run git status to ensure there are no undesirable changes. Then run the following in your command line from the curriculum folder to commit your progress.

$ git add .
$ git commit -m "finish Data Traversal exercise"
$ git push

We’re proud to offer our open-source curriculum free of charge for anyone to learn from at their own pace.

We also offer a paid course where you can learn from an instructor alongside a cohort of your peers. We will accept applications for the June-August 2023 cohort soon.

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