Boutique Suggestions

10 Points

comprehensions

Instructions

You work at an online fashion boutique store. You come up with the idea for a website feature where outfits are suggested to the user. Of interest are the potential outfits, their prices and eliminating clashing options.

Note

While there may be different ways to solve the following problems, all can be solved with a comprehension.

1. Create clothing item

Implement clothingitem() to take two Tuples, one of categories and the other of their respective qualities. The function should return a Dict with the categories as keys and qualities as values.

julia> categories = ("item_name", "price", "color", "base_color");

julia> qualities = ("Descriptive Name", 99.00, "Ochre Red", "red");

julia> clothingitem(categories, qualities)
Dict{String, Any} with 4 entries:
  "price"      => 99.0
  "item_name"  => "Descriptive Name"
  "base_color" => "red"
  "color"      => "Ochre Red"

Your function should be able to handle any number of categories.

2. Suggest combinations

Implement get_combinations() to take a Tuple of tops and a Tuple of bottoms. The function should return the cartesian product of the tuples as a 2-D array (i.e. Matrix). Each entry is a (top, bottom) combination as a Tuple. Tops change down the rows, bottoms change across the columns.

julia> tops = (
        Dict("item_name" => "Dress shirt"),
        Dict("item_name" => "Casual shirt")
        );

julia> bottoms = (
        Dict("item_name" => "Jeans"),
        Dict("item_name" => "Dress trousers")
       );

julia> get_combinations(tops, bottoms)
2×2 Matrix{Tuple{Dict{String, String}, Dict{String, String}}}:
 (Dict("item_name"=>"Dress shirt"), Dict("item_name"=>"Jeans"))   (Dict("item_name"=>"Dress shirt"), Dict("item_name"=>"Dress trousers"))
 (Dict("item_name"=>"Casual shirt"), Dict("item_name"=>"Jeans"))  (Dict("item_name"=>"Casual shirt"), Dict("item_name"=>"Dress trousers"))

3. Add up outfit prices

Each piece of clothing has a price field associated with it, so it could be helpful to be able to compare the full price of outfits. Implement get_prices() which takes an array of clothing combinations. The function should return a similarly shaped array with the prices of the outfits in their respective positions.

julia> tops = (
        Dict("item_name" => "Dress shirt", "base_color" => "blue", "price" => 35),
        Dict("item_name" => "Casual shirt", "base_color" => "black", "price" => 20)
       );

julia> bottoms = (
        Dict("item_name" => "Jeans", "base_color" => "blue", "price" => 30),
        Dict("item_name" => "Dress trousers", "base_color" => "black", "price" => 75)
       );

julia> combomatrix = get_combinations(tops, bottoms);

julia> get_prices(combomatrix)
2×2 Matrix{Int}::
 65  110
 50   95

julia> filteredmatrix = filter_clashing(combomatrix)
1-element Vector{Tuple{Dict{String, Any}, Dict{String, Any}}}:
 (Dict("price" => 20, "item_name" => "Casual shirt", "base_color" => "black"), Dict("price" => 30, "item_name" => "Jeans", "base_color" => "blue"))

julia> get_prices(filteredmatrix)
1-element Vector{Int}:
 50

4. Filter out clashing outfits

Each piece of clothing has a base_color field. Use this field to remove all combinations where the top and the bottom have the same base color. Implement filter_clashing() to take an array of clothing combinations. Return a 1-D array (i.e. Vector) of the matching combinations.

julia> tops = (
        Dict("item_name" => "Dress shirt", "base_color" => "blue", "price" => 35),
        Dict("item_name" => "Casual shirt", "base_color" => "black", "price" => 20)
       );

julia> bottoms = (
        Dict("item_name" => "Jeans", "base_color" => "blue", "price" => 30),
        Dict("item_name" => "Dress trousers", "base_color" => "black", "price" => 75)
       );

julia> combos = get_combinations(tops, bottoms);

julia> filter_clashing(combos)
1-element Vector{Tuple{Dict{String, Any}, Dict{String, Any}}}:
 (Dict("price" => 20, "item_name" => "Casual shirt", "base_color" => "black"), Dict("price" => 30, "item_name" => "Jeans", "base_color" => "blue"))

julia