Welcome to Mecha Munch Management on Exercism's Python Track.
If you need help running the tests or submitting your code, check out HELP.md.
If you get stuck on the exercise, check out HINTS.md, but try and solve it without using those first :)
The dict class in Python provides many useful methods for working with dictionaries.
Some were introduced in the concept for dicts.
Here we cover a few more - along with some techniques for iterating through and manipulating dictionaries.
The dictionary concept previously covered that .get(key, <default value>) returns an existing value or the default value if a key is not found in a dictionary, thereby avoiding a KeyError.
This works well in situations where you would rather not have extra error handling but cannot trust that a looked-for key will be present.
For a similarly "safe" (without KeyError) insertion operation, there is the .setdefault(key, <default value>) method.
setdefault(key, <default value>) will return the value if the key is found in the dictionary.
If the key is not found, it will insert the (key, default value) pair and return the default value for use.
>>> palette_I = {'Grassy Green': '#9bc400', 'Purple Mountains Majesty': '#8076a3', 'Misty Mountain Pink': '#f9c5bd'}
# Looking for the value associated with key "Rock Brown".
# The key does not exist, so it is added with the default value, and the value is returned.
>>> palette_I.setdefault('Rock Brown', '#694605')
'#694605'
# The (key, default value) pair has now been added to the dictionary.
>>> palette_I
{'Grassy Green': '#9bc400', 'Purple Mountains Majesty': '#8076a3', 'Misty Mountain Pink': '#f9c5bd', 'Rock Brown': '#694605'}To quickly populate a dictionary with various keys and default values, the class method fromkeys(iterable, <default value>) will iterate through an iterable of keys and create a new dict.
All values will be set to the default value provided:
>>> new_dict = dict.fromkeys(['Grassy Green', 'Purple Mountains Majesty', 'Misty Mountain Pink'], 'fill in hex color here')
{'Grassy Green': 'fill in hex color here',
'Purple Mountains Majesty': 'fill in hex color here',
'Misty Mountain Pink': 'fill in hex color here'}The .keys(), .values(), and .items() methods return iterable views of a dictionary.
These views can be used to easily loop over entries without altering them.
Views are also dynamic -- when underlying dictionary data changes, the associated view object will reflect the change:
>>> palette_I = {'Grassy Green': '#9bc400',
'Purple Mountains Majesty': '#8076a3',
'Misty Mountain Pink': '#f9c5bd'}
# Using .keys() returns a list of keys.
>>> palette_I.keys()
dict_keys(['Grassy Green', 'Purple Mountains Majesty', 'Misty Mountain Pink'])
# Using .values() returns a list of values.
>>> palette_I.values()
dict_values(['#9bc400', '#8076a3', '#f9c5bd'])
# Using .items() returns a list of (key, value) tuples.
>>> palette_I.items()
dict_items([('Grassy Green', '#9bc400'), ('Purple Mountains Majesty', '#8076a3'), ('Misty Mountain Pink', '#f9c5bd')])
# Views are dynamic. Changing values in the dict changes all of the associated views.
>>> palette_I['Purple Mountains Majesty'] = (128, 118, 163)
>>> palette_I['Deep Red'] = '#932432'
>>> palette_I.values()
dict_values(['#9bc400', (128, 118, 163), '#f9c5bd', '#932432'])
>>> palette_I.keys()
dict_keys(['Grassy Green', 'Purple Mountains Majesty', 'Misty Mountain Pink', 'Deep Red'])
>>> palette_I.items()
dict_items([('Grassy Green', '#9bc400'), ('Purple Mountains Majesty', (128, 118, 163)), ('Misty Mountain Pink', '#f9c5bd'), ('Deep Red', '#932432')])In Python 3.7+, dicts preserve the order in which entries are inserted allowing First-in, First-out (FIFO), iteration when using .keys(), .values(), or .items().
In Python 3.8+, views are also reversible.
This allows keys, values, or (key, value) pairs to be iterated over in Last-in, First-out (LIFO) order by using reversed(<dict>.keys()), reversed(<dict>.values()), or reversed(<dict>.items()):
>>> palette_II = {'Factory Stone Purple': '#7c677f', 'Green Treeline': '#478559', 'Purple baseline': '#161748'}
# Iterating in insertion order
>>> for item in palette_II.items():
... print(item)
...
('Factory Stone Purple', '#7c677f')
('Green Treeline', '#478559')
('Purple baseline', '#161748')
# Iterating in the reverse direction.
>>> for item in reversed(palette_II.items()):
... print (item)
...
('Purple baseline', '#161748')
('Green Treeline', '#478559')
('Factory Stone Purple', '#7c677f')Dictionaries do not have a built-in sorting method.
However, it is possible to sort a dict view using the built-in function sorted() with .items().
The sorted view can then be used to create a new dictionary.
Like iteration, the default sort is over dictionary keys.
# Default ordering for a dictionary is last in, first out (LIFO).
>>> color_palette = {'Grassy Green': '#9bc400',
'Purple Mountains Majesty': '#8076a3',
'Misty Mountain Pink': '#f9c5bd',
'Factory Stone Purple': '#7c677f',
'Green Treeline': '#478559',
'Purple baseline': '#161748'}
# The default sort order for a dictionary uses the keys.
>>> sorted_palette = dict(sorted(color_palette.items()))
>>> sorted_palette
{'Factory Stone Purple': '#7c677f',
'Grassy Green': '#9bc400',
'Green Treeline': '#478559',
'Misty Mountain Pink': '#f9c5bd',
'Purple Mountains Majesty': '#8076a3',
'Purple baseline': '#161748'}<dict_one>.update(<dict_two>) can be used to combine two dictionaries.
This method will take the (key,value) pairs of <dict_two> and write them into <dict_one>:
>>> palette_I = {'Grassy Green': '#9bc400',
'Purple Mountains Majesty': '#8076a3',
'Misty Mountain Pink': '#f9c5bd'}
>>> palette_II = {'Factory Stone Purple': '#7c677f',
'Green Treeline': '#478559',
'Purple Baseline': '#161748'}
>>> palette_I.update(palette_II)
# Note that new items from palette_II are added.
>>> palette_I
{'Grassy Green': '#9bc400', 'Purple Mountains Majesty': '#8076a3', 'Misty Mountain Pink': '#f9c5bd', 'Factory Stone Purple': '#7c677f', 'Green Treeline': '#478559', 'Purple Baseline': '#161748'}Where keys in the two dictionaries overlap, the value in dict_one will be overwritten by the corresponding value from dict_two:
>>> palette_I = {'Grassy Green': '#9bc400', 'Purple Mountains Majesty': '#8076a3', 'Misty Mountain Pink': '#f9c5bd',
'Factory Stone Purple': '#7c677f', 'Green Treeline': '#478559', 'Purple baseline': '#161748'}
>>> palette_III = {'Grassy Green': (155, 196, 0), 'Purple Mountains Majesty': (128, 118, 163),
'Misty Mountain Pink': (249, 197, 189)}
>>> palette_I.update(palette_III)
# Overlapping values in palette_I are replaced with values from palette_III
>>> palette_I
{'Grassy Green': (155, 196, 0),
'Purple Mountains Majesty': (128, 118, 163),
'Misty Mountain Pink': (249, 197, 189),
'Factory Stone Purple': '#7c677f',
'Green Treeline': '#478559', 'Purple baseline': '#161748'}Python 3.9 introduces a different means of merging dicts: the union operators.
dict_one | dict_two will create a new dictionary, made up of the (key, value) pairs of dict_one and dict_two.
When both dictionaries share keys, dict_two values take precedence.
>>> palette_I = {'Grassy Green': '#9bc400', 'Purple Mountains Majesty': '#8076a3', 'Misty Mountain Pink': '#f9c5bd'}
>>> palette_II = {'Factory Stone Purple': '#7c677f', 'Green Treeline': '#478559', 'Purple baseline': '#161748'}
>>> new_dict = palette_I | palette_II
>>> new_dict
...
{'Grassy Green': '#9bc400',
'Purple Mountains Majesty': '#8076a3',
'Misty Mountain Pink': '#f9c5bd',
'Factory Stone Purple': '#7c677f',
'Green Treeline': '#478559',
'Purple baseline': '#161748'}dict_one |= other behaves similar to <dict_one>.update(<dict_two>), but in this case, other can be either a dict or an iterable of (key, value) pairs:
>>> palette_III = {'Grassy Green': (155, 196, 0),
'Purple Mountains Majesty': (128, 118, 163),
'Misty Mountain Pink': (249, 197, 189)}
>>> new_dict |= palette_III
>>> new_dict
...
{'Grassy Green': (155, 196, 0),
'Purple Mountains Majesty': (128, 118, 163),
'Misty Mountain Pink': (249, 197, 189),
'Factory Stone Purple': '#7c677f',
'Green Treeline': '#478559',
'Purple baseline': '#161748'}For a detailed explanation of dictionaries and methods for working with them, the official tutorial and the official library reference are excellent starting places.
Real Python and Finxter also have very thorough articles on Python dictionaries.
Mecha Munch™, a grocery shopping automation company has just hired you to work on their ordering app. Your team is tasked with building an MVP (minimum viable product) that manages all the basic shopping cart activities, allowing users to add, remove, and sort their grocery orders. Thankfully, a different team is handling all the money and check-out functions!
The MVP should allow the user to add items to their shopping cart. This could be a single item or multiple items at once. Since this is an MVP, item quantity is indicated by repeats. If a user wants to add 2 Oranges, 'Oranges' will appear twice in the input iterable. If the user already has the item in their cart, the cart quantity should be increased by 1. If the item is new to the cart, it should be added with a quantity of 1.
Create the function add_items(<current_cart>, <items_to_add>) that takes a cart dictionary and any list-like iterable of items to add as arguments.
It should return a new/updated shopping cart dictionary for the user.
>>> add_items({'Banana': 3, 'Apple': 2, 'Orange': 1},
('Apple', 'Apple', 'Orange', 'Apple', 'Banana'))
{'Banana': 4, 'Apple': 5, 'Orange': 2}
>>> add_items({'Banana': 3, 'Apple': 2, 'Orange': 1},
['Banana', 'Orange', 'Blueberries', 'Banana'])
{'Banana': 5, 'Apple': 2, 'Orange': 2, 'Blueberries': 1}Uh-oh. Looks like the product team is engaging in feature creep. They want to add extra functionality to the MVP. The application now has to create a shopping cart by reading items off a users notes app. Convenient for the users, but slightly more work for the team.
Create the function read_notes(<notes>) that can take any list-like iterable as an argument.
The function should parse the items and create a user shopping cart/dictionary.
Each item should be added with a quantity of 1.
The new user cart should then be returned.
>>> read_notes(('Banana','Apple', 'Orange'))
{'Banana': 1, 'Apple': 1, 'Orange': 1}
>>> read_notes(['Blueberries', 'Pear', 'Orange', 'Banana', 'Apple'])
{'Blueberries' : 1, 'Pear' : 1, 'Orange' : 1, 'Banana' : 1, 'Apple' : 1}The app has an "ideas" section that's filled with finished recipes from various cuisines. The user can select any one of these recipes and have all its ingredients added to their shopping cart automatically. The project manager has asked you create a way to edit these "ideas" recipes, since the content team keeps changing around ingredients and quantities.
Create the function update_recipes(<ideas>, <recipe_updates>) that takes an "ideas" dictionary and an iterable of recipe updates as arguments.
The function should return the new/updated "ideas" dictionary.
>>> update_recipes({'Banana Bread' : {'Banana': 1, 'Apple': 1, 'Walnuts': 1, 'Flour': 1, 'Eggs': 2, 'Butter': 1},
'Raspberry Pie' : {'Raspberry': 1, 'Orange': 1, 'Pie Crust': 1, 'Cream Custard': 1}},
(('Banana Bread', {'Banana': 4, 'Walnuts': 2, 'Flour': 1, 'Eggs': 2, 'Butter': 1, 'Milk': 2, 'Eggs': 3}),))
...
{'Banana Bread' : {'Banana': 4, 'Walnuts': 2, 'Flour': 1, 'Eggs': 2, 'Butter': 1, 'Milk': 2, 'Eggs': 3},
'Raspberry Pie' : {'Raspberry': 1, 'Orange': 1, 'Pie Crust': 1, 'Cream Custard': 1}}
>>> update_recipes({'Banana Bread' : {'Banana': 1, 'Apple': 1, 'Walnuts': 1, 'Flour': 1, 'Eggs': 2, 'Butter': 1},
'Raspberry Pie' : {'Raspberry': 1, 'Orange': 1, 'Pie Crust': 1, 'Cream Custard': 1},
'Pasta Primavera': {'Eggs': 1, 'Carrots': 1, 'Spinach': 2, 'Tomatoes': 3, 'Parmesan': 2, 'Milk': 1, 'Onion': 1}},
[('Raspberry Pie', {'Raspberry': 3, 'Orange': 1, 'Pie Crust': 1, 'Cream Custard': 1, 'Whipped Cream': 2}),
('Pasta Primavera', {'Eggs': 1, 'Mixed Veggies': 2, 'Parmesan': 2, 'Milk': 1, 'Spinach': 1, 'Bread Crumbs': 1}),
('Blueberry Crumble', {'Blueberries': 2, 'Whipped Creme': 2, 'Granola Topping': 2, 'Yogurt': 3})])
...
{'Banana Bread': {'Banana': 1, 'Apple': 1, 'Walnuts': 1, 'Flour': 1, 'Eggs': 2, 'Butter': 1},
'Raspberry Pie': {'Raspberry': 3, 'Orange': 1, 'Pie Crust': 1, 'Cream Custard': 1, 'Whipped Cream': 2},
'Pasta Primavera': {'Eggs': 1, 'Mixed Veggies': 2, 'Parmesan': 2, 'Milk': 1, 'Spinach': 1, 'Bread Crumbs': 1},
'Blueberry Crumble': {'Blueberries': 2, 'Whipped Creme': 2, 'Granola Topping': 2, 'Yogurt': 3}}Once a user has started a cart, the app allows them to sort their items alphabetically. This makes things easier to find, and helps when there are data-entry errors like having 'potatoes' and 'Potato' in the database.
Create the function sort_entries(<cart>) that takes a shopping cart/dictionary as an argument and returns a new, alphabetically sorted one.
>>> sort_entries({'Banana': 3, 'Apple': 2, 'Orange': 1})
{'Apple': 2, 'Banana':3, 'Orange': 1}The app needs to send a given users cart to the store for fulfillment. However, the shoppers in the store need to know which store aisle the item can be found in and if the item needs refrigeration. So (rather arbitrarily) the "fulfillment cart" needs to be sorted in reverse alphabetical order with item quantities combined with location and refrigeration information.
Create the function send_to_store(<cart>, <aisle_mapping>) that takes a user shopping cart and a dictionary that has store aisle number and a True/False for refrigeration needed for each item.
The function should return a combined "fulfillment cart" that has (quantity, aisle, and refrigeration) for each item the customer is ordering.
Items should appear in reverse alphabetical order.
>>> send_to_store({'Banana': 3, 'Apple': 2, 'Orange': 1, 'Milk': 2},
{'Banana': ['Aisle 5', False], 'Apple': ['Aisle 4', False], 'Orange': ['Aisle 4', False], 'Milk': ['Aisle 2', True]})
{'Orange': [1, 'Aisle 4', False], 'Milk': [2, 'Aisle 2', True], 'Banana': [3, 'Aisle 5', False], 'Apple': [2, 'Aisle 4', False]}The app can't just place customer orders endlessly. Eventually, the store is going to run out of various products. So your app MVP needs to update the store inventory every time a user sends their order to the store. Otherwise, customers will order products that aren't actually available.
Create the function update_store_inventory(<fulfillment_cart>, <store_inventory>) that takes a "fulfillment cart" and a store inventory.
The function should reduce the store inventory amounts by the number "ordered" in the "fulfillment cart" and then return the updated store inventory.
Where a store item count falls to 0, the count should be replaced by the message 'Out of Stock'.
>>> update_store_inventory({'Orange': [1, 'Aisle 4', False], 'Milk': [2, 'Aisle 2', True], 'Banana': [3, 'Aisle 5', False], 'Apple': [2, 'Aisle 4', False]},
{'Banana': [15, 'Aisle 5', False], 'Apple': [12, 'Aisle 4', False], 'Orange': [1, 'Aisle 4', False], 'Milk': [4, 'Aisle 2', True]})
{'Banana': [12, 'Aisle 5', False], 'Apple': [10, 'Aisle 4', False], 'Orange': ['Out of Stock', 'Aisle 4', False], 'Milk': [2, 'Aisle 2', True]}- @meatball133
- @BethanyG