Data Structures Lab

Learning Goals

Practice using comprehensions and built-in methods for data structures in Python.
Execute and test Python code using the Python shell and pytest.

Key Vocab

Sequence: a data structure in which data is stored and accessed in a specific order.
Index: the location, represented by an integer, of an element in a sequence.
Iterable: able to be broken down into smaller parts of equal size that can be processed in turn. You can loop through any iterable object.
Slice: a group of neighboring elements in a sequence.
Mutable: an object that can be changed.
Immutable: an object that cannot be changed. (Many immutable objects appear mutable because programmers reuse their names for new objects.)
List: a mutable data type in Python that can store many types of data. The most common data structure in Python.
Tuple: an immutable data type in Python that can store many types of data.
Range: a data type in Python that stores integers in a fixed pattern.
String: an immutable data type in Python that stores unicode characters in a fixed pattern. Iterable and indexed, just like other sequences.

Instructions

Time to get some practice! Write your code in the data_structures.py file in the lib/ folder. Run pytest -x to check your work. Your goal is to practice manipulating sequences with the Python tools you've learned about in this lesson and the lessons before.

In data_structures.py, there is a list of dictionaries representing different spicy foods.

spicy_foods = [
    {
        "name": "Green Curry",
        "cuisine": "Thai",
        "heat_level": 9,
    },
    {
        "name": "Buffalo Wings",
        "cuisine": "American",
        "heat_level": 3,
    },
    {
        "name": "Mapo Tofu",
        "cuisine": "Sichuan",
        "heat_level": 6,
    },
]

Practice using loops and Python list comprehensions alongside list and dict methods to solve these deliverables.

`get_names()`

Define a function get_names() that takes a list of spicy_foods and returns a list of strings with the names of each spicy food.

get_names(spicy_foods)
# => ["Green Curry", "Buffalo Wings", "Mapo Tofu"]

`get_spiciest_foods()`

Define a function get_spiciest_foods() that takes a list of spicy_foods and returns a list of dictionaries where the heat level of the food is greater than 5.

get_spiciest_foods(spicy_foods)
# => [{"name": "Green Curry", "cuisine": "Thai", "heat_level": 9}, {"name": "Mapo Tofu", "cuisine": "Sichuan", "heat_level": 6}]

`print_spicy_foods()`

Define a function print_spicy_foods() that takes a list of spicy_foods and output to the terminal each spicy food in the following format using print(): Buffalo Wings (American) | Heat Level: 🌶🌶🌶.

HINT: you can use times (*) with a string to produce the correct number of "🌶" emojis.

For example:

"hello" * 3 == "hellohellohello"
# => True

print_spicy_foods(spicy_foods)
# => Green Curry (Thai) | Heat Level: 🌶🌶🌶🌶🌶🌶🌶🌶🌶
# => Buffalo Wings (American) | Heat Level: 🌶🌶🌶
# => Mapo Tofu (Sichuan) | Heat Level: 🌶🌶🌶🌶🌶🌶

`get_spicy_food_by_cuisine()`

Define a function get_spicy_food_by_cuisine() that takes a list of spicy_foods and a string representing a cuisine, and returns a single dictionary for the spicy food whose cuisine matches the cuisine being passed to the method.

get_spicy_food_by_cuisine(spicy_foods, "American")
# => {"name": "Buffalo Wings", "cuisine": "American", "heat_level": 3}

get_spicy_food_by_cuisine(spicy_foods, "Thai")
# => {"name": "Green Curry", "cuisine": "Thai", "heat_level": 9}

`print_spiciest_foods()`

Define a function print_spiciest_foods() that takes a list of spicy_foods and outputs to the terminal ONLY the spicy foods that have a heat level greater than 5, in the following format:

Buffalo Wings (American) | Heat Level: 🌶🌶🌶.

Try to use functions you've already written to solve this!

print_spiciest_foods(spicy_foods)
# => Green Curry (Thai) | Heat Level: 🌶🌶🌶🌶🌶🌶🌶🌶🌶
# => Mapo Tofu (Sichuan) | Heat Level: 🌶🌶🌶🌶🌶🌶

`get_average_heat_level()`

Define a function average_heat_level() that takes a list of spicy_foods and returns an integer representing the average heat level of all the spicy foods in the array. Recall that to derive the average of a collection, you need to calculate the total and divide number of elements in the collection.

average_heat_level(spicy_foods)
# => 6

`create_spicy_food()`

Define a function create_spicy_food() that takes a list of spicy_foods and a new spicy_food and returns the original list with the new spicy_food added.

Example:

create_spicy_food(
    spicy_foods,
    {
        'name': 'Griot',
        'cuisine': 'Haitian',
        'heat_level': 10,
    }
)

# => [
# =>     {
# =>         "name": "Green Curry",
# =>         "cuisine": "Thai",
# =>         "heat_level": 9,
# =>     },
# =>     {
# =>         "name": "Buffalo Wings",
# =>         "cuisine": "American",
# =>         "heat_level": 3,
# =>     },
# =>     {
# =>         "name": "Mapo Tofu",
# =>         "cuisine": "Sichuan",
# =>         "heat_level": 6,
# =>     },
# =>     {
# =>         'name': 'Griot',
# =>         'cuisine': 'Haitian',
# =>         'heat_level': 10,
# =>     },
# => ]

When all of your tests are passing, submit your work using git.

emileypalmquist / python-p3-data-structures-lab