Giter Site home page Giter Site logo

python-p3-data-structures-lab's Introduction

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 Python list comprehensions alongside list and dict methods to solve these deliverables. You could use a loop to solve all of these, but try to expand your toolkit and use some other methods to make the job easier, like get(), append(), and sort().

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

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


Resources

python-p3-data-structures-lab's People

Contributors

professor-ben avatar betalantz avatar

Watchers

James Cloos avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    πŸ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. πŸ“ŠπŸ“ˆπŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❀️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.