Git Product home page Git Product logo

prework-library-loops's Introduction

Welcome to Library Loops!

You have a massive collection of books; many you've read, many you have not! You've read so many, it's been hard to keep track of the information about these books. In order to keep track of all of your books, you've decided to catalogue them all, keeping track of specific data about each book.

Now you have your collection, minified to an array called library. This array contains hashes that represent each book, keeping track of the book's title, author, genres, publication year, number of pages, and whether or not you've completed reading the book. Though all this data is great, it's unwieldy, and hard to understand or navigate through. You give yourself another challenge: write some ruby methods to interpret the data! Here are the methods you have in mind...

Setup

If you have your local environment setup, you'll be able do this lab!

  • fork this repo so you have your own version of it
  • clone down this repo, either by clicking the green button that says "Clone or download" and copying that code, or by typing into your terminal (where your repositories go) git clone [email protected]:<your-github>/prework-library-loops.git
  • change your directory into that folder (cd prework-library-loops)
  • open up the lab in your preferred text editor
  • run bundle install in terminal

There is no rspec folder and there are no tests. Test the deliverables after you write each one to make sure the behavior you are getting is the behavior you expect!

Good Luck!

Deliverables

  • all_pages: all_pages takes in your library as an argument, and outputs how many pages are in all of your books in your library! (Bonus: try to complete this method using the .reduce method)

Example

all_pages(library)

12406

  • all_pages_read: all_pages_read takes in your library as an argument, and outputs how many pages are in all the books that you've read! (Bonus: try to complete this method using the .reduce method)

Example

all_pages_read(library)

781

  • all_genres: all_genres takes in your library as an argument, and outputs an array. This array should contain all of the genres that you have in your library. Try to make it display only unique strings; no duplicates!

Example

all_genres(library)

[
  "Fantasy",
  "Horror",
  "Science Fiction"
]

  • books_read: books_read takes in your library as an argument, and outputs an array of all of the books that you have completed.

Example

books_read(library)

[
  {title: "Dracula", author: "Bram Stoker", genres: ["Horror", "Gothic"], pages: 418, publication_year: 1897, completed: true},
  {title: "Mastering the Art of French Cooking", author: "Simone Beck, Louisette Bertholie, Julia Child", genres: ["Cooking", "Non-Fiction"], pages: 726, publication_year: 1961, completed: true}
]

  • completed_books_detail: completed_books_detail takes in your library as an argument, and outputs a string that lists how many books you've read, and how many pages you've read.

Example

completed_books_detail(library)

"I've read 5 books, totaling at 1074 pages."

  • books_in_library: books_in_library takes in your library as an argument, and outputs an array of strings, where each string is each book of your library, but only their name and author

Example

books_in_library(library)

[
  "Inferno by Dante Alighieri",
  "Mastering the Art of French Cooking by Simone Beck, Louisette Bertholie, Julia Child",
  "Animal Farm by George Orwell"
]

  • books_by_year: books_by_year takes in your library as an argument, and outputs an array of strings (just like the previous method). However, the books should be ordered by what year they were published.

Example

books_by_year(library)

[
  "Inferno by Dante Alighieri",
  "Animal Farm by George Orwell",
  "Mastering the Art of French Cooking by Simone Beck, Louisette Bertholie, Julia Child"
]

  • books_with_subtitles: books_with_subtitles takes in your library as an argument, and outputs an array of book hashes that have titles that have a subtitle.

Example

books_with_subtitles(library)

[
  {title: "Frankenstein; or, the Modern Prometheus", author: "Mary Shelley", genres: ["Gothic", "Horror", "Science Fiction"], pages: 280, publication_year: 1818, completed: true}
]

  • books_primary_title: books_primary_title takes in your library as an argument, and outputs an array of book title strings. If the book title has a subtitle, only output the primary title.

Example

books_primary_title(library)

[
  "Dracula",
  "Frankenstein",
  "Circe",
  "Animal Farm"
]

  • highest_page_count: highest_page_count takes in your library as an argument, and outputs the longest book. (Bonus: try to complete this method using the .reduce method)

Example

highest_page_count(library)

{title: "War and Peace", author: "Leo Tolstoy", genres: ["Historical Fiction"], pages: 1225, publication_year: 1869, completed: false}


BONUS Deliverables

  • recommended_books: recommended_books takes in your library and a number in as arguments, and outputs an array of strings. The number of strings in the array should be equal to the number argument. The strings are about books you are recommending from your entire library, organized by fewest page count to longest page count. e.g., If the number argument is 4, you should output the 4 shortest books.

Example

recommended_books(library, 3)

[
  "You should read Animal Farm by George Orwell; it's only 112 pages long!",
  "You should read Circe by Madeline Miller; it's only 385 pages long!",
  "You should War and Peace by Leo Tolstoy; it's only 1225 pages long!"
]

  • recommended_books_by_genre: recommended_books_by_genre takes in your library and two strings in as arguments, and outputs an array of strings. The first string argument should be a genre that is preferred, and the second string argument should be a genre that is not preferred. The array should a list of recommendations, listing the preferred genres first, followed by the the other books in your library. The books with the genres that are not preferred should not be in the array.

Example

recommended_books_by_genre(library, "Historical Fiction", "Science Fiction")

[
  "Since you like Historical Fiction, you should read Circe by Madeline Miller!",
  "Since you like Historical Fiction, you should read War and Peace by Leo Tolstoy!",
  "I also recommend Animal Farm by George Orwell.",
  "I also recommend Mastering the Art of French Cooking by Simone Beck, Louisette Bertholie, Julia Child.",
  "I also recommend Dracula by Bram Stoker."
]

prework-library-loops's People

Contributors

guillamoure avatar

Watchers

James Cloos avatar

Forkers

tiggy31

Recommend Projects

  • React photo React

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

  • Vue.js photo Vue.js

    ๐Ÿ–– 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. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

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 โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.