Get the snarf file that has the data files you need for this assignment or get them here.
Below is a list of the files and essential methods you need to create for this assignment. Feel free to also create additional helper methods.
IN ALL OF THESE, PRINT A LOT OF OUTPUT WHILE DEBUGGING. Strongly suggested after you create a new structure, print it out to make sure it was built correctly. If it is large, just print a small part of it, such as the first 20 items in a list, or print just ten items from the dictionary.
Here is the suggested 12-step process to work on this project.
At this point you have completed ProcessAllFood.py, RecommenderForAll.py and RecommenderFood.py. You've completed a large part of this assignment!
You are almost done!
Below are a list of all the files and methods you need to write. Each of these should have a main section that you use to test these functions out. More detail for each are on the details page.
processdata( filename) : The
function must read data about food and raters and return the
information in a list and dictionary. (see
details)filename argument must be a txt
file of food and ratings like this sample small one named AllFoodRatings.txt(also in the
snarf ) and in this format.
rater
(restaurant)(rating)
(restaurant)(rating)
(restaurant)(rating)
(restaurant)(rating)
(restaurant)(rating)
rater
(restaurant)(rating)
(restaurant)(rating)
(restaurant)(rating)
rater
(restaurant)(rating)
(restaurant)(rating)
....NOTE: A rater may not rate all of the restaurants. If they do not you should assign a rating of 0 to that restaurant, which means "not rated".
The call processdata(filename) must return two things:
itemlist a unique list of items (restaurants) being rated: [
"restaurant", "restaurant",
... ]
ratingsdict a dictionary of raters
and their ratings of the restaurants:
{"ratername" : [integer ratings for each restaurant],
"ratername" : [integer ratings for each restaurant], ...
}
The integer ratings will be in the same order as the list of
restaurants. For example, the first rating in the integer list of ratings for each rater will be for the first
restaurant in itemlist .
processdata( booktitles, bookratings ) : The
function must read data about books and raters and return the
information in a list and dictionary. (see
details)
The booktitles argument must be a txt
file of books like AllBooksAuthors.txt (supplied with the snarf or here) with each
book represented by two consecutive lines with the book title on one
line followed by the author on the next line. The format for the
book title line is a number, followed by a period followed by the book
title. The format of the author line is the same number, followed by
a period, followed by the authors name. The book titles and author
names are one or more words.
1.bookTitle
1.author
2.bookTitle
2.author
3.bookTitle
3.author
....
The bookratings argument must be a txt
file of raters like AllBooksRatings.txt (supplied with the snarf or here) with a
rater and their ratings spread over one or more lines. The format for
one rater is the word RATER, followed by a colon, followed by one or
more ratings on that line and possibly several other lines. Ratings
are separated by a colon, but there is no colon at the end of any
line. The word RATER is always the first word on any line. There will
be a rating for every book, with a 0 if the book has not been rated
by this rater.
RATER:ratername:rating:rating:rating:rating
rating:rating:rating:rating:rating:rating:rating
...
rating:rating:rating:rating
RATER:ratername:rating:rating:rating:rating:rating:rating:rating
rating:rating:rating:rating
...
rating:rating:rating:rating:rating:rating
RATER:ratername:rating:rating
rating:rating:rating:rating:rating:rating:rating:rating
...
rating:rating
....
The call processdata( booktitles, bookratings ) must return two things:
itemlist a unique list of books being rated (combine each
author and title into a string "title,author"
[
"title,author", "title,author",
... ]
raterdict a dictionary of raters
and their ratings of the books:
{"ratername" : [integer ratings for each book],
"ratername" : [integer ratings for each book], ...
}
The integer ratings will be in the same order as the list of
books. For example, the first rating in the integer list of ratings for each rater will be for the first
book in itemlist .
processdata( movieratings )
The movieratings argument must be a txt
file of movies like AllMoviesRatings.txt (supplied with the snarf or here) in the format
of one movie rating per three lines with three pieces of information:
ratername on the first line, movietitle on the second line and
rating on the third line.
Note that movietitles are one or more words. raternametitleratingraternametitleratingraternametitleratingThe processdata( movieratings ) must return two things:
itemlist a unique list of movies being rated: [
"title ", "title ",
"title ", ... ]
(see details and examples here)
ratingsdict a dictionary of raters and
their ratings of the movies:
{"ratername" : [integer ratings for each movie],
"ratername" : [integer ratings for each movie], ...
}
The integer ratings will be in the same order as the list of
movies. For example, the first rating in the integer list of ratings for each rater will be for the first
movie in itemlist .
Note that all three functions processdata for food, books
and movies, return the same types: a
list of strings (each item being rated) and a dictionary in which
keys are raters and values are lists of integer ratings by each rater.
In the module RecommenderForAll.py you must write the three
functions shown in the details pages:
averages, similarities, and
recommended. Each of these will be used for comparing
ratings of restaurants, movies and books in other programs, that is,
all three of these will be imported into other Python modules.
Here is briefly what each of these do, with more detail for each on the details page.
This is the main program for restaurant recommendations. It should read in the file of restaurant recommendations and then call processdata in ProcessAllFood.py to get the list of restaurants and the dictionary of raters and their ratings.
Then it will call the functions in RecommenderForAll to find out what the average rating is for each restaurant, find top raters who are similar to another rater, and give recommendations to a rater.
In particular, it should produce the following output. For all three make sure your output is easily identifiable and understandable.
AllFoodRatings.txt
averages).
similarities).
recommended).
This is the main program for book recommendations. It should read in the files of book recommendations and then call processdata in ProcessAllBooks.py to get the list of books and authors, and the dictionary of raters and their ratings.
Then it will call the functions in RecommenderForAll to find out what the average rating is for each book, find top raters who are similar to another rater, and give recommendations to a rater.
In particular, it should produce the following output. For all three make sure your output is easily identifiable and understandable.
AllBooksAuthors.txt and AllBooksRatings.txt .
averages).
similarities).
recommended).
This is the main program for movie recommendations. It should read in the file of movie recommendations and then call processdata in ProcessAllMovies.py to get the list of movies and the dictionary of raters and their ratings.
Then it will call the functions in RecommenderForAll to find out what the average rating is for each movie, find top raters who are similar to another rater, and give recommendations to a rater.
In particular, it should produce the following output. For all three make sure your output is easily identifiable and understandable.
AllMoviesRatings.txt
averages).
similarities).
recommended).