Academic Dishonesty Disclaimer
All of the work you submit must be done by you, and your work must not be submitted by someone else. Plagiarism is academic fraud and is taken very seriously. The department uses software that compares programs for evidence of similar code. Please read the Rules and Regulations from the U of T Governing Council (especially the Code of Behaviour on Academic Matters).
Please don’t copy. We want you to succeed and are here to help. Here are a couple of general guidelines to help you avoid plagiarism:
Never look at another assignment solution, whether it is on paper or on the computer screen. Never show another student your assignment solution. This applies to all drafts of a solution and to incomplete solutions. If you find code on the web that solves part or all of an assignment, do not use or submit any part of it! A large percentage of the academic offenses in CS involve students who have never met, and who just happened to find the same solution online. If you find a solution, someone else will too. The easiest way to avoid plagiarism is to only discuss a piece of work on the course discussion board, with the CSC108H TAs in the open labs, or the CSC108H instructors in office hours.
Assignment 3
Please read this document very carefully. Follow instructions exactly. If you have any questions please post them to the course Piazza page.
This assignment is due December 5th, by 10:00pm
Imagine you work for a social media company named ‘Chirper.’ On this social media platform users have profiles and publish relatively short text messages for other users to read, like, and/or dislike; these messages are referred to as chirps. You are tasked with implementing functions which parse and manipulate the data of this social network platform. You are given a file, assignment3.py, with five incomplete functions. For this assignment, you are required to complete these func- tions. A description regarding the intended behaviour of these functions follows.
Note: One potential difficulty of this assignment is to realize how the data is stored and what it represents. Pay close attention to the input and returns types of each function.
To give you a better idea to how the social platform works, here are some summary points and definitions.
- A chirp is string (like a message). A chirp may also have tags associated with it which users can add. These tags have %’s in front of them, do not include white space or other %’s in them. For example, a chirp may be: ‘Nothing on the midterm was taught in lecture! %MAT102 %Unfair %ShouldHaveGoneToWaterloo’ Valid tags are: %2EZ, %my cute cat, %EarnDat$$$, etc. Invalid tags are: %my cute cat, %The99%, my tag, etc.
- Each Chirper user has a set of profiles they follow, and a set of profiles which follow them. If User 1 follows User 2, it does not necessarily mean User 2 follows User 1.
- A profiles dictionary is of the type Dict[int, Tuple[str, List[int], List[int]]]; profiles dictionary is used as a shorthand for this type in the function descriptions later in this document. The keys of a profiles dictionary are unique integers representing user id numbers. The profiles dictionary values contain the profile information corresponding
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to the specific user id number given as the key. The values are Tuples, where the first element of the list is the corresponding user name, the second element is a list of user ids representing the user’s followers (the user id given as the key), and the third element is a list of user ids that the user in question is following.
4. A chirp dictionary is of the type Dict[int, Tuple[int, str, List[str], List[int], List[int]]]; chirp dictionary is used as a shorthand for this type in the function descrip- tions later in this document. The keys of a chirp dictionary are unique integers representing chirp id numbers. The chirp dictionary values contain the chirp information corresponding to the specific chirp id number given as the key. The values are Tuples. The first element of the list is the user id chirp’s author. The second element is the chirp itself. The third element is a list of tags associated with the chirp. The forth element is a list of user ids which liked the chirp. And the fifth element is a list of user ids which disliked the chirp.
Functions
You are required to implement all of the following functions. Pay attention to parameters of each function. For example, if it is said an input will be a Dict[int, str], you can trust your function will never be tested on input which isn’t a Dict[int, str]. For further examples of how these functions are intended to operate, view the docstrings of the starter code for this assignment.
1. create_profile_dictionary(str) -> profiles_dictionary
The input parameter is the name of a text file containing all of Chirper’s profile information.
You may assume the file is in the same directory as assignment3.py. The file is a series of
profile data, where data for each profile has the following format:
USERID
USERNAME
FOLLOWER1, FOLLOWER2, ..., FOLLOWERn
FOLLOWED1, FOLLOWED2, ..., FOLLOWEDm
where USERID, FOLLOWERi, and FOLLOWEDj are all unique numbers. The third line represents the users which follow USERNAME, and the forth line represents the users which USERNAME fol- lows. In the text file there is always a blank-line between different profiles. See profiles.txt as an example.
Based off this data, the function constructs a profiles_dictionary where the orders of the ids representing followers and users follows, are the same orders as which they appear in the text file. See the doctstring and profiles.txt for further clarification. Assume that the given text file is perfect and that there are no formatting errors.
2. create_chirp_dictionary(str) -> chirp_dictionary
The input parameter is the name of a text file containing all of Chirper’s message information.
You may assume the file is in the same directory as the as assignment3.py. The file is a series
of message data, where data for each message has the following format:
CHIRPID
USERID
MESSAGE
TAG1, TAG2, ..., TAGk
LIKED1, LIKED2, ..., LIKEDn
DISLIKED1, DISLIKED2, ..., DISLIKEDm
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where CHIRPID, USERID, LIKEDi, and DISLIKEDj are all unique numbers. USERID is the id of the user which made the chirp. The third line is the chirp itself. The forth line represents a list of tags associated with said chirp. The fifth line is a sequence of user ids which liked the chirp. The sixth line is a sequence of user ids which disliked the chirp. In the text file there is always a blank-line between different chirps. See chirps.txt as an example.
Based off this data, the function constructs a profiles_dictionary where the orders of the tags and ids representing likes and dislikes, are in the same orders in which they appear in the text file. If there are no tags associated with a chirp, the empty string is associated with it instead. See the doctstring and chirps.txt for further clarification. Assume that the given text file is perfect and that there are no formatting errors.
3. get_top_chirps(profile_dictionary, chirp_dictionary, int) -> List[str]
The third parameter is a user id which is in the given profile_dictionary. Let the user with
this user id be denoted by u. The function uses the data from the first two parameters to find
the chirp with the most likes for each user followed by u. The function creates a list of these
chirps and returns it. You may assume:
(a) For a given user, there does not exist any two chirps with the same number of likes.
(b) The order of the chirps in the returned list is arbitrary. As long as all the correct chirps are present and no incorrect chirps are present, the function is correct.
See the docstring for examples.
4. create_tag_dictionary(chirp_dictionary) -> Dict[str, Dict[int, List[str]]] Takes in a chirp_dictionary and creates a new dictionary. In the new dictionary, tags are keys, the values are dictionaries where the keys in these dictionaries are user ids, and the values of these dictionaries are chirps made by the corresponding user, which also had the corresponding tag. See the docstring for examples.
5. get_tagged_chirps(chirp_dictionary, str) -> List[str]
Takes in a chirp_dictionary and a tag, and returns a list which contains a list of all the
chirps which had said tag on them. The order of the returned list is arbitary, as long as all
the correct chirps are present and no incorrect chirps are present, the function is correct. See
the docstring for examples.
Submitting and Grading
This assignment will be submitted electronically via MarkUs. Please find the MarkUs link on the course website. Your submitted file must have the name assignment3.py, or you will receive 0.
This assignment is worth 10% of your final grade. Grading is done completely automatically. That is, a program calls your function, passes it certain arguments, and checks to see if it returns the expected output. Each function is worth 20% of assignment grade. For any one function, if you pass n of the m tests we run on that function, your grade for that function will be n/m.
Shortly after the deadline, you will receive your grade. If you are not content with this grade, you may resubmit your assignment up to 48 hours after the original deadline with a 20% penalty. If you choose to resubmit, your final grade on the assignment will be the higher of the two grades (the original submission, and the re-submission with a 20% penalty). Good luck!
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