Twitter Replica Using Python and MongoDB

General Overview

This project simulates a basic Twitter-like functionality using Python and MongoDB. It is divided into two phases:

1. Building the Document Store:

   • Takes a JSON file as input and constructs a MongoDB collection.
   • Creates a database named 291db with a collection of tweets.
   • Requires the input of a JSON file name and the port number where the MongoDB server is running.

2. Operating the Document Store:

   • Connects to the 291db database.
   • Provides a menu-driven interface for users to interact with the database.
   • Features include:
     • Searching for tweets or users.
     • Listing top tweets and users based on specific metrics.
     • Composing new tweets.
     • Exiting the program.

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User Guide

Functionalities

1. Search for Tweets:

   • Input a keyword or multiple keywords to display a list of tweets containing the keywords.
   • Select a tweet by user ID to view its detailed information.
   • Quit the search by entering q.

2. Search for Users:

   • Input a keyword or multiple keywords to display users whose name contains the keywords.
   • Displayed information includes username, display name, and location.
   • Select a user by username to view detailed user data.
   • Quit the search by entering q.

3. List Top Tweets:

   • Select a field to rank tweets:
     • 1: retweetCount
     • 2: likeCount
     • 3: quoteCount
   • Specify the number of top tweets to display.
   • View details such as tweet ID, date, content, username, and the chosen metric.

4. List Top Users:

   • Enter a number n to display the top n users based on followersCount.
   • View details of a selected user by username.
   • Quit by entering q.

5. Compose a Tweet:

   • Enter the content of the new tweet.
   • Metadata (username: 291user, current date, other fields: zero or null) is automatically added.
   • Quit by entering q.

6. Logout:

   • Exit the program and return to the command line.

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Design

Phase 1: Load JSON

• load-json.py creates the 291db database with a tweets collection.
• Drops existing documents and populates the collection with data from the input JSON file.

Phase 2: Main Interface

• Provides a menu for six functionalities:
  1. Search for tweets.
  2. Search for users.
  3. List top tweets.
  4. List top users.
  5. Compose a tweet.
  6. Logout.
• Returns to the main menu after each functionality.

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Testing Strategy

Common Bugs and Solutions

• Input Bugs:

  • Tested various edge cases with capitalized letters, numbers, and special characters.
  • Used try and except clauses for invalid inputs.

• Formatting Bugs:

  • Adjusted output formatting to ensure proper display of information.

• Function Call Errors:

  • Verified function calls return to the correct sub-functions.

• Variable Bugs:

  • Ensured consistent variable usage when integrating different parts of the code.

• Manipulating Field Values:

  • Tested edge cases with extreme values for fields like followersCount.

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Group Work Strategy

Team Contributions

• Khym Nad:

  • Responsibilities: Search for users, load-json.py, documentation, testing.
  • Time Allocated: 10 hours.

• Akila Edirisinghe:

  • Responsibilities: Search for tweets, load-json.py, testing, documentation.
  • Time Allocated: 10 hours.

• Samuel Chan:

  • Responsibilities: List top tweets, load-json.py, documentation, testing.
  • Time Allocated: 10 hours.

• Andrew Zhang:

  • Responsibilities: List top users, compose tweet, load-json.py, documentation, testing.
  • Time Allocated: 10 hours.

Coordination

• Conducted on-campus meetings for collaborative debugging and integration.
• Used a Discord group chat for updates and discussions.

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Requirements

Software

• Python 3.x
• MongoDB server