COMP SCI 2208

Practical 5

Introduction

Practical Exercises

Practical Exercises are designed to guide your learning by showing and directing you to relevant material whilst testing you on it. We remind you that work should be your own. You will learn nothing by using Copilot and ChatGPT and you are here to learn things!

There are six practical exercises, which take different forms but all have some aspect of taking what we talk about and making it real.

Part 1- Getting set-up & submitting your work

This semester you will be using preconfigured environments in the Visual Studio Code IDE called Development Containers to complete practical exercises that will bel integrated with the Gradescope submission system.

Let's get started:

Setup your development environment and access the files for this assignment:

Connect to GitHub Classroom to access your repository and configuration/starter files for this prac.

Clone your repository into your VSCode environment and open in a container

Guide

Connect to GitHub Classroom using this link https://classroom.github.com/a/xtCrssVUe

i. When prompted, log in with your GitHub credentials

ii. Select your student ID from the list. Contact your course coordinator if you can't find your student ID.

iii. Accept the assignment by clicking the button.

iv. This will create a new repository for your work; copy the link to this new repository.

Load the repository in VSCode

i. Open a new VSCode window.

ii. Select "Source Control" from the menu on the left

iii. Choose Clone Repository

iv. Select clone fron Github in the menu that appears at the top of the screen.

v. When prompted, Log in with your GitHub credentials

vi. Paste the link from 3 iii) above in the menu that appears at the top of the screen, and select the matching repository.

vii. When prompted, choose a location on your computer for the repository.

viii. When prompted, open the cloned repository.

Reopen the repository in a Dev Container

i. You should receive a prompt in the bottom-right corner to do this:

ii. If you didn't recieve a prompt, the open the Command Palette (view->Conmand Palette) and in the search box type Reopen, then select the option Dev Containers: Reopen in container.

iii. The container will load; this may take a few minutes the first time, or longer depending on your internet connection.

Part 2-Introduction and MongoDB Setup

Practical Scenario

In this exercise, you will transition from the world of relational databases (like MySQL) into the NoSQL paradigm using MongoDB. MongoDB is a popularl document-oriented NoSQL database that stores data in flexible, JSON-like documents instead of rigid tables. In MongoDB, related data can be embeddedl in a single record, and collections of documents do not require a fixed schema. This flexibility makes MongoDB suitable for scenarios where data structuresl may evolve or scale rapidly (e.g., social networks, big data applications).

Unlike MySQL, which uses structured tables and SQL queries, MongoDB allows you to retrieve and manipulate data with a Python driver (PyMongo) and dictionary-based queries.

When to Use NoSQL vs Relational

NoSQL databases like MongoDB excel when your application needs horizontal scalability, schema flexibility, or handling of large volumes of unstructured data. For example, a social media application with various post types and evolving features might benefit from MongoDB's dynamic schemas.

In contrast, relational databases are ideal when data is highly structured and relationships and transactions need strict enforcement (e.g., banking systems). In practice, many modern applications use a mix of both: relational for core transactional data and NoSQL for flexible or high-volume data.

In this assignment, we focus on MongoDB's strengths - flexible data modeling and quick iteration - in the context of a mini social network.

Scenario: SocialStream

We will build a simplified social media platform. called SocialStream. Users can create posts; other users can like and comment on those posts. We will design a MongoDB schema for this scenario and interact with it using Python. The goal is to make the assignment engaging and realistic, mirroring how a real social app might manage its data.

Environment Setup

You will work in a GitHub Codespaces development container which already has MongoDB (v6.0.6) and MongoDB Shell (mongosh v1.10.1) installed. The provided GitHub Classroom repository includes a starter code file (social_strean_starter.py) with skeleton code and TODO comments to guide you through each task.

Important: Ensure that the MongoDB service is running in the container. You must start it using the terminal:

service mongod start

We will use the PyMongo library to connect to MongoDB from Python - this is pre-installed in the container.

Working with the Starter Template:

Open social_strean_starter.py in your repository. This file contains:

TODO comments marking where you need to add your code

Example code snippets to guide your implementation

You should complete the TODO sections and add your own code where indicated. The template follows the structure of this practical guide, with clearly marked sections for each part.

Step 1: Establish a Connection

Use PyMongo to connect to the local MongoDB server. The default server runs on localhost at port 27017. 

In your Python script, add:

import pymongo

client - pymongo-Hongoclient("mongodb://localhost:27017/")

This creates a connection client to the MongoDB instance. (No username/password is needed for the default dev container setup.)

Verify the connection is successful by calling client.list database nanes() to retrieve a list of databases on the server and print it out. Initially, you may only see default databases like "admin", "config", "local".

Step 2: Select/Create a Database

Using the client, access a database for this lab. Let's call it social_network:

db-client social_network

In MongoDB, simply referencing client. social network is enough to select that database. (If it doesn't exist yet, it will be created when we first insert data.)

At this point, calling db. list_collection_names() wil likely return an empty list because we haven't created any collections in this database yet.

Step 3: Define Collection Objects

Within the social_network database, we will use multiple collections. Set up references to the collections we plan to use:

urorr coldh urors

nosts coldb.nosts

mments col = db.comments

This does not create any data yet, but prepares handles to the collections. The collections are lazily created- they will actually come into existence when we insert documents into them.

Step 4: (Optional) Test the Connection

It's a good idea to verify that everything is set up. You can print the result of client.server_info() or simply print users_col.count_documents(()) (which should be O at this point) to ensure no errors occur.

If you prefer using the Mongo shell, you could run mongosh and use show dbs (to show databases) or use social network and show collections to confirm the state. However, all required tasks can be done via PyMongo.

Checkpoint: If you encountered any connection issues, double-check that the MongoDB service is running in the container and that you used the correct connection URI. Once connected, proceed to the next part.