Project: Building Maintenance System 🏗️🛠️

Welcome to your Capstone Project! 🎓

This module brings together everything you've learned:

Agile: Planning what to build.
Python: Writing the logic.
AI: Using your Copilot to build faster and better.

The Mission: You are a Junior Developer at "PropTech Solutions". Your boss wants a quick MVP (Minimum Viable Product) for a system to track maintenance requests (e.g., "Broken heater in Apt 3B").

Phase 1: Agile Planning (The Blueprint) 📝

Integration: Agile Requirements | AI Design

1.1 The Scenario

It's Monday morning. Your Product Manager, Sarah, rushes in. "We have tenants complaining that their repair requests are getting lost in emails. We need a central list. Tenants report, Managers fix. Go!"

This is vague. If you code now, you will build the wrong thing.

1.2 From Vague Idea to User Stories

Your Task: Use AI to turn Sarah's vague request into clear User Stories.

Prompt:

"Act as a Product Manager. I need to build a 'Building Maintenance System' MVP. Break down the vague requirement 'Tenants report issues, Managers fix them' into 3 specific User Stories. Follow the format: 'As a [User], I want [Action], so that [Value]'."

The Backlog (Your Agile Board):

ID	User Story	Priority	Status
US-1	As a Tenant, I want to submit a request, so that my issue gets fixed.	High	To Do
US-2	As a Manager, I want to view pending requests, so I know what to work on.	High	To Do
US-3	As a Manager, I want to mark requests as 'Completed', so we don't duplicate work.	Medium	To Do

1.3 Designing the Data Structure

We aren't using a SQL database yet. We'll use a Python List of Dictionaries.

Prompt:

"I am building a Python script for maintenance requests. Design a dictionary structure for a single request. It needs: ID, Apartment Number, Description, Status (Pending/Done), and Priority."

The Blueprint:

python

# Our "Database" is just a list in memory
requests_db = [
    {
        "id": 1,
        "apt": "3B",
        "description": "Leaky faucet",
        "status": "Pending",
        "priority": "Normal"
    }
]

Phase 2: The Core Logic (Python + AI) 💻

Integration: Pair Programming | Python Functions

We will build the logic in a file called maintenance.py.

2.1 The Skeleton Builder

Don't write the full code yet. Ask AI for the structure.

Prompt:

"Create a Python file structure for maintenance.py. Write empty functions (with pass) and docstrings for:
add_request(db, apt, description)
get_pending_requests(db)
mark_completed(db, request_id) Don't implement the logic yet."

2.2 Implementing with "Driver Mode"

Now, you drive. You know Python lists and dicts. Fill in the functions.

Your Code (Draft):

python

def add_request(db, apt, description):
    new_id = len(db) + 1
    req = {
        "id": new_id,
        "apt": apt,
        "description": description,
        "status": "Pending",
        "priority": "Normal"
    }
    db.append(req)
    return req

AI Assist: If you get stuck on how to filter the list for pending requests, ask:

"How do I filter a list of dictionaries in Python to only show ones where status is 'Pending'?"

Phase 3: The CLI Interface (Interaction) 💬

Integration: Python Loops | Prompt Engineering

The logic needs a user interface. We'll build a simple command-line tool (main.py).

Prompt:

"Write a main.py script that acts as the interface. It should import maintenance. Use a while True loop to show a menu:
Report Issue
View Jobs
Finish Job
Exit
Use input() to get user choices. Call the functions from maintenance.py."

Phase 4: Refactoring & Intelligence ✨

Integration: Refactoring

4.1 Auto-Priority (AI Logic)

Let's make the system smart. If the user types "Fire" or "Flood", priority should be "High".

Prompt:

"Write a helper function calculate_priority(text). If the text contains urgent words like 'fire', 'leak', 'gas', return 'High'. Otherwise, return 'Normal'. Update my add_request function to use this."

4.2 Making it Persistent (Saving Data)

Right now, data vanishes when the script stops.

Prompt:

"Refactor maintenance.py to save the list to a requests.json file.
Write a save_data(db) function using the json module.
Write a load_data() function that returns the list from the file (or an empty list if file missing)."

Phase 5: Quality Assurance (Testing) 🧪

Integration: Tests & Docs

You can't ship code without testing it.

5.1 Unit Tests

Prompt:

"Write 3 pytest test cases for add_request.
Test adding a normal request.
Test that the ID increments correctly.
Test that priority is set to 'High' for urgent keywords."

5.2 Manual "Smoke Test"

Run your CLI. Try to break it.

Enter text when it asks for a number.
Try to complete a request ID that doesn't exist.

Prompt:

"I get a ValueError when I type 'apple' instead of a Request ID. How do I handle this with try/except in my main.py loop?"

Phase 6: Deployment (Going Live) 🚀

A CLI is cool, but a Web API is better.

6.1 The Flask Wrapper

We will wrap our Python functions in a tiny web server using Flask.

Prompt:

"I have maintenance.py. Create a simple app.py using Flask.
GET /requests: Returns the list from get_pending_requests.
POST /requests: Takes JSON input and calls add_request."

6.2 Deploying to Render.com

Requirements: Ask AI "Generate a requirements.txt for this Flask app."
Git: Push your code to GitHub.
Render: Connect your repo. Render detects the Python app and deploys it.

Result: You now have a live URL (e.g., https://my-proptech-app.onrender.com) that you can send to your "Manager"!

Appendix: The Full Code Solution 🧩

Stuck? Here is the complete working code for the CLI version.

`maintenance.py`

python

import json
import os

DB_FILE = "requests.json"

def load_data():
    if not os.path.exists(DB_FILE):
        return []
    with open(DB_FILE, "r") as f:
        return json.load(f)

def save_data(db):
    with open(DB_FILE, "w") as f:
        json.dump(db, f, indent=4)

def calculate_priority(description):
    urgent_words = ["fire", "leak", "gas", "flood", "broken", "danger"]
    for word in urgent_words:
        if word in description.lower():
            return "High"
    return "Normal"

def add_request(db, apt, description):
    new_id = len(db) + 1
    priority = calculate_priority(description)
    req = {
        "id": new_id,
        "apt": apt,
        "description": description,
        "status": "Pending",
        "priority": priority
    }
    db.append(req)
    save_data(db)
    return req

def get_pending_requests(db):
    return [r for r in db if r["status"] == "Pending"]

def mark_completed(db, request_id):
    for req in db:
        if req["id"] == request_id:
            req["status"] = "Completed"
            save_data(db)
            return True
    return False

`main.py`

python

import maintenance

def main():
    db = maintenance.load_data()
    
    while True:
        print("\n=== PropTech Maintenance System ===")
        print("1. Report Issue")
        print("2. View Pending Jobs")
        print("3. Mark Job Completed")
        print("4. Exit")
        
        choice = input("Select an option: ")
        
        if choice == "1":
            apt = input("Apartment Number: ")
            desc = input("Issue Description: ")
            req = maintenance.add_request(db, apt, desc)
            print(f"✅ Request #{req['id']} added with {req['priority']} priority.")
            
        elif choice == "2":
            pending = maintenance.get_pending_requests(db)
            print(f"\nThere are {len(pending)} pending jobs:")
            for req in pending:
                print(f"[ID: {req['id']}] {req['apt']}: {req['description']} ({req['priority']})")
                
        elif choice == "3":
            try:
                req_id = int(input("Enter Request ID to finish: "))
                if maintenance.mark_completed(db, req_id):
                    print("✅ Job marked as completed.")
                else:
                    print("❌ ID not found.")
            except ValueError:
                print("❌ Please enter a valid number.")
                
        elif choice == "4":
            print("Goodbye!")
            break
        else:
            print("Invalid choice, try again.")

if __name__ == "__main__":
    main()

Congratulations! You have built a full-stack Python application using an AI-Assisted workflow. 🚀

Project: Building Maintenance System 🏗️🛠️ ​

Phase 1: Agile Planning (The Blueprint) 📝 ​

1.1 The Scenario ​

1.2 From Vague Idea to User Stories ​

1.3 Designing the Data Structure ​

Phase 2: The Core Logic (Python + AI) 💻 ​

2.1 The Skeleton Builder ​

2.2 Implementing with "Driver Mode" ​

Phase 3: The CLI Interface (Interaction) 💬 ​

Phase 4: Refactoring & Intelligence ✨ ​

4.1 Auto-Priority (AI Logic) ​

4.2 Making it Persistent (Saving Data) ​

Phase 5: Quality Assurance (Testing) 🧪 ​

5.1 Unit Tests ​

5.2 Manual "Smoke Test" ​

Phase 6: Deployment (Going Live) 🚀 ​

6.1 The Flask Wrapper ​

6.2 Deploying to Render.com ​

Appendix: The Full Code Solution 🧩 ​

maintenance.py ​

main.py ​

Project: Building Maintenance System 🏗️🛠️

Phase 1: Agile Planning (The Blueprint) 📝

1.1 The Scenario

1.2 From Vague Idea to User Stories

1.3 Designing the Data Structure

Phase 2: The Core Logic (Python + AI) 💻

2.1 The Skeleton Builder

2.2 Implementing with "Driver Mode"

Phase 3: The CLI Interface (Interaction) 💬

Phase 4: Refactoring & Intelligence ✨

4.1 Auto-Priority (AI Logic)

4.2 Making it Persistent (Saving Data)

Phase 5: Quality Assurance (Testing) 🧪

5.1 Unit Tests

5.2 Manual "Smoke Test"

Phase 6: Deployment (Going Live) 🚀

6.1 The Flask Wrapper

6.2 Deploying to Render.com

Appendix: The Full Code Solution 🧩

`maintenance.py`

`main.py`