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https://github.com/tinovimba-hove/datadrivenapplication-python-mysql
A hotel management system built with Python, featuring a user-friendly UI and MySQL database integration. The app provides comprehensive functionality for managing users, rooms, reservations, and rewards. Designed for efficiency and ease of use, it streamlines hotel operations with robust data handling and an intuitive interface.
https://github.com/tinovimba-hove/datadrivenapplication-python-mysql
Last synced: 3 days ago
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A hotel management system built with Python, featuring a user-friendly UI and MySQL database integration. The app provides comprehensive functionality for managing users, rooms, reservations, and rewards. Designed for efficiency and ease of use, it streamlines hotel operations with robust data handling and an intuitive interface.
- Host: GitHub
- URL: https://github.com/tinovimba-hove/datadrivenapplication-python-mysql
- Owner: Tinovimba-Hove
- Created: 2024-12-23T19:10:26.000Z (3 days ago)
- Default Branch: main
- Last Pushed: 2024-12-23T19:22:51.000Z (3 days ago)
- Last Synced: 2024-12-23T20:28:31.730Z (3 days ago)
- Language: HTML
- Size: 188 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# DataDrivenApplication-Python-MySQL
### Authors
- Isabelle Crow
- Tinovimba Hove
## Narrative
We developed a __Hotel Reservation System__ to streamline the process of booking, managing, and analyzing hotel reservations. This system is designed to offer a user-friendly experience for both customers and administrators. Key features include real-time room availability tracking, a customer loyalty rewards program, and administrative tools to oversee operations and review analytics.
### Primary Use Cases
- __Managing Hotel Room Bookings__: Facilitate the entire reservation process, from searching for available rooms to confirming bookings.
- __User Management__: Provide tailored access for customers and administrators based on their roles.
- __Room Availability Tracking__: Ensure real-time updates on room status to enable informed booking decisions.
- __Rewards System__: Promote customer loyalty by allowing customers to earn and redeem points for rewards, such as free nights or room upgrades.
### User Roles
- __Admin__:
- Manage hotel operations, including room inventory and booking statuses.
- Access analytics via the dashboard to monitor revenue, occupancy rates, and other performance metrics.
- __Customer__:
- Search for available rooms and make reservations.
- Earn points for reservations and redeem them for rewards, enhancing customer loyalty and engagement.
## ER Diagram
## Relational Schema
## Custom SQL Queries
### Transactional
These SQL queries support core reservation operations, including availability checks, room status updates, and daily status maintenance:
__Availability Check__
The following query is used to determine whether a room is available for the requested dates:
```{python}
sql = """
SELECT COUNT(*)
FROM hotel_reservations
WHERE room_id = %s AND %s <= check_out_date AND %s >= check_in_date;
"""
```
__Room Status Updates__
Once a reservation is made, we execute two key SQL statements to update the status of the room:
1. Check if a room is currently booked:
```{python}
sql = """
SELECT COUNT(*)
FROM hotel_reservations
WHERE room_id = %s AND CURRENT_DATE BETWEEN check_in_date AND check_out_date;
"""
```
*Note: Additional intermediate code has been omitted for clarity.*
2. Update room status after a booking:
```{python}
sql_update = """
UPDATE hotel_rooms
SET status = %s
WHERE id = %s;
"""
```
__Daily Status Cleanup__
To ensure the room status remains accurate, this query updates the status of rooms based on the current date:
```{python}
sql = """
UPDATE hotel_rooms
SET status = 'Available'
WHERE id IN (
SELECT room_id
FROM reservations
WHERE CURRENT_DATE > check_out_date
);
"""
```
### Analytical
The following SQL statements are integral to the `getReservationStats()` function in the reservations class, providing key insights into booking trends and customer behavior:
__Payment Method Analysis__
To understand the most popular payment methods, we use this query:
```{python}
sql_payment_method = """
SELECT payment_method, COUNT(*) AS reservation_count
FROM hotel_reservations
GROUP BY payment_method
ORDER BY reservation_count DESC
"""
```
__Reservation Amount Distribution__
This query segments the distribution of reservation amounts into defined ranges:
```{python}
sql_amount_ranges = """
SELECT
CASE
WHEN amount <= 1000 THEN '0-1000'
WHEN amount BETWEEN 1000 AND 2000 THEN '1000-2000'
ELSE '2000+'
END AS amount_range,
COUNT(*) AS total_reservations
FROM hotel_reservations
GROUP BY amount_range
"""
```
__Points Earned Per Customer__
To track customer engagement through loyalty points, we run this query:
```{python}
sql_points_gained = """
SELECT uid, SUM(points_gained) AS total_points
FROM hotel_reservations
GROUP BY uid
ORDER BY total_points DESC
"""
```
__Average Spending by Payment Method__
To evaluate spending patterns, we use this query to find the average amount spent per payment method:
```{python}
sql_avg_spending = """
SELECT payment_method, AVG(amount) AS average_amount
FROM hotel_reservations
GROUP BY payment_method
"""
```