Step by step guide for Python Microservices with SQL Server for Hotel Management

In the current digital world, micro service plays an important role in building a system that can be discussed and maintained.

This blog shows how to create Python Microservices with SQL Server To manage hotel data such as guest names, room types, check-in/check-out dates, and room numbers.

🧱 Used technology piles

• Python (Flask for Microservice Framework)

• Microsoft SQL Server (Relational DB)

• SQL Server Management Studio (Admin DB)

🎯 Project Objectives

We aim to make a simple restful Python Microservice Integrated with SQL Server who do:

🛠️ Steps to build Python Micro Services

1. Database settings on SQL Server

Create a new table on SQL Server to store hotel data.

SQL

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Create a Hotel Table (
ID primary key id identity id (1,1),
Guestname Varchar (100),
Roomtype Varchar (50),
checkindate date,
Checkoutdate date,
Roomnumber Int
);

2. Python Microservice Code With Flask

This is the complete code that must be implemented Python Microservices with SQL Server:

Python

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From Flask Import Flask, Demand, Jsonify
Import Pyodbc

App = Flask (__ Name__)

SQL Server Connection String
Conn_str = (
“Driver = {ODBC Driver 17 for SQL Server};”
“Server = Localhost \\ ‘SQLEXPRESS;” # Update with your server name
“Database = HotelDB;” # Update with your DB name
“Trusted_connection = Yes;”
)

# Create Hotel Notes
@app.route (‘/hotel’, method =[‘POST’])
def create_hotel ():
data = request.json
Conn = pyodbc.connect (conn_str)
cursor = Conn.Cursor ()
cursor.execute (“”
Put it to the hotel (guest name, roomtype, checkindate, checkoutdate, roomnumber)
Mark (?,?,?,?,?)
“” “, Data[‘guestName’]data[‘roomType’]data[‘checkInDate’]data[‘checkOutDate’]data[‘roomNumber’])
Conn.commit ()
Conn.Close ()
Return Jsonify ({‘message’: ‘Hotel Record Made’}), 201

# Get all the hotel notes
@app.route (‘/hotel’, method =[‘GET’])
Def Get_hotels ():
Conn = pyodbc.connect (conn_str)
cursor = Conn.Cursor ()
Cursor.execute (“select * from hotel”)
hotel = cursor.fetchall ()
Results = []
For lines at the hotel:
result.append ({
‘id’: row.id,
‘Guestname’: row.gestname,
‘Roomtype’: row.roomtype,
‘Checkindate’: row.checkindate.strfime (“%y-%m-%D”),
‘Checkoutdate’: row.checkoutdate.strfime (“%y-%m-%D”),
‘Roomnumber’: row.roomnumber
})
Conn.Close ()
Return jsonify (results)

# Update Hotel Notes
@app.route (‘/hotel/‘, Method =[‘PUT’])
def update_hotel (ID):
data = request.json
Conn = pyodbc.connect (conn_str)
cursor = Conn.Cursor ()
cursor.execute (“”
Renew the hotel
Set guestname =?, Roomtype =?, Checkindate =?, Checkoutdate =?, Roomnumber =?
Where is id =?
“” “, Data[‘guestName’]data[‘roomType’]data[‘checkInDate’]data[‘checkOutDate’]data[‘roomNumber’]identification)
Conn.commit ()
Conn.Close ()
Return Jsonify ({‘message’: ‘Updated Hotel Record’})

# Delete Hotel Notes
@app.route (‘/hotel/‘, Method =[‘DELETE’])
def delete_hotel (ID):
Conn = pyodbc.connect (conn_str)
cursor = Conn.Cursor ()
Cursor.execute (“Delete from the hotel where id =?”, ID)
Conn.commit ()
Conn.Close ()
Return Jsonify ({‘message’: ‘Hotel Record Deleted’})

if __name__ == ‘__main__’:
app.run (debug = true)

🔍 Test Microservice Python

Use a postman to test the end point of the fire:

• POST /Hotel → Create a new note

• GET /Hotel → See all notes

• PUT /Hotels/{id} → update notes

• DELETE /hotel/{id} → delete notes

🧠 Why use Python Microservices with SQL Server?

• Scalability: Breaking Monolithic Applications into Independent Micro Services.

• Database power: SQL Server handles relational data efficiently and safely.

• Python integration: Libraries such as pyodbc make it easy to connect Python services with SQL Server.

• Easy testing: Calm architecture makes it easy to be tested and debug.

🧩 Using cases in the hotel industry

• Manage orders and reservations

• Handling Check-In/Guest Check-In Operations

• Integrate the hotel system with the CRM platform

• Tracking and analysis of the availability of real time

🏁 Conclusion

Use Python Microservices with SQL ServerYou can create a modular system, can be maintained, and can be discussed for hotel data management. This architecture allows flexibility and ensures the reliability of the company’s class. Whether you are building a hotel CRM or ordering machine, this setting is strong and ready for production.

Additional resources: