SQL with Python
Connect, Query, and Automate School Data

Introduction

What if your Python program could directly talk to your school database? Whether it’s fetching a student’s marks, generating reports, or inserting attendance records — integrating SQL with Python makes it possible. This tutorial shows how to use SQL inside Python using both SQLite and MySQL with real-life school examples.

Why Use SQL with Python?

• Automate data entry and reporting
• 🔍 Query large datasets with SQL’s power
• 🤖 Build school applications like report cards, dashboards, or fee trackers

Getting Started: SQLite with Python

Step 1: Import sqlite3

import sqlite3

Step 2: Connect to a database

conn = sqlite3.connect("school.db")
cursor = conn.cursor()

Step 3: Create a table

cursor.execute("""
CREATE TABLE IF NOT EXISTS students (
  roll_no INTEGER PRIMARY KEY,
  name TEXT,
  class TEXT,
  city TEXT
)
""")
conn.commit()

Step 4: Insert student data

cursor.execute("INSERT INTO students (roll_no, name, class, city) VALUES (?, ?, ?, ?)", 
               (1, 'Aarav', '10A', 'Pune'))
conn.commit()

Step 5: Query the data

cursor.execute("SELECT * FROM students")
rows = cursor.fetchall()

for row in rows:
    print(row)

(1, 'Aarav', '10A', 'Pune')

Using MySQL with Python (via mysql-connector-python)

Step 1: Install package

pip install mysql-connector-python

Step 2: Connect to MySQL server

import mysql.connector

conn = mysql.connector.connect(
    host="localhost",
    user="root",
    password="your_password",
    database="school"
)
cursor = conn.cursor()

Step 3: Fetch student marks

cursor.execute("SELECT name, marks FROM marks WHERE subject = 'Maths'")
results = cursor.fetchall()

for name, marks in results:
    print(f"{name} scored {marks} in Maths")

Aarav scored 90 in Maths  
Diya scored 85 in Maths

Parameterized Queries to Avoid SQL Injection

name = "Aarav"
cursor.execute("SELECT * FROM students WHERE name = %s", (name,))
print(cursor.fetchall())

Real-World School Use Cases

• Auto-inserting daily attendance from a CSV file
• 📑 Generating report cards and emailing them to parents
• Bulk importing exam scores
• Visualizing student performance using matplotlib + SQL

Best Practices

• Always close your DB connection with conn.close()
• Use try/except for error handling
• Never use plain strings to insert values — always parameterize

Summary

Integrating SQL with Python unlocks automation, analytics, and application building at a whole new level. Whether you’re building a student tracker or a dynamic marks dashboard, Python + SQL is a powerful duo — especially for managing and visualizing school data.

What’s Next?

Next: SQL Interview Questions — master real-world SQL scenarios and test your knowledge.