pydbmanager 0.1.2

A Python package for seamless SQL Server database management, supporting secure connections, query execution, batch fetching, caching, and result exporting.

📌 PyDBManager - SQL Server Database Manager

Welcome to PyDBManager – a Python package for managing SQL Server connections and queries easily and efficiently! 🎯

This guide will help you:

• ✅ Install PyDBManager
• ✅ Set up your .env file for credentials
• ✅ Perform SQL operations using Python
• ✅ Save query results
• ✅ Use caching & batch fetching

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1. Install PyDBManager

Run the following command to install PyDBManager:

pip install pydbmanager

If installation is successful, continue to the next step!

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2. Create .env File to Store Database Credentials

To avoid hardcoding credentials, create a .env file in your project directory.

Steps

1. Create a .env file in your project root.
2. Add the following credentials (update as needed):

   DB_SERVER=localhost
   DB_DATABASE=your_database_name
   DB_USERNAME=your_username
   DB_PASSWORD=your_password
   DB_DRIVER={ODBC Driver 17 for SQL Server}
   

3. Ensure .env is ignored by Git (Add .env to .gitignore).
4. Verify that .env loads correctly (Next step).

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3. Verify .env File

Run this script to check if the values are loaded correctly:

import os
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

print("\u2705 Database Configuration Loaded:")
print(f"SERVER: {os.getenv('DB_SERVER')}")
print(f"DATABASE: {os.getenv('DB_DATABASE')}")
print(f"USERNAME: {os.getenv('DB_USERNAME')}")
print(f"PASSWORD: {'*' * len(os.getenv('DB_PASSWORD')) if os.getenv('DB_PASSWORD') else 'Not Set'}")
print(f"DRIVER: {os.getenv('DB_DRIVER')}")

Expected Output

Database Configuration Loaded:
SERVER: localhost
DATABASE: testDB
USERNAME: your_username
PASSWORD: **********
DRIVER: {ODBC Driver 17 for SQL Server}

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4. Connect to the Database

from pydbmanager.connection import DatabaseConnection

# Initialize and test database connection
db = DatabaseConnection()
conn = db.create_connection()

if conn:
    print("\u2705 Connection Successful!")
    db.close_connection()
else:
    print("\u274c Connection Failed!")

Expected Output

Connection Successful!

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5. Perform SQL Operations

🔹 Fetch All Users

from pydbmanager.operations import DatabaseOperations

db_ops = DatabaseOperations()

# Fetch all users
df = db_ops.query_data("SELECT * FROM users", batch_size=5)
df

Expected Output → A pandas DataFrame displaying user data.

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🔹 Insert a New Record

insert_query = """
INSERT INTO users (name, email, age, gender, phone_number, address, city, country)
VALUES ('John Doe', '[e-mail]', 29, 'Male', '123-456-7890', '123 Elm St', 'New York', 'USA')
"""
db_ops.execute_query(insert_query)
print("\u2705 User inserted successfully!")

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🔹 Update a Record

update_query = """
UPDATE users SET age = 30 WHERE email = '[e-mail]'
"""
db_ops.execute_query(update_query)
print("\u2705 User updated successfully!")

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🔹 Delete a Record

delete_query = """
DELETE FROM users WHERE email = '[e-mail]'
"""
db_ops.execute_query(delete_query)
print("\u2705 User deleted successfully!")

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6. Saving Query Results

🔹 Save Data to CSV

db_ops.save_results(df, "users_data.csv", "csv")
print("\u2705 Data saved to users_data.csv")

📁 Check your project folder for users_data.csv

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7. Using Caching & Batch Fetching

🔹 Query with Caching

df_cached = db_ops.cached_query("SELECT * FROM users")
df_cached

🔹 Query with Batch Fetching

df_batch = db_ops.query_data("SELECT * FROM users", batch_size= 10)
df_batch

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🔹 Closing Connection

db_ops.close()
print("\u2705 Database connection closed.")

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✅ Congratulations! 🎉

You’ve successfully used PyDBManager for:

• Connecting to SQL Server
• Running SQL queries in Python
• Fetching, inserting, updating & deleting data
• Using caching & batch fetching
• Saving results to a file

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🚀 Contributing & License

I welcome contributions! Feel free to submit issues and pull requests. 🛠️

This project is MIT Licensed — you are free to modify and distribute it as needed. 🏆

🔥 Happy Coding! 🚀