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SQLiteX33

📋 Overview

SQLiteX33 is a lightweight and streamlined context manager for SQLite databases in Python.
It simplifies the process of running SQL queries and ensures best practices such as committing transactions and closing connections.

🌟 Features

  • Seamless SQLite Connection Management: Easily manage SQLite database connections without the hassle.
  • External Execute Function: Provides a handy external function to execute SQL commands, making it easier to integrate into other modules.
  • Foreign Key Support: Automatically enables FOREIGN KEYS for SQLite 3 out of the box.
  • Dictionary-like Row Access: Results are returned as Row objects, allowing access by column name (e.g., row['name']).
  • Query Parameterization: Support for parameterized queries to prevent SQL injection and handle data types properly.
  • Batch Operations: Efficiently execute the same query with multiple parameter sets using SQLite's executemany functionality.

⚙️ Installation

🛠️ Prerequisites

  1. 🐍 Python: SQLiteX33 is a Python context manager. Ensure you have Python installed on your system. You can download it from Python's official website.

  2. 🖋️ IDE: For code editing, VS Code (Visual Studio Code) is recommended. Enhance your Python experience by adding the Python extension.

  3. 🔍 SQLite Extension (Optional): For easier overview and editing of SQLite databases, it's good to have an SQLite extension. @yy0931's SQLite3 Editor for VSCode is highly recommended.

⬇️ Steps

To set up SQLiteX33 in your project:

  1. Download: Download the sqlite_x33.py file from this repository.

  2. Place in Project Directory: Move the sqlite_x33.py file to the root directory of your Python project, or where you plan on using SQLiteX33.

  3. Import and Use: Follow the usage instructions below to get started with SQLiteX33.


🚀 Usage

1. Import the Python Module

To use SQLiteX33, first import the module in your Python script:

import sqlite_x33 as sql

2. Using the Context Manager

Fetching Data (all)

result = sql.execute("path_to_db.db", "SELECT * FROM table_name")

Fetching Data (specific)

result = sql.execute("path_to_db.db", "SELECT * FROM table_name WHERE column1 = ?", ('value1',))

Accessing Results by Column Name

rows = sql.execute("path_to_db.db", "SELECT column1, column2 FROM table_name")
for row in rows:
    print(f"Column1: {row['column1']}, Column2: {row['column2']}")

Inserting Data (single query)

sql.execute("path_to_db.db", "INSERT INTO table_name (column1, column2) VALUES (?, ?)", ('value1', 'value2'))

Inserting Data (batch query)

customers = [
    ['John Smith', '[email protected]', '2023-05-15'],
    ['Sarah Johnson', '[email protected]', '2023-05-16']
]

rows_affected = sql.execute("customers.db", "INSERT INTO customers (name, email, signup_date) VALUES (?, ?, ?)", customers)
print(f"Added {rows_affected} new customers")

Inserting Data (dynamic batch query)

customers = [
    {"name": "John Smith", "email": "[email protected]", "signup_date": "2023-05-15"},
    {"name": "Sarah Johnson", "email": "[email protected]", "signup_date": "2023-05-16"}
]

# Prepare SQL statement with column names from the first dictionary
columns = ', '.join(customers[0].keys())
placeholders = ', '.join(['?'] * len(customers[0]))
sql_query = f"INSERT INTO customers ({columns}) VALUES ({placeholders})"

# Extract values in the correct order for each customer
customer_data = [list(customer.values()) for customer in customers]

rows_affected = sql.execute("customers.db", sql_query, customer_data)
print(f"Added {rows_affected} new customers")

Updating Data

sql.execute("path_to_db.db", "UPDATE table_name SET column1 = ? WHERE column2 = ?", ('new_value', 'value2'))

Deleting Data

sql.execute("path_to_db.db", "DELETE FROM table_name WHERE column1 = ?", ('value1',))

⚠️ Important Notes

  • For single SELECT queries: The sql.execute() function returns the result rows as a list.
  • For single INSERT/UPDATE/DELETE queries: The sql.execute() function returns the number of affected rows.
  • For batch queries: The sql.execute() function returns the number of affected rows.
  • When using parameters, always use placeholders (?) in the query and provide values as a tuple or list.
  • Ensure the SQLite database file path provided is correct.

💡 Credits

Developed by hodel33 & dyaland. Enjoy and have fun! 💫


💬 Feedback & Contact

I'd love to network, discuss tech, or swap music recommendations. Feel free to connect with me on:

🌐 LinkedIn: Björn Hödel
🐦 Twitter: @hodel33
📸 Instagram: @hodel33
📧 Email: [email protected]