Database scaling & optimization
Indexing, connection pooling, read replicas, query tuning, and throughput-aware SQL.
How to Create a Database Helper Class for Beginners in Python
Build a beginner-friendly SQLite helper class with indexing and batch inserts to optimize database queries in Python.
import sqlite3
class DatabaseHelper:
def __init__(self, db_path):
self.connection = sqlite3.connect(db_path)
self.cursor = self.connection.cursor()
def create_table_with_index(self, table_name, columns, indexed_column):
columns_sql = ", ".join(f"{name} {dtype}" for name, dtype in col…How to Mock SQLite executemany When Batch Inserting in Python
Batch insert many rows into SQLite with executemany and mock the cursor for isolated tests.
import sqlite3
from unittest.mock import Mock, patch
def insert_users(conn, users):
"""Insert multiple user records using executemany."""
cursor = conn.cursor()
cursor.executemany(
"INSERT INTO users (name, age) VALUES (?, ?)",
users
)
conn.commit()
return cursor.rowcount
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Database scaling & optimization — Python code examples
What you will find here
This page collects database scaling & optimization snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.