Database scaling & optimization
Indexing, connection pooling, read replicas, query tuning, and throughput-aware SQL.
How to Explain SQLite Query Plans in Python
Build a Python function that runs EXPLAIN QUERY PLAN on SQLite in-memory tables and prints the optimizer's execution plan for any SELECT statement.
import sqlite3
def explain_query(sql: str) -> str:
"""Return the SQLite query plan for the given SQL statement."""
conn = sqlite3.connect(":memory:")
cursor = conn.cursor()
# Create sample data for a realistic plan
cursor.execute("CREATE TABLE users (id INTEGER PRIMARY KEY, name TEXT)")
c…How to Mock Replica Lag Monitoring in Python
Simulates database replica lag with a mock monitor class that generates realistic lag metrics and health statuses.
import time
import random
from datetime import datetime, timedelta
class MockReplicaLagMonitor:
def __init__(self, replicas=3, base_lag=0.5, jitter=0.2):
self.replicas = [f"replica-{i}" for i in range(replicas)]
self.base_lag = base_lag
self.jitter = jitter
self.last_write = dateti…Browse by section
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Database scaling & optimization — Python code examples
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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.
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