Database scaling & optimization
Indexing, connection pooling, read replicas, query tuning, and throughput-aware SQL.
Database indexing and query timing optimization in Python
Create SQLite indexes and time query performance to measure speedup for large table lookups in Python.
import sqlite3
import time
def time_query(db_path, query, params=()):
conn = sqlite3.connect(db_path)
conn.execute("PRAGMA journal_mode = WAL")
start = time.perf_counter()
result = conn.execute(query, params).fetchall()
elapsed = time.perf_counter() - start
conn.close()
return result, ela…How to Shard Data by User ID Hash in Python
Deterministically map user IDs to shard indexes using an MD5 hash modulo the shard count in Python.
import hashlib
def shard_id(user_id: str, num_shards: int = 4) -> int:
"""Deterministically map a user_id to a shard index using MD5."""
digest = hashlib.md5(user_id.encode("utf-8")).hexdigest()
return int(digest[:8], 16) % num_shards
if __name__ == "__main__":
user_ids = ["alice", "bob", "carol", "d…Browse by section
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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.