Database scaling & optimization
Indexing, connection pooling, read replicas, query tuning, and throughput-aware SQL.
How to Implement Consistent Hashing in Python
Build a consistent hash ring in Python that distributes keys across nodes and minimizes remapping when nodes are added or removed.
import hashlib
from bisect import bisect_right
class ConsistentHashRing:
def __init__(self, nodes, replicas=3):
self.replicas = replicas
self.ring = {}
self.sorted_keys = []
for node in nodes:
self.add_node(node)
def _hash(self, key):
return int(hashlib.md…Simulate PostgreSQL Vacuum to Reclaim Space in Python
A Python class that safely rewrites a data file to remove deleted rows and reclaim physical space, mimicking PostgreSQL's VACUUM operation.
import shutil
import os
class VacuumCleaner:
"""Simulates PostgreSQL-style vacuum reclaiming dead space in a file."""
def __init__(self, filepath, fill_ratio=0.7, dead_marker="[DELETED]"):
self.filepath = filepath
self.fill_ratio = fill_ratio
self.dead_marker = dead_marker
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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.