Database scaling & optimization
Indexing, connection pooling, read replicas, query tuning, and throughput-aware SQL.
How to Create a Data Helper Class in Python for JSON Files
Build a beginner-friendly Python helper class to read, write, filter, and summarize JSON data files with clean, reusable methods.
import json
from pathlib import Path
class DataHelper:
"""Simple beginner-friendly helper for reading and writing JSON data files."""
@staticmethod
def read_json(filename):
file_path = Path(filename)
if file_path.exists():
with file_path.open("r", encoding="utf-8") as f:
…How to mock directory-based sharding in Python
Simulates distributing files into logical shards using a deterministic hash of each filename, mocking how a database might shard rows across nodes.
import os
import hashlib
from collections import defaultdict
from pathlib import Path
def get_shard_for_key(key: str, num_shards: int) -> int:
"""Return a deterministic shard index (0..num_shards-1) for a key."""
digest = hashlib.md5(key.encode('utf-8')).hexdigest()
return int(digest, 16) % num_shards
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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.