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 batch commit of transactions in Python
Simulate a transaction batch writer with commit, rollback, and summary logic to test database write patterns without a real database.
import json
from datetime import datetime, timezone
class TransactionBatch:
def __init__(self):
self.pending = []
self.committed = []
self._log = []
def add(self, operation):
self.pending.append(operation)
def commit(self):
if not self.pending:
return …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.