Database scaling & optimization
Indexing, connection pooling, read replicas, query tuning, and throughput-aware SQL.
Build a Partial Index Mock in Python for Database Filtering
Simulate a partial database index by filtering keys with a predicate, then return a limited mock lookup dictionary.
data = [
"alpha", "beta", "gamma", "delta", "epsilon",
"zeta", "eta", "theta", "iota", "kappa"
]
filtered_keys = [item for item in data if len(item) >= 5]
def mock_partial_index(keys, filter_func, limit=3):
result = {}
for key in keys:
if not filter_func(key):
continue
res…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:
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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.