pyquerytracker 0.1.0

A lightweight, decorator-based query performance tracking library for Python applications. Monitor and analyze database query performance with ease.

🐍 pyquerytracker

pyquerytracker is a lightweight Python utility to track and analyze database query performance using simple decorators. It enables developers to gain visibility into SQL execution time, log metadata, and export insights in JSON format — with optional FastAPI integration and scheduled reporting.

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🚀 Features

• ✅ Easy-to-use decorator to track function execution (e.g., SQL queries)
• ✅ Capture runtime, function name, args, return values, and more

TODO Features

• ✅ Export logs to JSON or CSV
• ✅ FastAPI integration to expose tracked metrics via REST API
• ✅ Schedule periodic exports using APScheduler
• ✅ Plug-and-play with any Python database client (SQLAlchemy, psycopg2, etc.)
• ✅ Modular and extensible design

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📦 Installation

pip install pyquerytracker

Usage

Basic Usage

import time
from pyquerytracker import TrackQuery

@TrackQuery()
def run_query():
    time.sleep(0.3)  # Simulate SQL execution
    return "SELECT * FROM users;"

run_query()

Output

2025-06-14 14:23:00,123 - pyquerytracker - INFO - Function run_query executed successfully in 305.12ms

With Configure

import logging
from pyquerytracker.config import configure

configure(
    slow_log_threshold_ms=200,     # Log queries slower than 200ms
    slow_log_level=logging.DEBUG   # Use DEBUG level for slow logs
)

Output

2025-06-14 14:24:45,456 - pyquerytracker - WARNING - Slow execution: run_query took 501.87ms