AI Dev Tool: Python AsyncIO Web Scraper with Exponential Backoff & SQLite Sink

1. The Production Bottleneck

We engineered this zero-bloat Python 3.12+ / AsyncIO blueprint to enforce bounded concurrency, deterministic exponential backoff with jitter, strict schema validation at the ingestion boundary, and structured JSON telemetry—ready to drop into production without weeks of plumbing.

2. Request & Execution Architecture

3. Production Benchmarks

"""AI Dev Tool: Python AsyncIO Web Scraper with Exponential Backoff & SQLite Sink.

This module provides a production-ready web scraper that leverages Python's asyncio library for concurrent requests.
It features exponential backoff with jitter for handling transient failures, structured JSON logging, and deterministic error handling.
The scraper is designed to operate within bounded concurrency limits to prevent overwhelming target servers.

Usage:
    python web_scraper.py --config config.json --output db.sqlite

The configuration file should contain the following settings:
    - urls: list of URLs to scrape
    - max_concurrency: maximum number of concurrent requests
    - backoff_base: base delay for exponential backoff (in seconds)
    - backoff_max: maximum delay for exponential backoff (in seconds)
    - db_path: path to the SQLite database file

Example configuration file (config.json):
    {
        "urls": ["http://example.com/page1", "http://example.com/page2"],
        "max_concurrency": 5,
        "backoff_base": 1,
        "backoff_max": 32,
        "db_path": "db.sqlite"
    }
"""

import asyncio
import json

5. Choose Your Access Tier

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6. Frequently Asked Engineering Questions

7. Related Production Blueprints