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Web Scraping Framework
Scalable scraping with BeautifulSoup, Scrapy, and Playwright. Anti-detection, rate limiting, and data pipelines.
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📁 File Structure 18 files
web-scraping-framework/
├── LICENSE
├── README.md
├── configs/
│ └── scraper_config.yaml
├── examples/
│ ├── scrape_product_listings.py
│ └── scrape_quotes.py
├── guides/
│ └── web-scraping-guide.md
├── src/
│ └── scraper/
│ ├── base.py
│ ├── browser.py
│ ├── http_client.py
│ ├── middleware.py
│ ├── parser.py
│ ├── pipeline.py
│ ├── scheduler.py
│ └── storage.py
└── tests/
├── conftest.py
├── test_http_client.py
└── test_parser.py
📖 Documentation Preview README excerpt
Web Scraping Framework
Extract structured data from any website — responsibly and at scale.
An async-first Python scraping framework with rate limiting, proxy rotation, browser automation, and pluggable storage backends.
---
What You Get
- Abstract base scraper with fetch → parse → store pipeline
- Async HTTP client with retries, rate limiting, and proxy rotation
- HTML parser supporting CSS selectors, XPath, and structured data extraction
- Playwright browser integration for JavaScript-rendered pages
- Processing pipeline with cleaning, validation, deduplication
- Storage backends: JSON, CSV, SQLite, S3
- Middleware system: user-agent rotation, robots.txt, caching
- URL scheduler with priority queue, seen filter, and domain-level delays
- Working examples and comprehensive test suite
- Ethical scraping guide with legal considerations
File Tree
web-scraping-framework/
├── README.md
├── LICENSE
├── manifest.json
├── src/scraper/
│ ├── base.py # Abstract scraper base class
│ ├── http_client.py # Async HTTP with retries & rate limiting
│ ├── parser.py # CSS/XPath HTML parsing
│ ├── browser.py # Playwright headless browser
│ ├── pipeline.py # Data cleaning & validation pipeline
│ ├── storage.py # JSON, CSV, SQLite, S3 backends
│ ├── middleware.py # UA rotation, robots.txt, cache
│ └── scheduler.py # URL priority queue & scheduling
├── examples/
│ ├── scrape_quotes.py # Scrape quotes.toscrape.com
│ └── scrape_product_listings.py
├── configs/
│ └── scraper_config.yaml # Full configuration reference
├── tests/
│ ├── conftest.py # Fixtures & mock responses
│ ├── test_http_client.py # HTTP client tests
│ └── test_parser.py # Parser tests
└── guides/
└── web-scraping-guide.md
Getting Started
1. Install dependencies
pip install aiohttp lxml cssselect playwright
playwright install chromium
2. Build your first scraper
... continues with setup instructions, usage examples, and more.
📄 Code Sample .py preview
src/scraper/base.py
"""Abstract base scraper defining the fetch → parse → store pipeline.
Subclass this to build scrapers for specific websites. The base class
handles orchestration, error handling, and lifecycle management.
"""
from __future__ import annotations
import abc
import logging
from dataclasses import dataclass, field
from typing import Any
logger = logging.getLogger(__name__)
@dataclass
class ScrapeResult:
"""Container for scrape results with metadata."""
url: str
items: list[dict[str, Any]] = field(default_factory=list)
errors: list[str] = field(default_factory=list)
status_code: int = 0
elapsed_ms: float = 0.0
@property
def success(self) -> bool:
"""Return True if scrape produced items without errors."""
return len(self.items) > 0 and len(self.errors) == 0
class Scraper(abc.ABC):
"""Abstract base class for web scrapers.
Implements the template method pattern: subclasses override
`parse()` while the base class handles fetch/store orchestration.
Args:
client: HTTP client for making requests.
storage: Storage backend for persisting results.
middleware: Optional list of middleware to apply.
"""
def __init__(
self,
client: Any,
storage: Any,
middleware: list[Any] | None = None,
) -> None:
# ... 80 more lines ...