deepharvest 1.0.4

The world's most complete, resilient, multilingual web crawler

DeepHarvest

The World's Most Complete, Resilient, Multilingual Web Crawler

Features

Core Capabilities

• Complete Coverage: Crawls entire websites including all subpages
• All Content Types: HTML, PDF, DOCX, PPTX, XLSX, images, audio, video
• JavaScript Support: Full SPA support with Playwright
• Multilingual: Handles all languages, encodings, and scripts
• Distributed: Redis-based distributed crawling with multiple workers
• Resumable: Checkpoint and resume interrupted crawls
• Intelligent: ML-based trap detection, content extraction, deduplication

Advanced Features

• Smart Trap Detection: Calendar, pagination, session ID, faceted navigation
• ML Content Extraction: Page classification, soft-404 detection, quality scoring
• Advanced URL Management: SimHash, MinHash, LSH deduplication
• Site Graph Analysis: PageRank, clustering, GraphML export
• Observability: Prometheus metrics, Grafana dashboards
• Extensible: Plugin system for custom extractors
• OSINT Mode: Entity extraction, technology detection, link graph analysis
• Browser Automation: High-level Playwright integration with screenshot capture
• Pipeline Execution: YAML-based pipeline runner for complex workflows
• API Server: REST API for programmatic access
• Multiple Exporters: JSONL, Parquet, SQLite, VectorDB (FAISS/Chroma) support

Quick Start

Installation

pip install deepharvest

Basic Usage

Simple Crawls

# Basic crawl with depth limit
deepharvest crawl https://example.com --depth 5 --output ./output

# Crawl without JavaScript rendering (faster)
deepharvest crawl https://example.com --no-js --depth 3

# Crawl with JavaScript rendering (for SPAs)
deepharvest crawl https://example.com --js --depth 3

Limiting Crawl Scope

# Limit total number of URLs crawled
deepharvest crawl https://example.com --max-urls 1000 --depth 5

# Limit response size (skip large files)
deepharvest crawl https://example.com --max-size 10 --depth 3

# Limit pages per domain (useful for multi-domain crawls)
deepharvest crawl https://example.com --max-pages-per-domain 50 --depth 5

# Set time limit (stop after specified seconds)
deepharvest crawl https://example.com --time-limit 3600 --depth 5

# Combine multiple limits
deepharvest crawl https://example.com \
  --depth 5 \
  --max-urls 500 \
  --max-pages-per-domain 100 \
  --max-size 5 \
  --time-limit 1800 \
  --output ./output

Distributed Crawling

# Run in distributed mode with Redis
deepharvest crawl https://example.com \
  --distributed \
  --redis-url redis://localhost:6379 \
  --workers 5 \
  --depth 10

Using Configuration Files

# Use a YAML config file
deepharvest crawl --config config.yaml

OSINT Mode

# Basic OSINT collection
deepharvest osint https://example.com

# With JSON output and link graph
deepharvest osint https://example.com --json --graph

# With screenshots
deepharvest osint https://example.com --screenshot

API Server

# Start API server
deepharvest serve --host 0.0.0.0 --port 8000

Pipeline Execution

# Run a pipeline from YAML file
deepharvest run pipeline.yaml

Python API

import asyncio
from deepharvest import DeepHarvest, CrawlConfig

async def main():
    config = CrawlConfig(
        seed_urls=["https://example.com"],
        max_depth=5,
        enable_js=True
    )
    
    crawler = DeepHarvest(config)
    await crawler.initialize()
    await crawler.crawl()
    await crawler.shutdown()

asyncio.run(main())

Installation

From PyPI

pip install deepharvest

From Source

git clone https://github.com/deepharvest/deepharvest
cd deepharvest
pip install -e .

Using Docker

docker-compose up

Documentation

Comprehensive documentation is available in the docs/ directory:

• API Reference - Complete API documentation
• Plugin Development Guide - Create and use plugins
• OSINT Usage - OSINT mode examples
• Browser Automation - Browser automation guide
• Benchmarks - Performance benchmarks
• Troubleshooting - Common issues and solutions
• Architecture - System architecture overview

Architecture

┌─────────────────────────────────────────────────────────┐
│                    DeepHarvest Core                       │
├─────────────────────────────────────────────────────────┤
│  ┌─────────────┐  ┌──────────────┐  ┌───────────────┐  │
│  │  Frontier   │  │   Fetcher    │  │  JS Renderer  │  │
│  │  (BFS/DFS)  │  │  (HTTP/2)    │  │  (Playwright) │  │
│  └─────────────┘  └──────────────┘  └───────────────┘  │
│  ┌─────────────┐  ┌──────────────┐  ┌───────────────┐  │
│  │ Extractors  │  │  Trap Det.   │  │  URL Dedup    │  │
│  │  (50+ fmt)  │  │  (ML+Rules)  │  │  (SimHash)    │  │
│  └─────────────┘  └──────────────┘  └───────────────┘  │
├─────────────────────────────────────────────────────────┤
│                  Distributed Layer                       │
│  ┌──────────┐  ┌───────────┐  ┌──────────┐            │
│  │  Redis   │  │  Workers  │  │ Storage  │            │
│  │ Frontier │  │  (N proc) │  │ (S3/FS)  │            │
│  └──────────┘  └───────────┘  └──────────┘            │
└─────────────────────────────────────────────────────────┘

How It Works

DeepHarvest operates as a distributed web crawling system that systematically discovers, fetches, and extracts content from websites. The architecture follows a modular design with clear separation of concerns.

Core Workflow

1. Initialization: The crawler initializes components (frontier, fetcher, extractors, ML models) based on configuration.

2. URL Management (Frontier): A priority queue manages URLs to be crawled. Supports BFS, DFS, and priority-based strategies. In distributed mode, Redis coordinates URL distribution across workers.

3. Content Fetching: The fetcher downloads web pages with retry logic, timeout handling, and rate limiting. Attempts HTTP/2 support with fallback to HTTP/1.1.

4. HTML Parsing: Multi-strategy parser with fallback chain (lxml → html5lib → html.parser) ensures robust parsing of malformed HTML.

5. JavaScript Rendering: For Single Page Applications (SPAs), Playwright renders pages, executes JavaScript, handles infinite scroll, and captures the final DOM state.

6. Content Extraction: Specialized extractors process different content types:

   • Text: HTML text extraction with boilerplate removal
   • Documents: PDF, DOCX, PPTX, XLSX text extraction
   • Media: Image metadata, OCR, audio transcription, video metadata
   • Structured Data: JSON-LD, Microdata, OpenGraph, Schema.org

7. Link Discovery: Advanced link extractor finds URLs from multiple sources:

   • HTML attributes (href, src, srcset)
   • JavaScript code (router.push, window.location)
   • Structured data (JSON-LD, Microdata)
   • Meta tags and data URIs

8. Deduplication: Three-tier deduplication system:

   • SHA256: Exact URL/content duplicates
   • SimHash: Near-duplicate detection (64-bit hashing)
   • MinHash LSH: Scalable similarity search for large datasets

9. Trap Detection: ML and rule-based detection prevents infinite loops from:

   • Calendar-based URLs (date patterns)
   • Session ID parameters
   • Pagination traps
   • Query parameter explosions

10. Storage: Extracted content is stored with metadata. Supports filesystem, S3, and PostgreSQL backends.

Distributed Architecture

In distributed mode, multiple workers share a Redis-based frontier. Each worker:

• Pulls URLs from the shared queue
• Processes pages independently
• Respects per-host concurrency limits
• Reports metrics to centralized monitoring

This enables linear scaling: N workers process approximately N times the throughput of a single worker.

Resilience Features

• Parser Fallback: Automatic fallback between parsers when HTML is malformed
• Network Resilience: Exponential backoff retry, timeout handling, proxy support
• Memory Management: Streaming for large files, memory guards per worker
• Checkpointing: Periodic state saves enable resuming interrupted crawls
• Error Taxonomy: Structured error handling with detailed reporting

Machine Learning Integration

• Page Classification: Identifies page types (article, product, forum, etc.) for intelligent prioritization
• Soft-404 Detection: Identifies pages that return 200 but are effectively 404s
• Quality Scoring: ML-based content quality assessment
• Trap Detection: Pattern recognition for crawler traps

Multilingual Support

• Automatic encoding detection (charset_normalizer, chardet)
• Language detection (langdetect)
• CJK (Chinese, Japanese, Korean) text processing
• RTL (Right-to-Left) language support
• Unicode normalization

Use Cases

• Research: Academic data collection and analysis
• SEO: Site auditing and competitive analysis
• Media Monitoring: News and content aggregation
• Business Intelligence: Market research and data mining
• AI Training: Dataset creation for ML models
• Analytics: Web structure and link analysis

Configuration

Create a config.yaml:

seed_urls:
  - https://example.com
max_depth: 5
enable_js: true
distributed: true
redis_url: redis://localhost:6379
extractors:
  - text
  - pdf
  - office
  - images
ml_features:
  trap_detection: true
  soft404_detection: true
  content_extraction: true

Run with config:

deepharvest crawl --config config.yaml

Testing

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest tests/

# With coverage
pytest --cov=deepharvest tests/

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

License

Apache-2.0 License - see LICENSE for details.

Acknowledgments

Built with amazing open-source tools:

• Playwright for JavaScript rendering
• BeautifulSoup & lxml for HTML parsing
• PyMuPDF for PDF extraction
• Redis for distributed coordination
• scikit-learn for ML models

---

Contributions are welcome anytime! This project was initially developed by a single contributor, and we're excited to welcome new contributors to help make DeepHarvest even better.