webscraper-plus 0.1.0

A versatile web scraping library for extracting content from websites

WebScraper-Plus

A versatile web scraping library for extracting content from websites with robust error handling and customizable output options.

Features

• Text Extraction: Extract and clean text content from web pages
• Link Extraction: Find and save all hyperlinks from a page
• Document Download: Download documents like PDF, DOCX, CSV, Excel files
• Document Text Extraction: Extract text from downloaded documents
• Image Download: Download images from web pages
• OCR Capability: Extract text from images using Tesseract OCR
• Configurable Output: Choose between flat or nested directory structure
• Robust Error Handling: Gracefully handle network issues, missing dependencies, and more
• Command-line Interface: Easy to use CLI for quick scraping tasks
• Python API: Clean API for integration into your Python projects

Installation

Basic Installation

pip install webscraper-plus

With Document Support

pip install webscraper-plus[pdf,docx,excel]

With Image OCR Support

pip install webscraper-plus[ocr]

Full Installation (All Features)

pip install webscraper-plus[all]

Development Installation

pip install webscraper-plus[dev]

Dependencies

• Core: requests, BeautifulSoup4, spacy, chardet
• PDF: PyPDF2
• DOCX: python-docx
• Excel: openpyxl
• OCR: pytesseract, Pillow (and Tesseract OCR system package)

Tesseract OCR

For OCR functionality, you need to install Tesseract OCR on your system:

• Windows: Download installer from GitHub
• macOS: brew install tesseract
• Ubuntu/Debian: sudo apt-get install tesseract-ocr
• Fedora/RHEL: sudo dnf install tesseract

Command-line Usage

# Basic usage (extracts all content types)
webscraper-plus --url https://example.com --output ./scraped_data

# Extract only text and links
webscraper-plus --url https://example.com --text --links

# Extract documents and images with flat structure
webscraper-plus --url https://example.com --docs --images --flat

# Extract all content types with verbose logging
webscraper-plus --url https://example.com --all --verbose

Command-line Options

  -h, --help       show this help message and exit
  --version        show program's version number and exit
  --url URL        URL to scrape
  --output OUTPUT  Output directory for scraped content
  --text           Extract webpage text
  --links          Extract hyperlinks
  --docs           Download documents
  --images         Download images
  --flat           Use flat directory structure
  --all            Enable all extraction options
  --verbose        Enable verbose logging

Python Usage

Basic Usage

from webscraper import WebScraper

# Create scraper (extracts everything)
scraper = WebScraper(
    url="https://example.com",
    base_output_dir="./scraped_data",
    extract_text=True,
    extract_links=True,
    extract_documents=True,
    extract_images=True
)

# Run scraper and get results
results = scraper.scrape()
print(results)

Selective Extraction

# Create scraper with selective extraction
scraper = WebScraper(
    url="https://example.com",
    extract_text=True,     # Only extract text
    extract_links=False,
    extract_documents=False,
    extract_images=False,
    flat_structure=True    # Use flat directory structure
)

# Run scraper
results = scraper.scrape()

Output Structure

By default, WebScraper-Plus uses a nested directory structure:

output_directory/
├── domain_timestamp/
│   ├── webpage_text.txt
│   ├── links/
│   │   └── links.txt
│   ├── documents/
│   │   ├── document1.pdf
│   │   ├── document1.txt (extracted text)
│   │   └── ...
│   └── images/
│       ├── image1.jpg
│       ├── image1.txt (OCR text)
│       └── ...

With flat_structure=True, all files are saved in a single directory with prefixes:

output_directory/
├── domain_timestamp/
│   ├── webpage_text_main.txt
│   ├── links_extracted.txt
│   ├── doc_document1.pdf
│   ├── doc_document1.txt
│   ├── img_image1.jpg
│   ├── img_ocr_image1.txt
│   └── ...

License

MIT License - see LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Examples

The package includes several examples to help you get started:

Basic Usage Example

The examples/basic_usage.py script demonstrates how to use WebScraper with all extraction options enabled:

from webscraper import WebScraper

# Create WebScraper instance with all extraction options enabled
scraper = WebScraper(
    url="https://en.wikipedia.org/wiki/Web_scraping",
    base_output_dir="./scraped_output",
    extract_text=True,
    extract_links=True,
    extract_documents=True,
    extract_images=True
)

# Execute scraping
results = scraper.scrape()

Selective Scraping Example

The examples/selective_scraping.py script shows how to use WebScraper with specific extraction options:

# Example 1: Extract only text and links with flat directory structure
text_links_scraper = WebScraper(
    url="https://www.python.org",
    base_output_dir="./python_org_output",
    extract_text=True,
    extract_links=True,
    extract_documents=False,
    extract_images=False,
    flat_structure=True
)

# Example 2: Extract only images with nested directory structure
images_scraper = WebScraper(
    url="https://www.python.org",
    base_output_dir="./python_org_output",
    extract_text=False,
    extract_links=False,
    extract_documents=False,
    extract_images=True,
    flat_structure=False
)

Running Examples

To run the examples, clone the repository and run:

# Basic usage example
python examples/basic_usage.py

# Selective scraping example
python examples/selective_scraping.py