Native Ruby bindings for the parser-core Rust crate, providing high-performance document parsing and text extraction capabilities through Magnus. This gem wraps parser-core to extract text from PDFs, Office documents (DOCX, XLSX), images (with OCR), and more. Part of the ruby-nlp ecosystem.

• 📄 Document Parsing: Extract text from PDFs, Office documents (DOCX, XLSX)
• 🖼️ OCR Support: Extract text from images using Tesseract OCR
• 🚀 High Performance: Native Rust performance with Ruby convenience
• 🔧 Unified API: Single interface for multiple document formats
• 📦 Cross-Platform: Works on Linux, macOS, and Windows
• 🧪 Well Tested: Comprehensive test suite with RSpec

Add this line to your application's Gemfile:

gem 'parsekit'

And then execute:

$ bundle install

Or install it yourself as:

gem install parsekit

• Ruby >= 3.0.0
• Rust toolchain (stable)
• C compiler (for linking)

That's it! ParseKit bundles all necessary libraries including Tesseract for OCR, so you don't need to install any system dependencies.

require 'parsekit'

# Parse a PDF file
text = ParseKit.parse_file("document.pdf")
puts text  # Extracted text from the PDF

# Parse an Excel file
text = ParseKit.parse_file("spreadsheet.xlsx")
puts text  # Extracted text from all sheets

# Parse binary data directly
file_data = File.binread("document.pdf")
text = ParseKit.parse_bytes(file_data)
puts text

# Parse with a Parser instance
parser = ParseKit::Parser.new
text = parser.parse_file("report.docx")
puts text

# Parse files directly
content = ParseKit.parse_file('document.pdf')

# Parse bytes
data = File.read('document.pdf', mode: 'rb')
content = ParseKit.parse_bytes(data.bytes)

# Check supported formats
formats = ParseKit.supported_formats
# => ["txt", "json", "xml", "html", "docx", "xlsx", "xls", "csv", "pdf", "png", "jpg", "jpeg", "tiff", "bmp"]

# Check if a file is supported
ParseKit.supports_file?('document.pdf')  # => true

# Create parser with options
parser = ParseKit::Parser.new(
  strict_mode: true,
  max_size: 50 * 1024 * 1024,  # 50MB limit
  encoding: 'UTF-8'
)

# Or use the strict convenience method
parser = ParseKit::Parser.strict

parser = ParseKit::Parser.new

# Direct access to format-specific parsers
pdf_data = File.read('document.pdf', mode: 'rb').bytes
pdf_text = parser.parse_pdf(pdf_data)

image_data = File.read('image.png', mode: 'rb').bytes
ocr_text = parser.ocr_image(image_data)

excel_data = File.read('data.xlsx', mode: 'rb').bytes
excel_text = parser.parse_xlsx(excel_data)

ParseKit is built with performance in mind:

• Native Rust implementation for speed
• Statically linked C libraries (MuPDF, Tesseract) compiled with optimizations
• Efficient memory usage with streaming where possible
• Configurable size limits to prevent memory issues

After checking out the repo, run bin/setup to install dependencies. Then, run rake spec to run the tests.

To compile the Rust extension:

rake compile

To run tests with coverage:

rake dev:coverage

By default, ParseKit bundles Tesseract for zero-dependency OCR support. Advanced users who already have Tesseract installed system-wide and want faster gem installation can use system mode:

Using system Tesseract during installation:

gem install parsekit -- --no-default-features

For development with system Tesseract:

rake compile CARGO_FEATURES=""  # Disables bundled-tesseract feature

System Tesseract requirements:

• macOS: brew install tesseract
• Ubuntu/Debian: sudo apt-get install libtesseract-dev
• Fedora/RHEL: sudo dnf install tesseract-devel

The bundled mode adds ~1-3 minutes to initial gem installation but provides a completely self-contained experience with no external dependencies.

ParseKit uses a hybrid Ruby/Rust architecture:

• Ruby Layer: Provides convenient API and format detection
• Rust Layer: Implements high-performance parsing using:
  • MuPDF for PDF text extraction (statically linked)
  • tesseract-rs for OCR (with bundled Tesseract by default)
  • Pure Rust libraries for DOCX/XLSX parsing
  • Magnus for Ruby-Rust FFI bindings

Bug reports and pull requests are welcome on GitHub at https://github.com/scientist-labs/parsekit.

The gem is available as open source under the terms of the MIT License.

Note: This gem includes statically linked versions of MuPDF (AGPL/Commercial) and Tesseract (Apache 2.0). Please review their respective licenses for compliance with your use case.