⚡ RasgaPDF (Node.js)

Ultra-Fast 2D Spatial PDF Parser powered by Pure Rust.
Extract exact physical coordinates (Raw X/Y) or structured blocks & tables with sub-millisecond latency.

🚀 Installation

npm install rasgapdf

Note: Bundles pre-compiled native Rust C-ABI binaries. Works out-of-the-box with optional koffi fast FFI and automatic CLI fallback.

⚡ Two Extraction Modes

⚡ Mode 1: Flat Physical Coordinates (Raw X/Y)

Zero-overhead extraction returning exact physical 2D coordinates [x0, y0, x1, y1] for every text span (~3-8 ms):

const { parseRaw } = require('rasgapdf');

const raw = parseRaw('sample.pdf');
console.log(`Parsed ${raw.total_spans} spans in ${raw.parse_time_ms.toFixed(2)} ms`);

// Iterate through raw physical coordinates
for (const span of raw.spans) {
  console.log(`[Page ${span.page}] (${span.x0}, ${span.y0}, ${span.x1}, ${span.y1}) -> "${span.text}"`);
}

🎯 Mode 2: Hierarchical Structured Document

Extracts visual text blocks, lines, font sizes, and automatically detects matrix tables via column alignment:

const { parsePdf } = require('rasgapdf');

const doc = parsePdf('invoice.pdf', {
  detect_tables: true,
  min_table_columns: 3
});

console.log(`Total Pages: ${doc.total_pages}`);
for (const page of doc.pages) {
  // Access text blocks
  for (const block of page.text_blocks) {
    console.log(`Block #${block.block_id}: ${block.lines[0].text}`);
  }

  // Access detected tables
  for (const table of page.tables) {
    console.log('Table Headers:', table.headers);
    console.log('Table Rows:', table.rows);
  }
}

📐 Schema

Returns a deterministic JSON structure representing the exact 2D canvas geometry of the PDF.

`RawSpatialDocument`

interface RawSpatialDocument {
  file_name: string;
  total_pages: number;
  total_spans: number;
  parse_time_ms: number;
  spans: Array<{
    page: number;
    x0: number;
    y0: number;
    x1: number;
    y1: number;
    font_size: number;
    font_name: string;
    text: string;
  }>;
}

martinsmessias
/

rasgapdf