language:

• en license: mit tags:
• pdf
• spatial
• parser
• rust
• layout-analysis
• document-parsing
• bounding-box pipeline_tag: document-question-answering

⚡ RasgaPDF

The Blazing-Fast 2D Spatial PDF Parser powered by Pure Rust.
Extract exact physical coordinates (Raw X/Y) or structured blocks & tables at native hardware speeds.

Live Web / Space Demo • Two Modes • CLI Tool • Quickstart • Architecture • Spatial Schema

🎯 The Philosophy: Pure Spatial Parsing

Most PDF extraction tools make fragile guesses: they flatten multi-column layouts into corrupted text streams, mangle tables, and strip away 2D positional geometry.

RasgaPDF does one thing with uncompromising precision:
It returns the exact 2D physical spatial geometry of the PDF.

• Bounding Boxes Everywhere: Every character, word span, line, block, and table has exact coordinates [x0, y0, x1, y1].
• Zero Lossy Heuristics: No broken markdown assumptions. Downstream LLMs, RAG pipelines, or vision-language models receive the true physical layout.
• Microsecond Rayon Parallelism: Multi-threaded page processing in pure Rust utilizing AVX2/AVX-512 SIMD.
• Polyglot First: Native C-ABI FFI bindings for Python, Node.js, Go, and C# (.NET).

⚡ Two Extraction Modes

RasgaPDF offers two distinct modes for different engineering needs:

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

The fastest, most direct extraction possible. Returns an unnested list of physical 2D coordinates for every text span on the page, with zero block or table overhead:

• Latency: ~3 to 8 ms per page
• Supported Formats: Flat JSON, Formatted Text, TSV, or CSV
• Best For: Spatial RAG, 2D visualizers, vector indexing, OCR alignment, Unix pipelines with awk/grep.

[Page 1] (X0:  50.00, Y0:  67.00, X1: 244.00, Y1:  83.00) [12.0pt] The Revolution of Artificial Intelligence
[Page 1] (X0:  50.00, Y0: 103.00, X1: 478.00, Y1: 119.00) [12.0pt] Artificial Intelligence (AI) has transformed...

🎯 Mode 2: Hierarchical Structured Document

Reconstructs the visual hierarchy into visual paragraphs (text_blocks), text lines (lines), spans, and auto-detects matrix tables via horizontal column projection:

• Latency: ~8 to 15 ms per page
• Output: Hierarchical tree SpatialDocument -> pages -> text_blocks -> lines -> tables.

⚡ Performance Benchmark

Measured on Intel Core i7-1365U (10 Cores / 12 Threads, AVX2):

💻 Standalone CLI Tool

Install or build the standalone CLI binary:

cargo build --release
./target/release/rasgapdf --help

# ⚡ MODE 1: Raw Physical Coordinates (Raw X/Y)
./target/release/rasgapdf sample.pdf --raw
./target/release/rasgapdf sample.pdf --raw --format text
./target/release/rasgapdf sample.pdf --raw --format tsv | awk -F'\t' '$1 == 1 {print $2, $3, $8}'
./target/release/rasgapdf sample.pdf --raw --format csv -o coordinates.csv

# 🎯 MODE 2: Hierarchical Structured Document
./target/release/rasgapdf sample.pdf --pretty
./target/release/rasgapdf sample.pdf -o structured.json

🚀 Rust Quickstart

Add rasgapdf to your Cargo.toml:

[dependencies]
rasgapdf = "0.1.3"

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

Extract exact 2D bounding boxes [x0, y0, x1, y1] for every text span on the page with zero block overhead (~3 to 8 ms):

use rasgapdf::parse_raw_file;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let raw = parse_raw_file("sample.pdf")?;
    println!("Extracted {} spans in {:.2} ms", raw.total_spans, raw.parse_time_ms);

    for span in &raw.spans {
        println!(
            "[Page {}] bbox=({:.2}, {:.2}, {:.2}, {:.2}) font={} ({:.1}pt) \"{}\"",
            span.page, span.x0, span.y0, span.x1, span.y1,
            span.font_name, span.font_size, span.text
        );
    }
    Ok(())
}

🎯 Mode 2: Hierarchical Structured Document

Reconstruct the visual hierarchy into visual paragraphs (text_blocks), text lines (lines), and auto-detect matrix tables:

use rasgapdf::{parse_file, ParserOptions};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let options = ParserOptions {
        detect_tables: true,
        min_table_cols: 3,
        col_tolerance: 16.0,
        row_tolerance: 6.0,
        ..Default::default()
    };

    let doc = parse_file("document.pdf", &options)?;
    println!("Processed {} pages in {:.2} ms", doc.total_pages, doc.parse_time_ms);

    for page in &doc.pages {
        println!("--- Page {} ({}x{} pt) ---", page.page_number, page.width, page.height);

        // 1. Text blocks and lines
        for block in &page.text_blocks {
            println!("Block #{} at {:?}", block.block_id, block.bbox);
            for line in &block.lines {
                println!("  Line: {}", line.text);
            }
        }

        // 2. Reconstructed tables
        for table in &page.tables {
            println!("Table ({} cols x {} rows):", table.col_count, table.row_count);
            println!("  Headers: {:?}", table.headers);
            for row in &table.rows {
                println!("  Row: {:?}", row);
            }
        }
    }
    Ok(())
}

📦 Native Bindings for Other Ecosystems

RasgaPDF provides native C-ABI bindings for other languages, each published with its own language-specific package and documentation:

🎨 Interactive Web Visualizer

🌐 Live Hugging Face Space (Zero Server Quota / Client-Side)

Test RasgaPDF instantly without installing anything:

• Live Demo: https://huggingface.co/spaces/martinsmessias/rasgapdf
• Zero Server Costs: Runs directly in your browser using client-side WebAssembly & PDF.js.
• Run on Your Personal Quota: Click to clone into your own Hugging Face account with your personal compute quota.

🤝 Contributing & Community

Contributions are what make the open-source community thrive!

• Read our Contributing Guide to get started.
• Adhere to our Code of Conduct.

📄 License

RasgaPDF is licensed under the MIT License.
Copyright (c) 2026 Messias Martins.