afpp

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> afpp — A modern, dependency-light PDF parser for Node.js.
>
> Built for performance, reliability, and developer sanity.

---

Overview

afpp (Another PDF Parser, Properly) is a Node.js library for extracting text and images from PDF files without heavyweight native dependencies, event-loop blocking, or fragile runtime assumptions.

The project was created to address recurring problems encountered with existing PDF tooling in the Node.js ecosystem:

- Excessive bundle sizes and transitive dependencies
- Native build steps (canvas, ImageMagick, Ghostscript)
- Browser-specific assumptions (window, DOM, canvas)
- Poor TypeScript support
- Unreliable handling of encrypted PDFs
- Performance and memory inefficiencies

afpp focuses on predictable behavior, explicit APIs, and production-ready defaults.

---

Key Features

- Zero native build dependencies
- Fully asynchronous, non-blocking architecture
- First-class TypeScript support
- Supports local files, buffers, and remote URLs
- Handles encrypted PDFs
- Configurable concurrency and rendering scale
- Minimal and auditable dependency graph

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Requirements

- Node.js >= 22.14.0

---

Installation

Install using your preferred package manager:

``bash
npm install afpp


or

yarn add afpp

or

pnpm add afpp
`

---

Quick Start

All parsing functions accept the same input types:

- string (file path)
- Buffer
- URL

$3

`ts
import { readFile } from 'fs/promises';
import path from 'path';

import { pdf2string } from 'afpp';

(async () => {
const filePath = path.join('..', 'test', 'example.pdf');
const buffer = await readFile(filePath);

const pages = await pdf2string(buffer);
console.log(pages); // ['Page 1 text', 'Page 2 text', ...]
})();
`

---

$3

`ts
import { pdf2image } from 'afpp';

(async () => {
const url = new URL('https://pdfobject.com/pdf/sample.pdf');
const images = await pdf2image(url);

console.log(images); // [Buffer, Buffer, ...]
})();
`

---

$3

For large PDFs, use streaming functions to process pages incrementally without loading all results into memory:

`ts
import { writeFile } from 'fs/promises';

import { streamPdf2image, streamPdf2string } from 'afpp';

// Stream images - process each page as it's rendered
for await (const { pageNumber, pageCount, data } of streamPdf2image(
'./large.pdf',
)) {
await writeFile(page-${pageNumber}.png, data);
console.log(Processed ${pageNumber}/${pageCount});
}

// Stream text - process each page as it's extracted
for await (const { pageNumber, data } of streamPdf2string('./large.pdf')) {
console.log(Page ${pageNumber}: ${data.substring(0, 100)}...);
}
`

Benefits:

- Lower peak memory usage
- Faster time-to-first-result
- Built-in progress tracking via pageNumber and pageCount

---

$3

For advanced use cases, parsePdf exposes page-level control and transformation.

`ts
import { parsePdf } from 'afpp';

(async () => {
const response = await fetch('https://pdfobject.com/pdf/sample.pdf');
const buffer = Buffer.from(await response.arrayBuffer());

const result = await parsePdf(buffer, {}, (pageContent) => pageContent);
console.log(result);
})();
`

---

Configuration

All public APIs accept a shared options object.

`ts
const result = await parsePdf(buffer, {
concurrency: 5,
imageEncoding: 'jpeg',
password: 'STRONG_PASS',
scale: 4,
});
`

$3

| Option | Type | Default | Description |
| --------------- | ------------------------------------- | ------- | --------------------------------------------- |
| concurrency | number | 1 | Number of pages processed in parallel |
| imageEncoding | 'png' \| 'jpeg' \| 'webp' \| 'avif' | 'png' | Output format for rendered images |
| password | string | — | Password for encrypted PDFs |
| scale | number | 1.0` | Rendering scale (1.0 = 72 DPI, 2.0 = 144 DPI) |

---

Design Principles

- Node-first: No browser globals or DOM assumptions
- Explicit over implicit: No magic configuration
- Fail fast: Clear errors instead of silent corruption
- Production-oriented: Optimized for long-running processes

---

License

MIT © Richard Solár