n8n-nodes-pdf-to-csv

An n8n community node for converting PDF documents to CSV format. This node provides robust PDF parsing capabilities with coordinate-based extraction and OCR support for image-based PDFs.

Features

• 📄 Convert PDF documents to CSV format
• 🔗 Support for both binary data and URL inputs
• 🎯 Three parsing methods: Coordinate-based, OCR, and Auto-detect
• 📊 Multiple output formats (CSV string, JSON array, binary data, Excel)
• 🔍 OCR support for scanned/image-based PDFs using Tesseract.js
• ⚡ Fast coordinate-based extraction for native PDF text
• 🤖 Auto-detect with intelligent fallback from coordinate to OCR
• ⚙️ Configurable CSV delimiters and headers
• 🔧 Built-in error handling and validation

Installation

Community Nodes (Recommended)

1. Go to Settings > Community Nodes in your n8n instance
2. Select Install
3. Enter n8n-nodes-pdf-to-csv
4. Agree to the risks and select Install

Manual Installation

1. Clone this repository or download the source code
2. Install dependencies:

   pnpm install
   

3. Build the node:

   pnpm build
   

4. Link the node to your n8n installation:

   pnpm link
   cd ~/.n8n/custom
   pnpm link n8n-nodes-pdf-to-csv
   

5. Restart your n8n instance

Docker Installation

If you're using n8n with Docker, you can install this node by:

1. Create a Dockerfile extending the n8n image:

   FROM n8nio/n8n
   USER root
   RUN npm install -g n8n-nodes-pdf-to-csv
   USER node
   

2. Build and run your custom image:

   docker build -t n8n-custom .
   docker run -it --rm --name n8n -p 5678:5678 n8n-custom
   

Usage

Basic PDF to CSV Conversion

1. Add the PDF to CSV node to your workflow

2. Configure the input type:

   • Binary Data: Use when PDF comes from a previous node (e.g., HTTP Request, Google Drive)
   • URL: Provide a direct URL to the PDF file

3. Choose parsing method:

   • Auto-Detect: Tries coordinate-based first, falls back to OCR if needed (recommended)
   • Coordinate-Based (Fast): Uses coordinate analysis for native PDF text (fastest)
   • OCR (Image-Based): Uses Tesseract.js for scanned/image PDFs (slower but works with any PDF)

4. Configure output format:

   • CSV String: Returns formatted CSV text
   • JSON Array: Returns structured JSON data
   • Binary Data: Returns downloadable CSV file

Input Configuration

Binary Data Input

{
  "inputType": "binaryData",
  "binaryPropertyName": "data"
}

URL Input

{
  "inputType": "url",
  "pdfUrl": "https://example.com/document.pdf"
}

Parsing Methods

Auto-Detect (Recommended)

Intelligent method that tries coordinate-based extraction first, then falls back to OCR if needed. Best for:

• Unknown PDF types
• Mixed document collections
• When you want the fastest method that works

Coordinate-Based (Fast)

Uses coordinate analysis to detect table structure from native PDF text. Best for:

• PDFs created digitally (not scanned)
• Documents with clear table structures
• When speed is important
• Most business reports and invoices

OCR (Image-Based)

Uses Tesseract.js optical character recognition to extract text from PDF images. Best for:

• Scanned documents
• Image-based PDFs
• PDFs where coordinate extraction fails
• Documents with complex layouts or mixed content

Note: OCR is slower but more universally compatible with different PDF types.

Example Workflow

{
  "nodes": [
    {
      "parameters": {
        "url": "https://example.com/report.pdf",
        "options": {}
      },
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 1,
      "position": [250, 300],
      "id": "http-request",
      "name": "Download PDF"
    },
    {
      "parameters": {
        "operation": "convert",
        "inputType": "binaryData",
        "binaryPropertyName": "data",
        "parsingMethod": "auto",
        "outputFormat": "csvString",
        "csvDelimiter": ",",
        "includeHeaders": true,
        "skipEmptyLines": true
      },
      "type": "n8n-nodes-pdf-to-csv.pdfToCsv",
      "typeVersion": 1,
      "position": [450, 300],
      "id": "pdf-to-csv",
      "name": "PDF to CSV"
    }
  ]
}

Configuration Options

Parameter	Type	Default	Description
inputType	Options	binaryData	Source of PDF file (binaryData/url)
binaryPropertyName	String	data	Name of binary property containing PDF
pdfUrl	String	-	URL of PDF file to convert
parsingMethod	Options	auto	Method for parsing PDF content (auto/coordinate/ocr)
csvDelimiter	String	,	Delimiter for CSV output
includeHeaders	Boolean	true	Treat first row as headers
skipEmptyLines	Boolean	true	Skip empty lines in PDF
outputFormat	Options	csvString	Format of output data

Supported File Types

• PDF documents (.pdf)
• Password-protected PDFs are not currently supported

Error Handling

The node includes comprehensive error handling for:

• Invalid PDF files
• Network errors when fetching URLs
• Parsing failures
• Memory limitations for large files

Errors can be handled using n8n's built-in error handling mechanisms.

Limitations

• Large PDF files may consume significant memory
• Complex PDF layouts may not parse perfectly with auto-detection
• Scanned PDFs (images) require OCR preprocessing
• Password-protected PDFs are not supported

Development

Prerequisites

• Node.js 18.10 or higher
• pnpm 7.18 or higher

Setup

git clone https://github.com/your-username/n8n-nodes-pdf-to-csv.git
cd n8n-nodes-pdf-to-csv
pnpm install

Build

pnpm build

Development Mode

pnpm dev

Linting

pnpm lint
pnpm lintfix

Testing

pnpm test

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make your changes
4. Run tests and linting: pnpm test && pnpm lint
5. Commit your changes: git commit -m 'Add amazing feature'
6. Push to the branch: git push origin feature/amazing-feature
7. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

• 📧 Email: your.email@example.com
• 🐛 Issues: GitHub Issues
• 💬 Discussions: GitHub Discussions

Changelog

v1.0.0

• Initial release
• Basic PDF to CSV conversion
• Multiple parsing methods
• Flexible output formats
• Comprehensive error handling