GroupDocs.Parser Console - Command Line Document Parser

A powerful command-line tool for extracting structured data from documents using GroupDocs.Parser for .NET. Parse text, parse tables, parse barcodes, and parse images from PDFs, TIFFs, and other document formats using XML-based templates.

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📖 Overview

GroupDocs.Parser Console is a cross-platform CLI application that enables automated document parsing and data extraction. It supports:

• Parse text from documents using template-based extraction
• Parse tables with structured data extraction
• Parse barcodes from documents and images
• Parse images with OCR support for scanned documents
• Batch processing capabilities
• JSON and text output formats
• Verbose logging and progress indicators

Perfect for automation scripts, CI/CD pipelines, and server-side document processing.

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⚙️ Features

Core Parsing Capabilities

• Parse Text – Extract text fields from documents using visual templates
• Parse Tables – Extract structured table data with cell-level precision
• Parse Barcodes – Recognize and extract barcode values (QR codes, Code128, etc.)
• Parse Images – Process scanned documents and images with OCR support

Advanced Features

• Template-Based Extraction – Use XML templates to define extraction regions
• Multi-Template Support – Apply multiple templates to a single document
• OCR Integration – Enable OCR for scanned PDFs and TIFF images
• Page-Specific Parsing – Target specific pages for extraction
• Flexible Output – Generate results in JSON or human-readable text format
• Progress Indicators – Real-time progress feedback during parsing
• Verbose Logging – Detailed logging for debugging and monitoring
• Error Handling – Comprehensive error reporting with exit codes

Supported Document Formats

• PDF (text-based and scanned)
• TIFF images
• Other formats supported by GroupDocs.Parser

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🚀 Getting Started

Prerequisites

• .NET 8.0 SDK or later
• Valid GroupDocs.Parser license file

Installation

Option 1: Build from Source

git clone https://github.com/groupdocs-parser/groupdocs-parser-console.git
cd groupdocs-parser-console
dotnet build

Option 2: Use Precompiled Binary

Download the latest release from the Releases page.

Set License

The application supports multiple ways to configure the license file:

Option 1: Direct Path in config.json

Create or update config.json with your GroupDocs.Parser license path:

{
  "LicensePath": "D:\\Licenses\\GroupDocs.Parser.NET.lic"
}

Option 2: Environment Variable via config.json

If LicensePath doesn't exist, the application will check for LicenseEnv in config.json and use it as an environment variable name that points to the directory containing GroupDocs.Parser.NET.lic:

{
  "LicenseEnv": "LIC_PATH"
}

Then set the environment variable to the directory path:

# Windows (PowerShell)
$env:LIC_PATH = "D:\Licenses"

# Windows (CMD)
set LIC_PATH=D:\Licenses

# Linux/Mac
export LIC_PATH=/path/to/licenses

The application will look for GroupDocs.Parser.NET.lic in the directory specified by the environment variable.

Option 3: Place License in Application Directory

Alternatively, place a .lic file in the application directory.

👉 Don't have a license? Request a free temporary license:
Get Temporary License

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📖 Usage

Basic Syntax

documentparser -i <input-file> -t <template-file> -o <output-file> [options]

Command Options

Option	Short	Required	Description
--input	-i	Yes	Path to the input document file (PDF, TIFF, etc.)
--template	-t	Yes	Path(s) to template file(s) (XML format). Multiple templates can be specified.
--output	-o	Yes	Path to the output file where extracted data will be written
--page	-p	No	Zero-based page index to parse (default: 0)
--ocr		No	Enable OCR (Optical Character Recognition) for scanned documents
--dpi		No	DPI for image rendering and OCR (default: 288, range: 1-10000)
--verbose	-v	No	Enable verbose output with detailed progress information
--quiet	-q	No	Suppress all output except errors
--json		No	Output results in JSON format instead of plain text

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💡 Examples

Example 1: Parse Text from a PDF Document

Extract text fields from the first page of a PDF:

documentparser -i invoice.pdf -t invoice-template.xml -o output.txt

Output:

ℹ Starting document parsing...
✓ License loaded successfully
✓ Loaded 1 template(s)
✓ Parser initialized in 0.15s
✓ Document parsed in 1.23s
✓ Results written to: output.txt

✓ Parsing completed successfully!
  Fields matched: 5 of 5
  Total time: 1.45s
  Output format: Text

Output File Content:

============================================================
Document: invoice.pdf
Page: 1
Parsed: 2024-01-15 14:30:25
============================================================

Field: InvoiceNumber (Text)
----------------------------------------
INV-2024-001

Field: Date (Text)
----------------------------------------
2024-01-15

Field: Total (Text)
----------------------------------------
$1,250.00

Field: CustomerName (Text)
----------------------------------------
Acme Corporation

Field: Tax (Text)
----------------------------------------
$125.00

============================================================
Statistics: 5 of 5 fields matched
Parse time: 1.23 seconds

Example 2: Parse Tables with Multiple Templates

Extract data using multiple templates:

documentparser -i report.pdf -t header-template.xml -t table-template.xml -o results.txt -p 0

Output:

ℹ Starting document parsing...
✓ License loaded successfully
→ Loaded template: header-template.xml (3 fields)
→ Loaded template: table-template.xml (1 fields)
✓ Loaded 2 template(s)
✓ Parser initialized in 0.18s
✓ Document parsed in 2.45s
✓ Results written to: results.txt

Example 3: Parse Barcodes from Scanned Document

Extract barcodes from a scanned PDF with OCR enabled:

documentparser -i scanned-invoice.pdf -t barcode-template.xml -o barcodes.txt --ocr --dpi 300

Output:

ℹ Starting document parsing...
✓ License loaded successfully
✓ Loaded 1 template(s)
✓ Parser initialized in 0.22s
✓ Document parsed in 3.67s
✓ Results written to: barcodes.txt

✓ Parsing completed successfully!
  Fields matched: 2 of 2
  Total time: 3.92s
  Output format: Text

Output File Content:

============================================================
Document: scanned-invoice.pdf
Page: 1
Parsed: 2024-01-15 14:35:10
============================================================

Field: QRCode (Barcode)
----------------------------------------
https://example.com/invoice/12345

Field: ProductBarcode (Barcode)
----------------------------------------
1234567890123

============================================================
Statistics: 2 of 2 fields matched
Parse time: 3.67 seconds

Example 4: Parse Images with OCR

Process a scanned TIFF image with OCR:

documentparser -i document.tiff -t text-template.xml -o extracted.txt --ocr --dpi 288

Example 5: Verbose Mode

Enable detailed logging:

documentparser -i document.pdf -t template.xml -o output.txt --verbose

Output:

ℹ Starting document parsing...
→ Input document: C:\Documents\invoice.pdf
→ Templates: C:\Templates\invoice-template.xml
→ Output file: C:\Output\output.txt
→ Page index: 0
→ OCR enabled: False
→ DPI: 288
✓ License loaded successfully
→ Loaded template: invoice-template.xml (5 fields)
✓ Loaded 1 template(s)
✓ Parser initialized in 0.15s
✓ Document parsed in 1.23s
✓ Results written to: C:\Output\output.txt

✓ Parsing completed successfully!
  Fields matched: 5 of 5
  Total time: 1.45s
  Output format: Text

Example 6: Quiet Mode

Suppress all output except errors (useful for scripts):

documentparser -i document.pdf -t template.xml -o output.txt --quiet

Example 8: Parse Specific Page

Extract data from page 2 (zero-based index):

documentparser -i multi-page.pdf -t template.xml -o page2.txt -p 1

Example 9: High-Resolution OCR

Process scanned document with high DPI for better OCR accuracy:

documentparser -i scanned.pdf -t template.xml -o output.txt --ocr --dpi 600

Example 10: Parse Tables

Extract table data from a document:

documentparser -i report.pdf -t table-template.xml -o table-data.txt

Output File Content:

============================================================
Document: report.pdf
Page: 1
Parsed: 2024-01-15 14:40:00
============================================================

Field: ProductTable (Table)
----------------------------------------
Product Name	Quantity	Price	Total
Widget A	10	$5.00	$50.00
Widget B	5	$10.00	$50.00
Widget C	3	$15.00	$45.00

============================================================
Statistics: 1 of 1 fields matched
Parse time: 0.87 seconds

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📋 Exit Codes

The application returns the following exit codes:

Code	Description
0	Success
1	License file error
3	Parsing error
4	I/O error (file read/write)

Use these codes in automation scripts to handle errors appropriately.

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🎯 Use Cases

Parse Text Use Cases

• Extract invoice numbers, dates, and customer information
• Parse form data from PDFs
• Extract metadata from documents
• Automated data entry from scanned forms

Parse Tables Use Cases

• Extract financial data from reports
• Parse product catalogs
• Extract tabular data for database import
• Process structured reports automatically

Parse Barcodes Use Cases

• Extract QR codes from documents
• Read product barcodes from invoices
• Process shipping labels
• Extract tracking numbers

Parse Images Use Cases

• OCR text from scanned documents
• Extract data from image-based forms
• Process TIFF files with text recognition
• Convert scanned documents to structured data

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🛠 Template Creation

Templates define the regions where data should be extracted. Create templates using:

1. GroupDocs.Parser GUI – Visual template editor (see README-GUI.md)
2. Manual XML Creation – Define templates in XML format

Template Structure

Templates are XML files that define:

• Field positions and sizes
• Field types (Text, Table, Barcode)
• Field names for extracted data

Example template structure:

<Template>
  <Field Name="InvoiceNumber" Rectangle="100,100,200,120" />
  <Field Name="Date" Rectangle="100,130,200,150" />
  <Table Name="Items" Rectangle="50,200,500,400" />
  <Barcode Name="QRCode" Rectangle="400,100,500,200" />
</Template>

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📌 Limitations

Supported Documents

• PDFs with text
• Scanned PDFs & TIFF images (with OCR enabled)

Supported Field Types

• Text field – Extract text from specified regions
• Table field – Extract structured table data
• Barcode field – Extract barcode values

Template Scope

• Templates work per page (can be reused across pages with the same structure)

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🔧 Troubleshooting

License File Not Found

Error:

✗ License file not found.
ℹ Please ensure a license file exists in the current directory or configure 'LicensePath' in config.json

Solution:

1. Place a .lic file in the application directory, or
2. Update config.json with the correct LicensePath, or
3. Configure LicenseEnv in config.json and set the corresponding environment variable to point to the directory containing GroupDocs.Parser.NET.lic

Template File Not Found

Error:

✗ Template file not found: template.xml

Solution:

• Verify the template file path is correct
• Use absolute paths if relative paths fail
• Check file permissions

Parsing Failed

Error:

✗ Parsing failed: [error message]

Solution:

• Enable verbose mode (--verbose) for detailed error information
• Verify the document format is supported
• Check template compatibility with the document structure
• For scanned documents, enable OCR with --ocr

Low OCR Accuracy

Solution:

• Increase DPI setting: --dpi 600
• Ensure good image quality
• Use appropriate DPI for the document type (300-600 recommended)

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🤝 Contributing

This project is open-source. We welcome contributions!

• Suggest new features
• Submit pull requests
• Report issues
• Improve documentation

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📚 Additional Resources

• GroupDocs.Parser Product Page
• Documentation
• API Reference
• Live Demos
• Forum Support
• Blog

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📜 License

This tool is provided for customer convenience under open-source terms.
For core parsing functionality, a GroupDocs.Parser for .NET license is required.

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🔮 Roadmap

• Automatic detection of scanned vs text-based documents
• Enhanced table parsing support
• Batch processing multiple documents
• Template validation and preview
• Performance optimizations

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Keywords: Parse text, parse tables, parse barcodes, parse images, document parser, PDF parser, OCR, data extraction, template-based parsing, command-line parser, GroupDocs.Parser