An open API service indexing awesome lists of open source software.

https://github.com/rushi-balapure/pdf_2_json_extractor

A high-performance Python library for extracting structured content from PDF documents with layout-aware text extraction. pdf_to_json preserves document structure including headings (H1-H6) and body text, outputting clean JSON format.
https://github.com/rushi-balapure/pdf_2_json_extractor

cli-tool cpu-only cross-platform data-extraction document-parsing document-processing json layout-analysis nlp offline pdf pdf-extraction pdf-parser pdf-processing pdf-to-json python python-library structure-extraction text-extraction

Last synced: 6 days ago
JSON representation

A high-performance Python library for extracting structured content from PDF documents with layout-aware text extraction. pdf_to_json preserves document structure including headings (H1-H6) and body text, outputting clean JSON format.

Awesome Lists containing this project

README

          

# pdf_2_json_extractor

[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](LICENSE)
[![Python Version](https://img.shields.io/badge/python-3.8%2B-blue.svg)](https://python.org)
[![PyPI Version](https://img.shields.io/pypi/v/pdf_2_json_extractor.svg)](https://pypi.org/project/pdf_2_json_extractor/)
[![Coverage Status](https://coveralls.io/repos/github/Rushi-Balapure/pdf_2_json_extractor/badge.svg?branch=main)](https://coveralls.io/github/Rushi-Balapure/pdf_2_json_extractor?branch=main)

A high-performance Python library for extracting structured content from PDF documents with layout-aware text extraction. pdf_2_json_extractor preserves document structure including headings (H1-H6) and body text, outputting clean JSON format.

## Features

- **Layout-aware extraction**: Detects document structure including headings of different levels using font size and style analysis
- **Multilingual support**: Handles Latin, Cyrillic, Asian scripts (Chinese, Japanese, Korean), Arabic, Hebrew, and other complex Unicode scripts
- **High performance**: Processes 50-page PDFs in ≤10 seconds on modern CPUs
- **Small footprint**: Minimal dependencies, no heavy ML models used
- **Offline operation**: No internet connectivity required to run
- **Cross-platform**: AMD64 compatible, runs purely on CPU
- **Easy to use**: Simple API with both programmatic and CLI interfaces

## Installation

```bash
pip install pdf_2_json_extractor
```

## Quick Start

### Python API

```python
import pdf_2_json_extractor

# Extract PDF to dictionary
result = pdf_2_json_extractor.extract_pdf_to_dict("document.pdf")
print(f"Title: {result['title']}")
print(f"Number of sections: {result['stats']['num_sections']}")

# Extract PDF to JSON string
json_output = pdf_2_json_extractor.extract_pdf_to_json("document.pdf")
print(json_output)

# Save to file
pdf_2_json_extractor.extract_pdf_to_json("document.pdf", "output.json")
```

### Command Line Interface

```bash
# Extract to stdout
pdf_2_json_extractor document.pdf

# Save to file
pdf_2_json_extractor document.pdf -o output.json

# Compact output
pdf_2_json_extractor document.pdf --compact

# Pretty print (default)
pdf_2_json_extractor document.pdf --pretty
```

## JSON Output Format

```json
{
"title": "Document Title",
"sections": [
{
"level": "H1",
"title": "Chapter 1: Introduction",
"paragraphs": ["This is the introduction text..."]
},
{
"level": "H2",
"title": "1.1 Overview",
"paragraphs": ["Overview content..."]
},
{
"level": "content",
"title": null,
"paragraphs": ["Body text content..."]
}
],
"font_histogram": {
"12.0": 1500,
"14.0": 200,
"16.0": 50
},
"heading_levels": {
"16.0": "H1",
"14.0": "H2"
},
"stats": {
"page_count": 25,
"processing_time": 2.34,
"num_sections": 15,
"num_headings": 8,
"num_paragraphs": 45
}
}
```

## Advanced Usage

### Custom Configuration

```python
from pdf_2_json_extractor import PDFStructureExtractor, Config

# Create custom configuration
config = Config()
config.MAX_PAGES_FOR_FONT_ANALYSIS = 5
config.MIN_HEADING_FREQUENCY = 0.002

# Use with custom config
extractor = PDFStructureExtractor(config)
result = extractor.extract_text_with_structure("document.pdf")
```

### Error Handling

```python
from pdf_2_json_extractor import extract_pdf_to_dict
from pdf_2_json_extractor.exceptions import PdfToJsonError, InvalidPDFError, PDFFileNotFoundError

try:
result = extract_pdf_to_dict("document.pdf")
except PDFFileNotFoundError:
print("PDF file not found")
except InvalidPDFError:
print("Invalid or corrupted PDF file")
except PdfToJsonError as e:
print(f"Processing error: {e}")
```

## Configuration Options

You can configure pdf_2_json_extractor using environment variables:

```bash
# Font analysis settings
export PDF_TO_JSON_MAX_PAGES_FOR_FONT_ANALYSIS=10
export PDF_TO_JSON_FONT_SIZE_PRECISION=0.1
export PDF_TO_JSON_MIN_HEADING_FREQUENCY=0.001

# Text processing settings
export PDF_TO_JSON_MIN_TEXT_LENGTH=3
export PDF_TO_JSON_MAX_HEADING_LEVELS=6
export PDF_TO_JSON_COMBINE_CONSECUTIVE_TEXT=True

# Language support
export PDF_TO_JSON_MULTILINGUAL_SUPPORT=True
export PDF_TO_JSON_DEFAULT_ENCODING=utf-8

# Performance settings
export PDF_TO_JSON_PROCESS_PAGES_IN_CHUNKS=False
export PDF_TO_JSON_CHUNK_SIZE=10

# Debug settings
export PDF_TO_JSON_DEBUG_MODE=False
export PDF_TO_JSON_LOG_LEVEL=INFO
```

## Development

### Installation from Source

```bash
pip install pdf_2_json_extractor
```
or

```bash
git clone https://github.com/your-username/pdf_2_json_extractor.git
cd pdf_2_json_extractor
pip install -e .
```

### Building the Library

```bash
# Build the package
./build.sh

# Or manually
python -m build
```

### Running Tests

```bash
pip install -e ".[dev]"
pytest
```

### Docker Development

```bash
# Build Docker image
docker build -t pdf_2_json_extractor:latest .

# Run with Docker
docker run --rm -v $(pwd)/test:/test pdf_2_json_extractor:latest /test/document.pdf
```

## Performance

pdf_2_json_extractor is optimized for high performance:

- **CPU-only processing**: No GPU requirements
- **Memory efficient**: Processes large documents without excessive memory usage
- **Fast extraction**: Typical processing times:
- 10-page document: ~1-2 seconds
- 50-page document: ~5-10 seconds
- 100-page document: ~15-25 seconds

## Supported Languages

pdf_2_json_extractor supports text extraction from PDFs containing:

- Latin scripts (English, Spanish, French, German, etc.)
- Cyrillic scripts (Russian, Bulgarian, Serbian, etc.)
- Asian scripts (Chinese, Japanese, Korean)
- Arabic and Hebrew scripts
- Other Unicode scripts

## License

This project is licensed under the **Apache License 2.0** - see the [LICENSE](LICENSE) file for details.

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

## References

This library is inspired by the research paper:

**"Layout-Aware Text Extraction from Full-text PDF of Scientific Articles"**
_Cartic Ramakrishnan, Abhishek Patnia, Eduard Hovy, Gully APC Burns_
Published in Source Code for Biology and Medicine (2012)
[Full Paper](http://www.scfbm.org/content/7/1/7)

## Support

For questions, issues, or contributions:

- 📧 Email: rishibalapure12@gmail.com
- 🐛 Issues: [GitHub Issues](https://github.com/your-username/pdf_2_json_extractor/issues)
- 📖 Documentation: [GitHub Wiki](https://github.com/your-username/pdf_2_json_extractor/wiki)