csv2img 1.0.1

Convert CSV files to PNG/JPEG images with Unicode support

csv2img

Convert CSV files to high-quality PNG/JPEG images with full Unicode support (CJK, Arabic, Hebrew, Devanagari, etc.).

Features

• Simple API: Convert CSV to PNG/JPEG with one line of code
• High Quality: Configurable DPI (default 300) for crisp output
• Full Unicode: Auto-detects scripts and uses appropriate fonts — CJK, Arabic, Hebrew, Devanagari, Latin Extended
• Multi-page Support: Automatically handles CSV files that span multiple pages
• Flexible Formats: Output as PNG or JPEG
• Custom Delimiters: Supports TSV, semicolon-separated, or any delimiter
• CLI Support: Use from command line or as a Python library
• Zero csv2pdf dependency: Pure fpdf2 + PyMuPDF

Installation

From PyPI (recommended)

pip install csv2img

From Source

git clone https://github.com/Shun-Calvin/csv2img.git
cd csv2img
pip install -e .

Usage

Python Library

Basic Usage

from csv2img import saveas

# Convert a CSV file to PNG images
output_files = saveas("data.csv")
print(f"Generated {len(output_files)} images: {output_files}")

Unicode (CJK) — Auto-Detected

from csv2img import saveas

# Chinese/Japanese/Korean text is auto-detected and rendered with Noto Sans CJK
output_files = saveas("chinese_data.csv")
# Output: chinese_data1.png (with proper CJK characters)

Custom Format & DPI

from csv2img import saveas

# Convert to JPEG at 600 DPI
output_files = saveas("report.csv", dpi=600, output_format="jpeg")

Custom Delimiter (TSV, semicolon, etc.)

from csv2img import saveas

# Tab-separated values
output_files = saveas("data.tsv", delimiter="\t")

# Semicolon-separated (common in European locales)
output_files = saveas("data.csv", delimiter=";")

Custom Font

from csv2img import saveas

# Use your own TTF/OTF font file
output_files = saveas("data.csv", font_path="/path/to/your/font.ttf")

Using the Alternative Function Name

from csv2img import convert_file

output_files = convert_file("data.csv", output_dir="./images", dpi=300)

Command Line Interface

After installation, you can use the csv2img command:

# Basic usage
csv2img data.csv

# Specify output directory
csv2img data.csv ./output

# Specify output directory and DPI
csv2img data.csv ./output 600

# Specify output format
csv2img data.csv ./output 300 --format jpeg

# Specify delimiter (TSV)
csv2img data.csv ./output 300 --delimiter $'\t'

# Custom font
csv2img data.csv ./output 300 --font /path/to/font.ttf

API Reference

saveas(source, dpi=300, output_dir=None, output_format="png", delimiter=",", font_path=None)

Convert a CSV file to image files.

Parameters:

• source (str | Path): Path to the source CSV file (required)
• dpi (int): Resolution for output images (default: 300)
• output_dir (str, optional): Directory to save output images (default: same as source)
• output_format (str): Output format — 'png' or 'jpeg' (default: 'png')
• delimiter (str): CSV delimiter character (default: ',')
• font_path (str, optional): Path to a TTF/OTF font file. If None, auto-detects from system fonts based on CSV content.

Returns:

• List[str]: List of paths to the generated image files

Raises:

• FileNotFoundError: If the source CSV file doesn't exist
• ValueError: If the source file is not a CSV file or format is unsupported
• ImportError: If required dependencies are not installed

SUPPORTED_FORMATS

A list of supported output formats: ["png", "jpeg", "jpg"]

Unicode Font Support

csv2img auto-detects the dominant script in your CSV and uses the appropriate font:

Script	Unicode Range	Font Used
CJK (Chinese/Japanese/Korean)	\u4e00-\u9fff, \u3040-\u30ff	Noto Sans CJK
Arabic	\u0600-\u06ff	Noto Sans Arabic
Hebrew	\u0590-\u05ff	Noto Sans Hebrew
Devanagari (Hindi, etc.)	\u0900-\u097f	Noto Sans Devanagari
Latin Extended	\u0080-\u024f	Noto Sans Mono

You can override auto-detection by passing font_path explicitly.

How It Works

1. The CSV file is parsed using Python's built-in csv module (supports any delimiter)
2. fpdf2 renders the table to a PDF with Unicode-aware TTF fonts
3. PyMuPDF (fitz) renders each PDF page as a high-quality image
4. The temporary PDF file is automatically cleaned up

Example:

• Input: data.csv
• Output: data1.png, data2.png, data3.png (if the CSV spans 3 pages)

Requirements

• Python 3.7+
• fpdf2 (PDF rendering with Unicode font support)
• PyMuPDF (PDF to image rendering)

Troubleshooting

Font Missing for Specific Script

If your CSV contains characters not covered by the auto-detected font, pass a custom font:

from csv2img import saveas

# Use a font that covers your specific characters
output_files = saveas("data.csv", font_path="/path/to/font.ttf")

Permission Errors

Ensure you have write permissions in the output directory. If specifying a custom output directory, it will be created automatically if it doesn't exist.

Memory Issues

For very large CSV files:

• Reduce the DPI setting (e.g., use 150 instead of 300)
• Ensure sufficient disk space for temporary PDF and output images

Testing

pip install pytest
python -m pytest tests/ -v

Changelog

Version 0.4.0 (2026-06-17)

• ✨ Removed csv2pdf dependency — pure fpdf2 + PyMuPDF implementation
• ✨ Full Unicode support — auto-detects CJK, Arabic, Hebrew, Devanagari, Latin Extended
• ✨ JPEG output format — PNG and JPEG both supported
• ✨ Custom delimiter — TSV, semicolon, or any separator
• ✨ Custom font path — pass your own TTF/OTF font file
• ✨ Path object support — source accepts str or Path
• ✨ Empty CSV handling — returns [] instead of crashing
• ✨ Output validation — verifies generated files exist and are non-empty
• 🐛 Fixed PDF cleanup — removes temp PDF after return, not in finally
• 📦 Updated dependencies — csv2pdf>=1.0.0 → fpdf2>=2.5.0

Version 0.3.0 (2026-04-07)

• Added JPEG and PNG format support
• Added delimiter parameter
• Improved error handling and output validation

Version 0.2.0 (2026-04-07)

• ✨ Added comprehensive error handling and input validation
• ✨ Added type hints and docstrings
• ✨ Added logging support
• ✨ Added command-line interface
• ✨ Added setup.py for proper package installation
• ✨ Added requirements.txt
• ✨ Improved documentation with examples
• 🐛 Fixed temporary PDF cleanup
• 📦 Added proper package structure

Version 0.1.0 (2022)

• Initial release
• Basic CSV to PNG conversion functionality

License

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

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request