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glycorender

A bespoke SVG to PDF/PNG renderer for the GlycoDraw platform, specialized in accurately rendering glycan structures with support for chemical notations and path-based text positioning.

Features

Accurate SVG to PDF and PNG conversion for glycan structures
Support for text on paths with proper positioning and orientation
Special handling for monosaccharide properties like "Df" with proper styling
Gradient fills for circles and shapes
Precise connection path rendering between glycan elements
Support for various SVG path commands

Installation

pip install glycorender

Quick Start

from glycorender import convert_svg_to_pdf, convert_svg_to_png

# Convert SVG file to PDF
with open('glycan_structure.svg', 'r') as f:
    svg_data = f.read()
    
convert_svg_to_pdf(svg_data, 'output.pdf')

# Convert SVG file to PNG
convert_svg_to_png(svg_data, 'output.png')

# Or directly from SVG data
svg_data = """..."""
convert_svg_to_pdf(svg_data, 'output.pdf')
convert_svg_to_png(svg_data, 'output.png')

Use Cases

GlycoRender is specifically designed for:

Converting glycan structure diagrams from GlycoDraw to publication-quality PDFs or PNGs
Preserving the exact layout and styling of complex carbohydrate representations
Ensuring chemical notations are properly formatted in the output
Maintaining the correct connections between monosaccharide units

API Reference

`convert_svg_to_pdf(svg_data, pdf_file_path)`

`convert_svg_to_png(svg_data, png_file_path)`

Converts SVG data to a PDF/PNG file.

Parameters:

svg_data (str or bytes): SVG content either as a string or bytes
png_file_path (str): Path where the output PNG should be saved

Supported SVG Elements

<path>: Full support for path commands (M, L, H, V, Z, etc.)
<circle>: Support for basic circles and gradient-filled circles
<rect>: Support for rectangles with stroke and fill
<text> and <textPath>: Support for text placement along paths with proper orientation
<defs>: Support for path and gradient definitions
<radialGradient>: Support for radial gradients with stops

Dependencies

numpy

Contributing

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

License

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

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