name: create-2d-composition
description: >
Compose 2D graphics programmatically using SVG generation, diagram layout
algorithms, image compositing, and batch processing workflows. Use when
generating diagrams, flowcharts, or infographics programmatically, creating
reproducible scientific figures, automating production of badges or visual
assets, building custom chart types not in standard libraries, or batch
generating graphics with parameter variations.
license: MIT
allowed-tools: Read Write Edit Bash Grep Glob
metadata:
author: Philipp Thoss
version: "1.0"
domain: visualization
complexity: intermediate
language: Python
tags: svg, 2d, graphics, composition, diagrams, scripting, batch-processing
locale: es
source_locale: en
source_commit: "75ded7a1"
fence_basis_commit: 75ded7a1
translator: claude
translation_date: "2026-03-17"
Create 2D Composition
Generate 2D graphics programmatically using SVG construction, diagram layout algorithms, image compositing, and batch processing workflows. Covers vector graphics generation, raster image manipulation, typography, and automated production of charts, diagrams, and infographics.
Cuándo Usar
- Generating diagrams, flowcharts, or infographics programmatically
- Creating reproducible scientific figures or publication graphics
- Automating production of badges, icons, or visual assets
- Compositing multiple images or data visualizations
- Building custom chart types not available in standard libraries
- Batch generating graphics with parameter variations
- Creating SVG templates for web or print applications
Entradas
| Input | Type | Description | Example |
|---|
| Layout specification | Configuration | Dimensions, margins, grid layout | Canvas 800x600px, 20px margins |
| Visual elements | Data/Assets | Shapes, text, images, data points | Rectangle coordinates, labels, icons |
| Style parameters | CSS/Attributes | Colors, fonts, stroke widths, opacity | fill="#3366cc", stroke-width="2" |
| Data sources | Files/Arrays | Values to visualize or annotate | CSV data, JSON configuration |
| Output format | String | SVG, PNG, PDF, composite formats | output.svg, 300 DPI PNG |
Procedimiento
1. Set Up Python Environment
Install required libraries for 2D composition:
# Core libraries
pip install svgwrite pillow cairosvg
# Optional: advanced features
pip install drawsvg reportlab pycairo
# For data-driven graphics
pip install matplotlib numpy pandas
Esperado: Libraries installed successfully
En caso de fallo: Check Python version (3.7+), use virtual environment to avoid conflicts
2. Create Basic SVG Graphics
Generate SVG using svgwrite:
import svgwrite
from svgwrite import cm, mm
def create_basic_svg(output_path):
"""Create a simple SVG graphic."""
# Initialize drawing (use mm for precise dimensions)
dwg = svgwrite.Drawing(output_path, size=('180mm', '120mm'), profile='full')
# Add background rectangle
dwg.add(dwg.rect(
insert=(0, 0),
size=('100%', '100%'),
fill='white'
))
# Add shapes
dwg.add(dwg.circle(
center=(90*mm, 60*mm),
r=30*mm,
fill='lightblue',
stroke='navy',
stroke_width=2
))
dwg.add(dwg.rect(
insert=(30*mm, 30*mm),
size=(60*mm, 40*mm),
fill='lightgreen',
stroke='darkgreen',
stroke_width=2,
rx=5, # Rounded corners
ry=5
))
# Add text
dwg.add(dwg.text(
'Example Graphic',
insert=(90*mm, 20*mm),
text_anchor='middle',
font_size='18pt',
font_family='Arial',
fill='black'
))
dwg.save()
print(f"Saved: {output_path}")
Esperado: SVG file generated with shapes and text
En caso de fallo: Check svgwrite version, verify output directory writable
3. Build Diagrams with Layout Logic
Create structured diagrams with calculated positioning:
def create_flowchart(steps, output_path):
"""Generate a flowchart from list of steps."""
dwg = svgwrite.Drawing(output_path, size=('800px', '600px'))
# Layout parameters
box_width = 120
box_height = 60
spacing_y = 100
start_x = 340
start_y = 50
for i, step in enumerate(steps):
y_pos = start_y + i * spacing_y
# Draw box
box = dwg.add(dwg.g(id=f'step_{i}'))
box.add(dwg.rect(
insert=(start_x, y_pos),
size=(box_width, box_height),
fill='lightblue',
stroke='navy',
stroke_width=2,
rx=5,
ry=5
))
# Add text (wrapped if needed)
text_lines = wrap_text(step, max_width=16)
text_y = y_pos + box_height/2 - (len(text_lines)-1) * 7
for j, line in enumerate(text_lines):
box.add(dwg.text(
line,
insert=(start_x + box_width/2, text_y + j*14),
text_anchor='middle',
font_size='12pt',
font_family='Arial',
fill='black'
))
# Draw arrow to next step
if i < len(steps) - 1:
arrow_start_y = y_pos + box_height
arrow_end_y = y_pos + spacing_y
dwg.add(dwg.line(
start=(start_x + box_width/2, arrow_start_y),
end=(start_x + box_width/2, arrow_end_y),
stroke='black',
stroke_width=2,
marker_end=dwg.marker(
id='arrow',
viewBox='0 0 10 10',
refX=5,
refY=5,
markerWidth=6,
markerHeight=6,
orient='auto'
)
))
dwg.save()
def wrap_text(text, max_width=20):
"""Simple text wrapping."""
words = text.split()
lines = []
current_line = []
for word in words:
test_line = ' '.join(current_line + [word])
if len(test_line) <= max_width:
current_line.append(word)
else:
if current_line:
lines.append(' '.join(current_line))
current_line = [word]
if current_line:
lines.append(' '.join(current_line))
return lines
Esperado: Flowchart with connected boxes and arrows
En caso de fallo: Adjust layout calculations, verify arrow marker definitions
4. Composite Raster Images
Combine multiple images using Pillow:
Ejemplo completo de composición con Pillow (diseños en cuadrícula, horizontal y vertical, además de anotación de imágenes): véase references/EXAMPLES.md.
Esperado: Composite image created with proper layout
En caso de fallo: Check all input images exist, verify image modes compatible
5. Generate Data-Driven Graphics
Create visualizations from data:
import numpy as np
def create_bar_chart_svg(data, labels, output_path):
"""Generate SVG bar chart from data."""
dwg = svgwrite.Drawing(output_path, size=('600px', '400px'))
# Chart area
margin = 50
chart_width = 500
chart_height = 300
bar_spacing = 10
# Calculate bar dimensions
n_bars = len(data)
bar_width = (chart_width - (n_bars - 1) * bar_spacing) / n_bars
# Scale data to fit chart
max_value = max(data)
scale = chart_height / max_value
# Draw axes
dwg.add(dwg.line(
start=(margin, margin),
end=(margin, margin + chart_height),
stroke='black',
stroke_width=2
))
dwg.add(dwg.line(
start=(margin, margin + chart_height),
end=(margin + chart_width, margin + chart_height),
stroke='black',
stroke_width=2
))
# Draw bars
for i, (value, label) in enumerate(zip(data, labels)):
x = margin + i * (bar_width + bar_spacing)
bar_height = value * scale
y = margin + chart_height - bar_height
# Bar
dwg.add(dwg.rect(
insert=(x, y),
size=(bar_width, bar_height),
fill='steelblue',
stroke='navy',
stroke_width=1
))
# Value label
dwg.add(dwg.text(
f'{value:.1f}',
insert=(x + bar_width/2, y - 5),
text_anchor='middle',
font_size='10pt',
fill='black'
))
# X-axis label
dwg.add(dwg.text(
label,
insert=(x + bar_width/2, margin + chart_height + 20),
text_anchor='middle',
font_size='10pt',
fill='black'
))
dwg.save()
Esperado: SVG bar chart with scaled data
En caso de fallo: Handle edge cases (empty data, negative values), add validation
6. Batch Generate Graphics
Automate creation of multiple graphics:
def batch_generate_badges(users, template_path, output_dir):
"""Generate badge for each user."""
os.makedirs(output_dir, exist_ok=True)
for user in users:
output_path = os.path.join(output_dir, f"{user['id']}_badge.svg")
dwg = svgwrite.Drawing(output_path, size=('300px', '100px'))
# Background
dwg.add(dwg.rect(
insert=(0, 0),
size=('100%', '100%'),
fill='#3366cc',
rx=10,
ry=10
))
# User name
dwg.add(dwg.text(
user['name'],
insert=(150, 40),
text_anchor='middle',
font_size='20pt',
font_weight='bold',
fill='white'
))
# User role
dwg.add(dwg.text(
user['role'],
insert=(150, 70),
text_anchor='middle',
font_size='14pt',
fill='lightblue'
))
dwg.save()
print(f"Generated badge: {output_path}")
Esperado: Individual graphic generated for each data item
En caso de fallo: Check data structure, handle missing fields with defaults
7. Convert SVG to Raster
Export SVG to PNG/PDF for various uses:
import cairosvg
def svg_to_png(svg_path, png_path, dpi=300):
"""Convert SVG to PNG with specified DPI."""
# Calculate pixel dimensions from DPI
# Assuming A4 size as example
width_inches = 8.27
height_inches = 11.69
width_px = int(width_inches * dpi)
height_px = int(height_inches * dpi)
cairosvg.svg2png(
url=svg_path,
write_to=png_path,
output_width=width_px,
output_height=height_px
)
print(f"Converted to PNG: {png_path}")
def svg_to_pdf(svg_path, pdf_path):
"""Convert SVG to PDF."""
cairosvg.svg2pdf(url=svg_path, write_to=pdf_path)
print(f"Converted to PDF: {pdf_path}")
Esperado: Raster output generated at specified resolution
En caso de fallo: Install cairo system library if missing, check SVG validity
Validación
Errores Comunes
- Unit confusion: SVG units (px, mm, cm) vs screen pixels vs print DPI
- Text overflow: Text exceeding shape boundaries, implement wrapping
- Font availability: System fonts may differ, embed or use web-safe fonts
- Coordinate calculations: Off-by-one errors in grid layouts
- Color format: SVG uses hex strings (
#rrggbb), not tuples
- SVG validity: Check XML structure, close all tags
- File paths: Handle special characters, spaces in filenames
- Memory usage: Large batch operations may require chunking
- Aspect ratio: Maintain proportions when resizing images
- Transparency: PNG supports alpha, JPEG does not
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