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.
Scanned 9/3/2026
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---
name: create-2d-composition
locale: caveman
source_locale: en
source_commit: "75ded7a1"
fence_basis_commit: 75ded7a1
translator: "Julius Brussee homage — caveman"
translation_date: "2026-04-19"
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
---
# Create 2D Composition
Make 2D graphics by code. SVG building, diagram layout, image compositing, batch workflows. Covers vector, raster, typography, auto-production of charts, diagrams, infographics.
## When Use
- Making diagrams, flowcharts, infographics by code
- Building reproducible scientific figures
- Auto-producing badges, icons, assets
- Compositing images or data visualizations
- Building custom chart types not in standard libs
- Batch graphics with param variations
- SVG templates for web or print
## Inputs
| 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 |
## Steps
### 1. Set Up Python Environment
Install libs for 2D composition:
```bash
# Core libraries
pip install svgwrite pillow cairosvg
# Optional: advanced features
pip install drawsvg reportlab pycairo
# For data-driven graphics
pip install matplotlib numpy pandas
```
**Got:** Libraries installed fine. **If fail:** Check Python version (3.7+). Use virtual env
### 2. Create Basic SVG Graphics
Generate SVG with svgwrite:
```python
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}")
```
**Got:** SVG file made with shapes and text. **If fail:** Check svgwrite version. Confirm output dir writable
### 3. Build Diagrams with Layout Logic
Build structured diagrams with calculated positions:
```python
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
```
**Got:** Flowchart with connected boxes and arrows. **If fail:** Tune layout math. Verify arrow marker definitions
### 4. Composite Raster Images
Combine many images with Pillow:
Full Pillow composite example (grid, horizontal, vertical layout + image annotate) live in [references/EXAMPLES.md](../../../../skills/create-2d-composition/references/EXAMPLES.md).
**Got:** Composite image made with right layout. **If fail:** Check all input images exist. Verify image modes match
### 5. Generate Data-Driven Graphics
Make visualizations from data:
```python
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()
```
**Got:** SVG bar chart with scaled data. **If fail:** Handle edge cases (empty data, negatives). Add validation
### 6. Batch Generate Graphics
Auto-make many graphics:
```python
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}")
```
**Got:** Individual graphic made for each data item
**If fail:** Check data structure. Handle missing fields with defaults
### 7. Convert SVG to Raster
Export SVG to PNG/PDF for many uses:
```python
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}")
```
**Got:** Raster output at right resolution
**If fail:** Install cairo system library if missing. Check SVG validity
## Checks
- [ ] Graphics render right in target apps
- [ ] Text readable, positioned well
- [ ] Colors match specs
- [ ] Dimensions fit use case
- [ ] SVG validates (if needed)
- [ ] Raster exports have right DPI
- [ ] Layout adapts to data
- [ ] Batch processing finishes clean
- [ ] Output files organized
- [ ] Code has error handling
## Pitfalls
1. **Unit confusion**: SVG units (px, mm, cm) vs screen pixels vs print DPI
2. **Text overflow**: Text past shape boundaries. Wrap it
3. **Font availability**: System fonts differ. Embed or use web-safe fonts
4. **Coordinate math**: Off-by-one errors in grid layouts
5. **Color format**: SVG uses hex strings (`#rrggbb`), not tuples
6. **SVG validity**: Check XML. Close all tags
7. **File paths**: Handle special chars, spaces in filenames
8. **Memory usage**: Big batch jobs may need chunking
9. **Aspect ratio**: Keep proportions when resizing
10. **Transparency**: PNG supports alpha. JPEG does not
## See Also
- `render-publication-graphic` — publication output
- `create-3d-scene` — similar programmatic approach for 3D
- `generate-quarto-report` — integrating graphics into reports
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