pypgsvg 1.2.2

Generate SVG Entity Relationship Diagrams from PostgreSQL database dump files

pypgsvg - Lightweight PostgreSQL ERD Generator

pypgsvg is a lightweight Python tool that generates a JS/CSS/SVG interactive Entity Relationship Diagrams (ERDs) from PostgreSQL schema dump files. With only Graphviz as a dependency, manually run or place in CI/CD pipelines, fast rapid deployment verification scenarios.

📦 Installation

Lightweight setup - only 2 steps:

1. Install pypgsvg:

   pip install pypgsvg
   

2. Install Graphviz (external dependency):

   • macOS: brew install graphviz
   • Ubuntu/Debian: sudo apt-get install graphviz
   • CentOS/RHEL: sudo yum install graphviz
   • Windows: Download from Graphviz.org

That's it! Ready for deployment.

---

🎬 Quick Demo

[🎯 View Interactive Example]

Try it yourself:

# Download sample and generate interactive ERD
wget https://github.com/blackburnd/pypgsvg/raw/main/Samples/complex_schema.dump
pypgsvg schema.dump --output demo_erd --view

🛠️ Enterprise Usage

Quick Start - Schema Analysis

# Generate interactive ERD from schema dump
pypgsvg schema.dump --output database_erd --view

# Enterprise automation (CI/CD ready)
pypgsvg Samples/complex_schema.dump --output Samples/complex_schema --rankdir LR --node-sep 4

Advanced Enterprise Options

# Large schema optimization
pypgsvg Samples/complex_schema.dump --output Samples/complex_schema --rankdir LR --node-sep 4
source venv/bin/activate && python -m src.pypgsvg Samples/complex_schema.dump --node-shape=ellipse --show-standalone=false --output=./Samples/complex_schema --rankdir LR --node-sep 2 --packmode


# Custom layout for documentation
pypgsvg schema.dump --rankdir LR --fontsize 20 --node-fontsize 16 --output presentation_erd

Usage

Get Your PostgreSQL Schema

If you don't have a schema dump, generate one with pg_dump:

# Standard schema export (most common)
pg_dump -h your-host -d database -U username -s --no-owner --no-privileges > schema.dump

# Comprehensive export with triggers and functions
pg_dump -h your-host -d database -U username -s -O -F plain --disable-triggers --encoding=UTF8 > schema.dump

Or use our sample schema for testing.

Interactive ERD Generation

Basic usage:

pypgsvg schema.dump --output my_database_erd --view

Usage:

pypgsvg schema.dump \
  --output docs/database_architecture \
  --rankdir TB \
  --node-sep 4 \
  --packmode graph \
  --rank-sep 3 \
  --hide-standalone

The generated SVG includes:

• 🖱️ Interactive selection - Click tables/edges to view SQL details
• 📱 Miniature navigator - Overview panel for large schemas
• 📋 Copy/download tools - Export selected elements
• 🎨 Resizable panels - Customize your workspace
• ⌨️ Keyboard shortcuts - ESC/R to reset view

Note: For full interactivity, open the SVG file locally in your browser. GitHub restricts JavaScript for security.

Scriptable API

Perfect for automation and enterprise workflows:

from pypgsvg import parse_sql_dump, generate_erd_with_graphviz

# Parse schema dump
with open("schema.dump", "r", encoding='utf-8') as file:
    sql_content = file.read()

# Extract database structure  
tables, foreign_keys, triggers, errors = parse_sql_dump(sql_content)

# Generate interactive ERD
if not errors:
    generate_erd_with_graphviz(
        tables=tables,
        foreign_keys=foreign_keys, 
        output_file="enterprise_diagram",
        rankdir='TB',
        packmode='graph'
    )
    print("✅ Enterprise ERD generated successfully!")
else:
    print("⚠️ Parsing errors:", errors)

---

⚙️ Complete Command-Line Reference

Core Arguments

Argument	Type	Default	Description
input_file	Required	-	Path to the PostgreSQL dump file
-o, --output	String	schema_erd	Output file name (without extension)
--view	Flag	false	Open the generated SVG in a browser
--show-standalone	String	true	Show/hide tables with no foreign key relationships

Layout & Positioning

Argument	Type	Default	Options	Description
--packmode	String	array	array, cluster, graph	Graphviz packmode - Controls how components are packed together
--rankdir	String	TB	TB, LR, BT, RL	Graphviz rankdir - Graph direction (Top-Bottom, Left-Right, etc.)
--esep	String	8	Any number	Graphviz esep - Edge separation distance in points
--node-sep	String	0.5	Any number	Graphviz nodesep - Minimum distance between nodes
--rank-sep	String	1.2	Any number	Graphviz ranksep - Distance between ranks/levels

Typography & Styling

Argument	Type	Default	Description
--fontname	String	Arial	Font family for all text elements
--fontsize	Integer	18	Font size for graph title/labels
--node-fontsize	Integer	14	Font size for table names and column text
--edge-fontsize	Integer	12	Font size for relationship labels
--node-style	String	rounded,filled	Graphviz node style (e.g., filled, rounded,filled)
--node-shape	String	rect	Graphviz node shape (e.g., rect, ellipse, box)

Color & Visual Enhancement

Argument	Type	Default	Description
--saturate	Float	1.8	Color saturation multiplier for table backgrounds
--brightness	Float	1.0	Brightness adjustment for table colors

Understanding Graphviz Parameters

Packmode Options

• array (default): Tables arranged in a regular grid pattern
• cluster: Groups related tables together spatially
• graph: Optimizes overall graph layout, best for complex schemas

Rankdir Options

• TB (Top-Bottom): Traditional vertical flow, tables flow downward
• LR (Left-Right): Horizontal flow, good for wide displays
• BT (Bottom-Top): Reverse vertical flow
• RL (Right-Left): Reverse horizontal flow

Distance Parameters

• esep: Controls spacing between edges (relationship lines)
• node-sep: Minimum distance between table nodes
• rank-sep: Distance between different levels/ranks of tables

Advanced Filtering

Tables are automatically excluded based on common patterns:

• Views: vw_*, *_view
• Temporary: *_temp, *_tmp, temp_*
• Backup: *_bk, *_backup, *_old
• Audit/Log: *_log, *_audit, audit_*
• Duplicates: *_dups, *_duplicates
• Archives: *_archive, archive_*

Use --show-standalone false to hide tables with no foreign key relationships.

---

🎯 Interactive Components

The generated SVG includes several interactive panels that can be moved, resized, and minimized:

📊 Metadata Panel

Displays comprehensive information about your database schema:

• Schema statistics (table count, columns, relationships)
• Generation parameters used
• File information and timestamps
• Interactive controls (minimize, close, drag to reposition)

🗺️ Miniature Overview

Navigate large schemas effortlessly:

• Interactive minimap with viewport indicator
• Click to jump to specific schema areas
• Drag viewport for precise navigation
• Resizable panel - make it larger for detailed navigation

🔍 Selection Details

View and export detailed SQL information:

• Table definitions with column details and constraints
• Foreign key relationships with full SQL syntax
• Trigger information including execution details
• Copy button for instant clipboard access
• Download button for formatted text export
• Enterprise-friendly emoji-free output option

Example selection output:

📊 Selected Tables
==================
public_franchises
public_association_map
public_ecommerce
...

🔗 Foreign Key Relationships  
============================
🔑 franchise_id → id
ALTER TABLE ONLY public.association_map
    ADD CONSTRAINT association_map_franchise_id_fkey 
    FOREIGN KEY (franchise_id) REFERENCES public.franchises(id) 
    ON DELETE CASCADE;

---

For detailed testing instructions, see the Testing Guide.

Quality metrics:

• ✅ 95%+ code coverage
• ✅ 70+ comprehensive tests
• ✅ Cross-platform compatibility

---

🏗️ Architecture & Performance

Lightweight Design

📦 pypgsvg/
├── 🐍 Pure Python core (~450 lines)
├── 🎨 CSS styling (~200 lines)  
├── ⚡ JavaScript interactivity (~2000 lines)
├── 🧪 Comprehensive tests (~1000+ lines)
└── 📚 Zero runtime dependencies (except Graphviz)

Performance characteristics:

• Fast parsing - Processes large schemas in seconds
• Memory efficient - Minimal footprint for enterprise deployment
• Scalable output - Handles schemas with hundreds of tables
• Quick startup - No database connections or heavy frameworks

Enterprise-Ready Features

• 🔒 Security-focused - No network requirements, processes local files only
• 📋 Audit-friendly - Deterministic output for version control
• 🚀 Container-ready - Minimal Docker image size
• ⚙️ Configurable - Extensive customization options
• 📊 Monitoring - Built-in error reporting and validation

---

⚙️ Configuration & Customization

Advanced Layout Options

# Horizontal layout for wide displays
pypgsvg schema.dump --rankdir LR --node-sep 3 --rank-sep 2

# Compact layout for presentations  
pypgsvg schema.dump --packmode graph --fontsize 16 --node-fontsize 14

# Large schema optimization
pypgsvg schema.dump --hide-standalone --esep 8 --rank-sep 4

Table Filtering (Automatic)

Enterprise-focused exclusions for cleaner diagrams:

• Views (vw_*) - Database views
• Backup tables (*_bk, *_backup) - Temporary backup data
• Utility tables (*_temp, *_tmp) - Temporary processing tables
• Log tables (*_log, *_audit) - Audit and logging tables
• Duplicate tables (*_dups, *_duplicates) - Data cleanup tables
• Version tables (*_old, *_archive) - Historical data tables

Color & Accessibility

• WCAG-compliant color palette with proper contrast ratios
• Automatic text color calculation for readability
• Color-blind friendly palette selection
• High-contrast mode for professional presentations

---

---

🚨 Error Handling & Reliability

Error management:

• Graceful degradation - Continues processing despite individual parsing errors
• Detailed error reporting - Specific line numbers and context
• Encoding resilience - Handles various character encodings
• Malformed SQL recovery - Attempts to extract partial information
• Validation checks - Ensures output integrity

Logging:

# Built-in error collection for monitoring
tables, foreign_keys, triggers, errors = parse_sql_dump(sql_content)

if errors:
    for error in errors:
        log.warning(f"Schema parsing issue: {error}")
    # Continue with partial results

---

🤝 Contributing

Welcome users and contributors:

1. Code quality - Follow PEP 8 and maintain >95% test coverage
2. Enterprise focus - Consider automation and deployment scenarios
3. Performance - Optimize for large schemas and CI/CD usage
4. Documentation - Update examples for enterprise use cases
5. Testing - Add tests for new SQL patterns and edge cases

---

Required

• Python 3.8+ (standard in most enterprise environments)
• Graphviz (system package, widely available)

Development/Testing Only

• Node.js/npm - Required for running browser tests only
• pytest>=7.0.0 - Testing framework
• pytest-cov>=4.0.0 - Coverage reporting
• playwright>=1.37.0 - Browser testing framework

Development Setup

Quick Install (From Source)

If you're cloning the repository for development, use the automated installer:

# Clone the repository
git clone https://github.com/blackburnd/pypgsvg.git
cd pypgsvg

# Run the automated installer
./install.sh

The installer will:

• Detect your operating system (macOS, Ubuntu/Debian, CentOS/RHEL)
• Install Graphviz system package
• Install Node.js and npm
• Create Python virtual environment
• Install Python dependencies
• Install Playwright browser binaries

Supported platforms: macOS (with Homebrew), Ubuntu/Debian, CentOS/RHEL

Manual Setup

If the automated installer doesn't support your system:

# 1. Install system dependencies
brew install graphviz node  # macOS
# or
sudo apt-get install graphviz nodejs npm  # Ubuntu/Debian

# 2. Create virtual environment and install Python dependencies
python3 -m venv venv
source venv/bin/activate
pip install -e ".[test]"

# 3. Install Playwright browsers
npx playwright install

Testing

The project includes both unit tests (Python) and functional tests (browser-based).

Quick Start

Use the provided test runner script which handles environment setup:

# Run unit tests
./run-tests.sh

# Run browser tests
./run-tests.sh --browser