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Interactive Visualization of SQL Dependencies

SQLDeps provides powerful visualization capabilities to help you understand and explore SQL dependencies across your projects.

Interactive Dependency Graphs

The visualize_sql_dependencies() function creates an interactive network graph that shows the relationships between SQL files, tables, and their dependencies.

Basic Usage

from sqldeps.llm_parsers import create_extractor
from sqldeps.visualization import visualize_sql_dependencies

# Create an interactive network graph from multiple SQL files
extractor = create_extractor()
sql_profiles = extractor.extract_from_folder("path/to/folder", recursive=False)

# Generate an interactive visualization (saving output to an HTML file)
figure = visualize_sql_dependencies(sql_profiles, output_path="dependencies.html")

# Show figure on IDE
figure.show()

Visualization Options

The visualize_sql_dependencies() function offers extensive customization:

# See API documentation for more options
# https://sqldeps.readthedocs.io/en/latest/api-reference/visualization

figure = visualize_sql_dependencies(
    dependencies,
    output_path="dependencies.html",  # Optional: Save to HTML file
    show_columns=True,                # Show column details in hover text
    layout_algorithm="spring",        # Layout options: 'spring', 'circular', 'kamada_kawai'
    highlight_common_tables=True,     # Highlight tables used by multiple files
    show_file_text=True,              # Show file names
    show_table_text=False,            # Show table names
    color_gradient=True,              # Color intensity based on usage frequency
    min_file_size=20,                 # Minimum node size for files
    max_file_size=40,                 # Maximum node size for files
    show_text_buttons=True,           # Add buttons to toggle text visibility
    show_layout_buttons=True          # Add buttons to change graph layout
)

Visualization Features

  • Interactive Exploration: Hover over nodes to see detailed information
  • Dynamic Layout: Change graph layout with built-in buttons
  • Text Toggle: Show/hide labels for files and tables
  • Usage Visualization:
    • Node sizes indicate usage frequency
    • Color intensity represents how many files use a particular table
  • Dependency Insights:
    • Visualize connections between SQL files and tables
    • Identify common tables across multiple files

Example Use Cases

  1. Project Dependency Mapping 

    # Map dependencies across an entire project
project_deps = extractor.extract_from_folder(
    "path/to/project/sql", 
    recursive=True
)
# Plot dependencies
visualize_sql_dependencies(project_deps, output_path="project_deps.html")

  2. Focused Analysis 

    # Analyze dependencies for a specific subset of files
subset_deps = extractor.extract_from_folder(
    "path/to/specific/sql/folder", 
    recursive=False
)
# Plot dependencies
visualize_sql_dependencies(subset_deps, output_path="subset_deps.html")

Use cases

You can use the visualization to identify:

  • Shared tables across different files
  • Potential refactoring opportunities
  • Complex dependency relationships

Note: The visualization is best suited for projects with a moderate number of SQL files