graphable 0.3.0

A lightweight, type-safe library for building, managing, and visualizing dependency graphs.

graphable

graphable is a lightweight, type-safe Python library for building, managing, and visualizing dependency graphs. It provides a simple API for defining nodes and their relationships, performing topological sorts, and exporting graphs to various formats like Mermaid, Graphviz, and ASCII text trees.

Features

• Type-Safe: Built with modern Python generics and type hints.
• Topological Sorting: Easily get nodes in dependency order.
• Cycle Detection: Built-in protection against circular dependencies.
• Filtering & Tagging: Create subgraphs based on custom predicates or tags.
• Visualizations:
  • Mermaid: Generate flowchart definitions or export directly to SVG.
  • Graphviz: Generate DOT definitions or export to SVG with custom styling.
  • D2: Generate D2 definitions or export to SVG with modern styling and layouts.
  • PlantUML: Generate component or deployment diagram definitions.
  • TikZ: Generate high-quality LaTeX definitions for academic documents.
  • GraphML: Industrial-standard XML export for professional analysis tools (Gephi, yEd).
  • Interactive HTML: Generate a single, portable HTML file with zooming and panning.
  • JSON & Cytoscape: Export graph structure as machine-readable data.
  • CSV: Export simple edge lists for data processing.
  • NetworkX: Seamless integration with the NetworkX library for advanced analysis.
  • Text Tree & ASCII Flowchart: Generate beautiful ASCII representations.
• Modern Tooling: Managed with uv and just.

Installation

uv add graphable
# or
pip install graphable

Quick Start

from graphable.graph import Graph
from graphable.graphable import Graphable
from graphable.views.texttree import create_topology_tree_txt

# 1. Define your nodes
a = Graphable("Database")
b = Graphable("API Service")
c = Graphable("Web Frontend")

# 2. Build the graph
g = Graph()
g.add_edge(a, b)  # API Service depends on Database
g.add_edge(b, c)  # Web Frontend depends on API Service

# 3. Get topological order
for node in g.topological_order():
    print(node.reference)
# Output: Database, API Service, Web Frontend

# 4. Visualize as a text tree
print(create_topology_tree_txt(g))
# Output:
# Web Frontend
# └─ API Service
#    └─ Database

Visualizing with ASCII Flowchart

from graphable.views.asciiflow import create_topology_ascii_flow

print(create_topology_ascii_flow(g))
# Output:
# +----------+
# | Database |
# +----------+
#   v
#   +--> API Service
#
# +-------------+
# | API Service |
# +-------------+
#   v
#   +--> Web Frontend

Visualizing with Mermaid

from graphable.views.mermaid import create_topology_mermaid_mmd

mmd = create_topology_mermaid_mmd(g)
print(mmd)
# Output:
# flowchart TD
# Database --> API Service
# API Service --> Web Frontend

Visualizing with Graphviz

from graphable.views.graphviz import create_topology_graphviz_dot

dot = create_topology_graphviz_dot(g)
print(dot)
# Output:
# digraph G {
#     "Database" [label="Database"];
#     "Database" -> "API Service";
#     "API Service" [label="API Service"];
#     "API Service" -> "Web Frontend";
#     "Web Frontend" [label="Web Frontend"];
# }

Advanced Analysis with NetworkX

If you have networkx installed, you can convert your graph for advanced analysis:

import networkx as nx

# Convert to NetworkX DiGraph
dg = g.to_networkx()

# Use NetworkX algorithms
print(nx.dag_longest_path(dg))
# Output: ['Database', 'API Service', 'Web Frontend']

Visualizing with D2

from graphable.views.d2 import create_topology_d2

d2 = create_topology_d2(g)
print(d2)
# Output:
# Database: Database
# Database -> API Service
# API Service: API Service
# API Service -> Web Frontend
# Web Frontend: Web Frontend

Documentation

Full documentation is available in the docs/ directory. You can build it locally:

just docs-view

Development

This project uses uv for dependency management and just as a command runner.

just install    # Install dependencies
just check      # Run linting, type checking, and tests
just coverage   # Run tests with coverage report

License

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