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Generate and render Graphviz diagrams with clear, maintainable code by separating presentation from structure.

The heart of gvdot is the class Dot, a DOT language builder. Applications create diagrams using Dot methods, then either convert the instance to DOT language text or render it as SVG or an image. Users can also interactively display Dot objects in notebooks.

Example

Suppose we want to generate diagrams of nondeterministic finite automata like this:

Example NFA

represented by instances of

@dataclass
class NFA:
    alphabet : str
    delta    : dict[str, list[list[str]]]
    final    : list[str]
    start    : str

where delta["q"][0] is the list of states reached from state q by epsilon transitions, and delta["q"][i] is the list of states reached from q by symbol alphabet[i-1].

We start by defining a theme, a normal Dot object from which other Dot objects can inherit graph attributes, default attributes, and roles.

nfa_theme = (Dot()
    .all_default(fontsize=12)
    .node_default(shape="circle", style="filled", fillcolor="khaki")
    .node_role("init", label="", shape="none", width=0, height=0)
    .node_role("final", shape="doublecircle", penwidth=1.25)
    .graph(rankdir="LR", labelloc="t", fontsize=16))

The theme defines two gvdot roles, collections of Graphviz attribute values that applications can assign to diagram elements by name.

Having isolated presentation attributes in a theme, our generation code is straightforward.

def nfa_diagram(nfa:NFA, title:str):

    dot = Dot(directed=True).use_theme(nfa_theme)
    dot.graph(label=Markup(f"<b>{title}</b>"))

    init_id = Nonce()
    dot.node(init_id, role="init")
    dot.edge(init_id, nfa.start)

    for state in nfa.final:
        dot.node(state, role="final")

    for state, transitions in nfa.delta.items():
        merged = defaultdict(list)
        for index, targets in enumerate(transitions):
            for target in targets:
                merged[target].append(
                    nfa.alphabet[index-1] if index > 0 else '&epsilon;')
        for target, symbols in merged.items():
            dot.edge(state, target, label=", ".join(symbols))

    return dot

We can render and save the diagram above with

example = NFA("01", {
    "s0": [["q0", "r0"], [], []],
    "q0": [[], ["q1"], ["q0"]],
    "q1": [[], ["q1"], ["q2"]],
    "q2": [[], ["q3"], ["q0"]],
    "q3": [[], ["q1"], ["q4"]],
    "q4": [[], ["q4"], ["q4"]],
    "r0": [[], ["r0"], ["r1"]],
    "r1": [[], ["r0"], ["r2"]],
    "r2": [[], ["r3"], ["r1"]],
    "r3": [[], ["r3"], ["r3"]],
}, ["q4","r0","r1","r2"], "s0")

nfa_diagram(example,"Example NFA").save("example.svg")

In a notebook, we can directly display the diagram from a cell containing

nfa_diagram(example,"Example NFA").show()

You can find this NFA example and others in the examples directory. The documentation includes a Quick Tour

Installation

Using Python 3.12 or greater, you can install gvdot with

$ pip install gvdot

To ensure the optional notebook support is enabled, use

$ pip install gvdot[ipython]

Rendering requires a Graphviz installation. You can determine if one is in your PATH with

$ dot -V

To install Graphviz, see https://graphviz.org/download.

Reliability

gvdot includes automated tests with 100% code coverage, which are run on macOS, Linux, and Windows with Python 3.12, 3.13, 3.14, and 3.15. See the GitHub workflow for details.

Metadata

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