gvdot 1.2.1
Generate and render optionally themed Graphviz diagrams with simple, easy to maintain code.
Requires Python: >=3.12
Keywords: graphviz, dot, dot-language, graphs, graph, visualization, rendering, svg, png

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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](https://raw.githubusercontent.com/escreven/gvdot/main/readme-example.svg)

represented by instances of

```python
@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.

```python
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.

```python
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

```python
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

```python
nfa_diagram(example,"Example NFA").show()
```

You can find this [NFA
example](https://github.com/escreven/gvdot/blob/main/examples/nfa.ipynb) and
others in the [examples](https://github.com/escreven/gvdot/tree/main/examples)
directory.  The documentation includes a [Quick
Tour](https://gvdot.readthedocs.io/en/latest/quicktour.html)

## Installation

Using Python 3.12 or greater, you can install gvdot with

```bash
$ pip install gvdot
```

To ensure the optional notebook support is enabled, use

```bash
$ pip install gvdot[ipython]
```

[Rendering](https://gvdot.readthedocs.io/en/latest/discussion.html#rendering)
 requires a Graphviz installation.  You can determine if one is in your `PATH`
 with

 ```bash
 $ dot -V
 ```

To install Graphviz, see
[https://graphviz.org/download](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, and 3.14.  See [the GitHub
workflow](https://github.com/escreven/gvdot/blob/main/.github/workflows/test.yml)
for details.