Python interface to Graphviz's Dot language
pydot:
networkxcan convert its graphs to
pydot.
Development occurs at GitHub, where you can report issues and contribute code.
The examples here will show you the most common input, editing and output methods.
No matter what you want to do with
pydot, it will need some input to start with. Here are 3 common options:
Import a graph from an existing DOT-file.
Use this method if you already have a DOT-file describing a graph, for example as output of another program. Let's say you already have this
example.dot(based on an example from Wikipedia):
graph my_graph { bgcolor="yellow"; a [label="Foo"]; b [shape=circle]; a -- b -- c [color=blue]; }
Just read the graph from the DOT-file:
import pydotgraphs = pydot.graph_from_dot_file("example.dot") graph = graphs[0]
or: Parse a graph from an existing DOT-string.
Use this method if you already have a DOT-string describing a graph in a Python variable:
import pydotdot_string = """graph my_graph { bgcolor="yellow"; a [label="Foo"]; b [shape=circle]; a -- b -- c [color=blue]; }"""
graphs = pydot.graph_from_dot_data(dot_string) graph = graphs[0]
or: Create a graph from scratch using pydot objects.
Now this is where the cool stuff starts. Use this method if you want to build new graphs from Python.
import pydotgraph = pydot.Dot("my_graph", graph_type="graph", bgcolor="yellow")
Add nodes
my_node = pydot.Node("a", label="Foo") graph.add_node(my_node)
Or, without using an intermediate variable:
graph.add_node(pydot.Node("b", shape="circle"))
Add edges
my_edge = pydot.Edge("a", "b", color="blue") graph.add_edge(my_edge)
Or, without using an intermediate variable:
graph.add_edge(pydot.Edge("b", "c", color="blue"))
Imagine using these basic building blocks from your Python program to dynamically generate a graph. For example, start out with a basic
pydot.Dotgraph object, then loop through your data while adding nodes and edges. Use values from your data as labels, to determine shapes, edges and so forth. This way, you can easily build visualizations of thousands of interconnected items.
or: Convert a NetworkX graph to a pydot graph.
NetworkX has conversion methods for pydot graphs:
import networkx import pydotSee NetworkX documentation on how to build a NetworkX graph.
graph = networkx.drawing.nx_pydot.to_pydot(my_networkx_graph)
You can now further manipulate your graph using pydot methods:
graph.add_edge(pydot.Edge("b", "d", style="dotted"))
graph.set_bgcolor("lightyellow") graph.get_node("b")[0].set_shape("box")
Here are 3 different output options:
Generate an image.
To generate an image of the graph, use one of the
create_*()or
write_*()methods.
- If you need to further process the output in Python, the `create_*` methods will get you a Python bytes object:output_graphviz_svg = graph.create_svg()
If instead you just want to save the image to a file, use one of
the write_*
methods:
graph.write_png("output.png")
Retrieve the DOT string.
There are two different DOT strings you can retrieve:
- The "raw" pydot DOT: This is generated the fastest and will usually still look quite similar to the DOT you put in. It is generated by pydot itself, without calling Graphviz.# As a string: output_raw_dot = graph.to_string() # Or, save it as a DOT-file: graph.write_raw("output_raw.dot")
The Graphviz DOT: You can use it to check how Graphviz lays out the graph before it produces an image. It is generated by Graphviz.
# As a bytes literal:
output_graphviz_dot = graph.create_dot()
# Or, save it as a DOT-file:
graph.write_dot("output_graphviz.dot")
Convert to a NetworkX graph.
Here as well, NetworkX has a conversion method for pydot graphs:
my_networkx_graph = networkx.drawing.nx_pydot.from_pydot(graph)
For more help, see the docstrings of the various pydot objects and methods. For example,
help(pydot),
help(pydot.Graph)and
help(pydot.Dot.write).
More documentation contributions welcome.
From PyPI using
pip:
pip install pydot
From source:
python setup.py install
pyparsing: used only for loading DOT files, installed automatically during
pydotinstallation.
GraphViz: used to render graphs as PDF, PNG, SVG, etc. Should be installed separately, using your system's package manager, something similar (e.g., MacPorts), or from its source.
Distributed under an MIT license.
Maintainers: - Sebastian Kalinowski [email protected] (GitHub: @prmtl) - Peter Nowee [email protected] (GitHub: @peternowee)
Original author: Ero Carrera [email protected]