pydot:
- is an interface to Graphviz,
- can parse and dump into the DOT language used by GraphViz,
- is written in pure Python,
and networkx can 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 pydot graphs = 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 pydot dot_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 pydot graph = 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 pydot # See 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:
-
Add further nodes and edges:
graph.add_edge(pydot.Edge("b", "d", style="dotted"))
-
Edit attributes of graph, nodes and edges:
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_*()orwrite_*()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.
pip install pydot
From source:
python setup.py install
-
pyparsing: used only for loading DOT files, installed automatically duringpydotinstallation. -
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.
pydot uses Python's standard logging module. To see the logs,
assuming logging has not been configured already:
>>> import logging
>>> logging.basicConfig(level=logging.DEBUG)
>>> import pydot
DEBUG:pydot:pydot initializing
DEBUG:pydot:pydot <version>
DEBUG:pydot.core:pydot core module initializing
DEBUG:pydot.dot_parser:pydot dot_parser module initializing
Warning: When DEBUG level logging is enabled, pydot may log the
data that it processes, such as graph contents or DOT strings. This can
cause the log to become very large or contain sensitive information.
- Check out the Python logging documentation and the
logging_treevisualizer. pydotdoes not add any handlers to its loggers, nor does it setup or modify your root logger. Thepydotloggers are created with the default levelNOTSET.pydotregisters the following loggers:pydot: Parent logger. Emits a few messages during startup.pydot.core: Messages related to pydot objects, Graphviz execution and anything else not covered by the other loggers.pydot.dot_parser: Messages related to the parsing of DOT strings.
Distributed under an MIT license.
Current maintainer(s):
- Łukasz Łapiński <lukaszlapinski7 (at) gmail (dot) com>
Past maintainers:
- Sebastian Kalinowski <sebastian (at) kalinowski (dot) eu> (GitHub: @prmtl)
- Peter Nowee <peter (at) peternowee (dot) com> (GitHub: @peternowee)
Original author: Ero Carrera <ero (dot) carrera (at) gmail (dot) com>
![dependabot[bot] avatar](https://avatars.githubusercontent.com/in/29110?v=4 "dependabot[bot]")
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent
