Description
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 (under branch dev), where you can report issues and contribute code.
pydot alternatives and similar packages
Based on the "Data Visualization" category.
Alternatively, view pydot alternatives based on common mentions on social networks and blogs.

Apache Superset
Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset] 
redash
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data. 
plotly
The interactive graphing library for Python :sparkles: This project now includes Plotly Express! 
PyQtGraph
Fast data visualization and GUI tools for scientific / engineering applications 
Flask JSONDash
:snake: :bar_chart: :chart_with_upwards_trend: Build complex dashboards without any frontend code. Use your own endpoints. JSON config only. Ready to go. 
ipyvizzu
Build animated charts in Jupyter Notebook and similar environments with a simple Python syntax. 
GooPyCharts
A Google Charts API for Python, meant to be used as an alternative to matplotlib.
TestGPT  Generating meaningful tests for busy devs
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
Do you think we are missing an alternative of pydot or a related project?
README
About
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.
Examples
The examples here will show you the most common input, editing and output methods.
Input
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 DOTfile.
Use this method if you already have a DOTfile 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 DOTfile:
import pydot graphs = pydot.graph_from_dot_file("example.dot") graph = graphs[0]
or: Parse a graph from an existing DOTstring.
Use this method if you already have a DOTstring 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.Dot
graph 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)
Edit
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")
Output
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:
```python
output_graphviz_svg = graph.create_svg()
```
 If instead you just want to save the image to a file, use one of
the `write_*` methods:
```python
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.
```python
# As a string:
output_raw_dot = graph.to_string()
# Or, save it as a DOTfile:
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.
```python
# As a bytes literal:
output_graphviz_dot = graph.create_dot()
# Or, save it as a DOTfile:
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)
More help
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.
Installation
pip install pydot
From source:
python setup.py install
Dependencies
pyparsing
: used only for loading DOT files, installed automatically duringpydot
installation.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.
License
Distributed under an MIT license.
Contacts
Maintainers:
 Sebastian Kalinowski [email protected] (GitHub: @prmtl)
 Peter Nowee [email protected] (GitHub: @peternowee)
Original author: Ero Carrera [email protected]
*Note that all licence references and agreements mentioned in the pydot README section above
are relevant to that project's source code only.