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https://github.com/sio/graphviz-managed

Manipulate Graphviz graphs in Python prior to rendering
https://github.com/sio/graphviz-managed

graphs graphviz python

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Manipulate Graphviz graphs in Python prior to rendering

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# Manipulate Graphviz graphs in Python prior to rendering



Graphviz wrapper that allows to manage graph objects in Python prior to

translating them into dot language.



## Rationale



Unfortunately, both [graphviz] and [diagrams] packages do not allow any

operations on graphs besides adding nodes and edges. If you want to loop

through all graph nodes or edges to calculate some extra attributes - you're

out of luck.



This small library builds graphs as Python objects prior to translating them

into dot language. That means you can manipulate your graphs programmatically

in any way you want.



[graphviz]: https://graphviz.readthedocs.io/en/stable/manual.html

[diagrams]: https://diagrams.mingrammer.com/



## Installation



graphviz-managed is published at [PyPI], you can install it via pip:



```

$ pip install graphviz-managed

```



[PyPI]: https://pypi.org/project/graphviz-managed



## Usage



### Basic usage



This is nothing special, [diagrams] offers a lot more possibilities here.



```python

from graphviz_managed import Graph

graph = Graph(label='<Sample Graph #1>')

node = graph.node

foo = node(label='Foo!')

bar = node(label='BAR', fontcolor='red', penwidth=1.5)

foo >> bar >> foo

graph.render('basic.svg')

```



[![sample graph output](samples/basic.svg)](samples/basic.py)



### Change node style based on number of incoming/outgoing edges



Dynamic graph manipulation is impossible with [graphviz] or [diagrams],

but is rather straightforward with this library:



```python

from graphviz_managed import Graph

graph = Graph(label='Highlight graph entry points', rankdir='LR')

node = graph.node



# Define a larger graph

a = node(label='a')

b = node(label='b')

c = node(label='c')

d = node(label='d')

e = node(label='e')

f = node(label='f')

a >> [b, e]

c >> [b, e]

d >> a

e >> f

f >> [b, a]



# Highlight nodes with no incoming edges

from collections import defaultdict

incoming_count = defaultdict(int)

for edge in graph.edges:

    incoming_count[edge.end] += 1

for node in graph.nodes:

    if incoming_count[node] == 0:

        node.attrs.color = 'darkgreen'

        node.attrs.fontcolor = 'darkgreen'

        node.attrs.style = 'filled'

        node.attrs.fillcolor = 'beige'



# Save output

graph.render('count.svg')

```



[![sample graph output](samples/count.svg)](samples/count.py)



### Break long labels into multiple lines



Providing custom factories for nodes and edges allows for some interesting

customizations.



```python

from graphviz_managed import Graph

from graphviz_managed.custom import WrapLongLabelNode

graph = Graph(node_cls=WrapLongLabelNode, rankdir='LR', node_attrs=dict(shape='box'))

a = graph.node(label='Short text')

b = graph.node(label='Long label that will be wrapped into multiple lines')

c = graph.node(label='CantWrapSpecialCamelCaseWordsWithoutSpaces')

d = graph.node(label='CantWrapSpecialCamelCaseWordsWithoutSpaces but can wrap elsewhere')

a >> b >> c >> d

graph.render('labels.svg')

```



[![sample graph output](samples/labels.svg)](samples/labels.py)



### Wrapper for [diagrams] package



graphviz-managed can be extended to support other graph rendering libraries.

[Here is](src/graphviz_managed/diagrams.py) how it's done for [diagrams].

Resulting objects may be manipulated in the same way, enjoying all pre-rendering

freedoms demonstrated above.



```python

from graphviz_managed.diagrams import Diagram

diag = Diagram(label='Fancy node templates from https://pypi.org/project/diagrams/', pad=0.1)

node = diag.node

lb = node(kind='aws.network.ELB', label='lb')

web = node(kind='aws.compute.EC2', label='web')

db = node(kind='aws.database.RDS', label='db')

store = node(kind='aws.storage.S3', label='store')

lb >> web >> db >> store

diag.render('diag.png')

```



[![sample graph output](samples/diag.png)](samples/diag.py)



More samples can be found in [tests/](tests/) directory.



## Support and contributing



If you need help with using this library or including it into your project,

please create **[an issue][issues]**.

Issues are also the primary venue for reporting bugs and posting feature

requests. General discussion related to this project is also acceptable and

very welcome!



In case you wish to contribute code or documentation, feel free to open

**[a pull request](https://github.com/sio/graphviz-managed/pulls)**. That would

certainly make my day!



I'm open to dialog and I promise to behave responsibly and treat all

contributors with respect. Please try to do the same, and treat others the way

you want to be treated.



If for some reason you'd rather not use the issue tracker, contacting me via

email is OK too. Please use a descriptive subject line to enhance visibility

of your message. Also please keep in mind that public discussion channels are

preferable because that way many other people may benefit from reading past

conversations. My email is visible under the GitHub profile and in the commit

log.



[issues]: https://github.com/sio/graphviz-managed/issues



## License and copyright



Copyright 2021 Vitaly Potyarkin



    Licensed under the Apache License, Version 2.0 (the "License");

    you may not use this file except in compliance with the License.

    You may obtain a copy of the License at



        http://www.apache.org/licenses/LICENSE-2.0



    Unless required by applicable law or agreed to in writing, software

    distributed under the License is distributed on an "AS IS" BASIS,

    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

    See the License for the specific language governing permissions and

    limitations under the License.