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Packages that work with networkx that can handle clickable nodes

I'm looking to try and visualize data using networkx as a network graph. My data looks great, but i'm wanting to add on hover and on click events to display additional information.
For example, there might be a node called "New York", when clicked will display a small table to the side of the canvas that gives information like how many cities, current population, etc.
I'm currently using pyviz with networkx. That seems to be really straightforward as far as creating the graph, but not so much on the kind of user interaction i'm looking for.
I also tried bokeh and plotly, but on the on click and hover functions while work, isn't very straightforward to implement with networkx. Here's a picture of what my graph looks like. My goal is to show relationships between systems.
pyvis graph

I maintain a python library for network visualisations called netgraph, which works nicely with networkx or igraph Graph objects. I thought this was a neat idea for a feature, so I just implemented a bare bones version on the dev branch.
Installation via pip:
pip install https://github.com/paulbrodersen/netgraph/archive/dev.zip
Code to reproduce the example above:
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import networkx as nx
from netgraph import InteractiveGraph
g = nx.cubical_graph()
tables = dict()
for node in g.nodes:
data = np.round(np.random.rand(3,2), decimals=2)
table = pd.DataFrame(data, index=['Lorem', 'ipsum', 'dolor'], columns=['sit', 'amet'])
tables[node] = table
for edge in g.edges:
data = np.round(np.random.rand(4,1), decimals=2)
table = pd.DataFrame(data, index=['consectetur', 'adipiscing', 'elit', 'Mauris'], columns=['sed'])
tables[edge] = table
fig, ax = plt.subplots(figsize=(12,5))
fig.subplots_adjust(right=0.6) # make space for table on the right
bbox = [1.5, 0.1, 0.5, 0.8] # position of the table in axes coordinates
instance = InteractiveGraph(g, node_labels=True, tables=tables, table_kwargs=dict(edges='horizontal', fontsize=16, bbox=bbox), ax=ax)
plt.show()

Take a look at the kglab project which is an open source abstraction layer in Python that integrates both NetworkX and PyVis, along with other graph related libraries in Python. It was built for this kind of use case.
There's a class kglab.KnowledgeGraph which has transforms and inverse transforms to work these other libraries:
NetworkX examples https://derwen.ai/docs/kgl/ex6_0/
PyVis examples https://derwen.ai/docs/kgl/ex3_0/
For instance, you could:
build a graph using a KnowledgeGraph object
transform out to run NetworkX graph algorithms
use an inverse transform to populate calculated attributes on the main graph object
transform out to load and run a PyVis interactive session, which in turn can have clickable components
We've got Jupyter notebooks on the GH repo showing each of these steps. plus a developer community where other people can help for a specific use case (create a GH issue)

There is VisDCC, which requires Dash (a kind of data-science server thing).
The end result is a web server serving an HTML canvas that you can insert in a web page, for instance. (This is actually inherited from Vis.js)
VisDCC has almost no documentation but it works (I'm using it) and the usage follows that of Dash which is well-documented. You need to learn to use Dash's #callback format to write the code.
So I guess it's a good enough solution :)

How to draw readable, preferably interactive, network graphs with python?

I'm trying to draw a graph of any network running my script. I use scapy to collect packets and would like to have a node per computer communicating, and an edge per connection.
The issue is I can't find a way to visualize the graph well enough on my screen. So far combining networkx with matlib.pyplot managed to bring the best results, but it still seems pretty random and chaotic, the tags are hard to read, nodes are on top of each other, etc'. It is also preferable to have the ability to interact with the graph - move nodes around, hover over nodes/edges to get extra info, perhaps zoom in or even cluster together nodes so that when you click on the cluster you can see which nodes compose the cluster.
Since analyzing the network data and adding nodes&edges to the graph will be tedious for you to read, I'm adding only the relevant part here (the part that actually shows the graph I built):
pos = nx.spring_layout(Graph, scale=2)
edge_labels = nx.get_edge_attributes(Graph, "Protocol")
nx.draw(Graph,pos, with_labels=True, node_size=600, font_size=8, font_weight='bold')
nx.draw_networkx_edge_labels(Graph, pos, edge_labels=edge_labels, font_size=8)
plt.show()
(I imported networks as nx and matplotlib.pyplot as plt)
I also tried graphviz, ploty and bokeh but couldn't really make them work and after troubleshooting on Google got the impression that anyway they won't fix my problem, and I also tried adjustText - but I could not manage to fit it in my code in any way (can't find how to get the text attribute of my graph) and Holoviews - but it refuses to show an image no matter what I try (even if I copy and paste examples from their site - either python says that '%opts...' is invalid syntax, or if I try changing options any other way the code just runs until it ends and doesn't show anything on the screen.
This is what the graph looks like:
I'm finding a lot of partial solutions online so none of them work, does anybody has a comprehensive solution?

Drawing heavy graphs with plt can be a bit problematic, the problem here is not only with the data, it is also a problem for a human eye to get a lot of information in one look.
My suggestion is to use a more advanced graph visualization library, for example, ipycytoscape. you can define also styles and more features with it that will match your demands
from ipycytoscape import CytoscapeWidget
graph_draw = ipycytoscape.CytoscapeWidget()
graph_draw.graph.add_graph_from_networkx(nx_graph, directed=True)
In addition, if you will use CytoscapeWidget you can interact with the graph and match the focus of the view to the part in the graph that interests you the most.

You can tune the hyper-parameters (k and iterations) of the nx.spring_layout to arrange the nodes. Once you tune the parameters, the connected nodes will be close to each other, and not-contacted nodes will maintain a maximum possible distance.
pos = nx.spring_layout(G,k=0.1, iterations=20)

Python Weighted DiGraph Visualization

I'm trying to visualize markov style state diagrams.
I've tried using pygraphviz via both direct dot language and networkx.
I've tried using pyplot within matplotlib.
In both cases the outcome is ugly. In pyplot the arrows are just thicker lines, and in pygraphviz the labeled lines aren't arranged well.
Personally I prefer the networkx->pygraphviz option. Here's a brief code snippet that illustrates my question.
G = nx.DiGraph()
G.add_edge(0,1,weight=0.5)
G.add_edge(1,2,weight=0.5)
G.add_edge(2,3,weight=0.5)
G.add_edge(3,4,weight=0.5)
G.add_edge(1,0,weight=0.5)
G.add_edge(2,1,weight=0.5)
G.add_edge(3,2,weight=0.5)
G.add_edge(4,3,weight=0.5)
for u,v,d in G.edges(data=True):
d['label'] = d.get('weight','')
A = nx.drawing.nx_agraph.to_agraph(G)
A.layout(prog='dot')
A.draw('test.png')
Which produces
ugly graph labels
In reality I want something like this
better graph
Or even better yet something like this pretty transition diagram.
I would have embedded the photos, but I'm not yet allowed. :(
Thanks!

Plotting networkx graph with node labels defaulting to node name

NetworkX is powerful but I was trying to plot a graph which shows node labels by default and I was surprised how tedious this seemingly simple task could be for someone new to Networkx. There is an example which shows how to add labels to the plot.
https://networkx.github.io/documentation/latest/examples/drawing/labels_and_colors.html
The problem with this example is that it uses too many steps and methods when all I want to do is just show labels which are same as the node name while drawing the graph.
# Add nodes and edges
G.add_node("Node1")
G.add_node("Node2")
G.add_edge("Node1", "Node2")
nx.draw(G) # Doesn't draw labels. How to make it show labels Node1, Node2 along?
Is there a way to make nx.draw(G) show the default labels (Node1, Node2 in this case) inline in the graph?

tl/dr: just add with_labels=True to the nx.draw call.
The page you were looking at is somewhat complex because it shows how to set lots of different things as the labels, how to give different nodes different colors, and how to provide carefully control node positions. So there's a lot going on.
However, it appears you just want each node to use its own name, and you're happy with the default color and default position. So
import networkx as nx
import pylab as plt
G=nx.Graph()
# Add nodes and edges
G.add_edge("Node1", "Node2")
nx.draw(G, with_labels = True)
plt.savefig('labels.png')
If you wanted to do something so that the node labels were different you could send a dict as an argument. So for example,
labeldict = {}
labeldict["Node1"] = "shopkeeper"
labeldict["Node2"] = "angry man with parrot"
nx.draw(G, labels=labeldict, with_labels = True)

I feel a better answer is not to use networkx to draw. They explicitly warn you that graph visualization is hard and networkx is mainly meant for graph analysis (from https://networkx.org/documentation/stable/reference/drawing.html#module-networkx.drawing.layout):
Drawing
NetworkX provides basic functionality for visualizing graphs, but its main goal is to enable graph analysis rather than perform graph visualization. In the future, graph visualization functionality may be removed from NetworkX or only available as an add-on package.
Proper graph visualization is hard, and we highly recommend that people visualize their graphs with tools dedicated to that task. Notable examples of dedicated and fully-featured graph visualization tools are Cytoscape, Gephi, Graphviz and, for LaTeX typesetting, PGF/TikZ. To use these and other such tools, you should export your NetworkX graph into a format that can be read by those tools. For example, Cytoscape can read the GraphML format, and so, networkx.write_graphml(G, path) might be an appropriate choice.
thus my suggestion is to transform the graph to some format that has dedicated software for graph visualization and then draw (e.g. pydot, pygraphviz, graphviz etc). My suspicion is that pydot and pygraphviz are the best for some reason since networkx only supports those two. It seems from the docs in pygraphviz that it has a similar api so it might be the easiest to use if you already want like to use networkx (https://pygraphviz.github.io/documentation/stable/tutorial.html):
The API is very similar to that of NetworkX. Much of the NetworkX tutorial at https://networkx.org/documentation/latest/tutorial.html is applicable to PyGraphviz. See http://pygraphviz.github.io/documentation/latest/reference/api_notes.html for major differences.
In addition, pydot as of now does not really have docs (which personally bothers me. Idk if it's that it doesn't look nice on my browser or that it makes me feel that project is not being taken seriously by it's developers idk something just doesn't feel right even if it has a higher set of users pydot 15k vs pygraphviz 4k) reference: https://github.com/pydot/pydot/pull/241.
Also it seems that pygraphviz has more granular control than regular graphviz ref: Graphviz vs PyGraphViz. In addition, I don't know how to convert a networkx directly to a graphviz obj (since graphviz has the best docs and highest user base ~19k so I did prefer that), so I will go with pygraphviz for those reasons. Pygravix also has docs which although small make me happy (though not as good as graphviz but idk how to make graphviz graphs from networkx). It's hard to make these decisions but I can't stay on this forever and this seems mindful enough. Also, networkx is nice because I can transform dgl graphs to networkx too (and the relabeling was simple).
Considering those reasons let me give you the example code I wrote that does what you want using pygraphviz (but you could do it with pydot if you figured out how, transforming to pydot obj is trivial using networkx see my previous link):
# https://stackoverflow.com/questions/28533111/plotting-networkx-graph-with-node-labels-defaulting-to-node-name
import dgl
import numpy as np
import torch
import networkx as nx
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
from pathlib import Path
g = dgl.graph(([0, 0, 0, 0, 0], [1, 2, 3, 4, 5]), num_nodes=6)
print(f'{g=}')
print(f'{g.edges()=}')
# Since the actual graph is undirected, we convert it for visualization purpose.
g = g.to_networkx().to_undirected()
print(f'{g=}')
# relabel
int2label = {0: "app", 1: "cons", 2: "with", 3: "app3", 4: "app4", 5: "app5"}
g = nx.relabel_nodes(g, int2label)
# https://networkx.org/documentation/stable/reference/drawing.html#module-networkx.drawing.layout
g = nx.nx_agraph.to_agraph(g)
print(f'{g=}')
print(f'{g.string()=}')
# draw
g.layout()
g.draw("file.png")
# https://stackoverflow.com/questions/20597088/display-a-png-image-from-python-on-mint-15-linux
img = mpimg.imread('file.png')
plt.imshow(img)
plt.show()
# remove file https://stackoverflow.com/questions/6996603/how-to-delete-a-file-or-folder
Path('./file.png').expanduser().unlink()
# import os
# os.remove('./file.png')
output:
g=Graph(num_nodes=6, num_edges=5,
ndata_schemes={}
edata_schemes={})
g.edges()=(tensor([0, 0, 0, 0, 0]), tensor([1, 2, 3, 4, 5]))
g=<networkx.classes.multigraph.MultiGraph object at 0x7f8443e94250>
g=<AGraph <Swig Object of type 'Agraph_t *' at 0x7f846117a930>>
g.string()='graph "" {\n\tapp -- cons [key=0,\n\tid=0];\napp -- with [key=0,\nid=1];\napp -- app3 [key=0,\nid=2];\napp -- app4 [key=0,\nid=3];\napp -- app5 [key=0,\nid=4];\n}\n'
though I want to leave this link about pydot visualization since it seems very useful in general: Display graph without saving using pydot and probably provides the pydot answer for others if they need it. Though, I'd love to see arguments in favour of pydot.
Edit1: if you want to plot by attributed and not by label, see this answer: NetworkX node attribute drawing note that relabeling the way I suggested does not always have the intended semantics (e.g. it might join two nodes that were NOT meant to be joined).
Edit2: if you want to plot the attribute instead without self loops happening by accident see this answer: Draw more information on graph\nodes using PyGraphviz

graphing a relationship matrix in python

i have a python interface using wxpython which allows the user to fill in a matrix (0/1) and then graphs it for them. The program creates a numpy matrix, then makes a networkx graph out of that matrix, and then uses matplotlib.pylab to display the graph.
numpy is a must, because the program also does other things like get the transitive, reflexive, and symmetric closures... as for networkx i can use something else if u recommend something else better for graphing matrices, and as for matplotlib, i hate it, please if u know of any other way to display a graph please advice.
matplotlib is the source of my problem, when the users clicks the graph button, my programs reads the matrix, makes a graphs and matplotlib displays it in a new window (by default). Now if the users goes back to the original window and graphs a different matrix without first closing the matplotlib window, the program crashes.
also the way the relationship "arrows" are drawn is, in my opinion, unattractive.
i need a better way to graph my matrix, or at the very least as a way to force close the myplotlib window, i tried plt.close() but that didnt work, the window would remain open, and both windows will say (Not Responding) and i have to end process.
this is the part of the code in question:
import numpy as np
import networkx as nx
import matplotlib.pylab as plt
...
...
...
def graph(values)
plt.close() #with or without this it does not work
matrix = np.matrix(values)
graph = nx.DiGraph(matrix)
nx.draw(graph)
plt.show()
return

It seems to me like your main complaint is in the way that wx handles the matplotlib windows. It is possible to embed the Matplotlib figure in your wx window. Here's an example:
http://wiki.scipy.org/Matplotlib_figure_in_a_wx_panel (updated)
It gets a bit complicated. Basically, you should copy the code and replace the "DemoPlotPanel.draw()" method. You'll need to modify your code to specify the axis to draw on. It's buried in the networkx documentation here:
http://networkx.lanl.gov/reference/drawing.html

I am just using an example of the Networkx documentation:
try:
import matplotlib.pyplot as plt
except:
raise
import networkx as nx
G=nx.star_graph(20)
pos=nx.spring_layout(G)
nx.draw(G,pos)
plt.show() # display
So your plt.close() statement at the start does not make sense, you should remove it.You should also calculate the coordinates for your nodes, the sentence pos=nx.spring_layout(G) does this. You call a specific layout algorithm and supply your graph G, you get a dictionary in return with for each node the x and y coordinates.
Have a close look at the examples at: http://networkx.lanl.gov/gallery.html