Skip to main content

Interactive Graph Vis for Streamlit.

Project description

Based on react-graph-vis

Install

pip install streamlit-agraph

Example App

Check out the example App!

Use

import streamlit
from streamlit_agraph import agraph, Node, Edge, Config

nodes = []
edges = []
nodes.append( Node(id="Spiderman", 
                   label="Peter Parker", 
                   size=25, 
                   shape="circularImage",
                   image="http://marvel-force-chart.surge.sh/marvel_force_chart_img/top_spiderman.png") 
            ) # includes **kwargs
nodes.append( Node(id="Captain_Marvel", 
                   size=25,
                   shape="circularImage",
                   image="http://marvel-force-chart.surge.sh/marvel_force_chart_img/top_captainmarvel.png") 
            )
edges.append( Edge(source="Captain_Marvel", 
                   label="friend_of", 
                   target="Spiderman", 
                   # **kwargs
                   ) 
            ) 

config = Config(width=500, 
                height=500, 
                # **kwargs
                ) 

return_value = agraph(nodes=nodes, 
                      edges=edges, 
                      config=config)

You may also want to use the TripleStore (untested & incomplete - yet):

# Currently not workin since update to agraph 2.0 - work in progress
from rdflib import Graph
from streamlit_agraph import TripleStore, agraph

graph = Graph()
graph.parse("http://www.w3.org/People/Berners-Lee/card")
store = TripleStore()

for subj, pred, obj in graph:
    store.add_triple(subj, pred, obj, "")
    
agraph(list(store.getNodes()), list(store.getEdges()), config)

Also graph algos can dirctly supported via the networkx API (untested & incomplete - yet):

from streamlit_agraph import GraphAlgos

algos = GraphAlgos(store)
algos.shortest_path("Spiderman", "Captain_Marvel")
algos.density()

Formating the graph with hierachies is also possible, see examples/iris_decision_tree.py:

marvel.png

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

streamlit-agraph-0.0.42.tar.gz (1.3 MB view hashes)

Uploaded Source

Built Distribution

streamlit_agraph-0.0.42-py3-none-any.whl (1.3 MB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page