test streamlit-agraph

Testing streamlit agraph

app.py

@@ -2,4 +2,60 @@ import streamlit as st
 from datasets import load_dataset
 dataset = load_dataset("roneneldan/TinyStories")
 
-st.write(dataset['train'][0])
+st.write(dataset['train'][0])
+
+# ego_graph.py
+# An example of how to plot a node's ego network 
+# (egonet). This indirectly showcases slightly more involved 
+# interoperability between streamlit-agraph and networkx.
+
+# An egonet can be # created from (almost) any network (graph),
+# and exemplifies the # concept of a subnetwork (subgraph):
+# A node's egonet is the (sub)network comprised of the focal node 
+# and all the nodes to whom it is adjacent. The edges included
+# in the egonet are those nodes are both included in the aforementioned
+# nodes. 
+
+# Use the following command to launch the app
+# streamlit run <path-to-script>.py
+
+# standard library dependencies
+from operator import itemgetter
+
+# external dependencies
+import networkx as nx
+from streamlit_agraph import agraph, Node, Edge, Config
+
+# First create a graph using the Barabasi-Albert model
+n = 2000
+m = 2
+G = nx.generators.barabasi_albert_graph(n, m)
+
+# Then find the node with the largest degree; 
+# This node's egonet will be the focus of this example.
+node_and_degree = G.degree()
+most_connected_node = sorted(G.degree, key=lambda x: x[1], reverse=True)[0]
+degree = G.degree(most_connected_node)
+
+# Create egonet for the focal node
+hub_ego = nx.ego_graph(G, most_connected_node[0])
+
+# Now create the equivalent Node and Edge lists
+nodes = [Node(id=i, label=str(i), size=200) for i in hub_ego.nodes]
+edges = [Edge(source=i, target=j, type="CURVE_SMOOTH") for (i,j) in G.edges
+        if i in hub_ego.nodes and j in hub_ego.nodes]
+
+
+config = Config(width=500, 
+                height=500, 
+                directed=True,
+                nodeHighlightBehavior=False, 
+                highlightColor="#F7A7A6", # or "blue"
+                collapsible=False,
+                node={'labelProperty':'label'},
+                # **kwargs e.g. node_size=1000 or node_color="blue"
+                ) 
+
+return_value = agraph(nodes=nodes, 
+                      edges=edges, 
+                      config=config)