streamlit-agraph

Install

pip install streamlit-agraph

Example App

Check out the example App!

Basic Usage

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=750,
                height=950,
                directed=True, 
                physics=True, 
                hierarchical=False,
                # **kwargs
                )

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

Config Bilder

from streamlit_agraph.config import Config, ConfigBuilder

# 1. Build the config (with sidebar to play with options) .
config_builder = ConfigBuilder(nodes)
config = config_builder.build()

# 2. If your done, save the config to a file.
config.save("config.json")

# 3. Simple reload from json file (you can bump the builder at this point.)
config = Config(from_json="config.json")

Formating the graph with hierachies is also possible via Hierarchical Option (see config):
Group as you can see on the node colors too. Just pass the group attribute to the Node object.

TripleStore

You may also want to use the TripleStore (untested & incomplete - yet):
HINT: Make sure to add only unique nodes and edges.

# 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()

Metadata

Release files for streamlit-agraph 0.0.45

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for streamlit-agraph 0.0.45
File	Size	Uploaded
streamlit-agraph-0.0.45.tar.gz	1.3 MB	Jan 28, 2023	Details

Built distribution (wheel)

Table of built distributions (wheels) for streamlit-agraph 0.0.45
File	Interpreter	ABI	Platform	Reset
streamlit_agraph-0.0.45-py3-none-any.whl 1.3 MB Jan 28, 2023	Python 3	none	any	Details

Total release size: 2.6 MB

Release files / streamlit-agraph-0.0.45.tar.gz

Download URL	streamlit-agraph-0.0.45.tar.gz
Size	1.3 MB
Tags	Source
SHA-256 checksum How to use checksums	`b2b7cf1ad0a40dc906de50792b27f2878b0e186603cb3bc958ed78ca7e469cdd`
BLAKE2b-256 checksum How to use checksums	`e66300a16b1500cde32d43177bba1c16d12369ed7d1c8b45ab8162f6552d8519`
Upload date	Jan 28, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.4.1 importlib_metadata/3.10.1 pkginfo/1.6.1 requests/2.28.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12`

Release files / streamlit_agraph-0.0.45-py3-none-any.whl

Download URL	streamlit_agraph-0.0.45-py3-none-any.whl
Size	1.3 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`38e7271ffd76a6769968c2e9dfc16cbac7621d62be15af98b62598e1446bee2f`
BLAKE2b-256 checksum How to use checksums	`b9808a666e700332a9fe19e458678c95fab4d78340251d2f12da7d2ad915458a`
Upload date	Jan 28, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.4.1 importlib_metadata/3.10.1 pkginfo/1.6.1 requests/2.28.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12`