diff --git a/examples/gds-example.ipynb b/examples/gds-example.ipynb
index 57604af..3b032d6 100644
--- a/examples/gds-example.ipynb
+++ b/examples/gds-example.ipynb
@@ -2,6 +2,7 @@
"cells": [
{
"cell_type": "markdown",
+ "id": "7fb27b941602401d91542211134fc71a",
"metadata": {},
"source": [
"# Visualizing Neo4j Graph Data Science (GDS) Graphs"
@@ -10,6 +11,7 @@
{
"cell_type": "code",
"execution_count": null,
+ "id": "acae54e37e7d407bbb7b55eff062a284",
"metadata": {},
"outputs": [],
"source": [
@@ -17,47 +19,103 @@
"%pip install matplotlib"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "9a63283cbaf04dbcab1f6479b197f3a8",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from dotenv import load_dotenv\n",
+ "\n",
+ "load_dotenv()"
+ ]
+ },
{
"cell_type": "markdown",
+ "id": "8dd0d8092fe74a7c96281538738b07e2",
"metadata": {},
"source": [
- "## Setup GDS graph"
+ "## Setup GDS graph\n",
+ "\n",
+ "To use GDS, you can either use GDS as a plugin or Aura Graph Analytics.\n",
+ "In the following, you can choose:\n",
+ "\n",
+ " * Provide Aura API credentials and and use Aura Graph Analytics.\n",
+ " * Use Neo4j + GDS Plugin.\n",
+ "\n",
+ "For more information, see the [GDS documentation](https://neo4j.com/docs/graph-data-science/current/installation/)."
]
},
{
"cell_type": "code",
"execution_count": null,
+ "id": "72eea5119410473aa328ad9291626812",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
+ "from graphdatascience.session import (\n",
+ " GdsSessions,\n",
+ " DbmsConnectionInfo,\n",
+ " AuraAPICredentials,\n",
+ " SessionMemory,\n",
+ ")\n",
"from graphdatascience import GraphDataScience\n",
"\n",
"# Get Neo4j DB URI, credentials and name from environment if applicable\n",
- "NEO4J_URI = os.environ.get(\"NEO4J_URI\", \"bolt://localhost:7687\")\n",
- "NEO4J_AUTH = (\"neo4j\", None)\n",
- "NEO4J_DB = os.environ.get(\"NEO4J_DB\", \"neo4j\")\n",
- "if os.environ.get(\"NEO4J_USER\") and os.environ.get(\"NEO4J_PASSWORD\"):\n",
- " NEO4J_AUTH = (\n",
- " os.environ.get(\"NEO4J_USER\"),\n",
- " os.environ.get(\"NEO4J_PASSWORD\"),\n",
+ "db_connection = DbmsConnectionInfo(\n",
+ " aura_instance_id=os.environ.get(\"AURA_INSTANCEID\"),\n",
+ " username=os.environ[\"NEO4J_USERNAME\"],\n",
+ " password=os.environ[\"NEO4J_PASSWORD\"],\n",
+ " uri=os.environ[\"NEO4J_URI\"],\n",
+ ")\n",
+ "\n",
+ "session_name = \"neo4j-viz-gds-example\"\n",
+ "if os.environ.get(\"AURA_API_CLIENT_ID\"):\n",
+ " # Use Aura Graph Analytics\n",
+ " sessions = GdsSessions(\n",
+ " api_credentials=AuraAPICredentials(\n",
+ " client_id=os.environ[\"AURA_API_CLIENT_ID\"],\n",
+ " client_secret=os.environ[\"AURA_API_CLIENT_SECRET\"],\n",
+ " project_id=os.environ.get(\"AURA_API_PROJECT_ID\"),\n",
+ " )\n",
+ " )\n",
+ " gds = sessions.get_or_create(\n",
+ " session_name=session_name,\n",
+ " memory=SessionMemory.m_2GB,\n",
+ " db_connection=db_connection,\n",
" )\n",
- "gds = GraphDataScience(NEO4J_URI, auth=NEO4J_AUTH, database=NEO4J_DB)"
+ "else:\n",
+ " # Use GDS Plugin\n",
+ " sessions = None\n",
+ " gds = GraphDataScience(\n",
+ " endpoint=db_connection.get_uri(),\n",
+ " auth=(db_connection.username, db_connection.password),\n",
+ " )"
]
},
{
"cell_type": "code",
"execution_count": null,
+ "id": "8edb47106e1a46a883d545849b8ab81b",
"metadata": {},
"outputs": [],
"source": [
"G = gds.graph.load_cora(graph_name=\"cora\")"
]
},
+ {
+ "cell_type": "markdown",
+ "id": "10185d26023b46108eb7d9f57d49d2b3",
+ "metadata": {},
+ "source": []
+ },
{
"cell_type": "code",
"execution_count": null,
+ "id": "8763a12b2bbd4a93a75aff182afb95dc",
"metadata": {},
"outputs": [],
"source": [
@@ -71,6 +129,7 @@
},
{
"cell_type": "markdown",
+ "id": "7623eae2785240b9bd12b16a66d81610",
"metadata": {},
"source": [
"## Visualization"
@@ -79,1610 +138,32 @@
{
"cell_type": "code",
"execution_count": null,
+ "id": "7cdc8c89c7104fffa095e18ddfef8986",
"metadata": {},
"outputs": [],
"source": [
"from neo4j_viz.gds import from_gds\n",
"\n",
- "VG = from_gds(gds, G, max_node_count=500)\n",
- "str(VG)"
+ "VG = from_gds(\n",
+ " gds,\n",
+ " G,\n",
+ " max_node_count=100,\n",
+ ")"
]
},
{
"cell_type": "code",
- "execution_count": 41,
- "metadata": {
- "tags": [
- "preserve-output"
- ]
- },
- "outputs": [
- {
- "data": {
- "text/html": [
- "\n",
- "\n",
- " \n",
- " \n",
- " \n",
- " neo4j-viz\n",
- " \n",
- " \n",
- " \n",
- " \n",
- " \n",
- "\n",
- " \n",
- " \n",
- " \n",
- "\n"
- ],
- "text/plain": [
- ""
- ]
- },
- "execution_count": 41,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "execution_count": null,
+ "id": "b118ea5561624da68c537baed56e602f",
+ "metadata": {},
+ "outputs": [],
"source": [
- "VG.render(theme=\"auto\")"
+ "VG.render()"
]
},
{
"cell_type": "markdown",
+ "id": "938c804e27f84196a10c8828c723f798",
"metadata": {},
"source": [
"### Changing captions\n",
@@ -1694,6 +175,7 @@
{
"cell_type": "code",
"execution_count": null,
+ "id": "504fb2a444614c0babb325280ed9130a",
"metadata": {},
"outputs": [],
"source": [
@@ -1704,9 +186,8 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "tags": []
- },
+ "id": "59bbdb311c014d738909a11f9e486628",
+ "metadata": {},
"outputs": [],
"source": [
"VG.render()"
@@ -1714,6 +195,7 @@
},
{
"cell_type": "markdown",
+ "id": "b43b363d81ae4b689946ece5c682cd59",
"metadata": {},
"source": [
"## Sizing the nodes\n",
@@ -1724,16 +206,17 @@
{
"cell_type": "code",
"execution_count": null,
+ "id": "8a65eabff63a45729fe45fb5ade58bdc",
"metadata": {},
"outputs": [],
"source": [
"VG.resize_nodes(property=\"pagerank\")\n",
- "VG.color_nodes(property=\"componentId\")\n",
"VG.render()"
]
},
{
"cell_type": "markdown",
+ "id": "c3933fab20d04ec698c2621248eb3be0",
"metadata": {},
"source": [
"### Coloring"
@@ -1741,6 +224,7 @@
},
{
"cell_type": "markdown",
+ "id": "4dd4641cc4064e0191573fe9c69df29b",
"metadata": {},
"source": [
"There are two main ways of coloring the nodes of a graph:\n",
@@ -1754,17 +238,17 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "tags": []
- },
+ "id": "8309879909854d7188b41380fd92a7c3",
+ "metadata": {},
"outputs": [],
"source": [
- "VG.color_nodes(property=\"componentId\")\n",
+ "VG.color_nodes(property=\"subject\")\n",
"VG.render()"
]
},
{
"cell_type": "markdown",
+ "id": "3ed186c9a28b402fb0bc4494df01f08d",
"metadata": {},
"source": [
"Now, let us color by our continuous node field \"size\" that we computed above with PageRank, again using the default colors.\n",
@@ -1775,9 +259,8 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "tags": []
- },
+ "id": "cb1e1581032b452c9409d6c6813c49d1",
+ "metadata": {},
"outputs": [],
"source": [
"from neo4j_viz.colors import ColorSpace\n",
@@ -1788,6 +271,7 @@
},
{
"cell_type": "markdown",
+ "id": "379cbbc1e968416e875cc15c1202d7eb",
"metadata": {},
"source": [
"#### Custom coloring\n",
@@ -1799,6 +283,7 @@
{
"cell_type": "code",
"execution_count": null,
+ "id": "277c27b1587741f2af2001be3712ef0d",
"metadata": {},
"outputs": [],
"source": [
@@ -1808,6 +293,7 @@
{
"cell_type": "code",
"execution_count": null,
+ "id": "db7b79bc585a40fcaf58bf750017e135",
"metadata": {},
"outputs": [],
"source": [
@@ -1825,1599 +311,17 @@
},
{
"cell_type": "code",
- "execution_count": 49,
- "metadata": {
- "tags": [
- "preserve-output"
- ]
- },
- "outputs": [
- {
- "data": {
- "text/html": [
- "\n",
- "\n",
- " \n",
- " \n",
- " \n",
- " neo4j-viz\n",
- " \n",
- " \n",
- " \n",
- " \n",
- " \n",
- "\n",
- " \n",
- " \n",
- " \n",
- "\n"
- ],
- "text/plain": [
- ""
- ]
- },
- "execution_count": 49,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "execution_count": null,
+ "id": "916684f9a58a4a2aa5f864670399430d",
+ "metadata": {},
+ "outputs": [],
"source": [
"VG.render()"
]
},
{
"cell_type": "markdown",
+ "id": "1671c31a24314836a5b85d7ef7fbf015",
"metadata": {},
"source": [
"### Render options\n",
@@ -3433,1593 +337,10 @@
},
{
"cell_type": "code",
- "execution_count": 50,
- "metadata": {
- "tags": [
- "preserve-output"
- ]
- },
- "outputs": [
- {
- "data": {
- "text/html": [
- "\n",
- "\n",
- " \n",
- " \n",
- " \n",
- " neo4j-viz\n",
- " \n",
- " \n",
- " \n",
- "