| Name | neo4j-viz JSON |
| Version |
0.4.2
JSON |
| download |
| home_page | None |
| Summary | A simple graph visualization tool |
| upload_time | 2025-08-01 12:27:09 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | None |
| keywords |
graph
visualization
neo4j
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
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|
# Graph Visualization for Python by Neo4j
[](https://pypi.org/project/neo4j-viz/)
[](https://pypi.org/project/neo4j-viz/)
[](https://neo4j.com/docs/nvl-python/preview/)
[](https://discord.gg/neo4j)
[](https://community.neo4j.com)
[](https://pypi.org/project/neo4j-viz/)
`neo4j-viz` is a Python package for creating interactive graph visualizations.
The output is of type `IPython.display.HTML` and can be viewed directly in a Jupyter Notebook or Streamlit application.
Alternatively, you can export the output to a file and view it in a web browser.
The package wraps the [Neo4j Visualization JavaScript library (NVL)](https://neo4j.com/docs/nvl/current/).
> [!WARNING]
> This package is still in development and the API is subject to change.
## Some notable features
* Easy to import graphs represented as:
* projections in the Neo4j Graph Data Science (GDS) library
* graphs from Neo4j query results
* pandas DataFrames
* Node features:
* Sizing
* Colors
* Captions
* Pinning
* On hover tooltip
* Relationship features:
* Colors
* Captions
* On hover tooltip
* Graph features:
* Zooming
* Panning
* Moving nodes
* Using different layouts
* Additional convenience functionality for:
* Resizing nodes, optionally including scale normalization
* Coloring nodes based on a property
* Toggle whether nodes should be pinned or not
Please note that this list is by no means exhaustive.
## Getting started
### Installation
Simply install with pip:
```sh
pip install neo4j-viz
```
### Basic usage
We will use a small toy graph representing the purchase history of a few people and products.
We start by instantiating the [Nodes](https://neo4j.com/docs/nvl-python/preview/api-reference/node.html) and
[Relationships](https://neo4j.com/docs/nvl-python/preview/api-reference/relationship.html) we want in our graph.
The only mandatory fields for a node are the "id", and "source" and "target" for a relationship.
But the other fields can optionally be used to customize the appearance of the nodes and relationships in the
visualization.
Lastly we create a
[VisualizationGraph](https://neo4j.com/docs/nvl-python/preview/api-reference/visualization-graph.html) object with the
nodes and relationships we created, and call its `render` method to display the graph.
```python
from neo4j_viz import Node, Relationship, VisualizationGraph
nodes = [
Node(id=0, size=10, caption="Person"),
Node(id=1, size=10, caption="Product"),
Node(id=2, size=20, caption="Product"),
Node(id=3, size=10, caption="Person"),
Node(id=4, size=10, caption="Product"),
]
relationships = [
Relationship(
source=0,
target=1,
caption="BUYS",
),
Relationship(
source=0,
target=2,
caption="BUYS",
),
Relationship(
source=3,
target=2,
caption="BUYS",
),
]
VG = VisualizationGraph(nodes=nodes, relationships=relationships)
VG.render()
```
This will return a `IPython.display.HTML` object that can be rendered in a Jupyter Notebook or streamlit application.
Please refer to the [documentation](https://neo4j.com/docs/nvl-python/preview/) for more details on the API and usage.
### Examples
For more extensive examples, including how to import graphs from Neo4j GDS projections and Pandas DataFrames,
checkout the [tutorials chapter](https://neo4j.com/docs/nvl-python/preview/tutorials/index.html) in the documentation.
Raw data
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"description": "# Graph Visualization for Python by Neo4j\n\n[](https://pypi.org/project/neo4j-viz/)\n[](https://pypi.org/project/neo4j-viz/)\n\n[](https://neo4j.com/docs/nvl-python/preview/)\n[](https://discord.gg/neo4j)\n[](https://community.neo4j.com)\n[](https://pypi.org/project/neo4j-viz/)\n\n`neo4j-viz` is a Python package for creating interactive graph visualizations.\n\nThe output is of type `IPython.display.HTML` and can be viewed directly in a Jupyter Notebook or Streamlit application.\nAlternatively, you can export the output to a file and view it in a web browser.\n\nThe package wraps the [Neo4j Visualization JavaScript library (NVL)](https://neo4j.com/docs/nvl/current/).\n\n> [!WARNING]\n> This package is still in development and the API is subject to change.\n\n\n\n\n\n## Some notable features\n\n* Easy to import graphs represented as:\n * projections in the Neo4j Graph Data Science (GDS) library\n * graphs from Neo4j query results\n * pandas DataFrames\n* Node features:\n * Sizing\n * Colors\n * Captions\n * Pinning\n * On hover tooltip\n* Relationship features:\n * Colors\n * Captions\n * On hover tooltip\n* Graph features:\n * Zooming\n * Panning\n * Moving nodes\n * Using different layouts\n* Additional convenience functionality for:\n * Resizing nodes, optionally including scale normalization\n * Coloring nodes based on a property\n * Toggle whether nodes should be pinned or not\n\nPlease note that this list is by no means exhaustive.\n\n\n## Getting started\n\n\n### Installation\n\nSimply install with pip:\n\n```sh\npip install neo4j-viz\n```\n\n\n### Basic usage\n\nWe will use a small toy graph representing the purchase history of a few people and products.\n\nWe start by instantiating the [Nodes](https://neo4j.com/docs/nvl-python/preview/api-reference/node.html) and\n[Relationships](https://neo4j.com/docs/nvl-python/preview/api-reference/relationship.html) we want in our graph.\nThe only mandatory fields for a node are the \"id\", and \"source\" and \"target\" for a relationship.\nBut the other fields can optionally be used to customize the appearance of the nodes and relationships in the\nvisualization.\n\nLastly we create a\n[VisualizationGraph](https://neo4j.com/docs/nvl-python/preview/api-reference/visualization-graph.html) object with the\nnodes and relationships we created, and call its `render` method to display the graph.\n\n```python\nfrom neo4j_viz import Node, Relationship, VisualizationGraph\n\nnodes = [\n Node(id=0, size=10, caption=\"Person\"),\n Node(id=1, size=10, caption=\"Product\"),\n Node(id=2, size=20, caption=\"Product\"),\n Node(id=3, size=10, caption=\"Person\"),\n Node(id=4, size=10, caption=\"Product\"),\n]\nrelationships = [\n Relationship(\n source=0,\n target=1,\n caption=\"BUYS\",\n ),\n Relationship(\n source=0,\n target=2,\n caption=\"BUYS\",\n ),\n Relationship(\n source=3,\n target=2,\n caption=\"BUYS\",\n ),\n]\n\nVG = VisualizationGraph(nodes=nodes, relationships=relationships)\n\nVG.render()\n```\n\nThis will return a `IPython.display.HTML` object that can be rendered in a Jupyter Notebook or streamlit application.\n\nPlease refer to the [documentation](https://neo4j.com/docs/nvl-python/preview/) for more details on the API and usage.\n\n\n### Examples\n\nFor more extensive examples, including how to import graphs from Neo4j GDS projections and Pandas DataFrames,\ncheckout the [tutorials chapter](https://neo4j.com/docs/nvl-python/preview/tutorials/index.html) in the documentation.\n",
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