https://github.com/paulgb/nbgraph

Inline, interactive graphs inside jupyter/ipython notebooks
https://github.com/paulgb/nbgraph

Last synced: about 2 months ago
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Inline, interactive graphs inside jupyter/ipython notebooks

• Host: GitHub
• URL: https://github.com/paulgb/nbgraph
• Owner: paulgb
• License: other
• Created: 2016-12-02T02:16:39.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2017-08-19T17:49:36.000Z (about 7 years ago)
• Last Synced: 2024-07-10T16:32:52.483Z (2 months ago)
• Language: Python
• Size: 4.58 MB
• Stars: 16
• Watchers: 4
• Forks: 5
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

        
nbgraph

=======

Interactive graph exploration inside of a Jupyter notebook. Graphs are rendered

with [sigma.js](http://sigmajs.org/).

![screenshot](screenshot.gif)

Installation

------------

Install is as simple as:

    pip install nbgraph

Use

---

Graphs are represented with the `NotebookGraph` class. Although manual

graph construction is possible with the `add_node` and `add_edge` methods, the

anticipated use-case is that the user will create or load a graph with another

library and use the `nbgraph` represenation only for the final display of the

graph. With this in mind, `nbgraph` comes with loaders for working with graphs

represented by [igraph](http://igraph.org/) or [networkx](https://networkx.github.io/).

Quick-start Examples

--------------------

See the `examples` directory for the examples as Jupyter notebooks.

## igraph

    from nbgraph.loaders.igraph_loader import load_graph

    import igraph

    G = igraph.Graph.Atlas(381)

    load_graph(G)

## networkx

    from nbgraph.loaders.networkx_loader import load_graph

    import networkx as nx

    G=nx.dodecahedral_graph()

    load_graph(G)

Notebooks with multiple graphs

------------------------------

If you use multiple graphs within the same notebook, you will see a warning

about `nbgraph` being loaded multiple times. This is because the Python code

can't reliably know what's loaded in the JavaScript, so it tries to load it

every time a graph is displayed. This means sending the entire graph rendering

code for each graph, which can explode the size of an `.ipynb` file.

To avoid this, use `prepare_notebook`:

    from nbgraph.renderer import display_notebook, prepare_notebook

    prepare_notebook()

Then, use `display_notebook` with an extra `False` argument to display the

graph:

    my_graph = load_graph(G)

    display_notebook(load_graph(my_graph), False)