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A library for high-performant graph algorithms.

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TODO: - [x] Tests - [x] Lazy build of random walks - [x] Documentation

fixes #48 - Expose Wcc in unladen_swallow - Add numpy to dev requirements

Add two new graph building methods `from_numpy` and `from_pandas`

It would make live for devs much easier, trying to figure out which library to use for their needs. ... including at least [petgraph](https://github.com/petgraph/petgraph).

- `to_undirected` in the Rust API accepts an optional layout, which is not exposed in the Python API - Additionally, allow relabelling in the same step - Maybe we can...

See GDS client for some inspiration: https://github.com/neo4j/graph-data-science-client/blob/b02dbb4000cc408ebca906fe45af1fc0dd3ff141/graphdatascience/graph/nx_loader.py#L47-L129

Hello, I have some trouble with your librairy with graph like this one : ``` Node(0). Node(1). Node(2). Node(3). Node(4). Node(5). Node(6). Node(7). Node(8). Node(9). Node(10). Node(11). Node(12). Node(13). Node(14)....