Remove nx-cugraph from this repo

.gitignore

@@ -78,9 +78,6 @@ datasets/*
 !datasets/karate-disjoint.csv
 !datasets/netscience.csv
 
-# nx-cugraph side effects
-python/nx-cugraph/objects.inv
-
 .pydevproject
 
 # Jupyter Notebooks

.pre-commit-config.yaml

@@ -19,7 +19,6 @@ repos:
         language_version: python3
         args: [--target-version=py310]
         files: ^(python/.*|benchmarks/.*)$
-        exclude: ^python/nx-cugraph/
   - repo: https://github.com/PyCQA/flake8
     rev: 7.1.1
     hooks:
@@ -59,23 +58,3 @@ repos:
     hooks:
         - id: rapids-dependency-file-generator
           args: ["--clean"]
-  - repo: local
-    hooks:
-      - id: nx-cugraph-meta-data-update
-        name: nx-cugraph meta-data updater
-        entry: bash -c "PYTHONPATH=./python/nx-cugraph python ./python/nx-cugraph/_nx_cugraph/__init__.py"
-        files: ^python/nx-cugraph/
-        types: [python]
-        language: python
-        pass_filenames: false
-        additional_dependencies: ["networkx>=3.4"]
-  - repo: local
-    hooks:
-      - id: nx-cugraph-readme-update
-        name: nx-cugraph README updater
-        entry: bash -c "PYTHONPATH=./python/nx-cugraph python ./python/nx-cugraph/scripts/update_readme.py ./python/nx-cugraph/README.md"
-        files: ^python/nx-cugraph/
-        types_or: [python, markdown]
-        language: python
-        pass_filenames: false
-        additional_dependencies: ["networkx>=3.4"]

README.md

@@ -37,7 +37,7 @@
 -----
 ## News
 
-___NEW!___   _[nx-cugraph](./python/nx-cugraph/README.md)_, a NetworkX backend that provides GPU acceleration to NetworkX with zero code change.
+___NEW!___   _[nx-cugraph](https://rapids.ai/nx-cugraph/)_, a NetworkX backend that provides GPU acceleration to NetworkX with zero code change.
 ```
 > pip install nx-cugraph-cu11 --extra-index-url https://pypi.nvidia.com
 > export NETWORKX_AUTOMATIC_BACKENDS=cugraph
@@ -62,7 +62,7 @@ That's it.  NetworkX now leverages cuGraph for accelerated graph algorithms.
     - [External Data Types](./readme_pages/data_types.md)
   - [pylibcugraph](./readme_pages/pylibcugraph.md)
   - [libcugraph (C/C++/CUDA)](./readme_pages/libcugraph.md)
-  - [nx-cugraph](./python/nx-cugraph/README.md)
+  - [nx-cugraph](https://rapids.ai/nx-cugraph/)
   - [cugraph-service](./readme_pages/cugraph_service.md)
   - [cugraph-dgl](./readme_pages/cugraph_dgl.md)
   - [cugraph-ops](./readme_pages/cugraph_ops.md)
@@ -127,7 +127,7 @@ df_page.sort_values('pagerank', ascending=False).head(10)
 * ArangoDB - a free and open-source native multi-model database system  - https://www.arangodb.com/
 * CuPy - "NumPy/SciPy-compatible Array Library for GPU-accelerated Computing with Python" -  https://cupy.dev/
 * Memgraph - In-memory Graph database - https://memgraph.com/
-* NetworkX (via [nx-cugraph](./python/nx-cugraph/README.md) backend) - an extremely popular, free and open-source package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks - https://networkx.org/
+* NetworkX (via [nx-cugraph](https://rapids.ai/nx-cugraph/) backend) - an extremely popular, free and open-source package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks - https://networkx.org/
 * PyGraphistry - free and open-source GPU graph ETL, AI, and visualization, including native RAPIDS & cuGraph support - http://github.com/graphistry/pygraphistry
 * ScanPy - a scalable toolkit for analyzing single-cell gene expression data - https://scanpy.readthedocs.io/en/stable/