WIP/PoC: setting up sphinx website

.github/workflows/deploy-docs.yml

@@ -0,0 +1,34 @@
+name: Deploy-docs
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.13"
+
+      - name: Install deps
+        run: |
+          python3 -m pip install -U pip
+          python3 -m pip install -e ".[docs]"
+
+      - name: Build docs (warnings as errors)
+        run: |
+          python3 -m sphinx -b html docs docs/_build/html
+
+      - name: Upload HTML artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: docs-html
+          path: docs/_build/html

CONTRIBUTING.md

@@ -1,4 +1,4 @@
-# Welcome to nx-parallel!
+# Contributors Guide
 
 Hi, Thanks for stopping by!
 
@@ -105,7 +105,7 @@ git push origin <branch_name>
 
 For displaying a small note about nx-parallel's implementation at the end of the main NetworkX documentation, we use the `backend_info` [entry_point](https://packaging.python.org/en/latest/specifications/entry-points/#entry-points) (in the `pyproject.toml` file). The [`get_info` function](./_nx_parallel/__init__.py) is used to parse the docstrings of all the algorithms in nx-parallel and display the nx-parallel specific documentation on the NetworkX's main docs, in the "Additional Backend implementations" box, as shown in the screenshot below.
 
-![backend_box_ss](./assets/images/backend_box_ss.png)
+![backend_box_ss](_static/backend_box_ss.png)
 
 nx-parallel follows [sphinx docstring guidelines](https://the-ultimate-sphinx-tutorial.readthedocs.io/en/latest/_guide/_styleguides/docstrings-guidelines.html) for writing docstrings. But, while extracting the docstring to display on the main networkx docs, only the first paragraph of the function's description and the first paragraph of each parameter's description is extracted and displayed. So, make sure to include all the necessary information in the first paragraphs itself. And you only need to include the additional **backend** parameters in the `Parameters` section and not all the parameters. Also, it is recommended to include a link to the networkx function's documentation page in the docstring, at the end of the function description.
 

README.md

@@ -1,61 +1,7 @@
-# nx-parallel
+# Overview
 
 nx-parallel is a NetworkX backend that uses joblib for parallelization. This project aims to provide parallelized implementations of various NetworkX functions to improve performance. Refer [NetworkX backends documentation](https://networkx.org/documentation/latest/reference/backends.html) to learn more about the backend architecture in NetworkX.
 
-## Algorithms in nx-parallel
-
-- [adamic_adar_index](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/link_prediction.py#L108)
-- [all_pairs_all_shortest_paths](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/shortest_paths/generic.py#L11)
-- [all_pairs_bellman_ford_path](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/shortest_paths/weighted.py#L208)
-- [all_pairs_bellman_ford_path_length](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/shortest_paths/weighted.py#L165)
-- [all_pairs_dijkstra](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/shortest_paths/weighted.py#L29)
-- [all_pairs_dijkstra_path](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/shortest_paths/weighted.py#L122)
-- [all_pairs_dijkstra_path_length](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/shortest_paths/weighted.py#L72)
-- [all_pairs_node_connectivity](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/connectivity/connectivity.py#L18)
-- [all_pairs_shortest_path](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/shortest_paths/unweighted.py#L62)
-- [all_pairs_shortest_path_length](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/shortest_paths/unweighted.py#L19)
-- [approximate_all_pairs_node_connectivity](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/approximation/connectivity.py#L14)
-- [average_clustering](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/cluster.py#L213)
-- [average_neighbor_degree](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/assortativity/neighbor_degree.py#L10)
-- [betweenness_centrality](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/centrality/betweenness.py#L20)
-- [closeness_vitality](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/vitality.py#L10)
-- [clustering](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/cluster.py#L146)
-- [cn_soundarajan_hopcroft](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/link_prediction.py#L200)
-- [colliders](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/dag.py#L37)
-- [common_neighbor_centrality](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/link_prediction.py#L158)
-- [edge_betweenness_centrality](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/centrality/betweenness.py#L103)
-- [harmonic_centrality](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/centrality/harmonic.py#L10)
-- [is_reachable](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/tournament.py#L15)
-- [jaccard_coefficient](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/link_prediction.py#L80)
-- [johnson](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/shortest_paths/weighted.py#L251)
-- [local_efficiency](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/efficiency_measures.py#L11)
-- [node_redundancy](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/bipartite/redundancy.py#L12)
-- [number_attracting_components](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/components/attracting.py#L9)
-- [number_connected_components](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/components/connected.py#L9)
-- [number_of_isolates](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/isolate.py#L9)
-- [number_strongly_connected_components](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/components/strongly_connected.py#L9)
-- [number_weakly_connected_components](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/components/weakly_connected.py#L9)
-- [preferential_attachment](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/link_prediction.py#L133)
-- [ra_index_soundarajan_hopcroft](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/link_prediction.py#L232)
-- [resource_allocation_index](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/link_prediction.py#L55)
-- [square_clustering](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/cluster.py#L22)
-- [tournament_is_strongly_connected](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/tournament.py#L76)
-- [triangles](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/cluster.py#L84)
-- [v_structures](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/dag.py#L13)
-- [within_inter_cluster](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/algorithms/link_prediction.py#L264)
-
-<details>
-<summary>Script used to generate the above list</summary>
-
-```
-import _nx_parallel as nxp
-d = nxp.get_funcs_info() # temporarily add `from .update_get_info import *` to _nx_parallel/__init__.py
-for func in d:
-    print(f"- [{func}]({d[func]['url']})")
-```
-
-</details>
-
 ## Installation
 
 You can install the stable version of nx-parallel using pip or conda:
@@ -73,7 +19,7 @@ For more, see [INSTALL.md](./INSTALL.md).
 You can run your networkx code with nx-parallel backend by:
 
 ```sh
-export NETWORKX_AUTOMATIC_BACKENDS="parallel" && python nx_code.py
+export NETWORKX_BACKEND_PRIORITY="parallel" && python nx_code.py
 ```
 
 Note that for all functions inside `nx_code.py` that do not have an nx-parallel implementation, their original networkx implementation will be executed. You can also use the nx-parallel backend in your code for only some specific function calls in the following ways:

docs/CONTRIBUTING.md

@@ -0,0 +1 @@
+../CONTRIBUTING.md

docs/Config.md

@@ -0,0 +1 @@
+../Config.md

docs/INSTALL.md

@@ -0,0 +1 @@
+../INSTALL.md

docs/LICENSE.md

@@ -0,0 +1 @@
+../LICENSE.md

docs/Makefile

@@ -0,0 +1,20 @@
+# Minimal makefile for Sphinx documentation
+#
+
+# You can set these variables from the command line, and also
+# from the environment for the first two.
+SPHINXOPTS    ?=
+SPHINXBUILD   ?= sphinx-build
+SOURCEDIR     = .
+BUILDDIR      = _build
+
+# Put it first so that "make" without argument is like "make help".
+help:
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+.PHONY: help Makefile
+
+# Catch-all target: route all unknown targets to Sphinx using the new
+# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
+%: Makefile
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

docs/Overview.md

@@ -0,0 +1 @@
+../README.md

docs/Tutorial.md

@@ -0,0 +1,3 @@
+# Tutorial
+
+todo