move cuxfilter to 'inactive' projects, remove references (#809)

Contributes to rapidsai/build-planning#291

* moves `cuxfilter` to the "inactive projects' section of the API docs
* removes references encouraging its use

Authors:
  - James Lamb (https://github.com/jameslamb)

Approvers:
  - Bradley Dice (https://github.com/bdice)

URL: #809

Author: jameslamb

_data/docs.yml

@@ -46,17 +46,6 @@ apis:
       legacy: 1
       stable: 1
       nightly: 1
-  cuxfilter:
-    name: cuxfilter
-    path: cuxfilter
-    desc: 'cuxfilter acts as a connector library, which provides the connections between different visualization libraries and a GPU dataframe without much hassle. This also allows the user to use charts from different libraries in a single dashboard, while also providing the interaction.'
-    ghlink: https://github.com/rapidsai/cuxfilter
-    cllink: https://github.com/rapidsai/cuxfilter/blob/main/CHANGELOG.md
-    versions:
-      # enable or disable links; 0 = disabled, 1 = enabled
-      legacy: 1
-      stable: 1
-      nightly: 1
   cudf-java:
     name: 'Java + cuDF'
     path: cudf-java
@@ -294,6 +283,22 @@ inactive-projects:
     version-overrides:
       legacy: "25.02"
       stable: "25.04"
+  cuxfilter:
+    name: cuxfilter
+    path: cuxfilter
+    desc: 'cuxfilter acts as a connector library, which provides the connections between different visualization libraries and a GPU dataframe without much hassle. This also allows the user to use charts from different libraries in a single dashboard, while also providing the interaction.'
+    ghlink: https://github.com/rapidsai/cuxfilter
+    cllink: https://github.com/rapidsai/cuxfilter/blob/main/CHANGELOG.md
+    versions:
+      # enable or disable links; 0 = disabled, 1 = enabled
+      legacy: 1
+      stable: 1
+      nightly: 0
+    # always use these specific versions for these specific paths, regardless
+    # of the current state of RAPIDS
+    version-overrides:
+      legacy: "26.04"
+      stable: "26.06"
   libcuproj:
     name: libcuproj
     path: libcuproj

_includes/selector.html

@@ -395,11 +395,11 @@
             img_loc: ["NGC", "Docker Hub"],
             img_types: ["Base", "Notebooks"],
             packages: ["Standard", "Choose Specific Packages"],
-            additional_pip_packages: ["cuDF", "dask-cuDF", "cuML", "cuGraph/nx-cugraph", "cuxfilter", "cuCIM", "RAFT", "cuVS", "nvForest"],
-            additional_rapids_packages: ["cuDF", "cuML", "cuGraph", "cuxfilter", "cuCIM", "RAFT", "cuVS", "nvForest"],
+            additional_pip_packages: ["cuDF", "dask-cuDF", "cuML", "cuGraph/nx-cugraph", "cuCIM", "RAFT", "cuVS", "nvForest"],
+            additional_rapids_packages: ["cuDF", "cuML", "cuGraph", "cuCIM", "RAFT", "cuVS", "nvForest"],
             additional_packages: ["Graphistry", "JupyterLab", "NetworkX + nx-cugraph", "Plotly Dash", "PyTorch", "TensorFlow", "Xarray-Spatial"],
             note_prefix: "<i class='fas fa-info-circle text-blue'></i>",
-            rapids_meta_pkgs: ["cuDF", "cuML", "cuGraph", "nx-cugraph", "cuxfilter", "cuCIM", "RAFT", "cuVS"],
+            rapids_meta_pkgs: ["cuDF", "cuML", "cuGraph", "nx-cugraph", "cuCIM", "RAFT", "cuVS"],
             getStableVersion() {
                 return "{{ site.data.releases.stable.version }}";
             },

ci/customization/projects-to-versions.json

@@ -19,11 +19,6 @@
     "stable": "26.06",
     "nightly": "26.08"
   },
-  "cuxfilter": {
-    "legacy": "26.04",
-    "stable": "26.06",
-    "nightly": "26.08"
-  },
   "cudf-java": {
     "legacy": "26.04",
     "stable": "26.06"
@@ -115,6 +110,10 @@
     "legacy": "25.02",
     "stable": "25.04"
   },
+  "cuxfilter": {
+    "legacy": "26.04",
+    "stable": "26.06"
+  },
   "libcuproj": {
     "legacy": "25.02",
     "stable": "25.04"

user-guide/index.md

@@ -46,12 +46,6 @@ The RAPIDS data science framework is a collection of libraries for running end-t
  Start with the [cuSpatial User Guide](/api/cuspatial/stable/user_guide/cuspatial_api_examples/){: target="_blank"} for an intro to GPU Accelerated Spatial Analytics.
 {: .mb-8 }
 
-
-**<i class="fa-light fa-chart-scatter-bubble"></i> Accelerated Cross Filtered Visualization with [cuxfilter](https://github.com/rapidsai/cuxfilter)**:
- Start with [10 Minutes to Cuxfilter](api/cuxfilter/stable/user_guide/10_minutes_to_cuxfilter/){: target="_blank"} to get an overview of how to quickly create a dashboard. There are also broader examples in the [RAPIDS Visualization Guides](https://github.com/rapidsai/cuxfilter/tree/HEAD/notebooks/RAPIDS%20Visualization%20Guide){: target="_blank"}.
-{: .mb-8 }
-
-
 **<i class="fa-light fa-images"></i> Computer Vision and Analytics with [cuCIM](https://github.com/rapidsai/cucim){: target="_blank"}**:
  Start with the [Welcome Notebook](https://github.com/rapidsai/cucim/blob/branch-{{ site.data.releases.stable.version }}/notebooks/Welcome.ipynb){: target="_blank"} for links to resources guides and a good overview of the project structure.
 {: .mb-8 }

visualization/index.md

@@ -14,6 +14,7 @@ RAPIDS libraries can easily fit in visualization workflows. This catalog of feat
 *[330 million+ datapoints rendered in under 1.5s via RAPIDS + Plotly Dash 2020 Census Demo](https://github.com/rapidsai/plotly-dash-rapids-census-demo)*
 
 ### Featured Libraries
+
 - **[HoloViews](#holoviews):** Declarative objects for quickly building complex interactive plots from high-level specifications. Directly uses cuDF.
 - **[hvPlot](#hvplot):** Quickly return interactive plots from cuDF, Pandas, Xarray, or other data structures. Just replace `.plot()` with `.hvplot()`.
 - **[Datashader](#datashader):** Rasterizing huge datasets quickly as scatter, line, geospatial, or graph charts. Directly uses cuDF.
@@ -22,9 +23,9 @@ RAPIDS libraries can easily fit in visualization workflows. This catalog of feat
 - **[Seaborn](#seaborn):** Static single charting library that extends matplotlib.
 
 ### Other Notable Libraries
+
 - **[Panel](#panel):** A high-level app and dashboarding solution for the Python ecosystem.
 - **[PyDeck](#pydeck):** Python bindings for interactive spatial visualizations with webGL powered deck.gl, optimized for a Jupyter environment.
-- **[cuxfilter](#cuxfilter):** RAPIDS developed cross filtering dashboarding tool that integrates many of the libraries above.
 - **[node RAPIDS](#noderapids):** RAPIDS bindings in nodeJS, a high performance JS/TypeScript visualization alternative to using Python.
 
 
@@ -34,11 +35,10 @@ The below libraries directly use RAPIDS cuDF/Dask-cuDF and/or cuSpatial to creat
 - **[Holoviews with Linked Brushing User Guide](https://holoviews.org/user_guide/Linked_Brushing.html?highlight=linked%20brushing)**
 - **[Datashader User Guide](https://datashader.org/user_guide/Performance.html)**
 - **[Plotly Dash with Holoviews Docs](https://dash.plotly.com/holoviews#gpu-accelerating-datashader-and-linked-selections-with-rapids)**
-- **[cuxfilter GitHub](https://github.com/rapidsai/cuxfilter)**
-
 
 ### **Note:** Web Hosted vs Local Hosted Chart Interaction
-When interacting with this page through a website, the interactive examples below are all **static and use pre-computed data.** To run a true interactive version, host through the **active** instance found on our [cuxfilter GitHub Notebooks](https://github.com/rapidsai/cuxfilter/tree/branch-{{ site.data.releases.stable.version }}/notebooks/RAPIDS%20Visualization%20Guide).
+
+When interacting with this page through a website, the interactive examples below are all **static and use pre-computed data.**
 
 {% include viz-cdn-js-css.html %}
 
@@ -77,7 +77,7 @@ When interacting with this page through a website, the interactive examples belo
 <img src="/assets/images/clifford_interact.png" style="width:130px; display:inline-block; vertical-align:middle; padding-left:20px; "></a>
 
 - Datashader is a graphics pipeline system for creating meaningful representations of large datasets quickly and flexibly.
-- Datashader is able to render a variety of chart types statically, and interactively when combined with other libraries like HoloViews or cuxfilter.
+- Datashader is able to render a variety of chart types statically, and interactively when combined with other libraries like HoloViews.
 - Read about Datashader at [datashader.org](https://datashader.org) and explore its examples.
 - Read about [RAPIDS compatibility](https://datashader.org/user_guide/Performance.html?highlight=cudf#data-objects).
 <br/>
@@ -153,18 +153,6 @@ When interacting with this page through a website, the interactive examples belo
 - Read about pyDeck at [pydeck.gl/](https://pydeck.gl/) and explore its gallery [pydeck gallery](https://pydeck.gl/#gallery).
 - Further [Documentation](https://pydeck.gl/layer.html).
 
-
-<a id='cuxfilter'></a><br/>
-<img src="/assets/images/rapids_logo.png" style="width:150px; display:inline-block; vertical-align:middle;">
-<span style="color:#7400ff; font-size:2.5em; vertical-align: middle;">cuxfilter</span>
-<a href="https://docs.rapids.ai/api/cuxfilter/nightly/examples/examples.html" target="_blank" title="cuxfilter example page">
-<img src="/assets/images/cuxfilter-demo.gif" style="width:220px; display:inline-block; vertical-align:middle; padding-left:20px;"></a>
-<br/>
-- cuxfilter is a RAPIDS developed cross filtering library which enables GPU accelerated dashboards, using best in class charting libraries, with just a few lines of Python.
-- Read about cuxfilter at [github.com/rapidsai/cuxfilter](https://github.com/rapidsai/cuxfilter) and explore its examples [docs.rapids.ai/api/cuxfilter/stable/examples/examples.html](https://docs.rapids.ai/api/cuxfilter/stable/examples/examples.html).
-- Further [Documentation](https://docs.rapids.ai/api/cuxfilter/stable/10_minutes_to_cuxfilter.html).
-
-
 <a id='noderapids'></a><br/>
 <img src="/assets/images/rapids_logo.png" style="width:150px; display:inline-block; vertical-align:middle;">
 <span style="color:#7400ff; font-size:2.5em; vertical-align: middle;">nodeRAPIDS</span>
@@ -178,5 +166,4 @@ When interacting with this page through a website, the interactive examples belo
 - Further [Documentation](https://rapidsai.github.io/node/).
 
 
-
 <br/><br/><br/>