remove more cuspatial references (#774)

Contributes to rapidsai/build-planning#197

Follow-up to #742

Removes a few lingering mentions of `cuspatial`.

RAPIDS 25.04 was the last version with a `cuspatial` release: https://docs.rapids.ai/notices/rsn0045/

While updating this, also pulled in a few other very minor changes (to take advantage of the CI run):

* `pre-commit autoupdate`
* minor formatting improvements in READMEs (see https://yihui.org/en/2021/06/markdown-breath/)

## Notes for Reviewers

### How I tested this

Looked for references like this:

```shell
git grep -i cuspatial
git grep -i cuproj
```

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

Approvers:
  - Gil Forsyth (https://github.com/gforsyth)

URL: #774

Author: jameslamb

.pre-commit-config.yaml

@@ -9,7 +9,7 @@ repos:
       - id: end-of-file-fixer
       - id: trailing-whitespace
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.12.2
+    rev: v0.12.3
     hooks:
       - id: ruff
         args: ["--config", "pyproject.toml"]

Dockerfile

@@ -156,7 +156,7 @@ LABEL com.nvidia.workbench.package-manager-environment.type="conda"
 LABEL com.nvidia.workbench.package-manager.apt.binary="/usr/bin/apt"
 LABEL com.nvidia.workbench.package-manager.apt.installed-packages=""
 LABEL com.nvidia.workbench.package-manager.conda3.binary="/opt/conda/bin/conda"
-LABEL com.nvidia.workbench.package-manager.conda3.installed-packages="rapids cudf cuml cugraph rmm pylibraft cuspatial cuxfilter cucim xgboost jupyterlab"
+LABEL com.nvidia.workbench.package-manager.conda3.installed-packages="rapids cudf cuml cugraph rmm pylibraft cuxfilter cucim xgboost jupyterlab"
 LABEL com.nvidia.workbench.package-manager.pip.binary="/opt/conda/bin/pip"
 LABEL com.nvidia.workbench.package-manager.pip.installed-packages="jupyterlab-nvdashboard"
 LABEL com.nvidia.workbench.programming-languages="python3"

README.md

@@ -2,7 +2,6 @@
 
 This repository contains the end-user docker images for [RAPIDS](https://rapids.ai).
 
-
 ## Image types
 
 There are two image types: `base` ([`rapidsai/base`](https://hub.docker.com/r/rapidsai/base)) and `notebooks` ([`rapidsai/notebooks`](https://hub.docker.com/r/rapidsai/notebooks)).

dockerhub-readme.md

@@ -2,34 +2,32 @@
 
 ## What is RAPIDS?
 
-Visit [rapids.ai](https://rapids.ai) for more information.
-
 The RAPIDS suite of software libraries gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization, but exposes GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.
 
-**NOTE:** Review our [system requirements](https://docs.rapids.ai/install#system-req) to ensure you have a compatible system!
+Visit [rapids.ai](https://rapids.ai) for more information.
 
+**NOTE:** Review our [system requirements](https://docs.rapids.ai/install#system-req) to ensure you have a compatible system!
 
 ### Current Version - RAPIDS v25.08
 
 RAPIDS Libraries included in the images:
+
 - `cuDF`
 - `cuML`
 - `cuGraph`
 - `cuVS`
 - `RMM`
 - `RAFT`
-- `cuSpatial`
 - `cuxfilter`
 - `cuCIM`
 - `xgboost`
 
-
 ### Image Types
 
 The RAPIDS images are based on [`nvidia/cuda`](https://hub.docker.com/r/nvidia/cuda) and [`rapidsai/miniforge-cuda`](https://hub.docker.com/r/rapidsai/miniforge-cuda). The RAPIDS images provide `amd64` & `arm64` architectures [where supported](https://docs.rapids.ai/install#system-req).
 
-
 There are two types:
+
 - `rapidsai/base` - contains a RAPIDS environment ready for use.
   - **TIP: Use this image if you want to use RAPIDS as a part of your pipeline.**
 - `rapidsai/notebooks` - extends the `rapidsai/base` image by adding a [`jupyterlab` server](https://jupyter.org/), example notebooks, and dependencies.
@@ -38,7 +36,8 @@ There are two types:
 ### Image Tag Naming Scheme
 
 The tag naming scheme for RAPIDS images incorporates key platform details into the tag as shown below:
-```
+
+```text
 25.08-cuda12.9-py3.13
  ^        ^      ^
  |        |      Python version