chore: import upstream snapshot with attribution

examples/python/minimal/README.md

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+<!--[metadata]
+title = "Minimal example"
+thumbnail = "https://static.rerun.io/minimal-example/9e694c0689f20323ed0053506a7a099f7391afca/480w.png"
+thumbnail_dimensions = [480, 480]
+tags = ["3D", "API example"]
+-->
+
+Generates a 3D colored cube and demonstrates how to log a point cloud.
+
+<picture>
+  <source media="(max-width: 480px)" srcset="https://static.rerun.io/minimal/0e47ac513ab25d56cf2b493128097d499a07e5e8/480w.png">
+  <source media="(max-width: 768px)" srcset="https://static.rerun.io/minimal/0e47ac513ab25d56cf2b493128097d499a07e5e8/768w.png">
+  <source media="(max-width: 1024px)" srcset="https://static.rerun.io/minimal/0e47ac513ab25d56cf2b493128097d499a07e5e8/1024w.png">
+  <source media="(max-width: 1200px)" srcset="https://static.rerun.io/minimal/0e47ac513ab25d56cf2b493128097d499a07e5e8/1200w.png">
+  <img src="https://static.rerun.io/minimal/0e47ac513ab25d56cf2b493128097d499a07e5e8/full.png" alt="Minimal example screenshot">
+</picture>
+
+Straightforward example from the [Quick Start guide](https://www.rerun.io/docs/getting-started/data-in/python) to generate a 3D colored cube and demonstrate how to log a point cloud.
+
+## Used Rerun types
+
+[`Points3D`](https://www.rerun.io/docs/reference/types/archetypes/points3d)
+
+## Logging and visualizing with Rerun
+
+The visualizations in this example were created with the following Rerun code:
+
+It logs 3D points, each associated with a specific color, forming a grid pattern using [`Points3D`](https://www.rerun.io/docs/reference/types/archetypes/points3d) archetype.
+```python
+import rerun as rr
+import numpy as np
+
+rr.init("rerun_example_my_data", spawn=True)
+
+SIZE = 10
+
+pos_grid = np.meshgrid(*[np.linspace(-10, 10, SIZE)] * 3)
+positions = np.vstack([d.reshape(-1) for d in pos_grid]).T
+
+col_grid = np.meshgrid(*[np.linspace(0, 255, SIZE)] * 3)
+colors = np.vstack([c.reshape(-1) for c in col_grid]).astype(np.uint8).T
+
+rr.log("my_points", rr.Points3D(positions, colors=colors, radii=0.5))
+ ```
+
+## Run the code
+To run this example, make sure you have the Rerun repository checked out and the latest SDK installed:
+```bash
+pip install --upgrade rerun-sdk  # install the latest Rerun SDK
+git clone git@github.com:rerun-io/rerun.git  # Clone the repository
+cd rerun
+git checkout latest  # Check out the commit matching the latest SDK release
+```
+Install the necessary libraries specified in the requirements file:
+```bash
+pip install -e examples/python/minimal
+```
+To experiment with the provided example, simply execute the main Python script:
+```bash
+python -m minimal # run the example
+```

examples/python/minimal/minimal.py

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+#!/usr/bin/env python3
+"""Demonstrates the most barebone usage of the Rerun SDK."""
+
+from __future__ import annotations
+
+import sys
+
+import numpy as np
+
+import rerun as rr  # pip install rerun-sdk
+
+
+def main() -> None:
+    # sanity-check since all other example scripts take arguments:
+    assert len(sys.argv) == 1, f"{sys.argv[0]} does not take any arguments"
+
+    rr.init("rerun_example_minimal", spawn=True)
+
+    positions = np.vstack([xyz.ravel() for xyz in np.mgrid[3 * [slice(-10, 10, 10j)]]]).T
+    colors = np.vstack([rgb.ravel() for rgb in np.mgrid[3 * [slice(0, 255, 10j)]]]).astype(np.uint8).T
+
+    rr.log("my_points", rr.Points3D(positions, colors=colors, radii=0.5))
+
+
+if __name__ == "__main__":
+    main()

examples/python/minimal/pyproject.toml

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+[project]
+name = "minimal"
+version = "0.1.0"
+readme = "README.md"
+dependencies = ["numpy", "rerun-sdk"]
+
+[project.scripts]
+minimal = "minimal:main"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"