docs(notebooks): remove dev extra from install instructions

  The  installs pytest/ruff/pre-commit, not needed for
  running notebooks. Install guidance moved to getting-started docs.

  Signed-off-by: print-sid8 sidsub94@gmail.com

Author: print-sid8

docs/getting-started/index.md

@@ -36,6 +36,32 @@ Verify the installation:
 python -c "import rasteret; print(rasteret.version())"
 ```
 
+### Running notebooks
+
+=== "Jupyter / JupyterLab"
+
+    Jupyter runs each notebook in a **kernel** — a separate Python process.
+    To use your Rasteret environment as a kernel:
+
+    ```bash
+    uv pip install ipykernel
+    python -m ipykernel install --user --name rasteret --display-name "Rasteret"
+    ```
+
+    Then select the **Rasteret** kernel when you open a notebook.
+
+=== "marimo"
+
+    [marimo](https://marimo.io) manages dependencies inline — no kernel
+    registration needed.  Just `uv pip install marimo` alongside Rasteret
+    and run `marimo edit notebook.py`.
+
+=== "VS Code"
+
+    VS Code auto-detects virtual environments.  Open a `.ipynb` file,
+    click the kernel picker (top-right), and select the Python interpreter
+    from your Rasteret venv.
+
 ---
 
 ## Key concepts

notebooks/01_quickstart_xarray.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "id": "intro",
    "metadata": {},
-   "source": "# Quickstart: xarray\n\nThis notebook shows the minimal Rasteret workflow:\n\n1. **Build** a `Collection` from the dataset catalog (one-time, cached)\n2. **Fetch** pixels for a small AOI + time window as `xarray.Dataset`\n3. **Compute** NDVI\n\n### Requirements\n\n```bash\nuv sync --extra dev\n```"
+   "source": "# Quickstart: xarray\n\nThis notebook shows the minimal Rasteret workflow:\n\n1. **Build** a `Collection` from the dataset catalog (one-time, cached)\n2. **Fetch** pixels for a small AOI + time window as `xarray.Dataset`\n3. **Compute** NDVI"
   },
   {
    "cell_type": "code",

notebooks/02_torchgeo_09_accelerator.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "id": "intro",
    "metadata": {},
-   "source": "# TorchGeo Integration\n\nRasteret's TorchGeo integration is **opt-in** and stays TorchGeo-native:\n\n- Rasteret produces a standard `GeoDataset`. All TorchGeo samplers, transforms, and collation work unchanged.\n- If your data is not a tiled GeoTIFF/COG, use TorchGeo's built-in `RasterDataset` directly.\n- Rasteret handles data access; TorchGeo handles the ML workflow.\n\n### Requirements\n\n```bash\nuv sync --extra dev --extra torchgeo\n```"
+   "source": "# TorchGeo Integration\n\nRasteret's TorchGeo integration is **opt-in** and stays TorchGeo-native:\n\n- Rasteret produces a standard `GeoDataset`. All TorchGeo samplers, transforms, and collation work unchanged.\n- If your data is not a tiled GeoTIFF/COG, use TorchGeo's built-in `RasterDataset` directly.\n- Rasteret handles data access; TorchGeo handles the ML workflow."
   },
   {
    "cell_type": "code",

notebooks/05_torchgeo_comparison.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "id": "intro",
    "metadata": {},
-   "source": "# TorchGeo Benchmark\n\nThis notebook runs an **identical time-series workload** through two paths:\n\n- **Path A**: TorchGeo 0.9 `time_series=True`: sequential per-file reads via GDAL vsicurl\n- **Path B**: Rasteret `to_torchgeo_dataset(time_series=True)` with default backend routing\n\n**Controlled variables** (same across all paths):\n- AOI, date range, band (B04), scene count, chip size (256), batch size (2)\n- Same `RandomGeoSampler` → `DataLoader` → batch flow\n- Same output shape: `[batch, T, C, H, W]`, all timesteps stacked\n\nThe only difference is **how pixel data reaches the DataLoader**.\n\n### Requirements\n\n```bash\nuv sync --extra dev --extra torchgeo\n```"
+   "source": "# TorchGeo Benchmark\n\nThis notebook runs an **identical time-series workload** through two paths:\n\n- **Path A**: TorchGeo 0.9 `time_series=True`: sequential per-file reads via GDAL vsicurl\n- **Path B**: Rasteret `to_torchgeo_dataset(time_series=True)` with default backend routing\n\n**Controlled variables** (same across all paths):\n- AOI, date range, band (B04), scene count, chip size (256), batch size (2)\n- Same `RandomGeoSampler` → `DataLoader` → batch flow\n- Same output shape: `[batch, T, C, H, W]`, all timesteps stacked\n\nThe only difference is **how pixel data reaches the DataLoader**."
   },
   {
    "cell_type": "code",