Improved GeoArrow interop

docs/api/traits.md

@@ -1,5 +1,7 @@
 # lonboard.traits
 
+::: lonboard.traits.PyarrowTableTrait
+
 ::: lonboard.traits.ColorAccessor
 
 ::: lonboard.traits.FloatAccessor

lonboard/_layer.py

@@ -411,25 +411,51 @@ class ScatterplotLayer(BaseArrowLayer):
 
     **Example:**
 
+    From GeoPandas:
+
     ```py
     import geopandas as gpd
     from lonboard import Map, ScatterplotLayer
 
-    # A GeoDataFrame with Point geometries
+    # A GeoDataFrame with Point or MultiPoint geometries
     gdf = gpd.GeoDataFrame()
     layer = ScatterplotLayer.from_geopandas(
         gdf,
         get_fill_color=[255, 0, 0],
     )
     m = Map(layers=[layer])
     ```
+
+    From [geoarrow-rust](https://geoarrow.github.io/geoarrow-rs/python/latest):
+
+    ```py
+    from geoarrow.rust.core import read_parquet
+    from lonboard import Map, ScatterplotLayer
+
+    # Example: A GeoParquet file with Point or MultiPoint geometries
+    table = read_parquet("path/to/file.parquet")
+    layer = ScatterplotLayer(
+        table=table,
+        get_fill_color=[255, 0, 0],
+    )
+    m = Map(layers=[layer])
+    ```
     """
 
     _layer_type = traitlets.Unicode("scatterplot").tag(sync=True)
 
     table = PyarrowTableTrait(
         allowed_geometry_types={EXTENSION_NAME.POINT, EXTENSION_NAME.MULTIPOINT}
     )
+    """A GeoArrow table with a Point or MultiPoint column.
+
+    This is the fastest way to plot data from an existing GeoArrow source, such as
+    [geoarrow-rust](https://geoarrow.github.io/geoarrow-rs/python/latest) or
+    [geoarrow-pyarrow](https://geoarrow.github.io/geoarrow-python/main/index.html).
+
+    If you have a GeoPandas `GeoDataFrame`, use
+    [`from_geopandas`][lonboard.ScatterplotLayer.from_geopandas] instead.
+    """
 
     radius_units = traitlets.Unicode("meters", allow_none=True).tag(sync=True)
     """
@@ -605,11 +631,13 @@ class PathLayer(BaseArrowLayer):
 
     **Example:**
 
+    From GeoPandas:
+
     ```py
     import geopandas as gpd
     from lonboard import Map, PathLayer
 
-    # A GeoDataFrame with LineString geometries
+    # A GeoDataFrame with LineString or MultiLineString geometries
     gdf = gpd.GeoDataFrame()
     layer = PathLayer.from_geopandas(
         gdf,
@@ -618,6 +646,22 @@ class PathLayer(BaseArrowLayer):
     )
     m = Map(layers=[layer])
     ```
+
+    From [geoarrow-rust](https://geoarrow.github.io/geoarrow-rs/python/latest):
+
+    ```py
+    from geoarrow.rust.core import read_parquet
+    from lonboard import Map, PathLayer
+
+    # Example: A GeoParquet file with LineString or MultiLineString geometries
+    table = read_parquet("path/to/file.parquet")
+    layer = PathLayer(
+        table=table,
+        get_color=[255, 0, 0],
+        width_min_pixels=2,
+    )
+    m = Map(layers=[layer])
+    ```
     """
 
     _layer_type = traitlets.Unicode("path").tag(sync=True)
@@ -628,6 +672,15 @@ class PathLayer(BaseArrowLayer):
             EXTENSION_NAME.MULTILINESTRING,
         }
     )
+    """A GeoArrow table with a LineString or MultiLineString column.
+
+    This is the fastest way to plot data from an existing GeoArrow source, such as
+    [geoarrow-rust](https://geoarrow.github.io/geoarrow-rs/python/latest) or
+    [geoarrow-pyarrow](https://geoarrow.github.io/geoarrow-python/main/index.html).
+
+    If you have a GeoPandas `GeoDataFrame`, use
+    [`from_geopandas`][lonboard.PathLayer.from_geopandas] instead.
+    """
 
     width_units = traitlets.Unicode(allow_none=True).tag(sync=True)
     """
@@ -738,25 +791,51 @@ class SolidPolygonLayer(BaseArrowLayer):
 
     **Example:**
 
+    From GeoPandas:
+
     ```py
     import geopandas as gpd
     from lonboard import Map, SolidPolygonLayer
 
-    # A GeoDataFrame with Polygon geometries
+    # A GeoDataFrame with Polygon or MultiPolygon geometries
     gdf = gpd.GeoDataFrame()
     layer = SolidPolygonLayer.from_geopandas(
         gdf,
         get_fill_color=[255, 0, 0],
     )
     m = Map(layers=[layer])
     ```
+
+    From [geoarrow-rust](https://geoarrow.github.io/geoarrow-rs/python/latest):
+
+    ```py
+    from geoarrow.rust.core import read_parquet
+    from lonboard import Map, SolidPolygonLayer
+
+    # Example: A GeoParquet file with Polygon or MultiPolygon geometries
+    table = read_parquet("path/to/file.parquet")
+    layer = SolidPolygonLayer(
+        table=table,
+        get_fill_color=[255, 0, 0],
+    )
+    m = Map(layers=[layer])
+    ```
     """
 
     _layer_type = traitlets.Unicode("solid-polygon").tag(sync=True)
 
     table = PyarrowTableTrait(
         allowed_geometry_types={EXTENSION_NAME.POLYGON, EXTENSION_NAME.MULTIPOLYGON}
     )
+    """A GeoArrow table with a Polygon or MultiPolygon column.
+
+    This is the fastest way to plot data from an existing GeoArrow source, such as
+    [geoarrow-rust](https://geoarrow.github.io/geoarrow-rs/python/latest) or
+    [geoarrow-pyarrow](https://geoarrow.github.io/geoarrow-python/main/index.html).
+
+    If you have a GeoPandas `GeoDataFrame`, use
+    [`from_geopandas`][lonboard.SolidPolygonLayer.from_geopandas] instead.
+    """
 
     filled = traitlets.Bool(allow_none=True).tag(sync=True)
     """
@@ -857,17 +936,35 @@ def _validate_accessor_length(self, proposal):
 class HeatmapLayer(BaseArrowLayer):
     """The `HeatmapLayer` visualizes the spatial distribution of data.
 
-    **Example:**
+    **Example**
+
+    From GeoPandas:
 
     ```py
     import geopandas as gpd
     from lonboard import Map, HeatmapLayer
 
     # A GeoDataFrame with Point geometries
     gdf = gpd.GeoDataFrame()
-    layer = HeatmapLayer.from_geopandas(gdf,)
+    layer = HeatmapLayer.from_geopandas(gdf)
+    m = Map(layers=[layer])
+    ```
+
+    From [geoarrow-rust](https://geoarrow.github.io/geoarrow-rs/python/latest):
+
+    ```py
+    from geoarrow.rust.core import read_parquet
+    from lonboard import Map, HeatmapLayer
+
+    # Example: A GeoParquet file with Point geometries
+    table = read_parquet("path/to/file.parquet")
+    layer = HeatmapLayer(
+        table=table,
+        get_fill_color=[255, 0, 0],
+    )
     m = Map(layers=[layer])
     ```
+
     """
 
     _layer_type = traitlets.Unicode("heatmap").tag(sync=True)
@@ -880,6 +977,15 @@ def _default_rows_per_chunk(self):
         return len(self.table)
 
     table = PyarrowTableTrait(allowed_geometry_types={EXTENSION_NAME.POINT})
+    """A GeoArrow table with a Point column.
+
+    This is the fastest way to plot data from an existing GeoArrow source, such as
+    [geoarrow-rust](https://geoarrow.github.io/geoarrow-rs/python/latest) or
+    [geoarrow-pyarrow](https://geoarrow.github.io/geoarrow-python/main/index.html).
+
+    If you have a GeoPandas `GeoDataFrame`, use
+    [`from_geopandas`][lonboard.HeatmapLayer.from_geopandas] instead.
+    """
 
     radius_pixels = traitlets.Float(allow_none=True).tag(sync=True)
     """Radius of the circle in pixels, to which the weight of an object is distributed.

lonboard/_viewport.py

@@ -73,6 +73,16 @@ def bbox_to_zoom_level(bbox: Bbox) -> int:
 def compute_view(tables: List[pa.Table]):
     """Automatically computes a view state for the data passed in."""
     bbox, center = get_bbox_center(tables)
+
+    if center.x is not None and (center.x < 180 or center.x > 180):
+        msg = "Longitude of data's center is outside of WGS84 bounds.\n"
+        msg += "Is data in WGS84 projection?"
+        raise ValueError(msg)
+    if center.y is not None and (center.y < 90 or center.y > 90):
+        msg = "Latitude of data's center is outside of WGS84 bounds.\n"
+        msg += "Is data in WGS84 projection?"
+        raise ValueError(msg)
+
     # When no geo column is found, bbox will have inf values
     try:
         zoom = bbox_to_zoom_level(bbox)

lonboard/_viz.py

@@ -36,12 +36,17 @@ class GeoInterfaceProtocol(Protocol):
         def __geo_interface__(self) -> dict:
             ...
 
+    class ArrowStreamExportable(Protocol):
+        def __arrow_c_stream__(self, requested_schema: object | None = None) -> object:
+            ...
+
     VizDataInput = Union[
         gpd.GeoDataFrame,
         gpd.GeoSeries,
         pa.Table,
         NDArray[np.object_],
         shapely.geometry.base.BaseGeometry,
+        ArrowStreamExportable,
         GeoInterfaceProtocol,
         Dict[str, Any],
     ]
@@ -121,6 +126,11 @@ def create_layer_from_data_input(
     if isinstance(data, shapely.geometry.base.BaseGeometry):
         return _viz_shapely_scalar(data, **kwargs)
 
+    # Anything with __arrow_c_stream__
+    if hasattr(data, "__arrow_c_stream__"):
+        data = cast(ArrowStreamExportable, data)
+        return _viz_geoarrow_table(pa.table(data.__arrow_c_stream__()), **kwargs)
+
     # Anything with __geo_interface__
     if hasattr(data, "__geo_interface__"):
         data = cast(GeoInterfaceProtocol, data)
@@ -236,6 +246,7 @@ def _viz_geo_interface(
 def _viz_geoarrow_table(
     table: pa.Table, **kwargs
 ) -> Union[ScatterplotLayer, PathLayer, SolidPolygonLayer]:
+    # TODO: don't hard-code "geometry"
     geometry_ext_type = table.schema.field("geometry").metadata.get(
         b"ARROW:extension:name"
     )

lonboard/experimental/_layer.py

@@ -20,6 +20,15 @@ class ArcLayer(BaseLayer):
     _layer_type = traitlets.Unicode("arc").tag(sync=True)
 
     table = PyarrowTableTrait()
+    """A GeoArrow table.
+
+    This is the fastest way to plot data from an existing GeoArrow source, such as
+    [geoarrow-rust](https://geoarrow.github.io/geoarrow-rs/python/latest) or
+    [geoarrow-pyarrow](https://geoarrow.github.io/geoarrow-python/main/index.html).
+
+    If you have a GeoPandas `GeoDataFrame`, use
+    [`from_geopandas`][lonboard.ScatterplotLayer.from_geopandas] instead.
+    """
 
     great_circle = traitlets.Bool(allow_none=True).tag(sync=True)
     """If `True`, create the arc along the shortest path on the earth surface.
@@ -132,6 +141,15 @@ class TextLayer(BaseLayer):
     _layer_type = traitlets.Unicode("text").tag(sync=True)
 
     table = PyarrowTableTrait(allowed_geometry_types={EXTENSION_NAME.POINT})
+    """A GeoArrow table with a Point or MultiPoint column.
+
+    This is the fastest way to plot data from an existing GeoArrow source, such as
+    [geoarrow-rust](https://geoarrow.github.io/geoarrow-rs/python/latest) or
+    [geoarrow-pyarrow](https://geoarrow.github.io/geoarrow-python/main/index.html).
+
+    If you have a GeoPandas `GeoDataFrame`, use
+    [`from_geopandas`][lonboard.ScatterplotLayer.from_geopandas] instead.
+    """
 
     billboard = traitlets.Bool().tag(sync=True)
     """If `true`, the text always faces camera. Otherwise the text faces up (z).