Panel

Panel is a tool to build interactive web applications and dashboards using Python code.

Panel has been reported to work with Lonboard. However, it appears that Panel does not support reactive updates in the same way that Shiny does, so the map will necessarily be recreated from scratch on every update.

Example

This example was written by @MarcSkovMadsen in issue #262.

"""Panel data app based on https://developmentseed.org/lonboard/latest/examples/north-america-roads/"""
# pip install panel colorcet ipywidgets_bokeh geopandas palettable lonboard
import colorcet as cc
import geopandas as gpd

from lonboard import Map, PathLayer
from lonboard.colormap import apply_continuous_cmap
from palettable.palette import Palette

import panel as pn

url = "https://naciscdn.org/naturalearth/10m/cultural/ne_10m_roads_north_america.zip"
path = "ne_10m_roads_north_america.zip"

try:
    gdf = pn.state.as_cached(
        "ne_10m_roads_north_america", gpd.read_file, filename=path, engine="pyogrio"
    )
except:
    gdf = pn.state.as_cached(
        "ne_10m_roads_north_america", gpd.read_file, filename=url, engine="pyogrio"
    )

state_options = sorted(state for state in gdf["state"].unique() if state)


def to_rgb(hex: str) -> list:
    h = hex.strip("#")
    return list(int(h[i : i + 2], 16) for i in (0, 2, 4))


def to_palette(cmap) -> Palette:
    """Returns the ColorCet colormap as a palettable Palette"""
    colors = [to_rgb(item) for item in cmap]
    return Palette(name="colorcet", map_type="colorcet", colors=colors)


def create_map(state="California", cmap=cc.fire, alpha=0.8):
    palette = to_palette(cmap)
    data = gdf[gdf["state"] == state]
    layer = PathLayer.from_geopandas(data, width_min_pixels=0.8)
    normalized_scale_rank = (data["scalerank"] - 3) / 9
    layer.get_color = apply_continuous_cmap(normalized_scale_rank, palette, alpha=alpha)
    map_ = Map(layer, _height=650)
    return map_


description = """# lonboard

A Python library for **fast, interactive geospatial vector data visualization** in Jupyter (and Panel).

By utilizing new technologies like `GeoArrow` and `GeoParquet` in conjunction with GPU-based map rendering, lonboard aims to enable visualizing large geospatial datasets interactively through a simple interface."""


# THE PANEL APP
pn.extension("ipywidgets")
state = pn.widgets.Select(
    value="California",
    options=state_options,
    width=150,
    name="State",
    sizing_mode="stretch_width",
)
cmap = pn.widgets.ColorMap(
    value=cc.fire,
    options=cc.palette,
    ncols=3,
    swatch_width=100,
    name="cmap by Colorcet",
    sizing_mode="stretch_width",
)
alpha = pn.widgets.FloatSlider(
    value=0.8, start=0, end=1, name="Alpha", min_width=100, sizing_mode="stretch_width"
)
logo = pn.pane.Image(
    "https://github.com/developmentseed/lonboard/raw/main/assets/dalle-lonboard.jpg"
)
def title(state):
    return f"# North America Roads: {state}"

settings = pn.Column(state, cmap, alpha)
description = pn.Column(pn.pane.Markdown(description, margin=5), logo)
component = pn.Column(
    pn.bind(title, state=state),
    pn.panel(
        pn.bind(create_map, state=state, cmap=cmap, alpha=alpha.param.value_throttled),
        sizing_mode="stretch_both",
    ),
    sizing_mode="stretch_both",
)
pn.template.FastListTemplate(
    logo="https://panel.holoviz.org/_static/logo_horizontal_dark_theme.png",
    title="Works with LonBoard",
    main=[component],
    sidebar=[description, settings],
).servable()