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Parent(s):
326ffdb
Update app.py
Browse files
app.py
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import numpy as np
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import panel as pn
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""
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show_name=False,
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),
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self.text
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)
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def __panel__(self):
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return self._layout
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@param.depends("slider", "select")
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def text(self):
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if self.select:
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select = self.select
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else:
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select = 0
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return f"{select} + {self.slider} = {select + self.slider}"
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@pn.depends("run_blocking_task", watch=True)
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async def _run_blocking_tasks(self, num_tasks=10):
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"""Runs background tasks num_tasks times"""
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num_tasks = 20
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progress.num_tasks = num_tasks
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for _ in range(num_tasks):
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future = executor.submit(self._run_blocking_task)
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result = await wrap_future(future)
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self._update(result)
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@progress.increment()
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def _update(self, number):
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self.result += number
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@staticmethod
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def _run_blocking_task():
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time.sleep(np.random.randint(1, 2))
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return 5
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if pn.state.served:
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pn.extension()
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component = AsyncComponent()
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pn.template.FastListTemplate(
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site="Awesome Panel", site_url="https://awesome-panel.org", title="Async Tasks", main=[component], main_layout=None, main_max_width="400px"
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).servable()
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"""
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Checkout https://awesome-panel.org/resources/lonboard_dashboard/
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"""
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# pip install panel colorcet ipywidgets_bokeh geopandas palettable lonboard
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import colorcet as cc
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import geopandas as gpd
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from lonboard import Map, PathLayer
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from lonboard.colormap import apply_continuous_cmap
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from palettable.palette import Palette
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import panel as pn
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url = "https://naciscdn.org/naturalearth/10m/cultural/ne_10m_roads_north_america.zip"
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path = "ne_10m_roads_north_america.zip"
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try:
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gdf = pn.state.as_cached(
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"ne_10m_roads_north_america", gpd.read_file, filename=path, engine="pyogrio"
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)
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except:
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gdf = pn.state.as_cached(
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"ne_10m_roads_north_america", gpd.read_file, filename=url, engine="pyogrio"
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)
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state_options = sorted(state for state in gdf["state"].unique() if state)
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def to_rgb(hex: str) -> list:
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h = hex.strip("#")
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return list(int(h[i : i + 2], 16) for i in (0, 2, 4))
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def to_palette(cmap) -> Palette:
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"""Returns the ColorCet colormap as a palettable Palette"""
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colors = [to_rgb(item) for item in cmap]
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return Palette(name="colorcet", map_type="colorcet", colors=colors)
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def create_map(state="California", cmap=cc.fire, alpha=0.8):
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palette = to_palette(cmap)
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data = gdf[gdf["state"] == state]
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layer = PathLayer.from_geopandas(data, width_min_pixels=0.8)
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normalized_scale_rank = (data["scalerank"] - 3) / 9
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layer.get_color = apply_continuous_cmap(normalized_scale_rank, palette, alpha=alpha)
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map_ = Map(layers=[layer], _height=650)
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return map_
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description = """# lonboard
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A Python library for **fast, interactive geospatial vector data visualization** in Jupyter (and Panel).
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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."""
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# THE PANEL APP
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pn.extension("ipywidgets")
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state = pn.widgets.Select(
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value="California",
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options=state_options,
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width=150,
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name="State",
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sizing_mode="stretch_width",
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)
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cmap = pn.widgets.ColorMap(
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value=cc.fire,
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options=cc.palette,
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ncols=3,
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swatch_width=100,
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name="cmap by Colorcet",
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sizing_mode="stretch_width",
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)
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alpha = pn.widgets.FloatSlider(
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value=0.8, start=0, end=1, name="Alpha", min_width=100, sizing_mode="stretch_width"
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)
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logo = pn.pane.Image(
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"https://github.com/developmentseed/lonboard/raw/main/assets/dalle-lonboard.jpg"
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)
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def title(state):
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return f"# North America Roads: {state}"
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settings = pn.Column(state, cmap, alpha)
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description = pn.Column(pn.pane.Markdown(description, margin=5), logo)
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component = pn.Column(
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pn.bind(title, state=state),
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pn.panel(
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pn.bind(create_map, state=state, cmap=cmap, alpha=alpha.param.value_throttled),
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sizing_mode="stretch_both",
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),
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sizing_mode="stretch_both",
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)
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pn.template.FastListTemplate(
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logo="https://panel.holoviz.org/_static/logo_horizontal_dark_theme.png",
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title="Works with LonBoard",
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main=[component],
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sidebar=[description, settings],
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).servable()
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