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Opinionated OSM-theme road/edge map styling for folium, lonboard & the web (data-driven palettes, casing, themes)

Project description

roadstyle

Tests License: MIT Python 3.10+

Turn a GeoDataFrame of road edges into a styled, interactive, self-contained map — proper road cartography (the casing + fill "geometry sandwich", per-zoom widths, street names, one-way arrows, tunnel/bridge grade separation, optional 3D bridge decks) in one offline HTML file, with a scriptable JavaScript API.

3D bridges over Södermalm

Contents: Features · Installation · Quickstart · The studio (no code) · Rendering parameters · Data contract · Recipes · JavaScript API · Settings · Command line · Documentation

Features

  • Real road cartography — casing + fill sandwich, importance-ordered junctions, per-zoom widths (openstreetmap-carto model), two-way lanes, curved street names, one-way arrows.
  • Grade separation — tunnels faded + dashed underneath, bridges on decks on top (stacked structures ordered by their OSM layer), and an optional 3D view with extruded bridge decks.
  • One offline file — MapLibre and the data are bundled into the saved HTML; it opens by double-click, no server, no internet (with the blank basemap: zero network requests).
  • Data-driven styling — colour/width by any column (categorical or numeric ramps), per-edge colour tables, and multiple colour layers switchable client-side.
  • Big networkstiles=True packs the roads as an embedded vector tileset (PMTiles): ~10⁵-edge maps open in seconds and stay responsive, still one offline file.
  • A JavaScript API — every control is scriptable (rsQuery, rsFilter, rsColor, rsSelect, …) with rs:* events, so the saved map can power your own dashboard.
  • Three backendsweb (MapLibre, the flagship), folium (Leaflet, legends), lonboard (GPU, millions of edges).

Installation

Python ≥ 3.10. Two ways in, depending on who you are:

Using the library (pip, no clone)

pip install roadstyle                 # the library — geopandas, shapely, folium, branca come along
pip install "roadstyle[studio]"       # + the no-code Streamlit workbench: `roadstyle studio`

Every optional feature is an extra — combine what you need (e.g. pip install "roadstyle[numeric,tiles]"), or take everything at once with pip install "roadstyle[all]":

Extra Enables Pulls in
studio roadstyle studio — the interactive Streamlit workbench streamlit
numeric continuous colour ramps + classification (color_by on numbers) mapclassify, matplotlib
tiles tiles=True — embedded vector tiles for big networks mapbox-vector-tile, pmtiles
lonboard the GPU backend for very large edge sets lonboard
duckdb from_duckdb() — read edges straight from DuckDB duckdb
arrow read edges from a pyarrow Table pyarrow
basemaps any XYZ provider from the xyzservices registry xyzservices
all every extra above in one go all of the above

To try the latest unreleased state — still no clone, extras combine the same way: pip install "roadstyle[all] @ git+https://github.com/Khoshkhah/roadstyle.git" (or [studio], …; bare roadstyle @ git+… is core only)

Developing on it (clone + editable install)

git clone https://github.com/Khoshkhah/roadstyle.git && cd roadstyle
pip install -e ".[dev]"              # editable — every extra (incl. the studio) + pytest/ruff/mypy
# or with conda: conda env create -f environment.yml && conda activate roadstyle && pip install -e ".[dev]"
pytest                               # the full suite; browser tests need `pip install playwright`

From a checkout the studio runs against your working tree (roadstyle studio — streamlit comes with [dev]) and uses the repo's sample data in ui/studio/samples/ directly.

Uninstall: pip uninstall roadstyle. Your personal settings overrides (~/.config/roadstyle/roadstyle.json, project-local roadstyle.json) are your files — pip leaves them in place; delete them yourself if you want a clean slate.

Quickstart

import geopandas as gpd
import roadstyle as rs

edges = gpd.read_file("edges.gpkg")          # any CRS; needs a `highway` class column

rs.render_edges(edges).save("map.html")                          # done — open map.html

That one line gives you the full treatment: per-zoom widths, two-way lanes, arrows, street names, hover/select with popups, a base-map switcher, a class filter panel, grade separation. Common variations:

rs.render_edges(edges, basemap="dark_matter", view_3d=True).save("map3d.html")   # dark + 3D bridges
rs.render_edges(edges, palette="carto", basemap="positron").save("carto.html")   # the classic OSM look
rs.render_edges(edges, include=["motorway", "trunk", "primary"]).save("major.html")
rs.render_edges(edges, color_by="aadt", cmap="viridis").save("traffic.html")     # colour by your data
rs.render_edges(edges, tiles=True).save("big.html")                              # 10⁵-edge networks

rs.render_dashboard(edges).save("dashboard.html")   # a full query-sidebar dashboard page, one call
rs.render_report(edges).save("report.html")         # a stats-sidebar report page

Palettes: highsat (high-saturation, maximum legibility), carto (the muted openstreetmap-carto look), mono (grayscale — quiet backdrop for data overlays).

The studio — the library behind knobs, no code

The gentlest way in. The studio is a small Streamlit app that ships with the package — install the studio extra and run it (the sample networks, ~12 MB, download on first run):

pip install "roadstyle[studio]"
roadstyle studio                 # add streamlit args as usual: roadstyle studio --server.port 8502

roadstyle studio

Three pages, same idea — every knob updates the live map and the exact Python code that reproduces it:

  • Map — upload a road file (.gpkg / .geojson) or pick a bundled Södermalm sample, then click through palette, base map, 3D, vector tiles, colour-by-data, class filter, minzoom, labels/arrows, popups and overlays. Copy the generated render_edges(...) code out, or download the self-contained map.html.
  • Dashboard — the same knobs, but the product is a sidebar dashboard (query box, verb buttons, results table, detail panel) built on the JavaScript API. Preview it live, download dashboard.html. The generated code is a one-liner: rs.render_dashboard(edges, ...).
  • Report — a stats sidebar instead (KPI cards, the colour-by legend, a checkbox filter, search, a selected-road read-out). Generated as rs.render_report(edges, ...).

Both sidebar pages are shipped in the library — rs.render_dashboard(edges).save("dashboard.html") and rs.render_report(edges) build them in one call, no repo checkout needed (see below).

Rendering parameters

The keywords of rs.render_edges(gdf, ...) — the ones you'll actually reach for. Full reference with every type and edge case: docs/parameters.md.

Core

Parameter Default What it does
backend "web" "web" (MapLibre, the flagship) / "folium" (Leaflet + legends) / "lonboard" (GPU)
palette "highsat" Class colour palette: "highsat" / "carto" / "mono", or your own
basemap "voyager" Background map: voyager, positron, dark_matter, osm, satellite, blank, blank_dark
basemaps all built-ins The set offered in the in-map base-layer dropdown
name "roadstyle" Page / layer title
settings None Per-call settings override (dict or path) — see Settings

Filtering

Parameter Default What it does
include / exclude None Keep / drop road classes (include=["motorway","primary"]); _link variants follow automatically
filter_col None Let the filter panel list a different column than the one that drives styling
minzoom None (off) Hide minor classes when zoomed out: True for the built-in table, or a {class: zoom} dict. Applies to the vector tiles too

Colour by data

Parameter Default What it does
color_by None Colour by a column instead of road class
colors None Categorical {value: "#hex"} map, or "self" to use the column's value as the literal colour
cmap / vmin / vmax None Numeric colour ramp ("viridis", …) and its value range
width_by None (min_px, max_px) — scale line width with the numeric value
color_table None Per-edge colours: {edge_id: "#hex"} dict / Series / DataFrame (gray fallback, class widths kept)
color_options None Bake several colour layers + a client-side Colour by dropdown: {"Traffic": {"color_by": "aadt", "cmap": "viridis"}, ...}

Camera & 3D (web backend)

Parameter Default What it does
view_3d False Tilted camera + extruded, ramped, cased 3D bridge decks + an on-map 2D/3D toggle
pitch / bearing settings Starting camera tilt / rotation

UI toggles (web backend)

Parameter Default What it does
arrows True One-way direction chevrons
labels True Curved street-name labels
filter_control True The collapsible road-class filter panel (doubles as a colour legend)
basemap_switcher True The base-layer dropdown
road_popup True Click popup: True (curated fields) / [fields] / "all" / "panel" (docked read-out) / False
tooltip None (off) Hover tooltip fields (list of columns)
hover_color / select_color violet Highlight colours for hovered / selected roads

Extra content (web backend)

Parameter Default What it does
overlays None Your own layers (Overlay(...)) — zones under the roads, POIs on top, clickable, with a Layers toggle
boundary None Dashed outline of the clip area, drawn on top
selected None Pre-highlighted edges (folium backend)

Output & scale

Parameter Default What it does
compress True Gzip the inlined data (3–4× smaller files; compress=False for plain JSON)
tiles False Embedded-PMTiles vector tileset — for ~10⁵-edge networks (needs the tiles extra)

Column mapping

Parameter Default What it does
highway_col "highway" The road-class column that drives styling
tunnel_col / bridge_col / layer_col "tunnel" / "bridge" / "layer" Grade-separation columns

Everything stylistic — the actual colours, widths, casing, label/arrow cosmetics, camera defaults, bridge-deck geometry — is deliberately not a keyword but a setting.

Data contract — which column powers what

Only two things are required; every other column lights up a feature when present and is skipped when absent:

Column Values Powers
geometry LineString (any CRS) required — the edges themselves
highway OSM class (motorwayservice) required — colour, width, casing, draw order
name text street-name labels + the popup title
oneway True/False / yes/no direction arrows (without it, one-way is inferred from reverse-geometry twins)
bridge / tunnel truthy grade separation: tunnels below, bridges on decks above, 3D decks in view_3d
layer int stacking order of bridges/tunnels; negative → below ground even without tunnel
edge_id id (64-bit safe) popups + click-to-copy; ids > 2⁵³ are kept exact as strings
anything else anything shown in the click popup / hover tooltip, queryable from JavaScript

Networks exported by duckOSM (duckosm export-gis) carry exactly this column set.

Recipes

Each of these is one call — details behind the links.

# colour each edge from your own table (cluster / route / metric per edge)
rs.render_edges(edges, color_table={"4897…": "#e6194B", "5193…": "#3cb44b"})

# several colour layers in one map, switchable client-side (no re-render)
rs.render_edges(edges, palette="mono", color_options={
    "Road class": {},
    "Traffic":    {"color_by": "aadt", "cmap": "viridis"},
    "Speed":      {"color_by": "maxspeed_kmh", "cmap": "magma"}})

# your own layers under/over the roads
rs.render_edges(edges, overlays=[
    rs.Overlay(zones,   placement="under", color="#2d6cdf", opacity=0.25, label="Zones",
               popup=["taz_id", "population"]),
    rs.Overlay(sensors, placement="over",  color="#ffd166", radius=6, label="Sensors")])

# your own tile server as a base map
rs.register_basemap(rs.Basemap(key="lm", label="Lantmäteriet",
                               url="https://tiles.example.se/{z}/{x}/{y}.png", attr="© LM"))

# a static PNG for a paper, through a real headless browser (pip install playwright)
rs.snapshot(rs.render_edges(edges, view_3d=True), "fig.png",
            center=(18.076, 59.303), zoom=16, pitch=60)

# roads straight from DuckDB
edges = rs.from_duckdb(con, "SELECT edge_id, highway, name, ST_AsWKB(geom) AS geometry FROM edges")

More: the gallery — one screenshot + recipe per look.

Drive the map from JavaScript

Every in-map control is a thin UI over a window.rs* function, and the baked features are a queryable table — so a saved map can power your own dashboard with plain HTML:

const ids = rsQuery(p => p.lanes >= 2 && p.maxspeed_kmh > 30);   // WHERE clause → id set
rsFilter(ids);                 // show only these         rsFilter(null) resets
rsColor(ids, "#ff00aa");       // paint them one colour   rsColor(null) resets
rsHighlight(ids);              // selection glow
rsGetProps(ids);               // the rows behind the ids — table-ready
rsFocus(ids);                  // fly the camera to fit them
rsSelect(id);                  // select + popup, like a click

rsSetBasemap("dark_matter");   rsSetClasses(["primary","secondary"]);
rsSetColorField("Traffic");    rsSetOverlay("Zones", false);      rsSetView3D(true);

document.addEventListener("rs:select", e => showSidebar(e.detail.properties));

Everything works the same on overlays (pass the overlay's label as the last argument) and on tiled maps. Full API table: docs/web-backend.md.

Two ready-made sidebars ship inside the package, built entirely on this API — one call each:

rs.render_dashboard(edges).save("dashboard.html")   # query box, colour-by, class filter + legend, table
rs.render_report(edges).save("report.html")          # KPI cards, colour-by legend, filter, search

color_options={...} populates their Colour by picker; every render_edges keyword passes through. To reshape one, rs.sidebar_html("dashboard") (or "report") returns the HTML/CSS/JS fragment — edit it and re-inject before </body>. The same fragments live in ui/ with a build.py per template.

Settings — one defaults file, your overrides on top

EVERY styling default — palettes, opacities, casing, the width/draw-order model, base map, camera, labels, arrows, bridge decks — ships in one file, roadstyle/data/defaults.json. You never edit it; you state only what changes, at any of five levels (later wins):

  1. ~/.config/roadstyle/roadstyle.json — personal defaults
  2. ./roadstyle.json — project-local
  3. $ROADSTYLE_CONFIG=/path/to/file.json — per run
  4. rs.use_settings({...}) — from code, applies immediately
  5. render_edges(..., settings={...}) — this one call only
{
  "palettes":  { "highsat": { "service": { "fill": "#E0E0E0" } } },   // retint one class
  "config":    { "basemap": "dark_matter", "labels": { "color": "#8899aa" } },
  "roads":     { "z_order": { "service": 5 }, "width": { "secondary": { "18": 14 } } }
}

Details: docs/palettes.md.

Command line

No Python required — point the roadstyle command at any road file:

roadstyle edges.gpkg -o map.html --basemap dark_matter        # styled interactive map
roadstyle edges.gpkg --view-3d --tiles                        # 3D + embedded vector tiles
roadstyle edges.gpkg --include motorway trunk primary
roadstyle edges.gpkg --color-by aadt --cmap viridis --width-by 1 6
roadstyle edges.gpkg -f spec -o map_data.json                 # JSON spec for your own frontend

roadstyle studio                                              # the interactive workbench (needs the studio extra)
roadstyle studio --server.port 8502                           # any streamlit flag is forwarded

Every flag mirrors a render_edges keyword; roadstyle --help lists them all. roadstyle studio launches the Streamlit workbench (install it with pip install "roadstyle[studio]") and passes any extra arguments straight to streamlit run.

Documentation

Gallery one screenshot + recipe per look
Parameter reference every keyword, type, and default
Web backend grade separation, 3D, vector tiles, colour options, the full JS API
Choosing an engine web vs folium vs lonboard, data-size guidance
Palettes & settings the built-in palettes and the override system
When to use roadstyle vs .explore(), prettymaps, kepler.gl, raw MapLibre
Notebooks a runnable manual, one topic per notebook
UI templates the dashboard / report scaffolding + the studio's sample data (the studio itself ships in the package — roadstyle studio)

Full MkDocs site: khoshkhah.github.io/roadstyle (mkdocs serve locally).

License

MIT. Base-map tiles are third-party services (CARTO, OSM, Esri) with their own attribution and terms; the styling spec is transcribed from the cartographic design docs in the osm-traffic-enrichment project.

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