Opinionated OSM-theme road/edge map styling for folium, lonboard & the web (data-driven palettes, casing, themes)
Project description
roadstyle
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.
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
blankbasemap: 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 networks —
tiles=Truepacks 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, …) withrs:*events, so the saved map can power your own dashboard. - Three backends —
web(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
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 generatedrender_edges(...)code out, or download the self-containedmap.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 (motorway…service) |
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):
~/.config/roadstyle/roadstyle.json— personal defaults./roadstyle.json— project-local$ROADSTYLE_CONFIG=/path/to/file.json— per runrs.use_settings({...})— from code, applies immediatelyrender_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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