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H3 Bound Cells

Convert geographic polygons into multi-resolution H3 cell coverings, with fast point-in-region lookups.

Rust core is built on h3o and exposed to Python via PyO3 / Maturin.

Overview

BoundCells is a pair of dicts keyed by H3 resolution:

  • area — cells whose interior lies inside the polygon.
    • The area layer is compacted: wherever all 7 children at a resolution are present, they collapse up to the parent.
    • A single covering naturally spans multiple resolutions (chunky cells in the interior, smaller cells near the edge).
  • border — cells that overlap the polygon boundary, materialised at every coarser resolution down to min_cell_resolution.

The border layer is what makes containment lookups cheap. To check whether an arbitrary cell falls inside the region, cell_in_bound_cells first tests the cell against the border layer at its own resolution, then walks its ancestors from fine to coarse against the compacted area cells, returning true on the first hit — no need to materialise every leaf cell of the polygon. A query cell is "inside" if it — or one of its H3 ancestors computed via cell.parent() — is an area cell.

BoundCells

Install

The package is built locally with maturin:

uv sync --dev
uv run maturin develop --release

The dev dependency group (declared in pyproject.toml) also pulls in flask, h3, polars, and pytest, used by the visualisation server, the tests, and the optional Polars integration below.

Usage

import h3
from h3_bound_cells import polygon_to_bound_cells, cell_in_bound_cells, BoundCells

# Rectangle around central London. (lat, lng) pairs; the ring need not be closed.
exterior = [
    (51.50, -0.13),
    (51.52, -0.13),
    (51.52, -0.08),
    (51.50, -0.08),
]

bc = polygon_to_bound_cells(exterior, start_res=9, min_cell_resolution=4)

print(bc)
# BoundCells(area_resolutions=[...], border_resolutions=[...])

for res, cells in bc.area.items():
    print(f"area   res {res}: {len(cells)} cells")
for res, cells in bc.border.items():
    print(f"border res {res}: {len(cells)} cells")

# Point-in-region check: Trafalgar Square at H3 resolution 11.
cell = h3.latlng_to_cell(51.5074, -0.1278, 11)
assert cell_in_bound_cells(cell, bc)

# JSON-friendly round trip
restored = BoundCells.from_dict(bc.to_dict())

API

  • polygon_to_bound_cells(exterior, holes=None, start_res=None, min_cell_resolution=None) -> BoundCells
    • exterior, holes — lists of (lat, lng) tuples.
    • start_res — H3 resolution to tile at. When omitted, it is auto-picked from the polygon's planar area.
    • min_cell_resolution — floor for the border layer (default 4).
  • cell_in_bound_cells(cell: str, bound_cells: BoundCells) -> bool — membership test by H3 cell id.
  • BoundCells — frozen class:
    • .area, .border — dict[str, list[str]] keyed by stringified resolution.
    • .to_dict() / BoundCells.from_dict(d) — JSON-friendly round trip.
    • BoundCells.merge([bc1, bc2, ...]) — union of multiple results.
    • .cells_at_resolution(res) — flatten/expand the covering to a single H3 resolution (parents map up, coarser cells expand to their children).

Polars integration (optional)

Filter a Polars DataFrame/LazyFrame down to the rows whose H3 cell falls inside a covering.

Install the optional polars extra:

pip install h3_bound_cells[polars]

Importing h3_bound_cells registers a bound_cells namespace on Polars expressions (only registered when polars is installed):

import polars as pl
import h3_bound_cells                       # registers the bound_cells namespace

bc = h3_bound_cells.polygon_to_bound_cells(exterior, start_res=9)

df = pl.DataFrame({"cell": [...]})          # H3 cells as hex strings or u64 ints

# Filter to rows inside the covering:
df.filter(pl.col("cell").bound_cells.is_in(bc))

# Or use the boolean result as a column:
df.with_columns(inside=pl.col("cell").bound_cells.is_in(bc))
  • pl.col(cell_column).bound_cells.is_in(bound_cells) — a boolean expression, true where the cell lies inside bound_cells.
  • Use it anywhere an expression is accepted (filter, select, with_columns, boolean combinations, …).
  • Works with both eager and lazy frames. Cells may be hex strings or u64 ints; a null cell maps to false (dropped by filter).

Dev server

A small Flask + MapLibre app for drawing polygons and visualising the output:

just serve
# or:
uv run --dev dev/server.py

Then open http://127.0.0.1:5050/. Draw a polygon, hit Compute Bound Cells, and the area and border layers render colour-coded by resolution. Renders are capped at 50,000 cells; reduce start_res or shrink the polygon if you trip the limit. The page also accepts a pre-computed {"area": {...}, "border": {...}} blob via the Render Cells panel for offline inspection of saved output.

Release files for h3_bound_cells 0.1.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for h3_bound_cells 0.1.2
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h3_bound_cells-0.1.2.tar.gz 5.4 MB Details

Built distributions (wheels)

Table of built distributions (wheels) for h3_bound_cells 0.1.2
File
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h3_bound_cells-0.1.2-cp310-cp310-musllinux_1_2_x86_64.whl CPython 3.10 CPython 3.10 Linux musl 1.2+ x86-64 Details
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h3_bound_cells-0.1.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl CPython 3.8 CPython 3.8 Linux glibc 2.17+ ARM64 Details

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0.5.3

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