LanguageValues and typesStandard typesGeospatial
H3Cell
On this page
A cell of Uber's H3 grid of hexagons, as 15 hexadecimal digits: 8928308280fffff.
Use it to group data by area on a hexagon grid, such as demand by neighbourhood. For a grid of rectangles that shortens by prefix, use Geohash.
Shape
One value, held as text in one set form, with no parts: 8f2830828052d25.
Example
H3Cell("8928308280fffff")H3Cell(raw) checks the text, and text that isn't one breaks the format rule.
text.parse(raw, as: H3Cell) reads one from text that comes from outside. Text that isn't one at all fails malformed, such as 80f5fffffffffff, 892830828ffffff or 8928308287fffff.
Good to know
- It checks the bits inside as well as the form, so not every 15 digits pass.
==tells you whether two are the same.<andlist.sort_bydon't take it.
In JSON
A string, in a request, a response or json.write:
"8001fffffffffff""85283473fffffff""8928308280fffff"
Details
Text form, storage, how it is shown, and operations
H3Cell is in the group Geospatial, and has been in Jadpo since 0.1.0.
Text form
text.from writes one standard text form, the same form text.parse reads back: 8001fffffffffff, 85283473fffffff and 8928308280fffff.
How it is stored
It is stored in one column named for the field, of type text. 8928308280fffff is stored as '8928308280fffff'.
How it is shown to people
text.format(value, locale:) shows it to people in their locale.
With locale: Locale.en_gb:
| Value | Shown |
|---|---|
8001fffffffffff |
8001fffffffffff |
85283473fffffff |
85283473fffffff |
8928308280fffff |
8928308280fffff |
8f2830828052d25 |
8f2830828052d25 |
Operations
It also takes text.parse, text.from, text.format, json.read, json.write and ==. How every standard type behaves says how they work.
Markdown for agents: /docs/types/type-h3-cell.md.Built from Jadpo main at aee2e8f.