# datasette-geojson-map
[](https://pypi.org/project/datasette-geojson-map/)
[](https://github.com/eyeseast/datasette-geojson-map/releases)
[](https://github.com/eyeseast/datasette-geojson-map/actions?query=workflow%3ATest)
[](https://github.com/eyeseast/datasette-geojson-map/blob/main/LICENSE)
Render a map for any query with a geometry column
## Installation
Install this plugin in the same environment as Datasette.
$ datasette install datasette-geojson-map
## Usage
Start by loading a GIS file.
For example, you might use [geojson-to-sqlite](https://pypi.org/project/geojson-to-sqlite/) or [shapefile-to-sqlite](https://pypi.org/project/shapefile-to-sqlite/) to load [neighborhood boundaries](https://bostonopendata-boston.opendata.arcgis.com/datasets/3525b0ee6e6b427f9aab5d0a1d0a1a28_0/explore) into a SQLite database.
```sh
wget -O neighborhoods.geojson https://opendata.arcgis.com/datasets/3525b0ee6e6b427f9aab5d0a1d0a1a28_0.geojson
geojson-to-sqlite boston.db neighborhoods neighborhoods.geojson
```
(The command above uses Spatialite, but that's not required.)
Start up `datasette` and navigate to the `neighborhoods` table.
```sh
datasette serve boston.db
# in another terminal tab
open http://localhost:8001/boston/neighborhoods
```
You should see a map centered on Boston with each neighborhood outlined. Clicking a boundary will bring up a popup with details on that feature.
This plugin relies on (and will install) [datasette-geojson](https://github.com/eyeseast/datasette-geojson). Any query that includes a `geometry` column will produce a map of the results. This also includes single row views.
Run the included `demo` project to see it live.
## Configuration
This project uses the same map configuration as [datasette-cluster-map](https://github.com/simonw/datasette-cluster-map). Here's how you would use [Stamen's terrain tiles](http://maps.stamen.com/terrain/#12/37.7706/-122.3782):
```yaml
plugins:
datasette-geojson-map:
tile_layer: https://stamen-tiles-{s}.a.ssl.fastly.net/terrain/{z}/{x}/{y}.{ext}
tile_layer_options:
attribution: >-
Map tiles by <a href="http://stamen.com">Stamen Design</a>,
under <a href="http://creativecommons.org/licenses/by/3.0">CC BY 3.0</a>.
Data by <a href="http://openstreetmap.org">OpenStreetMap</a>,
under <a href="http://www.openstreetmap.org/copyright">ODbL</a>.
subdomains: abcd
minZoom: 1
maxZoom: 16
ext: jpg
```
Options:
- `tile_layer`: Use a URL template that can be passed to a [Leaflet Tilelayer](https://leafletjs.com/reference-1.7.1.html#tilelayer)
- `tile_layer_options`: All options will be passed to the tile layer. See [Leaflet documentation](https://leafletjs.com/reference-1.7.1.html#tilelayer) for more on possible values here.
## Styling map features
Map features can be styled using the [simplestyle-spec](https://github.com/mapbox/simplestyle-spec). This requires setting specific fields on returned rows. Here's an example:
```sql
SELECT Name, geometry, "#ff0000" as fill, "#0000ff" as stroke, 0.2 as stroke-width, from neighborhoods
```
That will render a neighborhood map where each polygon is filled in red, outlined in blue and lines are 0.2 pixels wide.
A more useful approach would use the `CASE` statement to color features based on data:
```sql
SELECT
Name,
geometry,
CASE
Name
WHEN "Roslindale" THEN "#ff0000"
WHEN "Dorchester" THEN "#0000ff"
ELSE "#dddddd"
END fill
FROM
neighborhoods
```
This will fill Roslindale in red, Dorchester in blue and all other neighborhoods in gray.
## Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd datasette-geojson-map
python3 -mvenv venv
source venv/bin/activate
Or if you are using `pipenv`:
pipenv shell
Now install the dependencies and test dependencies:
pip install -e '.[test]'
To run the tests:
pytest
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"description": "# datasette-geojson-map\n\n[](https://pypi.org/project/datasette-geojson-map/)\n[](https://github.com/eyeseast/datasette-geojson-map/releases)\n[](https://github.com/eyeseast/datasette-geojson-map/actions?query=workflow%3ATest)\n[](https://github.com/eyeseast/datasette-geojson-map/blob/main/LICENSE)\n\nRender a map for any query with a geometry column\n\n## Installation\n\nInstall this plugin in the same environment as Datasette.\n\n $ datasette install datasette-geojson-map\n\n## Usage\n\nStart by loading a GIS file.\n\nFor example, you might use [geojson-to-sqlite](https://pypi.org/project/geojson-to-sqlite/) or [shapefile-to-sqlite](https://pypi.org/project/shapefile-to-sqlite/) to load [neighborhood boundaries](https://bostonopendata-boston.opendata.arcgis.com/datasets/3525b0ee6e6b427f9aab5d0a1d0a1a28_0/explore) into a SQLite database.\n\n```sh\nwget -O neighborhoods.geojson https://opendata.arcgis.com/datasets/3525b0ee6e6b427f9aab5d0a1d0a1a28_0.geojson\ngeojson-to-sqlite boston.db neighborhoods neighborhoods.geojson\n```\n\n(The command above uses Spatialite, but that's not required.)\n\nStart up `datasette` and navigate to the `neighborhoods` table.\n\n```sh\ndatasette serve boston.db\n\n# in another terminal tab\nopen http://localhost:8001/boston/neighborhoods\n```\n\nYou should see a map centered on Boston with each neighborhood outlined. Clicking a boundary will bring up a popup with details on that feature.\n\n\n\nThis plugin relies on (and will install) [datasette-geojson](https://github.com/eyeseast/datasette-geojson). Any query that includes a `geometry` column will produce a map of the results. This also includes single row views.\n\nRun the included `demo` project to see it live.\n\n## Configuration\n\nThis project uses the same map configuration as [datasette-cluster-map](https://github.com/simonw/datasette-cluster-map). Here's how you would use [Stamen's terrain tiles](http://maps.stamen.com/terrain/#12/37.7706/-122.3782):\n\n```yaml\nplugins:\n datasette-geojson-map:\n tile_layer: https://stamen-tiles-{s}.a.ssl.fastly.net/terrain/{z}/{x}/{y}.{ext}\n tile_layer_options:\n attribution: >-\n Map tiles by <a href=\"http://stamen.com\">Stamen Design</a>, \n under <a href=\"http://creativecommons.org/licenses/by/3.0\">CC BY 3.0</a>. \n Data by <a href=\"http://openstreetmap.org\">OpenStreetMap</a>, \n under <a href=\"http://www.openstreetmap.org/copyright\">ODbL</a>.\n subdomains: abcd\n minZoom: 1\n maxZoom: 16\n ext: jpg\n```\n\nOptions:\n\n- `tile_layer`: Use a URL template that can be passed to a [Leaflet Tilelayer](https://leafletjs.com/reference-1.7.1.html#tilelayer)\n- `tile_layer_options`: All options will be passed to the tile layer. See [Leaflet documentation](https://leafletjs.com/reference-1.7.1.html#tilelayer) for more on possible values here.\n\n## Styling map features\n\nMap features can be styled using the [simplestyle-spec](https://github.com/mapbox/simplestyle-spec). This requires setting specific fields on returned rows. Here's an example:\n\n```sql\nSELECT Name, geometry, \"#ff0000\" as fill, \"#0000ff\" as stroke, 0.2 as stroke-width, from neighborhoods\n```\n\nThat will render a neighborhood map where each polygon is filled in red, outlined in blue and lines are 0.2 pixels wide.\n\nA more useful approach would use the `CASE` statement to color features based on data:\n\n```sql\nSELECT\n Name,\n geometry,\n CASE\n Name\n WHEN \"Roslindale\" THEN \"#ff0000\"\n WHEN \"Dorchester\" THEN \"#0000ff\"\n ELSE \"#dddddd\"\n END fill\nFROM\n neighborhoods\n```\n\nThis will fill Roslindale in red, Dorchester in blue and all other neighborhoods in gray.\n\n## Development\n\nTo set up this plugin locally, first checkout the code. Then create a new virtual environment:\n\n cd datasette-geojson-map\n python3 -mvenv venv\n source venv/bin/activate\n\nOr if you are using `pipenv`:\n\n pipenv shell\n\nNow install the dependencies and test dependencies:\n\n pip install -e '.[test]'\n\nTo run the tests:\n\n pytest\n",
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