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https://github.com/tilezen/mapbox-vector-tile
Python package for encoding & decoding Mapbox Vector Tiles
https://github.com/tilezen/mapbox-vector-tile
Last synced: 5 days ago
JSON representation
Python package for encoding & decoding Mapbox Vector Tiles
- Host: GitHub
- URL: https://github.com/tilezen/mapbox-vector-tile
- Owner: tilezen
- License: mit
- Created: 2014-11-18T19:57:49.000Z (about 10 years ago)
- Default Branch: master
- Last Pushed: 2024-05-31T16:13:57.000Z (6 months ago)
- Last Synced: 2024-10-12T14:01:27.111Z (2 months ago)
- Language: Python
- Homepage:
- Size: 540 KB
- Stars: 244
- Watchers: 34
- Forks: 47
- Open Issues: 22
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
- awesome-vector-tiles - mapbox-vector-tile - vector-tile/issues/42) Only support V1 Tile spec and not V2, no longer maintained (Parsers & Generators)
README
# Mapbox Vector Tile
[](https://github.com/tilezen/mapbox-vector-tile/actions/workflows/ci.yml)
[](https://github.com/tilezen/mapbox-vector-tile/actions/workflows/pre-commit.yml)
[](https://coveralls.io/github/tilezen/mapbox-vector-tile?branch=master)
## Installation
mapbox-vector-tile is compatible with Python 3.9 or newer. It is listed on PyPi as `mapbox-vector-tile`. The
recommended way to install is via `pip`:
```shell
pip install mapbox-vector-tile
```
An extra dependency has been defined to install [`pyproj`](https://pyproj4.github.io/pyproj/stable/). This is useful
when changing the Coordinate Reference System when encoding or decoding tiles.
```shell
pip install mapbox-vector-tile[proj]
```
## Encoding
Encode method expects an array of layers or at least a single valid layer. A valid layer is a dictionary with the
following keys
- `name`: layer name
- `features`: an array of features. A feature is a dictionary with the following keys:
- `geometry`: representation of the feature geometry in WKT, WKB, or a shapely geometry. Coordinates are relative to the tile, scaled in the range `[0, 4096)`. See below for example code to perform the necessary transformation. _Note_ that `GeometryCollection` types are not supported, and will trigger a `ValueError`.
- `properties`: a dictionary with a few keys and their corresponding values.
The encoding operation accepts options which can be defined per layer using the `per_layer_options` argument. If
there is missing layer or missing options values in the `per_layer_options`, the options of `default_options` are
taken into account. Finally, global default values are used. See the docstring of the `encode` method for more
details about the available options and their global default values.
```python
>>> import mapbox_vector_tile
# Using WKT
>>> mapbox_vector_tile.encode([
{
"name": "water",
"features": [
{
"geometry":"POLYGON ((0 0, 0 1, 1 1, 1 0, 0 0))",
"properties":{
"uid":123,
"foo":"bar",
"cat":"flew"
}
}
]
},
{
"name": "air",
"features": [
{
"geometry":"LINESTRING(159 3877, -1570 3877)",
"properties":{
"uid":1234,
"foo":"bar",
"cat":"flew"
}
}
]
}
])
b'\x1aH\n\x05water\x12\x18\x12\x06\x00\x00\x01\x01\x02\x02\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03uid\x1a\x03foo\x1a\x03cat"\x02 {"\x05\n\x03bar"\x06\n\x04flew(\x80 x\x02\x1aD\n\x03air\x12\x15\x12\x06\x00\x00\x01\x01\x02\x02\x18\x02"\t\t\xbe\x02\xb6\x03\n\x81\x1b\x00\x1a\x03uid\x1a\x03foo\x1a\x03cat"\x03 \xd2\t"\x05\n\x03bar"\x06\n\x04flew(\x80 x\x02'
# Using WKB
>>> mapbox_vector_tile.encode([
{
"name": "water",
"features": [
{
"geometry":b"\x01\x03\x00\x00\x00\x01\x00\x00\x00\x05\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00",
"properties":{
"uid":123,
"foo":"bar",
"cat":"flew"
}
}
]
},
{
"name": "air",
"features": [
{
"geometry":b"\x01\x03\x00\x00\x00\x01\x00\x00\x00\x05\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00",
"properties":{
"uid":1234,
"foo":"bar",
"cat":"flew"
}
}
]
}
])
b'\x1aH\n\x05water\x12\x18\x12\x06\x00\x00\x01\x01\x02\x02\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03uid\x1a\x03foo\x1a\x03cat"\x02 {"\x05\n\x03bar"\x06\n\x04flew(\x80 x\x02\x1aG\n\x03air\x12\x18\x12\x06\x00\x00\x01\x01\x02\x02\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03uid\x1a\x03foo\x1a\x03cat"\x03 \xd2\t"\x05\n\x03bar"\x06\n\x04flew(\x80 x\x02'
```
### Coordinate transformations for encoding
The encoder expects geometries either:
1. In tile-relative coordinates, where the lower left corner is origin and values grow up and to the right, and the tile is 4096 pixels square. For example, `POINT(0 0)` is the lower left corner of the tile and `POINT(4096, 4096)` is the upper right corner of the tile. In this case, the library does no projection, and coordinates are encoded as-is.
2. In another coordinate system, with the tile bounds given by the `quantize_bounds` parameter. In this case, the library will scale coordinates so that the `quantize_bounds` fit within the range (0, 4096) in both `x` and `y` directions. Aside than the affine transformation, the library does no other projection.
It is possible to control whether the tile is in a "y down" coordinate system by setting the parameter `y_coord_down=True` on the call to `encode()`. The default is "y up".
It is possible to control the tile extents (by default, 4096 as used in the examples above), by setting the `extents` parameter on the call to `encode()`. The default is 4096.
If you have geometries in longitude and latitude (EPSG:4326), you can convert to tile-based coordinates by first projecting to Spherical Mercator (EPSG:3857) and then computing the pixel location within the tile. This example code uses Django's included GEOS library to do the transformation for `LineString` objects:
```python
SRID_SPHERICAL_MERCATOR = 3857
def linestring_in_tile(tile_bounds, line):
# `mapbox-vector-tile` has a hardcoded tile extent of 4096 units.
MVT_EXTENT = 4096
from django.contrib.gis.geos import LineString
# We need tile bounds in spherical mercator
assert tile_bounds.srid == SRID_SPHERICAL_MERCATOR
# And we need the line to be in a known projection so we can re-project
assert line.srid is not None
line.transform(SRID_SPHERICAL_MERCATOR)
(x0, y0, x_max, y_max) = tile_bounds.extent
x_span = x_max - x0
y_span = y_max - y0
tile_based_coords = []
for x_merc, y_merc in line:
tile_based_coord = (int((x_merc - x0) * MVT_EXTENT / x_span),
int((y_merc - y0) * MVT_EXTENT / y_span))
tile_based_coords.append(tile_based_coord)
return LineString(*tile_based_coords)
```
The tile bounds can be found with `mercantile`, so a complete usage example might look like this:
```python
from django.contrib.gis.geos import LineString, Polygon
import mercantile
import mapbox_vector_tile
SRID_LNGLAT = 4326
SRID_SPHERICAL_MERCATOR = 3857
tile_xyz = (2452, 3422, 18)
tile_bounds = Polygon.from_bbox(mercantile.bounds(*tile_xyz))
tile_bounds.srid = SRID_LNGLAT
tile_bounds.transform(SRID_SPHERICAL_MERCATOR)
lnglat_line = LineString(((-122.1, 45.1), (-122.2, 45.2)), srid=SRID_LNGLAT)
tile_line = linestring_in_tile(tile_bounds, lnglat_line)
tile_pbf = mapbox_vector_tile.encode({
"name": "my-layer",
"features": [ {
"geometry": tile_line.wkt,
"properties": { "stuff": "things" },
} ]
})
```
Note that this example may not have anything visible within the tile when rendered. It's up to you to make sure you put the right data in the tile!
Also note that the spec allows the extents to be modified, even though they are often set to 4096 by convention. `mapbox-vector-tile` assumes an extent of 4096.
```python
import mapbox_vector_tile
from pyproj import Transformer
from shapely.geometry import LineString
SRID_LNGLAT = 4326
SRID_SPHERICAL_MERCATOR = 3857
direct_transformer = Transformer.from_crs(crs_from=SRID_LNGLAT, crs_to=SRID_SPHERICAL_MERCATOR, always_xy=True)
lnglat_line = LineString(((-122.1, 45.1), (-122.2, 45.2)))
# Encode the tile
tile_pbf = mapbox_vector_tile.encode({
"name": "my-layer",
"features": [{
"geometry": lnglat_line.wkt,
"properties": {"stuff": "things"},
}]
},
default_options={"transformer": direct_transformer.transform})
# Decode the tile
reverse_transformer = Transformer.from_crs(crs_from=SRID_SPHERICAL_MERCATOR, crs_to=SRID_LNGLAT, always_xy=True)
mapbox_vector_tile.decode(tile=tile_pbf, default_options={"transformer": reverse_transformer.transform})
{
"my-layer": {
"extent": 4096,
"version": 1,
"features": [
{
"geometry": {
"type": "LineString",
"coordinates": [
[-122.10000156433787, 45.09999871982179],
[-122.20000202176608, 45.20000292038091]
]
},
"properties": {
"stuff": "things"
},
"id": 0,
"type": "Feature"
}
],
"type": "FeatureCollection"
}
}
```
### Quantization
The encoder also has options to quantize the data for you via the `quantize_bounds` option. When encoding, pass in the bounds in the form (minx, miny, maxx, maxy) and the coordinates will be scaled appropriately during encoding.
```python
mapbox_vector_tile.encode([
{
"name": "water",
"features": [
{
"geometry":"POINT(15 15)",
"properties":{
"foo":"bar",
}
}
]
}
], default_options={"quantize_bounds": (10.0, 10.0, 20.0, 20.0)})
```
In this example, the coordinate that would get encoded would be (2048, 2048)
Additionally, if the data is already in a coordinate system with y values going down, the encoder supports an
option, `y_coord_down`, that can be set to True. This will suppress flipping the y coordinate values during encoding.
### Custom extents
The encoder also supports passing in custom extents. These will be passed through to the layer in the pbf, and honored during any quantization or y coordinate flipping.
```python
mapbox_vector_tile.encode([
{
"name": "water",
"features": [
{
"geometry":"POINT(15 15)",
"properties":{
"foo":"bar",
}
}
]
}
], default_options={"quantize_bounds": (0.0, 0.0, 10.0, 10.0), "extents":50})
```
## Decoding
Decode method takes in a valid google.protobuf.message Tile and returns decoded string in the following format:
```python
{
layername: {
'extent': 'integer layer extent'
'version': 'integer'
'features': [{
'geometry': 'list of points',
'properties': 'dictionary of key/value pairs',
'id': 'unique id for the given feature within the layer '
}, ...
]
},
layername2: {
# ...
}
}
```
The decoding operation accepts options which can be defined per layer using the `per_layer_options` argument. If
there is missing layer or missing options values in the `per_layer_options`, the options of `default_options` are
taken into account. Finally, global default values are used. See the docstring of the `decode` method for more
details about the available options and their global default values.
```python
>>> import mapbox_vector_tile
>>> mapbox_vector_tile.decode(b'\x1aJ\n\x05water\x12\x1a\x08\x01\x12\x06\x00\x00\x01\x01\x02\x02\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03foo\x1a\x03uid\x1a\x03cat"\x05\n\x03bar"\x02 {"\x06\n\x04flew(\x80 x\x02\x1aY\n\x03air\x12\x1c\x08\x01\x12\x08\x00\x00\x01\x01\x02\x02\x03\x03\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03foo\x1a\x03uid\x1a\x05balls\x1a\x03cat"\x05\n\x03bar"\x03 \xd2\t"\x05\n\x03foo"\x06\n\x04flew(\x80 x\x02')
{
"water": {
"extent": 4096,
"version": 2,
"features": [
{
"geometry": {
"type": "Polygon",
"coordinates": [[[0,0],[0,1],[1,1],[1,0],[0,0]]]
},
"properties": {
"foo": "bar",
"uid": 123,
"cat": "flew"
},
"id": 1,
"type": "Feature"
}
],
"type": "FeatureCollection"
},
"air": {
"extent": 4096,
"version": 2,
"features": [
{
"geometry": {
"type": "Polygon",
"coordinates": [[[0,0],[0,1],[1,1],[1,0],[0,0]]]
},
"properties": {
"foo": "bar",
"uid": 1234,
"balls": "foo",
"cat": "flew"
},
"id": 1,
"type": "Feature"
}
],
"type": "FeatureCollection"
}
}
```
Here's how you might decode a tile from a file.
```python
>>> import mapbox_vector_tile
>>> with open('tile.mvt', 'rb') as f:
>>> data = f.read()
>>> decoded_data = mapbox_vector_tile.decode(data)
>>> with open('out.txt', 'w') as f:
>>> f.write(repr(decoded_data))
```
The `decode` function has a `geojson` option which enforces a GeoJson RFC7946 compatible result. Its default value
is `True`. To enforce the behaviour of versions <2.0.0, please use `geojson=False`.
## Use native protobuf library for performance
The c++ implementation of the underlying protobuf library is more performant than the pure python one. Depending on your operating system, you might need to [compile the C++ library](https://github.com/google/protobuf/tree/master/python#c-implementation) or install it.
Since May 6, 2022, the Python `profobuf` library is based on the udp library and thus, the generated Python code
requires `protoc` 3.19.0 or newer. Cf. [here](https://developers.google.com/protocol-buffers/docs/news/2022-05-06). On
debian Bullseye, the version of `protoc` available in the package registry is too old. Please install it from [protobuf
+GitHub repository](https://github.com/protocolbuffers/protobuf/releases).
To compile the `proto` file, you have to enable two environnement variables BEFORE running your python program :
$ sudo apt-get install libprotoc9 libprotobuf9 protobuf-compiler python-protobuf
Then, you'll have to enable two environnement variable BEFORE runing your python program :
$ export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=cpp
$ export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION_VERSION=2
and then:
$ protoc -I=mapbox_vector_tile/Mapbox/ --python_out=mapbox_vector_tile/Mapbox/ mapbox_vector_tile/Mapbox/vector_tile.proto
## Changelog
Click [here](https://github.com/tilezen/mapbox-vector-tile/blob/master/CHANGELOG.md) to see what changed over time in various versions.