Simple .mbtiles processor for python. Built with the QA Tiles in mind.
Based on the map/reduce/end structure in @mapbox/tilereduce. Tiles are read from the mbtiles container and passed to a worker pool as asynchronous jobs that can run concurrently.
The main function is tilereduce(options, map_function=map_function, callback=callback, error_callback=error_callback, done=done):
options
A dictionary with the following keys:
- source: a path to an mbtiles
- bbox: a bounding box limiting the tiles to read
- zoom: the zoom level to read from
- args: an optional dictionary which is passed to each worker
map_function: (x, y, z, data) -> any
A function that run on each tile asynchronously. x, y and z specify the tile coordinates, and data is the tile contents. The mapfunc takes the tile data and should return a value.
callback: (any) -> void
A function called with the return value of map_function.
error_callback: (any) -> void
A function called with an exception instance if one occurs in the worker.
done: () -> void
A function called at the end of all jobs.
You can install tilepie from PyPi ✨
pip install tilepiefrom tilepie import tilereduce
import mapbox_vector_tile
total_count = 0
## Define a mapper function that operates on each tile
def mapper(x, y, z, data):
if data is None:
return 0
tile = mapbox_vector_tile.decode(data)
count = 0
if (tile['osm']['features']):
count = len(tile['osm']['features'])
return count
## Define a callback when each tile finishes
def on_tile_done(count):
global total_count
total_count += count
## Define a function that runs at the end of all jobs
def on_end():
global total_count
print total_count
## Log errors
def on_error(e):
print(e)
# Call tilereduce
# This is using lebanon.mbtiles from the QA Tiles
tilereduce(
{
'zoom': 12,
'source': '~/data/lebanon.mbtiles',
'bbox': (35.1260526873, 33.0890400254, 36.6117501157, 34.6449140488)
},
map_function=mapper,
callback=on_tile_done,
error_callback=on_error,
done=on_end
)MIT © Marc Farra unless otherwise specified