utiles = utils + tiles
A mostly drop-in replacement for mercantile written w/ rust, plus several other util(e)ities.
pip install utilesI use mercantile regularly and wished it were a bit more ergonomic, had type annotations, and was faster, but overall it's a great library.
This was an excuse to learn some more rust as well as pyo3.
Do I/you REALLY need a rust-port of mercantile?
I don't know, decide for yourself. utiles is certainly faster than mercantile for some things (see benchmarks below)
Is it really a drop in replacement for mercantile?
Not quite, but it's close. utiles doesn't throw the same exceptions as mercantile, instead it throws ValueError's and
TypeError's.
There might be other differences, but I have been using it instead of mercantile for a bit now and it works pretty decent, tho I am open to suggestions!
import utiles as ut
ut.bounds(1, 1, 1)
# Out: LngLatBbox(west=0, south=-85.0511287798066, east=180, north=0)
t = ut.Tile(1, 2, 3)
x, y, z = t
(x, y, z)
# Out: (1, 2, 3)
list(ut.tiles(*ut.bounds(1, 1, 1), 3)) # tiles is an ultra fast generator
# Out: [Tile(x=4, y=4, z=3), Tile(x=4, y=5, z=3), Tile(x=4, y=6, z=3), Tile(x=4, y=7, z=3), Tile(x=5, y=4, z=3), Tile(x=5, y=5, z=3), Tile(x=5, y=6, z=3), Tile(x=5, y=7, z=3), Tile(x=6, y=4, z=3), Tile(x=6, y=5, z=3), Tile(x=6, y=6, z=3), Tile(x=6, y=7, z=3), Tile(x=7, y=4, z=3), Tile(x=7, y=5, z=3), Tile(x=7, y=6, z=3), Tile(x=7, y=7, z=3)]
t
# Out: Tile(x=1, y=2, z=3)
t.parent()
# Out: Tile(x=0, y=1, z=2)
t.children()
# Out:
# [Tile(x=2, y=4, z=4),
# Tile(x=3, y=4, z=4),
# Tile(x=3, y=5, z=4),
# Tile(x=2, y=5, z=4)]
t.bounds()
# Out: LngLatBbox(west=-135, south=40.97989806962013, east=-90, north=66.51326044311186)
t.ul()
# Out: LngLat(lng=-135, lat=66.51326044311186)
t.asdict()
# Out: {'x': 1, 'z': 3, 'y': 2}
t.center()
# Out: LngLat(lng=-112.5, lat=53.74657925636599)
~t # tms flip
# Out: Tile(x=1, y=5, z=3)
t.valid()
# Out: True
ut.Tile(1000, 1231234124, 2).valid()
# Out: False
t.pmtileid()
# Out: 34
from_pmtile_id = ut.Tile.from_pmtileid(34)
ut.Tile.from_pmtileid(34)
# Out: Tile(x=1, y=2, z=3)
t.json_arr()
# Out: '[1, 2, 3]'
t.json_obj()
# Out: '{"x":1,"y":2,"z":3}'
t.fmt_zxy()
# Out: '3/1/2'
t.fmt_zxy_ext('.png')
# Out: '3/1/2..png'
t.fmt_zxy_ext('png')
# Out: '3/1/2.png'
t == (1, 2, 3)
# Out: True
t == (1, 2, 2234234)
# Out: False
t == (1, 2, 22)
# Out: False---------------------------------------------------------------------------------------------------- benchmark 'quadkey': 12 tests -----------------------------------------------------------------------------------------------------
Name (time in ns) Min Max Mean StdDev Median IQR Outliers OPS (Kops/s) Rounds Iterations
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_quadkey_bench[utiles-(0, 0, 0)] 199.9942 (1.0) 47,100.0021 (8.78) 284.7909 (1.0) 315.1058 (6.70) 299.9950 (1.06) 100.0008 (>1000.0) 966;1164 3,511.3476 (1.0) 38911 1
test_quadkey_bench[utiles-(1, 1, 1)] 252.6316 (1.26) 5,363.1581 (1.0) 293.9171 (1.03) 47.0478 (1.0) 284.2108 (1.0) 10.5264 (>1000.0)2884;35689 3,402.3204 (0.97) 196079 19
test_quadkey_bench[utiles-(1, 0, 1)] 299.9950 (1.50) 86,300.0023 (16.09) 397.2831 (1.39) 383.5726 (8.15) 399.9958 (1.41) 0.0073 (1.0) 1451;22409 2,517.0967 (0.72) 99010 1
test_quadkey_bench[mercantile-(0, 0, 0)] 599.9973 (3.00) 28,200.0037 (5.26) 821.2744 (2.88) 301.0209 (6.40) 799.9988 (2.81) 0.0073 (1.0) 658;21559 1,217.6198 (0.35) 69445 1
test_quadkey_bench[utiles-(1, 40, 7)] 599.9973 (3.00) 136,899.9947 (25.53) 758.0325 (2.66) 676.4311 (14.38) 699.9981 (2.46) 0.0073 (1.0) 565;29079 1,319.2047 (0.38) 108696 1
test_quadkey_bench[utiles-(486, 332, 10)] 749.9999 (3.75) 8,055.0002 (1.50) 838.5705 (2.94) 137.5439 (2.92) 824.9997 (2.90) 23.7496 (>1000.0) 1445;4742 1,192.5056 (0.34) 63695 20
test_quadkey_bench[mercantile-(1, 0, 1)] 799.9988 (4.00) 104,300.0011 (19.45) 1,015.6996 (3.57) 539.0831 (11.46) 1,000.0003 (3.52) 0.0073 (1.0) 1217;51791 984.5431 (0.28) 119048 1
test_quadkey_bench[mercantile-(1, 1, 1)] 799.9988 (4.00) 75,999.9966 (14.17) 1,047.5805 (3.68) 419.8019 (8.92) 1,000.0003 (3.52) 100.0008 (>1000.0) 3366;4074 954.5806 (0.27) 166667 1
test_quadkey_bench[utiles-(486, 332, 20)] 1,299.9953 (6.50) 83,399.9948 (15.55) 1,545.1801 (5.43) 461.2615 (9.80) 1,499.9969 (5.28) 100.0008 (>1000.0)8793;17328 647.1738 (0.18) 163935 1
test_quadkey_bench[mercantile-(1, 40, 7)] 1,599.9976 (8.00) 110,599.9982 (20.62) 1,789.4247 (6.28) 711.1950 (15.12) 1,799.9992 (6.33) 100.0008 (>1000.0) 1599;2703 558.8388 (0.16) 116280 1
test_quadkey_bench[mercantile-(486, 332, 10)] 1,999.9934 (10.00) 117,000.0032 (21.82) 2,353.1110 (8.26) 768.5591 (16.34) 2,300.0030 (8.09) 200.0015 (>1000.0) 1917;2168 424.9693 (0.12) 117648 1
test_quadkey_bench[mercantile-(486, 332, 20)] 3,199.9953 (16.00) 66,100.0013 (12.32) 3,601.3369 (12.65) 567.1348 (12.05) 3,599.9983 (12.67) 100.0080 (>1000.0) 1479;4347 277.6747 (0.08) 97088 1
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
---------------------------------------------------------------------------------------------- benchmark 'tiles': 2 tests ---------------------------------------------------------------------------------------------
Name (time in us) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_tiles_gen_bench[utiles] 239.3000 (1.0) 1,597.3000 (1.0) 308.5684 (1.0) 130.3316 (1.0) 267.2000 (1.0) 16.5000 (1.0) 312;559 3,240.7721 (1.0) 3232 1
test_tiles_gen_bench[mercantile] 1,349.9000 (5.64) 7,159.2000 (4.48) 1,798.2186 (5.83) 779.7610 (5.98) 1,526.7000 (5.71) 149.6250 (9.07) 66;111 556.1059 (0.17) 601 1
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
------------------------------------------------------------------------------------------------------- benchmark 'ul': 12 tests ------------------------------------------------------------------------------------------------------
Name (time in ns) Min Max Mean StdDev Median IQR Outliers OPS (Kops/s) Rounds Iterations
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_ul_bench[utiles-(1, 1, 1)] 204.3478 (1.0) 7,160.8697 (1.0) 263.7100 (1.0) 125.3400 (1.00) 221.7392 (1.0) 26.0868 (1.30) 17101;28014 3,792.0436 (1.0) 169492 23
test_ul_bench[utiles-(1, 0, 1)] 229.9999 (1.13) 10,579.9998 (1.48) 273.2589 (1.04) 124.7846 (1.0) 250.0001 (1.13) 20.0002 (1.0) 9266;14360 3,659.5327 (0.97) 188680 20
test_ul_bench[utiles-(1, 40, 7)] 229.9999 (1.13) 42,870.0001 (5.99) 311.4689 (1.18) 188.2129 (1.51) 255.0001 (1.15) 35.0003 (1.75) 16764;39465 3,210.5932 (0.85) 200000 20
test_ul_bench[utiles-(486, 332, 20)] 229.9999 (1.13) 65,699.9997 (9.17) 318.4368 (1.21) 243.5307 (1.95) 259.9998 (1.17) 35.0003 (1.75) 11008;36596 3,140.3404 (0.83) 178572 20
test_ul_bench[utiles-(0, 0, 0)] 299.9950 (1.47) 33,899.9962 (4.73) 349.3773 (1.32) 205.0577 (1.64) 300.0023 (1.35) 100.0008 (5.00) 618;618 2,862.2349 (0.75) 70423 1
test_ul_bench[utiles-(486, 332, 10)] 299.9950 (1.47) 57,999.9978 (8.10) 403.1283 (1.53) 400.2343 (3.21) 399.9958 (1.80) 100.0008 (5.00) 2013;20449 2,480.5998 (0.65) 192308 1
test_ul_bench[mercantile-(0, 0, 0)] 999.9931 (4.89) 206,099.9977 (28.78) 1,296.5665 (4.92) 1,201.7776 (9.63) 1,200.0019 (5.41) 100.0008 (5.00) 387;2129 771.2678 (0.20) 45872 1
test_ul_bench[mercantile-(1, 0, 1)] 999.9931 (4.89) 166,500.0018 (23.25) 1,288.3700 (4.89) 712.6090 (5.71) 1,299.9953 (5.86) 100.0008 (5.00) 2119;3450 776.1746 (0.20) 147059 1
test_ul_bench[mercantile-(1, 1, 1)] 1,000.0003 (4.89) 102,799.9970 (14.36) 1,253.0401 (4.75) 570.2565 (4.57) 1,200.0019 (5.41) 100.0008 (5.00) 2957;3697 798.0590 (0.21) 144928 1
test_ul_bench[mercantile-(1, 40, 7)] 1,000.0003 (4.89) 89,599.9983 (12.51) 1,263.1955 (4.79) 586.9464 (4.70) 1,200.0019 (5.41) 100.0008 (5.00) 1775;2965 791.6431 (0.21) 166667 1
test_ul_bench[mercantile-(486, 332, 10)] 1,099.9938 (5.38) 90,200.0029 (12.60) 1,327.0801 (5.03) 536.7494 (4.30) 1,299.9953 (5.86) 100.0008 (5.00) 6813;7956 753.5340 (0.20) 135136 1
test_ul_bench[mercantile-(486, 332, 20)] 1,099.9938 (5.38) 107,300.0021 (14.98) 1,264.2361 (4.79) 594.6154 (4.77) 1,200.0019 (5.41) 100.0008 (5.00) 1522;2265 790.9915 (0.21) 123457 1
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
- Please do! Would love some feedback!
- Be kind!
- I will happily accept PRs, and add you to the currently (5/26/2023) non-existent contributors list.
- benchmark against mercantile
- Maybe:
- Split library into
utiles(rust lib) andutiles-python(python/pip package)? - [] Mbtiles support??
- [] Reading/writing mvt files?
- [] Re-write cli in rust with clap?
- Split library into
zoom info
| zoom | ntiles | total | rowcol_range | max_rowcol |
|---|---|---|---|---|
| 0 | 1 | 1 | 0 | 1 |
| 1 | 4 | 5 | 1 | 2 |
| 2 | 16 | 21 | 3 | 4 |
| 3 | 64 | 85 | 7 | 8 |
| 4 | 256 | 341 | 15 | 16 |
| 5 | 1_024 | 1_365 | 31 | 32 |
| 6 | 4_096 | 5_461 | 63 | 64 |
| 7 | 16_384 | 21_845 | 127 | 128 |
| 8 | 65_536 | 87_381 | 255 | 256 |
| 9 | 262_144 | 349_525 | 511 | 512 |
| 10 | 1_048_576 | 1_398_101 | 1_023 | 1_024 |
| 11 | 4_194_304 | 5_592_405 | 2_047 | 2_048 |
| 12 | 16_777_216 | 22_369_621 | 4_095 | 4_096 |
| 13 | 67_108_864 | 89_478_485 | 8_191 | 8_192 |
| 14 | 268_435_456 | 357_913_941 | 16_383 | 16_384 |
| 15 | 1_073_741_824 | 1_431_655_765 | 32_767 | 32_768 |
| 16 | 4_294_967_296 | 5_726_623_061 | 65_535 | 65_536 |
| 17 | 17_179_869_184 | 22_906_492_245 | 131_071 | 131_072 |
| 18 | 68_719_476_736 | 91_625_968_981 | 262_143 | 262_144 |
| 19 | 274_877_906_944 | 366_503_875_925 | 524_287 | 524_288 |
| 20 | 1_099_511_627_776 | 1_466_015_503_701 | 1_048_575 | 1_048_576 |
| 21 | 4_398_046_511_104 | 5_864_062_014_805 | 2_097_151 | 2_097_152 |
| 22 | 17_592_186_044_416 | 23_456_248_059_221 | 4_194_303 | 4_194_304 |
| 23 | 70_368_744_177_664 | 93_824_992_236_885 | 8_388_607 | 8_388_608 |
| 24 | 281_474_976_710_656 | 375_299_968_947_541 | 16_777_215 | 16_777_216 |
| 25 | 1_125_899_906_842_624 | 1_501_199_875_790_165 | 33_554_431 | 33_554_432 |
| 26 | 4_503_599_627_370_496 | 6_004_799_503_160_661 | 67_108_863 | 67_108_864 |
| 27 | 18_014_398_509_481_984 | 24_019_198_012_642_645 | 134_217_727 | 134_217_728 |
| 28 | 72_057_594_037_927_936 | 96_076_792_050_570_581 | 268_435_455 | 268_435_456 |
| 29 | 288_230_376_151_711_744 | 384_307_168_202_282_325 | 536_870_911 | 536_870_912 |
| 30 | 1_152_921_504_606_846_976 | 1_537_228_672_809_129_301 | 1_073_741_823 | 1_073_741_824 |
| 31 | 4_611_686_018_427_387_904 | 6_148_914_691_236_517_205 | 2_147_483_647 | 2_147_483_648 |
Zoom levels
zoom ntiles total rowcol_range max_rowcol
0 0 1 1 0 1
1 1 4 5 1 2
2 2 16 21 3 4
3 3 64 85 7 8
4 4 256 341 15 16
5 5 1024 1365 31 32
6 6 4096 5461 63 64
7 7 16384 21845 127 128
8 8 65536 87381 255 256
9 9 262144 349525 511 512
10 10 1048576 1398101 1023 1024
11 11 4194304 5592405 2047 2048
12 12 16777216 22369621 4095 4096
13 13 67108864 89478485 8191 8192
14 14 268435456 357913941 16383 16384
15 15 1073741824 1431655765 32767 32768
16 16 4294967296 5726623061 65535 65536
17 17 17179869184 22906492245 131071 131072
18 18 68719476736 91625968981 262143 262144
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22 22 17592186044416 23456248059221 4194303 4194304
23 23 70368744177664 93824992236885 8388607 8388608
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25 25 1125899906842624 1501199875790165 33554431 33554432
26 26 4503599627370496 6004799503160661 67108863 67108864
27 27 18014398509481984 24019198012642645 134217727 134217728
28 28 72057594037927936 96076792050570581 268435455 268435456
29 29 288230376151711744 384307168202282325 536870911 536870912
30 30 1152921504606846976 1537228672809129301 1073741823 1073741824
31 31 4611686018427387904 6148914691236517205 2147483647 2147483648
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