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4cd8639
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Possible performance regression was detected for benchmark 'TiPg Benchmarks'.
Benchmark result of this commit is worse than the previous benchmark result exceeding threshold
1.30
.tests/benchmarks.py::test_benchmark_collections[json-1]
218.17449027849244
iter/sec (stddev: 0.0012080961964354335
)389.8174657849523
iter/sec (stddev: 0.0001346513331121
)1.79
tests/benchmarks.py::test_benchmark_collections[json-10]
141.6977098041463
iter/sec (stddev: 0.001885074909774726
)235.81724379810439
iter/sec (stddev: 0.0001314043223951821
)1.66
tests/benchmarks.py::test_benchmark_collections[html-1]
219.83424278258306
iter/sec (stddev: 0.001437689013235457
)386.9907532429826
iter/sec (stddev: 0.00012887457842136315
)1.76
tests/benchmarks.py::test_benchmark_collections[html-10]
140.8749498825268
iter/sec (stddev: 0.000945956898324737
)226.57826331125347
iter/sec (stddev: 0.00016911503432068357
)1.61
tests/benchmarks.py::test_benchmark_collection[json]
294.86058588521485
iter/sec (stddev: 0.00030912728993643724
)497.36579735757243
iter/sec (stddev: 0.00012218872577341353
)1.69
tests/benchmarks.py::test_benchmark_collection[html]
283.85523348740077
iter/sec (stddev: 0.0007220129425748756
)474.5252825568808
iter/sec (stddev: 0.00012230952747538322
)1.67
tests/benchmarks.py::test_benchmark_queryables
343.77602291301
iter/sec (stddev: 0.00048622758568530217
)560.1728217671863
iter/sec (stddev: 0.00009868798011117214
)1.63
tests/benchmarks.py::test_benchmark_items[geojson-1]
103.98236999028411
iter/sec (stddev: 0.0008794826175333024
)171.72340015031662
iter/sec (stddev: 0.0001975764018515539
)1.65
tests/benchmarks.py::test_benchmark_items[geojson-10]
92.30454547452304
iter/sec (stddev: 0.0015242390399558415
)150.89509342585401
iter/sec (stddev: 0.0005174120591189715
)1.63
tests/benchmarks.py::test_benchmark_items[geojson-50]
65.03897022399762
iter/sec (stddev: 0.0014222348598595667
)92.37633529510073
iter/sec (stddev: 0.004799516181177598
)1.42
tests/benchmarks.py::test_benchmark_items[geojson-100]
44.56621951889656
iter/sec (stddev: 0.012838397954430732
)65.4199256164811
iter/sec (stddev: 0.005496999397562707
)1.47
tests/benchmarks.py::test_benchmark_items[geojson-200]
29.501769553544815
iter/sec (stddev: 0.012822291147388273
)40.93348370299044
iter/sec (stddev: 0.006767118864512801
)1.39
tests/benchmarks.py::test_benchmark_items[csv-1]
100.38307511846098
iter/sec (stddev: 0.002709775088755286
)164.99236600027038
iter/sec (stddev: 0.0001625180883885496
)1.64
tests/benchmarks.py::test_benchmark_items[csv-10]
71.62969217974369
iter/sec (stddev: 0.002205595572500069
)131.78887347828973
iter/sec (stddev: 0.0003126913356476361
)1.84
tests/benchmarks.py::test_benchmark_items[csv-50]
37.91350582878962
iter/sec (stddev: 0.0016602625724890625
)71.00074025478915
iter/sec (stddev: 0.0004241045785840394
)1.87
tests/benchmarks.py::test_benchmark_items[csv-100]
23.42911717170071
iter/sec (stddev: 0.007037673222364735
)44.912298902681094
iter/sec (stddev: 0.0004133500660856742
)1.92
tests/benchmarks.py::test_benchmark_items[csv-200]
13.295687734724245
iter/sec (stddev: 0.010473543469190853
)25.38712730341501
iter/sec (stddev: 0.0015488591510809668
)1.91
tests/benchmarks.py::test_benchmark_items[csv-250]
11.221889353840709
iter/sec (stddev: 0.009016648968119488
)21.20231606184937
iter/sec (stddev: 0.0009630622441218977
)1.89
tests/benchmarks.py::test_benchmark_items[html-1]
99.15846456770889
iter/sec (stddev: 0.002347229145944913
)161.2583038976123
iter/sec (stddev: 0.00015107003155602982
)1.63
tests/benchmarks.py::test_benchmark_items[html-10]
82.80465425724122
iter/sec (stddev: 0.0023761846467990014
)131.41922491054981
iter/sec (stddev: 0.00038299977072516665
)1.59
tests/benchmarks.py::test_benchmark_items[html-50]
45.309949763957846
iter/sec (stddev: 0.011377877445539999
)71.18975022809582
iter/sec (stddev: 0.0060196890867636015
)1.57
tests/benchmarks.py::test_benchmark_items[html-100]
27.41068479918186
iter/sec (stddev: 0.027758702665916308
)50.012686611030425
iter/sec (stddev: 0.00017634477829479224
)1.82
tests/benchmarks.py::test_benchmark_items[html-200]
15.540421752390143
iter/sec (stddev: 0.03573905146983195
)25.74513671846712
iter/sec (stddev: 0.015851254043987614
)1.66
tests/benchmarks.py::test_benchmark_items[html-250]
13.704055002925916
iter/sec (stddev: 0.03611240281639115
)19.446041680188895
iter/sec (stddev: 0.02196395036197749
)1.42
tests/benchmarks.py::test_benchmark_item[geojson-NewfoundlandandLabrador]
1.5607069018895499
iter/sec (stddev: 0.026137200511787785
)2.451994014029415
iter/sec (stddev: 0.009399100052411144
)1.57
tests/benchmarks.py::test_benchmark_item[geojson-Saskatchewan]
36.39180963685581
iter/sec (stddev: 0.023988642316204793
)50.561971751322865
iter/sec (stddev: 0.01543572328009663
)1.39
tests/benchmarks.py::test_benchmark_item[html-NewfoundlandandLabrador]
0.649568195813314
iter/sec (stddev: 0.09954551706431072
)0.9127396645615509
iter/sec (stddev: 0.039552382563250214
)1.41
tests/benchmarks.py::test_benchmark_item[html-Saskatchewan]
12.364589252321895
iter/sec (stddev: 0.05371056416562014
)20.11363481067079
iter/sec (stddev: 0.030565646770264313
)1.63
tests/benchmarks.py::test_benchmark_tile[0/0/0-WGS1984Quad]
6.978369510901955
iter/sec (stddev: 0.01574465093101298
)9.071946454832053
iter/sec (stddev: 0.007972027740308708
)1.30
tests/benchmarks.py::test_benchmark_tile[4/8/5-WGS1984Quad]
129.84576598901157
iter/sec (stddev: 0.001755601860580967
)197.51129716783083
iter/sec (stddev: 0.00011718955652817509
)1.52
tests/benchmarks.py::test_benchmark_tile[4/8/5-WebMercatorQuad]
98.21865170874219
iter/sec (stddev: 0.000990751830177583
)132.2249070318908
iter/sec (stddev: 0.0002176113631555468
)1.35
tests/benchmarks.py::test_benchmark_tile[6/33/25-WGS1984Quad]
163.77414897855775
iter/sec (stddev: 0.000955493497521207
)253.74316349195954
iter/sec (stddev: 0.00010642252659784684
)1.55
tests/benchmarks.py::test_benchmark_tile[6/33/25-WebMercatorQuad]
146.61237734136915
iter/sec (stddev: 0.0019162542785118109
)232.08461437687794
iter/sec (stddev: 0.0002772635786773613
)1.58
tests/benchmarks.py::test_benchmark_tilematrixset_endpoints[/tileMatrixSets]
334.1964321643578
iter/sec (stddev: 0.0015004437625633317
)504.3077044734148
iter/sec (stddev: 0.0028841331379532574
)1.51
tests/benchmarks.py::test_benchmark_tilematrixset_endpoints[/tileMatrixSets/WGS1984Quad]
443.6848724820769
iter/sec (stddev: 0.004105934191698231
)714.4151473564792
iter/sec (stddev: 0.00011123610818711978
)1.61
tests/benchmarks.py::test_benchmark_tilematrixset_endpoints[/tileMatrixSets/WebMercatorQuad]
495.9972463664904
iter/sec (stddev: 0.0004081857980586652
)708.851850379112
iter/sec (stddev: 0.00007234887368660502
)1.43
tests/benchmarks.py::test_benchmark_tilematrixset_endpoints[/collections/public.landsat_wrs/tiles]
37.02183998307772
iter/sec (stddev: 0.0013581990726481646
)51.44201801933845
iter/sec (stddev: 0.0002227153087666646
)1.39
tests/benchmarks.py::test_benchmark_tilematrixset_endpoints[/collections/public.landsat_wrs/tiles/WGS1984Quad]
162.58409125598413
iter/sec (stddev: 0.0018844028624617093
)230.92654791968474
iter/sec (stddev: 0.00007775541167608782
)1.42
tests/benchmarks.py::test_benchmark_tilematrixset_endpoints[/collections/public.landsat_wrs/tiles/WebMercatorQuad]
167.79644072347773
iter/sec (stddev: 0.0013485356254824962
)224.97888641484812
iter/sec (stddev: 0.00008029404899892052
)1.34
This comment was automatically generated by workflow using github-action-benchmark.