Closed HexDecimal closed 1 month ago
I mentioned profiling earlier and decided to write some benchmarks. These use pytest-benchmark.
pytest-benchmark
============================= test session starts ============================= platform win32 -- Python 3.10.5, pytest-6.2.5, py-1.10.0, pluggy-1.0.0 benchmark: 3.4.1 (defaults: timer=time.perf_counter disable_gc=False min_rounds=5 min_time=0.000005 max_time=1.0 calibration_precision=10 warmup=False warmup_iterations=100000) rootdir: C:\Users\4b796\Projects\_others_projects\flaschen-taschen\api\python plugins: benchmark-3.4.1, cov-2.12.1 collected 7 items test_flaschen.py ....... [100%] ------------------------------------------------------------------------------------------------------- benchmark: 7 tests ------------------------------------------------------------------------------------------------------- Name (time in ns) Min Max Mean StdDev Median IQR Outliers OPS (Kops/s) Rounds Iterations ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- test_set 439.9917 (1.0) 2,645.0027 (1.0) 461.4312 (1.0) 28.1379 (1.0) 459.9919 (1.0) 10.0001 (1.0) 3306;4980 2,167.1704 (1.0) 87721 20 test_send 3,699.9118 (8.41) 27,799.9789 (10.51) 4,184.8972 (9.07) 765.3272 (27.20) 4,000.0305 (8.70) 299.6530 (29.97) 598;686 238.9545 (0.11) 10289 1 test_send_array_transparent 5,799.8113 (13.18) 146,599.9521 (55.43) 6,799.1550 (14.73) 3,027.1605 (107.58) 6,299.9316 (13.70) 299.8859 (29.99) 189;2150 147.0771 (0.07) 13948 1 test_send_array 47,299.7781 (107.50) 199,300.0042 (75.35) 50,716.3139 (109.91) 5,579.8516 (198.30) 49,399.9105 (107.39) 1,899.8981 (189.99) 409;469 19.7175 (0.01) 4622 1 test_send_new_array 50,200.1494 (114.09) 193,000.0726 (72.97) 53,330.9120 (115.58) 3,547.6356 (126.08) 52,800.1692 (114.79) 1,299.8935 (129.99) 334;451 18.7509 (0.01) 6072 1 test_flaschen_init 185,099.8960 (420.69) 433,399.8077 (163.86) 205,587.9331 (445.54) 24,393.0880 (866.91) 199,100.0026 (432.83) 10,499.9635 (>1000.0) 33;41 4.8641 (0.00) 323 1 test_set_full 657,600.1178 (>1000.0) 885,799.9928 (334.90) 682,893.4062 (>1000.0) 18,145.3584 (644.87) 681,199.9483 (>1000.0) 17,100.0138 (>1000.0) 150;21 1.4644 (0.00) 1334 1 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Legend: Outliers: 1 Standard Deviation from Mean; 1.5 IQR (InterQuartile Range) from 1st Quartile and 3rd Quartile. OPS: Operations Per Second, computed as 1 / Mean ============================== 7 passed in 3.96s ==============================
It seems transparency handing is a big factor in the performance of send_array. Ignoring that it's about twice as slow as sending _data.
_data
I mentioned profiling earlier and decided to write some benchmarks. These use
pytest-benchmark.It seems transparency handing is a big factor in the performance of send_array. Ignoring that it's about twice as slow as sending
_data.