Lint code with `ruff` #5519

mariosasko · 2023-02-09T17:50:21Z

EDIT:
Use ruff for linting instead of isort and flake8 ~~black~~ to be consistent with transformers and hfh.

TODO:

~~Merge the community contributors' PR to avoid having to run make style on their PR branches~~ (we have some new PRs, but fixing those shouldn't be too big of a problem)

HuggingFaceDocBuilderDev · 2023-02-09T17:54:28Z

The documentation is not available anymore as the PR was closed or merged.

github-actions · 2023-02-09T19:33:12Z

Show benchmarks

PyArrow==6.0.0

Show updated benchmarks!

Benchmark: benchmark_array_xd.json

metric	read_batch_formatted_as_numpy after write_array2d	read_batch_formatted_as_numpy after write_flattened_sequence	read_batch_formatted_as_numpy after write_nested_sequence	read_batch_unformated after write_array2d	read_batch_unformated after write_flattened_sequence	read_batch_unformated after write_nested_sequence	read_col_formatted_as_numpy after write_array2d	read_col_formatted_as_numpy after write_flattened_sequence	read_col_formatted_as_numpy after write_nested_sequence	read_col_unformated after write_array2d	read_col_unformated after write_flattened_sequence	read_col_unformated after write_nested_sequence	read_formatted_as_numpy after write_array2d	read_formatted_as_numpy after write_flattened_sequence	read_formatted_as_numpy after write_nested_sequence	read_unformated after write_array2d	read_unformated after write_flattened_sequence	read_unformated after write_nested_sequence	write_array2d	write_flattened_sequence	write_nested_sequence
new / old (diff)	0.009729 / 0.011353 (-0.001624)	0.005342 / 0.011008 (-0.005666)	0.100194 / 0.038508 (0.061686)	0.036391 / 0.023109 (0.013282)	0.294163 / 0.275898 (0.018264)	0.364117 / 0.323480 (0.040637)	0.008231 / 0.007986 (0.000246)	0.005954 / 0.004328 (0.001626)	0.076484 / 0.004250 (0.072234)	0.045028 / 0.037052 (0.007976)	0.308163 / 0.258489 (0.049674)	0.339473 / 0.293841 (0.045632)	0.039268 / 0.128546 (-0.089279)	0.012357 / 0.075646 (-0.063289)	0.334176 / 0.419271 (-0.085096)	0.049502 / 0.043533 (0.005969)	0.294134 / 0.255139 (0.038995)	0.319370 / 0.283200 (0.036170)	0.113040 / 0.141683 (-0.028643)	1.450750 / 1.452155 (-0.001405)	1.490265 / 1.492716 (-0.002452)

Benchmark: benchmark_getitem_100B.json

metric	get_batch_of_1024_random_rows	get_batch_of_1024_rows	get_first_row	get_last_row
new / old (diff)	0.252860 / 0.018006 (0.234854)	0.554299 / 0.000490 (0.553810)	0.002105 / 0.000200 (0.001905)	0.000091 / 0.000054 (0.000037)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.026557 / 0.037411 (-0.010854)	0.104464 / 0.014526 (0.089938)	0.116724 / 0.176557 (-0.059833)	0.154736 / 0.737135 (-0.582399)	0.122017 / 0.296338 (-0.174322)

Benchmark: benchmark_iterating.json

metric	read 5000	read 50000	read_batch 50000 10	read_batch 50000 100	read_batch 50000 1000	read_formatted numpy 5000	read_formatted pandas 5000	read_formatted tensorflow 5000	read_formatted torch 5000	read_formatted_batch numpy 5000 10	read_formatted_batch numpy 5000 1000	shuffled read 5000	shuffled read 50000	shuffled read_batch 50000 10	shuffled read_batch 50000 100	shuffled read_batch 50000 1000	shuffled read_formatted numpy 5000	shuffled read_formatted_batch numpy 5000 10	shuffled read_formatted_batch numpy 5000 1000
new / old (diff)	0.398170 / 0.215209 (0.182961)	3.979309 / 2.077655 (1.901654)	1.773051 / 1.504120 (0.268931)	1.587247 / 1.541195 (0.046053)	1.620446 / 1.468490 (0.151956)	0.692152 / 4.584777 (-3.892625)	3.724821 / 3.745712 (-0.020891)	2.133122 / 5.269862 (-3.136739)	1.455612 / 4.565676 (-3.110065)	0.084721 / 0.424275 (-0.339554)	0.012461 / 0.007607 (0.004854)	0.498909 / 0.226044 (0.272865)	4.983837 / 2.268929 (2.714908)	2.258489 / 55.444624 (-53.186135)	1.891690 / 6.876477 (-4.984786)	1.976944 / 2.142072 (-0.165128)	0.836950 / 4.805227 (-3.968277)	0.165401 / 6.500664 (-6.335263)	0.061623 / 0.075469 (-0.013846)

Benchmark: benchmark_map_filter.json

metric	filter	map fast-tokenizer batched	map identity	map identity batched	map no-op batched	map no-op batched numpy	map no-op batched pandas	map no-op batched pytorch	map no-op batched tensorflow
new / old (diff)	1.205945 / 1.841788 (-0.635842)	15.101603 / 8.074308 (7.027295)	14.393739 / 10.191392 (4.202347)	0.176313 / 0.680424 (-0.504110)	0.029102 / 0.534201 (-0.505099)	0.439785 / 0.579283 (-0.139498)	0.437360 / 0.434364 (0.002996)	0.539668 / 0.540337 (-0.000669)	0.641452 / 1.386936 (-0.745484)

PyArrow==latest

Show updated benchmarks!

Benchmark: benchmark_array_xd.json

metric	read_batch_formatted_as_numpy after write_array2d	read_batch_formatted_as_numpy after write_flattened_sequence	read_batch_formatted_as_numpy after write_nested_sequence	read_batch_unformated after write_array2d	read_batch_unformated after write_flattened_sequence	read_batch_unformated after write_nested_sequence	read_col_formatted_as_numpy after write_array2d	read_col_formatted_as_numpy after write_flattened_sequence	read_col_formatted_as_numpy after write_nested_sequence	read_col_unformated after write_array2d	read_col_unformated after write_flattened_sequence	read_col_unformated after write_nested_sequence	read_formatted_as_numpy after write_array2d	read_formatted_as_numpy after write_flattened_sequence	read_formatted_as_numpy after write_nested_sequence	read_unformated after write_array2d	read_unformated after write_flattened_sequence	read_unformated after write_nested_sequence	write_array2d	write_flattened_sequence	write_nested_sequence
new / old (diff)	0.007184 / 0.011353 (-0.004169)	0.005215 / 0.011008 (-0.005793)	0.074617 / 0.038508 (0.036109)	0.033209 / 0.023109 (0.010100)	0.334304 / 0.275898 (0.058406)	0.370270 / 0.323480 (0.046790)	0.005851 / 0.007986 (-0.002135)	0.004106 / 0.004328 (-0.000222)	0.075487 / 0.004250 (0.071237)	0.051133 / 0.037052 (0.014080)	0.335401 / 0.258489 (0.076912)	0.391457 / 0.293841 (0.097616)	0.036525 / 0.128546 (-0.092021)	0.012423 / 0.075646 (-0.063223)	0.086446 / 0.419271 (-0.332825)	0.050707 / 0.043533 (0.007174)	0.336186 / 0.255139 (0.081047)	0.353273 / 0.283200 (0.070074)	0.105625 / 0.141683 (-0.036057)	1.486118 / 1.452155 (0.033963)	1.584931 / 1.492716 (0.092214)

Benchmark: benchmark_getitem_100B.json

metric	get_batch_of_1024_random_rows	get_batch_of_1024_rows	get_first_row	get_last_row
new / old (diff)	0.237589 / 0.018006 (0.219583)	0.552030 / 0.000490 (0.551540)	0.002863 / 0.000200 (0.002663)	0.000097 / 0.000054 (0.000042)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.028078 / 0.037411 (-0.009333)	0.112516 / 0.014526 (0.097990)	0.121119 / 0.176557 (-0.055438)	0.158874 / 0.737135 (-0.578262)	0.129501 / 0.296338 (-0.166837)

Benchmark: benchmark_iterating.json

metric	read 5000	read 50000	read_batch 50000 10	read_batch 50000 100	read_batch 50000 1000	read_formatted numpy 5000	read_formatted pandas 5000	read_formatted tensorflow 5000	read_formatted torch 5000	read_formatted_batch numpy 5000 10	read_formatted_batch numpy 5000 1000	shuffled read 5000	shuffled read 50000	shuffled read_batch 50000 10	shuffled read_batch 50000 100	shuffled read_batch 50000 1000	shuffled read_formatted numpy 5000	shuffled read_formatted_batch numpy 5000 10	shuffled read_formatted_batch numpy 5000 1000
new / old (diff)	0.419479 / 0.215209 (0.204270)	4.192216 / 2.077655 (2.114561)	1.990513 / 1.504120 (0.486393)	1.792892 / 1.541195 (0.251697)	1.853904 / 1.468490 (0.385413)	0.712702 / 4.584777 (-3.872074)	3.820682 / 3.745712 (0.074970)	2.143695 / 5.269862 (-3.126166)	1.369621 / 4.565676 (-3.196055)	0.087451 / 0.424275 (-0.336824)	0.012622 / 0.007607 (0.005014)	0.521056 / 0.226044 (0.295011)	5.204873 / 2.268929 (2.935944)	2.481169 / 55.444624 (-52.963455)	2.112134 / 6.876477 (-4.764342)	2.200681 / 2.142072 (0.058609)	0.860323 / 4.805227 (-3.944904)	0.171452 / 6.500664 (-6.329212)	0.065235 / 0.075469 (-0.010234)

Benchmark: benchmark_map_filter.json

metric	filter	map fast-tokenizer batched	map identity	map identity batched	map no-op batched	map no-op batched numpy	map no-op batched pandas	map no-op batched pytorch	map no-op batched tensorflow
new / old (diff)	1.241047 / 1.841788 (-0.600741)	14.977890 / 8.074308 (6.903582)	13.584265 / 10.191392 (3.392873)	0.180050 / 0.680424 (-0.500374)	0.018247 / 0.534201 (-0.515954)	0.429585 / 0.579283 (-0.149698)	0.429448 / 0.434364 (-0.004916)	0.542663 / 0.540337 (0.002326)	0.649525 / 1.386936 (-0.737411)

github-actions · 2023-02-09T19:51:19Z

Show benchmarks

PyArrow==6.0.0

Show updated benchmarks!

Benchmark: benchmark_array_xd.json

metric	read_batch_formatted_as_numpy after write_array2d	read_batch_formatted_as_numpy after write_flattened_sequence	read_batch_formatted_as_numpy after write_nested_sequence	read_batch_unformated after write_array2d	read_batch_unformated after write_flattened_sequence	read_batch_unformated after write_nested_sequence	read_col_formatted_as_numpy after write_array2d	read_col_formatted_as_numpy after write_flattened_sequence	read_col_formatted_as_numpy after write_nested_sequence	read_col_unformated after write_array2d	read_col_unformated after write_flattened_sequence	read_col_unformated after write_nested_sequence	read_formatted_as_numpy after write_array2d	read_formatted_as_numpy after write_flattened_sequence	read_formatted_as_numpy after write_nested_sequence	read_unformated after write_array2d	read_unformated after write_flattened_sequence	read_unformated after write_nested_sequence	write_array2d	write_flattened_sequence	write_nested_sequence
new / old (diff)	0.011289 / 0.011353 (-0.000064)	0.005841 / 0.011008 (-0.005167)	0.120994 / 0.038508 (0.082486)	0.043627 / 0.023109 (0.020517)	0.353254 / 0.275898 (0.077356)	0.394685 / 0.323480 (0.071205)	0.009520 / 0.007986 (0.001535)	0.004770 / 0.004328 (0.000442)	0.088857 / 0.004250 (0.084607)	0.048426 / 0.037052 (0.011373)	0.353815 / 0.258489 (0.095326)	0.404109 / 0.293841 (0.110268)	0.060079 / 0.128546 (-0.068467)	0.013840 / 0.075646 (-0.061806)	0.403133 / 0.419271 (-0.016139)	0.072227 / 0.043533 (0.028694)	0.354585 / 0.255139 (0.099446)	0.377937 / 0.283200 (0.094737)	0.139080 / 0.141683 (-0.002602)	1.733266 / 1.452155 (0.281112)	1.828402 / 1.492716 (0.335686)

Benchmark: benchmark_getitem_100B.json

metric	get_batch_of_1024_random_rows	get_batch_of_1024_rows	get_first_row	get_last_row
new / old (diff)	0.215095 / 0.018006 (0.197088)	0.486669 / 0.000490 (0.486179)	0.001425 / 0.000200 (0.001225)	0.000097 / 0.000054 (0.000043)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.032832 / 0.037411 (-0.004579)	0.136335 / 0.014526 (0.121809)	0.141827 / 0.176557 (-0.034730)	0.185917 / 0.737135 (-0.551218)	0.149046 / 0.296338 (-0.147293)

Benchmark: benchmark_iterating.json

metric	read 5000	read 50000	read_batch 50000 10	read_batch 50000 100	read_batch 50000 1000	read_formatted numpy 5000	read_formatted pandas 5000	read_formatted tensorflow 5000	read_formatted torch 5000	read_formatted_batch numpy 5000 10	read_formatted_batch numpy 5000 1000	shuffled read 5000	shuffled read 50000	shuffled read_batch 50000 10	shuffled read_batch 50000 100	shuffled read_batch 50000 1000	shuffled read_formatted numpy 5000	shuffled read_formatted_batch numpy 5000 10	shuffled read_formatted_batch numpy 5000 1000
new / old (diff)	0.474587 / 0.215209 (0.259378)	4.753686 / 2.077655 (2.676031)	2.152147 / 1.504120 (0.648027)	1.941762 / 1.541195 (0.400567)	2.077493 / 1.468490 (0.609003)	0.822432 / 4.584777 (-3.762345)	4.860151 / 3.745712 (1.114439)	2.527292 / 5.269862 (-2.742569)	1.580442 / 4.565676 (-2.985234)	0.102104 / 0.424275 (-0.322171)	0.015060 / 0.007607 (0.007453)	0.598780 / 0.226044 (0.372736)	5.998318 / 2.268929 (3.729390)	2.754115 / 55.444624 (-52.690509)	2.317509 / 6.876477 (-4.558967)	2.409942 / 2.142072 (0.267870)	1.008830 / 4.805227 (-3.796397)	0.196203 / 6.500664 (-6.304461)	0.075378 / 0.075469 (-0.000091)

Benchmark: benchmark_map_filter.json

metric	filter	map fast-tokenizer batched	map identity	map identity batched	map no-op batched	map no-op batched numpy	map no-op batched pandas	map no-op batched pytorch	map no-op batched tensorflow
new / old (diff)	1.430676 / 1.841788 (-0.411112)	19.597628 / 8.074308 (11.523320)	17.364673 / 10.191392 (7.173281)	0.216621 / 0.680424 (-0.463803)	0.039505 / 0.534201 (-0.494696)	0.529027 / 0.579283 (-0.050256)	0.572014 / 0.434364 (0.137650)	0.702898 / 0.540337 (0.162560)	0.785748 / 1.386936 (-0.601188)

PyArrow==latest

Show updated benchmarks!

Benchmark: benchmark_array_xd.json

metric	read_batch_formatted_as_numpy after write_array2d	read_batch_formatted_as_numpy after write_flattened_sequence	read_batch_formatted_as_numpy after write_nested_sequence	read_batch_unformated after write_array2d	read_batch_unformated after write_flattened_sequence	read_batch_unformated after write_nested_sequence	read_col_formatted_as_numpy after write_array2d	read_col_formatted_as_numpy after write_flattened_sequence	read_col_formatted_as_numpy after write_nested_sequence	read_col_unformated after write_array2d	read_col_unformated after write_flattened_sequence	read_col_unformated after write_nested_sequence	read_formatted_as_numpy after write_array2d	read_formatted_as_numpy after write_flattened_sequence	read_formatted_as_numpy after write_nested_sequence	read_unformated after write_array2d	read_unformated after write_flattened_sequence	read_unformated after write_nested_sequence	write_array2d	write_flattened_sequence	write_nested_sequence
new / old (diff)	0.009150 / 0.011353 (-0.002203)	0.006088 / 0.011008 (-0.004920)	0.090629 / 0.038508 (0.052121)	0.044284 / 0.023109 (0.021174)	0.411363 / 0.275898 (0.135465)	0.445499 / 0.323480 (0.122020)	0.007129 / 0.007986 (-0.000856)	0.004843 / 0.004328 (0.000515)	0.087919 / 0.004250 (0.083668)	0.060329 / 0.037052 (0.023277)	0.405802 / 0.258489 (0.147313)	0.468301 / 0.293841 (0.174460)	0.044271 / 0.128546 (-0.084275)	0.014895 / 0.075646 (-0.060751)	0.103728 / 0.419271 (-0.315544)	0.084190 / 0.043533 (0.040657)	0.407210 / 0.255139 (0.152071)	0.432585 / 0.283200 (0.149386)	0.137132 / 0.141683 (-0.004550)	1.720261 / 1.452155 (0.268107)	1.858575 / 1.492716 (0.365858)

Benchmark: benchmark_getitem_100B.json

metric	get_batch_of_1024_random_rows	get_batch_of_1024_rows	get_first_row	get_last_row
new / old (diff)	0.331395 / 0.018006 (0.313389)	0.494757 / 0.000490 (0.494267)	0.043426 / 0.000200 (0.043226)	0.000470 / 0.000054 (0.000415)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.035288 / 0.037411 (-0.002123)	0.140856 / 0.014526 (0.126330)	0.146597 / 0.176557 (-0.029959)	0.192775 / 0.737135 (-0.544360)	0.155307 / 0.296338 (-0.141032)

Benchmark: benchmark_iterating.json

metric	read 5000	read 50000	read_batch 50000 10	read_batch 50000 100	read_batch 50000 1000	read_formatted numpy 5000	read_formatted pandas 5000	read_formatted tensorflow 5000	read_formatted torch 5000	read_formatted_batch numpy 5000 10	read_formatted_batch numpy 5000 1000	shuffled read 5000	shuffled read 50000	shuffled read_batch 50000 10	shuffled read_batch 50000 100	shuffled read_batch 50000 1000	shuffled read_formatted numpy 5000	shuffled read_formatted_batch numpy 5000 10	shuffled read_formatted_batch numpy 5000 1000
new / old (diff)	0.504000 / 0.215209 (0.288791)	5.011081 / 2.077655 (2.933427)	2.380420 / 1.504120 (0.876300)	2.154819 / 1.541195 (0.613624)	2.293883 / 1.468490 (0.825393)	0.864429 / 4.584777 (-3.720348)	5.134475 / 3.745712 (1.388763)	4.984024 / 5.269862 (-0.285837)	2.333754 / 4.565676 (-2.231923)	0.105854 / 0.424275 (-0.318422)	0.015833 / 0.007607 (0.008226)	0.633614 / 0.226044 (0.407569)	6.330974 / 2.268929 (4.062046)	3.020498 / 55.444624 (-52.424126)	2.578234 / 6.876477 (-4.298243)	2.654429 / 2.142072 (0.512357)	1.022041 / 4.805227 (-3.783186)	0.205085 / 6.500664 (-6.295579)	0.081122 / 0.075469 (0.005653)

Benchmark: benchmark_map_filter.json

metric	filter	map fast-tokenizer batched	map identity	map identity batched	map no-op batched	map no-op batched numpy	map no-op batched pandas	map no-op batched pytorch	map no-op batched tensorflow
new / old (diff)	1.538929 / 1.841788 (-0.302859)	19.907799 / 8.074308 (11.833490)	17.174568 / 10.191392 (6.983176)	0.228165 / 0.680424 (-0.452258)	0.024688 / 0.534201 (-0.509513)	0.508958 / 0.579283 (-0.070326)	0.544469 / 0.434364 (0.110105)	0.590805 / 0.540337 (0.050468)	0.705947 / 1.386936 (-0.680989)

…g-ruff

github-actions · 2023-02-14T14:40:32Z

Show benchmarks

PyArrow==6.0.0

Show updated benchmarks!

Benchmark: benchmark_array_xd.json

metric	read_batch_formatted_as_numpy after write_array2d	read_batch_formatted_as_numpy after write_flattened_sequence	read_batch_formatted_as_numpy after write_nested_sequence	read_batch_unformated after write_array2d	read_batch_unformated after write_flattened_sequence	read_batch_unformated after write_nested_sequence	read_col_formatted_as_numpy after write_array2d	read_col_formatted_as_numpy after write_flattened_sequence	read_col_formatted_as_numpy after write_nested_sequence	read_col_unformated after write_array2d	read_col_unformated after write_flattened_sequence	read_col_unformated after write_nested_sequence	read_formatted_as_numpy after write_array2d	read_formatted_as_numpy after write_flattened_sequence	read_formatted_as_numpy after write_nested_sequence	read_unformated after write_array2d	read_unformated after write_flattened_sequence	read_unformated after write_nested_sequence	write_array2d	write_flattened_sequence	write_nested_sequence
new / old (diff)	0.008377 / 0.011353 (-0.002975)	0.004445 / 0.011008 (-0.006563)	0.100671 / 0.038508 (0.062163)	0.029216 / 0.023109 (0.006107)	0.300311 / 0.275898 (0.024413)	0.356907 / 0.323480 (0.033427)	0.006921 / 0.007986 (-0.001065)	0.003384 / 0.004328 (-0.000944)	0.078529 / 0.004250 (0.074278)	0.034689 / 0.037052 (-0.002364)	0.304647 / 0.258489 (0.046158)	0.343584 / 0.293841 (0.049743)	0.032700 / 0.128546 (-0.095846)	0.011403 / 0.075646 (-0.064244)	0.321540 / 0.419271 (-0.097732)	0.040770 / 0.043533 (-0.002762)	0.306900 / 0.255139 (0.051761)	0.322482 / 0.283200 (0.039282)	0.085396 / 0.141683 (-0.056287)	1.450735 / 1.452155 (-0.001419)	1.491829 / 1.492716 (-0.000888)

Benchmark: benchmark_getitem_100B.json

metric	get_batch_of_1024_random_rows	get_batch_of_1024_rows	get_first_row	get_last_row
new / old (diff)	0.009439 / 0.018006 (-0.008567)	0.406805 / 0.000490 (0.406315)	0.002993 / 0.000200 (0.002793)	0.000102 / 0.000054 (0.000048)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.025034 / 0.037411 (-0.012378)	0.100567 / 0.014526 (0.086042)	0.107267 / 0.176557 (-0.069290)	0.149945 / 0.737135 (-0.587190)	0.111150 / 0.296338 (-0.185189)

Benchmark: benchmark_iterating.json

metric	read 5000	read 50000	read_batch 50000 10	read_batch 50000 100	read_batch 50000 1000	read_formatted numpy 5000	read_formatted pandas 5000	read_formatted tensorflow 5000	read_formatted torch 5000	read_formatted_batch numpy 5000 10	read_formatted_batch numpy 5000 1000	shuffled read 5000	shuffled read 50000	shuffled read_batch 50000 10	shuffled read_batch 50000 100	shuffled read_batch 50000 1000	shuffled read_formatted numpy 5000	shuffled read_formatted_batch numpy 5000 10	shuffled read_formatted_batch numpy 5000 1000
new / old (diff)	0.418387 / 0.215209 (0.203178)	4.177979 / 2.077655 (2.100324)	1.886650 / 1.504120 (0.382530)	1.685692 / 1.541195 (0.144497)	1.728270 / 1.468490 (0.259780)	0.700904 / 4.584777 (-3.883873)	3.379998 / 3.745712 (-0.365714)	1.874779 / 5.269862 (-3.395083)	1.170366 / 4.565676 (-3.395310)	0.083190 / 0.424275 (-0.341085)	0.012506 / 0.007607 (0.004899)	0.528633 / 0.226044 (0.302589)	5.301793 / 2.268929 (3.032865)	2.334050 / 55.444624 (-53.110574)	1.986988 / 6.876477 (-4.889488)	2.020508 / 2.142072 (-0.121565)	0.817227 / 4.805227 (-3.988000)	0.150284 / 6.500664 (-6.350380)	0.065489 / 0.075469 (-0.009980)

Benchmark: benchmark_map_filter.json

metric	filter	map fast-tokenizer batched	map identity	map identity batched	map no-op batched	map no-op batched numpy	map no-op batched pandas	map no-op batched pytorch	map no-op batched tensorflow
new / old (diff)	1.224216 / 1.841788 (-0.617572)	13.729808 / 8.074308 (5.655500)	14.283402 / 10.191392 (4.092010)	0.159434 / 0.680424 (-0.520990)	0.028471 / 0.534201 (-0.505730)	0.395102 / 0.579283 (-0.184181)	0.402733 / 0.434364 (-0.031631)	0.470852 / 0.540337 (-0.069485)	0.568530 / 1.386936 (-0.818406)

PyArrow==latest

Show updated benchmarks!

Benchmark: benchmark_array_xd.json

metric	read_batch_formatted_as_numpy after write_array2d	read_batch_formatted_as_numpy after write_flattened_sequence	read_batch_formatted_as_numpy after write_nested_sequence	read_batch_unformated after write_array2d	read_batch_unformated after write_flattened_sequence	read_batch_unformated after write_nested_sequence	read_col_formatted_as_numpy after write_array2d	read_col_formatted_as_numpy after write_flattened_sequence	read_col_formatted_as_numpy after write_nested_sequence	read_col_unformated after write_array2d	read_col_unformated after write_flattened_sequence	read_col_unformated after write_nested_sequence	read_formatted_as_numpy after write_array2d	read_formatted_as_numpy after write_flattened_sequence	read_formatted_as_numpy after write_nested_sequence	read_unformated after write_array2d	read_unformated after write_flattened_sequence	read_unformated after write_nested_sequence	write_array2d	write_flattened_sequence	write_nested_sequence
new / old (diff)	0.006750 / 0.011353 (-0.004603)	0.004479 / 0.011008 (-0.006529)	0.074926 / 0.038508 (0.036418)	0.027619 / 0.023109 (0.004510)	0.342070 / 0.275898 (0.066172)	0.372452 / 0.323480 (0.048972)	0.005094 / 0.007986 (-0.002892)	0.003494 / 0.004328 (-0.000834)	0.074963 / 0.004250 (0.070713)	0.038457 / 0.037052 (0.001405)	0.340587 / 0.258489 (0.082098)	0.381212 / 0.293841 (0.087371)	0.031597 / 0.128546 (-0.096950)	0.011631 / 0.075646 (-0.064015)	0.084646 / 0.419271 (-0.334626)	0.042072 / 0.043533 (-0.001461)	0.340977 / 0.255139 (0.085838)	0.366502 / 0.283200 (0.083302)	0.091181 / 0.141683 (-0.050502)	1.435119 / 1.452155 (-0.017035)	1.520426 / 1.492716 (0.027710)

Benchmark: benchmark_getitem_100B.json

metric	get_batch_of_1024_random_rows	get_batch_of_1024_rows	get_first_row	get_last_row
new / old (diff)	0.211320 / 0.018006 (0.193313)	0.466154 / 0.000490 (0.465664)	0.002901 / 0.000200 (0.002701)	0.000080 / 0.000054 (0.000026)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.025122 / 0.037411 (-0.012289)	0.098929 / 0.014526 (0.084403)	0.106551 / 0.176557 (-0.070005)	0.142820 / 0.737135 (-0.594316)	0.110701 / 0.296338 (-0.185637)

Benchmark: benchmark_iterating.json

metric	read 5000	read 50000	read_batch 50000 10	read_batch 50000 100	read_batch 50000 1000	read_formatted numpy 5000	read_formatted pandas 5000	read_formatted tensorflow 5000	read_formatted torch 5000	read_formatted_batch numpy 5000 10	read_formatted_batch numpy 5000 1000	shuffled read 5000	shuffled read 50000	shuffled read_batch 50000 10	shuffled read_batch 50000 100	shuffled read_batch 50000 1000	shuffled read_formatted numpy 5000	shuffled read_formatted_batch numpy 5000 10	shuffled read_formatted_batch numpy 5000 1000
new / old (diff)	0.445187 / 0.215209 (0.229978)	4.457524 / 2.077655 (2.379870)	2.088323 / 1.504120 (0.584203)	1.888076 / 1.541195 (0.346881)	1.923340 / 1.468490 (0.454850)	0.723354 / 4.584777 (-3.861423)	3.428479 / 3.745712 (-0.317233)	1.914580 / 5.269862 (-3.355281)	1.191810 / 4.565676 (-3.373866)	0.087008 / 0.424275 (-0.337267)	0.013431 / 0.007607 (0.005824)	0.545089 / 0.226044 (0.319044)	5.465887 / 2.268929 (3.196958)	2.527431 / 55.444624 (-52.917194)	2.240622 / 6.876477 (-4.635854)	2.232472 / 2.142072 (0.090399)	0.815968 / 4.805227 (-3.989259)	0.152842 / 6.500664 (-6.347822)	0.067152 / 0.075469 (-0.008317)

Benchmark: benchmark_map_filter.json

metric	filter	map fast-tokenizer batched	map identity	map identity batched	map no-op batched	map no-op batched numpy	map no-op batched pandas	map no-op batched pytorch	map no-op batched tensorflow
new / old (diff)	1.328360 / 1.841788 (-0.513427)	14.163349 / 8.074308 (6.089040)	13.814255 / 10.191392 (3.622863)	0.131684 / 0.680424 (-0.548740)	0.016980 / 0.534201 (-0.517221)	0.396045 / 0.579283 (-0.183238)	0.395078 / 0.434364 (-0.039286)	0.471728 / 0.540337 (-0.068609)	0.567830 / 1.386936 (-0.819106)

lhoestq

Thank you !

github-actions · 2023-02-14T16:28:27Z

Show benchmarks

PyArrow==6.0.0

Show updated benchmarks!

Benchmark: benchmark_array_xd.json

metric	read_batch_formatted_as_numpy after write_array2d	read_batch_formatted_as_numpy after write_flattened_sequence	read_batch_formatted_as_numpy after write_nested_sequence	read_batch_unformated after write_array2d	read_batch_unformated after write_flattened_sequence	read_batch_unformated after write_nested_sequence	read_col_formatted_as_numpy after write_array2d	read_col_formatted_as_numpy after write_flattened_sequence	read_col_formatted_as_numpy after write_nested_sequence	read_col_unformated after write_array2d	read_col_unformated after write_flattened_sequence	read_col_unformated after write_nested_sequence	read_formatted_as_numpy after write_array2d	read_formatted_as_numpy after write_flattened_sequence	read_formatted_as_numpy after write_nested_sequence	read_unformated after write_array2d	read_unformated after write_flattened_sequence	read_unformated after write_nested_sequence	write_array2d	write_flattened_sequence	write_nested_sequence
new / old (diff)	0.012630 / 0.011353 (0.001277)	0.007038 / 0.011008 (-0.003970)	0.158816 / 0.038508 (0.120308)	0.044142 / 0.023109 (0.021032)	0.389393 / 0.275898 (0.113495)	0.479745 / 0.323480 (0.156265)	0.009335 / 0.007986 (0.001349)	0.005434 / 0.004328 (0.001105)	0.107747 / 0.004250 (0.103497)	0.048382 / 0.037052 (0.011330)	0.398144 / 0.258489 (0.139655)	0.446373 / 0.293841 (0.152532)	0.066285 / 0.128546 (-0.062261)	0.021174 / 0.075646 (-0.054472)	0.449176 / 0.419271 (0.029905)	0.063044 / 0.043533 (0.019511)	0.390523 / 0.255139 (0.135384)	0.451435 / 0.283200 (0.168236)	0.116369 / 0.141683 (-0.025314)	1.881269 / 1.452155 (0.429114)	1.944527 / 1.492716 (0.451811)

Benchmark: benchmark_getitem_100B.json

metric	get_batch_of_1024_random_rows	get_batch_of_1024_rows	get_first_row	get_last_row
new / old (diff)	0.227989 / 0.018006 (0.209983)	0.538514 / 0.000490 (0.538024)	0.009404 / 0.000200 (0.009204)	0.000510 / 0.000054 (0.000455)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.029826 / 0.037411 (-0.007585)	0.129623 / 0.014526 (0.115098)	0.142067 / 0.176557 (-0.034489)	0.218586 / 0.737135 (-0.518549)	0.160524 / 0.296338 (-0.135814)

Benchmark: benchmark_iterating.json

metric	read 5000	read 50000	read_batch 50000 10	read_batch 50000 100	read_batch 50000 1000	read_formatted numpy 5000	read_formatted pandas 5000	read_formatted tensorflow 5000	read_formatted torch 5000	read_formatted_batch numpy 5000 10	read_formatted_batch numpy 5000 1000	shuffled read 5000	shuffled read 50000	shuffled read_batch 50000 10	shuffled read_batch 50000 100	shuffled read_batch 50000 1000	shuffled read_formatted numpy 5000	shuffled read_formatted_batch numpy 5000 10	shuffled read_formatted_batch numpy 5000 1000
new / old (diff)	0.667195 / 0.215209 (0.451986)	6.694192 / 2.077655 (4.616537)	2.542493 / 1.504120 (1.038373)	2.124042 / 1.541195 (0.582847)	2.024854 / 1.468490 (0.556364)	1.306222 / 4.584777 (-3.278555)	5.631557 / 3.745712 (1.885845)	3.405978 / 5.269862 (-1.863884)	2.471399 / 4.565676 (-2.094278)	0.165187 / 0.424275 (-0.259088)	0.014880 / 0.007607 (0.007273)	0.842718 / 0.226044 (0.616673)	8.584358 / 2.268929 (6.315430)	3.377228 / 55.444624 (-52.067396)	2.667265 / 6.876477 (-4.209212)	2.699462 / 2.142072 (0.557389)	1.623115 / 4.805227 (-3.182112)	0.253929 / 6.500664 (-6.246735)	0.077189 / 0.075469 (0.001720)

Benchmark: benchmark_map_filter.json

metric	filter	map fast-tokenizer batched	map identity	map identity batched	map no-op batched	map no-op batched numpy	map no-op batched pandas	map no-op batched pytorch	map no-op batched tensorflow
new / old (diff)	1.778962 / 1.841788 (-0.062825)	18.997636 / 8.074308 (10.923328)	24.255222 / 10.191392 (14.063830)	0.304754 / 0.680424 (-0.375670)	0.049656 / 0.534201 (-0.484545)	0.590871 / 0.579283 (0.011588)	0.649292 / 0.434364 (0.214928)	0.751281 / 0.540337 (0.210943)	0.872193 / 1.386936 (-0.514743)

PyArrow==latest

Show updated benchmarks!

Benchmark: benchmark_array_xd.json

metric	read_batch_formatted_as_numpy after write_array2d	read_batch_formatted_as_numpy after write_flattened_sequence	read_batch_formatted_as_numpy after write_nested_sequence	read_batch_unformated after write_array2d	read_batch_unformated after write_flattened_sequence	read_batch_unformated after write_nested_sequence	read_col_formatted_as_numpy after write_array2d	read_col_formatted_as_numpy after write_flattened_sequence	read_col_formatted_as_numpy after write_nested_sequence	read_col_unformated after write_array2d	read_col_unformated after write_flattened_sequence	read_col_unformated after write_nested_sequence	read_formatted_as_numpy after write_array2d	read_formatted_as_numpy after write_flattened_sequence	read_formatted_as_numpy after write_nested_sequence	read_unformated after write_array2d	read_unformated after write_flattened_sequence	read_unformated after write_nested_sequence	write_array2d	write_flattened_sequence	write_nested_sequence
new / old (diff)	0.010660 / 0.011353 (-0.000693)	0.006492 / 0.011008 (-0.004516)	0.112190 / 0.038508 (0.073682)	0.045391 / 0.023109 (0.022281)	0.439852 / 0.275898 (0.163954)	0.486489 / 0.323480 (0.163009)	0.007155 / 0.007986 (-0.000830)	0.006323 / 0.004328 (0.001995)	0.099775 / 0.004250 (0.095525)	0.055762 / 0.037052 (0.018709)	0.439457 / 0.258489 (0.180968)	0.505322 / 0.293841 (0.211481)	0.057019 / 0.128546 (-0.071527)	0.031382 / 0.075646 (-0.044264)	0.121211 / 0.419271 (-0.298061)	0.066091 / 0.043533 (0.022558)	0.499760 / 0.255139 (0.244622)	0.508312 / 0.283200 (0.225113)	0.146975 / 0.141683 (0.005292)	1.916347 / 1.452155 (0.464193)	2.065860 / 1.492716 (0.573144)

Benchmark: benchmark_getitem_100B.json

metric	get_batch_of_1024_random_rows	get_batch_of_1024_rows	get_first_row	get_last_row
new / old (diff)	0.247176 / 0.018006 (0.229170)	0.565141 / 0.000490 (0.564652)	0.004841 / 0.000200 (0.004641)	0.000141 / 0.000054 (0.000087)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.036378 / 0.037411 (-0.001033)	0.143470 / 0.014526 (0.128944)	0.148096 / 0.176557 (-0.028461)	0.225877 / 0.737135 (-0.511258)	0.147072 / 0.296338 (-0.149266)

Benchmark: benchmark_iterating.json

metric	read 5000	read 50000	read_batch 50000 10	read_batch 50000 100	read_batch 50000 1000	read_formatted numpy 5000	read_formatted pandas 5000	read_formatted tensorflow 5000	read_formatted torch 5000	read_formatted_batch numpy 5000 10	read_formatted_batch numpy 5000 1000	shuffled read 5000	shuffled read 50000	shuffled read_batch 50000 10	shuffled read_batch 50000 100	shuffled read_batch 50000 1000	shuffled read_formatted numpy 5000	shuffled read_formatted_batch numpy 5000 10	shuffled read_formatted_batch numpy 5000 1000
new / old (diff)	0.723119 / 0.215209 (0.507910)	6.824981 / 2.077655 (4.747326)	2.883840 / 1.504120 (1.379720)	2.468707 / 1.541195 (0.927513)	2.525549 / 1.468490 (1.057059)	1.426640 / 4.584777 (-3.158137)	5.816045 / 3.745712 (2.070333)	5.727037 / 5.269862 (0.457175)	2.650307 / 4.565676 (-1.915369)	0.160306 / 0.424275 (-0.263970)	0.015371 / 0.007607 (0.007764)	0.835778 / 0.226044 (0.609733)	8.622836 / 2.268929 (6.353907)	3.616338 / 55.444624 (-51.828287)	2.974243 / 6.876477 (-3.902234)	2.884557 / 2.142072 (0.742485)	1.734874 / 4.805227 (-3.070353)	0.277474 / 6.500664 (-6.223190)	0.094189 / 0.075469 (0.018720)

Benchmark: benchmark_map_filter.json

metric	filter	map fast-tokenizer batched	map identity	map identity batched	map no-op batched	map no-op batched numpy	map no-op batched pandas	map no-op batched pytorch	map no-op batched tensorflow
new / old (diff)	1.785728 / 1.841788 (-0.056059)	19.376490 / 8.074308 (11.302182)	24.560403 / 10.191392 (14.369011)	0.250686 / 0.680424 (-0.429738)	0.034333 / 0.534201 (-0.499868)	0.557331 / 0.579283 (-0.021952)	0.641007 / 0.434364 (0.206643)	0.657138 / 0.540337 (0.116800)	0.759023 / 1.386936 (-0.627913)

* Update config files * Format code * Some manual fixes * Fix

albertvillanova · 2024-06-01T15:34:05Z

I am editing the title and description of this PR:

It should be "Lint code" instead of "Format code": formatting was still done with black
This PR uses ruff instead of isort and flake8 (not black): note that black was still used for formatting

mariosasko added 2 commits February 9, 2023 18:40

Update config files

460b3d0

Format code

84bcb9e

Some manual fixes

26cf1d2

Fix

2573861

Merge branch 'main' of github.com:huggingface/datasets into formattin…

82331b0

…g-ruff

mariosasko marked this pull request as ready for review February 14, 2023 14:43

mariosasko requested a review from lhoestq February 14, 2023 14:43

lhoestq approved these changes Feb 14, 2023

View reviewed changes

mariosasko merged commit 06ae3f6 into main Feb 14, 2023

mariosasko deleted the formatting-ruff branch February 14, 2023 16:18

AJDERS pushed a commit to AJDERS/datasets that referenced this pull request Feb 15, 2023

Format code with ruff (huggingface#5519)

8916925

* Update config files * Format code * Some manual fixes * Fix

filip-halt pushed a commit to filip-halt/datasets that referenced this pull request Feb 16, 2023

Format code with ruff (huggingface#5519)

ec1f47e

* Update config files * Format code * Some manual fixes * Fix

filip-halt pushed a commit to filip-halt/datasets that referenced this pull request Feb 16, 2023

Format code with ruff (huggingface#5519)

e491a2d

* Update config files * Format code * Some manual fixes * Fix

alvarobartt mentioned this pull request Feb 19, 2023

Add ruff in replacement of isort and flake8, and define YAML to check style huggingface/fuego#10

Merged

albertvillanova changed the title ~~Format code with ruff~~ Lint code with ruff Jun 1, 2024

This was referenced Jun 2, 2024

Import sorting is disabled by flake8 noqa directive after switching to ruff linter #6942

Closed

Re-enable import sorting disabled by flake8:noqa directive when using ruff linter #6946

Merged

Lint code with ruff #5519

Lint code with ruff #5519

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mariosasko commented Feb 9, 2023 • edited by albertvillanova Loading

HuggingFaceDocBuilderDev commented Feb 9, 2023 • edited Loading

github-actions bot commented Feb 9, 2023

Benchmark: benchmark_array_xd.json

Benchmark: benchmark_getitem_100B.json

Benchmark: benchmark_indices_mapping.json

Benchmark: benchmark_iterating.json

Benchmark: benchmark_map_filter.json

Benchmark: benchmark_array_xd.json

Benchmark: benchmark_getitem_100B.json

Benchmark: benchmark_indices_mapping.json

Benchmark: benchmark_iterating.json

Benchmark: benchmark_map_filter.json

github-actions bot commented Feb 9, 2023

Benchmark: benchmark_array_xd.json

Benchmark: benchmark_getitem_100B.json

Benchmark: benchmark_indices_mapping.json

Benchmark: benchmark_iterating.json

Benchmark: benchmark_map_filter.json

Benchmark: benchmark_array_xd.json

Benchmark: benchmark_getitem_100B.json

Benchmark: benchmark_indices_mapping.json

Benchmark: benchmark_iterating.json

Benchmark: benchmark_map_filter.json

github-actions bot commented Feb 14, 2023

Benchmark: benchmark_array_xd.json

Benchmark: benchmark_getitem_100B.json

Benchmark: benchmark_indices_mapping.json

Benchmark: benchmark_iterating.json

Benchmark: benchmark_map_filter.json

Benchmark: benchmark_array_xd.json

Benchmark: benchmark_getitem_100B.json

Benchmark: benchmark_indices_mapping.json

Benchmark: benchmark_iterating.json

Benchmark: benchmark_map_filter.json

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github-actions bot commented Feb 14, 2023

Benchmark: benchmark_array_xd.json

Benchmark: benchmark_getitem_100B.json

Benchmark: benchmark_indices_mapping.json

Benchmark: benchmark_iterating.json

Benchmark: benchmark_map_filter.json

Benchmark: benchmark_array_xd.json

Benchmark: benchmark_getitem_100B.json

Benchmark: benchmark_indices_mapping.json

Benchmark: benchmark_iterating.json

Benchmark: benchmark_map_filter.json

albertvillanova commented Jun 1, 2024

Lint code with `ruff` #5519

Lint code with `ruff` #5519

mariosasko commented Feb 9, 2023 •

edited by albertvillanova

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HuggingFaceDocBuilderDev commented Feb 9, 2023 •

edited

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