fix os.listdir return name is empty string

[d710055071]

fix #6588

xlistdir return name is empty string

for example：
`
from datasets.download.streaming_download_manager import xjoin
from datasets.download.streaming_download_manager import xlistdir
config = DownloadConfig(storage_options=options)
manger = StreamingDownloadManager("ILSVRC2012",download_config=config)
input_path = "lakefs://datalab/main/imagenet/ILSVRC2012.zip"

download_files = manger.download_and_extract(input_path)

current_dir = xjoin(download_files,"ILSVRC2012/Images/ILSVRC2012_img_train")
folder_list = xlistdir(current_dir)

`

[HuggingFaceDocBuilderDev]

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[d710055071]

Obj ["name"] ends with "/"

[d710055071]

@lhoestq

hello,
Can you help me check if there are any issues with this PR? Why hasn't anyone merged?

[lhoestq]

Good catch ! thanks for the fix :)

[github-actions]

Show benchmarks

PyArrow==8.0.0

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)	0.004968 / 0.011353 (-0.006385)	0.003516 / 0.011008 (-0.007492)	0.063787 / 0.038508 (0.025279)	0.031695 / 0.023109 (0.008586)	0.240081 / 0.275898 (-0.035817)	0.260984 / 0.323480 (-0.062496)	0.003832 / 0.007986 (-0.004153)	0.002680 / 0.004328 (-0.001648)	0.049199 / 0.004250 (0.044948)	0.044720 / 0.037052 (0.007668)	0.255812 / 0.258489 (-0.002677)	0.275923 / 0.293841 (-0.017918)	0.026849 / 0.128546 (-0.101697)	0.010473 / 0.075646 (-0.065174)	0.209069 / 0.419271 (-0.210202)	0.035731 / 0.043533 (-0.007802)	0.246596 / 0.255139 (-0.008543)	0.265889 / 0.283200 (-0.017311)	0.017607 / 0.141683 (-0.124075)	1.128648 / 1.452155 (-0.323507)	1.174379 / 1.492716 (-0.318338)

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)	0.098214 / 0.018006 (0.080207)	0.311969 / 0.000490 (0.311480)	0.000266 / 0.000200 (0.000066)	0.000056 / 0.000054 (0.000002)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.018401 / 0.037411 (-0.019010)	0.061347 / 0.014526 (0.046821)	0.073628 / 0.176557 (-0.102928)	0.121359 / 0.737135 (-0.615776)	0.075148 / 0.296338 (-0.221190)

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)	0.274098 / 0.215209 (0.058889)	2.707633 / 2.077655 (0.629978)	1.453615 / 1.504120 (-0.050504)	1.311942 / 1.541195 (-0.229253)	1.332394 / 1.468490 (-0.136096)	0.566947 / 4.584777 (-4.017830)	2.383291 / 3.745712 (-1.362421)	2.754779 / 5.269862 (-2.515083)	1.725164 / 4.565676 (-2.840512)	0.062124 / 0.424275 (-0.362152)	0.005111 / 0.007607 (-0.002496)	0.334217 / 0.226044 (0.108173)	3.271619 / 2.268929 (1.002690)	1.776906 / 55.444624 (-53.667718)	1.519238 / 6.876477 (-5.357239)	1.534722 / 2.142072 (-0.607351)	0.646143 / 4.805227 (-4.159084)	0.117015 / 6.500664 (-6.383649)	0.042578 / 0.075469 (-0.032891)

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)	0.948488 / 1.841788 (-0.893299)	11.598027 / 8.074308 (3.523719)	10.269199 / 10.191392 (0.077807)	0.144887 / 0.680424 (-0.535537)	0.014745 / 0.534201 (-0.519456)	0.289185 / 0.579283 (-0.290099)	0.275243 / 0.434364 (-0.159120)	0.328088 / 0.540337 (-0.212250)	0.430161 / 1.386936 (-0.956775)

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)	0.005020 / 0.011353 (-0.006333)	0.003246 / 0.011008 (-0.007762)	0.049810 / 0.038508 (0.011302)	0.032215 / 0.023109 (0.009105)	0.271033 / 0.275898 (-0.004866)	0.294957 / 0.323480 (-0.028523)	0.004192 / 0.007986 (-0.003793)	0.002652 / 0.004328 (-0.001677)	0.049132 / 0.004250 (0.044881)	0.047818 / 0.037052 (0.010766)	0.292370 / 0.258489 (0.033881)	0.316142 / 0.293841 (0.022301)	0.049539 / 0.128546 (-0.079007)	0.010533 / 0.075646 (-0.065113)	0.058131 / 0.419271 (-0.361141)	0.033807 / 0.043533 (-0.009725)	0.277623 / 0.255139 (0.022484)	0.292294 / 0.283200 (0.009094)	0.021110 / 0.141683 (-0.120573)	1.160997 / 1.452155 (-0.291157)	1.213553 / 1.492716 (-0.279163)

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)	0.098220 / 0.018006 (0.080214)	0.312342 / 0.000490 (0.311852)	0.000231 / 0.000200 (0.000031)	0.000052 / 0.000054 (-0.000002)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.022893 / 0.037411 (-0.014519)	0.075572 / 0.014526 (0.061046)	0.088357 / 0.176557 (-0.088199)	0.126354 / 0.737135 (-0.610782)	0.089763 / 0.296338 (-0.206575)

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)	0.284368 / 0.215209 (0.069159)	2.785497 / 2.077655 (0.707842)	1.499364 / 1.504120 (-0.004756)	1.376020 / 1.541195 (-0.165175)	1.394270 / 1.468490 (-0.074220)	0.571945 / 4.584777 (-4.012832)	2.419148 / 3.745712 (-1.326564)	2.796974 / 5.269862 (-2.472887)	1.749531 / 4.565676 (-2.816145)	0.064088 / 0.424275 (-0.360187)	0.005294 / 0.007607 (-0.002313)	0.336250 / 0.226044 (0.110206)	3.315933 / 2.268929 (1.047004)	1.877165 / 55.444624 (-53.567459)	1.592336 / 6.876477 (-5.284140)	1.599979 / 2.142072 (-0.542093)	0.655617 / 4.805227 (-4.149610)	0.117636 / 6.500664 (-6.383028)	0.040813 / 0.075469 (-0.034656)

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)	0.976887 / 1.841788 (-0.864901)	12.668753 / 8.074308 (4.594445)	11.081253 / 10.191392 (0.889861)	0.134494 / 0.680424 (-0.545930)	0.016053 / 0.534201 (-0.518148)	0.291607 / 0.579283 (-0.287676)	0.287726 / 0.434364 (-0.146638)	0.328108 / 0.540337 (-0.212229)	0.425194 / 1.386936 (-0.961742)