Title: datasets.filesystems: fix is_remote_filesystems
Author: ap-- (CONTRIBUTOR)
State: closed
Created: 2023-10-23T09:17:54Z

Close #6330, close #6333.

`fsspec.implementations.LocalFilesystem.protocol`
was changed from `str` "file" to `tuple[str,...]` ("file", "local") in `fsspec>=2023.10.0`

This commit supports both styles.

Comments:
_The documentation is not available anymore as the PR was closed or merged._

<details>
<summary>Show benchmarks</summary>

PyArrow==8.0.0

<details>
<summary>Show updated benchmarks!</summary>

### 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) | 0.006648 / 0.011353 (-0.004705) | 0.004104 / 0.011008 (-0.006904) | 0.084718 / 0.038508 (0.046210) | 0.075342 / 0.023109 (0.052232) | 0.332624 / 0.275898 (0.056726) | 0.376758 / 0.323480 (0.053278) | 0.005371 / 0.007986 (-0.002614) | 0.003317 / 0.004328 (-0.001011) | 0.065153 / 0.004250 (0.060902) | 0.055270 / 0.037052 (0.018218) | 0.342410 / 0.258489 (0.083920) | 0.397484 / 0.293841 (0.103643) | 0.031168 / 0.128546 (-0.097379) | 0.008545 / 0.075646 (-0.067101) | 0.297641 / 0.419271 (-0.121631) | 0.052404 / 0.043533 (0.008871) | 0.327633 / 0.255139 (0.072494) | 0.362177 / 0.283200 (0.078977) | 0.025056 / 0.141683 (-0.116627) | 1.459023 / 1.452155 (0.006868) | 1.529651 / 1.492716 (0.036935) |

### 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) | 0.242838 / 0.018006 (0.224832) | 0.451007 / 0.000490 (0.450517) | 0.013732 / 0.000200 (0.013532) | 0.000345 / 0.000054 (0.000290) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.028068 / 0.037411 (-0.009343) | 0.081970 / 0.014526 (0.067444) | 0.096148 / 0.176557 (-0.080409) | 0.151758 / 0.737135 (-0.585377) | 0.095617 / 0.296338 (-0.200721) |

### 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) | 0.389188 / 0.215209 (0.173979) | 3.867506 / 2.077655 (1.789852) | 1.941912 / 1.504120 (0.437792) | 1.759270 / 1.541195 (0.218076) | 1.774714 / 1.468490 (0.306224) | 0.476587 / 4.584777 (-4.108190) | 3.539342 / 3.745712 (-0.206370) | 3.434389 / 5.269862 (-1.835472) | 2.047581 / 4.565676 (-2.518096) | 0.056322 / 0.424275 (-0.367954) | 0.007286 / 0.007607 (-0.000321) | 0.461826 / 0.226044 (0.235781) | 4.604179 / 2.268929 (2.335251) | 2.405267 / 55.444624 (-53.039357) | 2.133998 / 6.876477 (-4.742479) | 2.187724 / 2.142072 (0.045652) | 0.566578 / 4.805227 (-4.238650) | 0.130007 / 6.500664 (-6.370657) | 0.059685 / 0.075469 (-0.015784) |

### 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) | 1.256204 / 1.841788 (-0.585584) | 18.829475 / 8.074308 (10.755167) | 13.937879 / 10.191392 (3.746487) | 0.163948 / 0.680424 (-0.516475) | 0.018118 / 0.534201 (-0.516083) | 0.389369 / 0.579283 (-0.189914) | 0.399988 / 0.434364 (-0.034376) | 0.459504 / 0.540337 (-0.080834) | 0.674696 / 1.386936 (-0.712240) |

</details>
PyArrow==latest

<details>
<summary>Show updated benchmarks!</summary>

### 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) | 0.006806 / 0.011353 (-0.004547) | 0.004103 / 0.011008 (-0.006905) | 0.064477 / 0.038508 (0.025969) | 0.079514 / 0.023109 (0.056405) | 0.391657 / 0.275898 (0.115759) | 0.422997 / 0.323480 (0.099517) | 0.005485 / 0.007986 (-0.002501) | 0.003461 / 0.004328 (-0.000868) | 0.064621 / 0.004250 (0.060371) | 0.057686 / 0.037052 (0.020633) | 0.396885 / 0.258489 (0.138396) | 0.431508 / 0.293841 (0.137667) | 0.032305 / 0.128546 (-0.096241) | 0.008617 / 0.075646 (-0.067030) | 0.071577 / 0.419271 (-0.347694) | 0.047769 / 0.043533 (0.004236) | 0.394037 / 0.255139 (0.138898) | 0.412593 / 0.283200 (0.129393) | 0.023800 / 0.141683 (-0.117883) | 1.479114 / 1.452155 (0.026959) | 1.562422 / 1.492716 (0.069706) |

### 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) | 0.229822 / 0.018006 (0.211816) | 0.452465 / 0.000490 (0.451975) | 0.005877 / 0.000200 (0.005677) | 0.000097 / 0.000054 (0.000043) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.033528 / 0.037411 (-0.003884) | 0.091819 / 0.014526 (0.077294) | 0.106188 / 0.176557 (-0.070368) | 0.159480 / 0.737135 (-0.577655) | 0.106326 / 0.296338 (-0.190013) |

### 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) | 0.427396 / 0.215209 (0.212187) | 4.275196 / 2.077655 (2.197541) | 2.287446 / 1.504120 (0.783326) | 2.137089 / 1.541195 (0.595894) | 2.198439 / 1.468490 (0.729949) | 0.491006 / 4.584777 (-4.093771) | 3.531067 / 3.745712 (-0.214645) | 3.264357 / 5.269862 (-2.005505) | 2.047760 / 4.565676 (-2.517916) | 0.057982 / 0.424275 (-0.366293) | 0.007278 / 0.007607 (-0.000329) | 0.507471 / 0.226044 (0.281426) | 5.073901 / 2.268929 (2.804973) | 2.781799 / 55.444624 (-52.662825) | 2.410759 / 6.876477 (-4.465718) | 2.623331 / 2.142072 (0.481258) | 0.601601 / 4.805227 (-4.203626) | 0.131461 / 6.500664 (-6.369204) | 0.060045 / 0.075469 (-0.015424) |

### 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) | 1.372946 / 1.841788 (-0.468842) | 19.560818 / 8.074308 (11.486509) | 14.388468 / 10.191392 (4.197076) | 0.177310 / 0.680424 (-0.503114) | 0.020233 / 0.534201 (-0.513967) | 0.395938 / 0.579283 (-0.183345) | 0.418336 / 0.434364 (-0.016028) | 0.471731 / 0.540337 (-0.068607) | 0.684679 / 1.386936 (-0.702257) |

</details>
</details>

![](https://cml.dev/watermark.png#4bedb7dcbaedd292ae5764f0fe6d44c16e1c2c10 "CML watermark")


We did a patch release containing your fix @ap-- !