Title: Always return list in `list_datasets`
Author: mariosasko (COLLABORATOR)
State: closed
Created: 2023-06-19T13:07:08Z

Fix #5925 

Plus, deprecate `list_datasets`/`inspect_dataset` in favor of `huggingface_hub.list_datasets`/"git clone workflow" (downloads data files)

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) | 0.006795 / 0.011353 (-0.004558) | 0.004170 / 0.011008 (-0.006838) | 0.098698 / 0.038508 (0.060190) | 0.045393 / 0.023109 (0.022284) | 0.309205 / 0.275898 (0.033307) | 0.361333 / 0.323480 (0.037853) | 0.006009 / 0.007986 (-0.001977) | 0.003334 / 0.004328 (-0.000995) | 0.075071 / 0.004250 (0.070821) | 0.062587 / 0.037052 (0.025535) | 0.322395 / 0.258489 (0.063906) | 0.360499 / 0.293841 (0.066659) | 0.032243 / 0.128546 (-0.096303) | 0.008768 / 0.075646 (-0.066878) | 0.329799 / 0.419271 (-0.089472) | 0.062261 / 0.043533 (0.018728) | 0.298112 / 0.255139 (0.042973) | 0.322815 / 0.283200 (0.039615) | 0.032348 / 0.141683 (-0.109335) | 1.445807 / 1.452155 (-0.006347) | 1.528768 / 1.492716 (0.036051) |

### 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) | 0.195701 / 0.018006 (0.177695) | 0.437042 / 0.000490 (0.436552) | 0.003867 / 0.000200 (0.003667) | 0.000080 / 0.000054 (0.000026) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.026713 / 0.037411 (-0.010698) | 0.109548 / 0.014526 (0.095022) | 0.119216 / 0.176557 (-0.057341) | 0.178947 / 0.737135 (-0.558188) | 0.125224 / 0.296338 (-0.171114) |

### 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) | 0.400885 / 0.215209 (0.185676) | 3.991223 / 2.077655 (1.913568) | 1.818449 / 1.504120 (0.314329) | 1.609285 / 1.541195 (0.068090) | 1.666675 / 1.468490 (0.198184) | 0.531486 / 4.584777 (-4.053291) | 3.770142 / 3.745712 (0.024430) | 3.057189 / 5.269862 (-2.212673) | 1.517491 / 4.565676 (-3.048186) | 0.065782 / 0.424275 (-0.358493) | 0.011251 / 0.007607 (0.003644) | 0.504277 / 0.226044 (0.278233) | 5.038979 / 2.268929 (2.770050) | 2.254717 / 55.444624 (-53.189908) | 1.929743 / 6.876477 (-4.946734) | 2.080051 / 2.142072 (-0.062022) | 0.656831 / 4.805227 (-4.148396) | 0.142860 / 6.500664 (-6.357804) | 0.063057 / 0.075469 (-0.012412) |

### 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) | 1.208819 / 1.841788 (-0.632969) | 14.456966 / 8.074308 (6.382658) | 12.839799 / 10.191392 (2.648407) | 0.164361 / 0.680424 (-0.516063) | 0.017330 / 0.534201 (-0.516871) | 0.397384 / 0.579283 (-0.181899) | 0.422704 / 0.434364 (-0.011660) | 0.472065 / 0.540337 (-0.068273) | 0.576960 / 1.386936 (-0.809976) |

</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) | 0.006950 / 0.011353 (-0.004403) | 0.004012 / 0.011008 (-0.006997) | 0.076050 / 0.038508 (0.037542) | 0.046646 / 0.023109 (0.023537) | 0.353813 / 0.275898 (0.077915) | 0.417111 / 0.323480 (0.093631) | 0.005422 / 0.007986 (-0.002564) | 0.003356 / 0.004328 (-0.000972) | 0.076662 / 0.004250 (0.072411) | 0.055018 / 0.037052 (0.017966) | 0.371561 / 0.258489 (0.113072) | 0.410471 / 0.293841 (0.116630) | 0.031860 / 0.128546 (-0.096686) | 0.008754 / 0.075646 (-0.066893) | 0.083192 / 0.419271 (-0.336079) | 0.050479 / 0.043533 (0.006946) | 0.351725 / 0.255139 (0.096586) | 0.371596 / 0.283200 (0.088396) | 0.023042 / 0.141683 (-0.118641) | 1.480533 / 1.452155 (0.028379) | 1.545970 / 1.492716 (0.053254) |

### 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) | 0.220095 / 0.018006 (0.202089) | 0.441550 / 0.000490 (0.441061) | 0.000375 / 0.000200 (0.000175) | 0.000056 / 0.000054 (0.000002) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.029527 / 0.037411 (-0.007884) | 0.111645 / 0.014526 (0.097119) | 0.125732 / 0.176557 (-0.050825) | 0.177322 / 0.737135 (-0.559813) | 0.128620 / 0.296338 (-0.167718) |

### 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) | 0.432415 / 0.215209 (0.217206) | 4.314381 / 2.077655 (2.236726) | 2.079450 / 1.504120 (0.575331) | 1.893139 / 1.541195 (0.351944) | 1.951363 / 1.468490 (0.482873) | 0.531466 / 4.584777 (-4.053311) | 3.716860 / 3.745712 (-0.028852) | 1.850111 / 5.269862 (-3.419750) | 1.100676 / 4.565676 (-3.465000) | 0.066247 / 0.424275 (-0.358028) | 0.011503 / 0.007607 (0.003896) | 0.537208 / 0.226044 (0.311164) | 5.367560 / 2.268929 (3.098631) | 2.543697 / 55.444624 (-52.900927) | 2.221670 / 6.876477 (-4.654806) | 2.252009 / 2.142072 (0.109937) | 0.658509 / 4.805227 (-4.146718) | 0.142345 / 6.500664 (-6.358319) | 0.064701 / 0.075469 (-0.010768) |

### 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) | 1.266442 / 1.841788 (-0.575346) | 15.105953 / 8.074308 (7.031645) | 14.288229 / 10.191392 (4.096837) | 0.161182 / 0.680424 (-0.519242) | 0.017074 / 0.534201 (-0.517127) | 0.399464 / 0.579283 (-0.179819) | 0.419459 / 0.434364 (-0.014905) | 0.467553 / 0.540337 (-0.072784) | 0.566337 / 1.386936 (-0.820599) |

</details>
</details>

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