Issue: Don't expand_info in HF glob
State: closed
Author: lhoestq

Finally fix https://github.com/huggingface/datasets/issues/5537

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6469). All of your documentation changes will be reflected on that endpoint.

Merging this one for now, but lmk if you had other optimizations in mind for the next version of `huggingface_hub`

<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) | 0.004998 / 0.011353 (-0.006355) | 0.003523 / 0.011008 (-0.007486) | 0.064932 / 0.038508 (0.026424) | 0.050107 / 0.023109 (0.026998) | 0.253715 / 0.275898 (-0.022183) | 0.275364 / 0.323480 (-0.048116) | 0.003902 / 0.007986 (-0.004084) | 0.002716 / 0.004328 (-0.001612) | 0.048458 / 0.004250 (0.044208) | 0.037802 / 0.037052 (0.000750) | 0.262328 / 0.258489 (0.003839) | 0.285911 / 0.293841 (-0.007930) | 0.027112 / 0.128546 (-0.101435) | 0.010780 / 0.075646 (-0.064867) | 0.206447 / 0.419271 (-0.212824) | 0.035771 / 0.043533 (-0.007761) | 0.255031 / 0.255139 (-0.000108) | 0.270530 / 0.283200 (-0.012670) | 0.017152 / 0.141683 (-0.124530) | 1.094734 / 1.452155 (-0.357421) | 1.163480 / 1.492716 (-0.329237) |

### 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) | 0.092944 / 0.018006 (0.074938) | 0.301042 / 0.000490 (0.300553) | 0.000238 / 0.000200 (0.000038) | 0.000049 / 0.000054 (-0.000006) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.019090 / 0.037411 (-0.018321) | 0.061046 / 0.014526 (0.046520) | 0.073330 / 0.176557 (-0.103227) | 0.121124 / 0.737135 (-0.616012) | 0.080544 / 0.296338 (-0.215795) |

### 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) | 0.323866 / 0.215209 (0.108657) | 2.797727 / 2.077655 (0.720072) | 1.502994 / 1.504120 (-0.001126) | 1.376177 / 1.541195 (-0.165018) | 1.422741 / 1.468490 (-0.045749) | 0.562990 / 4.584777 (-4.021786) | 2.431781 / 3.745712 (-1.313931) | 2.783226 / 5.269862 (-2.486635) | 1.788055 / 4.565676 (-2.777621) | 0.064206 / 0.424275 (-0.360069) | 0.004989 / 0.007607 (-0.002618) | 0.338282 / 0.226044 (0.112237) | 3.356226 / 2.268929 (1.087297) | 1.855644 / 55.444624 (-53.588980) | 1.580876 / 6.876477 (-5.295601) | 1.617418 / 2.142072 (-0.524655) | 0.636816 / 4.805227 (-4.168411) | 0.117680 / 6.500664 (-6.382985) | 0.042560 / 0.075469 (-0.032909) |

### 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) | 0.956410 / 1.841788 (-0.885377) | 11.764886 / 8.074308 (3.690578) | 10.535801 / 10.191392 (0.344409) | 0.137797 / 0.680424 (-0.542627) | 0.014368 / 0.534201 (-0.519833) | 0.286213 / 0.579283 (-0.293070) | 0.267093 / 0.434364 (-0.167271) | 0.334802 / 0.540337 (-0.205535) | 0.441866 / 1.386936 (-0.945070) |

</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) | 0.005348 / 0.011353 (-0.006005) | 0.003551 / 0.011008 (-0.007458) | 0.049226 / 0.038508 (0.010718) | 0.052072 / 0.023109 (0.028963) | 0.268025 / 0.275898 (-0.007873) | 0.289968 / 0.323480 (-0.033512) | 0.004034 / 0.007986 (-0.003952) | 0.002675 / 0.004328 (-0.001653) | 0.048099 / 0.004250 (0.043848) | 0.040141 / 0.037052 (0.003089) | 0.272974 / 0.258489 (0.014485) | 0.296097 / 0.293841 (0.002256) | 0.028972 / 0.128546 (-0.099575) | 0.010689 / 0.075646 (-0.064957) | 0.057853 / 0.419271 (-0.361418) | 0.032488 / 0.043533 (-0.011045) | 0.272018 / 0.255139 (0.016879) | 0.287179 / 0.283200 (0.003980) | 0.018446 / 0.141683 (-0.123237) | 1.140346 / 1.452155 (-0.311809) | 1.247743 / 1.492716 (-0.244974) |

### 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) | 0.091987 / 0.018006 (0.073980) | 0.300527 / 0.000490 (0.300037) | 0.000224 / 0.000200 (0.000024) | 0.000044 / 0.000054 (-0.000010) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.021390 / 0.037411 (-0.016021) | 0.068768 / 0.014526 (0.054242) | 0.080798 / 0.176557 (-0.095759) | 0.119081 / 0.737135 (-0.618054) | 0.082461 / 0.296338 (-0.213878) |

### 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) | 0.286631 / 0.215209 (0.071422) | 2.804633 / 2.077655 (0.726978) | 1.574122 / 1.504120 (0.070002) | 1.459994 / 1.541195 (-0.081201) | 1.499739 / 1.468490 (0.031249) | 0.579595 / 4.584777 (-4.005182) | 2.426407 / 3.745712 (-1.319306) | 2.917994 / 5.269862 (-2.351868) | 1.846439 / 4.565676 (-2.719238) | 0.063274 / 0.424275 (-0.361001) | 0.005028 / 0.007607 (-0.002579) | 0.341114 / 0.226044 (0.115070) | 3.402677 / 2.268929 (1.133748) | 1.940980 / 55.444624 (-53.503645) | 1.651902 / 6.876477 (-5.224575) | 1.677037 / 2.142072 (-0.465036) | 0.651576 / 4.805227 (-4.153651) | 0.116398 / 6.500664 (-6.384266) | 0.041060 / 0.075469 (-0.034409) |

### 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) | 0.973278 / 1.841788 (-0.868509) | 12.248332 / 8.074308 (4.174024) | 10.830627 / 10.191392 (0.639235) | 0.143146 / 0.680424 (-0.537278) | 0.016249 / 0.534201 (-0.517952) | 0.298563 / 0.579283 (-0.280720) | 0.278643 / 0.434364 (-0.155721) | 0.338206 / 0.540337 (-0.202132) | 0.589485 / 1.386936 (-0.797451) |

</details>
</details>

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