Add pre-commit config yaml file to enable automatic code formatting

@huggingface/datasets do you think it would be useful? Motivation - sometimes PRs are like 30% "fix: style" commits :)

If so - I need to double check the config but for me locally it works as expected.


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

Better yet have someone enable pre-commit CI https://pre-commit.ci/ and it will apply the pre-commit fixes to the PR automatically as an additional commit.

@Skylion007 hi! I agree with @nateraw here, I'd better not force to use pre-commit so I'm not setting it up in the CI for now. And regarding end-of-file - currently it's being done by `black`.  


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

PyArrow==6.0.0

<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) | 0.008704 / 0.011353 (-0.002649) | 0.004448 / 0.011008 (-0.006560) | 0.099530 / 0.038508 (0.061022) | 0.029739 / 0.023109 (0.006629) | 0.329267 / 0.275898 (0.053369) | 0.368805 / 0.323480 (0.045325) | 0.006852 / 0.007986 (-0.001133) | 0.004575 / 0.004328 (0.000246) | 0.076838 / 0.004250 (0.072588) | 0.033885 / 0.037052 (-0.003167) | 0.336340 / 0.258489 (0.077851) | 0.384880 / 0.293841 (0.091039) | 0.034051 / 0.128546 (-0.094495) | 0.011638 / 0.075646 (-0.064009) | 0.321650 / 0.419271 (-0.097622) | 0.041202 / 0.043533 (-0.002330) | 0.330841 / 0.255139 (0.075702) | 0.361329 / 0.283200 (0.078130) | 0.084864 / 0.141683 (-0.056819) | 1.454005 / 1.452155 (0.001850) | 1.542167 / 1.492716 (0.049451) |

### 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) | 0.196207 / 0.018006 (0.178200) | 0.400675 / 0.000490 (0.400185) | 0.000403 / 0.000200 (0.000203) | 0.000059 / 0.000054 (0.000005) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022694 / 0.037411 (-0.014717) | 0.095139 / 0.014526 (0.080613) | 0.104129 / 0.176557 (-0.072427) | 0.168688 / 0.737135 (-0.568447) | 0.109243 / 0.296338 (-0.187096) |

### 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) | 0.427520 / 0.215209 (0.212311) | 4.237726 / 2.077655 (2.160071) | 2.191887 / 1.504120 (0.687767) | 1.987750 / 1.541195 (0.446555) | 1.996540 / 1.468490 (0.528050) | 0.696416 / 4.584777 (-3.888361) | 3.454536 / 3.745712 (-0.291176) | 2.023600 / 5.269862 (-3.246261) | 1.336394 / 4.565676 (-3.229282) | 0.082933 / 0.424275 (-0.341342) | 0.012572 / 0.007607 (0.004965) | 0.534330 / 0.226044 (0.308285) | 5.347588 / 2.268929 (3.078659) | 2.640397 / 55.444624 (-52.804228) | 2.338266 / 6.876477 (-4.538211) | 2.431969 / 2.142072 (0.289897) | 0.821335 / 4.805227 (-3.983893) | 0.151905 / 6.500664 (-6.348759) | 0.067983 / 0.075469 (-0.007486) |

### 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) | 1.228841 / 1.841788 (-0.612947) | 13.660437 / 8.074308 (5.586128) | 13.729442 / 10.191392 (3.538050) | 0.165835 / 0.680424 (-0.514589) | 0.028753 / 0.534201 (-0.505448) | 0.400143 / 0.579283 (-0.179140) | 0.403714 / 0.434364 (-0.030650) | 0.492168 / 0.540337 (-0.048170) | 0.581151 / 1.386936 (-0.805785) |

</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) | 0.006289 / 0.011353 (-0.005064) | 0.004419 / 0.011008 (-0.006589) | 0.077220 / 0.038508 (0.038712) | 0.027170 / 0.023109 (0.004060) | 0.344988 / 0.275898 (0.069090) | 0.374150 / 0.323480 (0.050670) | 0.004842 / 0.007986 (-0.003144) | 0.003289 / 0.004328 (-0.001039) | 0.076200 / 0.004250 (0.071950) | 0.036287 / 0.037052 (-0.000766) | 0.345764 / 0.258489 (0.087275) | 0.387439 / 0.293841 (0.093599) | 0.031547 / 0.128546 (-0.096999) | 0.011586 / 0.075646 (-0.064060) | 0.086599 / 0.419271 (-0.332672) | 0.042338 / 0.043533 (-0.001195) | 0.355384 / 0.255139 (0.100246) | 0.369474 / 0.283200 (0.086275) | 0.090945 / 0.141683 (-0.050738) | 1.488632 / 1.452155 (0.036477) | 1.554606 / 1.492716 (0.061890) |

### 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) | 0.212962 / 0.018006 (0.194956) | 0.399647 / 0.000490 (0.399157) | 0.003055 / 0.000200 (0.002856) | 0.000083 / 0.000054 (0.000029) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.024349 / 0.037411 (-0.013062) | 0.100342 / 0.014526 (0.085817) | 0.105657 / 0.176557 (-0.070899) | 0.175139 / 0.737135 (-0.561997) | 0.110014 / 0.296338 (-0.186324) |

### 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) | 0.434785 / 0.215209 (0.219575) | 4.346950 / 2.077655 (2.269295) | 2.045411 / 1.504120 (0.541291) | 1.844258 / 1.541195 (0.303064) | 1.889503 / 1.468490 (0.421013) | 0.704530 / 4.584777 (-3.880247) | 3.362435 / 3.745712 (-0.383277) | 2.797205 / 5.269862 (-2.472656) | 1.504431 / 4.565676 (-3.061245) | 0.083331 / 0.424275 (-0.340945) | 0.012274 / 0.007607 (0.004666) | 0.531123 / 0.226044 (0.305078) | 5.322588 / 2.268929 (3.053660) | 2.483875 / 55.444624 (-52.960750) | 2.147218 / 6.876477 (-4.729258) | 2.164024 / 2.142072 (0.021952) | 0.807191 / 4.805227 (-3.998036) | 0.151189 / 6.500664 (-6.349475) | 0.068027 / 0.075469 (-0.007442) |

### 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) | 1.316001 / 1.841788 (-0.525787) | 13.892785 / 8.074308 (5.818477) | 13.485982 / 10.191392 (3.294590) | 0.138904 / 0.680424 (-0.541520) | 0.016748 / 0.534201 (-0.517453) | 0.379840 / 0.579283 (-0.199443) | 0.384854 / 0.434364 (-0.049510) | 0.464275 / 0.540337 (-0.076063) | 0.553622 / 1.386936 (-0.833314) |

</details>
</details>

![](https://cml.dev/watermark.png#a940972a9a38543b2066129dc6e7987e08dca082 "CML watermark")


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

PyArrow==6.0.0

<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) | 0.009179 / 0.011353 (-0.002174) | 0.005080 / 0.011008 (-0.005929) | 0.099061 / 0.038508 (0.060553) | 0.035252 / 0.023109 (0.012143) | 0.293496 / 0.275898 (0.017598) | 0.360365 / 0.323480 (0.036886) | 0.007757 / 0.007986 (-0.000229) | 0.003985 / 0.004328 (-0.000343) | 0.076021 / 0.004250 (0.071771) | 0.042286 / 0.037052 (0.005233) | 0.316542 / 0.258489 (0.058053) | 0.341711 / 0.293841 (0.047870) | 0.037970 / 0.128546 (-0.090576) | 0.011977 / 0.075646 (-0.063670) | 0.333341 / 0.419271 (-0.085931) | 0.049211 / 0.043533 (0.005678) | 0.297401 / 0.255139 (0.042262) | 0.313424 / 0.283200 (0.030224) | 0.105719 / 0.141683 (-0.035964) | 1.487879 / 1.452155 (0.035724) | 1.529785 / 1.492716 (0.037068) |

### 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) | 0.201062 / 0.018006 (0.183056) | 0.438024 / 0.000490 (0.437534) | 0.002129 / 0.000200 (0.001929) | 0.000083 / 0.000054 (0.000028) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.026422 / 0.037411 (-0.010989) | 0.104863 / 0.014526 (0.090337) | 0.114934 / 0.176557 (-0.061623) | 0.179173 / 0.737135 (-0.557962) | 0.119734 / 0.296338 (-0.176604) |

### 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) | 0.397195 / 0.215209 (0.181986) | 3.959945 / 2.077655 (1.882290) | 1.794059 / 1.504120 (0.289939) | 1.606814 / 1.541195 (0.065619) | 1.674681 / 1.468490 (0.206191) | 0.680130 / 4.584777 (-3.904646) | 3.742730 / 3.745712 (-0.002982) | 2.021793 / 5.269862 (-3.248069) | 1.322726 / 4.565676 (-3.242950) | 0.084519 / 0.424275 (-0.339756) | 0.012012 / 0.007607 (0.004405) | 0.510076 / 0.226044 (0.284032) | 5.084163 / 2.268929 (2.815234) | 2.241032 / 55.444624 (-53.203592) | 1.911936 / 6.876477 (-4.964540) | 1.947992 / 2.142072 (-0.194080) | 0.838779 / 4.805227 (-3.966448) | 0.165103 / 6.500664 (-6.335561) | 0.060722 / 0.075469 (-0.014747) |

### 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) | 1.180274 / 1.841788 (-0.661514) | 14.285364 / 8.074308 (6.211056) | 12.941205 / 10.191392 (2.749813) | 0.153815 / 0.680424 (-0.526609) | 0.028554 / 0.534201 (-0.505647) | 0.441551 / 0.579283 (-0.137732) | 0.434906 / 0.434364 (0.000542) | 0.516120 / 0.540337 (-0.024217) | 0.603062 / 1.386936 (-0.783874) |

</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) | 0.007287 / 0.011353 (-0.004066) | 0.004998 / 0.011008 (-0.006010) | 0.074997 / 0.038508 (0.036489) | 0.033209 / 0.023109 (0.010100) | 0.336836 / 0.275898 (0.060938) | 0.365562 / 0.323480 (0.042082) | 0.005739 / 0.007986 (-0.002246) | 0.003942 / 0.004328 (-0.000387) | 0.074681 / 0.004250 (0.070430) | 0.049530 / 0.037052 (0.012478) | 0.335642 / 0.258489 (0.077153) | 0.388874 / 0.293841 (0.095033) | 0.037198 / 0.128546 (-0.091349) | 0.011983 / 0.075646 (-0.063664) | 0.087601 / 0.419271 (-0.331671) | 0.053761 / 0.043533 (0.010228) | 0.334142 / 0.255139 (0.079003) | 0.351348 / 0.283200 (0.068148) | 0.107462 / 0.141683 (-0.034221) | 1.497015 / 1.452155 (0.044860) | 1.608287 / 1.492716 (0.115571) |

### 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) | 0.255395 / 0.018006 (0.237389) | 0.439141 / 0.000490 (0.438651) | 0.021391 / 0.000200 (0.021191) | 0.000230 / 0.000054 (0.000176) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.028331 / 0.037411 (-0.009080) | 0.108744 / 0.014526 (0.094218) | 0.118201 / 0.176557 (-0.058355) | 0.189556 / 0.737135 (-0.547579) | 0.123112 / 0.296338 (-0.173226) |

### 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) | 0.431394 / 0.215209 (0.216185) | 4.296121 / 2.077655 (2.218466) | 2.126371 / 1.504120 (0.622251) | 1.978178 / 1.541195 (0.436983) | 2.082674 / 1.468490 (0.614184) | 0.701789 / 4.584777 (-3.882988) | 3.791495 / 3.745712 (0.045783) | 2.115267 / 5.269862 (-3.154594) | 1.342159 / 4.565676 (-3.223517) | 0.088132 / 0.424275 (-0.336143) | 0.011903 / 0.007607 (0.004295) | 0.528398 / 0.226044 (0.302354) | 5.270077 / 2.268929 (3.001148) | 2.498860 / 55.444624 (-52.945765) | 2.155515 / 6.876477 (-4.720962) | 2.192866 / 2.142072 (0.050793) | 0.859596 / 4.805227 (-3.945631) | 0.170544 / 6.500664 (-6.330120) | 0.063883 / 0.075469 (-0.011587) |

### 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) | 1.240679 / 1.841788 (-0.601109) | 14.497379 / 8.074308 (6.423071) | 12.881417 / 10.191392 (2.690025) | 0.147295 / 0.680424 (-0.533129) | 0.017465 / 0.534201 (-0.516736) | 0.424695 / 0.579283 (-0.154588) | 0.414929 / 0.434364 (-0.019435) | 0.536079 / 0.540337 (-0.004259) | 0.638245 / 1.386936 (-0.748691) |

</details>
</details>

![](https://cml.dev/watermark.png#a940972a9a38543b2066129dc6e7987e08dca082 "CML watermark")


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

PyArrow==6.0.0

<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) | 0.008806 / 0.011353 (-0.002547) | 0.004712 / 0.011008 (-0.006297) | 0.102383 / 0.038508 (0.063875) | 0.030260 / 0.023109 (0.007151) | 0.330175 / 0.275898 (0.054277) | 0.376816 / 0.323480 (0.053337) | 0.008065 / 0.007986 (0.000079) | 0.003534 / 0.004328 (-0.000794) | 0.078824 / 0.004250 (0.074573) | 0.036704 / 0.037052 (-0.000349) | 0.331848 / 0.258489 (0.073359) | 0.351031 / 0.293841 (0.057190) | 0.033406 / 0.128546 (-0.095140) | 0.011543 / 0.075646 (-0.064103) | 0.322114 / 0.419271 (-0.097157) | 0.041249 / 0.043533 (-0.002284) | 0.309413 / 0.255139 (0.054274) | 0.329156 / 0.283200 (0.045956) | 0.088636 / 0.141683 (-0.053047) | 1.508226 / 1.452155 (0.056071) | 1.557203 / 1.492716 (0.064487) |

### 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) | 0.196696 / 0.018006 (0.178690) | 0.426360 / 0.000490 (0.425870) | 0.001263 / 0.000200 (0.001064) | 0.000079 / 0.000054 (0.000024) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.023747 / 0.037411 (-0.013664) | 0.100756 / 0.014526 (0.086230) | 0.105817 / 0.176557 (-0.070739) | 0.172573 / 0.737135 (-0.564562) | 0.110705 / 0.296338 (-0.185634) |

### 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) | 0.436913 / 0.215209 (0.221704) | 4.365753 / 2.077655 (2.288099) | 2.201346 / 1.504120 (0.697226) | 1.978800 / 1.541195 (0.437605) | 1.951585 / 1.468490 (0.483094) | 0.699208 / 4.584777 (-3.885569) | 3.381492 / 3.745712 (-0.364220) | 2.966174 / 5.269862 (-2.303687) | 1.487521 / 4.565676 (-3.078156) | 0.082673 / 0.424275 (-0.341602) | 0.012436 / 0.007607 (0.004829) | 0.553276 / 0.226044 (0.327232) | 5.554081 / 2.268929 (3.285153) | 2.653286 / 55.444624 (-52.791339) | 2.404788 / 6.876477 (-4.471689) | 2.484610 / 2.142072 (0.342537) | 0.817073 / 4.805227 (-3.988154) | 0.151619 / 6.500664 (-6.349045) | 0.068259 / 0.075469 (-0.007210) |

### 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) | 1.273481 / 1.841788 (-0.568306) | 13.908825 / 8.074308 (5.834517) | 13.106695 / 10.191392 (2.915303) | 0.139609 / 0.680424 (-0.540815) | 0.028425 / 0.534201 (-0.505776) | 0.395626 / 0.579283 (-0.183657) | 0.405526 / 0.434364 (-0.028838) | 0.465628 / 0.540337 (-0.074709) | 0.542824 / 1.386936 (-0.844112) |

</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) | 0.006821 / 0.011353 (-0.004532) | 0.004570 / 0.011008 (-0.006438) | 0.076568 / 0.038508 (0.038060) | 0.028109 / 0.023109 (0.004999) | 0.342768 / 0.275898 (0.066870) | 0.390680 / 0.323480 (0.067200) | 0.005056 / 0.007986 (-0.002930) | 0.003359 / 0.004328 (-0.000970) | 0.075835 / 0.004250 (0.071584) | 0.038888 / 0.037052 (0.001836) | 0.343489 / 0.258489 (0.085000) | 0.400766 / 0.293841 (0.106925) | 0.031816 / 0.128546 (-0.096730) | 0.011637 / 0.075646 (-0.064009) | 0.085474 / 0.419271 (-0.333797) | 0.041740 / 0.043533 (-0.001793) | 0.342501 / 0.255139 (0.087362) | 0.377467 / 0.283200 (0.094267) | 0.091532 / 0.141683 (-0.050151) | 1.457368 / 1.452155 (0.005213) | 1.537187 / 1.492716 (0.044471) |

### 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) | 0.187507 / 0.018006 (0.169501) | 0.415706 / 0.000490 (0.415217) | 0.001816 / 0.000200 (0.001616) | 0.000072 / 0.000054 (0.000018) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.026251 / 0.037411 (-0.011161) | 0.106609 / 0.014526 (0.092083) | 0.109822 / 0.176557 (-0.066735) | 0.180462 / 0.737135 (-0.556674) | 0.114647 / 0.296338 (-0.181691) |

### 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) | 0.438804 / 0.215209 (0.223595) | 4.387960 / 2.077655 (2.310306) | 2.056804 / 1.504120 (0.552684) | 1.848584 / 1.541195 (0.307389) | 1.939470 / 1.468490 (0.470980) | 0.702539 / 4.584777 (-3.882238) | 3.419535 / 3.745712 (-0.326177) | 1.933889 / 5.269862 (-3.335973) | 1.189631 / 4.565676 (-3.376045) | 0.084105 / 0.424275 (-0.340170) | 0.012520 / 0.007607 (0.004913) | 0.538125 / 0.226044 (0.312081) | 5.370000 / 2.268929 (3.101072) | 2.497487 / 55.444624 (-52.947137) | 2.156054 / 6.876477 (-4.720423) | 2.225909 / 2.142072 (0.083837) | 0.811456 / 4.805227 (-3.993771) | 0.151461 / 6.500664 (-6.349203) | 0.066940 / 0.075469 (-0.008530) |

### 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) | 1.301246 / 1.841788 (-0.540542) | 14.459755 / 8.074308 (6.385447) | 13.147151 / 10.191392 (2.955759) | 0.129236 / 0.680424 (-0.551188) | 0.016427 / 0.534201 (-0.517774) | 0.380047 / 0.579283 (-0.199236) | 0.392217 / 0.434364 (-0.042147) | 0.470338 / 0.540337 (-0.069999) | 0.559800 / 1.386936 (-0.827136) |

</details>
</details>

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