Fix style
Fix C419 issues
_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) | 0.010336 / 0.011353 (-0.001017) | 0.007085 / 0.011008 (-0.003924) | 0.135577 / 0.038508 (0.097069) | 0.038301 / 0.023109 (0.015192) | 0.427919 / 0.275898 (0.152021) | 0.461451 / 0.323480 (0.137971) | 0.008929 / 0.007986 (0.000944) | 0.005260 / 0.004328 (0.000931) | 0.103481 / 0.004250 (0.099231) | 0.054885 / 0.037052 (0.017833) | 0.434956 / 0.258489 (0.176467) | 0.466915 / 0.293841 (0.173074) | 0.052403 / 0.128546 (-0.076144) | 0.021128 / 0.075646 (-0.054518) | 0.466847 / 0.419271 (0.047576) | 0.085096 / 0.043533 (0.041563) | 0.439935 / 0.255139 (0.184796) | 0.453613 / 0.283200 (0.170413) | 0.123913 / 0.141683 (-0.017769) | 1.930114 / 1.452155 (0.477959) | 2.052083 / 1.492716 (0.559366) |

### 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) | 0.280612 / 0.018006 (0.262606) | 0.583937 / 0.000490 (0.583447) | 0.004542 / 0.000200 (0.004342) | 0.000117 / 0.000054 (0.000063) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.035901 / 0.037411 (-0.001510) | 0.160357 / 0.014526 (0.145831) | 0.141661 / 0.176557 (-0.034896) | 0.234915 / 0.737135 (-0.502220) | 0.164110 / 0.296338 (-0.132228) |

### 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) | 0.659901 / 0.215209 (0.444692) | 6.529102 / 2.077655 (4.451447) | 2.635324 / 1.504120 (1.131204) | 2.275777 / 1.541195 (0.734583) | 2.343205 / 1.468490 (0.874715) | 1.241310 / 4.584777 (-3.343467) | 5.683784 / 3.745712 (1.938072) | 3.377162 / 5.269862 (-1.892700) | 2.176404 / 4.565676 (-2.389273) | 0.144303 / 0.424275 (-0.279972) | 0.016352 / 0.007607 (0.008745) | 0.817383 / 0.226044 (0.591339) | 8.148356 / 2.268929 (5.879428) | 3.489277 / 55.444624 (-51.955347) | 2.848086 / 6.876477 (-4.028391) | 2.973304 / 2.142072 (0.831232) | 1.517821 / 4.805227 (-3.287407) | 0.278794 / 6.500664 (-6.221870) | 0.096385 / 0.075469 (0.020916) |

### 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) | 1.631693 / 1.841788 (-0.210095) | 19.564716 / 8.074308 (11.490408) | 23.583081 / 10.191392 (13.391689) | 0.252363 / 0.680424 (-0.428061) | 0.027644 / 0.534201 (-0.506557) | 0.579634 / 0.579283 (0.000351) | 0.645702 / 0.434364 (0.211338) | 0.667302 / 0.540337 (0.126965) | 0.766425 / 1.386936 (-0.620511) |

</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) | 0.011186 / 0.011353 (-0.000167) | 0.007327 / 0.011008 (-0.003681) | 0.105441 / 0.038508 (0.066933) | 0.040293 / 0.023109 (0.017184) | 0.480557 / 0.275898 (0.204659) | 0.522049 / 0.323480 (0.198569) | 0.007779 / 0.007986 (-0.000207) | 0.007338 / 0.004328 (0.003009) | 0.104744 / 0.004250 (0.100494) | 0.059463 / 0.037052 (0.022411) | 0.494055 / 0.258489 (0.235566) | 0.534340 / 0.293841 (0.240499) | 0.062800 / 0.128546 (-0.065746) | 0.020687 / 0.075646 (-0.054959) | 0.135833 / 0.419271 (-0.283439) | 0.087472 / 0.043533 (0.043939) | 0.465019 / 0.255139 (0.209880) | 0.526713 / 0.283200 (0.243513) | 0.131424 / 0.141683 (-0.010259) | 1.884759 / 1.452155 (0.432605) | 2.015817 / 1.492716 (0.523101) |

### 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) | 0.237032 / 0.018006 (0.219026) | 0.605209 / 0.000490 (0.604719) | 0.006653 / 0.000200 (0.006453) | 0.000264 / 0.000054 (0.000210) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.034982 / 0.037411 (-0.002430) | 0.141409 / 0.014526 (0.126883) | 0.151635 / 0.176557 (-0.024922) | 0.217298 / 0.737135 (-0.519837) | 0.171945 / 0.296338 (-0.124393) |

### 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) | 0.678596 / 0.215209 (0.463387) | 6.802432 / 2.077655 (4.724777) | 3.021617 / 1.504120 (1.517497) | 2.722508 / 1.541195 (1.181313) | 2.728194 / 1.468490 (1.259704) | 1.245863 / 4.584777 (-3.338914) | 5.762676 / 3.745712 (2.016963) | 5.497855 / 5.269862 (0.227994) | 2.855764 / 4.565676 (-1.709912) | 0.157359 / 0.424275 (-0.266916) | 0.015562 / 0.007607 (0.007955) | 0.865559 / 0.226044 (0.639515) | 8.553052 / 2.268929 (6.284123) | 3.905544 / 55.444624 (-51.539081) | 3.272528 / 6.876477 (-3.603949) | 3.399481 / 2.142072 (1.257408) | 1.540155 / 4.805227 (-3.265072) | 0.275871 / 6.500664 (-6.224793) | 0.092346 / 0.075469 (0.016877) |

### 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) | 1.753646 / 1.841788 (-0.088142) | 20.074050 / 8.074308 (11.999742) | 23.920391 / 10.191392 (13.728999) | 0.257161 / 0.680424 (-0.423263) | 0.027805 / 0.534201 (-0.506396) | 0.565605 / 0.579283 (-0.013678) | 0.643277 / 0.434364 (0.208914) | 0.633504 / 0.540337 (0.093167) | 0.754317 / 1.386936 (-0.632619) |

</details>
</details>

![](https://cml.dev/watermark.png#2d34c7968ea1a3fe7d4fa7cdf23673e0354f69ac "CML watermark")
