Less zip false positives
Opened by lhoestq (closed)

`zipfile.is_zipfile` return false positives for some Parquet files. It causes errors when loading certain parquet datasets, where some files are considered ZIP files by `zipfile.is_zipfile`

This is a known issue: https://github.com/python/cpython/issues/72680

At first I wanted to rely only on magic numbers, but then I found that someone contributed a [fix to is_zipfile](https://github.com/python/cpython/pull/5053) - do you think we should use it @albertvillanova or not ?

IMO it's ok to rely on magic numbers only for now, since in streaming mode we've had no issue checking only the magic number so far.

Close https://github.com/huggingface/datasets/issues/5639

Comments: <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) | 0.006998 / 0.011353 (-0.004355) | 0.005093 / 0.011008 (-0.005916) | 0.100490 / 0.038508 (0.061982) | 0.032736 / 0.023109 (0.009627) | 0.297738 / 0.275898 (0.021840) | 0.322255 / 0.323480 (-0.001225) | 0.005583 / 0.007986 (-0.002402) | 0.004007 / 0.004328 (-0.000321) | 0.075863 / 0.004250 (0.071613) | 0.044212 / 0.037052 (0.007159) | 0.300033 / 0.258489 (0.041544) | 0.341997 / 0.293841 (0.048156) | 0.036172 / 0.128546 (-0.092374) | 0.012176 / 0.075646 (-0.063471) | 0.356052 / 0.419271 (-0.063220) | 0.050438 / 0.043533 (0.006905) | 0.294677 / 0.255139 (0.039538) | 0.318050 / 0.283200 (0.034850) | 0.104733 / 0.141683 (-0.036950) | 1.435681 / 1.452155 (-0.016474) | 1.534793 / 1.492716 (0.042076) |

### 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) | 0.242815 / 0.018006 (0.224809) | 0.565983 / 0.000490 (0.565494) | 0.006800 / 0.000200 (0.006600) | 0.000124 / 0.000054 (0.000070) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.026548 / 0.037411 (-0.010863) | 0.104816 / 0.014526 (0.090290) | 0.116222 / 0.176557 (-0.060335) | 0.172143 / 0.737135 (-0.564992) | 0.121631 / 0.296338 (-0.174707) |

### 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) | 0.400126 / 0.215209 (0.184917) | 4.004538 / 2.077655 (1.926883) | 1.798822 / 1.504120 (0.294702) | 1.595191 / 1.541195 (0.053996) | 1.645777 / 1.468490 (0.177287) | 0.705643 / 4.584777 (-3.879134) | 3.750887 / 3.745712 (0.005175) | 2.136547 / 5.269862 (-3.133315) | 1.475881 / 4.565676 (-3.089795) | 0.086921 / 0.424275 (-0.337354) | 0.012379 / 0.007607 (0.004771) | 0.505824 / 0.226044 (0.279779) | 5.052364 / 2.268929 (2.783435) | 2.279983 / 55.444624 (-53.164641) | 1.932253 / 6.876477 (-4.944224) | 2.051359 / 2.142072 (-0.090714) | 0.851906 / 4.805227 (-3.953321) | 0.169566 / 6.500664 (-6.331098) | 0.064600 / 0.075469 (-0.010869) |

### 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) | 1.165859 / 1.841788 (-0.675929) | 15.049950 / 8.074308 (6.975642) | 14.095981 / 10.191392 (3.904589) | 0.151779 / 0.680424 (-0.528645) | 0.017537 / 0.534201 (-0.516664) | 0.420164 / 0.579283 (-0.159119) | 0.418932 / 0.434364 (-0.015432) | 0.488749 / 0.540337 (-0.051588) | 0.582359 / 1.386936 (-0.804577) |

</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) | 0.007426 / 0.011353 (-0.003927) | 0.005248 / 0.011008 (-0.005761) | 0.074118 / 0.038508 (0.035610) | 0.034223 / 0.023109 (0.011114) | 0.337780 / 0.275898 (0.061882) | 0.376300 / 0.323480 (0.052820) | 0.006142 / 0.007986 (-0.001843) | 0.004246 / 0.004328 (-0.000083) | 0.074177 / 0.004250 (0.069926) | 0.052698 / 0.037052 (0.015646) | 0.340229 / 0.258489 (0.081740) | 0.396172 / 0.293841 (0.102331) | 0.037293 / 0.128546 (-0.091253) | 0.012514 / 0.075646 (-0.063132) | 0.087144 / 0.419271 (-0.332128) | 0.051922 / 0.043533 (0.008390) | 0.333188 / 0.255139 (0.078049) | 0.355420 / 0.283200 (0.072220) | 0.110273 / 0.141683 (-0.031410) | 1.447826 / 1.452155 (-0.004329) | 1.561135 / 1.492716 (0.068419) |

### 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) | 0.269203 / 0.018006 (0.251197) | 0.551997 / 0.000490 (0.551508) | 0.001558 / 0.000200 (0.001359) | 0.000090 / 0.000054 (0.000035) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.029511 / 0.037411 (-0.007900) | 0.108614 / 0.014526 (0.094089) | 0.123438 / 0.176557 (-0.053118) | 0.171596 / 0.737135 (-0.565539) | 0.126828 / 0.296338 (-0.169511) |

### 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) | 0.420520 / 0.215209 (0.205310) | 4.175672 / 2.077655 (2.098017) | 1.982220 / 1.504120 (0.478101) | 1.788575 / 1.541195 (0.247381) | 1.860840 / 1.468490 (0.392349) | 0.706730 / 4.584777 (-3.878047) | 3.858718 / 3.745712 (0.113005) | 3.069389 / 5.269862 (-2.200472) | 1.827603 / 4.565676 (-2.738073) | 0.087893 / 0.424275 (-0.336382) | 0.012613 / 0.007607 (0.005006) | 0.524177 / 0.226044 (0.298132) | 5.177077 / 2.268929 (2.908148) | 2.494397 / 55.444624 (-52.950227) | 2.189484 / 6.876477 (-4.686992) | 2.217626 / 2.142072 (0.075554) | 0.846326 / 4.805227 (-3.958901) | 0.176558 / 6.500664 (-6.324106) | 0.065018 / 0.075469 (-0.010451) |

### 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) | 1.268618 / 1.841788 (-0.573170) | 15.132711 / 8.074308 (7.058403) | 14.585530 / 10.191392 (4.394138) | 0.163454 / 0.680424 (-0.516970) | 0.017442 / 0.534201 (-0.516759) | 0.421746 / 0.579283 (-0.157537) | 0.425412 / 0.434364 (-0.008952) | 0.499178 / 0.540337 (-0.041159) | 0.595458 / 1.386936 (-0.791478) |

</details>
</details>

![](https://cml.dev/watermark.png#ab77e58cd32413f4ef4828134a2470ebd53bb542 "CML watermark")


_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) | 0.007980 / 0.011353 (-0.003373) | 0.005414 / 0.011008 (-0.005594) | 0.099226 / 0.038508 (0.060718) | 0.035442 / 0.023109 (0.012332) | 0.304851 / 0.275898 (0.028952) | 0.337144 / 0.323480 (0.013664) | 0.006162 / 0.007986 (-0.001823) | 0.004151 / 0.004328 (-0.000177) | 0.074708 / 0.004250 (0.070458) | 0.049690 / 0.037052 (0.012638) | 0.307658 / 0.258489 (0.049168) | 0.358472 / 0.293841 (0.064631) | 0.037181 / 0.128546 (-0.091365) | 0.012259 / 0.075646 (-0.063387) | 0.335426 / 0.419271 (-0.083846) | 0.050790 / 0.043533 (0.007257) | 0.301715 / 0.255139 (0.046576) | 0.320834 / 0.283200 (0.037634) | 0.102357 / 0.141683 (-0.039326) | 1.454750 / 1.452155 (0.002596) | 1.571994 / 1.492716 (0.079278) |

### 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) | 0.218708 / 0.018006 (0.200702) | 0.444391 / 0.000490 (0.443901) | 0.005717 / 0.000200 (0.005517) | 0.000089 / 0.000054 (0.000035) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.028017 / 0.037411 (-0.009395) | 0.112753 / 0.014526 (0.098227) | 0.121003 / 0.176557 (-0.055554) | 0.181085 / 0.737135 (-0.556050) | 0.127211 / 0.296338 (-0.169127) |

### 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) | 0.400803 / 0.215209 (0.185594) | 4.007315 / 2.077655 (1.929660) | 1.826911 / 1.504120 (0.322791) | 1.637799 / 1.541195 (0.096605) | 1.699754 / 1.468490 (0.231264) | 0.709413 / 4.584777 (-3.875364) | 4.008904 / 3.745712 (0.263192) | 3.916540 / 5.269862 (-1.353322) | 1.902102 / 4.565676 (-2.663575) | 0.089048 / 0.424275 (-0.335227) | 0.012763 / 0.007607 (0.005155) | 0.498957 / 0.226044 (0.272913) | 4.979865 / 2.268929 (2.710937) | 2.301987 / 55.444624 (-53.142637) | 1.929404 / 6.876477 (-4.947073) | 2.107839 / 2.142072 (-0.034233) | 0.857253 / 4.805227 (-3.947974) | 0.171935 / 6.500664 (-6.328729) | 0.066753 / 0.075469 (-0.008716) |

### 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) | 1.186811 / 1.841788 (-0.654977) | 15.866319 / 8.074308 (7.792011) | 14.738555 / 10.191392 (4.547163) | 0.142879 / 0.680424 (-0.537544) | 0.017679 / 0.534201 (-0.516522) | 0.422840 / 0.579283 (-0.156443) | 0.450307 / 0.434364 (0.015943) | 0.491802 / 0.540337 (-0.048536) | 0.588837 / 1.386936 (-0.798099) |

</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) | 0.007659 / 0.011353 (-0.003694) | 0.005331 / 0.011008 (-0.005678) | 0.075360 / 0.038508 (0.036852) | 0.034011 / 0.023109 (0.010902) | 0.354488 / 0.275898 (0.078590) | 0.401781 / 0.323480 (0.078301) | 0.005806 / 0.007986 (-0.002179) | 0.004029 / 0.004328 (-0.000300) | 0.073822 / 0.004250 (0.069572) | 0.049067 / 0.037052 (0.012015) | 0.364483 / 0.258489 (0.105994) | 0.405637 / 0.293841 (0.111796) | 0.037166 / 0.128546 (-0.091380) | 0.012397 / 0.075646 (-0.063249) | 0.087346 / 0.419271 (-0.331926) | 0.050888 / 0.043533 (0.007355) | 0.334796 / 0.255139 (0.079657) | 0.387681 / 0.283200 (0.104481) | 0.105056 / 0.141683 (-0.036627) | 1.471630 / 1.452155 (0.019475) | 1.554764 / 1.492716 (0.062047) |

### 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) | 0.231825 / 0.018006 (0.213819) | 0.449746 / 0.000490 (0.449256) | 0.000888 / 0.000200 (0.000688) | 0.000078 / 0.000054 (0.000023) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.030363 / 0.037411 (-0.007049) | 0.115234 / 0.014526 (0.100708) | 0.123005 / 0.176557 (-0.053551) | 0.172772 / 0.737135 (-0.564363) | 0.127818 / 0.296338 (-0.168520) |

### 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) | 0.425761 / 0.215209 (0.210552) | 4.237950 / 2.077655 (2.160295) | 1.992045 / 1.504120 (0.487925) | 1.801622 / 1.541195 (0.260427) | 1.918477 / 1.468490 (0.449987) | 0.722730 / 4.584777 (-3.862047) | 4.015968 / 3.745712 (0.270256) | 3.720412 / 5.269862 (-1.549450) | 1.763111 / 4.565676 (-2.802566) | 0.089041 / 0.424275 (-0.335234) | 0.012608 / 0.007607 (0.005001) | 0.522645 / 0.226044 (0.296601) | 5.227108 / 2.268929 (2.958180) | 2.444714 / 55.444624 (-52.999910) | 2.109745 / 6.876477 (-4.766732) | 2.194042 / 2.142072 (0.051969) | 0.871781 / 4.805227 (-3.933447) | 0.173149 / 6.500664 (-6.327515) | 0.066192 / 0.075469 (-0.009277) |

### 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) | 1.312051 / 1.841788 (-0.529737) | 16.024315 / 8.074308 (7.950007) | 15.123823 / 10.191392 (4.932431) | 0.163997 / 0.680424 (-0.516427) | 0.017595 / 0.534201 (-0.516606) | 0.426379 / 0.579283 (-0.152904) | 0.467709 / 0.434364 (0.033345) | 0.498308 / 0.540337 (-0.042030) | 0.591426 / 1.386936 (-0.795510) |

</details>
</details>

![](https://cml.dev/watermark.png#13488cc110b67090289794f48d5c84a4fd0c063a "CML watermark")


CI is failing due to unrelated issues, hopefully https://github.com/huggingface/datasets/pull/5642 fixes it

<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) | 0.006478 / 0.011353 (-0.004875) | 0.004347 / 0.011008 (-0.006661) | 0.097103 / 0.038508 (0.058595) | 0.027650 / 0.023109 (0.004541) | 0.372355 / 0.275898 (0.096457) | 0.408794 / 0.323480 (0.085314) | 0.005034 / 0.007986 (-0.002952) | 0.003252 / 0.004328 (-0.001076) | 0.074068 / 0.004250 (0.069818) | 0.035542 / 0.037052 (-0.001510) | 0.367392 / 0.258489 (0.108903) | 0.409644 / 0.293841 (0.115803) | 0.031745 / 0.128546 (-0.096801) | 0.011501 / 0.075646 (-0.064145) | 0.323355 / 0.419271 (-0.095917) | 0.043065 / 0.043533 (-0.000467) | 0.377313 / 0.255139 (0.122174) | 0.395326 / 0.283200 (0.112127) | 0.087101 / 0.141683 (-0.054582) | 1.461228 / 1.452155 (0.009073) | 1.529413 / 1.492716 (0.036696) |

### 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) | 0.199245 / 0.018006 (0.181239) | 0.409978 / 0.000490 (0.409488) | 0.002655 / 0.000200 (0.002455) | 0.000070 / 0.000054 (0.000016) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.023903 / 0.037411 (-0.013508) | 0.097855 / 0.014526 (0.083330) | 0.106405 / 0.176557 (-0.070152) | 0.166889 / 0.737135 (-0.570247) | 0.110256 / 0.296338 (-0.186082) |

### 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) | 0.440351 / 0.215209 (0.225142) | 4.382848 / 2.077655 (2.305194) | 2.049602 / 1.504120 (0.545482) | 1.824638 / 1.541195 (0.283443) | 1.850519 / 1.468490 (0.382029) | 0.702652 / 4.584777 (-3.882125) | 3.394571 / 3.745712 (-0.351141) | 1.940608 / 5.269862 (-3.329254) | 1.263961 / 4.565676 (-3.301716) | 0.083985 / 0.424275 (-0.340290) | 0.013046 / 0.007607 (0.005439) | 0.538272 / 0.226044 (0.312228) | 5.407563 / 2.268929 (3.138634) | 2.519207 / 55.444624 (-52.925418) | 2.153379 / 6.876477 (-4.723098) | 2.394512 / 2.142072 (0.252439) | 0.812840 / 4.805227 (-3.992387) | 0.152868 / 6.500664 (-6.347796) | 0.067823 / 0.075469 (-0.007646) |

### 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) | 1.220031 / 1.841788 (-0.621757) | 13.781237 / 8.074308 (5.706929) | 14.203975 / 10.191392 (4.012583) | 0.141077 / 0.680424 (-0.539347) | 0.016518 / 0.534201 (-0.517682) | 0.379079 / 0.579283 (-0.200204) | 0.378916 / 0.434364 (-0.055448) | 0.434589 / 0.540337 (-0.105749) | 0.521129 / 1.386936 (-0.865807) |

</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) | 0.006997 / 0.011353 (-0.004356) | 0.004599 / 0.011008 (-0.006410) | 0.078700 / 0.038508 (0.040192) | 0.027902 / 0.023109 (0.004793) | 0.344406 / 0.275898 (0.068508) | 0.392918 / 0.323480 (0.069438) | 0.005175 / 0.007986 (-0.002811) | 0.004755 / 0.004328 (0.000427) | 0.077707 / 0.004250 (0.073457) | 0.039409 / 0.037052 (0.002357) | 0.343250 / 0.258489 (0.084761) | 0.405544 / 0.293841 (0.111703) | 0.032286 / 0.128546 (-0.096260) | 0.011674 / 0.075646 (-0.063972) | 0.087633 / 0.419271 (-0.331639) | 0.043346 / 0.043533 (-0.000186) | 0.355076 / 0.255139 (0.099937) | 0.382155 / 0.283200 (0.098955) | 0.090914 / 0.141683 (-0.050769) | 1.518369 / 1.452155 (0.066215) | 1.583530 / 1.492716 (0.090813) |

### 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) | 0.160369 / 0.018006 (0.142362) | 0.406844 / 0.000490 (0.406354) | 0.002651 / 0.000200 (0.002451) | 0.000080 / 0.000054 (0.000025) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.025295 / 0.037411 (-0.012116) | 0.101490 / 0.014526 (0.086964) | 0.108825 / 0.176557 (-0.067732) | 0.161673 / 0.737135 (-0.575462) | 0.113610 / 0.296338 (-0.182729) |

### 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) | 0.443514 / 0.215209 (0.228305) | 4.436722 / 2.077655 (2.359067) | 2.144008 / 1.504120 (0.639888) | 2.005324 / 1.541195 (0.464129) | 2.123356 / 1.468490 (0.654866) | 0.697217 / 4.584777 (-3.887560) | 3.401105 / 3.745712 (-0.344607) | 1.874621 / 5.269862 (-3.395240) | 1.165069 / 4.565676 (-3.400608) | 0.082799 / 0.424275 (-0.341476) | 0.012806 / 0.007607 (0.005199) | 0.542688 / 0.226044 (0.316644) | 5.420963 / 2.268929 (3.152034) | 2.579034 / 55.444624 (-52.865590) | 2.240201 / 6.876477 (-4.636276) | 2.261309 / 2.142072 (0.119237) | 0.800246 / 4.805227 (-4.004981) | 0.150380 / 6.500664 (-6.350285) | 0.066880 / 0.075469 (-0.008589) |

### 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) | 1.281721 / 1.841788 (-0.560067) | 13.906361 / 8.074308 (5.832053) | 14.135336 / 10.191392 (3.943944) | 0.128865 / 0.680424 (-0.551559) | 0.016452 / 0.534201 (-0.517749) | 0.373563 / 0.579283 (-0.205720) | 0.385321 / 0.434364 (-0.049043) | 0.437198 / 0.540337 (-0.103139) | 0.530720 / 1.386936 (-0.856216) |

</details>
</details>

![](https://cml.dev/watermark.png#e2f8e17f3c8f8d0cb77a4c566a78e31fab47108c "CML watermark")


<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) | 0.008099 / 0.011353 (-0.003254) | 0.005093 / 0.011008 (-0.005916) | 0.106258 / 0.038508 (0.067750) | 0.037051 / 0.023109 (0.013942) | 0.347960 / 0.275898 (0.072062) | 0.370849 / 0.323480 (0.047369) | 0.006122 / 0.007986 (-0.001863) | 0.004094 / 0.004328 (-0.000235) | 0.079549 / 0.004250 (0.075299) | 0.046563 / 0.037052 (0.009510) | 0.332735 / 0.258489 (0.074246) | 0.417061 / 0.293841 (0.123220) | 0.038105 / 0.128546 (-0.090441) | 0.011886 / 0.075646 (-0.063760) | 0.342103 / 0.419271 (-0.077169) | 0.053233 / 0.043533 (0.009700) | 0.344754 / 0.255139 (0.089615) | 0.355354 / 0.283200 (0.072155) | 0.101059 / 0.141683 (-0.040624) | 1.518561 / 1.452155 (0.066406) | 1.558652 / 1.492716 (0.065935) |

### 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) | 0.225919 / 0.018006 (0.207913) | 0.518539 / 0.000490 (0.518049) | 0.006230 / 0.000200 (0.006030) | 0.000124 / 0.000054 (0.000070) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.026782 / 0.037411 (-0.010629) | 0.108457 / 0.014526 (0.093931) | 0.125203 / 0.176557 (-0.051353) | 0.175726 / 0.737135 (-0.561409) | 0.127051 / 0.296338 (-0.169287) |

### 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) | 0.416427 / 0.215209 (0.201217) | 4.168851 / 2.077655 (2.091196) | 1.962238 / 1.504120 (0.458118) | 1.825224 / 1.541195 (0.284029) | 1.831200 / 1.468490 (0.362710) | 0.765526 / 4.584777 (-3.819250) | 4.303957 / 3.745712 (0.558245) | 2.193467 / 5.269862 (-3.076395) | 1.654605 / 4.565676 (-2.911071) | 0.096709 / 0.424275 (-0.327566) | 0.013792 / 0.007607 (0.006185) | 0.537862 / 0.226044 (0.311818) | 5.152230 / 2.268929 (2.883302) | 2.520938 / 55.444624 (-52.923686) | 2.108422 / 6.876477 (-4.768054) | 2.214220 / 2.142072 (0.072147) | 0.834320 / 4.805227 (-3.970907) | 0.170635 / 6.500664 (-6.330029) | 0.063131 / 0.075469 (-0.012338) |

### 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) | 1.215767 / 1.841788 (-0.626020) | 15.254781 / 8.074308 (7.180473) | 14.360764 / 10.191392 (4.169372) | 0.172511 / 0.680424 (-0.507913) | 0.020161 / 0.534201 (-0.514040) | 0.426936 / 0.579283 (-0.152347) | 0.438771 / 0.434364 (0.004407) | 0.486973 / 0.540337 (-0.053364) | 0.584238 / 1.386936 (-0.802698) |

</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) | 0.006777 / 0.011353 (-0.004576) | 0.005304 / 0.011008 (-0.005704) | 0.073717 / 0.038508 (0.035209) | 0.033604 / 0.023109 (0.010494) | 0.340448 / 0.275898 (0.064550) | 0.351861 / 0.323480 (0.028381) | 0.005786 / 0.007986 (-0.002199) | 0.005013 / 0.004328 (0.000685) | 0.071263 / 0.004250 (0.067012) | 0.048189 / 0.037052 (0.011137) | 0.339457 / 0.258489 (0.080968) | 0.384383 / 0.293841 (0.090542) | 0.035563 / 0.128546 (-0.092983) | 0.011509 / 0.075646 (-0.064137) | 0.083722 / 0.419271 (-0.335550) | 0.048886 / 0.043533 (0.005353) | 0.350184 / 0.255139 (0.095045) | 0.361037 / 0.283200 (0.077837) | 0.105191 / 0.141683 (-0.036492) | 1.503247 / 1.452155 (0.051093) | 1.582298 / 1.492716 (0.089581) |

### 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) | 0.221687 / 0.018006 (0.203681) | 0.466489 / 0.000490 (0.465999) | 0.000484 / 0.000200 (0.000284) | 0.000069 / 0.000054 (0.000015) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.027978 / 0.037411 (-0.009434) | 0.119572 / 0.014526 (0.105047) | 0.133530 / 0.176557 (-0.043026) | 0.177892 / 0.737135 (-0.559243) | 0.127045 / 0.296338 (-0.169294) |

### 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) | 0.430198 / 0.215209 (0.214989) | 4.435512 / 2.077655 (2.357858) | 2.007183 / 1.504120 (0.503063) | 1.799230 / 1.541195 (0.258036) | 1.884750 / 1.468490 (0.416260) | 0.745232 / 4.584777 (-3.839545) | 4.088069 / 3.745712 (0.342357) | 4.114669 / 5.269862 (-1.155193) | 2.374086 / 4.565676 (-2.191590) | 0.089154 / 0.424275 (-0.335121) | 0.012938 / 0.007607 (0.005331) | 0.505954 / 0.226044 (0.279909) | 5.194226 / 2.268929 (2.925298) | 2.487230 / 55.444624 (-52.957394) | 2.163353 / 6.876477 (-4.713124) | 2.177879 / 2.142072 (0.035807) | 0.828728 / 4.805227 (-3.976499) | 0.171157 / 6.500664 (-6.329507) | 0.062883 / 0.075469 (-0.012586) |

### 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) | 1.275906 / 1.841788 (-0.565882) | 15.235484 / 8.074308 (7.161176) | 14.467396 / 10.191392 (4.276004) | 0.198994 / 0.680424 (-0.481430) | 0.020203 / 0.534201 (-0.513998) | 0.447904 / 0.579283 (-0.131380) | 0.454210 / 0.434364 (0.019846) | 0.528062 / 0.540337 (-0.012275) | 0.619311 / 1.386936 (-0.767625) |

</details>
</details>

![](https://cml.dev/watermark.png#11cd0f73acbce1d16174f2555e56fda511d5a08b "CML watermark")