File size: 4,744 Bytes
8193465 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 |
# Copyright 2020 The HuggingFace Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import sys
from functools import partial
from typing import TYPE_CHECKING, Optional
import pyarrow as pa
from .. import config
from ..features import Features
from ..features.features import decode_nested_example
from ..utils.py_utils import no_op_if_value_is_null
from .formatting import BaseArrowExtractor, TableFormatter
if TYPE_CHECKING:
import polars as pl
class PolarsArrowExtractor(BaseArrowExtractor["pl.DataFrame", "pl.Series", "pl.DataFrame"]):
def extract_row(self, pa_table: pa.Table) -> "pl.DataFrame":
if config.POLARS_AVAILABLE:
if "polars" not in sys.modules:
import polars
else:
polars = sys.modules["polars"]
return polars.from_arrow(pa_table.slice(length=1))
else:
raise ValueError("Polars needs to be installed to be able to return Polars dataframes.")
def extract_column(self, pa_table: pa.Table) -> "pl.Series":
if config.POLARS_AVAILABLE:
if "polars" not in sys.modules:
import polars
else:
polars = sys.modules["polars"]
return polars.from_arrow(pa_table.select([0]))[pa_table.column_names[0]]
else:
raise ValueError("Polars needs to be installed to be able to return Polars dataframes.")
def extract_batch(self, pa_table: pa.Table) -> "pl.DataFrame":
if config.POLARS_AVAILABLE:
if "polars" not in sys.modules:
import polars
else:
polars = sys.modules["polars"]
return polars.from_arrow(pa_table)
else:
raise ValueError("Polars needs to be installed to be able to return Polars dataframes.")
class PolarsFeaturesDecoder:
def __init__(self, features: Optional[Features]):
self.features = features
import polars as pl # noqa: F401 - import pl at initialization
def decode_row(self, row: "pl.DataFrame") -> "pl.DataFrame":
decode = (
{
column_name: no_op_if_value_is_null(partial(decode_nested_example, feature))
for column_name, feature in self.features.items()
if self.features._column_requires_decoding[column_name]
}
if self.features
else {}
)
if decode:
row[list(decode.keys())] = row.map_rows(decode)
return row
def decode_column(self, column: "pl.Series", column_name: str) -> "pl.Series":
decode = (
no_op_if_value_is_null(partial(decode_nested_example, self.features[column_name]))
if self.features and column_name in self.features and self.features._column_requires_decoding[column_name]
else None
)
if decode:
column = column.map_elements(decode)
return column
def decode_batch(self, batch: "pl.DataFrame") -> "pl.DataFrame":
return self.decode_row(batch)
class PolarsFormatter(TableFormatter["pl.DataFrame", "pl.Series", "pl.DataFrame"]):
table_type = "polars dataframe"
column_type = "polars series"
def __init__(self, features=None, **np_array_kwargs):
super().__init__(features=features)
self.np_array_kwargs = np_array_kwargs
self.polars_arrow_extractor = PolarsArrowExtractor
self.polars_features_decoder = PolarsFeaturesDecoder(features)
import polars as pl # noqa: F401 - import pl at initialization
def format_row(self, pa_table: pa.Table) -> "pl.DataFrame":
row = self.polars_arrow_extractor().extract_row(pa_table)
row = self.polars_features_decoder.decode_row(row)
return row
def format_column(self, pa_table: pa.Table) -> "pl.Series":
column = self.polars_arrow_extractor().extract_column(pa_table)
column = self.polars_features_decoder.decode_column(column, pa_table.column_names[0])
return column
def format_batch(self, pa_table: pa.Table) -> "pl.DataFrame":
row = self.polars_arrow_extractor().extract_batch(pa_table)
row = self.polars_features_decoder.decode_batch(row)
return row
|