europeana_newspapers.py

# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.
"""TODO"""

from collections import defaultdict
from pathlib import Path

import datasets
import pyarrow as pa
import pyarrow.parquet as pq
from datasets import Sequence, Value
from datasets.config import PYARROW_VERSION
from datasets.utils.logging import get_logger
from huggingface_hub import hf_api

logger = get_logger(__name__)

if PYARROW_VERSION.major <= 6:
    msg = f"pyarrow version >= 7.0.0 required for this loading script, you have {PYARROW_VERSION}"
    logger.warning(msg)
    raise RuntimeError(msg)

_DESCRIPTION = "TODO"

_HOMEPAGE = "TODO"


api = hf_api.HfApi()
files = api.list_repo_files("biglam/europeana_newspapers", repo_type="dataset")
data = defaultdict(dict)
parquet_files = (f for f in files if f.endswith(".parquet"))
for file in parquet_files:
    lang, decade = Path(file).stem.split("-")
    data[lang].update({decade: file})
_DATA = dict(data)

_LANG_CONFIGS = set(_DATA.keys())


class EuropeanaNewspapersConfig(datasets.BuilderConfig):
    """BuilderConfig for the Europeana Newspapers dataset."""

    def __init__(
        self, *args, languages=None, min_decade=None, max_decade=None, **kwargs
    ):
        """BuilderConfig for the Europeana Newspapers dataset.

        Args:
            languages (:obj:`List[str]`): List of languages to load.
            **kwargs: keyword arguments forwarded to super.
        """

        super().__init__(
            *args,
            name="+".join(languages),
            **kwargs,
        )
        for lang in languages:
            if lang not in _LANG_CONFIGS:
                raise ValueError(
                    f"{lang} not a valid language key for this dataset, valid keys are {_LANG_CONFIGS}"
                )
        self.languages = languages
        self.min_decade = min_decade
        self.max_decade = max_decade


class EuropeanaNewspapers(datasets.GeneratorBasedBuilder):
    """TODO."""

    VERSION = datasets.Version("1.0.0")

    BUILDER_CONFIG_CLASS = EuropeanaNewspapersConfig
    BUILDER_CONFIGS = [
        EuropeanaNewspapersConfig(languages=[lang]) for lang in _LANG_CONFIGS
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": Value(dtype="string"),
                    "mean_ocr": Value(dtype="float64"),
                    "std_ocr": Value(dtype="float64"),
                    "bounding_boxes": Sequence(
                        feature=Sequence(
                            feature=Value(dtype="float64", id=None),
                            length=-1,
                        ),
                    ),
                    "title": Value(dtype="string"),
                    "date": Value(dtype="string"),
                    "language": Sequence(
                        feature=Value(dtype="string", id=None),
                    ),
                    "item_iiif_url": Value(
                        dtype="string",
                    ),
                    # "multi_language": Value(dtype="bool"),
                    "issue_uri": Value(dtype="string"),
                    "id": Value(dtype="string"),
                }
            ),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            license="Multiple: see the 'license' field of each sample.",
        )

    def _split_generators(self, dl_manager):
        # parquet_files = list(Path(".").rglob("*.parquet"))
        languages = self.config.languages
        min_decade = self.config.min_decade
        max_decade = self.config.max_decade
        data_files = []
        for language in languages:
            for decade, file in _DATA[language].items():
                decade = int(decade)
                if max_decade is None and min_decade is None:
                    data_files.append(file)
                if (
                    max_decade is not None
                    and min_decade is not None
                    and min_decade <= decade <= max_decade
                ):
                    data_files.append(file)
                if (
                    min_decade is not None
                    and max_decade is None
                    and decade >= min_decade
                ):
                    data_files.append(file)
                if (
                    min_decade is None
                    and max_decade is not None
                    and decade <= max_decade
                ):
                    data_files.append(file)

        files = dl_manager.download(data_files)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "files": files,
                },
            ),
        ]

    def _generate_examples(self, files):
        key = 0
        for file in files:
            with open(file, "rb") as f:
                parquet_file = pq.ParquetFile(f)
                for record_batch in parquet_file.iter_batches(batch_size=10_000):
                    pa_table = pa.Table.from_batches([record_batch])
                    rows = pa_table.to_pylist()
                    for row in rows:
                        row.pop("multi_language")
                        yield key, row
                        key += 1