Datasets:

Helsinki-NLP
/

opus_paracrawl

	# coding=utf-8
	# Copyright 2020 HuggingFace Datasets 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.

	# Lint as: python3
	import os

	import datasets


	_DESCRIPTION = """\
	Parallel corpora from Web Crawls collected in the ParaCrawl project.

	42 languages, 43 bitexts
	total number of files: 59,996
	total number of tokens: 56.11G
	total number of sentence fragments: 3.13G
	"""
	_HOMEPAGE = "http://opus.nlpl.eu/ParaCrawl.php"
	_CITATION = r"""\
	@inproceedings{banon-etal-2020-paracrawl,
	title = "{P}ara{C}rawl: Web-Scale Acquisition of Parallel Corpora",
	author = "Ba{\~n}{\'o}n, Marta and
	Chen, Pinzhen and
	Haddow, Barry and
	Heafield, Kenneth and
	Hoang, Hieu and
	Espl{\`a}-Gomis, Miquel and
	Forcada, Mikel L. and
	Kamran, Amir and
	Kirefu, Faheem and
	Koehn, Philipp and
	Ortiz Rojas, Sergio and
	Pla Sempere, Leopoldo and
	Ram{\'\i}rez-S{\'a}nchez, Gema and
	Sarr{\'\i}as, Elsa and
	Strelec, Marek and
	Thompson, Brian and
	Waites, William and
	Wiggins, Dion and
	Zaragoza, Jaume",
	booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
	month = jul,
	year = "2020",
	address = "Online",
	publisher = "Association for Computational Linguistics",
	url = "https://aclanthology.org/2020.acl-main.417",
	doi = "10.18653/v1/2020.acl-main.417",
	pages = "4555--4567",
	}
	@InProceedings{TIEDEMANN12.463,
	author = {Jörg Tiedemann},
	title = {Parallel Data, Tools and Interfaces in OPUS},
	booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
	year = {2012},
	month = {may},
	date = {23-25},
	address = {Istanbul, Turkey},
	editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
	publisher = {European Language Resources Association (ELRA)},
	isbn = {978-2-9517408-7-7},
	language = {english}
	}
	"""

	_VERSION = "9.0.0"
	_BASE_NAME = "ParaCrawl.{}.{}"
	_BASE_URL = "https://object.pouta.csc.fi/OPUS-ParaCrawl/v9/moses/{}-{}.txt.zip"
	# Please note that only few pairs are shown here. You can use config to generate data for all language pairs
	_LANGUAGE_PAIRS = [
	("el", "en"),
	("en", "km"),
	("en", "so"),
	("de", "pl"),
	("fr", "nl"),
	("en", "sw"),
	("en", "tl"),
	("es", "gl"),
	]


	class ParaCrawlConfig(datasets.BuilderConfig):
	def __init__(self, args, lang1=None, lang2=None, *kwargs):
	super().__init__(
	*args,
	name=f"{lang1}-{lang2}",
	**kwargs,
	)
	assert lang1 != lang2, "'language 1' & 'language 2' should be different from each other"
	self.lang1 = lang1
	self.lang2 = lang2


	class OpusParaCrawl(datasets.GeneratorBasedBuilder):
	BUILDER_CONFIGS = [
	ParaCrawlConfig(
	lang1=lang1,
	lang2=lang2,
	description=f"Translating {lang1} to {lang2} or vice versa",
	version=datasets.Version(_VERSION),
	)
	for lang1, lang2 in _LANGUAGE_PAIRS
	]
	BUILDER_CONFIG_CLASS = ParaCrawlConfig

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"id": datasets.Value("string"),
	"translation": datasets.Translation(languages=(self.config.lang1, self.config.lang2)),
	},
	),
	supervised_keys=None,
	homepage=_HOMEPAGE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	download_url = _BASE_URL.format(self.config.lang1, self.config.lang2)
	path = dl_manager.download_and_extract(download_url)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={"datapath": path},
	)
	]

	def _generate_examples(self, datapath):
	lang1, lang2 = self.config.lang1, self.config.lang2
	folder = lang1 + "-" + lang2
	lang1_filename = _BASE_NAME.format(folder, lang1)
	lang2_filename = _BASE_NAME.format(folder, lang2)
	lang1_path = os.path.join(datapath, lang1_filename)
	lang2_path = os.path.join(datapath, lang2_filename)
	with open(lang1_path, encoding="utf-8") as f1, open(lang2_path, encoding="utf-8") as f2:
	for id_, (lang1_sentence, lang2_sentence) in enumerate(zip(f1, f2)):
	lang1_sentence = lang1_sentence.strip()
	lang2_sentence = lang2_sentence.strip()
	yield id_, {
	"id": str(id_),
	"translation": {lang1: lang1_sentence, lang2: lang2_sentence},
	}