Parallelize data download
#9
by
albertvillanova
HF Staff
- opened
- open_access.py +40 -89
open_access.py
CHANGED
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@@ -57,6 +57,11 @@ _SUBSETS = {
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}
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_BASELINE_DATE = "2022-12-17"
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_BASELINE_MAX_RANGE = 10
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class OpenAccessConfig(datasets.BuilderConfig):
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@@ -71,7 +76,8 @@ class OpenAccessConfig(datasets.BuilderConfig):
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"""
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subsets = [subsets] if isinstance(subsets, str) else subsets
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super().__init__(
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name="+".join(subsets),
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)
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self.subsets = subsets if self.name != "all" else list(_SUBSETS.keys())
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@@ -106,36 +112,16 @@ class OpenAccess(datasets.GeneratorBasedBuilder):
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def _split_generators(self, dl_manager):
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"incremental_file_lists": [],
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"incremental_archives": []
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}
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baseline_file_lists = []
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baseline_archives = []
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for subset in self.config.subsets:
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url = _URL.format(subset=_SUBSETS[subset])
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basename = f"{_SUBSETS[subset]}_txt."
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# Baselines
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baselines = [f"PMC00{i}xxxxxx.baseline.{_BASELINE_DATE}" for i in
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# baseline_paths = dl_manager.download(baseline_urls)
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for baseline in baselines:
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baseline_file_list_url = f"{url}{basename}{baseline}.filelist.csv"
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try:
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baseline_file_list = dl_manager.download(baseline_file_list_url)
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except FileNotFoundError: # non-commercial PMC000xxxxxx baseline does not exist
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continue
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baseline_archive_url = f"{url}{basename}{baseline}.tar.gz"
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try:
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baseline_archive = dl_manager.download(baseline_archive_url)
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except FileNotFoundError:
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continue
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baseline_file_lists.append(baseline_file_list)
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baseline_archives.append(baseline_archive)
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# Incremental
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date_delta = datetime.date.today() - datetime.date.fromisoformat(_BASELINE_DATE)
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incremental_dates = [
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@@ -143,75 +129,40 @@ class OpenAccess(datasets.GeneratorBasedBuilder):
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for i in range(date_delta.days)
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]
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incrementals = [f"incr.{date}" for date in incremental_dates]
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incremental_urls =
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"
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}
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paths = dl_manager.download(incremental_urls)
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incremental_paths["incremental_file_lists"].extend(paths["incremental_file_lists"])
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incremental_paths["incremental_archives"].extend(paths["incremental_archives"])
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"
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"baseline_archives": [dl_manager.iter_archive(archive) for archive in baseline_archives],
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"incremental_file_lists": incremental_paths["incremental_file_lists"],
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"incremental_archives": [
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dl_manager.iter_archive(archive) for archive in incremental_paths["incremental_archives"]
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],
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},
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),
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]
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def _generate_examples(self,
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key = 0
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data
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yield key, data
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key += 1
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except FileNotFoundError: # non-commercial PMC000xxxxxx baseline does not exist
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continue
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# Incrementals
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if incremental_file_lists:
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for incremental_file_list, incremental_archive in zip(incremental_file_lists, incremental_archives):
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incrementals = pd.read_csv(incremental_file_list, index_col="Article File").to_dict(orient="index")
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for path, file in incremental_archive:
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data = incrementals.pop(path)
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content = file.read()
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try:
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text = content.decode("utf-8").strip()
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except UnicodeDecodeError as e:
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text = content.decode("latin-1").strip()
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data = {
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"text": text,
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"pmid": data["PMID"],
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"accession_id": data["AccessionID"],
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"license": data["License"],
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"last_updated": data["LastUpdated (YYYY-MM-DD HH:MM:SS)"],
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"retracted": data["Retracted"],
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"citation": data["Article Citation"],
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}
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yield key, data
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key += 1
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}
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_BASELINE_DATE = "2022-12-17"
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_BASELINE_MAX_RANGE = 10
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_BASELINE_RANGES = {
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"commercial": range(_BASELINE_MAX_RANGE),
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"non_commercial": range(1, _BASELINE_MAX_RANGE), # non-commercial PMC000xxxxxx baseline does not exist
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"other": range(_BASELINE_MAX_RANGE),
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}
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class OpenAccessConfig(datasets.BuilderConfig):
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"""
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subsets = [subsets] if isinstance(subsets, str) else subsets
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super().__init__(
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name="+".join(subsets),
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**kwargs,
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)
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self.subsets = subsets if self.name != "all" else list(_SUBSETS.keys())
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def _split_generators(self, dl_manager):
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paths = []
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for subset in self.config.subsets:
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url = _URL.format(subset=_SUBSETS[subset])
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basename = f"{_SUBSETS[subset]}_txt."
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# Baselines
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baselines = [f"PMC00{i}xxxxxx.baseline.{_BASELINE_DATE}" for i in _BASELINE_RANGES[subset]]
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baseline_urls = [
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(f"{url}{basename}{baseline}.filelist.csv", f"{url}{basename}{baseline}.tar.gz")
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for baseline in baselines
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]
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# Incremental
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date_delta = datetime.date.today() - datetime.date.fromisoformat(_BASELINE_DATE)
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incremental_dates = [
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for i in range(date_delta.days)
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]
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incrementals = [f"incr.{date}" for date in incremental_dates]
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incremental_urls = [
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(f"{url}{basename}{incremental}.filelist.csv", f"{url}{basename}{incremental}.tar.gz")
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for incremental in incrementals
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]
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paths += dl_manager.download(baseline_urls + incremental_urls)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"paths": [(file_list, dl_manager.iter_archive(archive)) for file_list, archive in paths],
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},
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),
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]
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def _generate_examples(self, paths):
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key = 0
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for file_list, archive in paths:
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file_list_data = pd.read_csv(file_list, index_col="Article File").to_dict(orient="index")
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for path, file in archive:
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data = file_list_data.pop(path)
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content = file.read()
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try:
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text = content.decode("utf-8").strip()
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except UnicodeDecodeError as e:
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text = content.decode("latin-1").strip()
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data = {
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"text": text,
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"pmid": data["PMID"],
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"accession_id": data["AccessionID"],
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"license": data["License"],
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"last_updated": data["LastUpdated (YYYY-MM-DD HH:MM:SS)"],
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"retracted": data["Retracted"],
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"citation": data["Article Citation"],
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}
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yield key, data
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key += 1
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