"""Rewrite PubMed metadata Parquet with compact, query-friendly scalar types.""" from __future__ import annotations import argparse import hashlib import re from datetime import datetime from pathlib import Path import polars as pl import pyarrow.parquet as pq CITATION_STATUS = pl.Enum(["In-Data-Review", "In-Process", "MEDLINE", "PubMed-not-MEDLINE", "Publisher"]) PUBLICATION_STATUS = pl.Enum(["aheadofprint", "epublish", "ppublish"]) PUB_MODEL = pl.Enum(["Electronic", "Electronic-Print", "Electronic-eCollection", "Print", "Print-Electronic"]) DOAJ_START_YEAR = "When did the journal start to publish all content using an open license?" DOAJ_PRINT_ISSN = "Journal ISSN (print version)" DOAJ_EISSN = "Journal EISSN (online version)" DOAJ_COMPLIES = "Does the journal comply to DOAJ's definition of open access?" def _parquet_metadata(path: Path) -> dict[str, str]: metadata = pq.read_metadata(path).metadata or {} return {key.decode(): value.decode() for key, value in metadata.items() if key != b"ARROW:schema"} def _normalized_issn(column: str) -> pl.Expr: return pl.col(column).cast(pl.String).str.to_uppercase().str.replace_all(r"[^0-9X]", "") def _doaj_issn_start_years(path: Path) -> pl.DataFrame: if not path.is_file(): raise FileNotFoundError(path) journals = pl.read_csv( path, columns=[DOAJ_PRINT_ISSN, DOAJ_EISSN, DOAJ_START_YEAR, DOAJ_COMPLIES], schema_overrides={ DOAJ_PRINT_ISSN: pl.String, DOAJ_EISSN: pl.String, DOAJ_START_YEAR: pl.String, DOAJ_COMPLIES: pl.String, }, null_values="", ).filter(pl.col(DOAJ_COMPLIES) == "Yes") issns = pl.concat([ journals.select(pl.col(DOAJ_PRINT_ISSN).alias("issn"), pl.col(DOAJ_START_YEAR)), journals.select(pl.col(DOAJ_EISSN).alias("issn"), pl.col(DOAJ_START_YEAR)), ]).with_columns( _normalized_issn("issn").alias("issn"), pl.col(DOAJ_START_YEAR).cast(pl.UInt16).alias("oa_start_year"), ) return issns.filter(pl.col("issn").str.len_chars() == 8).group_by("issn").agg(pl.col("oa_start_year").min()) def _add_is_oa(source: pl.LazyFrame, doaj_csv_path: Path) -> pl.LazyFrame: lookup = _doaj_issn_start_years(doaj_csv_path).lazy() issn_columns = ["issn", "eissn", "issn_linking"] source = source.with_columns(*(_normalized_issn(column).alias(f"__{column}") for column in issn_columns)) start_columns: list[str] = [] for column in issn_columns: key = f"__{column}" start = f"__{column}_oa_start_year" start_columns.append(start) source = source.join( lookup.rename({"issn": key, "oa_start_year": start}), on=key, how="left", ) return source.with_columns(pl.min_horizontal(start_columns).alias("__oa_start_year")).with_columns( (pl.col("pmcid").is_not_null() | (pl.col("year") >= pl.col("__oa_start_year")).fill_null(False)).alias("is_oa") ) def _doaj_metadata(path: Path, lookup_rows: int) -> dict[str, str]: with path.open("rb") as handle: checksum = hashlib.file_digest(handle, "sha256").hexdigest() date_match = re.search(r"doaj_journalcsv_(\d{8})", path.name) snapshot_date = datetime.strptime(date_match.group(1), "%Y%m%d").date().isoformat() if date_match else "unknown" return { "doaj_source": "https://doaj.org/csv", "doaj_snapshot_date": snapshot_date, "doaj_csv_sha256": checksum, "doaj_unique_issns": str(lookup_rows), "is_oa_definition": ( "true when PMCID is present, or when issn, eissn, or issn_linking matches a current DOAJ journal " "and publication year is at least the journal's all-content open-license start year; this indicates " "practical full-text accessibility, not necessarily a permissive reuse license" ), } def clean_pubmed_parquet( input_path: Path, output_path: Path, *, doaj_csv_path: Path | None = None, overwrite: bool = False, ) -> None: """Stream ``input_path`` into an atomically replaced, typed Parquet file.""" if not input_path.is_file(): raise FileNotFoundError(input_path) if output_path.exists() and not overwrite: raise FileExistsError(f"Output already exists: {output_path}; pass --overwrite to replace it") partial_path = output_path.with_name(f".{output_path.name}.partial") if partial_path.exists(): raise FileExistsError(f"Refusing to overwrite existing partial output: {partial_path}") source = pl.scan_parquet(input_path) source_columns = source.collect_schema().names() if "publication_date" not in source_columns: raise ValueError("Input is missing required publication_date column") output_columns = ( source_columns[:7] + ["publication_month", "publication_day"] + [column for column in source_columns[7:] if column != "publication_date"] ) if doaj_csv_path is not None: source = _add_is_oa(source, doaj_csv_path) output_columns.insert(output_columns.index("eissn") + 1, "is_oa") typed = source.with_columns( pl.col("pmid").cast(pl.UInt32), pl.col("year").cast(pl.UInt16), pl.col("publication_date").str.slice(5, 2).cast(pl.UInt8, strict=False).alias("publication_month"), pl.col("publication_date").str.slice(8, 2).cast(pl.UInt8, strict=False).alias("publication_day"), pl.col("date_completed").str.to_date("%Y-%m-%d", strict=True), pl.col("date_revised").str.to_date("%Y-%m-%d", strict=True), pl.col("citation_status").cast(CITATION_STATUS), pl.col("publication_status").cast(PUBLICATION_STATUS), pl.col("pub_model").cast(PUB_MODEL), ).select(output_columns) metadata = _parquet_metadata(input_path) metadata["transform"] = ( "pmid=uint32; year=uint16; publication_date split into uint8 month/day; " "completion/revision dates=date32; bounded statuses=enum" ) if doaj_csv_path is not None: metadata.update(_doaj_metadata(doaj_csv_path, _doaj_issn_start_years(doaj_csv_path).height)) output_path.parent.mkdir(parents=True, exist_ok=True) try: typed.sink_parquet( partial_path, compression="zstd", compression_level=3, statistics=True, row_group_size=100_000, data_page_size=1024 * 1024, maintain_order=True, sync_on_close="data", metadata=metadata, ) partial_path.replace(output_path) except BaseException: partial_path.unlink(missing_ok=True) raise def main() -> None: parser = argparse.ArgumentParser(description=__doc__) parser.add_argument("input", type=Path, help="Source PubMed Parquet") parser.add_argument("output", type=Path, help="Destination clean Parquet") parser.add_argument("--doaj-csv", type=Path, help="DOAJ journal CSV used to derive is_oa") parser.add_argument("--overwrite", action="store_true", help="Atomically replace an existing output") args = parser.parse_args() clean_pubmed_parquet(args.input, args.output, doaj_csv_path=args.doaj_csv, overwrite=args.overwrite) if __name__ == "__main__": main()