adsfolio.pdf.prefetch

Publication prefetch helpers to reduce first-run ADS query volume.

class adsfolio.pdf.prefetch.PublicationIndex(documents, by_doi, by_filename_key)

Bases: object

In-memory lookup index built from prefetched ADS docs.

Parameters:

• documents (list[dict[str, Any]])

• by_doi (dict[str, list[dict[str, Any]]])

• by_filename_key (dict[tuple[str, str, str, str, str], list[dict[str, Any]]])

by_doi: dict[str, list[dict[str, Any]]]

by_filename_key: dict[tuple[str, str, str, str, str], list[dict[str, Any]]]

documents: list[dict[str, Any]]

class adsfolio.pdf.prefetch.PublicationProfile(orcid='', query_names=<factory>, debut_year=None, retire_year=None, library_ids=<factory>, end_year=None)

Bases: object

Saved setup profile for low-query identify bootstrap.

Parameters:

• orcid (str)

• query_names (list[str])

• debut_year (int | None)

• retire_year (int | None)

• library_ids (list[str])

• end_year (int | None)

debut_year: int | None = None

end_year: int | None = None

property has_identity: bool

library_ids: list[str]

orcid: str = ''

query_names: list[str]

retire_year: int | None = None

adsfolio.pdf.prefetch.build_publication_index(documents)

Build DOI and filename-derived lookup indexes.

Parameters:

documents (list[dict[str, Any]])

Return type:

adsfolio.pdf.prefetch.PublicationIndex

adsfolio.pdf.prefetch.estimated_query_budget(unmatched_file_count, strategies_per_file=4)

Rough upper bound estimate for ADS query count during fallback phase.

Parameters:

• unmatched_file_count (int)

• strategies_per_file (int)

Return type:

int

adsfolio.pdf.prefetch.load_profile()

Load setup profile from config storage.

Return type:

adsfolio.pdf.prefetch.PublicationProfile

adsfolio.pdf.prefetch.match_pdf_from_prefetch(pdf_path, identifier, index)

Match PDF against prefetched docs without performing ADS query.

Parameters:

• pdf_path (pathlib.Path)

• identifier (adsfolio.pdf.identifier.PdfIdentifier)

• index (adsfolio.pdf.prefetch.PublicationIndex)

Return type:

dict[str, Any] | None

adsfolio.pdf.prefetch.match_prefetch_from_doi_candidates(metadata_doi, text_doi, index)

Match prefetched doc using pre-extracted DOI candidates.

Parameters:

• metadata_doi (str | None)

• text_doi (str | None)

• index (adsfolio.pdf.prefetch.PublicationIndex)

Return type:

dict[str, Any] | None

adsfolio.pdf.prefetch.query_publications(client, profile)

Query ADS publications for profile identity (ORCID + optional names).

Parameters:

• client (Any)

• profile (adsfolio.pdf.prefetch.PublicationProfile)

Return type:

list[dict[str, Any]]