from pathlib import Path import fitz import Levenshtein import magic import papis.config import papis.logging from papis_extract.annotation import Annotation logger = papis.logging.get_logger(__name__) class PdfExtractor: def can_process(self, filename: Path) -> bool: if not filename.is_file(): logger.error(f"File {str(filename)} not readable.") return False if not self._is_pdf(filename): return False return True def run(self, filename: Path) -> list[Annotation]: """Extract annotations from a file. Returns all readable annotations contained in the file passed in. Only returns Highlight or Text annotations. """ annotations = [] with fitz.Document(filename) as doc: for page in doc: for annot in page.annots(): quote, note = self._retrieve_annotation_content(page, annot) if not quote and not note: continue col = ( annot.colors.get("fill") or annot.colors.get("stroke") or (0.0, 0.0, 0.0) ) a = Annotation( file=str(filename), content=quote or "", note=note or "", color=col, type=annot.type[1], page=(page.number or 0) + 1, ) annotations.append(a) logger.debug( f"Found {len(annotations)} " f"{'annotation' if len(annotations) == 1 else 'annotations'} for {filename}." ) return annotations def _is_pdf(self, fname: Path) -> bool: """Check if file is a pdf, using mime type.""" return magic.from_file(fname, mime=True) == "application/pdf" def _retrieve_annotation_content( self, page: fitz.Page, annotation: fitz.Annot ) -> tuple[str | None, str | None]: """Gets the text content of an annotation. Returns the actual content of an annotation. Sometimes that is only the written words, sometimes that is only annotation notes, sometimes it is both. Runs a similarity comparison between strings to find out whether they should both be included or are the same, using Levenshtein distance. """ content = annotation.info["content"].replace("\n", " ") written = page.get_textbox(annotation.rect).replace("\n", " ") # highlight with selection in note minimum_similarity = ( papis.config.getfloat("minimum_similarity_content", "plugins.extract") or 1.0 ) if Levenshtein.ratio(content, written) > minimum_similarity: return (content, None) # both a highlight and a note elif content and written: return (written, content) # an independent note, not a highlight elif content: return (None, content) # highlight with selection not in note elif written: return (written, None) # just a highlight without any text return (None, None)