papis-extract/papis_extract/exporters/notes.py

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from dataclasses import dataclass
import Levenshtein
from papis.document import Document
from papis_extract.annotation import Annotation
from papis_extract.formatter import Formatter
from papis.logging import get_logger
import papis.notes
import papis.document
import papis.git
import papis.config
import papis.commands.edit
logger = get_logger(__name__)
@dataclass
class NotesExporter:
formatter: Formatter
edit: bool = False
git: bool = False
force: bool = False
def run(self, annot_docs: list[tuple[Document, list[Annotation]]]) -> None:
"""Write annotations into document notes.
Permanently writes the given annotations into notes
belonging to papis documents. Creates new notes for
documents missing a note field or appends to existing.
"""
for doc, annots in annot_docs:
# first always true since we write single doc per note
2024-06-12 09:46:39 +00:00
formatted_annotations: list[str] = self.formatter(
doc, annots, first=True
).split("\n")
if formatted_annotations:
self._add_annots_to_note(doc, formatted_annotations, force=self.force)
if self.edit:
papis.commands.edit.edit_notes(doc, git=self.git)
def _add_annots_to_note(
self,
document: Document,
formatted_annotations: list[str],
git: bool = False,
force: bool = False,
) -> None:
"""
Append new annotations to the end of a note.
This function appends new annotations to the end of a note file. It takes in a
document object containing the note, a list of formatted annotations to be
added, and optional flags git and force. If git is True, the changes will be
committed to git. If force is True, the annotations will be added even if they
already exist in the note.
:param document: The document object representing the note
:type document: class:`papis.document.Document`
:param formatted_annotations: A list of already formatted annotations to be added
:type formatted_annotations: list[str]
:param git: Flag indicating whether to commit changes to git, defaults to False.
:type git: bool, optional
:param force: Flag indicating whether to force adding annotations even if they
already exist, defaults to False.
:type force: bool, optional
"""
logger.debug("Adding annotations to note.")
notes_path = papis.notes.notes_path_ensured(document)
existing: list[str] = []
with open(notes_path, "r") as file_read:
existing = file_read.readlines()
new_annotations: list[str] = []
if not force:
new_annotations = self._drop_existing_annotations(
formatted_annotations, existing
)
if not new_annotations:
return
with open(notes_path, "a") as f:
# add newline if theres no empty space at file end
if len(existing) > 0 and existing[-1].strip() != "":
f.write("\n")
# FIXME this either joins them too close or moves them too far apart
# We need a better algorithm which knows what a full 'annotation' is.
f.write("\n".join(new_annotations))
f.write("\n")
logger.info(
f"Wrote {len(new_annotations)} "
f"{'line' if len(new_annotations) == 1 else 'lines'} "
f"to {papis.document.describe(document)}"
)
if git:
msg = "Update notes for '{0}'".format(papis.document.describe(document))
folder = document.get_main_folder()
if folder:
papis.git.add_and_commit_resources(
folder, [notes_path, document.get_info_file()], msg
)
def _drop_existing_annotations(
self, formatted_annotations: list[str], file_lines: list[str]
) -> list[str]:
"""Returns the input annotations dropping any existing.
Takes a list of formatted annotations and a list of strings
(most probably existing lines in a file). If anny annotations
match an existing line closely enough, they will be dropped.
Returns list of annotations without duplicates.
"""
minimum_similarity = (
papis.config.getfloat("minimum_similarity", "plugins.extract") or 1.0
)
remaining: list[str] = []
for an in formatted_annotations:
an_split = an.splitlines()
if an_split and not self._test_similarity(
an_split[0], file_lines, minimum_similarity
):
remaining.append(an)
return remaining
def _test_similarity(
self, string: str, lines: list[str], minimum_similarity: float = 1.0
) -> bool:
for line in lines:
ratio = Levenshtein.ratio(string, line)
if ratio > minimum_similarity:
return True
return False