2023-08-28 08:28:06 +00:00
|
|
|
import papis.logging
|
|
|
|
import papis.document
|
|
|
|
import papis.notes
|
|
|
|
import papis.commands.edit
|
|
|
|
import papis.api
|
|
|
|
import papis.git
|
|
|
|
import papis.config
|
|
|
|
import Levenshtein
|
|
|
|
|
|
|
|
from papis_extract.annotation_data import AnnotatedDocument, Annotation
|
|
|
|
|
|
|
|
logger = papis.logging.get_logger(__name__)
|
|
|
|
|
|
|
|
|
|
|
|
def _format_annotation(annotation: Annotation) -> str:
|
|
|
|
note = f"NOTE: {annotation.content}" if annotation.content else ""
|
|
|
|
return f"> {annotation.text}\n {note}"
|
|
|
|
|
|
|
|
|
|
|
|
def to_stdout(annots: list[AnnotatedDocument]) -> None:
|
|
|
|
if not annots:
|
|
|
|
return
|
|
|
|
|
|
|
|
for entry in annots:
|
|
|
|
if not entry.annotations:
|
|
|
|
continue
|
|
|
|
|
|
|
|
title_decoration = "=" * len(entry.document.get("title", ""))
|
|
|
|
print(
|
|
|
|
f"{title_decoration}\n{papis.document.describe(entry.document)}\n{title_decoration}\n"
|
|
|
|
)
|
|
|
|
for a in entry.annotations:
|
|
|
|
print(_format_annotation(a))
|
|
|
|
print("\n")
|
|
|
|
|
|
|
|
|
|
|
|
def to_notes(annots: list[AnnotatedDocument], edit: bool, git: bool) -> 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.
|
|
|
|
"""
|
|
|
|
if not annots:
|
|
|
|
return
|
|
|
|
|
|
|
|
for entry in annots:
|
|
|
|
if not entry.annotations:
|
|
|
|
continue
|
|
|
|
|
|
|
|
formatted_annotations: list[str] = []
|
|
|
|
for a in entry.annotations:
|
|
|
|
formatted_annotations.append(_format_annotation(a))
|
|
|
|
|
|
|
|
_add_annots_to_note(entry.document, formatted_annotations)
|
|
|
|
|
|
|
|
if edit:
|
|
|
|
papis.commands.edit.edit_notes(entry.document, git=git)
|
|
|
|
|
|
|
|
|
|
|
|
def _add_annots_to_note(
|
|
|
|
document: papis.document.Document,
|
|
|
|
formatted_annotations: list[str],
|
|
|
|
git: bool = False,
|
|
|
|
) -> None:
|
|
|
|
"""Append new annotations to the end of a note.
|
|
|
|
|
|
|
|
Looks through note to determine any new annotations which should be
|
|
|
|
added and adds them to the end of the note file.
|
|
|
|
"""
|
|
|
|
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] = _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")
|
|
|
|
f.write("\n".join(new_annotations))
|
|
|
|
f.write("\n")
|
|
|
|
logger.info(
|
2023-08-28 10:53:03 +00:00
|
|
|
f"Wrote {len(new_annotations)} "
|
|
|
|
f"{'annotation' if len(new_annotations) == 1 else 'annotations'}"
|
2023-08-28 08:28:06 +00:00
|
|
|
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(
|
|
|
|
formatted_annotations: list[str], file_lines: list[str]
|
|
|
|
) -> list[str]:
|
|
|
|
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 not _test_similarity(an_split[0], file_lines, minimum_similarity):
|
|
|
|
remaining.append(an)
|
|
|
|
|
|
|
|
return remaining
|
|
|
|
|
|
|
|
|
|
|
|
def _test_similarity(
|
|
|
|
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
|