Marty Oehme
b564ab4792
Added static analysis (lint, type checking) to be done on each push, and testing to be done on each master branch commit.
112 lines
3.6 KiB
Python
112 lines
3.6 KiB
Python
from pathlib import Path
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from typing import Any, Optional
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import Levenshtein
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import fitz_new as fitz
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import papis.logging
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import papis.config
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from papis_extract.annotation_data import Annotation
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logger = papis.logging.get_logger(__name__)
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def start(filename: Path) -> list[Annotation]:
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"""Extract annotations from a file.
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Returns all readable annotations contained in the file
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passed in. Only returns Highlight or Text annotations.
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"""
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annotations = []
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with fitz.Document(filename) as doc:
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for page in doc:
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for annot in page.annots():
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quote, note = _retrieve_annotation_content(page, annot)
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if not quote and not note:
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continue
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a = Annotation(
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file=str(filename),
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text=quote or "",
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content=note or "",
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colors=annot.colors,
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type=annot.type[1],
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page=(page.number or 0) + 1,
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)
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a.tag = _tag_from_colorname(a.colorname or "")
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annotations.append(a)
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logger.debug(
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f"Found {len(annotations)} "
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f"{'annotation' if len(annotations) == 1 else 'annotations'} for {filename}."
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)
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return annotations
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def _tag_from_colorname(colorname: str) -> str:
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color_mapping: dict[str, str] = getdict("tags", "plugins.extract")
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if not color_mapping:
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return ""
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return color_mapping.get(colorname, "")
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def _retrieve_annotation_content(
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page: fitz.Page, annotation: fitz.Annot
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) -> tuple[str | None, str | None]:
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"""Gets the text content of an annotation.
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Returns the actual content of an annotation. Sometimes
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that is only the written words, sometimes that is only
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annotation notes, sometimes it is both. Runs a similarity
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comparison between strings to find out whether they
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should both be included or are the same, using
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Levenshtein distance.
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"""
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content = annotation.info["content"].replace("\n", " ")
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written = page.get_textbox(annotation.rect).replace("\n", " ")
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# highlight with selection in note
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minimum_similarity = (
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papis.config.getfloat("minimum_similarity_content", "plugins.extract") or 1.0
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)
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if Levenshtein.ratio(content, written) > minimum_similarity:
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return (content, None)
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# both a highlight and a note
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elif content and written:
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return (written, content)
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# an independent note, not a highlight
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elif content:
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return (None, content)
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# highlight with selection not in note
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elif written:
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return (written, None)
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# just a highlight without any text
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return (None, None)
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# mimics the functions in papis.config.{getlist,getint,getfloat} etc.
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def getdict(key: str, section: Optional[str] = None) -> dict[str, str]:
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"""Dict getter
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:returns: A python dict
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:raises SyntaxError: Whenever the parsed syntax is either not a valid
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python object or a valid python dict.
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"""
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rawvalue: Any = papis.config.general_get(key, section=section)
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if isinstance(rawvalue, dict):
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return rawvalue
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try:
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rawvalue = eval(rawvalue)
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except Exception:
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raise SyntaxError(
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"The key '{}' must be a valid Python object: {}".format(key, rawvalue)
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)
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else:
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if not isinstance(rawvalue, dict):
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raise SyntaxError(
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"The key '{}' must be a valid Python dict. Got: {} (type {!r})".format(
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key, rawvalue, type(rawvalue).__name__
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)
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)
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return rawvalue
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