124 lines
4.3 KiB
Python
124 lines
4.3 KiB
Python
from __future__ import annotations
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import logging
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import re
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from typing import Any, Callable
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from comicapi.comicarchive import ComicArchive
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from comicapi.genericmetadata import GenericMetadata
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from comictaggerlib.ctsettings import ct_ns
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from comictaggerlib.issueidentifier import IssueIdentifier, IssueIdentifierOptions
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from comictaggerlib.issueidentifier import Result as IIResult
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from comictaggerlib.md import prepare_metadata
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from comictaggerlib.resulttypes import Action, MatchStatus, OnlineMatchResults, Result, Status
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from comictalker.comictalker import ComicTalker, RLCallBack, TalkerError
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logger = logging.getLogger(__name__)
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def identify_comic(
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ca: ComicArchive,
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md: GenericMetadata,
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tags_read: list[str],
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match_results: OnlineMatchResults,
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config: ct_ns,
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talker: ComicTalker,
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output: Callable[[str], Any],
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on_rate_limit: RLCallBack | None,
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on_progress: Callable[[int, int, bytes], Any] | None = None,
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) -> tuple[Result, OnlineMatchResults]:
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# ct_md, results, matches, match_results
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if md is None or md.is_empty:
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logger.error("No metadata given to search online with!")
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res = Result(
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Action.save,
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status=Status.match_failure,
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original_path=ca.path,
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match_status=MatchStatus.no_match,
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tags_read=tags_read,
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)
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match_results.no_matches.append(res)
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return res, match_results
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iio = IssueIdentifierOptions(
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series_match_search_thresh=config.Issue_Identifier__series_match_search_thresh,
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series_match_identify_thresh=config.Issue_Identifier__series_match_identify_thresh,
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use_publisher_filter=config.Auto_Tag__use_publisher_filter,
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publisher_filter=config.Auto_Tag__publisher_filter,
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quiet=config.Runtime_Options__quiet,
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cache_dir=config.Runtime_Options__config.user_cache_dir,
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border_crop_percent=config.Issue_Identifier__border_crop_percent,
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talker=talker,
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)
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ii = IssueIdentifier(
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iio,
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output=output,
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on_rate_limit=on_rate_limit,
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on_progress=on_progress,
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)
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if not config.Auto_Tag__use_year_when_identifying:
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md.year = None
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if config.Auto_Tag__ignore_leading_numbers_in_filename and md.series is not None:
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md.series = re.sub(r"^([\d.]+)", "", md.series)
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result, matches = ii.identify(ca, md)
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res = Result(
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Action.save,
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status=Status.match_failure,
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original_path=ca.path,
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online_results=matches,
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tags_read=tags_read,
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)
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if result == IIResult.multiple_bad_cover_scores:
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res.match_status = MatchStatus.low_confidence_match
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logger.error("Online search: Multiple low confidence matches. Save aborted")
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match_results.low_confidence_matches.append(res)
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return res, match_results
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if result == IIResult.single_bad_cover_score and config.Runtime_Options__abort_on_low_confidence:
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logger.error("Online search: Low confidence match. Save aborted")
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res.match_status = MatchStatus.low_confidence_match
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match_results.low_confidence_matches.append(res)
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return res, match_results
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if result == IIResult.multiple_good_matches:
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logger.error("Online search: Multiple good matches. Save aborted")
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res.match_status = MatchStatus.multiple_match
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match_results.multiple_matches.append(res)
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return res, match_results
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if result == IIResult.no_matches:
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logger.error("Online search: No match found. Save aborted")
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res.match_status = MatchStatus.no_match
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match_results.no_matches.append(res)
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return res, match_results
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# we got here, so we have a single match
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# now get the particular issue data
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try:
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ct_md = talker.fetch_comic_data(issue_id=matches[0].issue_id, on_rate_limit=on_rate_limit)
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except TalkerError as e:
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logger.exception(f"Error retrieving issue details. Save aborted.\n{e}")
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ct_md = GenericMetadata()
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ct_md = prepare_metadata(md, ct_md, config)
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if ct_md.is_empty:
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res.status = Status.fetch_data_failure
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res.match_status = MatchStatus.good_match
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match_results.fetch_data_failures.append(res)
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return res, match_results
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res.status = Status.success
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res.md = ct_md
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if result == IIResult.single_good_match:
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res.match_status = MatchStatus.good_match
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return res, match_results
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