dschlueter
cd62feab69
Ersetzt das Modell ein gültiges Wort nur durch eine andere Form („Punkten“ → „Punkte“, „das“ → „dass“, „sehe“ → „sähe“), heißt der Grund jetzt „Wortform geändert“. Diese Fälle stehen im Bericht in einer eigenen Tabelle nach den sinnverändernden, im Text gestrichelt umrahmt, und in der Konsole am Ende. „-in“ zählt nicht als Endung: „Professor“ → „Professorin“ bleibt oben. Außerdem: Die Tabellen scrollen auf schmalen Bildschirmen waagrecht, und aenderungen.py meldet Zeit-Überschriften nicht als Einfügung, wenn der Rohtext (z. B. eine .vtt) keine hat. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
323 lines
13 KiB
Python
323 lines
13 KiB
Python
"""Tests for aenderungen.py (change report raw transcript -> corrected text)."""
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import html
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import re
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import sys
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from pathlib import Path
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import pytest
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import aenderungen as ae
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def changes(raw, corrected):
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return [(tag, " ".join(old), " ".join(new))
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for tag, old, new in ae.compare(raw, corrected).changes()]
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def report_text(page):
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"""Corrected text as shown in the report, without original/deleted words."""
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body = page.split("<h2>Korrigierter Text</h2>")[1]
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body = re.sub(r"<del[^>]*>.*?</del>|<span class=orig>.*?</span>", "", body)
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return html.unescape(re.sub(r"<[^>]+>", " ", body)).split()
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@pytest.mark.parametrize("raw, corrected", [
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("das ist gut", "Das ist gut."), # case, punctuation
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("all das zerstritten", "All das – zerstritten."), # dash only
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("wie z.B. hier", "wie z. B. hier"), # split abbreviation
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("eins zwei", "eins\n\nzwei"), # paragraph break
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])
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def test_expected_edits_are_no_changes(raw, corrected):
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assert changes(raw, corrected) == []
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@pytest.mark.parametrize("raw, corrected", [
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("gibt's", "gibt’s"), # apostrophe variants
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("er sagte Frieden", "Er sagte ‚Frieden‘."), # quotes at the edges
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])
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def test_apostrophes_and_quotes_unchanged(raw, corrected):
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assert changes(raw, corrected) == []
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def test_apostrophe_inside_word_is_a_change():
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assert changes("Egon Bahrs Politik", "Egon Bahr’s Politik") == [
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("replace", "Bahrs", "Bahr’s"),
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]
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def test_english_review_marks():
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comparison = ae.compare("his name is Kocher", "His name is Kocher [check: Kocha].")
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assert list(comparison.changes()) == []
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assert sum(len(m) for m in comparison.marks.values()) == 1
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def test_replace_insert_delete():
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raw = "die gedeiliche Zusammenarbeit war das gut heute"
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corrected = "die gedeihliche Zusammenarbeit war doch gut"
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assert changes(raw, corrected) == [
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("replace", "gedeiliche", "gedeihliche"),
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("replace", "das", "doch"),
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("delete", "heute", ""),
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]
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assert changes("ein Wort", "ein neues Wort") == [("insert", "", "neues")]
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def test_change_summary_counts_and_sorts():
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raw = "Kremmel und Kremmel und Bar"
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corrected = "Kreml und Kreml und Bahr"
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assert ae.change_summary(ae.compare(raw, corrected)) == [
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("Kremmel", "Kreml", 2), ("Bar", "Bahr", 1),
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]
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def test_review_marks_are_not_changes_but_shown():
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corrected = "Er heißt Gerhard [prüfen: Ghard] Kocher."
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comparison = ae.compare("Er heißt Gerhard Kocher", corrected)
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assert list(comparison.changes()) == []
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page = ae.render_html(comparison, "t")
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assert "<span class=check>[prüfen: Ghard]</span>" in page
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assert "1 Prüfmarken" in page
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def test_render_html_shows_text_original_and_paragraphs():
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raw = "die gedeiliche Zusammenarbeit <b> ist gut heute neuer Absatz"
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corrected = "Die gedeihliche Zusammenarbeit <b> ist gut.\n\nNeuer Absatz."
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page = ae.render_html(ae.compare(raw, corrected), "Rede & Co")
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assert report_text(page) == corrected.split()
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assert "title='Original: gedeiliche'" in page
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assert "<del title='gestrichen'>heute</del>" in page
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assert "<b>" in page and "<b>" not in page.split("<body>")[1]
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assert "Rede & Co" in page
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assert page.split("<h2>Korrigierter Text</h2>")[1].count("<p>") == 2
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def test_report_path():
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assert ae.report_path(Path("a/rede.korrigiert.txt")) == Path("a/rede.aenderungen.html")
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assert ae.report_path(Path("out.txt")) == Path("out.aenderungen.html")
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def test_cli(tmp_path, monkeypatch, capsys):
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raw = tmp_path / "rede.vtt"
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raw.write_text(
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"WEBVTT\n\n00:00:01.000 --> 00:00:02.000\ndas Kremmel heute\n", encoding="utf-8"
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)
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corrected = tmp_path / "rede.korrigiert.txt"
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corrected.write_text("Das Kreml heute.\n", encoding="utf-8")
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monkeypatch.setattr(sys, "argv", ["aenderungen.py", "-a", str(raw), "-b", str(corrected)])
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ae.main()
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assert (tmp_path / "rede.aenderungen.html").is_file()
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out = capsys.readouterr().out
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assert "1× „Kremmel“ → „Kreml“" in out
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def test_cli_missing_file(tmp_path, monkeypatch, capsys):
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monkeypatch.setattr(sys, "argv", ["aenderungen.py", "-a", "fehlt.txt", "-b", "fehlt.txt"])
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with pytest.raises(SystemExit):
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ae.main()
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assert "Datei nicht gefunden" in capsys.readouterr().err
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# === Suspect changes ===
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WORDS = {"professor", "das", "dass", "ist", "haus", "unterschreiben", "bar"}
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def suspects(model_input, corrected, wordlist=WORDS, glossary=(), lang="de"):
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found = ae.review_candidates(ae.compare(model_input, corrected), wordlist, glossary, lang)
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return [(s.reason, s.old, s.new) for s in found]
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@pytest.mark.parametrize("model_input, corrected, expected", [
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("Der Professor kam", "Der Professorin kam", [(ae.VALID_WORD, "Professor", "Professorin")]),
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("wir unterschreiben das", "wir unterscheiden das",
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[(ae.VALID_WORD, "unterschreiben", "unterscheiden")]),
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("im CT1 heute", "im ZDF heute", [(ae.CHANGED_A_LOT, "CT1", "ZDF")]),
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("er kam heute", "er ist kam heute", [(ae.INSERTED, "", "ist")]),
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("er kam heute", "er kam", [(ae.DELETED, "heute", "")]),
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])
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def test_review_candidates_reports(model_input, corrected, expected):
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assert suspects(model_input, corrected) == expected
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@pytest.mark.parametrize("model_input, corrected", [
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("das Kremmel heute", "das Kreml heute"), # recognition error
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("die Gradwanderung", "die Gratwanderung"),
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("die Clan Kriminalität", "die Clankriminalität"), # spacing only
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("KI generierte Videos", "KI-generierte Videos"), # hyphen only
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("er äh kam ähm heute", "er kam heute"), # fillers
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("das ist gut", "Das ist gut."), # case, punctuation
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])
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def test_review_candidates_ignores(model_input, corrected):
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assert suspects(model_input, corrected) == []
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def test_review_candidates_glossary_spellings_are_not_reported():
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glossary = ae.glossary_entries(["Egon Bahr", ""], [("Bars", "Bahrs")])
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assert glossary == {("egon", "bahr"), ("bahrs",)}
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assert suspects("Bar sagte", "Bahr sagte", glossary=glossary) == []
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assert suspects("Bar sagte", "Bahr sagte") == [(ae.VALID_WORD, "Bar", "Bahr")]
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@pytest.mark.parametrize("model_input, corrected, expected", [
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# A common word of a longer entry explains nothing on its own
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("das sagt ihn nicht", "Das sagt Sie nicht.", [(ae.CHANGED_A_LOT, "ihn", "Sie")]),
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# Inserted words stay suspect even if they are in the glossary
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("er kam heute", "er ist kam heute", [(ae.INSERTED, "", "ist")]),
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("Dobrind sagte", "Alexander Dobrindt sagte",
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[(ae.CHANGED_A_LOT, "Dobrind", "Alexander Dobrindt")]),
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])
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def test_review_candidates_glossary_explains_only_spellings(model_input, corrected, expected):
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glossary = ae.glossary_entries(
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["Alexander Dobrindt"], [("befinden Sie", "finden Sie"), ("is", "ist")]
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)
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assert suspects(model_input, corrected, glossary=glossary) == expected
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def test_review_candidates_fillers_per_language():
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# "er" and "um" are real German words; in English they are fillers
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assert suspects("dann kam er um zu helfen", "Dann kam, zu helfen.") == [
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(ae.DELETED, "er um", "")
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]
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english = suspects("so er we um go", "So we go.", lang="en")
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assert english == []
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def test_review_candidates_without_wordlist():
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# Similar replacements of real words go unnoticed, the rest still counts
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assert suspects("Der Professor kam", "Der Professorin kam", wordlist=None) == []
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assert suspects("im CT1 heute", "im ZDF heute", wordlist=None) == [
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(ae.CHANGED_A_LOT, "CT1", "ZDF")
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]
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def test_review_candidates_indices_point_into_corrected_words():
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comparison = ae.compare("a b Professor c d", "A b Professorin c d.")
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[suspect] = ae.review_candidates(comparison, WORDS, set())
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assert comparison.words[suspect.j1:suspect.j2] == ["Professorin"]
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def test_load_wordlist(capsys):
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assert "professor" in ae.load_wordlist("de")
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assert ae.load_wordlist("en") is None
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assert "keine Wortliste für „en“ (Paket wamerican)" in capsys.readouterr().out
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def suspect_section(page):
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return page.split("<h2>Zu prüfen")[1].split("<h2>Alle Änderungen")[0]
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def test_report_suspects_only_against_model_input(tmp_path, capsys):
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target = tmp_path / "bericht.html"
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# Glossary turned "Kremmel" into "Kreml" before the model; the model
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# replaced "Professor" and deleted "heute" on its own
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comparison = ae.write_report(
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"der Professor im Kremmel heute dort", "Der Professorin im Kreml dort.", target,
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"rede", model_input="der Professor im Kreml heute dort",
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)
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page = target.read_text(encoding="utf-8")
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section = suspect_section(page)
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assert [s.reason for s in comparison.suspects] == [ae.VALID_WORD, ae.DELETED]
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assert "Zu prüfen (2)" in page
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assert "Professorin" in section and "Kremmel" not in section
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assert "<span class='warn' title='gültiges Wort ersetzt: „Professor“ → „Professorin“'>" in page
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assert "<span class=warn title='gestrichen: „heute“ → „∅“'>⚠</span>" in page
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# Framing changes nothing about the text itself
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assert report_text(page) == "Der Professorin im Kreml ⚠ dort.".split()
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ae.print_summary(comparison)
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out = capsys.readouterr().out
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assert "Zu prüfen: 2 Stellen" in out
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assert "gültiges Wort ersetzt: „Professor“ → „Professorin“" in out
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def test_report_without_suspects(tmp_path):
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target = tmp_path / "bericht.html"
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comparison = ae.write_report("das Kremmel", "Das Kreml.", target, "rede")
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assert comparison.suspects == []
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assert "Keine auffälligen Änderungen" in suspect_section(target.read_text(encoding="utf-8"))
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def test_cli_ignores_time_headers_missing_in_raw(tmp_path, monkeypatch, capsys):
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raw = tmp_path / "rede.vtt"
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raw.write_text(
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"WEBVTT\n\n00:00:01.000 --> 00:00:02.000\ndas Kremmel heute\n", encoding="utf-8"
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)
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corrected = tmp_path / "rede.korrigiert.txt"
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corrected.write_text("[00:00:01 - 00:00:02]\n\nDas Kreml heute.\n", encoding="utf-8")
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monkeypatch.setattr(sys, "argv", ["aenderungen.py", "-a", str(raw), "-b", str(corrected)])
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ae.main()
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out = capsys.readouterr().out
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assert "Zu prüfen: 0 Stellen" in out
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assert "00:00:01" not in out
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def test_cli_glossary(tmp_path, monkeypatch, capsys):
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raw = tmp_path / "rede.txt"
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raw.write_text("das Kremmel und\nBar heute\n", encoding="utf-8")
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corrected = tmp_path / "rede.korrigiert.txt"
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corrected.write_text("Das Kreml und Bahr heute.\n", encoding="utf-8")
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glossary = tmp_path / "g.txt"
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glossary.write_text("Kremmel => Kreml\nEgon Bahr\n", encoding="utf-8")
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argv = ["aenderungen.py", "-a", str(raw), "-b", str(corrected)]
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monkeypatch.setattr(sys, "argv", argv)
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ae.main()
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assert "gültiges Wort ersetzt: „Bar“ → „Bahr“" in capsys.readouterr().out
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monkeypatch.setattr(sys, "argv", [*argv, "-g", str(glossary)])
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ae.main()
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out = capsys.readouterr().out
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assert "Zu prüfen: 0 Stellen" in out
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# The report still compares against the raw transcript
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assert "1× „Kremmel“ → „Kreml“" in out
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@pytest.mark.parametrize("old, new, expected", [
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("Punkten", "Punkte", True),
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("das", "dass", True),
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("sehe", "sähe", True), # umlaut
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("sein", "seien", True), # both endings change
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("kommt,", "kommen,", True), # punctuation does not count
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("Professor", "Professorin", False), # "-in" is no inflection
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("geworben", "geworden", False),
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("unterschreiben", "unterscheiden", False),
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("ich", "sich", False),
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("den", "der", False), # stem too short
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("sich dazu", "zu", False), # more than one word
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])
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def test_word_form_change(old, new, expected):
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assert ae.word_form_change(old.split(), new.split()) is expected
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def test_word_form_change_english():
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assert ae.word_form_change(["walk"], ["walked"], "en")
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assert not ae.word_form_change(["walk"], ["walker"], "en")
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def test_review_candidates_word_forms():
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words = WORDS | {"punkten", "punkte"}
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assert suspects("die Punkten und das", "die Punkte und dass", wordlist=words) == [
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(ae.WORD_FORM, "Punkten", "Punkte"), (ae.WORD_FORM, "das", "dass"),
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]
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def test_report_and_summary_put_word_forms_last(tmp_path, capsys):
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target = tmp_path / "bericht.html"
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comparison = ae.write_report(
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"das sagte der Professor", "dass sagte der Professorin", target, "rede"
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)
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assert [s.reason for s in comparison.suspects] == [ae.WORD_FORM, ae.VALID_WORD]
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page = target.read_text(encoding="utf-8")
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section = suspect_section(page)
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# Meaning change in the main table, the word form in its own group after it
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assert section.index("Professorin") < section.index("Wortform geändert (1)")
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assert section.index("Wortform geändert (1)") < section.index("<ins>dass</ins>")
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assert "<span class='warn form' title='Wortform geändert: „das“ → „dass“'>" in page
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ae.print_summary(comparison)
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out = capsys.readouterr().out.split("Zu prüfen: ")[1]
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assert out.startswith("2 Stellen (davon 1 Wortformen)")
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assert out.index("Professorin") < out.index("„das“ → „dass“")
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