class ManuscriptLineFactory(factory.Factory):
class Meta:
model = ManuscriptLine
manuscript_id = factory.Sequence(lambda n: n)
labels = (
SurfaceLabel.from_label(Surface.OBVERSE),
ColumnLabel.from_label("iii", [Status.COLLATION, Status.CORRECTION]),
)
line = factory.Sequence(
lambda n: TextLine.of_iterable(
LineNumber(n),
(
Word.of(
[
Reading.of_name("ku"),
Joiner.hyphen(),
BrokenAway.open(),
Reading.of_name("nu"),
Joiner.hyphen(),
Reading.of_name("ši"),
BrokenAway.close(),
]
),
),
)
)
paratext = (NoteLine((StringPart("note"),)), RulingDollarLine(Ruling.SINGLE))
omitted_words = (1,)
def test_text_line_atf_erasure(erasure, expected: str) -> None:
word = Word.of(
[Reading.of_name("mu"),
Joiner.hyphen(),
Reading.of_name("mu")])
line = TextLine.of_iterable(LINE_NUMBER, [word, *erasure, word])
assert line.atf == f"{line.line_number.atf} {word.value} {expected} {word.value}"
def test_dump_line():
text = Text(
(
TextLine.of_iterable(
LineNumber(1),
[
Word.of(
parts=[
Reading.of_name("ha"),
Joiner.hyphen(),
Reading.of_name("am"),
]
)
],
),
EmptyLine(),
ControlLine("#", " comment"),
),
"1.0.0",
)
assert TextSchema().dump(text) == {
"lines": OneOfLineSchema().dump(text.lines, many=True),
"parser_version": text.parser_version,
"numberOfLines": 1,
}
def test_update_lemmatization() -> None:
tokens = [list(line) for line in TEXT.lemmatization.tokens]
tokens[0][0] = LemmatizationToken(tokens[0][0].value, (WordId("nu I"),))
lemmatization = Lemmatization(tokens)
expected = Text(
(
TextLine(
LineNumber(1),
(
Word.of(
unique_lemma=(WordId("nu I"),),
parts=[
Reading.of_name("ha"),
Joiner.hyphen(),
Reading.of_name("am"),
],
),
),
),
RulingDollarLine(atf.Ruling.SINGLE),
),
TEXT.parser_version,
)
assert TEXT.update_lemmatization(lemmatization) == expected
def test_update_lemmatization_wrong_lenght() -> None:
line = TextLine.of_iterable(
LINE_NUMBER,
[Word.of([Reading.of_name("bu")]),
Word.of([Reading.of_name("bu")])],
)
lemmatization = (LemmatizationToken("bu", (WordId("nu I"), )), )
with pytest.raises(LemmatizationError):
line.update_lemmatization(lemmatization)
def test_extent_before_translation() -> None:
with pytest.raises(ValueError):
Text.of_iterable(
[
TextLine.of_iterable(LineNumber(1), [Word.of([Reading.of_name("bu")])]),
TextLine.of_iterable(LineNumber(2), [Word.of([Reading.of_name("bu")])]),
TranslationLine(tuple(), "en", Extent(LineNumber(1))),
]
)
def test_update_lemmatization() -> None:
line = TextLine.of_iterable(LINE_NUMBER,
[Word.of([Reading.of_name("bu")])])
lemmatization = (LemmatizationToken("bu", (WordId("nu I"), )), )
expected = TextLine.of_iterable(
LINE_NUMBER,
[Word.of([Reading.of_name("bu")], unique_lemma=(WordId("nu I"), ))])
assert line.update_lemmatization(lemmatization) == expected
def test_extent_overlapping_languages() -> None:
Text.of_iterable(
[
TextLine.of_iterable(LineNumber(1), [Word.of([Reading.of_name("bu")])]),
TranslationLine(tuple(), "en", Extent(LineNumber(2))),
TextLine.of_iterable(LineNumber(2), [Word.of([Reading.of_name("bu")])]),
TranslationLine(tuple(), "de"),
]
)
def test_exent_overlapping() -> None:
with pytest.raises(ValueError):
Text.of_iterable(
[
TextLine.of_iterable(LineNumber(1), [Word.of([Reading.of_name("bu")])]),
TranslationLine(tuple(), extent=Extent(LineNumber(2))),
TextLine.of_iterable(LineNumber(2), [Word.of([Reading.of_name("bu")])]),
TranslationLine(tuple()),
]
)
def text_with_labels():
return Text.of_iterable([
TextLine.of_iterable(LineNumber(1),
[Word.of([Reading.of_name("bu")])]),
ColumnAtLine(ColumnLabel.from_int(1)),
SurfaceAtLine(SurfaceLabel([], atf.Surface.SURFACE, "Stone wig")),
ObjectAtLine(ObjectLabel([], atf.Object.OBJECT, "Stone wig")),
TextLine.of_iterable(LineNumber(2),
[Word.of([Reading.of_name("bu")])]),
])
def test_updating_alignment(client, bibliography, sign_repository, signs,
text_repository):
allow_signs(signs, sign_repository)
chapter = ChapterFactory.build()
allow_references(chapter, bibliography)
text_repository.create_chapter(chapter)
alignment = 0
omitted_words = (1, )
updated_chapter = attr.evolve(
chapter,
lines=(attr.evolve(
chapter.lines[0],
variants=(attr.evolve(
chapter.lines[0].variants[0],
manuscripts=(attr.evolve(
chapter.lines[0].variants[0].manuscripts[0],
line=TextLine.of_iterable(
chapter.lines[0].variants[0].manuscripts[0].line.
line_number,
(Word.of(
[
Reading.of_name("ku"),
Joiner.hyphen(),
BrokenAway.open(),
Reading.of_name("nu"),
Joiner.hyphen(),
Reading.of_name("ši"),
BrokenAway.close(),
],
alignment=alignment,
variant=Word.of(
[Logogram.of_name("KU")],
language=Language.SUMERIAN,
),
), ),
),
omitted_words=omitted_words,
), ),
), ),
), ),
)
expected_chapter = ApiChapterSchema().dump(updated_chapter)
post_result = client.simulate_post(create_chapter_url(
chapter, "/alignment"),
body=json.dumps(DTO))
assert post_result.status == falcon.HTTP_OK
assert post_result.json == expected_chapter
get_result = client.simulate_get(create_chapter_url(chapter))
assert get_result.status == falcon.HTTP_OK
assert get_result.json == expected_chapter
def test_text_line_atf_gloss() -> None:
line = TextLine.of_iterable(
LINE_NUMBER,
[
DocumentOrientedGloss.open(),
Word.of([Reading.of_name("mu")]),
Word.of([Reading.of_name("bu")]),
DocumentOrientedGloss.close(),
],
)
assert line.atf == f"{line.line_number.atf} {{(mu bu)}}"
def test_updating_alignment(corpus, text_repository, bibliography, changelog,
signs, sign_repository, user, when) -> None:
aligmnet = 0
omitted_words = (1, )
updated_chapter = attr.evolve(
CHAPTER,
lines=(attr.evolve(
CHAPTER.lines[0],
variants=(attr.evolve(
CHAPTER.lines[0].variants[0],
manuscripts=(attr.evolve(
CHAPTER.lines[0].variants[0].manuscripts[0],
line=TextLine.of_iterable(
CHAPTER.lines[0].variants[0].manuscripts[0].line.
line_number,
(Word.of(
[
Reading.of_name("ku"),
Joiner.hyphen(),
BrokenAway.open(),
Reading.of_name("nu"),
Joiner.hyphen(),
Reading.of_name("ši"),
BrokenAway.close(),
],
alignment=aligmnet,
), ),
),
omitted_words=omitted_words,
), ),
), ),
), ),
)
expect_find_and_update_chapter(
bibliography,
changelog,
CHAPTER_WITHOUT_DOCUMENTS,
updated_chapter,
signs,
sign_repository,
text_repository,
user,
when,
)
alignment = Alignment((((ManuscriptLineAlignment(
(AlignmentToken("ku-[nu-ši]", aligmnet), ), omitted_words), ), ), ))
assert corpus.update_alignment(CHAPTER.id_, alignment,
user) == updated_chapter
def test_lemmatization() -> None:
line = TextLine.of_iterable(
LINE_NUMBER,
[
Word.of([Reading.of_name("bu")], unique_lemma=(WordId("nu I"), )),
UnknownNumberOfSigns.of(),
Word.of([Reading.of_name("nu")]),
],
)
assert line.lemmatization == (
LemmatizationToken("bu", (WordId("nu I"), )),
LemmatizationToken("..."),
LemmatizationToken("nu", tuple()),
)
def test_parse_normalized_akkadain_shift() -> None:
word = "ha"
line = f"1. {word} %n {word} %sux {word}"
expected = Text((TextLine.of_iterable(
LineNumber(1),
(
Word.of((Reading.of_name(word), ), DEFAULT_LANGUAGE),
LanguageShift.normalized_akkadian(),
AkkadianWord.of((ValueToken.of(word), )),
LanguageShift.of("%sux"),
Word.of((Reading.of_name(word), ), Language.SUMERIAN),
),
), ))
assert parse_atf_lark(line).lines == expected.lines
def test_set_language():
parts = [Determinative.of([Reading.of_name("bu")])]
language = Language.SUMERIAN
lone_determinative = LoneDeterminative.of(parts, Language.AKKADIAN)
expected = LoneDeterminative.of(parts, language)
assert lone_determinative.set_language(language) == expected
def test_parse_atf_language_shifts(code: str,
expected_language: Language) -> None:
word = "ha-am"
parts = [Reading.of_name("ha"), Joiner.hyphen(), Reading.of_name("am")]
line = f"1. {word} {code} {word} %sb {word}"
expected = Text((TextLine.of_iterable(
LineNumber(1),
(
Word.of(parts, DEFAULT_LANGUAGE),
LanguageShift.of(code),
Word.of(parts, expected_language),
LanguageShift.of("%sb"),
Word.of(parts, Language.AKKADIAN),
),
), ))
assert parse_atf_lark(line).lines == expected.lines
def test_determinative():
parts = [Reading.of_name("kur"), Joiner.hyphen(), Reading.of_name("kur")]
determinative = Determinative.of(parts)
expected_value = f"{{{''.join(part.value for part in parts)}}}"
expected_clean_value = f"{{{''.join(part.clean_value for part in parts)}}}"
expected_parts = f"⟨{'⁚'.join(part.get_key() for part in parts)}⟩"
assert determinative.value == expected_value
assert determinative.clean_value == expected_clean_value
assert determinative.get_key() == f"Determinative⁝{expected_value}{expected_parts}"
assert determinative.parts == tuple(parts)
assert determinative.lemmatizable is False
serialized = {
"type": "Determinative",
"parts": OneOfTokenSchema().dump(parts, many=True),
}
assert_token_serialization(determinative, serialized)
def test_linguistic_gloss():
parts = [Reading.of_name("kur"), Joiner.hyphen(), Reading.of_name("kur")]
gloss = LinguisticGloss.of(parts)
expected_value = f"{{{{{''.join(part.value for part in parts)}}}}}"
expected_clean_value = f"{{{{{''.join(part.clean_value for part in parts)}}}}}"
expected_parts = f"⟨{'⁚'.join(part.get_key() for part in parts)}⟩"
assert gloss.value == expected_value
assert gloss.clean_value == expected_clean_value
assert gloss.get_key() == f"LinguisticGloss⁝{expected_value}{expected_parts}"
assert gloss.parts == tuple(parts)
assert gloss.lemmatizable is False
serialized = {
"type": "LinguisticGloss",
"parts": OneOfTokenSchema().dump(parts, many=True),
}
assert_token_serialization(gloss, serialized)
def test_updating_lines_edit(corpus, text_repository, bibliography, changelog,
signs, sign_repository, user, when) -> None:
updated_chapter = attr.evolve(
CHAPTER,
lines=(attr.evolve(
CHAPTER.lines[0],
number=LineNumber(1, True),
variants=(attr.evolve(
CHAPTER.lines[0].variants[0],
manuscripts=(attr.evolve(
CHAPTER.lines[0].variants[0].manuscripts[0],
line=TextLine.of_iterable(
LineNumber(1, True),
(Word.of([
Reading.of_name("nu"),
Joiner.hyphen(),
BrokenAway.open(),
Reading.of_name("ku"),
Joiner.hyphen(),
Reading.of_name("ši"),
BrokenAway.close(),
]), ),
),
), ),
), ),
), ),
signs=("ABZ075 KU ABZ207a\\u002F207b\\u0020X\nKU\nABZ075", ),
parser_version=ATF_PARSER_VERSION,
)
expect_find_and_update_chapter(
bibliography,
changelog,
CHAPTER_WITHOUT_DOCUMENTS,
updated_chapter,
signs,
sign_repository,
text_repository,
user,
when,
)
assert (corpus.update_lines(
CHAPTER.id_, LinesUpdate([], set(), {0: updated_chapter.lines[0]}),
user) == updated_chapter)
def test_statistics(database, fragment_repository):
database[COLLECTION].insert_many(
[
SCHEMA.dump(
FragmentFactory.build(
text=Text(
(
TextLine(
LineNumber(1),
(
Word.of([Reading.of_name("first")]),
Word.of([Reading.of_name("line")]),
),
),
ControlLine("#", "ignore"),
EmptyLine(),
)
)
)
),
SCHEMA.dump(
FragmentFactory.build(
text=Text(
(
ControlLine("#", "ignore"),
TextLine(
LineNumber(1), (Word.of([Reading.of_name("second")]),)
),
TextLine(
LineNumber(2), (Word.of([Reading.of_name("third")]),)
),
ControlLine("#", "ignore"),
TextLine(
LineNumber(3), (Word.of([Reading.of_name("fourth")]),)
),
)
)
)
),
SCHEMA.dump(FragmentFactory.build(text=Text())),
]
)
assert fragment_repository.count_transliterated_fragments() == 2
assert fragment_repository.count_lines() == 4
def test_of_value():
value = "{bu}"
parts = [Determinative.of([Reading.of_name("bu")])]
lone_determinative = LoneDeterminative.of_value(parts)
assert lone_determinative.value == value
assert lone_determinative.lemmatizable is False
assert lone_determinative.language == DEFAULT_LANGUAGE
assert lone_determinative.normalized is False
assert lone_determinative.unique_lemma == tuple()
assert lone_determinative.erasure == ErasureState.NONE
assert lone_determinative.alignment is None
def make_token(self, data, **kwargs):
return (
Reading.of(
data["name_parts"],
data["sub_index"],
data["modifiers"],
data["flags"],
data["sign"],
)
.set_enclosure_type(frozenset(data["enclosure_type"]))
.set_erasure(data["erasure"])
)
def expected_transliteration(language: Language) -> Sequence[Token]:
return (
Word.of([Reading.of_name("bu")], language),
LanguageShift.of("%es"),
Word.of(
[
BrokenAway.open(),
Reading.of((ValueToken(
frozenset({EnclosureType.BROKEN_AWAY}),
ErasureState.NONE,
"kur",
), )).set_enclosure_type(frozenset({EnclosureType.BROKEN_AWAY
})),
],
Language.EMESAL,
),
UnknownNumberOfSigns(frozenset({EnclosureType.BROKEN_AWAY}),
ErasureState.NONE),
BrokenAway.close().set_enclosure_type(
frozenset({EnclosureType.BROKEN_AWAY})),
)
class ManuscriptFactory(factory.Factory):
class Meta:
model = Manuscript
id = factory.Sequence(lambda n: n + 1)
siglum_disambiguator = factory.Faker("word")
museum_number = factory.Sequence(
lambda n: MuseumNumber("M", str(n)) if pydash.is_odd(n) else None
)
accession = factory.Sequence(lambda n: f"A.{n}" if pydash.is_even(n) else "")
period_modifier = factory.fuzzy.FuzzyChoice(PeriodModifier)
period = factory.fuzzy.FuzzyChoice(set(Period) - {Period.NONE})
provenance = factory.fuzzy.FuzzyChoice(set(Provenance) - {Provenance.STANDARD_TEXT})
type = factory.fuzzy.FuzzyChoice(set(ManuscriptType) - {ManuscriptType.NONE})
notes = factory.Faker("sentence")
colophon = Transliteration.of_iterable(
[TextLine.of_iterable(LineNumber(1, True), (Word.of([Reading.of_name("ku")]),))]
)
unplaced_lines = Transliteration.of_iterable(
[TextLine.of_iterable(LineNumber(1, True), (Word.of([Reading.of_name("nu")]),))]
)
references = factory.List(
[factory.SubFactory(ReferenceFactory, with_document=True)], TupleFactory
)
def test_updating_manuscripts(corpus, text_repository, bibliography, changelog,
signs, sign_repository, user, when) -> None:
uncertain_fragments = (MuseumNumber.of("K.1"), )
updated_chapter = attr.evolve(
CHAPTER,
manuscripts=(attr.evolve(
CHAPTER.manuscripts[0],
colophon=Transliteration.of_iterable([
TextLine.of_iterable(LineNumber(1, True),
(Word.of([Reading.of_name("ba")]), ))
]),
unplaced_lines=Transliteration.of_iterable([
TextLine.of_iterable(LineNumber(1, True),
(Word.of([Reading.of_name("ku")]), ))
]),
notes="Updated manuscript.",
), ),
uncertain_fragments=uncertain_fragments,
signs=("KU ABZ075 ABZ207a\\u002F207b\\u0020X\nBA\nKU", ),
)
expect_find_and_update_chapter(
bibliography,
changelog,
CHAPTER_WITHOUT_DOCUMENTS,
updated_chapter,
signs,
sign_repository,
text_repository,
user,
when,
)
manuscripts = (updated_chapter.manuscripts[0], )
assert (corpus.update_manuscripts(CHAPTER.id_, manuscripts,
uncertain_fragments,
user) == updated_chapter)
def test_lone_determinative(language):
value = "{mu}"
parts = [Determinative.of([Reading.of_name("mu")])]
lone_determinative = LoneDeterminative.of(parts, language)
equal = LoneDeterminative.of(parts, language)
other_language = LoneDeterminative.of(parts, Language.UNKNOWN)
other_parts = LoneDeterminative.of(
[Determinative.of([Reading.of_name("bu")])], language)
assert lone_determinative.value == value
assert lone_determinative.lemmatizable is False
assert lone_determinative.language == language
assert lone_determinative.normalized is False
assert lone_determinative.unique_lemma == tuple()
serialized = {
"type": "LoneDeterminative",
"uniqueLemma": [],
"normalized": False,
"language": lone_determinative.language.name,
"lemmatizable": lone_determinative.lemmatizable,
"alignable": lone_determinative.lemmatizable,
"erasure": ErasureState.NONE.name,
"parts": OneOfTokenSchema().dump(parts, many=True),
}
assert_token_serialization(lone_determinative, serialized)
assert lone_determinative == equal
assert hash(lone_determinative) == hash(equal)
for not_equal in [other_language, other_parts]:
assert lone_determinative != not_equal
assert hash(lone_determinative) != hash(not_equal)
assert lone_determinative != ValueToken.of(value)
def test_text_line_of_iterable(code: str, language: Language) -> None:
tokens = [
Word.of([Reading.of_name("first")]),
LanguageShift.of(code),
Word.of([Reading.of_name("second")]),
LanguageShift.of("%sb"),
LoneDeterminative.of([Determinative.of([Reading.of_name("third")])]),
Word.of([BrokenAway.open(),
Reading.of_name("fourth")]),
UnknownNumberOfSigns.of(),
BrokenAway.close(),
]
expected_tokens = (
Word.of([Reading.of_name("first")], DEFAULT_LANGUAGE),
LanguageShift.of(code),
Word.of([Reading.of_name("second")], language),
LanguageShift.of("%sb"),
LoneDeterminative.of([Determinative.of([Reading.of_name("third")])],
Language.AKKADIAN),
Word.of(
[
BrokenAway.open(),
Reading.of((ValueToken(
frozenset({EnclosureType.BROKEN_AWAY}),
ErasureState.NONE,
"fourth",
), )).set_enclosure_type(frozenset({EnclosureType.BROKEN_AWAY
})),
],
DEFAULT_LANGUAGE,
),
UnknownNumberOfSigns(frozenset({EnclosureType.BROKEN_AWAY}),
ErasureState.NONE),
BrokenAway.close().set_enclosure_type(
frozenset({EnclosureType.BROKEN_AWAY})),
)
line = TextLine.of_iterable(LINE_NUMBER, tokens)
assert line.line_number == LINE_NUMBER
assert line.content == expected_tokens
assert (
line.key ==
f"TextLine⁞{line.atf}⟨{'⁚'.join(token.get_key() for token in expected_tokens)}⟩"
)
assert line.atf == f"1. first {code} second %sb {{third}} [fourth ...]"
def test_variant():
reading = Reading.of([ValueToken.of("sa"), BrokenAway.open(), ValueToken.of("l")])
divider = Divider.of(":")
variant = Variant.of(reading, divider)
expected_value = "sa[l/:"
assert variant.value == expected_value
assert variant.clean_value == "sal/:"
assert variant.tokens == (reading, divider)
assert variant.parts == variant.tokens
assert (
variant.get_key()
== f"Variant⁝{expected_value}⟨{'⁚'.join(token.get_key() for token in variant.tokens)}⟩"
)
assert variant.lemmatizable is False
serialized = {
"type": "Variant",
"tokens": OneOfTokenSchema().dump([reading, divider], many=True),
}
assert_token_serialization(variant, serialized)
def test_reading(
name_parts,
sub_index,
modifiers,
flags,
sign,
expected_value,
expected_clean_value,
expected_name,
) -> None:
reading = Reading.of(name_parts, sub_index, modifiers, flags, sign)
expected_parts = (*name_parts, sign) if sign else name_parts
assert reading.value == expected_value
assert reading.clean_value == expected_clean_value
assert (
reading.get_key() ==
f"Reading⁝{expected_value}⟨{'⁚'.join(token.get_key() for token in expected_parts)}⟩"
)
assert reading.name_parts == name_parts
assert reading.name == expected_name
assert reading.modifiers == tuple(modifiers)
assert reading.flags == tuple(flags)
assert reading.lemmatizable is False
assert reading.sign == sign
serialized = {
"type": "Reading",
"name": expected_name,
"nameParts": OneOfTokenSchema().dump(name_parts, many=True),
"subIndex": sub_index,
"modifiers": modifiers,
"flags": [flag.value for flag in flags],
"sign": sign and OneOfTokenSchema().dump(sign),
}
assert_token_serialization(reading, serialized)
