text
stringlengths 1
93.6k
|
|---|
epub,
|
xhtml_path,
|
)
|
supported_languages = load_languages_data(data.plugin_path)
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gloss_lang = prefs["gloss_lang"]
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gloss_source = supported_languages[gloss_lang]["gloss_source"]
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epub.modify_epub(prefs, data.book_lang, gloss_lang, gloss_source)
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return
|
# Kindle
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final_start = calculate_final_start(data)
|
if data.create_ww:
|
ll_conn, ll_path = create_lang_layer(
|
data.asin,
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data.book_path,
|
data.acr,
|
data.revision,
|
)
|
if data.create_x:
|
x_ray_conn, x_ray_path = create_x_ray_db(
|
data.asin,
|
data.book_path,
|
data.book_lang,
|
data.plugin_path,
|
prefs,
|
mediawiki.sitename,
|
)
|
x_ray = X_Ray(x_ray_conn, mediawiki, wikidata, custom_x_ray)
|
for doc, context in nlp.pipe(parse_book(data), as_tuples=True):
|
if data.kfx_json is not None:
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start = context
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escaped_text = None
|
else:
|
start, escaped_text = context
|
if data.create_x:
|
find_named_entity(
|
start,
|
x_ray,
|
doc,
|
data.mobi_codec,
|
data.book_lang,
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escaped_text,
|
custom_x_ray,
|
)
|
if data.create_ww:
|
kindle_find_lemma(
|
doc,
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lemma_matcher,
|
start,
|
data.mobi_codec,
|
escaped_text,
|
lemmas_conn,
|
ll_conn,
|
data.book_lang,
|
prefs,
|
)
|
if notif:
|
notif.put((start / final_start, "Creating files"))
|
if data.create_x:
|
x_ray.finish(
|
x_ray_path,
|
final_start,
|
data.kfx_json,
|
data.mobi_html,
|
data.mobi_codec,
|
prefs,
|
)
|
if data.create_ww:
|
save_db(ll_conn, ll_path)
|
lemmas_conn.close() # type: ignore
|
def parse_book(data: ParseJobData) -> Iterator[tuple[str, tuple[int, str] | int]]:
|
if data.kfx_json is not None:
|
for entry in filter(lambda x: x["type"] == 1, data.kfx_json):
|
# Remove byte order mark and word joiner
|
yield re.sub(r"\ufeff|\u2060", " ", entry["content"]), entry["position"]
|
elif data.mobi_html is not None:
|
# match text inside HTML tags
|
for match_body in re.finditer(b"<body.{3,}?</body>", data.mobi_html, re.DOTALL):
|
for m in re.finditer(b">[^<]{2,}<", match_body.group(0)):
|
text = m.group(0)[1:-1].decode(data.mobi_codec)
|
text = re.sub(r"\ufeff|\u2060", " ", text)
|
yield unescape(text), (match_body.start() + m.start() + 1, text)
|
def index_in_escaped_text(
|
token: str, escaped_text: str, start_offset: int
|
) -> tuple[int, int] | None:
|
if token not in escaped_text[start_offset:]:
|
# replace Unicode character to numeric character reference
|
token = escape(token, False).encode("ascii", "xmlcharrefreplace").decode()
|
if token in escaped_text[start_offset:]:
|
token_start = escaped_text.index(token, start_offset)
|
return token_start, token_start + len(token)
|
else:
|
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