Datasets:
jblitzar
/
github-python-corpus

Dataset card Data Studio Files
xet
Community
text
stringlengths
1
93.6k
else:
return get_kindle_lemma_without_pos(word, conn)
def get_kindle_lemma_with_pos(
lemma: str,
word: str,
pos: str,
conn: sqlite3.Connection,
lemma_lang: str,
prefs: Prefs,
) -> tuple[int, int] | None:
if use_kindle_ww_db(lemma_lang, prefs):
pos = spacy_to_kindle_pos(pos)
else:
pos = spacy_to_wiktionary_pos(pos)
for data in conn.execute(
"""
SELECT difficulty, senses.id
FROM senses JOIN lemmas ON senses.lemma_id = lemmas.id
WHERE lemma = ? AND pos = ? AND enabled = 1 LIMIT 1
""",
(lemma, pos),
):
return data
return get_kindle_lemma_without_pos(word, conn)
def get_kindle_lemma_without_pos(
word: str, conn: sqlite3.Connection
) -> tuple[int, int] | None:
for data in conn.execute(
"""
SELECT difficulty, senses.id
FROM senses JOIN lemmas
ON senses.lemma_id = lemmas.id
WHERE lemma = ? AND enabled = 1 LIMIT 1
""",
(word,),
):
return data
for data in conn.execute(
"""
SELECT difficulty, senses.id
FROM senses JOIN forms
ON senses.lemma_id = forms.lemma_id AND senses.pos = forms.pos
WHERE form = ? AND enabled = 1 LIMIT 1
""",
(word,),
):
return data
return None
def kindle_add_lemma(
token_start: int,
token_end: int,
text_start: int,
text: str,
ll_conn: Connection,
mobi_codec: str,
escaped_text: str,
starts: set[int],
data: tuple[int, int],
):
end = None
lemma = text[token_start:token_end]
if mobi_codec:
result = index_in_escaped_text(lemma, escaped_text, token_start)
if result is None:
return
lemma_start, lemma_end = result
index = text_start + len(escaped_text[:lemma_start].encode(mobi_codec))
else:
index = text_start + token_start
if index in starts:
return
else:
starts.add(index)
if " " in lemma:
if mobi_codec:
end = index + len(escaped_text[lemma_start:lemma_end].encode(mobi_codec))
else:
end = index + len(lemma)
insert_lemma(ll_conn, (index, end) + data)
DIRECTIONS = frozenset(
[
"north",
"east",
"south",
"west",
"northeast",
"southeast",
"southwest",
"northwest",
]