def data_of_file(file: str) -> Conversacion:
ms = (Mensaje.parse(m) for m in lineas_de_fichero(file))
mensajes = [m for m in ms if m is not None]
palabrasHuecas = {
p
for p in lineas_de_fichero(
"../../../resources/palabras_huecas.txt") if len(p) > 0
}
return Conversacion(mensajes, palabrasHuecas)
def linea_numero(file: str, n: int) -> str:
return find_first(enumerate(lineas_de_fichero(file)),
predicate=lambda p: p[0] == n).get()[1]
def palabra_en_lineas(file: str) -> OrderedDict[str, set[int]]:
lns = lineas_de_fichero(file, encoding='utf-16')
palabras = ((i, p) for i, linea in enumerate(lns)
for p in re.split(sep, linea) if len(p) > 0)
d = grouping_set(palabras, fkey=lambda e: e[1], fvalue=lambda e: e[0])
return OrderedDict(sorted(d.items(), key=lambda t: t[0]))
def linea_mas_larga(file: str) -> str:
return max(lineas_de_fichero(file), key=lambda x: len(x))
def primera_linea_con_palabra(file: str, palabra: str) -> str:
return find_first(lineas_de_fichero(file),
predicate=lambda ln: palabra in ln).get()
def longitud_media_de_lineas(file: str) -> float:
return average(len(ln) for ln in lineas_de_fichero(file))
def numero_de_lineas_vacias(file: str) -> int:
return count(ln for ln in lineas_de_fichero(file, encoding='utf-16')
if len(ln) == 0)
def numero_de_lineas(file: str) -> int:
return len(lineas_de_fichero(file))
def palabras_no_huecas(file: str) -> Iterable[str]:
huecas = palabras_huecas()
lns = lineas_de_fichero(file, encoding='utf-16')
pls = flat_map(lns, lambda x: re.split(sep, x))
palabras = (p for p in pls if p not in huecas if len(p) > 0)
return palabras
def palabras_huecas() -> set[str]:
lns = lineas_de_fichero("../../../resources/palabras_huecas.txt")
return {p for p in lns}
if __name__ == '__main__':
i = 0
for n in numeros:
print(i, n, sep=': ')
i = i + 1
texto = "Muestrame con puntos"
for c in texto:
print(c, end='.')
with open('../../../resources/datos_2.txt', encoding='utf-8') as f:
contenido = f.read()
print(contenido) # Mostramos el contenido del fichero
with open('../../../resources/datos_2.txt', encoding='utf-8') as f:
for linea in f:
print(linea, end='')
print(f)
ls = lineas_de_fichero('../../../resources/datos_2.txt')
print(ls)
print(math.pi)
r = montecarlo_list(1000000)
draw_multiline(r)
print(r[-1])
# similar a Counter
def groups_size(iterable: Iterable[E],
fkey: Callable[[E], K] = identity,
fsum: Callable[[E], int] = lambda e: 1) -> dict[K, int]:
return grouping_reduce(iterable, fkey, op=lambda x, y: x + y, fvalue=fsum)
if __name__ == '__main__':
print(str_iterable(range(0, 100)))
print(average(range(0, 100)))
print(str_iterable(flat_map([[0, 1], [2, 3, 4], [5, 6], [9]])))
print(str_iterable(geometric(2, 100, 5)))
print(index_bool((x % 29 == 0 for x in aleatorios(10, 1000, 50))))
print(str_iterable(lineas_de_fichero('../../../resources/datos.txt')))
print(
index_predicate(
(int(e)
for e in lineas_de_fichero('../../../resources/datos.txt')),
lambda x: x == 7))
print(first_and_last(arithmetic(3, 500, 29)))
print(list(zip2([1, 2, 3, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14, 15])))
g = grouping_reduce(range(0, 10, 2),
fkey=lambda x: x % 3,
op=lambda x, y: x + y)
print(g[0])
cp = Counter(['a', 'b', 'c', 'a', 'b', 'b'])
print(cp.most_common(1)[0][1])
r = ((1, 2, 3, 4) * 2)[-2:-1]
print(r)