Библиотека Python разработчика | Книги по питону
Погружение в CPython и архитектуру. Разбираем неочевидное поведение (GIL, Memory), Best Practices (SOLID, DDD) и тонкости Django/FastAPI. Решаем задачи с подвохом и оптимизируем алгоритмы. 🐍 По всем вопросам @evgenycarter РКН clck.ru/3Ko7Hq
Mostrar más📈 Análisis del canal de Telegram Библиотека Python разработчика | Книги по питону
El canal Библиотека Python разработчика | Книги по питону (@bookpython) en el segmento lingüístico de Ruso es un actor destacado. Actualmente la comunidad reúne a 18 312 suscriptores, ocupando la posición 7 332 en la categoría Tecnologías y Aplicaciones y el puesto 36 891 en la región Rusia.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 18 312 suscriptores.
Según los últimos datos del 11 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -82, y en las últimas 24 horas de 0, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 5.51%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 2.69% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 1 009 visualizaciones. En el primer día suele acumular 492 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 2.
- Intereses temáticos: El contenido se centra en temas clave como numbers, yield, модуль, none, декоратор.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Погружение в CPython и архитектуру. Разбираем неочевидное поведение (GIL, Memory), Best Practices (SOLID, DDD) и тонкости Django/FastAPI. Решаем задачи с подвохом и оптимизируем алгоритмы. 🐍
По всем вопросам @evgenycarter
РКН clck.ru/3Ko7Hq”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 12 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
Все уроки записаны в 2022 году, материал обновлен и дополнен.
Спикеры:
Марсель Ибраев (Southbridge)
Павел Селиванов (Yandex Cloud).
Форматы обучения:
Поток: открываем доступ к двум новым темам каждую неделю, общаемся в чате с куратором и спикерами, два раза в неделю — AMA-сессии по темам курса со спикерами.
Видеокурс: доступны сразу все темы, можно изучать в своём темпе.
Оба формата включают практику на стендах и итоговую сертификацию.
Подробнее про курс: https://slurm.club/3zPAuGrsuper() function allows referring to the base class. This can be extremely helpful in cases when a derived class wants to add something to the method implementation instead of overriding it completely:
class BaseTestCase(TestCase):
def setUp(self):
self._db = create_db()
class UserTestCase(BaseTestCase):
def setUp(self):
super().setUp()
self._user = create_user()
The function's name doesn't mean excellent or very good. The word super implies above in this context (like in superintendant). Despite what I said earlier, super() doesn't always refer to the base class, it can easily return a sibling. The proper name could be next() since the next class according to MRO is returned.
class Top:
def foo(self):
return 'top'
class Left(Top):
def foo(self):
return super().foo()
class Right(Top):
def foo(self):
return 'right'
class Bottom(Left, Right):
pass
# prints 'right'
print(Bottom().foo())
Mind that super() may produce different results since they depend on the MRO of the original call.
>>> Bottom().foo()
'right'
>>> Left().foo()
'top'gen.throw(e) you may raise an exception at the point where the gen generator is paused, i. e. at some yield. If gen catches the exception, get.throw(e) returns the next value yielded (or StopIteration is raised). If gen doesn't catch the exception, it propagates back to you.
In : def gen():
...: try:
...: yield 1
...: except ValueError:
...: yield 2
...:
...: g = gen()
...:
In : next(g)
Out: 1
In : g.throw(ValueError)
Out: 2
In : g.throw(RuntimeError('TEST'))
...
RuntimeError: TEST
You can use it to control generator behavior more precisely, not only by sending data to it but by notifying about some problems with values yielded for example. But this is rarely required, and you have a little chance to encounter g.throw in the wild.
However, the @contextmanager decorator from contextlib does exactly this to let the code inside the context catch exceptions.
In : from contextlib import contextmanager
...:
...: @contextmanager
...: def atomic():
...: print('BEGIN')
...:
...: try:
...: yield
...: except Exception:
...: print('ROLLBACK')
...: else:
...: print('COMMIT')
...:
In : with atomic():
...: print('ERROR')
...: raise RuntimeError()
...:
BEGIN
ERROR
ROLLBACKö can be just LATIN SMALL LETTER O WITH DIAERESIS (U+00F6) or a combination of o and a diaeresis modifier: LATIN SMALL LETTER O (U+006F) + COMBINING DIAERESIS (U+0308).
Compatible sequences look different but may be treated the same semantically, e. g. ff and ff.
For each of these types of equivalence, you can normalize a Unicode string by compressing or decompressing sequences. In Python, you can use unicodedata for this:
modes = [
# Compress canonically equivalent
'NFC',
# Decompress canonically equivalent
'NFD',
# Compress compatible
'NFKC',
# Decompress compatible
'NFKD',
]
s = 'ff + ö'
for mode in modes:
norm = unicodedata.normalize(mode, s)
print('\t'.join([
mode,
norm,
str(len(norm.encode('utf8'))),
]))
NFC ff + ö 8
NFD ff + ö 9
NFKC ff + ö 7
NFKD ff + ö 8__init__ it may be better to pass them as arguments and have a factory method instead. It separates business logic from technical details on how objects are created.
In this example __init__ accepts host and port to construct a database connection:
class Query:
def __init__(self, host, port):
self._connection = Connection(host, port)
The possible refactoring is:
class Query:
def __init__(self, connection):
self._connection = connection
@classmethod
def create(cls, host, port):
return cls(Connection(host, port))
This approach has at least these advantages:
• It makes dependency injection easy. You can do Query(FakeConnection()) in your tests.
• The class can have as many factory methods as needed; the connection may be constructed not only by host and port but also by cloning another connection, reading a config file or object, using the default, etc.
• Such factory methods can be turned into asynchronous functions; this is completely impossible for __init__.utf-8, which is (usually) a default in Python. When you read from a file, Python automatically decodes utf-8. You can choose any other encoding with encoding= parameter of the open function, or you can read plane bytes by appending b to its mode.
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