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
显示更多📈 Telegram 频道 Библиотека Python разработчика | Книги по питону 的分析概览
频道 Библиотека Python разработчика | Книги по питону (@bookpython) 俄语 语言赛道中的 是活跃参与者。目前社区聚集了 17 959 名订阅者,在 技术与应用 类别中位列第 7 250,并在 俄罗斯 地区排名第 36 565 位。
📊 受众指标与增长动态
自 невідомо 创建以来,项目保持高速增长,吸引了 17 959 名订阅者。
根据 04 十一月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 -87,过去 24 小时变化为 -3,整体触达仍然可观。
- 认证状态: 未认证
- 互动率 (ER): 平均受众互动率为 5.31%。内容发布后 24 小时内通常能获得 2.70% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 953 次浏览,首日通常累积 485 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 4。
- 主题关注点: 内容集中在 numbers, yield, модуль, none, декоратор 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台:
“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”
凭借高频更新(最新数据采集于 05 十一月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。
class GrandParent:
pass
class Parent1(GrandParent):
pass
class Parent2(GrandParent):
pass
class Child(Parent1, Parent2):
pass
Which order will be used to look up the Child.x() method? The naive approach is to recursively search through all parent classes which gives us Child, Parent1, GrandParent, Parent2. While many programming languages follow this method indeed, it doesn't quite make sense, because Parent2 is more specific than GrandParent and should be looked up first.
In order to fix that problem, Python uses C3 superclass linearization, the algorithm that always searches for a method in all child classes before looking up the parent one:
In : Child.__mro__
Out:
(__main__.Child,
__main__.Parent1,
__main__.Parent2,
__main__.GrandParent,
object)for and with can be asynchronous. async with uses __aenter__ and __aexit__ magic methods, async for uses __aiter__ and __anext__. All of them are async and you can await within them:
import asyncio
class Sleep:
def __init__(self, t):
self._t = t
async def __aenter__(self):
await asyncio.sleep(self._t / 2)
async def __aexit__(self, *args):
await asyncio.sleep(self._t / 2)
async def main():
async with Sleep(2):
print('*')
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
When you implement __iter__ you often don't write an iterator with __next__ method, you just use yield that makes __iter__ a generator:
class Bracketed:
def __init__(self, data):
self._data = data
def __iter__(self):
for x in self._data:
yield '({})'.format(x)
print(list(Bracketed([1, 2, 3])))
# ['(1)', '(2)', '(3)']
PEP 525 allows you do the same with __aiter__. Both yield and await in the function body make it asynchronous generator. While await is used to communicate with the loop, yield deals with for:
import asyncio
class Slow:
def __init__(self, data, t=1):
self._data = data
self._t = t
async def __aiter__(self):
for x in self._data:
await asyncio.sleep(self._t)
yield x
async def main():
async for x in Slow([1, 2, 3]):
print(x)
loop = asyncio.get_event_loop()
loop.run_until_complete(main())abs() - возвращает модуль переданного параметра.
all() - функция возвращает значение True, если все элементы в итерируемом объекте - истинны. В противном случае, она возвращает значение False.
any() - функция возвращает True, если какой-либо (любой) элемент в итерируемом объекте является истинным True. В противном случае, any() возвращает значение False.
ascii() - возвращает строку, содержащую печатное представление объекта, и экранирует символы, отличные от ASCII, в строке с помощью экранирования \ x, \ u или \ U.
bin() - функция преобразует целое число в двоичную строку с префиксом 0b.
Подписывайтесь на канал 👉@pythonofffthreading module gets you covered, it provides the threading.local() object that is thread-safe. Store there any data by simply accessing attributes: threading.local().symbol = '@'.
Still, both of that approaches are concurrency-unsafe meaning they won't work for coroutine call-chain where functions are not only called but can be awaited too. Once a coroutine does await, an event loop may run a completely different coroutine from a completely different chain. That won't work:
import asyncio
import sys
global_symbol = '.'
async def indication(timeout):
while True:
print(global_symbol, end='')
sys.stdout.flush()
await asyncio.sleep(timeout)
async def sleep(t, indication_t, symbol='.'):
loop = asyncio.get_event_loop()
global global_symbol
global_symbol = symbol
loop.create_task(indication(indication_t))
await asyncio.sleep(t)
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.gather(
sleep(1, 0.1, '0'),
sleep(1, 0.1, 'a'),
sleep(1, 0.1, 'b'),
sleep(1, 0.1, 'c'),
))
You can fix that by having the loop set and restore the context every time it resumes some coroutine. The aiotask_context module does exactly this by changing the way how tasks are created with loop.set_task_factory. This works:
import asyncio
import sys
import aiotask_context as context
async def indication(timeout):
while True:
print(context.get('symbol'), end='')
sys.stdout.flush()
await asyncio.sleep(timeout)
async def sleep(t, indication_t, symbol='.'):
loop = asyncio.get_event_loop()
context.set(key='symbol', value=symbol)
loop.create_task(indication(indication_t))
await asyncio.sleep(t)
loop = asyncio.get_event_loop()
loop.set_task_factory(context.task_factory)
loop.run_until_complete(asyncio.gather(
sleep(1, 0.1, '0'),
sleep(1, 0.1, 'a'),
sleep(1, 0.1, 'b'),
sleep(1, 0.1, 'c'),
))