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 18 312 名订阅者,在 技术与应用 类别中位列第 7 332,并在 俄罗斯 地区排名第 36 891 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 18 312 名订阅者。
根据 11 六月, 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 -82,过去 24 小时变化为 0,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 5.51%。内容发布后 24 小时内通常能获得 2.69% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 1 009 次浏览,首日通常累积 492 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 2。
- 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 12 六月, 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。
__del__, который вызовется автоматически при удалении объекта.
Вообще деструкторы крайне редко переопределяется в Python, но полезно знать, что именно эти методы отвечают за очистку при удалении объекта.sorted with the custom key function:
>>> d = dict(a=1, c=3, b=2)
>>> sorted(d.items(), key=lambda item: item[1])
[('a', 1), ('b', 2), ('c', 3)]
However, such function already exists in the operator module:
>>> sorted(d.items(), key=itemgetter(1))
[('a', 1), ('b', 2), ('c', 3)]
You can also sort keys instead of items:
>>> sorted(d, key=lambda k: d[k])
['a', 'b', 'c']
Again, this lambda can be replaced with the already existing method:
>>> sorted(d, key=d.get)
['a', 'b', 'c']__new__ method. Even if you provide custom __new__ for your class, you have to call super().__new__(...).
You might think that object.__new__ is a root implementation that is responsible for the creation of all objects. That is not entirely true. There are several such implementations, and they are incompatible. For example, dict has its own low-level __new__ and objects of types derived from dict can't be created with object.__new__:
In : class D(dict):
...: pass
...:
In : class A:
...: pass
...:
In : object.__new__(A)
Out: <__main__.A at 0x7f200c8902e8>
In : object.__new__(D)
...
TypeError: object.__new__(D) is not safe,
use D.__new__()itertools.islice. It lets you iterate over the part of the list, but doesn't support indexing or modification.
To achieve more than this, we have to write a custom class. Luckily Python provides the suitable abstract base class: collections.abc.MutableSequence. You only need to override __getitem__, __setitem__, __delitem__, __len__ and insert.
This is the example of how you do it. It doesn't support deletion and inserting, but supports slicing slices and modifications.next(x) returns the new value from the x iterator unless an exception is raised. If this is StopIteration, it means the iterator is exhausted and can supply no more values. If a generator is iterated, it automatically raises StopIteration upon the end of the body:
>>> def one_two():
... yield 1
... yield 2
...
>>> i = one_two()
>>> next(i)
1
>>> next(i)
2
>>> next(i)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
StopIteration
StopIteration is automatically handled by tools that calls next for you:
>>> list(one_two())
[1, 2]
The problem is, any unexpected StopIteration that is raised within a generator causes it to stop silently instead of actually raising an exception:
def one_two():
yield 1
yield 2
def one_two_repeat(n):
for _ in range(n):
i = one_two()
yield next(i)
yield next(i)
yield next(i)
print(list(one_two_repeat(3)))
The last yield here is a mistake: StopIteration is raised and makes list(...) to stop the iteration. The result is [1, 2], surprisingly.
However, that was changed in Python 3.7. Such foreign StopIteration is now replaced with RuntimeError:
Traceback (most recent call last):
File "test.py", line 10, in one_two_repeat
yield next(i)
StopIteration
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "test.py", line 12, in <module>
print(list(one_two_repeat(3)))
RuntimeError: generator raised StopIteration
You can enable the same behavior since python3.5 by from __future__ import generator_stop.stdout instead of providing some API that is usable within a program (returning a string, for example).
Instead of refactoring such code you may use the contextlib.redirect_stdout context manager that allows temporary redirecting stdout to any custom file-like object. In conjuncture with io.StringIO, it allows capturing output to a variable.
from contextlib import redirect_stdout
from io import StringIO
s = StringIO()
with redirect_stdout(s):
print(42)
print(s.getvalue())
There is also contextlib.redirect_stderr available for redirecting sys.stderr.
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