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 7 334,并在 俄罗斯 地区排名第 36 889 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 12 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 -83,过去 24 小时变化为 -1,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 5.49%。内容发布后 24 小时内通常能获得 2.76% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 1 006 次浏览,首日通常累积 505 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 13 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。
list allows you to store an array of any objects. This is quite helpful but may be inefficient. The array module can be used to represent arrays of base values compactly. The supported values include various C types including char, int, long, double and so on. The actual representation is determined by the C implementation.
In : a = array.array('B')
In : a.append(240)
In : a.append(159)
In : a.append(144)
In : a.append(180)
In : a.tobytes().decode('utf8')
Out: '🐴'.request, можно просмотреть PreparedRequest.
Проверка PreparedRequest открывает доступ ко всей информации о выполняемом запросе. Это может быть пейлоад, URL, заголовки, аутентификация и многое другое.
Подписывайтесь на канал 👉@pythonofffx = 1
def scope():
x = 2
def inner_scope():
print(x) # prints 2
inner_scope()
scope()
However, the variable assignment doesn't work the same way. The new variable is always created in the current scope unless global or nonlocal is specified:
x = 1
def scope():
x = 2
def inner_scope():
x = 3
print(x) # prints 3
inner_scope()
print(x) # prints 2
scope()
print(x) # prints 1
global allows using variables of global namespaces while nonlocal searches for the variable in the nearest enclosing scope. Compare:
x = 1
def scope():
x = 2
def inner_scope():
global x
x = 3
print(x) # prints 3
inner_scope()
print(x) # prints 2
scope()
print(x) # prints 3
x = 1
def scope():
x = 2
def inner_scope():
nonlocal x
x = 3
print(x) # prints 3
inner_scope()
print(x) # prints 3
scope()
print(x) # prints 1sorted:
In : sorted([1, -1, 2, -3, 3])
Out: [-3, -1, 1, 2, 3]
With the key argument you can provide a function that will be used to get a comparison key of each value. Let's sort the same sequence by absolute values:
In : sorted([1, -1, 2, -3, 3], key=abs)
Out: [1, -1, 2, -3, 3]
Let's suppose we also want to put the numbers with the same absolute value in ascending order. In that case, we can provide a tuple as a comparison key:
In : sorted([1, -1, 2, -3, 3], key=lambda x: (abs(x), x))
Out: [-1, 1, 2, -3, 3]
This is not some sorted magic, this is how tuples are sorted in general:
In : (1, 2) == (1, 2)
Out: True
In : (1, 2) > (1, 1)
Out: True
In : (1, 2) < (2, 1)
Out: True-O and -OO flags.
-O sets __debug__ to False and removes all assert statements from the program. -OO do the same and also discards docstrings.
A regular version of a script is cached to .pyc file while an optimized one is cached to .pyo. However, since Python 3.5 .pyo is no more a thing, .opt-1.pyc and .opt-2.pyc are introduced by PEP 488 instead.float.
Float также можно использовать для преобразования целых чисел в числа с плавающей запятой.
В Python 2 такое преобразование необходимо, но в Python 3 целочисленное деление больше не является чем-то особенным (если вы специально не используете оператор «//»). Поэтому больше не нужно использовать float для этой цели, теперь float(x)/y можно легко заменить на x/y.
Подписывайтесь на канал 👉@pythonofffpython -m module.py, that prevents the traditional if __name__ == '__main__' block from running. Still, all imports will be executed, and this may fail if you want to check syntax in the environment where the module can't be and shouldn't be run.
However, the python standard library contains the py_compile module that generates byte-code from Python source file without running it. That's exactly what we need:
$ python -m py_compile test.c
File "test.c", line 1
int main() {
^
SyntaxError: invalid syntax.d = {} (for dictionaries) but it's not exactly clearing, it's creating a new collection and throwing the old one away. It may work for you, but other owners of the same object will still have a reference to the original one.
The proper way to clear dictionary, set, deque and other collections is to call x.clear().
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