Python/ django
по всем вопросам @workakkk @itchannels_telegram - 🔥 все ит каналы @ai_machinelearning_big_data -ML @ArtificialIntelligencedl -AI @datascienceiot - 📚 @pythonlbooks РКН: clck.ru/3FmxmM
Show more📈 Analytical overview of Telegram channel Python/ django
Channel Python/ django (@pythonl) in the Russian language segment is an active participant. Currently, the community unites 58 537 subscribers, ranking 2 245 in the Technologies & Applications category and 10 310 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 58 537 subscribers.
According to the latest data from 28 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -164 over the last 30 days and by -36 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 6.11%. Within the first 24 hours after publication, content typically collects 3.03% reactions from the total number of subscribers.
- Post reach: On average, each post receives 3 575 views. Within the first day, a publication typically gains 1 773 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 21.
- Thematic interests: Content is focused on key topics such as github, claude, контекст, архитектура, api.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“по всем вопросам @workakkk
@itchannels_telegram - 🔥 все ит каналы
@ai_machinelearning_big_data -ML
@ArtificialIntelligencedl -AI
@datascienceiot - 📚
@pythonlbooks
РКН: clck.ru/3Fm...”
Thanks to the high frequency of updates (latest data received on 29 October, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
subprocess с принудительным сбросом привилегий. Такой приём позволяет запускать команды даже в окружениях с потенциально небезопасным вводом, блокируя доступ к опасным системным вызовам и снижая риск эксплуатации.
import subprocess
import os
def safe_run(cmd):
# Запускаем процесс без наследования переменных окружения
env = {"PATH": "/usr/bin:/bin"}
# Сбрасываем привилегии, если процесс запущен от root
def drop_priv():
os.setgid(65534)
os.setuid(65534)
result = subprocess.run(
cmd,
env=env,
preexec_fn=drop_priv,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
text=True,
timeout=3,
)
return result.stdout
print(safe_run(["ls", "/"]))
@pythonlreversed(), но работает она не со всеми структурами данных. Быстрый разбор:
✓ Список можно развернуть
reversed([1, 2, 3]) возвращает итератор.
list(reversed([1, 2, 3])) → [3, 2, 1]
✓ Кортежи тоже разворачиваются
Можно итерироваться по reversed((1, 2, 3))
✓ Множества не разворачиваются
reversed({1, 2, 3}) → TypeError: 'set' object is not reversible
Причина: множества *не имеют порядка*, а значит разворачивать нечего.
Если нужно развернуть множество — сначала сделай его списком:
list(reversed(list({1, 2, 3})))
@pythonl
funcs = []
for i in range(5):
funcs.append(lambda x=i: x) # фиксируем i как значение по умолчанию
print([f() for f in funcs]) # [0, 1, 2, 3, 4]
from pathlib import Path
from collections import Counter
import json, statistics as stats
chunks = lambda it, n: [it[i:i + n] for i in range(0, len(it), n)]
flatten = lambda lst: [x for sub in lst for x in sub]
unique = lambda seq: list(dict.fromkeys(seq))
sliding = lambda it, n: [it[i:i + n] for i in range(len(it) - n + 1)]
freqs = lambda seq: Counter(seq)
read_text = lambda p: Path(p).read_text(encoding="utf-8")
write_text = lambda p, text: Path(p).write_text(text, encoding="utf-8")
read_json = lambda p: json.loads(Path(p).read_text(encoding="utf-8"))
write_json = lambda p, obj: Path(p).write_text(json.dumps(obj, ensure_ascii=False, indent=2), encoding="utf-8")
mean_std = lambda xs: (stats.mean(xs), stats.pstdev(xs))
@pythonl
pip install myfy
myfy init
myfy frontend init
myfy run
https://github.com/psincraian/myfy
@pythonl