Бэкап
Исходные коды проектов, инструменты OSINT и готовые алгоритмы с GitHub. Сотрудничество: @workhouse_price #1CWQG Купить рекламу: https://telega.in/c/becaps РКН: https://clck.ru/3FtTHF
Show more📈 Analytical overview of Telegram channel Бэкап
Channel Бэкап (@becaps) in the Russian language segment is an active participant. Currently, the community unites 10 307 subscribers, ranking 11 815 in the Technologies & Applications category and 62 975 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 10 307 subscribers.
According to the latest data from 03 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -140 over the last 30 days and by -4 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 13.01%. Within the first 24 hours after publication, content typically collects 5.94% reactions from the total number of subscribers.
- Post reach: On average, each post receives 1 341 views. Within the first day, a publication typically gains 612 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 6.
- Thematic interests: Content is focused on key topics such as max.ru/becaps, c++, linux, html, javascript.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Исходные коды проектов, инструменты OSINT и готовые алгоритмы с GitHub.
Сотрудничество: @workhouse_price
#1CWQG
Купить рекламу: https://telega.in/c/becaps
РКН: https://clck.ru/3FtTHF”
Thanks to the high frequency of updates (latest data received on 04 July, 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.
import time
# начальное время
start_time = time.time()
# код, время выполнения которого нужно измерить
for i in range(0, 1000000):
pass
# конечное время
end_time = time.time()
# разница между конечным и начальным временем
elapsed_time = end_time - start_time
print(elapsed_time)pip install pytesseract3. Запускаем наш код:
import pytesseract
from PIL import Image
# указываем путь к изображению
image = Image.open("img.jpg")
# устанавливаем Tesseract-OCR и указываем путь к tesseract.exe
pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'
# получаем из изображения текст
# в lang можно указать значение rus для распознавания кириллицы
string = pytesseract.image_to_string(image, lang='eng')
print(string)
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