import requests
from typing import Optional

def get_exchange_rate(base_currency: str, target_currency: str) -> Optional[float]:
    """
    Получает курс обмена из base_currency в target_currency.

    :param base_currency: Базовая валюта (например, 'USD').
    :param target_currency: Целевая валюта (например, 'RUB').
    :return: Курс обмена или None в случае ошибки.
    """
    url = f"https://open.er-api.com/v6/latest/{base_currency}"
    try:
        response = requests.get(url, timeout=10)
        response.raise_for_status()
        data = response.json()
        rate = data["rates"].get(target_currency)
        if rate is None:
            print(f"Курс для {target_currency} не найден.")
            return None
        return rate
    except requests.RequestException as e:
        print(f"Ошибка при запросе к API: {e}")
        return None

if __name__ == "__main__":
    base = "USD"
    target = "RUB"
    rate = get_exchange_rate(base, target)
    if rate:
        print(f"Курс {base} к {target}: {rate}")
    else:
        print("Не удалось получить курс обмена.")


# Курс USD к RUB: 80.926191

from io import StringIO
from pdfminer.pdfinterp import PDFPageInterpreter, PDFResourceManager
from pdfminer.pdfpage import PDFPage
from pdfminer.converter import TextConverter
from pdfminer.layout import LAParams
 
# PDFMiner Analyzers
rsrcmgr = PDFResourceManager()
sio = StringIO()
codec = "utf-8"
laparams = LAParams()
device = TextConverter(rsrcmgr, sio, codec=codec, laparams=laparams)
interpreter = PDFPageInterpreter(rsrcmgr, device)
 
# path to our input file
pdf_file = "sample.pdf"
 
# Extract text
pdfFile = open(pdf_file, "rb")
for page in PDFPage.get_pages(pdfFile):
   interpreter.process_page(page)
pdfFile.close()
 
# Return text from StringIO
text = sio.getvalue()
 
print(text)
 
# Freeing Up
device.close()
sio.close()

import fitz
import io
from PIL import Image
 
# path to our input file
pdf_file = "sample.pdf"
 
# Input PDF file
pdf_file = fitz.open(pdf_file)
 
for page_no in range(len(pdf_file)):
   curr_page = pdf_file[page_no]
   images = curr_page.getImageList()
 
   for image_no, image in enumerate(curr_page.getImageList()):
       # get the XREF of the image
       xref = image[0]
       # extract the image bytes
       curr_image = pdf_file.extractImage(xref)
       img_bytes = curr_image["image"]
       # get the image extension
       img_extension = curr_image["ext"]
       # load it to PIL
       image = Image.open(io.BytesIO(img_bytes))
       # save it to local disk
       image.save(open(f"page{page_no+1}_img{image_no}.{img_extension}", "wb"))

pip install weasyprint

   pip3 install -U TG-AutoPoster

   python3 -m TG_AutoPoster

vk:
  login: "your_vk_login"
  pass: "your_vk_password"
  token: "your_vk_token"  # предпочтительно использовать токен
telegram:
  api_id: 123456
  api_hash: "your_api_hash"
  bot_token: "your_bot_token"
proxy:
  enabled: false
  hostname: ""
  port: 0
  username: ""
  password: ""

git clone https://github.com/NikolaySimakov/Shop-bot.git
cd Shop-bot

python3 -m venv venv
source venv/bin/activate

 
pip install -r requirements.txt

python3 app.py

$ bandit your_script.py

$ git clone https://github.com/NativeSensors/EyeGestures.git
$ cd EyeGestures
$ pip install -r requirements.txt

python3 -m pip install eyeGestures