### 📱 Mobile & Embedded
21. PyQt for Android (Kivy + PyQt)
- Experimental but working solutions
- *Best for:* Targeting mobile platforms

22. Raspberry Pi PyQt5 Guides
- Optimizing PyQt5 for low-power devices

---

### Key Tips for Effective Learning:
1. Start with Qt Designer – Visual prototyping accelerates learning
2. Convert Qt C++ examples – 90% of Qt's official examples translate directly to PyQt5
3. Master signals/slots early – Core to Qt's event-driven architecture
4. Use `QThread` properly – Critical for responsive UIs
5. Explore QSS styling – Makes your apps look professional with CSS-like syntax

# Example QSS Styling
app.setStyleSheet("""
    QPushButton {
        background-color: #4CAF50;
        border-radius: 4px;
        padding: 8px;
    }
    QLineEdit:focus {
        border: 2px solid #2196F3;
    }
""")

Which resource to choose?
- Beginners: Start with ZetCode or Real Python tutorials
- Intermediate: Build projects using PyQt5 Boilerplate
- Advanced: Study the Qt source code and contribute to PyQtGraph

Happy coding! 🚀

🚀 Comprehensive Tutorial: Build a Folder Monitoring & Intruder Detection System in Python

In this comprehensive, step-by-step tutorial, you will learn how to build a real-time folder monitoring and intruder detection system using Python.

🔐 Your Goal:
- Create a background program that:
- Monitors a specific folder on your computer.
- Instantly captures a photo using the webcam whenever someone opens that folder.
- Saves the photo with a timestamp in a secure folder.
- Runs automatically when Windows starts.
- Keeps running until you manually stop it (e.g., via Task Manager or a hotkey).

Read and get code: https://hackmd.io/@husseinsheikho/Build-a-Folder-Monitoring

#Python #Security #FolderMonitoring #IntruderDetection #OpenCV #FaceCapture #Automation #Windows #TaskScheduler #ComputerVision

✉️ Our Telegram channels: https://news.1rj.ru/str/addlist/0f6vfFbEMdAwODBk

📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

Python tip:

Using built-in functions makes your code shorter and makes you look like a genius.

Traditional way 👇

def find_max(numbers):
    max_num = numbers[0]
    for num in numbers:
        if num > max_num:
            max_num = num
    return max_num

numbers = [4, 2, 9, 7, 5, 6]
print(find_max(numbers))

# Output: 9

Genius way 👇

def find_max(numbers):
    return max(numbers)

numbers = [4, 2, 9, 7, 5, 6]
print(find_max(numbers))

# Output: 9

👉 @DataScience4

👉 @DataScience4

Python Cheat sheet

👉 @DataScience4

Another powerful open-source text-to-speech tool for Python has been found on GitHub — Abogen

🌟 link: https://github.com/denizsafak/abogen

It allows you to quickly convert ePub, PDF, or plain text files into high-quality audio with auto-generated synchronized subnoscripts.

Main features:

🔸Support for input files in ePub, PDF, and TXT formats
🔸Generation of natural, smooth speech based on the Kokoro-82M model
🔸Automatic creation of subnoscripts with time stamps
🔸Built-in voice mixer for customizing sound
🔸Support for multiple languages, including Chinese, English, Japanese, and more
🔸Processing multiple files through batch queue

👉 @DataScience4

📘 Ultimate Guide to Web Scraping with Python: Part 1 — Foundations, Tools, and Basic Techniques

Duration: ~60 minutes reading time | Comprehensive introduction to web scraping with Python

Start learn: https://hackmd.io/@husseinsheikho/WS1

https://hackmd.io/@husseinsheikho/WS1#WebScraping #Python #DataScience #WebCrawling #DataExtraction #WebMining #PythonProgramming #DataEngineering #60MinuteRead

✉️ Our Telegram channels: https://news.1rj.ru/str/addlist/0f6vfFbEMdAwODBk

📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

Part 2: Advanced Web Scraping Techniques – Mastering Dynamic Content, Authentication, and Large-Scale Data Extraction

Duration: ~60 minutes 😮

✅ Link: https://hackmd.io/@husseinsheikho/WS-2

#WebScraping #AdvancedScraping #Selenium #Scrapy #DataEngineering #Python #APIs #WebAutomation #DataCleaning #AntiScraping

✉️ Our Telegram channels: https://news.1rj.ru/str/addlist/0f6vfFbEMdAwODBk

📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

Part 3: Enterprise Web Scraping – Building Scalable, Compliant, and Future-Proof Data Extraction Systems

Duration: ~60 minutes

Link A: https://hackmd.io/@husseinsheikho/WS-3A

Link B (Rest): https://hackmd.io/@husseinsheikho/WS-3B

#EnterpriseScraping #DataEngineering #ScrapyCluster #MachineLearning #RealTimeData #Compliance #WebScraping #BigData #CloudScraping #DataMonetization

✉️ Our Telegram channels: https://news.1rj.ru/str/addlist/0f6vfFbEMdAwODBk

📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

Want to learn Python quickly and from scratch? Then here’s what you need — CodeEasy: Python Essentials

🔹Explains complex things in simple words
🔹Based on a real story with tasks throughout the plot
🔹Free start

Ready to begin? Click https://codeeasy.io/course/python-essentials 🌟

👉 @DataScience4

Transcribe Youtube Videos using Python

https://news.1rj.ru/str/DataScience4 🔰

Slugify module

A slug is a simplified version of a noscript or name where special characters are replaced with hyphens (-), and all letters are converted to lowercase. For example, the noscript "How to create a slug in Python!" becomes "how-to-create-a-slug-in-python"

A slug is a friendly and readable string format commonly used in URLs to identify a resource.
 

from slugify import slugify

noscript = "Example post about creating slugs"
slug = slugify(noscript)
print(slug)  # output: example-post-about-creating-slugs

🔸The string is converted to lowercase.
🔸Special characters and spaces are removed and replaced with hyphens.
🔸The result is short and easy to read.

Library installation:

pip install python-slugify

👉 @DataScience4

🐍 Python GUI Programming 📈

Does your Python program need a Graphical User Interface (GUI)? With this learning path you'll develop your Python GUI programming skills from scratch
#python #learnpython

Link: https://realpython.com/learning-paths/python-gui-programming/

https://news.1rj.ru/str/DataScience4 🏐

html-to-markdown

A modern, fully typed Python library for converting HTML to Markdown. This library is a completely rewritten fork of markdownify with a modernized codebase, strict type safety and support for Python 3.9+.

Features:
⭐️ Full HTML5 Support: Comprehensive support for all modern HTML5 elements including semantic, form, table, ruby, interactive, structural, SVG, and math elements
⭐️ Enhanced Table Support: Advanced handling of merged cells with rowspan/colspan support for better table representation
⭐️ Type Safety: Strict MyPy adherence with comprehensive type hints
Metadata Extraction: Automatic extraction of document metadata (noscript, meta tags) as comment headers
⭐️ Streaming Support: Memory-efficient processing for large documents with progress callbacks
⭐️ Highlight Support: Multiple styles for highlighted text (<mark> elements)
⭐️ Task List Support: Converts HTML checkboxes to GitHub-compatible task list syntax

nstallation

pip install html-to-markdown

Optional lxml Parser
For improved performance, you can install with the optional lxml parser:

pip install html-to-markdown[lxml]

The lxml parser offers:

🆘 ~30% faster HTML parsing compared to the default html.parser
🆘 Better handling of malformed HTML
🆘 More robust parsing for complex documents

Quick Start
Convert HTML to Markdown with a single function call:

from html_to_markdown import convert_to_markdown

html = """
<!DOCTYPE html>
<html>
<head>
    <noscript>Sample Document</noscript>
    <meta name="denoscription" content="A sample HTML document">
</head>
<body>
    <article>
        <h1>Welcome</h1>
        <p>This is a <strong>sample</strong> with a <a href="https://example.com">link</a>.</p>
        <p>Here's some <mark>highlighted text</mark> and a task list:</p>
        <ul>
            <li><input type="checkbox" checked> Completed task</li>
            <li><input type="checkbox"> Pending task</li>
        </ul>
    </article>
</body>
</html>
"""

markdown = convert_to_markdown(html)
print(markdown)

Working with BeautifulSoup:
If you need more control over HTML parsing, you can pass a pre-configured BeautifulSoup instance:

from bs4 import BeautifulSoup
from html_to_markdown import convert_to_markdown

# Configure BeautifulSoup with your preferred parser
soup = BeautifulSoup(html, "lxml")  # Note: lxml requires additional installation
markdown = convert_to_markdown(soup)

Github: https://github.com/Goldziher/html-to-markdown

https://news.1rj.ru/str/DataScience4 ⭐️