Python tip:
Using built-in functions makes your code shorter and makes you look like a genius.
Traditional way👇
Genius way👇
👉 @DataScience4
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
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Join our WhatsApp channel
There are dedicated resources only for WhatsApp users
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Python | Machine Learning | Data Science | WhatsApp Channel
Python | Machine Learning | Data Science WhatsApp Channel. Welcome to our official WhatsApp Channel – your daily dose of AI, Python, and cutting-edge technology!
Here, we share:
Python tutorials and ready-to-use code snippets
AI & machine learning tips…
Here, we share:
Python tutorials and ready-to-use code snippets
AI & machine learning tips…
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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 subtitles.
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 subtitles 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
It allows you to quickly convert ePub, PDF, or plain text files into high-quality audio with auto-generated synchronized subtitles.
Main features:
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📘 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
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
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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
Duration: ~60 minutes
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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
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
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Part 4: Cutting-Edge Web Scraping – AI, Blockchain, Quantum Resistance, and the Future of Data Extraction
Duration: ~60 minutes
Link A: https://hackmd.io/@husseinsheikho/WS-4A
Link B: https://hackmd.io/@husseinsheikho/WS-4B
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Duration: ~60 minutes
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Link B: https://hackmd.io/@husseinsheikho/WS-4B
#AIWebScraping #BlockchainData #QuantumScraping #EthicalAI #FutureProof #SelfHealingScrapers #DataSovereignty #LLM #Web3 #Innovation
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Part 5: Specialized Web Scraping – Social Media, Mobile Apps, Dark Web, and Advanced Data Extraction
Duration: ~60 minutes
Link A: https://hackmd.io/@husseinsheikho/WS-5A
Link B: https://hackmd.io/@husseinsheikho/WS-5B
Duration: ~60 minutes
Link A: https://hackmd.io/@husseinsheikho/WS-5A
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#SocialMediaScraping #MobileScraping #DarkWeb #FinancialData #MediaExtraction #AuthScraping #ScrapingSaaS #APIReverseEngineering #EthicalScraping #DataScience
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Part 6: Advanced Web Scraping Techniques – JavaScript Rendering, Fingerprinting, and Large-Scale Data Processing
Duration: ~60 minutes
Link A: https://hackmd.io/@husseinsheikho/WS-6A
Link B: https://hackmd.io/@husseinsheikho/WS-6B
Duration: ~60 minutes
Link A: https://hackmd.io/@husseinsheikho/WS-6A
Link B: https://hackmd.io/@husseinsheikho/WS-6B
#AdvancedScraping #JavaScriptRendering #BrowserFingerprinting #DataPipelines #LegalCompliance #ScrapingOptimization #EnterpriseScraping #WebScraping #DataEngineering #TechInnovation
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Want to learn Python quickly and from scratch? Then here’s what you need — CodeEasy: Python Essentials
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Slugify module
A slug is a simplified version of a title or name where special characters are replaced with hyphens (-), and all letters are converted to lowercase. For example, the title
A slug is a friendly and readable string format commonly used in URLs to identify a resource.
🔸 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:
👉 @DataScience4
A slug is a simplified version of a title or name where special characters are replaced with hyphens (-), and all letters are converted to lowercase. For example, the title
"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
title = "Example post about creating slugs"
slug = slugify(title)
print(slug) # output: example-post-about-creating-slugs
Library installation:
pip install python-slugify
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🐍 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/
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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/
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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 (title, 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
Optional lxml Parser
For improved performance, you can install with the optional lxml parser:
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:
Working with BeautifulSoup:
If you need more control over HTML parsing, you can pass a pre-configured BeautifulSoup instance:
Github: https://github.com/Goldziher/html-to-markdown
https://t.iss.one/DataScience4⭐️
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:
Metadata Extraction: Automatic extraction of document metadata (title, meta tags) as comment headers
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:
Quick Start
Convert HTML to Markdown with a single function call:
from html_to_markdown import convert_to_markdown
html = """
<!DOCTYPE html>
<html>
<head>
<title>Sample Document</title>
<meta name="description" 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://t.iss.one/DataScience4
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🐍📰 Python args and kwargs: Demystified
In this step-by-step tutorial, you'll learn how to use args and kwargs in Python to add more flexibility to your functions
#python
Link: https://realpython.com/python-kwargs-and-args/
https://t.iss.one/DataScience4⭐️
In this step-by-step tutorial, you'll learn how to use args and kwargs in Python to add more flexibility to your functions
#python
Link: https://realpython.com/python-kwargs-and-args/
https://t.iss.one/DataScience4
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🐍📰 Python Mappings: A Comprehensive Guide
https://realpython.com/python-mappings/
#python
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https://realpython.com/python-mappings/
#python
https://t.iss.one/DataScience4
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