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Learn Python Coding

Learn Python Coding

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Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills. Admin: @HusseinSheikho || @Hussein_Sheikho

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📈 Analytical overview of Telegram channel Learn Python Coding

Channel Learn Python Coding (@pythonre) in the English language segment is an active participant. Currently, the community unites 40 881 subscribers, ranking 3 287 in the Technologies & Applications category and 9 164 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 40 881 subscribers.

According to the latest data from 29 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 336 over the last 30 days and by 1 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 5.33%. Within the first 24 hours after publication, content typically collects 1.52% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 2 179 views. Within the first day, a publication typically gains 622 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
  • Thematic interests: Content is focused on key topics such as math, harvard, oxford, supervision, waybienad.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills. Admin: @HusseinSheikho || @Hussein_Sheikho”

Thanks to the high frequency of updates (latest data received on 30 October, 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.

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40 881
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🚀 Master Data Science & Programming! Unlock your potential with this curated list of Telegram channels. Whether you need boo
🚀 Master Data Science & Programming! Unlock your potential with this curated list of Telegram channels. Whether you need books, datasets, interview prep, or project ideas, we have the perfect resource for you. Join the community today! 🔰 Machine Learning with Python Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. https://t.me/CodeProgrammer 🔖 Machine Learning Machine learning insights, practical tutorials, and clear explanations for beginners and aspiring data scientists. Follow the channel for models, algorithms, coding guides, and real-world ML applications. https://t.me/DataScienceM 🧠 Code With Python This channel delivers clear, practical content for developers, covering Python, Django, Data Structures, Algorithms, and DSA – perfect for learning, coding, and mastering key programming skills. https://t.me/DataScience4 🎯 PyData Careers | Quiz Python Data Science jobs, interview tips, and career insights for aspiring professionals. https://t.me/DataScienceQ 💾 Kaggle Data Hub Your go-to hub for Kaggle datasets – explore, analyze, and leverage data for Machine Learning and Data Science projects. https://t.me/datasets1 🧑‍🎓 Udemy Coupons | Courses The first channel in Telegram that offers free Udemy coupons https://t.me/DataScienceC 😀 ML Research Hub Advancing research in Machine Learning – practical insights, tools, and techniques for researchers. https://t.me/DataScienceT 💬 Data Science Chat An active community group for discussing data challenges and networking with peers. https://t.me/DataScience9 🐍 Python Arab| بايثون عربي The largest Arabic-speaking group for Python developers to share knowledge and help. https://t.me/PythonArab 🖊 Data Science Jupyter Notebooks Explore the world of Data Science through Jupyter Notebooks—insights, tutorials, and tools to boost your data journey. Code, analyze, and visualize smarter with every post. https://t.me/DataScienceN 📺 Free Online Courses | Videos Free online courses covering data science, machine learning, analytics, programming, and essential skills for learners. https://t.me/DataScienceV 📈 Data Analytics Dive into the world of Data Analytics – uncover insights, explore trends, and master data-driven decision making. https://t.me/DataAnalyticsX 🎧 Learn Python Hub Master Python with step-by-step courses – from basics to advanced projects and practical applications. https://t.me/Python53 ⭐️ Research Papers Professional Academic Writing & Simulation Services https://t.me/DataScienceY ━━━━━━━━━━━━━━━━━━ Admin: @HusseinSheikho

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✨ wheel | Python Tools ✨ 📖 Reference implementation and CLI for the Python wheel format. 🏷️ #Python

✨ build | Python Tools ✨ 📖 A Python packaging frontend that uses project settings from pyproject.toml. 🏷️ #Python

Checking the reliability of a password with Python! Sometimes you need to quickly check how secure a password is. Let's look at a simple example using regular expressions - a good opportunity to practice with re and conditional logic. Import the module:
import re
Create a password check function:
def check_password_strength(password):
    length = len(password) >= 8
    upper = re.search(r"[A-Z]", password)
    lower = re.search(r"[a-z]", password)
    digit = re.search(r"\d", password)
    special = re.search(r"[@$!%*?&]", password)

    if all([length, upper, lower, digit, special]):
        return "✅ Reliable password"
    else:
        return "⚠️ Weak password"
Check a few examples:
print(check_password_strength("Qwerty123"))
print(check_password_strength("Qw!8zYt@1"))
Output example:
⚠️ Weak password  
✅ Reliable password
🔥 Example of how to check a string for compliance with several conditions using code - and practice with regular expressions. 🚪 @DataScience4

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✨ Invoke | Python Tools ✨ 📖 A Python library and command-line tool that lets you define reusable tasks. 🏷️ #Python

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✨ Positron | Code Editors & IDEs ✨ 📖 A free, modern integrated development environment (IDE) for data science. 🏷️ #Python

✨ Nox | Python Tools ✨ 📖 A command-line tool that automates running tasks like testing and linting. 🏷️ #Python

✨ Wing IDE | Code Editors & IDEs ✨ 📖 An integrated development environment (IDE) for Python. 🏷️ #Python

✨ absolute import | Python Glossary ✨ 📖 Uses a module’s full path from your project’s top-level package. 🏷️ #Python

✨ doit | Python Tools ✨ 📖 A Python task runner and build tool. 🏷️ #Python

A cheat sheet about functions and techniques in Python: shows useful built-in functions, working with iterators, strings, and
A cheat sheet about functions and techniques in Python: shows useful built-in functions, working with iterators, strings, and collections, as well as popular tricks with unpacking, zip, enumerate, map, filter, and dictionaries @DataScience4

This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visualization 4️⃣ Artificial Intelligence 5️⃣ Data Analysis 6️⃣ Statistics 7️⃣ Deep Learning 8️⃣ programming Languages ✅ https://t.me/addlist/8_rRW2scgfRhOTc0 ✅ https://t.me/Codeprogrammer

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