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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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Сеть:Machine Learning with Python Индия9 164 Технологии и приложения3 287...

📈 Аналитический обзор Telegram-канала Learn Python Coding

Канал Learn Python Coding (@pythonre) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 40 875 подписчиков, занимая 3 287 место в категории Технологии и приложения и 9 164 место в регионе Индия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 40 875 подписчиков.

Согласно последним данным от 29 октября, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 336, а за последние 24 часа — 1, при этом общий охват остаётся высоким.

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Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 5.33%. В первые 24 часа после публикации контент обычно набирает 1.52% реакций от общего числа подписчиков.
Охват публикаций: В среднем каждый пост получает 2 179 просмотров. В течение первых суток публикация набирает 622 просмотров.
Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 3.
Тематические интересы: Контент сосредоточен на ключевых темах, таких как math, harvard, oxford, supervision, waybienad.

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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”

Благодаря высокой частоте обновлений (последние данные получены 30 октября, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Технологии и приложения.

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40 875

Подписчики

+124 часа

-497 дней

+33630 дней

2 179

Просмотры поста

~ 62224 часа

~ 96248 часов

5.33%

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🚀 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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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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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

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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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