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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Red:📈 Análisis del canal de Telegram Learn Python Coding
El canal Learn Python Coding (@pythonre) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 40 058 suscriptores, ocupando la posición 3 241 en la categoría Tecnologías y Aplicaciones y el puesto 9 590 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 058 suscriptores.
Según los últimos datos del 29 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 114, y en las últimas 24 horas de -8, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.75%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.09% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 1 103 visualizaciones. En el primer día suele acumular 438 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 2.
- Intereses temáticos: El contenido se centra en temas clave como math, harvard, oxford, supervision, waybienad.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“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”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 30 agosto, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
40 058
Suscriptores
-824 horas
-517 días
+11430 días
Archivo de publicaciones
40 058
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
40 058
✨ tox | Python Tools ✨
📖 An environment orchestrator and test automation tool for Python.
🏷️ #Python
40 058
✨ Code Testing | Python Best Practices ✨
📖 Guidelines and best practices for putting together a robust and flexible test suite for your Python code.
🏷️ #Python
40 058
✨ Classes | Python Best Practices ✨
📖 Guidelines and best practices for using Python classes as an expert in OOP.
🏷️ #Python
40 058
✨ Hatch | Python Tools ✨
📖 A project manager and builder for Python.
🏷️ #Python
40 058
Repost from Machine Learning with Python
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40 058
🚀 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
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Admin: @HusseinSheikho
40 058
✨ wheel | Python Tools ✨
📖 Reference implementation and CLI for the Python wheel format.
🏷️ #Python
40 058
✨ build | Python Tools ✨
📖 A Python packaging frontend that uses project settings from pyproject.toml.
🏷️ #Python
40 058
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 redef 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"print(check_password_strength("Qwerty123"))
print(check_password_strength("Qw!8zYt@1"))⚠️ Weak password
✅ Reliable password
40 058
✨ Invoke | Python Tools ✨
📖 A Python library and command-line tool that lets you define reusable tasks.
🏷️ #Python
