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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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📈 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 39 140 suscriptores, ocupando la posición 3 511 en la categoría Tecnologías y Aplicaciones y el puesto 10 551 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 39 140 suscriptores.

Según los últimos datos del 07 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 433, y en las últimas 24 horas de 10, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.62%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.01% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 1 026 visualizaciones. En el primer día suele acumular 395 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 4.
  • 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 08 junio, 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.

39 140
Suscriptores
+1024 horas
+887 días
+43330 días
Archivo de publicaciones
Neovim | Code Editors & IDEs ✨ 📖 A free, open-source, Vim-based text editor that focuses on extensibility. 🏷️ #Python

Anaconda | Python Tools ✨ 📖 A curated distribution of Python and R for data science. 🏷️ #Python

abc | Python Standard Library ✨ 📖 Provides infrastructure for defining Abstract Base Classes (ABCs). 🏷️ #Python

🚀 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

✨ Quiz: Recursion in Python: An Introduction ✨ 📖 Test your understanding of recursion in Python, including base cases, recur
Quiz: Recursion in Python: An Introduction ✨ 📖 Test your understanding of recursion in Python, including base cases, recursive structure, performance considerations, and common use cases. 🏷️ #intermediate #algorithms #python

flit | Python Tools ✨ 📖 A build and publish tool that packages pure Python. 🏷️ #Python

Vim | Code Editors & IDEs ✨ 📖 A free, open-source, highly configurable text editor. 🏷️ #Python

ipaddress | Python Standard Library ✨ 📖 Provides the capabilities to create, manipulate, and operate on IPv4 and IPv6 addresses. 🏷️ #Python

⚠ Message was hidden by channel owner
⚠ Message was hidden by channel owner

⚠ Message was hidden by channel owner
⚠ Message was hidden by channel owner

Advice on clean code in Python Don't use "naive" datetime without time zones. Store and process time in UTC, and display it t
Advice on clean code in Python Don't use "naive" datetime without time zones. Store and process time in UTC, and display it to the user in his local time zone
import datetime
from zoneinfo import ZoneInfo

# BAD
now = datetime.datetime.now()

print(now.isoformat())
# 2025-10-21T15:03:07.332217

# GOOD
now = datetime.datetime.now(tz=ZoneInfo("UTC"))
print(now.isoformat())
# 2025-10-21T12:04:22.573590+00:00

print(now.astimezone().isoformat())
# 2025-10-21T15:04:22.573590+03:00

Create a simple weather parser that displays the current temperature and weather conditions from a free API We will write a script that retrieves weather data for your city and displays it in a convenient format. First, we need the requests library for network operations. If it's not installed, install it via the terminal with the command:
pip install requests
Import the module and define a function that retrieves data from the Open-Meteo API (no key required) for specific coordinates:
import requests

def get_weather(lat, lon):
    url = f"https://api.open-meteo.com/v1/forecast?latitude={lat}&longitude={lon}&current_weather=true"
    return requests.get(url).json()['current_weather']
Specify the coordinates of your city (for example, Moscow): moscow_coords = (55.75, 37.62) Display the temperature and wind speed:
weather = get_weather(*moscow_coords)
print(f"Temperature: {weather['temperature']}°C, Wind speed: {weather['windspeed']} km/h")
🔥 Get fresh weather data without registration or passwords — useful for your own projects or bots! 🚪 @DataScience4

✨ Topic: Python Machine Learning ✨ 📖 Learn how to implement machine learning (ML) algorithms in Python. With these skills, y
Topic: Python Machine Learning ✨ 📖 Learn how to implement machine learning (ML) algorithms in Python. With these skills, you can create intelligent systems capable of learning and making decisions. 🏷️ #35_resources

✨ Quiz: SOLID Design Principles: Improve Object-Oriented Code in Python ✨ 📖 Learn Liskov substitution in Python. Spot Square
Quiz: SOLID Design Principles: Improve Object-Oriented Code in Python ✨ 📖 Learn Liskov substitution in Python. Spot Square and Rectangle pitfalls and design safer APIs with polymorphism. Test your understanding now. 🏷️ #intermediate #best-practices #python

Spyder | Code Editors & IDEs ✨ 📖 A free, open source integrated development environment (IDE) for Python that is tailored to scientific computing and data analysis. 🏷️ #Python

Emacs | Code Editors & IDEs ✨ 📖 A free, open-source, highly extensible text editor and computing environment. 🏷️ #Python

Coverage.py | Python Tools ✨ 📖 A tool that measures test coverage for Python. 🏷️ #Python

Jupyter Notebook | Code Editors & IDEs ✨ 📖 A web-based interactive computing environment that lets you combine executable code and narrative text. 🏷️ #Python

Cookiecutter | Python Tools ✨ 📖 A project templating and scaffolding tool. 🏷️ #Python

JupyterLab | Code Editors & IDEs ✨ 📖 A web-based interactive development environment (IDE) for Jupyter notebooks. 🏷️ #Python