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 40 875 suscriptores, ocupando la posición 3 287 en la categoría Tecnologías y Aplicaciones y el puesto 9 164 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 875 suscriptores.
Según los últimos datos del 29 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 336, y en las últimas 24 horas de 1, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 5.33%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.52% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 179 visualizaciones. En el primer día suele acumular 622 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 3.
- 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 octubre, 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.
40 875
Suscriptores
+124 horas
-497 días
+33630 días
Archivo de publicaciones
40 875
✨ Sublime Text | Code Editors & IDEs ✨
📖 A commercial, cross-platform text editor for code, markup, and prose.
🏷️ #Python
40 875
✨ pip-tools | Python Tools ✨
📖 A set of CLI tools that generate and apply fully pinned package requirement files for Python.
🏷️ #Python
40 875
✨ Quiz: LlamaIndex in Python: A RAG Guide With Examples ✨
📖 Take this Python LlamaIndex quiz to test your understanding of index persistence, reloading, and performance gains in RAG applications.
🏷️ #intermediate #ai
40 875
✨ pdm | Python Tools ✨
📖 A modern package and project manager for Python.
🏷️ #Python
40 875
✨ Neovim | Code Editors & IDEs ✨
📖 A free, open-source, Vim-based text editor that focuses on extensibility.
🏷️ #Python
40 875
✨ Anaconda | Python Tools ✨
📖 A curated distribution of Python and R for data science.
🏷️ #Python
40 875
✨ abc | Python Standard Library ✨
📖 Provides infrastructure for defining Abstract Base Classes (ABCs).
🏷️ #Python
40 875
🚀 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
40 875
✨ 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
40 875
✨ flit | Python Tools ✨
📖 A build and publish tool that packages pure Python.
🏷️ #Python
40 875
✨ Vim | Code Editors & IDEs ✨
📖 A free, open-source, highly configurable text editor.
🏷️ #Python
40 875
✨ ipaddress | Python Standard Library ✨
📖 Provides the capabilities to create, manipulate, and operate on IPv4 and IPv6 addresses.
🏷️ #Python
40 875
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+03:0040 875
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}¤t_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!
🚪 @DataScience440 875
✨ 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
40 875
✨ 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
40 875
✨ Spyder | Code Editors & IDEs ✨
📖 A free, open source integrated development environment (IDE) for Python that is tailored to scientific computing and data analysis.
🏷️ #Python
