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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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πŸ“ˆ 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 39 142 subscribers, ranking 3 508 in the Technologies & Applications category and 10 563 in the India region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 39 142 subscribers.

According to the latest data from 08 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 425 over the last 30 days and by 11 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 2.56%. Within the first 24 hours after publication, content typically collects 1.00% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 003 views. Within the first day, a publication typically gains 391 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 4.
  • Thematic interests: Content is focused on key topics such as math, harvard, oxford, supervision, waybienad.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œLearn 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 09 June, 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.

39 142
Subscribers
+1124 hours
+797 days
+42530 days
Posts Archive
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✨ Anaconda | Python Tools ✨ πŸ“– A curated distribution of Python and R for data science. 🏷️ #Python

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

πŸš€ Master Data Science & Programming! Unlock your potential with this curated list of Telegram channels. Whether you need boo
πŸš€ 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! πŸ”° 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 πŸ”– 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 πŸ’Ύ 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 πŸ§‘β€πŸŽ“ Udemy Coupons | Courses The first channel in Telegram that offers free Udemy coupons https://t.me/DataScienceC πŸ˜€ ML Research Hub Advancing research in Machine Learning – practical insights, tools, and techniques for researchers. https://t.me/DataScienceT πŸ’¬ Data Science Chat An active community group for discussing data challenges and networking with peers. https://t.me/DataScience9 🐍 Python Arab| Ψ¨Ψ§ΩŠΨ«ΩˆΩ† عربي The largest Arabic-speaking group for Python developers to share knowledge and help. https://t.me/PythonArab πŸ–Š Data Science Jupyter Notebooks Explore the world of Data Science through Jupyter Notebooksβ€”insights, tutorials, and tools to boost your data journey. Code, analyze, and visualize smarter with every post. https://t.me/DataScienceN πŸ“Ί Free Online Courses | Videos Free online courses covering data science, machine learning, analytics, programming, and essential skills for learners. https://t.me/DataScienceV πŸ“ˆ 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 ✨ πŸ“– Test your understanding of recursion in Python, including base cases, recur
✨ Quiz: Recursion in Python: An Introduction ✨ πŸ“– Test your understanding of recursion in Python, including base cases, recursive structure, performance considerations, and common use cases. 🏷️ #intermediate #algorithms #python

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

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

✨ ipaddress | Python Standard Library ✨ πŸ“– 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']}Β°C, Wind speed: {weather['windspeed']} km/h")
πŸ”₯ Get fresh weather data without registration or passwords β€” useful for your own projects or bots! πŸšͺ @DataScience4

✨ Topic: Python Machine Learning ✨ πŸ“– Learn how to implement machine learning (ML) algorithms in Python. With these skills, y
✨ Topic: Python Machine Learning ✨ πŸ“– 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 ✨ πŸ“– Learn Liskov substitution in Python. Spot Square
✨ Quiz: SOLID Design Principles: Improve Object-Oriented Code in Python ✨ πŸ“– 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 ✨ πŸ“– A free, open source integrated development environment (IDE) for Python that is tailored to scientific computing and data analysis. 🏷️ #Python

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

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

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

✨ Cookiecutter | Python Tools ✨ πŸ“– A project templating and scaffolding tool. 🏷️ #Python

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