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

Red:Machine Learning with Python India10 504 Tecnologías y Aplicaciones3 497...

📈 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 39 177 suscriptores, ocupando la posición 3 497 en la categoría Tecnologías y Aplicaciones y el puesto 10 504 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 39 177 suscriptores.

Según los últimos datos del 10 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 435, y en las últimas 24 horas de 20, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.50%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.94% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 980 visualizaciones. En el primer día suele acumular 367 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 11 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.

39 177

Suscriptores

+2024 horas

+867 días

+43530 días

980

Visitas de la publicación

~ 36724 horas

~ 46248 horas

2.50%

Tasa de compromiso

~ 3

Mensajes por día

Ads index

beta

Archivo de publicaciones

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Repost from Github Top Repositories

🔥 Trending Repository: 90DaysOfCyberSecurity 📝 Description: This repository contains a 90-day cybersecurity study plan, along with resources and materials for learning various cybersecurity concepts and technologies. The plan is organized into daily tasks, covering topics such as Network+, Security+, Linux, Python, Traffic Analysis, Git, ELK, AWS, Azure, and Hacking. The repository also includes a `LEARN.md 🔗 Repository URL: https://github.com/farhanashrafdev/90DaysOfCyberSecurity 📖 Readme: https://github.com/farhanashrafdev/90DaysOfCyberSecurity#readme 📊 Statistics: 🌟 Stars: 10.7K stars 👀 Watchers: 192 🍴 Forks: 1.2K forks 💻 Programming Languages: Not available 🏷️ Related Topics:

#cybersecurity #learn #hacktoberfest #ethical_hacking #communityexchange

================================== 🧠 By: https://t.me/DataScienceN

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Repost from Machine Learning with Python

https://t.me/DataScienceN. We have created a channel to guide students towards their educational paths correctly Join our channel

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Repost from Machine Learning with Python

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Fundamentals of python.pdf10.65 MB

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marimo: A Reactive, Reproducible Notebook marimo notebooks redefine the notebook experience by offering a reactive environment that addresses the limitations of traditional linear notebooks. With marimo, you can seamlessly reproduce and share content while benefiting from automatic cell updates and a correct execution order. Discover how marimo’s features make it an ideal tool for documenting research and learning activities. Link: https://realpython.com/marimo-notebook/ https://t.me/DataScience4 🫰 https://t.me/DataScience4 📁

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Top 100 Flask Developer Interview Questions & Answers Part 1: https://hackmd.io/@husseinsheikho/flask-int1 Part 2: https://hackmd.io/@husseinsheikho/flask-int2 Part 3: https://hackmd.io/@husseinsheikho/flask-int3 Part 4: https://hackmd.io/@husseinsheikho/flask-int4 Part 5: https://hackmd.io/@husseinsheikho/flask-int5 https://t.me/DataScience4

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🐍📰 What Are Mixin Classes in Python? Learn how to use Python mixin classes to write modular, reusable, and flexible code with practical examples and design tips https://realpython.com/python-mixin/ https://t.me/DataScience4 🍏

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python-docx: Create and Modify Word Documents #python python-docx is a Python library for reading, creating, and updating Microsoft Word 2007+ (.docx) files. Installation

pip install python-docx

Example

from docx import Document

document = Document()
document.add_paragraph("It was a dark and stormy night.")
<docx.text.paragraph.Paragraph object at 0x10f19e760>
document.save("dark-and-stormy.docx")

document = Document("dark-and-stormy.docx")
document.paragraphs[0].text
'It was a dark and stormy night.'

https://t.me/DataScienceN 🚗

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Building a Real-time Dashboard with FastAPI and Svelte In this tutorial, you'll learn how to build a real-time analytics dashboard using FastAPI and Svelte. We'll use server-sent events (SSE) to stream live data updates from FastAPI to our Svelte frontend, creating an interactive dashboard that updates in real-time. Start: https://testdriven.io/blog/fastapi-svelte/

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Nested Loops in Python Nested loops in Python allow you to place one loop inside another, enabling you to perform repeated actions over multiple sequences. Understanding nested loops helps you write more efficient code, manage complex data structures, and avoid common pitfalls such as poor readability and performance issues. Learn: https://realpython.com/nested-loops-python/

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Django REST Framework and Vue versus Django and HTMX https://testdriven.io/blog/drf-vue-vs-django-htmx/ Learn how the development process varies between working with Django REST Framework and Vue versus #Django and #HTMX. https://t.me/DataScience4 🌟

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Get a weather forecast without API and complex settings in Python We use the wttr.in (https://github.com/chubin/wttr.in) service — a simple and powerful tool that shows the weather right in the console. To work with the HTTP request, you only need one library - requests. Installing it is very easy: pip install requests Here is the minimal and clear code to get the forecast: import requests city = input("Enter the city name: ") url = f"https://wttr.in/{city}" try: response = requests.get(url) print(response.text) except Exception: print("Oops! Something went wrong. Please try again later.") Just enter the desired city and get a detailed forecast with temperature, precipitation Try it yourself 😏