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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 40 118 suscriptores, ocupando la posición 3 231 en la categoría Tecnologías y Aplicaciones y el puesto 9 549 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 118 suscriptores.

Según los últimos datos del 31 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 153, y en las últimas 24 horas de 7, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.05%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.08% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 824 visualizaciones. En el primer día suele acumular 435 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 01 septiembre, 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.

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40 118
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Archivo de publicaciones
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Fundamentals of python.pdf10.65 MB

marimo: A Reactive, Reproducible Notebook marimo notebooks redefine the notebook experience by offering a reactive environmen
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 📁

🐍📰 What Are Mixin Classes in Python? Learn how to use Python mixin classes to write modular, reusable, and flexible code wi
🐍📰 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 🍏

python-docx: Create and Modify Word Documents #python python-docx is a Python library for reading, creating, and updating Mic
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 🚗

Building a Real-time Dashboard with FastAPI and Svelte In this tutorial, you'll learn how to build a real-time analytics dash
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 ac
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/

Django REST Framework and Vue versus Django and HTMX https://testdriven.io/blog/drf-vue-vs-django-htmx/ Learn how the develop
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 🌟

Get a weather forecast without API and complex settings in Python We use the wttr.in (https://github.com/chubin/wttr.in) serv
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 😏

python-docx: Create and Modify Word Documents #python python-docx is a Python library for reading, creating, and updating Mic
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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This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
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_rRW2scgfRhOTc0https://t.me/Codeprogrammer

Stelvio v0.3.0 is here! The easiest way to deploy a Python application on AWS. Only Python. No YAML. No JSON. No clicking around in the AWS Console. ✓ CLI with no prior setup ✓ Environment support Watch how I deploy an API from an empty folder — in less than 60 seconds. Try it right now 💊 Documentation: https://docs.stelvio.dev GitHub: https://github.com/michal-stlv/stelvio/ 👉 https://t.me/DataScience4 🌟

🐍📰 Skip Ahead in Loops With Python's Continue Keyword Learn how #Python's continue statement works, when to use it, common
🐍📰 Skip Ahead in Loops With Python's Continue Keyword Learn how #Python's continue statement works, when to use it, common mistakes to avoid, and what happens under the hood in CPython byte code https://realpython.com/python-continue/ https://t.me/DataScience4 🩷

Master Python Interviews with These 150 Essential Questions Preparing for a Python-based role in data science, analytics, software development, or AI? You need more than just coding skills — you need clarity on concepts, frameworks, and best practices. This document contains 150 most commonly asked Python interview questions with clear, concise answers covering: -Core Python – data types, control flow, OOP, memory management, iterators, decorators, and more -Data Science Libraries – NumPy, Pandas, Matplotlib, Seaborn -Frameworks – Flask, Django, Pyramid -Data Handling – CSV reading, DataFrames, joins, merges, file handling -Advanced Topics – GIL, multithreading, pickling, deep vs. shallow copy, generators -Coding Challenges – from Fibonacci to palindrome checkers, sorting algorithms, and data structure problems https://t.me/DataScienceQ 🧠

🐍📰 Python String Formatting: Available Tools and Their Features https://realpython.com/python-string-formatting/ #python
🐍📰 Python String Formatting: Available Tools and Their Features https://realpython.com/python-string-formatting/ #python

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