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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 40 060 suscriptores, ocupando la posición 3 242 en la categoría Tecnologías y Aplicaciones y el puesto 9 688 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 060 suscriptores.

Según los últimos datos del 27 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 168, y en las últimas 24 horas de 12, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 3.06%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.11% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 1 227 visualizaciones. En el primer día suele acumular 443 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 28 agosto, 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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40 060
Suscriptores
+1224 horas
-377 días
+16830 días
Archivo de publicaciones
✨ Quiz: Gemini CLI vs Claude Code: Which to Choose for Python Tasks ✨ 📖 Compare Gemini CLI and Claude Code across user exper
Quiz: Gemini CLI vs Claude Code: Which to Choose for Python Tasks ✨ 📖 Compare Gemini CLI and Claude Code across user experience, performance, code quality, and cost to find the right AI coding tool for you. 🏷️ #intermediate #ai #tools

✨ Quiz: Python Continuous Integration and Deployment Using GitHub Actions ✨ 📖 Practice essential GitHub Actions concepts, fr
Quiz: Python Continuous Integration and Deployment Using GitHub Actions ✨ 📖 Practice essential GitHub Actions concepts, from workflow file locations to triggers and common CI/CD tasks, with this hands-on quiz. 🏷️ #advanced #devops

dbm | Python Standard Library ✨ 📖 Provides a generic dictionary-like interface to DBM-style key-value databases backed by a file on disk. 🏷️ #Python

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✨ Quiz: Exploring Protocols in Python ✨ 📖 Test your knowledge of Python protocols, structural subtyping, and static type che
Quiz: Exploring Protocols in Python ✨ 📖 Test your knowledge of Python protocols, structural subtyping, and static type checking, including generic and subprotocol usage. 🏷️ #intermediate #python

curses | Python Standard Library ✨ 📖 Provides tools for building text-based user interfaces in Unix terminals, providing control over cursor position, colors, windows, and keyboard input. 🏷️ #Python

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

✨ Quiz: Reading Input and Writing Output in Python ✨ 📖 Test your Python basics: read user input with input(), display output
Quiz: Reading Input and Writing Output in Python ✨ 📖 Test your Python basics: read user input with input(), display output with print(), and handle numeric conversions. 🏷️ #basics #python

ctypes | Python Standard Library ✨ 📖 Allows for calling functions in shared C libraries and DLLs using C-compatible data types. 🏷️ #Python

✨ Dictionaries in Python ✨ 📖 Learn how dictionaries in Python work: create and modify key-value pairs using dict literals, t
Dictionaries in Python ✨ 📖 Learn how dictionaries in Python work: create and modify key-value pairs using dict literals, the dict() constructor, built-in methods, and operators. 🏷️ #basics #python

✨ Quiz: Implementing the Factory Method Pattern in Python ✨ 📖 Learn how the Factory Method pattern separates creation from u
Quiz: Implementing the Factory Method Pattern in Python ✨ 📖 Learn how the Factory Method pattern separates creation from use, promotes decoupling, and organizes Python products efficiently. 🏷️ #intermediate #best-practices

🚀 Sber has released two open-source MoE models: GigaChat-3.1 Ultra and Lightning Both code and weights are available under t
🚀 Sber has released two open-source MoE models: GigaChat-3.1 Ultra and Lightning Both code and weights are available under the MIT license on HuggingFace. 👉 Key details: • Trained from scratch (not a finetune) on proprietary data and infrastructure • Mixture-of-Experts (MoE) architecture Models: 🧠 GigaChat-3.1 Ultra • 702B MoE model for high-performance environments • Outperforms DeepSeek-V3-0324 and Qwen3-235B on math and reasoning benchmarks • Supports FP8 training and MTP ⚡️ GigaChat-3.1 Lightning • 10B model (1.8B active parameters) • Outperforms Qwen3-4B and Gemma-3-4B on Sber benchmarks • Efficient local inference • Up to 256k context Engineering highlights: • Custom metric to detect and reduce generation loops • DPO training moved to native FP8 • Improvements in post-training pipeline • Identified and fixed a critical issue affecting evaluation quality 🌍 Trained on 14 languages (optimized for English and Russian) Use cases: • chatbots • AI assistants • copilots • internal ML systems Sber provides a solid open foundation for developers to build production-ready AI systems with lower infrastructure costs.

✨ Quiz: Using Loguru to Simplify Python Logging ✨ 📖 Test your knowledge of Loguru for Python logging, from zero-config setup
Quiz: Using Loguru to Simplify Python Logging ✨ 📖 Test your knowledge of Loguru for Python logging, from zero-config setup and log levels to custom formats and adding context. 🏷️ #intermediate #tools

✨ Quiz: Building a Python GUI Application With Tkinter ✨ 📖 Test your Tkinter skills with this interactive challenge on widge
Quiz: Building a Python GUI Application With Tkinter ✨ 📖 Test your Tkinter skills with this interactive challenge on widgets, layouts, event loops, and text/file handling in Python GUIs. 🏷️ #basics #gui #stdlib

copyreg | Python Standard Library ✨ 📖 Provides a registry for defining custom pickling and copying functions for specific object types. 🏷️ #Python