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 40 872 suscriptores, ocupando la posición 3 281 en la categoría Tecnologías y Aplicaciones y el puesto 9 100 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 872 suscriptores.
Según los últimos datos del 01 noviembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 294, y en las últimas 24 horas de 3, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 5.30%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.56% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 167 visualizaciones. En el primer día suele acumular 637 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 02 noviembre, 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.
40 872
Suscriptores
+324 horas
-237 días
+29430 días
Archivo de publicaciones
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✨ Microsoft Copilot | AI Coding Tools ✨
📖 A generative AI assistant available in Bing, Microsoft Edge, and Windows.
🏷️ #Python
40 872
✨ Quiz: Get Started With FastAPI ✨
📖 This hands-on quiz will test your knowledge of FastAPI basics, from installation and endpoints to automatic JSON responses and Swagger UI.
🏷️ #intermediate #api #front-end #web-dev
40 872
✨ CodeGeeX | AI Coding Tools ✨
📖 An open multilingual code generation model family and an IDE assistant.
🏷️ #Python
40 872
Repost from Machine Learning with Python
Visualization of Python objects and references
Many beginner Python developers face confusion when working with mutability and references between variables. It is especially difficult to understand during debugging of complex data structures when it is unclear how exactly they are connected. ⌨️
So here is memory_graph — an open-source tool for visualizing Python objects and references. It shows the data structure, call stack, and connections between variables.
👉 Link: https://github.com/bterwijn/memory_graph?tab=readme-ov-file
It also supports working with recursion and structures such as binary trees or linked lists.
Works in VS Code, Jupyter, PyCharm, and is available online without installation.
😁 more: https://memory-graph.com/#breakpoints=8&continues=1×tep=1.0&play
👉 https://t.me/CodeProgrammer
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✨ Polars vs pandas: What's the Difference? ✨
📖 Discover the key differences in Polars vs pandas to help you choose the right Python library for faster, more efficient data analysis.
🏷️ #intermediate #data-science #python
40 872
✨ Jupyter AI | AI Coding Tools ✨
📖 A JupyterLab extension that brings generative AI into notebooks.
🏷️ #Python
40 872
✨ Zed | AI Coding Tools ✨
📖 A high-performance, collaborative code editor with built-in AI agent tooling.
🏷️ #Python
40 872
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4 ways to copy a list in Python
In Python, there are several ways to make a copy of a list. But it is important to understand the difference between a shallow copy and a deep copy.
original = [1, 2, [3, 4]]
# 1. Slice (shallow copy)
copy1 = original[:]
# 2. .copy() method (shallow copy)
copy2 = original.copy()
# 3. Using list() (shallow copy)
copy3 = list(original)
# 4. deepcopy (deep copy)
import copy
copy4 = copy.deepcopy(original)original[2].append(5)
print(copy1)
# [1, 2, [3, 4, 5]] — nested list changed!
print(copy4)
# [1, 2, [3, 4]] — unchanged40 872
✨ Astral's ty: A New Blazing-Fast Type Checker for Python ✨
📖 Learn to use ty, an ultra-fast Python type checker written in Rust. Get setup instructions, run type checks, and fine-tune custom rules in personal projects.
🏷️ #intermediate #tools
40 872
✨ Quiz: What Can You Do With Python? ✨
📖 Review where Python shines: web, APIs, CLIs, GUIs, data science, ORMs, automation, and robots. Practice key terms, tools, and workflows.
🏷️ #basics #career
40 872
✨ Quiz: Ways to Start Interacting With Python ✨
📖 Test your knowledge of running Python interactively using REPL, scripts, and IDEs, and clarify key concepts.
🏷️ #basics #python
40 872
✨ Code Llama | AI Coding Tools ✨
📖 A family of code-specialized large language models (LLMs) for generating, completing, and explaining source code.
🏷️ #Python
40 872
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