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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Red:📈 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 40 122 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 40 122 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.
40 122
Suscriptores
+724 horas
+497 días
+15330 días
Archivo de publicaciones
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✨ How to Expense Your Real Python Membership ✨
📖 Many companies offer professional development or learning budgets that can cover the cost of a Real Python membership. Here's how you can get your membership reimbursed.
🏷️ #Python
40 122
✨ OverflowAI | AI Coding Tools ✨
📖 A suite of generative AI features that bring conversational search and assistants to Stack Overflow.
🏷️ #Python
40 122
✨ Quiz: Strip Characters From a Python String ✨
📖 Test your Python skills on removing characters from strings using strip, lstrip, and rstrip. Practice default behavior, custom chars, and more.
🏷️ #basics #python
40 122
✨ Microsoft Copilot | AI Coding Tools ✨
📖 A generative AI assistant available in Bing, Microsoft Edge, and Windows.
🏷️ #Python
40 122
✨ 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
40 122
✨ CodeGeeX | AI Coding Tools ✨
📖 An open multilingual code generation model family and an IDE assistant.
🏷️ #Python
40 122
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
40 122
✨ Jupyter AI | AI Coding Tools ✨
📖 A JupyterLab extension that brings generative AI into notebooks.
🏷️ #Python
40 122
✨ Zed | AI Coding Tools ✨
📖 A high-performance, collaborative code editor with built-in AI agent tooling.
🏷️ #Python
40 122
🌟 Swiftproxy – Fast, Secure, and Reliable Proxies for Every Project
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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 122
✨ 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
40 122
✨ 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
