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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
Mostrar más📈 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 39 118 suscriptores, ocupando la posición 3 502 en la categoría Tecnologías y Aplicaciones y el puesto 10 597 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 39 118 suscriptores.
Según los últimos datos del 05 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 458, y en las últimas 24 horas de 21, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.68%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.04% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 1 048 visualizaciones. En el primer día suele acumular 405 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 06 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.
39 118
Suscriptores
+2124 horas
+1207 días
+45830 días
Archivo de publicaciones
39 119
✨ Quiz: Test-Driven Development With pytest ✨
📖 Test your TDD skills with pytest. Practice writing unit tests, following pytest conventions, and measuring code coverage.
🏷️ #intermediate #testing
39 119
✨ codecs | Python Standard Library ✨
📖 Defines base classes for standard codecs and provides access to the codec registry for encoding and decoding text and binary data.
🏷️ #Python
39 119
✨ Quiz: Using Jupyter Notebooks ✨
📖 Test your Jupyter Notebook skills: cells, modes, shortcuts, Markdown, server tools, and exporting notebooks to HTML.
🏷️ #intermediate #tools
39 119
✨ code | Python Standard Library ✨
📖 Provides classes and functions for implementing read-eval-print loops and embedding interactive interpreter consoles in applications.
🏷️ #Python
39 119
✨ Quiz: Interacting With REST APIs and Python ✨
📖 Test your Python REST API knowledge: consuming, building, HTTP methods, status codes, Flask, FastAPI, and Django basics.
🏷️ #intermediate #api #web-dev
39 119
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_rRW2scgfRhOTc0
✅ https://t.me/Codeprogrammer
39 119
✨ Quiz: Getting Started With Django: Building a Portfolio App ✨
📖 Test your Django basics: frameworks, projects, views, templates, models, URLs, and migrations with practical questions.
🏷️ #basics #django #projects #web-dev
39 119
Repost from Machine Learning with Python
📱 Python enthusiasts, this is for you — 15 BEST REPOSITORIES on GitHub for learning Python
▶️ Awesome Python — https://github.com/vinta/awesome-python
— the largest and most authoritative collection of frameworks, libraries, and resources for Python — a must-save
▶️ TheAlgorithms/Python — https://github.com/TheAlgorithms/Python
— a huge collection of algorithms and data structures written in Python
▶️ Project-Based-Learning — https://github.com/practical-tutorials/project-based-learning
— learning Python (and not only) through real projects
▶️ Real Python Guide — https://github.com/realpython/python-guide
— a high-quality guide to the Python ecosystem, tools, and best practices
▶️ Materials from Real Python — https://github.com/realpython/materials
— a collection of code and projects for Real Python articles and courses
▶️ Learn Python — https://github.com/trekhleb/learn-python
— a reference with explanations, examples, and exercises
▶️ Learn Python 3 — https://github.com/jerry-git/learn-python3
— a convenient guide to modern Python 3 with tasks
▶️ Python Reference — https://github.com/rasbt/python_reference
— cheat sheets, scripts, and useful tips from one of the most respected Python authors
▶️ 30-Days-Of-Python — https://github.com/Asabeneh/30-Days-Of-Python
— a 30-day challenge: from syntax to more complex topics
▶️ Python Programming Exercises — https://github.com/zhiwehu/Python-programming-exercises
— 100+ Python tasks with answers
▶️ Coding Problems — https://github.com/MTrajK/coding-problems
— tasks on algorithms and data structures, including for preparation for interviews
▶️ Projects — https://github.com/karan/Projects
— a list of ideas for pet projects (not just Python). Great for practice
▶️ 100-Days-Of-ML-Code — https://github.com/Avik-Jain/100-Days-Of-ML-Code
— machine learning in Python in the format of a challenge
▶️ 30-Seconds-of-Python — https://github.com/30-seconds/30-seconds-of-python
— useful snippets and tricks for everyday tasks
▶️ Geekcomputers/Python — https://github.com/geekcomputers/Python
— various scripts: from working with the network to automation tasks
React ♥️ for more posts like this 💛
39 119
✨ Quiz: Using Data Classes in Python ✨
📖 Test your knowledge of Python data classes, namedtuple, immutability, auto-generated methods, inheritance, and slots.
🏷️ #intermediate #python
39 119
Repost from Machine Learning with Python
📱 A huge cheat sheet for Python, Django, Plotly, Matplotlib, Pygame
Many topics are covered inside:
🔸 All basic constructs: variables, conditions, loops, lists, dictionaries, functions, and classes — with clear examples;
🔸 Working with files, exceptions, and data input — understandable even for beginners;
🔸 #Django, #Pygame, #Matplotlib, and #Plotly — brief instructions on how to get started with each of the frameworks;
🔸 Tips on #Git, project structure, and unit testing.
https://t.me/CodeProgrammer ❤️
39 119
✨ Quiz: Python Modules and Packages: An Introduction ✨
📖 Test your knowledge of Python modules and packages. Learn about imports, namespaces, the dir() function, and more.
🏷️ #basics #python
39 119
Repost from Machine Learning with Python
⚡️ Colorizing old black-and-white videos and "bringing faces to life" for FREE
SVFR — a full-fledged framework for restoring faces in videos.
It can:
💬 BFR — improve blurry faces.
💬 Colorization — colorize black-and-white videos.
💬 Inpainting — redraw damaged areas.
💬 and combine all of this in one pass.
Essentially, the model takes old or damaged videos and makes them "as if they were shot yesterday". And it's free and open-source.
⚙️ Installation locally:
1. Create an environment
conda create -n svfr python=3.9 -y
conda activate svfrpip install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2pip install -r requirements.txtconda install git-lfs
git lfs install
git clone https://huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt models/stable-video-diffusion-img2vid-xtpython infer.py \
--config config/infer.yaml \
--task_ids 0 \
--input_path input.mp4 \
--output_dir results/ \
--crop_face_region0 — face enhancement
* 1 — colorization
* 2 — redrawing damage
An ideal tool if:
🟢you're restoring archival videos;
🟢you're creating historical content;
🟢you're working with neural networks and video effects;
🟢you want a wow result without paid services.
▶️ Demo on Hugging Face
♎️ GitHub/Instructions
#python #soft #github
https://t.me/CodeProgrammer39 119
🐍 Learning Python through real projects
A collection of projects with which you can master Python by creating real applications: from backends and parsers to bots, games, and automation systems.
Instead of theory — specific tasks, step-by-step tutorials, and repositories that help hone skills through practice.
📱 Link to GitHub
https://github.com/practical-tutorials/project-based-learning?tab=readme-ov-file#python
39 119
Repost from Machine Learning with Python
Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
39 119
✨ Quiz: Strings and Character Data in Python ✨
📖 Test your Python string and bytes knowledge! Explore immutability, f-strings, indexing, string methods, and bytes() usage.
🏷️ #basics #python
39 119
✨ Google Colab | Python Tools ✨
📖 A cloud-based Jupyter Notebook environment from Google for running Python code in a browser without any local installation.
🏷️ #Python
