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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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📈 Аналитический обзор Telegram-канала Learn Python Coding

Канал Learn Python Coding (@pythonre) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 40 873 подписчиков, занимая 3 292 место в категории Технологии и приложения и 9 353 место в регионе Индия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 40 873 подписчиков.

Согласно последним данным от 28 октября, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 351, а за последние 24 часа — -15, при этом общий охват остаётся высоким.

  • Статус верификации: Не верифицирован
  • Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 4.54%. В первые 24 часа после публикации контент обычно набирает 1.43% реакций от общего числа подписчиков.
  • Охват публикаций: В среднем каждый пост получает 1 854 просмотров. В течение первых суток публикация набирает 586 просмотров.
  • Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 3.
  • Тематические интересы: Контент сосредоточен на ключевых темах, таких как math, harvard, oxford, supervision, waybienad.

📝 Описание и контентная политика

Автор описывает ресурс как площадку для выражения субъективного мнения:
“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”

Благодаря высокой частоте обновлений (последние данные получены 29 октября, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Технологии и приложения.

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40 873
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-337 дней
+35130 дней
Архив постов
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✨ Quiz: Using Jupyter Notebooks ✨ 📖 Test your Jupyter Notebook skills: cells, modes, shortcuts, Markdown, server tools, and
✨ Quiz: Using Jupyter Notebooks ✨ 📖 Test your Jupyter Notebook skills: cells, modes, shortcuts, Markdown, server tools, and exporting notebooks to HTML. 🏷️ #intermediate #tools

✨ code | Python Standard Library ✨ 📖 Provides classes and functions for implementing read-eval-print loops and embedding interactive interpreter consoles in applications. 🏷️ #Python

✨ Quiz: Interacting With REST APIs and Python ✨ 📖 Test your Python REST API knowledge: consuming, building, HTTP methods, st
✨ 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

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_rRW2scgfRhOTc0 ✅ https://t.me/Codeprogrammer

✨ Quiz: Getting Started With Django: Building a Portfolio App ✨ 📖 Test your Django basics: frameworks, projects, views, temp
✨ 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

📱 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 💛

✨ Quiz: Using Data Classes in Python ✨ 📖 Test your knowledge of Python data classes, namedtuple, immutability, auto-generate
✨ Quiz: Using Data Classes in Python ✨ 📖 Test your knowledge of Python data classes, namedtuple, immutability, auto-generated methods, inheritance, and slots. 🏷️ #intermediate #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 ❤️

✨ Quiz: Python Modules and Packages: An Introduction ✨ 📖 Test your knowledge of Python modules and packages. Learn about imp
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⚡️ Colorizing old black-and-white videos and "bringing faces to life" for FREE SVFR — a full-fledged framework for restoring
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⚡️ 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 svfr
2. Install PyTorch (for your CUDA)
pip install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2
3. Install dependencies
pip install -r requirements.txt
4. Download models
conda install git-lfs
git lfs install
git clone https://huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt models/stable-video-diffusion-img2vid-xt
5. Start processing videos
python infer.py \
--config config/infer.yaml \
--task_ids 0 \
--input_path input.mp4 \
--output_dir results/ \
--crop_face_region
Where task_ids: * 0 — 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/CodeProgrammer

🐍 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

Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

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✨ Quiz: Strings and Character Data in Python ✨ 📖 Test your Python string and bytes knowledge! Explore immutability, f-string
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✨ Google Colab | Python Tools ✨ 📖 A cloud-based Jupyter Notebook environment from Google for running Python code in a browser without any local installation. 🏷️ #Python

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