Уже доступно! Исследование Telegram 2025 — ключевые инсайты года 
Learn Python Coding
Открыть в Telegram
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
Больше📈 Аналитический обзор Telegram-канала Learn Python Coding
Канал Learn Python Coding (@pythonre) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 39 118 подписчиков, занимая 3 502 место в категории Технологии и приложения и 10 597 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 39 118 подписчиков.
Согласно последним данным от 05 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 458, а за последние 24 часа — 21, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 2.68%. В первые 24 часа после публикации контент обычно набирает 1.04% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 1 048 просмотров. В течение первых суток публикация набирает 405 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 06 июня, 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.
39 118
Подписчики
+2124 часа
+1207 дней
+45830 день
Архив постов
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
