اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
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
نمایش بیشتر📈 تحلیل کانال تلگرام Learn Python Coding
کانال Learn Python Coding (@pythonre) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 39 118 مشترک است و جایگاه 3 502 را در دسته فناوری و برنامهها و رتبه 10 597 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 39 118 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 05 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 458 و در ۲۴ ساعت گذشته برابر 21 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 2.68% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 1.04% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 1 048 بازدید دریافت میکند. در اولین روز معمولاً 405 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 3 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند math, harvard, oxford, supervision, waybienad تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“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”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 06 ژوئن, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامهها تبدیل کردهاند.
39 118
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✨ 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
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✨ 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
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✨ Quiz: Using Jupyter Notebooks ✨
📖 Test your Jupyter Notebook skills: cells, modes, shortcuts, Markdown, server tools, and exporting notebooks to HTML.
🏷️ #intermediate #tools
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✨ code | Python Standard Library ✨
📖 Provides classes and functions for implementing read-eval-print loops and embedding interactive interpreter consoles in applications.
🏷️ #Python
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✨ 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
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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
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✨ 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
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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 💛
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✨ Quiz: Using Data Classes in Python ✨
📖 Test your knowledge of Python data classes, namedtuple, immutability, auto-generated methods, inheritance, and slots.
🏷️ #intermediate #python
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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 ❤️
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✨ 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
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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
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Repost from Machine Learning with Python
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-strings, indexing, string methods, and bytes() usage.
🏷️ #basics #python
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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
