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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
Show moreπ Analytical overview of Telegram channel Learn Python Coding
Channel Learn Python Coding (@pythonre) in the English language segment is an active participant. Currently, the community unites 39 118 subscribers, ranking 3 502 in the Technologies & Applications category and 10 597 in the India region.
π Audience metrics and dynamics
Since its creation on Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 39 118 subscribers.
According to the latest data from 05 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 458 over the last 30 days and by 21 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 2.68%. Within the first 24 hours after publication, content typically collects 1.04% reactions from the total number of subscribers.
- Post reach: On average, each post receives 1 048 views. Within the first day, a publication typically gains 405 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
- Thematic interests: Content is focused on key topics such as math, harvard, oxford, supervision, waybienad.
π Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
βLearn 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_Sheikhoβ
Thanks to the high frequency of updates (latest data received on 06 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
39 118
Subscribers
+2124 hours
+1207 days
+45830 days
Posts Archive
39 119
β¨ Quiz: Test-Driven Development With pytest β¨
π Test your TDD skills with pytest. Practice writing unit tests, following pytest conventions, and measuring code coverage.
π·οΈ #intermediate #testing
39 119
β¨ codecs | Python Standard Library β¨
π Defines base classes for standard codecs and provides access to the codec registry for encoding and decoding text and binary data.
π·οΈ #Python
39 119
β¨ Quiz: Using Jupyter Notebooks β¨
π Test your Jupyter Notebook skills: cells, modes, shortcuts, Markdown, server tools, and exporting notebooks to HTML.
π·οΈ #intermediate #tools
39 119
β¨ code | Python Standard Library β¨
π Provides classes and functions for implementing read-eval-print loops and embedding interactive interpreter consoles in applications.
π·οΈ #Python
39 119
β¨ Quiz: Interacting With REST APIs and Python β¨
π Test your Python REST API knowledge: consuming, building, HTTP methods, status codes, Flask, FastAPI, and Django basics.
π·οΈ #intermediate #api #web-dev
39 119
This channels is for Programmers, Coders, Software Engineers.
0οΈβ£ Python
1οΈβ£ Data Science
2οΈβ£ Machine Learning
3οΈβ£ Data Visualization
4οΈβ£ Artificial Intelligence
5οΈβ£ Data Analysis
6οΈβ£ Statistics
7οΈβ£ Deep Learning
8οΈβ£ programming Languages
β
https://t.me/addlist/8_rRW2scgfRhOTc0
β
https://t.me/Codeprogrammer
39 119
β¨ Quiz: Getting Started With Django: Building a Portfolio App β¨
π Test your Django basics: frameworks, projects, views, templates, models, URLs, and migrations with practical questions.
π·οΈ #basics #django #projects #web-dev
39 119
Repost from Machine Learning with Python
π± Python enthusiasts, this is for you β 15 BEST REPOSITORIES on GitHub for learning Python
βΆοΈ Awesome Python β https://github.com/vinta/awesome-python
β the largest and most authoritative collection of frameworks, libraries, and resources for Python β a must-save
βΆοΈ TheAlgorithms/Python β https://github.com/TheAlgorithms/Python
β a huge collection of algorithms and data structures written in Python
βΆοΈ Project-Based-Learning β https://github.com/practical-tutorials/project-based-learning
β learning Python (and not only) through real projects
βΆοΈ Real Python Guide β https://github.com/realpython/python-guide
β a high-quality guide to the Python ecosystem, tools, and best practices
βΆοΈ Materials from Real Python β https://github.com/realpython/materials
β a collection of code and projects for Real Python articles and courses
βΆοΈ Learn Python β https://github.com/trekhleb/learn-python
β a reference with explanations, examples, and exercises
βΆοΈ Learn Python 3 β https://github.com/jerry-git/learn-python3
β a convenient guide to modern Python 3 with tasks
βΆοΈ Python Reference β https://github.com/rasbt/python_reference
β cheat sheets, scripts, and useful tips from one of the most respected Python authors
βΆοΈ 30-Days-Of-Python β https://github.com/Asabeneh/30-Days-Of-Python
β a 30-day challenge: from syntax to more complex topics
βΆοΈ Python Programming Exercises β https://github.com/zhiwehu/Python-programming-exercises
β 100+ Python tasks with answers
βΆοΈ Coding Problems β https://github.com/MTrajK/coding-problems
β tasks on algorithms and data structures, including for preparation for interviews
βΆοΈ Projects β https://github.com/karan/Projects
β a list of ideas for pet projects (not just Python). Great for practice
βΆοΈ 100-Days-Of-ML-Code β https://github.com/Avik-Jain/100-Days-Of-ML-Code
β machine learning in Python in the format of a challenge
βΆοΈ 30-Seconds-of-Python β https://github.com/30-seconds/30-seconds-of-python
β useful snippets and tricks for everyday tasks
βΆοΈ Geekcomputers/Python β https://github.com/geekcomputers/Python
β various scripts: from working with the network to automation tasks
React β₯οΈ for more posts like this π
39 119
β¨ Quiz: Using Data Classes in Python β¨
π Test your knowledge of Python data classes, namedtuple, immutability, auto-generated methods, inheritance, and slots.
π·οΈ #intermediate #python
39 119
Repost from Machine Learning with Python
π± A huge cheat sheet for Python, Django, Plotly, Matplotlib, Pygame
Many topics are covered inside:
πΈ All basic constructs: variables, conditions, loops, lists, dictionaries, functions, and classes β with clear examples;
πΈ Working with files, exceptions, and data input β understandable even for beginners;
πΈ #Django, #Pygame, #Matplotlib, and #Plotly β brief instructions on how to get started with each of the frameworks;
πΈ Tips on #Git, project structure, and unit testing.
https://t.me/CodeProgrammer β€οΈ
39 119
β¨ Quiz: Python Modules and Packages: An Introduction β¨
π Test your knowledge of Python modules and packages. Learn about imports, namespaces, the dir() function, and more.
π·οΈ #basics #python
39 119
Repost from Machine Learning with Python
β‘οΈ Colorizing old black-and-white videos and "bringing faces to life" for FREE
SVFR β a full-fledged framework for restoring faces in videos.
It can:
π¬ BFR β improve blurry faces.
π¬ Colorization β colorize black-and-white videos.
π¬ Inpainting β redraw damaged areas.
π¬ 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.
βοΈ 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 β face enhancement
* 1 β colorization
* 2 β redrawing damage
An ideal tool if:
π’you're restoring archival videos;
π’you're creating historical content;
π’you're working with neural networks and video effects;
π’you want a wow result without paid services.
βΆοΈ Demo on Hugging Face
βοΈ GitHub/Instructions
#python #soft #github
https://t.me/CodeProgrammer39 119
π 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 β specific tasks, step-by-step tutorials, and repositories that help hone skills through practice.
π± 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
β¨ Quiz: Strings and Character Data in Python β¨
π Test your Python string and bytes knowledge! Explore immutability, f-strings, indexing, string methods, and bytes() usage.
π·οΈ #basics #python
39 119
β¨ Google Colab | Python Tools β¨
π A cloud-based Jupyter Notebook environment from Google for running Python code in a browser without any local installation.
π·οΈ #Python
