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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Network:š 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 40 873 subscribers, ranking 3 292 in the Technologies & Applications category and 9 353 in the India region.
š Audience metrics and dynamics
Since its creation on Š½ŠµŠ²ŃŠ“Š¾Š¼Š¾, the project has demonstrated rapid growth, gathering an audience of 40 873 subscribers.
According to the latest data from 28 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 351 over the last 30 days and by -15 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 4.54%. Within the first 24 hours after publication, content typically collects 1.43% reactions from the total number of subscribers.
- Post reach: On average, each post receives 1 854 views. Within the first day, a publication typically gains 586 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.
š Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
āLearn 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_Sheikhoā
Thanks to the high frequency of updates (latest data received on 29 October, 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.
40 873
Subscribers
-1524 hours
-337 days
+35130 days
Posts Archive
40 873
āØ codecs | Python Standard Library āØ
š Defines base classes for standard codecs and provides access to the codec registry for encoding and decoding text and binary data.
š·ļø #Python
40 873
āØ Quiz: Using Jupyter Notebooks āØ
š Test your Jupyter Notebook skills: cells, modes, shortcuts, Markdown, server tools, and exporting notebooks to HTML.
š·ļø #intermediate #tools
40 873
āØ code | Python Standard Library āØ
š Provides classes and functions for implementing read-eval-print loops and embedding interactive interpreter consoles in applications.
š·ļø #Python
40 873
āØ Quiz: Interacting With REST APIs and Python āØ
š Test your Python REST API knowledge: consuming, building, HTTP methods, status codes, Flask, FastAPI, and Django basics.
š·ļø #intermediate #api #web-dev
40 873
This channels is for Programmers, Coders, Software Engineers.
0ļøā£ Python
1ļøā£ Data Science
2ļøā£ Machine Learning
3ļøā£ Data Visualization
4ļøā£ Artificial Intelligence
5ļøā£ Data Analysis
6ļøā£ Statistics
7ļøā£ Deep Learning
8ļøā£ programming Languages
ā
https://t.me/addlist/8_rRW2scgfRhOTc0
ā
https://t.me/Codeprogrammer
40 873
āØ Quiz: Getting Started With Django: Building a Portfolio App āØ
š Test your Django basics: frameworks, projects, views, templates, models, URLs, and migrations with practical questions.
š·ļø #basics #django #projects #web-dev
40 873
Repost from Machine Learning with Python
š± Python enthusiasts, this is for you ā 15 BEST REPOSITORIES on GitHub for learning Python
ā¶ļø Awesome Python ā https://github.com/vinta/awesome-python
ā the largest and most authoritative collection of frameworks, libraries, and resources for Python ā a must-save
ā¶ļø TheAlgorithms/Python ā https://github.com/TheAlgorithms/Python
ā a huge collection of algorithms and data structures written in Python
ā¶ļø Project-Based-Learning ā https://github.com/practical-tutorials/project-based-learning
ā learning Python (and not only) through real projects
ā¶ļø Real Python Guide ā https://github.com/realpython/python-guide
ā a high-quality guide to the Python ecosystem, tools, and best practices
ā¶ļø Materials from Real Python ā https://github.com/realpython/materials
ā a collection of code and projects for Real Python articles and courses
ā¶ļø Learn Python ā https://github.com/trekhleb/learn-python
ā a reference with explanations, examples, and exercises
ā¶ļø Learn Python 3 ā https://github.com/jerry-git/learn-python3
ā a convenient guide to modern Python 3 with tasks
ā¶ļø Python Reference ā https://github.com/rasbt/python_reference
ā cheat sheets, scripts, and useful tips from one of the most respected Python authors
ā¶ļø 30-Days-Of-Python ā https://github.com/Asabeneh/30-Days-Of-Python
ā a 30-day challenge: from syntax to more complex topics
ā¶ļø Python Programming Exercises ā https://github.com/zhiwehu/Python-programming-exercises
ā 100+ Python tasks with answers
ā¶ļø Coding Problems ā https://github.com/MTrajK/coding-problems
ā tasks on algorithms and data structures, including for preparation for interviews
ā¶ļø Projects ā https://github.com/karan/Projects
ā a list of ideas for pet projects (not just Python). Great for practice
ā¶ļø 100-Days-Of-ML-Code ā https://github.com/Avik-Jain/100-Days-Of-ML-Code
ā machine learning in Python in the format of a challenge
ā¶ļø 30-Seconds-of-Python ā https://github.com/30-seconds/30-seconds-of-python
ā useful snippets and tricks for everyday tasks
ā¶ļø Geekcomputers/Python ā https://github.com/geekcomputers/Python
ā various scripts: from working with the network to automation tasks
React ā„ļø for more posts like this š
40 873
āØ Quiz: Using Data Classes in Python āØ
š Test your knowledge of Python data classes, namedtuple, immutability, auto-generated methods, inheritance, and slots.
š·ļø #intermediate #python
40 873
Repost from Machine Learning with Python
š± A huge cheat sheet for Python, Django, Plotly, Matplotlib, Pygame
Many topics are covered inside:
šø All basic constructs: variables, conditions, loops, lists, dictionaries, functions, and classes ā with clear examples;
šø Working with files, exceptions, and data input ā understandable even for beginners;
šø #Django, #Pygame, #Matplotlib, and #Plotly ā brief instructions on how to get started with each of the frameworks;
šø Tips on #Git, project structure, and unit testing.
https://t.me/CodeProgrammer ā¤ļø
40 873
āØ Quiz: Python Modules and Packages: An Introduction āØ
š Test your knowledge of Python modules and packages. Learn about imports, namespaces, the dir() function, and more.
š·ļø #basics #python
40 873
Repost from Machine Learning with Python
+2ā”ļø Colorizing old black-and-white videos and "bringing faces to life" for FREE
SVFR ā a full-fledged framework for restoring faces in videos.
It can:
š¬ BFR ā improve blurry faces.
š¬ Colorization ā colorize black-and-white videos.
š¬ Inpainting ā redraw damaged areas.
š¬ 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.
āļø 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 ā face enhancement
* 1 ā colorization
* 2 ā redrawing damage
An ideal tool if:
š¢you're restoring archival videos;
š¢you're creating historical content;
š¢you're working with neural networks and video effects;
š¢you want a wow result without paid services.
ā¶ļø Demo on Hugging Face
āļø GitHub/Instructions
#python #soft #github
https://t.me/CodeProgrammer40 873
š 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 ā specific tasks, step-by-step tutorials, and repositories that help hone skills through practice.
š± Link to GitHub
https://github.com/practical-tutorials/project-based-learning?tab=readme-ov-file#python
40 873
Repost from Machine Learning with Python
Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
40 873
āØ Quiz: Strings and Character Data in Python āØ
š Test your Python string and bytes knowledge! Explore immutability, f-strings, indexing, string methods, and bytes() usage.
š·ļø #basics #python
40 873
āØ Google Colab | Python Tools āØ
š A cloud-based Jupyter Notebook environment from Google for running Python code in a browser without any local installation.
š·ļø #Python
