Learn Python Coding

✨ D-Strings Could End Your textwrap.dedent() Days and Other Python News for April 2026 ✨

📖 D-strings proposed to kill textwrap.dedent(), Python 3.15 alpha 7 ships lazy imports, GPT-5.4 launches, and Python Insider moves home.

🏷️ #community #news

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: Python's Counter: The Pythonic Way to Count Objects ✨

📖 Test your understanding of Python's Counter class from the collections module, including construction, counting, and multiset operations.

🏷️ #basics #python #stdlib

✨ codeop | Python Standard Library ✨

📖 Provides utilities for incrementally compiling Python source code and tracking future statements.

🏷️ #Python

✨ Python Classes: The Power of Object-Oriented Programming ✨

📖 Learn how to define and use Python classes to implement object-oriented programming. Dive into attributes, methods, inheritance, and more.

🏷️ #intermediate #best-practices #python

✨ Quiz: Exploring Keywords in Python ✨

📖 Test your understanding of Python keywords, including the difference between regular and soft keywords, keyword categories, and common pitfalls.

🏷️ #basics #python

📚 Python Interview Basics for Beginners

#Development #Python #Free #Udemy

📝 prepare for next python interview

⏱ Duration: 39 m
👥 Enrollments: 23
⭐ Rating: 4 (1 reviews)
🎓 Features: Udemy • English • Beginner • Development,Python

━━━━━━━━━━━━━━━━━━━━
📢 Join our channel: @Courses27

⚠️ Note: You may need to watch a short ad to access the course. This helps keep the service free for everyone. 🙏

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

✨ 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

✨ 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

✨ 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, 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 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, 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-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 imports, namespaces, the dir() function, and more.

🏷️ #basics #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 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