Learn Python Coding
Open in 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
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Network:📈 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 40 872 subscribers, ranking 3 281 in the Technologies & Applications category and 9 100 in the India region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 40 872 subscribers.
According to the latest data from 01 November, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 294 over the last 30 days and by 3 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 5.30%. Within the first 24 hours after publication, content typically collects 1.56% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 167 views. Within the first day, a publication typically gains 637 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.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“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”
Thanks to the high frequency of updates (latest data received on 02 November, 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.
40 872
Subscribers
+324 hours
-237 days
+29430 days
Posts Archive
40 872
✨ Microsoft Copilot | AI Coding Tools ✨
📖 A generative AI assistant available in Bing, Microsoft Edge, and Windows.
🏷️ #Python
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✨ Quiz: Get Started With FastAPI ✨
📖 This hands-on quiz will test your knowledge of FastAPI basics, from installation and endpoints to automatic JSON responses and Swagger UI.
🏷️ #intermediate #api #front-end #web-dev
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✨ CodeGeeX | AI Coding Tools ✨
📖 An open multilingual code generation model family and an IDE assistant.
🏷️ #Python
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Repost from Machine Learning with Python
Visualization of Python objects and references
Many beginner Python developers face confusion when working with mutability and references between variables. It is especially difficult to understand during debugging of complex data structures when it is unclear how exactly they are connected. ⌨️
So here is memory_graph — an open-source tool for visualizing Python objects and references. It shows the data structure, call stack, and connections between variables.
👉 Link: https://github.com/bterwijn/memory_graph?tab=readme-ov-file
It also supports working with recursion and structures such as binary trees or linked lists.
Works in VS Code, Jupyter, PyCharm, and is available online without installation.
😁 more: https://memory-graph.com/#breakpoints=8&continues=1×tep=1.0&play
👉 https://t.me/CodeProgrammer
40 872
✨ Polars vs pandas: What's the Difference? ✨
📖 Discover the key differences in Polars vs pandas to help you choose the right Python library for faster, more efficient data analysis.
🏷️ #intermediate #data-science #python
40 872
✨ Jupyter AI | AI Coding Tools ✨
📖 A JupyterLab extension that brings generative AI into notebooks.
🏷️ #Python
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✨ Zed | AI Coding Tools ✨
📖 A high-performance, collaborative code editor with built-in AI agent tooling.
🏷️ #Python
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40 872
4 ways to copy a list in Python
In Python, there are several ways to make a copy of a list. But it is important to understand the difference between a shallow copy and a deep copy.
original = [1, 2, [3, 4]]
# 1. Slice (shallow copy)
copy1 = original[:]
# 2. .copy() method (shallow copy)
copy2 = original.copy()
# 3. Using list() (shallow copy)
copy3 = list(original)
# 4. deepcopy (deep copy)
import copy
copy4 = copy.deepcopy(original)original[2].append(5)
print(copy1)
# [1, 2, [3, 4, 5]] — nested list changed!
print(copy4)
# [1, 2, [3, 4]] — unchanged40 872
✨ Astral's ty: A New Blazing-Fast Type Checker for Python ✨
📖 Learn to use ty, an ultra-fast Python type checker written in Rust. Get setup instructions, run type checks, and fine-tune custom rules in personal projects.
🏷️ #intermediate #tools
40 872
✨ Quiz: What Can You Do With Python? ✨
📖 Review where Python shines: web, APIs, CLIs, GUIs, data science, ORMs, automation, and robots. Practice key terms, tools, and workflows.
🏷️ #basics #career
40 872
✨ Quiz: Ways to Start Interacting With Python ✨
📖 Test your knowledge of running Python interactively using REPL, scripts, and IDEs, and clarify key concepts.
🏷️ #basics #python
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✨ Code Llama | AI Coding Tools ✨
📖 A family of code-specialized large language models (LLMs) for generating, completing, and explaining source code.
🏷️ #Python
40 872
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