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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Сеть:📈 Аналитический обзор Telegram-канала Learn Python Coding
Канал Learn Python Coding (@pythonre) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 40 872 подписчиков, занимая 3 287 место в категории Технологии и приложения и 9 131 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 40 872 подписчиков.
Согласно последним данным от 31 октября, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 306, а за последние 24 часа — -6, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 5.91%. В первые 24 часа после публикации контент обычно набирает 1.63% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 2 414 просмотров. В течение первых суток публикация набирает 665 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 3.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как math, harvard, oxford, supervision, waybienad.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“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”
Благодаря высокой частоте обновлений (последние данные получены 01 ноября, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Технологии и приложения.
40 872
Подписчики
-624 часа
-237 дней
+30630 дней
Архив постов
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✨ 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
40 872
✨ 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
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✨ 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
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✨ Jupyter AI | AI Coding Tools ✨
📖 A JupyterLab extension that brings generative AI into notebooks.
🏷️ #Python
40 872
✨ Zed | AI Coding Tools ✨
📖 A high-performance, collaborative code editor with built-in AI agent tooling.
🏷️ #Python
40 872
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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
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✨ 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
40 872
✨ Code Llama | AI Coding Tools ✨
📖 A family of code-specialized large language models (LLMs) for generating, completing, and explaining source code.
🏷️ #Python
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