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:Machine Learning with Python Индия10 504 Технологии и приложения3 497...

📈 Аналитический обзор Telegram-канала Learn Python Coding

Канал Learn Python Coding (@pythonre) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 39 177 подписчиков, занимая 3 497 место в категории Технологии и приложения и 10 504 место в регионе Индия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 39 177 подписчиков.

Согласно последним данным от 10 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 435, а за последние 24 часа — 20, при этом общий охват остаётся высоким.

Статус верификации: Не верифицирован
Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 2.50%. В первые 24 часа после публикации контент обычно набирает 0.94% реакций от общего числа подписчиков.
Охват публикаций: В среднем каждый пост получает 980 просмотров. В течение первых суток публикация набирает 367 просмотров.
Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 4.
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 11 июня, 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.

39 177

Подписчики

+2024 часа

+867 дней

+43530 день

980

Просмотры поста

~ 36724 часа

~ 46248 часов

2.50%

Коэффициент вовлеченности

~ 3

Постов в день

Ads index

beta

Архив постов

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Repost from Github Top Repositories

🔥 Trending Repository: 90DaysOfCyberSecurity 📝 Description: This repository contains a 90-day cybersecurity study plan, along with resources and materials for learning various cybersecurity concepts and technologies. The plan is organized into daily tasks, covering topics such as Network+, Security+, Linux, Python, Traffic Analysis, Git, ELK, AWS, Azure, and Hacking. The repository also includes a `LEARN.md 🔗 Repository URL: https://github.com/farhanashrafdev/90DaysOfCyberSecurity 📖 Readme: https://github.com/farhanashrafdev/90DaysOfCyberSecurity#readme 📊 Statistics: 🌟 Stars: 10.7K stars 👀 Watchers: 192 🍴 Forks: 1.2K forks 💻 Programming Languages: Not available 🏷️ Related Topics:

#cybersecurity #learn #hacktoberfest #ethical_hacking #communityexchange

================================== 🧠 By: https://t.me/DataScienceN

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Repost from Machine Learning with Python

https://t.me/DataScienceN. We have created a channel to guide students towards their educational paths correctly Join our channel

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Repost from Machine Learning with Python

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Fundamentals of python.pdf10.65 MB

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marimo: A Reactive, Reproducible Notebook marimo notebooks redefine the notebook experience by offering a reactive environment that addresses the limitations of traditional linear notebooks. With marimo, you can seamlessly reproduce and share content while benefiting from automatic cell updates and a correct execution order. Discover how marimo’s features make it an ideal tool for documenting research and learning activities. Link: https://realpython.com/marimo-notebook/ https://t.me/DataScience4 🫰 https://t.me/DataScience4 📁

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Top 100 Flask Developer Interview Questions & Answers Part 1: https://hackmd.io/@husseinsheikho/flask-int1 Part 2: https://hackmd.io/@husseinsheikho/flask-int2 Part 3: https://hackmd.io/@husseinsheikho/flask-int3 Part 4: https://hackmd.io/@husseinsheikho/flask-int4 Part 5: https://hackmd.io/@husseinsheikho/flask-int5 https://t.me/DataScience4

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🐍📰 What Are Mixin Classes in Python? Learn how to use Python mixin classes to write modular, reusable, and flexible code with practical examples and design tips https://realpython.com/python-mixin/ https://t.me/DataScience4 🍏

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python-docx: Create and Modify Word Documents #python python-docx is a Python library for reading, creating, and updating Microsoft Word 2007+ (.docx) files. Installation

pip install python-docx

Example

from docx import Document

document = Document()
document.add_paragraph("It was a dark and stormy night.")
<docx.text.paragraph.Paragraph object at 0x10f19e760>
document.save("dark-and-stormy.docx")

document = Document("dark-and-stormy.docx")
document.paragraphs[0].text
'It was a dark and stormy night.'

https://t.me/DataScienceN 🚗

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Building a Real-time Dashboard with FastAPI and Svelte In this tutorial, you'll learn how to build a real-time analytics dashboard using FastAPI and Svelte. We'll use server-sent events (SSE) to stream live data updates from FastAPI to our Svelte frontend, creating an interactive dashboard that updates in real-time. Start: https://testdriven.io/blog/fastapi-svelte/

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Nested Loops in Python Nested loops in Python allow you to place one loop inside another, enabling you to perform repeated actions over multiple sequences. Understanding nested loops helps you write more efficient code, manage complex data structures, and avoid common pitfalls such as poor readability and performance issues. Learn: https://realpython.com/nested-loops-python/

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Django REST Framework and Vue versus Django and HTMX https://testdriven.io/blog/drf-vue-vs-django-htmx/ Learn how the development process varies between working with Django REST Framework and Vue versus #Django and #HTMX. https://t.me/DataScience4 🌟

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Get a weather forecast without API and complex settings in Python We use the wttr.in (https://github.com/chubin/wttr.in) service — a simple and powerful tool that shows the weather right in the console. To work with the HTTP request, you only need one library - requests. Installing it is very easy: pip install requests Here is the minimal and clear code to get the forecast: import requests city = input("Enter the city name: ") url = f"https://wttr.in/{city}" try: response = requests.get(url) print(response.text) except Exception: print("Oops! Something went wrong. Please try again later.") Just enter the desired city and get a detailed forecast with temperature, precipitation Try it yourself 😏