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 40 118 подписчиков, занимая 3 231 место в категории Технологии и приложения и 9 549 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 40 118 подписчиков.
Согласно последним данным от 31 августа, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 153, а за последние 24 часа — 7, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 2.05%. В первые 24 часа после публикации контент обычно набирает 1.08% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 824 просмотров. В течение первых суток публикация набирает 435 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 2.
- 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 сентября, 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.
40 118
Подписчики
+724 часа
+497 дней
+15330 дней
Архив постов
40 124
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 📁
40 124
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
40 124
🐍📰 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 🍏
40 124
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-docxfrom 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.'40 124
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/
40 124
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/
40 124
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 🌟
40 124
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 😏
40 124
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-docxfrom 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.'
40 124
Repost from Machine Learning with Python
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
40 124
Stelvio v0.3.0 is here!
The easiest way to deploy a Python application on AWS.
Only Python.
No YAML. No JSON. No clicking around in the AWS Console.
✓ CLI with no prior setup
✓ Environment support
Watch how I deploy an API from an empty folder — in less than 60 seconds.
Try it right now 💊
Documentation: https://docs.stelvio.dev
GitHub: https://github.com/michal-stlv/stelvio/
👉 https://t.me/DataScience4 🌟
40 124
🐍📰 Skip Ahead in Loops With Python's Continue Keyword
Learn how #Python's continue statement works, when to use it, common mistakes to avoid, and what happens under the hood in CPython byte code
https://realpython.com/python-continue/
https://t.me/DataScience4 🩷
40 124
Master Python Interviews with These 150 Essential Questions
Preparing for a Python-based role in data science, analytics, software development, or AI?
You need more than just coding skills — you need clarity on concepts, frameworks, and best practices.
This document contains 150 most commonly asked Python interview questions with clear, concise answers covering:
-Core Python – data types, control flow, OOP, memory management, iterators, decorators, and more
-Data Science Libraries – NumPy, Pandas, Matplotlib, Seaborn
-Frameworks – Flask, Django, Pyramid
-Data Handling – CSV reading, DataFrames, joins, merges, file handling
-Advanced Topics – GIL, multithreading, pickling, deep vs. shallow copy, generators
-Coding Challenges – from Fibonacci to palindrome checkers, sorting algorithms, and data structure problems
https://t.me/DataScienceQ 🧠
40 124
🐍📰 Python String Formatting: Available Tools and Their Features
https://realpython.com/python-string-formatting/
#python
40 124
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