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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Red:📈 Análisis del canal de Telegram Learn Python Coding
El canal Learn Python Coding (@pythonre) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 40 900 suscriptores, ocupando la posición 3 279 en la categoría Tecnologías y Aplicaciones y el puesto 9 343 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 900 suscriptores.
Según los últimos datos del 25 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 455, y en las últimas 24 horas de 3, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 3.41%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.49% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 1 395 visualizaciones. En el primer día suele acumular 608 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 2.
- Intereses temáticos: El contenido se centra en temas clave como math, harvard, oxford, supervision, waybienad.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“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”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 26 octubre, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
40 900
Suscriptores
+324 horas
+277 días
+45530 días
Archivo de publicaciones
40 900
In Python 3.15, a single asterisk replaces nested loops. 🐍✨
Previously, to flatten a list, you would write:
rows = [[1, 2], [3], [4, 5]]
flat = [x for row in rows for x in row]flat = [*row for row in rows]
# [1, 2, 3, 4, 5]configs = [
{"debug": False, "timeout": 10},
{"timeout": 30},
]
config = {**part for part in configs}
# {'debug': False, 'timeout': 30}SyntaxError. 🚫
https://peps.python.org/pep-0798/
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40 900
Python is the #1 language in AI. 🐍
But you don’t need to learn all of it. (save this) 📌
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40 900
🔥 Free IT & Dev Study Kits – 2026 Prep, No Signup
If you’re prepping for cloud, dev, or AI roles this year, these free kits cover the gaps most people skip — cert basics, hands-on labs, and mock exams. No signup traps, no hidden fees.
📘 Cert E-Book — covers Cisco & AWS fundamentals, good for first-time cert takers
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40 900
😰 15-Hour "Python for Data Science" Course
⚡️ Learn Python for Data Science
40 900
Repost from Machine Learning with Python
https://substack.com/@husseinsheikho?utm_source=share&utm_medium=android&r=3hwnr8
Follow me to more posts and useful content
40 900
Repost from Machine Learning with Python
📚 Download 10 Python books for FREE:
1. Think Python — O’Reilly
https://t.co/X7y3pX68IW
2. The Big Book of Small Python Projects
https://inventwithpython.com/bigbookpython/
3. Data Structures
https://opendatastructures.org/ods-python.pdf
4. Data Science Handbook
https://t.co/9aOLdiAbim
5. Data Analysis
https://wesmckinney.com/book/
6. Data Science
https://t.co/TusyBWGfrx
7. Machine Learning
https://t.co/7veOwESe8q
8. Statistics
https://t.co/waWDQylQpY
9. Think Bayes
https://allendowney.github.io/ThinkBayes2/
10. Clean Code in Python — Packt
https://t.co/OHhVgF1L65
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40 900
Python Lists: A Quick Reference 🐍
* Definition: Lists are ordered, mutable collections that can contain various data types and duplicates.
* Creating Lists: Creating empty, numerical, mixed, nested lists, and lists with duplicates.
* Accessing List Elements: Accessing elements using positive and negative indexing, as well as slicing with
start:end:step. * Common Operations: Adding, inserting, concatenating, deleting, clearing, searching, sorting, and reversing lists. * List Methods:
append(),
insert(),
extend(),
remove(),
pop(),
clear(),
index(),
count(),
sort(), and
reverse(). * List Comprehension: Quickly creating lists using expressions and conditions. * List vs. Tuple: Differences between mutable lists and immutable tuples. * Important Points: Specifics of indexing, slicing, data types, and working with lists. #Python #Coding #Programming #DataStructures #PythonTips #LearnPython ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
40 900
📱 270 tools for Python developers
The repository contains:
🫡 Linters and formatters;
🫡 Type checkers;
🫡 Testing tools;
🫡 Debugging and profiling tools;
🫡 Package managers;
🫡 Logging tools;
🫡 Security tools;
🫡 Documentation and package building tools.
Save this to your favorites, as the list is updated regularly.
⛓️ Link to the repository
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Repost from Udemy Free
Hands On Python Data Science - Data Science Bootcamp
Master Python for Data Science with Real-World Applications: Dive Deep into Data Analysis, Machine Learning
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40 900
Repost from Udemy Free
Python For Beginners Course In-Depth
Python: A Comprehensive Introduction to Fundamental Python Concepts and the Python Advanced Programming Concepts
🏷 Category: IT & Software
🌍 Language: English
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