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Learn Python Coding

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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📈 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 40 657 suscriptores, ocupando la posición 3 225 en la categoría Tecnologías y Aplicaciones y el puesto 9 421 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 657 suscriptores.

Según los últimos datos del 05 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 458, y en las últimas 24 horas de 8, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 5.17%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.92% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 2 100 visualizaciones. En el primer día suele acumular 375 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 5.
  • 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 06 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.

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40 657
Suscriptores
+824 horas
+1297 días
+45830 días
Archivo de publicaciones
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This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
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👩‍💻 heapq.merge(): Combining sorted data! If you have multiple sources of data that are already sorted, you don't need to collect them into a single collection and sort them again. heapq.merge() combines such sources into a single, ordered iterator. In this guide: • We will combine multiple sorted sequences; • We will explore lazy processing of large data sources; • We will configure comparison using the key argument; • We will combine data sorted in reverse order. This is especially useful when working with logs, files, and query results, where each source already provides data in the correct order. #Python #heapq #DataProcessing #CodingTips #Programming #Algorithms ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

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📌 Marking Deprecated Code in Python: deprecated() In large projects, old functions are not always immediately removed. They are often left for compatibility, but it's important to warn developers that they should no longer be used. Previously,
warnings.warn()
was often used for this purpose:
import warnings

def old_api():
    warnings.warn(
        "Use new_api()",
        DeprecationWarning
    )
In Python 3.13, a
deprecated()
decorator has been introduced:
from warnings import deprecated

@deprecated("Use new_api()")
def old_api():
    return "old"
Now, the information about deprecation is part of the API itself. It can be recognized not only during runtime, but also by editors and static analysis tools. This also works for classes:
@deprecated("Use NewClient")
class OldClient:
    pass
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Do not violate the Single Responsibility Principle 🎯 A function should do one thing, and do it well. This function does too much:
def calculate_final_total(
    price: float,
    quantity: int,
    discount_rate: float,
    tax_rate: float
) -> float:
    # Calculate the subtotal
    subtotal = price * quantity

    # Apply the discount
    discounted_amount = subtotal * (1 - discount_rate)

    # Calculate the tax
    final_total = discounted_amount * (1 + tax_rate)

    return final_total
The problem here is that the calculation of the subtotal, discount, and tax are all combined into one function. Any change to one of these steps can affect the entire calculation. It's better to break down the logic into smaller, more specialized functions:
def calculate_subtotal(price: float, quantity: int) -> float:
    return price * quantity

def apply_discount(subtotal: float, discount: float) -> float:
    return subtotal * (1 - discount)

def calculate_tax(amount: float, tax_rate: float) -> float:
    return amount * (1 + tax_rate)
This is much better. ✅ Smaller functions with a single task are easier to test with unit tests because they have fewer dependencies and require less mocking. Furthermore, isolated components are easier to reuse in different parts of the application or pipeline without bringing in unnecessary dependencies. Therefore, keep your functions simple and focused. One function – one responsibility. 📝 #Python #Coding #SoftwareDevelopment #CleanCode #Programming #BestPractices ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

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