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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 40 123 suscriptores, ocupando la posición 3 250 en la categoría Tecnologías y Aplicaciones y el puesto 9 587 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 123 suscriptores.

Según los últimos datos del 01 septiembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 146, y en las últimas 24 horas de 9, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 1.86%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.08% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 748 visualizaciones. En el primer día suele acumular 435 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 02 septiembre, 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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+924 horas
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+14630 días
Archivo de publicaciones
Topic: Python List vs Tuple — Differences and Use Cases --- Key Differences • Lists are mutable — you can change, add, or rem
Topic: Python List vs Tuple — Differences and Use Cases --- Key DifferencesLists are mutable — you can change, add, or remove elements. • Tuples are immutable — once created, they cannot be changed. --- Creating Lists and Tuples
my_list = [1, 2, 3]
my_tuple = (1, 2, 3)
--- When to Use Each • Use lists when you need a collection that can change over time. • Use tuples when the collection should remain constant, providing safer and faster data handling. --- Common Tuple Uses • Returning multiple values from a function.
def get_coordinates():
    return (10, 20)

x, y = get_coordinates()
• Using as keys in dictionaries (since tuples are hashable, lists are not). --- Converting Between Lists and Tuples
list_to_tuple = tuple(my_list)
tuple_to_list = list(my_tuple)
--- Performance Considerations • Tuples are slightly faster than lists due to immutability. --- SummaryLists: mutable, dynamic collections. • Tuples: immutable, fixed collections. • Choose based on whether data should change or stay constant. --- \#Python #Lists #Tuples #DataStructures #ProgrammingTips https://t.me/DataScience4

Topic: Python Exception Handling — Managing Errors Gracefully --- Why Handle Exceptions? • To prevent your program from crash
Topic: Python Exception Handling — Managing Errors Gracefully --- Why Handle Exceptions? • To prevent your program from crashing unexpectedly. • To provide meaningful error messages or recovery actions. --- Basic Try-Except Block
try:
    result = 10 / 0
except ZeroDivisionError:
    print("Cannot divide by zero!")
--- Catching Multiple Exceptions
try:
    x = int(input("Enter a number: "))
    result = 10 / x
except (ValueError, ZeroDivisionError) as e:
    print(f"Error occurred: {e}")
--- Using Else and Finallyelse block runs if no exceptions occur. • finally block always runs, used for cleanup.
try:
    file = open("data.txt", "r")
    data = file.read()
except FileNotFoundError:
    print("File not found.")
else:
    print("File read successfully.")
finally:
    file.close()
--- Raising Exceptions • You can raise exceptions manually using raise.
def check_age(age):
    if age < 0:
        raise ValueError("Age cannot be negative.")

check_age(-1)
--- Custom Exceptions • Create your own exception classes by inheriting from Exception.
class MyError(Exception):
    pass

def do_something():
    raise MyError("Something went wrong!")

try:
    do_something()
except MyError as e:
    print(e)
--- Summary • Use try-except to catch and handle errors. • Use else and finally for additional control. • Raise exceptions to signal errors. • Define custom exceptions for specific needs. --- #Python #ExceptionHandling #Errors #Debugging #ProgrammingTips

Topic: Python Classes and Objects — Basics of Object-Oriented Programming Python supports object-oriented programming (OOP), allowing you to model real-world entities using classes and objects. --- Defining a Class
class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    def greet(self):
        print(f"Hello, my name is {self.name} and I am {self.age} years old.")
--- Creating Objects
person1 = Person("Alice", 30)
person1.greet()  # Output: Hello, my name is Alice and I am 30 years old.
--- Key ConceptsClass: Blueprint for creating objects. • Object: Instance of a class. • `__init__` method: Constructor that initializes object attributes. • `self` parameter: Refers to the current object instance. --- Adding Methods
class Circle:
    def __init__(self, radius):
        self.radius = radius

    def area(self):
        return 3.1416 * self.radius ** 2

circle = Circle(5)
print(circle.area())  # Output: 78.54
--- **Inheritance** • Allows a class to inherit attributes and methods from another class.
class Animal:
    def speak(self):
        print("Animal speaks")

class Dog(Animal):
    def speak(self):
        print("Woof!")

dog = Dog()
dog.speak()  # Output: Woof!
--- Summary • Classes and objects are core to Python OOP. • Use `class` keyword to define classes. • Initialize attributes with `__init__` method. • Objects are instances of classes. • Inheritance enables code reuse and polymorphism. --- #Python #OOP #Classes #Objects #ProgrammingConcepts

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🔰 Convert Images to PDF using Python
🔰 Convert Images to PDF using Python

This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
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_rRW2scgfRhOTc0https://t.me/Codeprogrammer

Important Python Functions
Important Python Functions

🐍 Tip of the day for experienced Python developers 📌 Use decorators with parameters — a powerful technique for logging, control, caching, and custom checks. Example: a logger that can set the logging level with an argument:

import functools
import logging

def log(level=logging.INFO):
   def decorator(func):
       @functools.wraps(func)
       def wrapper(*args, **kwargs):
           logging.log(level, f"Call {func.__name__} with args={args}, kwargs={kwargs}")
           return func(*args, **kwargs)
       return wrapper
   return decorator

@log(logging. DEBUG)
def compute(x, y):
   return x + y
✅ Why you need it: The decorator is flexibly adjustable; Suitable for prod tracing and debugging in maiden; Retains the signature and docstring thanks to @functools.wraps. ⚠️ Tip: avoid nesting >2 levels and always write tests for decorator behavior. Python gives you tools that look like magic, but work stably if you know how to use them.

8. Set up the user interface and trigger the main function. • Provides an input field for the user's question • Triggers the
8. Set up the user interface and trigger the main function. • Provides an input field for the user's question • Triggers the main function when the user clicks "Get Answer"

7. Define the main function to run all LLMs and aggregate results. • Runs all reference models asynchronously • Displays indi
7. Define the main function to run all LLMs and aggregate results. • Runs all reference models asynchronously • Displays individual responses in expandable sections • Aggregates responses using the aggregator model • Streams the aggregated response.

6. Implement the LLM call function. • Asynchronously calls the LLM with the user's prompt • Returns the model name and its re
6. Implement the LLM call function. • Asynchronously calls the LLM with the user's prompt • Returns the model name and its response

5. Define the models and aggregator system prompt. • Specifies the LLMs to be used for generating responses • Defines the agg
5. Define the models and aggregator system prompt. • Specifies the LLMs to be used for generating responses • Defines the aggregator model and its system prompt

4. Initialize Together AI clients. • Sets up Together API key as an environment variable • Initializes both synchronous and a
4. Initialize Together AI clients. • Sets up Together API key as an environment variable • Initializes both synchronous and asynchronous Together clients

3. Set up the Streamlit app and API key input. • Creates a title for the app • Adds a secure input field for the Together API
3. Set up the Streamlit app and API key input. • Creates a title for the app • Adds a secure input field for the Together API key

2. Import necessary libraries • Streamlit for the web interface • asyncio for asynchronous operations • Together AI for LLM i
2. Import necessary libraries • Streamlit for the web interface • asyncio for asynchronous operations • Together AI for LLM interactions

1. Install the necessary Python Libraries Run the following commands from your terminal to install the required libraries:
1. Install the necessary Python Libraries Run the following commands from your terminal to install the required libraries: