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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 40 051 suscriptores, ocupando la posición 3 241 en la categoría Tecnologías y Aplicaciones y el puesto 9 624 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 051 suscriptores.

Según los últimos datos del 28 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 145, 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 3.02%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.11% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 1 211 visualizaciones. En el primer día suele acumular 444 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 29 agosto, 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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Working with f-strings: more possibilities than it seems! f-strings often replace .format() in everyday code, but their capabilities are not always fully utilized. They support formatting, function calls, working with data structures, and convenient debugging (from 3.8+). f-strings are convenient for aligning columns without additional tools. This makes the output readable in the CLI and logs:
rows = [
    ("id", "name", "role"),
    (1, "Ivan", "admin"),
    (2, "Olga", "editor"),
]

for r in rows:
    print(f"{r[0]:<5} {r[1]:<10} {r[2]:<10}")
Debug expressions (Python 3.8+): {x=> displays the name and value of the variable, which speeds up debugging. Supports formatting of calculations:
x = 12
y = 7
print(f"{x=} {y=} {x*y=} x/y={x/y:.3f}")
Specifiers !r, !a: !r - repr(), !a - ascii() for unambiguous logs. Eliminates ambiguities in the output of objects:
path = "/var/data/config.yaml"
print(f"{path!r} {path!a}")  # repr and ascii()
Specifiers support width and padding, for example 08d for zeros. This is convenient for reports and IDs:
n = 42
print(f"{n:08d}")  # → #00000042
You can access dictionaries and immediately calculate metrics, for example len():
data = {"user": "Ivan", "items": [1, 2, 3]}
print(f"{data['user&#39]}=», items={data['items&#39]}")
print(f"len(data['items&#39])={len(data['items&#39])}")
🔥 f-strings are a cool tool for formatting, logging, and debugging, if you apply them taking into account the version of Python and the context of the output. 🚪 @DataScience4

🙏💸 500$ FOR THE FIRST 500 WHO JOIN THE CHANNEL! 🙏💸 Join our channel today for free! Tomorrow it will cost 500$! https://t
🙏💸 500$ FOR THE FIRST 500 WHO JOIN THE CHANNEL! 🙏💸 Join our channel today for free! Tomorrow it will cost 500$! https://t.me/+0-w7MQwkOs02MmJi You can join at this link! 👆👇 https://t.me/+0-w7MQwkOs02MmJi

✨ Quiz: How to Integrate Local LLMs With Ollama and Python ✨ 📖 Check your understanding of using Ollama with Python to run l
Quiz: How to Integrate Local LLMs With Ollama and Python ✨ 📖 Check your understanding of using Ollama with Python to run local LLMs, generate text, chat, and call tools for private, offline apps. 🏷️ #intermediate #ai #tools

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unpacking | Python Glossary ✨ 📖 Passing multiple values at once by expanding an iterable. 🏷️ #Python

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Repost from ADMINOTEKA
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Anaconda Navigator | Python Tools ✨ 📖 A desktop graphical interface included with the Anaconda Distribution. 🏷️ #Python

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✨ Quiz: How to Integrate ChatGPT's API With Python Projects ✨ 📖 Test your knowledge of the ChatGPT API in Python. Practice s
Quiz: How to Integrate ChatGPT's API With Python Projects ✨ 📖 Test your knowledge of the ChatGPT API in Python. Practice sending prompts with openai and handling text and code responses in this quick quiz. 🏷️ #intermediate #ai #api

local variable | Python Glossary ✨ 📖 A variable that you bind inside a function or method body. 🏷️ #Python

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introspection | Python Glossary ✨ 📖 The ability of a program to examine the type or properties of an object at runtime. 🏷️ #Python

✨ How to Integrate Local LLMs With Ollama and Python ✨ 📖 Learn how to integrate your Python projects with local models (LLMs
How to Integrate Local LLMs With Ollama and Python ✨ 📖 Learn how to integrate your Python projects with local models (LLMs) using Ollama for enhanced privacy and cost efficiency. 🏷️ #intermediate #ai #tools

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🔥 Generating fake data in Python — no pain at all If you're testing forms, mockups, or just want to play with data, there's
🔥 Generating fake data in Python — no pain at all If you're testing forms, mockups, or just want to play with data, there's Mimesis — a generator of fake data. Names, emails, addresses, and phone numbers. There's a location setting that allows you to select a country, and the data will be generated accordingly. 📦 Installation:
from typing import Dict
from mimesis.enums import Gender
from mimesis import Person

def generate_fake_user(locale: str = "es", gender: Gender = Gender.MALE) -> Dict[str, str]:
    """
    Generates fake user data based on the locale and gender.

    :param locale: The locale (for example, 'ru', 'en', 'es')
    :param gender: The gender (Gender.MALE or Gender.FEMALE)
    :return: A dictionary with the fake user data
    """
    person = Person(locale)

    user_data = {
        "name": person.full_name(gender=gender),
        "height": person.height(),
        "phone": person.telephone(),
        "occupation": person.occupation(),
    }

    return user_data

if __name__ == "__main__":
    fake_user = generate_fake_user(locale="es", gender=Gender.MALE)
    print(fake_user)
📌 Result:
{
  'name': 'Carlos Herrera',
  'height': '1.84',
  'phone': '912 475 289',
  'occupation': 'Arquitecto'
)
⚡️ Mimesis can: 🖱 Generate names, addresses, phone numbers, professions, etc.  🖱 Work with different countries (🇷🇺 ru, 🇺🇸 en, 🇪🇸 es, etc.)  🖱 Suitable for tests, fake accounts, demo data in projects, and bots. ⚙️ GitHub/Instructions Save it, it'll come in handy 👍 #python #github #interview

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😰 A repository of more than 100+ ready-made Python scripts that solve a bunch of tasks - without reinventing the wheel and s
😰 A repository of more than 100+ ready-made Python scripts that solve a bunch of tasks - without reinventing the wheel and suffering at night. 💬 parsing and searching on the internet; 💬 working with photos and videos; 💬 keyloggers and password managers; 💬 cloning websites; 💬 automating routines; 💬 and dozens of other useful things for real cases. 🔥 Ready-made practice + code, suitable for both learning and work. ⬇️ Save it, it will definitely come in handy! #python #soft #github

global variable | Python Glossary ✨ 📖 A variable defined at the top level of a module. 🏷️ #Python