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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 40 101 suscriptores, ocupando la posición 3 241 en la categoría Tecnologías y Aplicaciones y el puesto 9 590 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 101 suscriptores.

Según los últimos datos del 29 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 114, 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 2.75%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.09% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 1 103 visualizaciones. En el primer día suele acumular 438 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 30 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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ptpython | Python Tools ✨ 📖 An enhanced interactive REPL for Python. 🏷️ #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

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How to Build the Python Skills That Get You Hired ✨ 📖 Build a focused learning plan that helps you identify essential Python skills, assess your strengths, and practice effectively to progress. 🏷️ #basics #career

# Less readable
items = ["a", "b", "c"]
for item in items[::-1]:
    print(item)

# More readable 👍
for item in reversed(items):
    print(item)
--- 🔟. Use continue to Skip the Rest of an Iteration The continue keyword ends the current iteration and moves to the next one. It's great for skipping items that don't meet a condition, reducing nested if statements.
# Using 'if'
for i in range(10):
    if i % 2 == 0:
        print(i, "is even")

# Using 'continue' can be cleaner
for i in range(10):
    if i % 2 != 0:
        continue  # Skip odd numbers
    print(i, "is even")
━━━━━━━━━━━━━━━ By: @DataScience4

🔰 For Loop In Python (10 Best Tips & Tricks) Here are 10 tips to help you write cleaner, more efficient, and more "Pythonic" for loops. --- 1️⃣. Use enumerate() for Index and Value Instead of using range(len(sequence)) to get an index, enumerate gives you both the index and the item elegantly.
# Less Pythonic 👎
items = ["a", "b", "c"]
for i in range(len(items)):
    print(i, items[i])

# More Pythonic 👍
for i, item in enumerate(items):
    print(i, item)
--- 2️⃣. Use zip() to Iterate Over Multiple Lists To loop through two or more lists at the same time, zip() is the perfect tool. It stops when the shortest list runs out.
names = ["Alice", "Bob", "Charlie"]
ages = [25, 30, 35]

for name, age in zip(names, ages):
    print(f"{name} is {age} years old.")
--- 3️⃣. Iterate Directly Over Dictionaries with .items() To get both the key and value from a dictionary, use the .items() method. It's much cleaner than accessing the key and then looking up the value.
# Less Pythonic 👎
config = {"host": "localhost", "port": 8080}
for key in config:
    print(key, "->", config[key])

# More Pythonic 👍
for key, value in config.items():
    print(key, "->", value)
--- 4️⃣. Use List Comprehensions for Simple Loops If your for loop just creates a new list, a list comprehension is almost always a better choice. It's more concise and often faster.
# Standard for loop
squares = []
for i in range(5):
    squares.append(i * i)
# squares -> [0, 1, 4, 9, 16]

# List comprehension 👍
squares_comp = [i * i for i in range(5)]
# squares_comp -> [0, 1, 4, 9, 16]
--- 5️⃣. Use the _ Underscore for Unused Variables If you need to loop a certain number of times but don't care about the loop variable, use _ as a placeholder by convention.
# I don't need 'i', I just want to repeat 3 times
for _ in range(3):
    print("Hello!")
--- 6️⃣. Unpack Tuples Directly in the Loop If you're iterating over a list of tuples or lists, you can unpack the values directly into named variables for better readability.
points = [(1, 2), (3, 4), (5, 6)]

# Unpacking directly into x and y
for x, y in points:
    print(f"x: {x}, y: {y}")
--- 7️⃣. Use break and a for-else Block A for loop can have an else block that runs only if the loop completes without hitting a break. This is perfect for search operations.
numbers = [1, 3, 5, 7, 9]

for num in numbers:
    if num % 2 == 0:
        print("Even number found!")
        break
else:  # This runs only if the 'break' was never hit
    print("No even numbers in the list.")
--- 8️⃣. Iterate Over a Copy to Safely Modify Never modify a list while you are iterating over it directly. This can lead to skipped items. Instead, iterate over a copy.
# This will not work correctly! 👎
numbers = [1, 2, 3, 2, 4]
for num in numbers:
    if num == 2:
        numbers.remove(num) # Skips the second '2'

# Correct way: iterate over a slice copy [:] 👍
numbers = [1, 2, 3, 2, 4]
for num in numbers[:]:
    if num == 2:
        numbers.remove(num)
print(numbers) # [1, 3, 4]
--- 9️⃣. Use reversed() for Reverse Iteration To loop over a sequence in reverse, use the built-in reversed() function. It's more readable and efficient than creating a reversed slice.

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MkDocs | Python Tools ✨ 📖 A static site generator for Python projects. 🏷️ #Python

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✨ Lazy Imports Land in Python and Other Python News for December 2025 ✨ 📖 PEP 810 brings lazy imports to Python 3.15, PyPI t
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Of course! Here is another post in the same style, formatted for a platform like Telegram that uses Markdown. ✖️ MODIFYING A LIST WHILE LOOPING OVER IT SKIPS ITEMS. Because of this, Python's iterator gets confused. When you remove an element, the next element shifts into its place, but the loop moves on to the next index, causing the shifted element to be skipped entirely. The code looks logical, but the result is buggy — a classic iteration trap. Correct — iterate over a copy* of the list, or build a new list. Follow for more Python tips daily!
# hidden error — removing items while iterating skips elements
numbers = [1, 2, 3, 2, 4, 2, 5]

for num in numbers:
    if num == 2:
        numbers.remove(num) # seems like it should remove all 2s

# a '2' was skipped and remains in the list!
print(numbers)  # [1, 3, 4, 2, 5]
# ✅ correct version — iterate over a copy
numbers_fixed = [1, 2, 3, 2, 4, 2, 5]

# The [:] makes a crucial copy!
for num in numbers_fixed[:]:
    if num == 2:
        numbers_fixed.remove(num)

print(numbers_fixed)  # [1, 3, 4, 5]

# A more Pythonic way is to use a list comprehension:
# [n for n in numbers if n != 2]
━━━━━━━━━━━━━━━ By: @DataScience4

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import pathlib
import shutil

# --- Setup: Create a temporary directory and files for the demo ---
# We use a relative path './temp_docs' so it works anywhere
docs_dir = pathlib.Path("temp_docs")
if docs_dir.exists():
    shutil.rmtree(docs_dir) # Clean up from previous runs
docs_dir.mkdir()

# Create dummy files
(docs_dir / "report.txt").write_text("This is a test report.")
(docs_dir / "notes.txt").write_text("Some important notes.")
# ----------------------------------------------------------------

# 1. Create a Path object for our report file
file_path = docs_dir / "report.txt"

# 2. Inspect Path Components
print(f"File Name: {file_path.name}")
print(f"Parent Directory: {file_path.parent}")
print(f"File Stem: {file_path.stem}")
print(f"File Suffix: {file_path.suffix}")

# 3. Check Path Properties
print(f"Exists: {file_path.exists()}")
print(f"Is File: {file_path.is_file()}")
print(f"Is Directory: {file_path.is_dir()}")

# 4. Manipulate Paths and prepare for renaming/moving
archive_dir = docs_dir / "archive"
archive_dir.mkdir() # Create the 'archive' subdirectory
new_file_path = archive_dir / "old_report.txt"
print(f"New Path: {new_file_path}")

# To demonstrate renaming, let's rename the original file
file_path.rename(new_file_path)

# 5. Iterate over the original directory to find files
for found_file in sorted(docs_dir.glob("*.txt")):
    print(f"Found File: {found_file.name}")

# 6. Demonstrate a copy operation
# `pathlib` itself doesn't have a copy method, but works perfectly with `shutil`
source_file = docs_dir / "notes.txt"
destination_file = archive_dir / "notes_backup.txt"
shutil.copy(source_file, destination_file)
print("File copied successfully!")


# --- Cleanup: Remove the temporary directory ---
shutil.rmtree(docs_dir)
# -----------------------------------------------
This self-contained script first sets up a realistic file structure, then demonstrates the power and simplicity of pathlib to inspect, manipulate, and manage files and directories, cleaning up after itself when it's done. ━━━━━━━━━━━━━━━ By: @DataScience4

🔰 Master File Paths with pathlib in Python The pathlib module, introduced in Python 3.4, provides an object-oriented interface for working with filesystem paths. It makes your code cleaner, more readable, and platform-independent, saving you from the complexities of string manipulation that come with older modules like os.path. --- #### Why Use pathlib?Object-Oriented: Paths are objects with methods, not just strings. • Intuitive Operators: Use the / operator to join paths naturally. • Platform Agnostic: Automatically handles differences between Windows (\) and Unix-like (/) path separators. • Cleaner Code: Methods like .exists(), .is_file(), and .read_text() simplify common operations. --- 1. Creating a Path Object The first step is to import the Path class and create an object representing a path on your filesystem.
from pathlib import Path

# Create a Path object
# This path might not exist yet, it's just an object representing it.
p = Path('/home/user/documents/report.txt')
2. Accessing Path Components Once you have a Path object, you can easily inspect its various parts without any string splitting.
# Get the full file name including the extension
print(f"File Name: {p.name}")

# Get the parent directory
print(f"Parent Directory: {p.parent}")

# Get the file name without the extension
print(f"File Stem: {p.stem}")

# Get the file extension
print(f"File Suffix: {p.suffix}")
3. Checking Path Properties pathlib makes it trivial to check the status of a path.
# Check if the path exists on the filesystem
print(f"Exists: {p.exists()}")

# Check if it's a file
print(f"Is File: {p.is_file()}")

# Check if it's a directory
print(f"Is Directory: {p.is_dir()}")
4. Manipulating Paths Modifying paths is clean and intuitive. The / operator is used to join path components, and methods like .rename() handle file operations.
# Join paths using the '/' operator
new_dir = p.parent / 'archive'

# Create a new path by renaming the file
new_path = new_dir / 'old_report.txt'

print(f"New Path: {new_path}")

# To actually rename the file on the filesystem:
# p.rename(new_path)
5. Working with Directories pathlib provides simple methods for creating and iterating over directories.
# Create a directory (and any necessary parent directories)
# exist_ok=True prevents an error if the directory already exists
archive_dir = Path('/home/user/documents/archive')
archive_dir.mkdir(parents=True, exist_ok=True)

# Find all .txt files in a directory
docs_dir = Path('/home/user/documents')
for file in docs_dir.glob('*.txt'):
    print(f"Found File: {file.name}")
--- Putting It All Together: A Complete Example This script will perform all the operations discussed and generate the exact output shown in the prompt. For this to be a runnable example, it first creates a temporary directory structure and files.

import qrcode

# Data to be encoded
custom_data = "This is a custom QR code made with Python!"

# Instantiate the QRCode class with custom parameters
qr = qrcode.QRCode(
    version=1,
    error_correction=qrcode.constants.ERROR_CORRECT_H, # High error correction
    box_size=15,
    border=5,
)

# Add the data to the QR code instance
qr.add_data(custom_data)
qr.make(fit=True)

# Create the image with custom colors
# fill_color is the color of the QR code blocks
# back_color is the background color
img_custom = qr.make_image(fill_color="darkblue", back_color="white")

# Save the custom image
img_custom.save("custom_python_qr.png")

print("Customized QR code generated successfully and saved as 'custom_python_qr.png'")
In this example: • We create a QRCode object with specific settings for version, error_correction, box_size, and border. • We use qr.add_data() to add our content. • qr.make(fit=True) finalizes the QR code structure. • qr.make_image() generates the actual image object, where we can specify the colors. • Finally, we save the resulting image. --- Conclusion You now have the tools to generate QR codes effortlessly using Python. You've learned how to create a quick, standard QR code with qrcode.make() and how to build a fully customized one using the QRCode class to control everything from size and durability to color. #### What's Next?Integrate into Applications: Add QR code generation to a web application (e.g., a Flask or Django app) to create user-specific codes. • Generate Different Content: Encode Wi-Fi network details, contact information (vCards), or calendar events. • Dynamic Generation: Build a script that takes user input to generate QR codes on the fly. ━━━━━━━━━━━━━━━ By: @DataScience4