Learn Python Coding
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
Mostrar más📈 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 40 879 suscriptores, ocupando la posición 3 292 en la categoría Tecnologías y Aplicaciones y el puesto 9 353 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 879 suscriptores.
Según los últimos datos del 27 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 395, y en las últimas 24 horas de -12, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 3.98%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.48% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 1 628 visualizaciones. En el primer día suele acumular 604 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 28 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.
os.path for path operations: join, dirname, exists, and more. It works, but the code quickly becomes cluttered with string manipulations and harder to read — especially when there are many paths being actively combined.
Since Python 3.4, there's pathlib — an object-oriented API for working with files and directories.
Importing the module is simple:
from pathlib import Path
You can create a path like any regular object:
path = Path("data/users.json")
When working with Path and the / operator, the correct separators for the current OS are used automatically. This keeps the code portable between Linux, macOS, and Windows without extra checks.
If you need an absolute path, use resolve():
print(path.resolve())
Very often when working with files, you need to check if a path exists:
if path.exists():
print("File found")
Pathlib also lets you quickly determine the type of file system object:
path.is_file()
path.is_dir()
The Path object has convenient properties for getting path parts. This eliminates manual string parsing and working with split().
print(path.name) # users.json
print(path.stem) # users
print(path.suffix) # .json
print(path.parent) # data
For joining paths, the / operator is used, which looks noticeably cleaner and is easier to read compared to os.path.join:
base = Path("logs")
file_path = base / "2026" / "app.log"
Creating directories is also compact and convenient:
Path("backup/archive").mkdir(parents=True, exist_ok=True)
Here: parents=True creates nested directories; exist_ok=True doesn't raise an error if the folder already exists.
For reading and writing text files, there are built-in methods that cover most everyday tasks:
config = Path("config.txt")
config.write_text("debug=true", encoding="utf-8")
content = config.read_text(encoding="utf-8")
print(content)
For binary data, read_bytes() and write_bytes() methods are available.
You can iterate through directory contents using iterdir():
for file in Path("logs").iterdir():
print(file)
If you need to search for files by pattern, use glob():
for py_file in Path(".").glob("*.py"):
print(py_file)
And for recursive directory traversal, there's rglob():
for file in Path(".").rglob("*.json"):
print(file)
Practical example — finding logs older than a certain date. This is a more real-world task:
from pathlib import Path
from datetime import datetime
logs = Path("logs")
limit_date = datetime(2026, 1, 1)
for file in logs.glob("*.log"):
modified = datetime.fromtimestamp(file.stat().st_mtime)
if modified < limit_date:
print(file.name, modified)
The stat() method lets you get file metadata: size, modification time, permissions, and other system data.
Deleting files and directories is also built directly into the Path API:
path.unlink() # file
path.rmdir() # empty directory
It's important to note that pathlib doesn't fully replace shutil or os. For example, for copying files, recursive directory deletion, or complex permission operations, additional modules are usually used.
🔥 pathlib makes working with the file system noticeably cleaner: less string operations, better readability, and more predictable code when working with paths and files.
#Python #Pathlib #Programming #Coding #Developer #SoftwareEngineering #TechTips #LearnPython #PythonTips #FileSystemclass User:
def __init__(self, tags=[]):
self.tags = tags
This results in a change in one instance affecting the others:
u1 = User(); u2 = User()
u1.tags.append("x"); print(u2.tags)
default_factory creates a new object each time the constructor is called, eliminating shared state:
field(default_factory=list)
Thus, each instance receives an independent data structure:
User().tags is User().tags
🔥 Using default_factory is an important practice when working with mutable types and prevents hard-to-detect state errors.if type(x) == str:
print("This is a string")
it might work, but it breaks on subclasses of str.
It's better to use isinstance(). It takes into account inheritance and is more consistent with polymorphism.
if isinstance(x, str):
print("This is a string")
This variant will work for str and its subclasses.
Conclusion: type(x) == str is only suitable for simple cases, but it's fragile. isinstance(x, str) is a more stable and correct option almost always.