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
Больше📈 Аналитический обзор Telegram-канала Learn Python Coding
Канал Learn Python Coding (@pythonre) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 40 879 подписчиков, занимая 3 292 место в категории Технологии и приложения и 9 353 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 40 879 подписчиков.
Согласно последним данным от 27 октября, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 395, а за последние 24 часа — -12, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 3.98%. В первые 24 часа после публикации контент обычно набирает 1.48% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 1 628 просмотров. В течение первых суток публикация набирает 604 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 2.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как math, harvard, oxford, supervision, waybienad.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“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”
Благодаря высокой частоте обновлений (последние данные получены 28 октября, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Технологии и приложения.
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.