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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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📈 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.

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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.

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  • 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.
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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.

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❔ Interview question What tools are used for error monitoring in Python services? Answer: Most often, Sentry, centralized logging, and metrics are used. Sentry collects stack traces, context, and shows the frequency of errors. It's also important to set up alerts - a sharp increase in exceptions usually signals problems after a release or a service degradation. tags: #interview https://t.me/pythonRe ✅

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Exploring pathlib for Working with Paths! Many projects still use 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 #FileSystem

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Why can't you use mutable default values in constructors? If you set a list or dictionary as the default value, the object is
Why can't you use mutable default values in constructors? If you set a list or dictionary as the default value, the object is created once and then reused by all instances.
class 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.

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Python: simple things that improve code If you write like this: if type(x) == str: print("This is a string") it might work, b
Python: simple things that improve code If you write like this:
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.

Python Basics Arrays & Loops 🐍 Essential you need to start strong 💪 https://t.me/pythonRe 🔗
Python Basics Arrays & Loops 🐍 Essential you need to start strong 💪 https://t.me/pythonRe 🔗

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Unlock Your AI Career Join our Data Science Full Stack with AI Course – a real-time, project-based online training designed f
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