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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πŸ”° Comprehensions in python with example
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🧐 Python Cheatsheet - A handy reference guide!

A compact reference that gathers the main constructs of the language in one place. On the page, you can quickly find information about strings, lists, dictionaries, functions, classes, exceptions, regular expressions, and built-in functions.

πŸ“Œ Here's the link: https://labex.io/pythoncheatsheet/
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🐱 Awesome Python Typing β€” Everything for Learning Typing in Python! 🐍✨

If you want to understand type annotations in Python, this repository is definitely worth saving. It contains the best articles, books, tools, libraries, and other materials dedicated to typing and its use in real-world projects. πŸ’»πŸ“š

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https://github.com/typeddjango/awesome-python-typing

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Python allows you to create enumerations that are also regular strings!

Previously, when working with APIs, JSON, and configurations, it was often necessary to manually extract the value from an Enum.

For example:
class Status(Enum):
ACTIVE = "active"

When serializing, you would get an enumeration object:
Status.ACTIVE

rather than a regular string:
"active"

In Python 3.11, StrEnum was introduced to solve this problem.
from enum import StrEnum

class Status(StrEnum):
ACTIVE = "active"
BLOCKED = "blocked"

Now, the value can be used wherever a string is expected:
json.dumps({"status": Status.ACTIVE})

The result:
{"status": "active"}

At the same time, the advantages of enumerations are preserved:
Status.ACTIVE
Status.BLOCKED

You cannot accidentally pass an incorrect value:
Status("unknown")

will result in an error.

πŸ”₯ StrEnum allows you to combine the strict typing of enumerations with the convenience of regular strings, without manual conversion when working with APIs, JSON, and configurations.

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