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لا تقع ضحية للمخادعين! تيليمتريو يكتشف ويُميّز هذه القنوات 👉 إذا كنت تريد رؤية العلامة، اشترك

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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✨ wildcard import | Python Glossary ✨ 📖 An import uses the star syntax to pull many names into your current namespace at once. 🏷️ #Python

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✨ transitive dependency | Python Glossary ✨ 📖 An indirect requirement of your project. 🏷️ #Python

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This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
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✨ relative import | Python Glossary ✨ 📖 Import modules from the same package or parent packages using leading dots. 🏷️ #Python

Python Clean Code: Stop Writing Bad Code — Lessons from Uncle Bob Are you tired of writing messy and unorganized code that le
Python Clean Code: Stop Writing Bad Code — Lessons from Uncle Bob Are you tired of writing messy and unorganized code that leads to frustration and bugs? You can transform your code from a confusing mess into something crystal clear with a few simple changes. In this article, we'll explore key principles from the book "Clean Code" by Robert C. Martin, also known as Uncle Bob, and apply them to Python. Whether you're a web developer, software engineer, data analyst, or data scientist, these principles will help you write clean, readable, and maintainable Python code. Read: https://habr.com/en/articles/841820/ https://t.me/CodeProgrammer 🧠

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Working with f-strings: more possibilities than it seems! f-strings often replace .format() in everyday code, but their capabilities are not always fully utilized. They support formatting, function calls, working with data structures, and convenient debugging (from 3.8+). f-strings are convenient for aligning columns without additional tools. This makes the output readable in the CLI and logs:
rows = [
    ("id", "name", "role"),
    (1, "Ivan", "admin"),
    (2, "Olga", "editor"),
]

for r in rows:
    print(f"{r[0]:<5} {r[1]:<10} {r[2]:<10}")
Debug expressions (Python 3.8+): {x=> displays the name and value of the variable, which speeds up debugging. Supports formatting of calculations:
x = 12
y = 7
print(f"{x=} {y=} {x*y=} x/y={x/y:.3f}")
Specifiers !r, !a: !r - repr(), !a - ascii() for unambiguous logs. Eliminates ambiguities in the output of objects:
path = "/var/data/config.yaml"
print(f"{path!r} {path!a}")  # repr and ascii()
Specifiers support width and padding, for example 08d for zeros. This is convenient for reports and IDs:
n = 42
print(f"{n:08d}")  # → #00000042
You can access dictionaries and immediately calculate metrics, for example len():
data = {"user": "Ivan", "items": [1, 2, 3]}
print(f"{data['user&#39]}=», items={data['items&#39]}")
print(f"len(data['items&#39])={len(data['items&#39])}")
🔥 f-strings are a cool tool for formatting, logging, and debugging, if you apply them taking into account the version of Python and the context of the output. 🚪 @DataScience4

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✨ unpacking | Python Glossary ✨ 📖 Passing multiple values at once by expanding an iterable. 🏷️ #Python

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✨ Anaconda Navigator | Python Tools ✨ 📖 A desktop graphical interface included with the Anaconda Distribution. 🏷️ #Python

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