Hello, checkiomates🐱‍👤!

This week, we explore the new features in Python 3.15, dive into NumPy's pursuit of type completeness for better data science, and consider the philosophy that practical testing outweighs abstract Data Structures and Algorithms knowledge. Our mission challenges you to tackle a core science concept: generating the Noble Gas Notation for electron configurations.

💡TIP

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🏁 MISSION

Noble Gas Notation by freeman_lex -

Electron configuration is a standardized notational method for describing the arrangement of electrons in an atom's orbitals. The task requires a specific shorthand form known as Noble Gas Notation. This notation provides a condensed representation by using the symbol of the previous noble gas element (if existed) in brackets as a stand-in for the core. The remaining electrons are then listed in the standard configuration format.

notation("H") == "1s1"
notation("He") == "1s2"
notation("Al") == "[Ne] 3s2 3p1"

📖 ARTICLES

What’s new in Python 3.15 -

This article explains the new features in Python 3.15, compared to 3.14.

Bringing NumPy's type-completeness score to nearly 90% -

Because NumPy is one of the most downloaded packages in the Python ecosystem, any incremental improvement can have a large impact on the data science ecosystem. In particular, improvements related to static typing can improve developer experience and help downstream libraries write safer code. We'll tell the story about how we (Quansight Labs, with support from Meta's Pyrefly team) helped bring its type-completeness score to nearly 90% from an initial 33%.

Testing is better than DSA -

Ned Batchelder: People should spend less time learning DSA, more time learning testing.

👩‍💻CODE SHOT

What do you think the following code does?

def checkio(b: int, s: int, c: int) -> str:
    p = b + 2*s + 3*c
    return "NBSC"[(p >= 100) + (p >= 120) + (p >= 150)]

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