Python的海象運算符（:=）通過在表達式中賦值提升代碼簡潔性與效率，主要應用於避免循環(huán)和條件判斷中的冗餘計算。 1. 在循環(huán)中讀取輸入時，可直接在while條件中賦值，減少重複調(diào)用input()；2. 在條件判斷中計算並複用值，如檢查數(shù)據(jù)長度時僅計算一次len(data)；3. 在列表推導中使用但需謹慎，雖可實現(xiàn)過濾並保留計算結(jié)果，但可能降低可讀性。適用場景包括避免重複計算、簡化初始化邏輯及編寫簡潔腳本，但不應犧牲代碼清晰度，尤其在共享或舊代碼中應避免濫用。

Python's assignment expressions, introduced in Python 3.8 via PEP 572 , are commonly referred to as the walrus operator ( := ). They allow you to assign values to variables within an expression — something that wasn't possible before without splitting the logic into multiple lines.

This might seem like a small change, but it can make your code cleaner and more efficient in specific cases.

Simplifying Loops and Conditionals

One of the most common use cases for the walrus operator is reducing redundancy in loops and conditionals where you need to both compute and use a value.

For example, imagine you're reading lines from input until you hit one that meets a certain condition:

 while (line := input()) != 'quit':
    print(f"You entered: {line}")

Before this, you'd have to write:

 line = input()
while line != 'quit':
    print(f"You entered: {line}")
    line = input()

You avoid repeating input() outside and inside the loop. That's not just fewer lines — it reduces the chance of bugs if you forget to update one of the calls.

Avoiding Redundant Computations

If you're doing a computation that's expensive or has side effects, and you need the result in a conditional check and later in the body, using := helps keep your code clean and efficient.

Say you're checking the length of some processed data:

 if (n := len(data)) > 10:
    print(f"Data is too long ({n} items)")

Without the walrus operator, you'd typically calculate len(data) twice or split it into two lines:

 n = len(data)
if n > 10:
    print(f"Data is too long ({n} items)")

Again, it's about keeping things concise without sacrificing clarity — especially useful in list comprehensions or generator expressions.

Use in List Comprehensions (With Caution)

Assignment expressions can be used inside list comprehensions, which opens up some interesting possibilities — though it's worth being cautious here because overuse can hurt readability.

Here's a somewhat practical example: filtering based on a computed value, then using that value in the output:

 values = [y for x in data if (y := f(x)) > 0]

In this case, f(x) is only called once per element, and we use its result both for filtering and constructing the new list.

That said, many people find this less readable than the alternative:

 values = []
for x in data:
    y = f(x)
    if y > 0:
        values.append(y)

So while it's possible, consider whether clarity is preserved before using walrus in comprehensions.

Idiomatic Uses (and When Not To Use It)

The walrus operator shines when:

• You want to avoid repeated computations.
• You're working with conditions or loops where initializing a variable beforehand feels clunky.
• You're writing concise scripts or handling input/output efficiently.

But don't reach for it just because you can. Some good times not to use it include:

• When it makes the code harder to read at a glance.
• In simple assignments where breaking it out improves clarity.
• In shared or legacy codebases where not everyone is familiar with Python 3.8 features.

It's a tool, not a rule — use it where it adds real value.

基本上就這些。 Walrus operator 是個實用的小功能，但用得好才顯得專業(yè)。

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