Python operator3/22/2023 ![]() Print(oups()) # AttributeError: 'bool' object has no attribute 'group' If match := re.match(r"^.*(thing).*", text) and flag: Print(line) # TypeError: 'closing' object is not iterableĪnother issue you might run into is the relative precedence of :=, which is lower than that of logical operators: This oftentimes doesn't really matter because context._enter_() usually returns self, but in case it doesn't it will create very hard to debug issues.įor a more practical example see below what happens when you use walrus operator with closing context manager: , the context is bound to the return value of context._enter_(), while if you use the version with :=, then it's bound to the result of ContextManager() itself. When using the normal syntax with ContextManager() as context. Print(all(number 10 for number in numbers) # True Print(any(number > 10 for number in numbers)) # True What if you however want to also capture the value that caused any() to return True (so-called "witness") or the value that caused all() to fail (so-called "counterexample")? You can use Python's any() and all() functions to verify whether any or all values in some iterable satisfy certain condition. Notice also that the walrus expressions have to be surrounded by parentheses for f-string to interpret it correctly. In this case we also use it in conjunction with what looks like a "reverse walrus" operator - this really is just = which forces the expression to be printed along its value, plus the : used for formatting the expression. Similarly, in the second example, we declare theta variable, which is then reused to compute sin(theta) and cos(theta). In the first print statement above, we use := to define variable today which is then reused on the same line saving us a repeated call to datetime.today(). One of the most common use cases for walrus operator is reducing nested conditionals, such as when using RegEx matching: You could avoid using walrus operator while keeping the performance by changing it to full for loop, but that would require 5 lines of code. The code length is same, both lines are equally readable, but the second one is twice as efficient. Instead - using walrus operator - we compute it once in the if statement and then reuse it. In the first line, func(x) is called twice in every loop. Consider the following list comprehensions with the same expensive func(): If you're not convinced by the above, I have another one. You might say, "I can just add y = func(x) before the list declaration and I don't need the walrus!", you can, but that's one extra, unnecessary line of code and at first glance - without knowing that func(x) is super slow - it might not be clear why the extra y variable needs to exist. When rewritten using walrus operator, func() is invoked only once, assigning its result to y and reusing it for remaining 2 list values. In the first list declaration above, the func(x) is called 3 times, everytime returning same result, which wastes time and compute resources. # Reuse result of "func" without splitting the code into multiple lines It takes a long time to compute results, so we don't want to call it many times: Let's imagine a function called func() that performs some very expensive computations. In case you're not yet familiar with the :=, let's first review some of the basic use cases that might persuade you to give this Python feature a shot.įirst example I want to show you is how you can use walrus operator to reduce number of function invocations. In this article I will try to convince you that the walrus operator really is a good addition to the language and that if you use it properly, then it can help you make your code more concise and readable. Then something like this will work, and now, for instances of Foo only, the ^ symbol will mean exponentiation.The assignment operator - or walrus operator as we all know it - is a feature that's been in Python for a while now (since 3.8), yet it's still somewhat controversial and many people have unfounded hate for it. You could do that this way, just as one example: class Foo(float): For example, in some languages the ^ symbol means exponentiation. One neat thing about Python is that you can override this behavior in a class of your own. TypeError: unsupported operand type(s) for ^: 'float' and 'int' TypeError Traceback (most recent call last) ![]() For integers, it is the common XOR operation, but for example there is not a built-in definition of the function for type float with type int: In : 3 ^ 4 Whatever data types are placed to the right and left of the symbol must implement this function in a compatible way. Generally speaking, the symbol ^ is an infix version of the _xor_ or _rxor_ methods.
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