__imatmul__() magic method implements in-place matrix multiplication
x @= y that calculates the matrix multiplication of the two operands and assigns the result to the left operand. This operation is also called augmented arithmetic assignment. The method simply returns the new value to be assigned to the first operand.
- When you call
x @= y, Python first attempts to call
- If this is not implemented, it tries the normal matrix multiplication
- If this is not implemented either, it tries reverse matrix multiplication
y.__rmatmul__(x)with swapped operands.
The result is then assigned to the first operand
x. If none of those operations is implemented, Python raises a
We call this a “Dunder Method” for “Double Underscore Method” (also called “magic method”). To get a list of all dunder methods with explanation, check out our dunder cheat sheet article on this blog.
Basic Example Overriding __imatmul__
In the following code example, you create a class
Data and define the magic method
- The “self” argument is the default argument of each method and it refers to the object on which it is called—in our case, the first operand of the in-place operation.
- The “other” argument of the in-place method refers to the second operand, i.e.,
yin the in-place operation
x @= y.
The return value of the operation returns a dummy string
'finxter 42' to be assigned to the first operand. In practice, this would be the result of the in-place matrix multiplication.
class Data: def __imatmul__(self, other): return 'finxter 42' x = Data() y = Data() x @= y print(x) # finxter 42
In-Place Matrix Multiplication @ Without __imatmul__()
To support in-place matrix multiplication on a custom class, you don’t have to overwrite the in-place
__imatmul__() method. Because if the method is not defined, Python will fall back to the normal
__matmul__() method and assign its result to the first operand.
Here’s an example:
class Data: def __matmul__(self, other): return 'finxter 42' x = Data() y = Data() x @= y print(x) # finxter 42
Even though the
__imatmul__() method is not defined, the in-place matrix multiplication operation
x @= y still works due to the
__matmul__() “fallback” magic method!
In-Place Matrix Multiplication Without __imatmul__() and __matmul__()
To support in-place multiplication
x @= y on a custom class, you don’t even have to overwrite any of the
x.__matmul__(y) methods. If both are not defined, Python falls back to the reverse
y.__rmatmul__(x) method and assigns its result to the first operand.
Here’s an example where you create a custom class for the first operand that doesn’t support the matrix multiplication operation. Then you define a custom class for the second operand that defines the
__rmatmul__() method. For the in-place operation, Python falls back to the
__rmatmul__() method defined on the second operand and assigns it to the first operand
class Data_1: pass class Data_2: def __rmatmul__(self, other): return 'finxter 42' x = Data_1() y = Data_2() x @= y print(x) # finxter 42
TypeError: unsupported operand type(s) for @=
If you try to perform in-place multiplication
x @= y but neither
y.__rmatmul(x) is defined, Python raises a “
TypeError: unsupported operand type(s) for @=“. To fix this error, simply define any of those methods before performing the in-place operation.
class Data: pass x = Data() y = Data() x @= y
Traceback (most recent call last): File "C:\Users\xcent\Desktop\code.py", line 8, in <module> x @= y TypeError: unsupported operand type(s) for @=: 'Data' and 'Data'
Where to Go From Here?
Enough theory. Let’s get some practice!
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While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.
To help students reach higher levels of Python success, he founded the programming education website Finxter.com that has taught exponential skills to millions of coders worldwide. He’s the author of the best-selling programming books Python One-Liners (NoStarch 2020), The Art of Clean Code (NoStarch 2022), and The Book of Dash (NoStarch 2022). Chris also coauthored the Coffee Break Python series of self-published books. He’s a computer science enthusiast, freelancer, and owner of one of the top 10 largest Python blogs worldwide.
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