suppose i a have a multiplicative expression with lots of multiplicands (small expressions)
expression = a*b*c*d*....*w
where for example c is (x-1), d is (y**2-16), k is (xy-60)..... x,y are numbers
and i know that c,d,k,j maybe zero
Does the order i write the expression matters for faster evaluation?
Is it better to write cdkj....*w or python will evaluate all expression no matter the order i write?
In the "if then" statement, the statement will only do the add and assignment when blah is true. In short, the answer to your question in this case is "yes". Show activity on this post. This code shows they perform similarly, but multiplication is usually slightly faster.
In python, to multiply number, we will use the asterisk character ” * ” to multiply number. After writing the above code (how to multiply numbers in Python), Ones you will print “ number ” then the output will appear as a “ The product is: 60 ”. Here, the asterisk character is used to multiply the number.
You can multiply large numbers in python directly without worrying about speed. Python supports a "bignum" integer type which can work with arbitrarily large numbers. In Python 2.5+, this type is called long and is separate from the int type, but the interpreter will automatically use whichever is more appropriate.
Python v2.6.5 does not check for zero values.
def foo():
a = 1
b = 2
c = 0
return a * b * c
>>> import dis
>>> dis.dis(foo)
2 0 LOAD_CONST 1 (1)
3 STORE_FAST 0 (a)
3 6 LOAD_CONST 2 (2)
9 STORE_FAST 1 (b)
4 12 LOAD_CONST 3 (3)
15 STORE_FAST 2 (c)
5 18 LOAD_FAST 0 (a)
21 LOAD_FAST 1 (b)
24 BINARY_MULTIPLY
25 LOAD_FAST 2 (c)
28 BINARY_MULTIPLY
29 RETURN_VALUE
Update: I tested Baldur's expressions, and Python can and will optimize code that involve constant expressions. The weird is that test6
isn't optimized.
def test1():
return 0 * 1
def test2():
a = 1
return 0 * a * 1
def test3():
return 243*(5539**35)*0
def test4():
return 0*243*(5539**35)
def test5():
return (256**256)*0
def test6():
return 0*(256**256)
>>> dis.dis(test1) # 0 * 1
2 0 LOAD_CONST 3 (0)
3 RETURN_VALUE
>>> dis.dis(test2) # 0 * a * 1
5 0 LOAD_CONST 1 (1)
3 STORE_FAST 0 (a)
6 6 LOAD_CONST 2 (0)
9 LOAD_FAST 0 (a)
12 BINARY_MULTIPLY
13 LOAD_CONST 1 (1)
16 BINARY_MULTIPLY
17 RETURN_VALUE
>>> dis.dis(test3) # 243*(5539**35)*0
9 0 LOAD_CONST 1 (243)
3 LOAD_CONST 5 (104736434394484...681759461305771899L)
6 BINARY_MULTIPLY
7 LOAD_CONST 4 (0)
10 BINARY_MULTIPLY
11 RETURN_VALUE
>>> dis.dis(test4) # 0*243*(5539**35)
12 0 LOAD_CONST 5 (0)
3 LOAD_CONST 6 (104736433252667...001759461305771899L)
6 BINARY_MULTIPLY
7 RETURN_VALUE
>>> dis.dis(test5) # (256**256)*0
15 0 LOAD_CONST 4 (0L)
3 RETURN_VALUE
>>> dis.dis(test6) # 0*(256**256)
18 0 LOAD_CONST 1 (0)
3 LOAD_CONST 3 (323170060713110...853611059596230656L)
6 BINARY_MULTIPLY
7 RETURN_VALUE
In brief, if the expression includes variables, the order doesn't matter. Everything will be evaluated.
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