Python: difference between map() and for loop when handling a function that edits a local variable

If we define a function that modifies a global variable, and run that function using map(), it fails to make the changes to the variable.

The question is how come there is a difference in behavior compared to simply running inside a for loop?

Minmal working example with for loop:

size = 5
datavals = np.random.random((size,4))

mydict = {'values':np.zeros((size))}
def myfun(index):
    v1 = np.sum(datavals[index,:]**2)**0.5    
    mydict['values'][index] = v1
    return

for i1 in np.arange(size):
    myfun(i1)

print('function evaluated in for loop')
print(mydict['values'])

Gives the expected output of

function evaluated in for loop
[1.60797084 1.15736358 0.91658427 1.47411556 1.62382541]

However, running the same function in map():

size = 5
datavals = np.random.random((size,4))

mydict = {'values':np.zeros((size))}
def myfun(index):
    v1 = np.sum(datavals[index,:]**2)**0.5    
    mydict['values'][index] = v1
    return

map(myfun, np.arange(size))
print('function evaluated using map()')
print(mydict['values'])

shows the variable is not modified:

function evaluated using map()
[0. 0. 0. 0. 0.]

>Solution :

Because map is lazy calculation, when you don’t traverse the results of map, map doesn’t apply your function to each variable.