Parallelize Python Loop: Questions

Question

I have some code that is calculating the value of a large number of discrete actions and outputting the best action and it's value.

A_max = 0
for i in...
    A = f(i)
    if A > A_max
        x = i
        A_max = A

I'd like to parallelize this code in order to save time. Now, my understanding is that as calculating f(i) doesn't depend on calculating f(j) first, I can just use joblib.Parallel for that part of the code and get something like:

results = Parallel(n_jobs=-1)(delayed(f)(i) for i in...)
A_max = max(results)
x = list.index(A_max)

is this correct?

My next issue is that my code contains a dictionary that the function f alters as it does it calculation. My understanding is that if the code is parallelized, each concurrent process will be altering the same dictionary. Is this correct and if so would creating copies of the dictionary at the beginning of f solve the issue?

Finally, in the documentation I'm seeing references to backends called "Lorky" and "threading", what is the difference between these backends?