Advanced Python Programming

Synchronization and locks

Even if multiprocessing uses processes (with their own independent memory), it lets you define certain variables and arrays as shared memory. You can define a shared variable using multiprocessing.Value, passing its data type as a string (i integer, d double, f float, and so on). You can update the content of the variable through the value attribute, as shown in the following code snippet:

    shared_variable = multiprocessing.Value('f')     shared_variable.value = 0

When using shared memory, you should be aware of concurrent accesses. Imagine that you have a shared integer variable and each process increments its value multiple times. You will define a process class as follows:

 class Process(multiprocessing.Process): ...