![]() ![]() When the program was run, we found that the values were inconsistent. This lets us observe the iterations multiple times without manually calling processes. The _name_ variable is set to _main, and the method transact() is called inside a for loop. Print("Final balance = ".format(bal.value)) Proc2 = multiprocessing.Process(target=dpst, args=(bal,)) Proc1 = multiprocessing.Process(target=wthdrw, args=(bal,)) But when the program is compiled, the results are variable. Technically, the iteration would result in no change in the final balance as the same number is added and deducted over and over. This operation is run inside a loop thousands of times. The program has two processes: the first deposits $1 in an account, another deducts $1 from it, and then the balance is printed in the end. This section will clarify why locking a file in Python is important. Impact of Resource Sharing by Multiple Processes in Python #PYTHON XFILE HOW TO#This article will explain how to lock a file in Python. ![]() Similarly, in programming, whenever two processes or threads share the same resource, it can create problems that must be avoided by using locks. So, that’s why the shared resource is protected with a lock. If two people had access simultaneously, it could cause confusion and embarrassment. Every changing room has a lock that only one person can access at a time. Some resources cannot be accessed by two people simultaneously in our daily life, for example, a changing room. File State and Its Impact on Locking a File in Python.Impact of Resource Sharing by Multiple Processes in Python. ![]()
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