This article reviews some common options for parallelizing Python code, including process-based parallelism, specialized libraries, ipython parallel, and Ray.

iterations_count = round(1e7)
def complex_operation(input_index):
print("Complex operation. Input index: {:2d}".format(input_index))
[math.exp(i) * math.sinh(i) for i in [1] * iterations_count]
@timebudget
def run_complex_operations(operation, input):
for i in input:
operation(i)

input =...

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Source: towardsdatascience.com