I heard threading is not very efficient in Python (compared to other languages).
Is this true? If so, how can a Python programmer overcome this?
I heard threading is not very efficient in Python (compared to other languages). Is
Share
Sign Up to our social questions and Answers Engine to ask questions, answer people’s questions, and connect with other people.
Login to our social questions & Answers Engine to ask questions answer people’s questions & connect with other people.
Lost your password? Please enter your email address. You will receive a link and will create a new password via email.
Please briefly explain why you feel this question should be reported.
Please briefly explain why you feel this answer should be reported.
Please briefly explain why you feel this user should be reported.
I heard threading is not very efficient in Python (compared to other languages).
Is this true? If so, how can a Python programmer overcome this?
The reason people say that multi-threading is not very efficient in python is because of the Global Interpreter Lock. Because of the way the interpreter is written, only one thread can safely execute code in the interpreter at the same time.
This means that if you have threads which are quite heavily compute bound, that is, doing lots of stuff in the interpreter, then you effectively still only have the performance of a single threaded program. In this case you might be better off using the multiprocessing module, which has the same interface as the multithreading module but launches multiple copies of the interpreter (the downside of this is that you will have to explicitly share memory).
Where you still can reap speed gains from multithreading in python is if you are doing something that is heavily IO bound. While one thread is waiting for disk or network i/o the other threads can still execute, because when threads block they release the interpreter lock.