Used to think the problem just occured in command like "integer::a=1".
And i find that it has the same implicit save problem as mentioned before. Recently I tried the "data" command to assign values.
(If this question is considered to be irrelevant, I will remove it.) I am new to python and wonder if it is able to use the module in python's "multiprocessing". As mentioned by de Buyl, the module generated through f2py is not threadsafe. No useful "reload" methods reported yet.įortran has the implicit save problem as mentioned before.Ĭs.rpi.edu/~szymansk/OOF90/bugs.html here is a useful link provided by there is a new relevant question about the usage of the fortran module in parallel computation. Python import the fortran module as a library and it will remain in the memory between two calls. California is cracking down on catalytic converter theft by making it harder to sell the parts. So I wonder if there is any wiser way to crack this problem. Here is a test code, and the actual fortran code is much more complicated, so it may be impossible for me to simply clear some variables.Īgain that I cannot simply use the integer::aīecause I have too many subroutines in my actual fortran code, so it is hard to check every variable declaration. But why would the variable values be saved between two calls of the module? Is there any way that I can reset the fortran module every time I call it in python? I understand that the fortran variable declarations would only be executed once. But some variable values in the fortran code seems to be inheritated between these two calls.
I wrapeed up a fortran code using f2py and called the module twice in a python code.
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