High-Performance Python – Compiled Code and Fortran Interface

f2py

Early in the development and growth of Python, the desire to integrate Fortran into Python led people to develop the necessary tools. To make the process more accessible, Pearu Peterson decided to create a tool for make porting easier. The tool, f2py , was first released in 1999 and was known as f2py.py . Eventually, the tool was incorporated into NumPy (numpy.f2py ) and is still there today.

F2py is probably the most popular tool for interfacing Fortran with Python and has been used in a large number of projects. It creates an extension module that is imported into Python by the import  Python command. The module has automatically generated wrapper functions that create the interface between Fortran and Python.

The f2py  users guide introduction shows three methods of use. Instead of presenting all three methods, I will focus on the “quick and smart way.”

The first step is to create a signature file for the Fortran (or C) code (f2py  also accommodates C code) that describes the wrapper for the Fortran or C functions. F2py refers to these as “signatures” of the functions. Usually f2py  can create a signature file for you just by scanning the source. Once the signatures are created, you compile the code to make it ready for Python.

f2py example

The simple Fortran code in Listing 2 illustrates how to call a subroutine with input data:

Listing 2: secret.f90

subroutine hellofortran(n)
integer n
 
write(*,*)  "Hello from Fortran! The secret number is: ", n
 
return
end

The next step is to create the signature of the code for f2py :

$ python3 -m numpy.f2py secret.f90 -m secretcode -h secret.pyf

For this command, f2py  takes the Fortran90 code and creates the signature file secret.pyf . The Python module is named secretcode  (the -m  option). The resulting signature file is shown in Listing 3.

Listing 3: secret.pyf

$ more secret.pyf
!    -*- f90 -*-
! Note: the context of this file is case sensitive.
 
python module secretcode ! in 
    interface  ! in :secretcode
        subroutine hellofortran(n) ! in :secretcode:secret.f90
            integer :: n
        end subroutine hellofortran
    end interface 
end python module secretcode
 
! This file was auto-generated with f2py (version:2).
! See http://cens.ioc.ee/projects/f2py2e/

The final step is to compile the code with f2py  and create the Python module:

$ python3 -m numpy.f2py -c secret.pyf secret.f90

The output from the command (not shown) provides some good information about what it's doing and is useful in understanding what f2py  does.

F2py creates a shared object (.so ) suitable for Python to import:

$ ls -s
total 120
112 secretcode.cpython-37m-x86_64-linux-gnu.so    4 secret.f90    4 secret.pyf

To test the code, run python3  (Listing 4). Remember, the Python module is secretcode .

Listing 4: Testing the Code

$ python3
Python 3.7.3 (default, Mar 27 2019, 22:11:17) 
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import secretcode
>>> secretcode.hellofortran(5)
 Hello from Fortran! The secret number is:            5

The first command (see the >>>  prompts) imports the secretcode  Python module. The shared object has the function hellofortran , which you use in the second command, secretcode.hellowfortran() . I used the argument 5  in the test.

OpenMP and f2py

If you can compile Fortran routines to use in Python, shouldn't you be able to compile OpenMP Fortran code for Python? After all, Python only uses a single core. If you either take existing Fortran routines or write new Fortran routines that use OpenMP to take advantage of all of the CPU cores, you would make much better use of computational resources.

Previously, I wrote an article that introduced the concept of using multicore processing with Fortran and OpenMP. The article has a simple example of finding the minimum of an array. F2py was used on the command line with several options for the compiler to build OpenMP code:

$ f2py --f90flags=-fopenmp -L/usr/lib/gcc/x86_64-redhat-linux/4.8.2/ -lgomp -c -m test test.f90

In this case, the GFortran compiler option -fopenmp  was used to compile the OpenMP. It also added the appropriate gomp  library with the full path. This test.f90  code also used the ompmin  function and created the test  module. Read the article to understand how you can use OpenMP with your Fortran code in Python.

gfort2py

During my research for this article, I ran into the interesting gfort2py  project, which uses GFortran, the GNU Fortran compiler, and Fortran modules (.mod  files) to translate the Fortran code's ABI (application binary interface) to Python-compatible types with Python's ctypes  library.

In principle, gfort2py  can accommodate anything the compiler can compile (i.e., valid Fortran), as long as it is in a Fortran module. Gfort2py is mostly written in Python and requires no changes to your Fortran code, as long as it is a module; however, you can only use GFortran.

The requirements for gfort2py  is a GFortran version greater than 5.3.1. It works with both Python 2.7 and Python 3. Although it is set up to be installed by pip , because I’m using Anaconda, I will install it the old-fashioned way and build it on the target system. The instructions for installation on the gfort2py website are easy to follow, and it's simple to install. Just be sure to start with the Python version you intend to use later.

The Fortran test code is very simple (Listing 5) and almost the same as the previous code. It just writes out a variable that is passed in. Notice that the code is in a module, as required.

Listing 5: test1.f90

module test1
contains 
subroutine hello(n)
    integer :: n
    write(*,*) "hello world. The secret number is ",n
    return 
end
end module test1

The next step is to compile the code and create the library (Listing 6). The resulting Python library is very easy to use: You use a function from the gfort2py  Python module, and it handles the heavy lifting, so to speak (Listing 7).

Listing 6: Compiling Fortran Code

$ gfortran -fPIC -shared -c test1.f90
$ gfortran -fPIC -shared -o libtest1.so test1.f90
$ ls -s
total 28
8 libtest1.so  4 test1.f90  4 test1.fpy  4 test1.mod  4 test1.o  4 test1.py

Listing 7: Using the Python Library

import gfort2py as gf
 
SHARED_LIB_NAME = "./libtest1.so"
MOD_FILE_NAME="test1.mod"
 
x = gf.fFort(SHARED_LIB_NAME, MOD_FILE_NAME)
 
y = x.hello(6)

First, variables are defined pointing to the library and the compiled .mod  file. Next, an object is defined that contains the functions in the Fortran module file (x ). Finally, a function from the code is used. Running the Python code shows the output:

$ python3 test1.py
 hello world. The secret number is            6

Going beyond this simple code would make the article too long, but it seems like almost anything you can put into a Fortran module would work – perhaps even OpenMP or an other extension. Gfort2py seems to be under active development, so check back in from time to time to see what new features have been added.