Using F2PY#

This page contains a reference to all command-line options for the f2py command, as well as a reference to internal functions of the numpy.f2py module.

Using f2py as a command-line tool#

When used as a command-line tool, f2py has three major modes, distinguished by the usage of -c and -h switches.

1. Signature file generation#

To scan Fortran sources and generate a signature file, use

f2py -h <filename.pyf> <options> <fortran files>   \
  [[ only: <fortran functions>  : ]                \
    [ skip: <fortran functions>  : ]]...           \
  [<fortran files> ...]


A Fortran source file can contain many routines, and it is often not necessary to allow all routines to be usable from Python. In such cases, either specify which routines should be wrapped (in the only: .. : part) or which routines F2PY should ignore (in the skip: .. : part).

F2PY has no concept of a “per-file” skip or only list, so if functions are listed in only, no other functions will be taken from any other files.

If <filename.pyf> is specified as stdout, then signatures are written to standard output instead of a file.

Among other options (see below), the following can be used in this mode:


Overwrites an existing signature file.

2. Extension module construction#

To construct an extension module, use

f2py -m <modulename> <options> <fortran files>   \
  [[ only: <fortran functions>  : ]              \
    [ skip: <fortran functions>  : ]]...          \
  [<fortran files> ...]

The constructed extension module is saved as <modulename>module.c to the current directory.

Here <fortran files> may also contain signature files. Among other options (see below), the following options can be used in this mode:


Adds debugging hooks to the extension module. When using this extension module, various diagnostic information about the wrapper is written to the standard output, for example, the values of variables, the steps taken, etc.


Add a CPP #include statement to the extension module source. <includefile> should be given in one of the following forms


The include statement is inserted just before the wrapper functions. This feature enables using arbitrary C functions (defined in <includefile>) in F2PY generated wrappers.


This option is deprecated. Use usercode statement to specify C code snippets directly in signature files.


Create Fortran subroutine wrappers to Fortran functions. --wrap-functions is default because it ensures maximum portability and compiler independence.

--include-paths "<path1>:<path2>..."

Search include files from given directories.


The paths are to be separated by the correct operating system separator pathsep, that is : on Linux / MacOS and ; on Windows. In CMake this corresponds to using $<SEMICOLON>.

--help-link [<list of resources names>]

List system resources found by numpy_distutils/ For example, try f2py --help-link lapack_opt.

3. Building a module#

To build an extension module, use

f2py -c <options> <fortran files>       \
  [[ only: <fortran functions>  : ]     \
    [ skip: <fortran functions>  : ]]... \
  [ <fortran/c source files> ] [ <.o, .a, .so files> ]

If <fortran files> contains a signature file, then the source for an extension module is constructed, all Fortran and C sources are compiled, and finally all object and library files are linked to the extension module <modulename>.so which is saved into the current directory.

If <fortran files> does not contain a signature file, then an extension module is constructed by scanning all Fortran source codes for routine signatures, before proceeding to build the extension module.


From Python 3.12 onwards, distutils has been removed. Use environment variables or native files to interact with meson instead. See its FAQ for more information.

Among other options (see below) and options described for previous modes, the following can be used.


Changed in version 1.26.0: There are now two separate build backends which can be used, distutils and meson. Users are strongly recommended to switch to meson since it is the default above Python 3.12.

Common build flags:

--backend <backend_type>

Specify the build backend for the compilation process. The supported backends are meson and distutils. If not specified, defaults to distutils. On Python 3.12 or higher, the default is meson.


Specify F77 compiler flags


Specify F90 compiler flags


Compile with debugging information


Use the library <libname> when linking.


Define macro <macro> as <defn>.


Define macro <macro>


Append directory <dir> to the list of directories searched for include files.


Add directory <dir> to the list of directories to be searched for -l.

The meson specific flags are:

--dep <dependency> meson only

Specify a meson dependency for the module. This may be passed multiple times for multiple dependencies. Dependencies are stored in a list for further processing. Example: --dep lapack --dep scalapack This will identify “lapack” and “scalapack” as dependencies and remove them from argv, leaving a dependencies list containing [“lapack”, “scalapack”].

The older distutils flags are:

--help-fcompiler no meson

List the available Fortran compilers.

--fcompiler=<Vendor> no meson

Specify a Fortran compiler type by vendor.

--f77exec=<path> no meson

Specify the path to a F77 compiler

--f90exec=<path> no meson

Specify the path to a F90 compiler

--opt=<string> no meson

Specify optimization flags

--arch=<string> no meson

Specify architecture specific optimization flags

--noopt no meson

Compile without optimization flags

--noarch no meson

Compile without arch-dependent optimization flags

link-<resource> no meson

Link the extension module with <resource> as defined by numpy_distutils/ E.g. to link with optimized LAPACK libraries (vecLib on MacOSX, ATLAS elsewhere), use --link-lapack_opt. See also --help-link switch.


The f2py -c option must be applied either to an existing .pyf file (plus the source/object/library files) or one must specify the -m <modulename> option (plus the sources/object/library files). Use one of the following options:

f2py -c -m fib1 fib1.f


f2py -m fib1 fib1.f -h fib1.pyf
f2py -c fib1.pyf fib1.f

For more information, see the Building C and C++ Extensions Python documentation for details.

When building an extension module, a combination of the following macros may be required for non-gcc Fortran compilers:


To test the performance of F2PY generated interfaces, use -DF2PY_REPORT_ATEXIT. Then a report of various timings is printed out at the exit of Python. This feature may not work on all platforms, and currently only Linux is supported.

To see whether F2PY generated interface performs copies of array arguments, use -DF2PY_REPORT_ON_ARRAY_COPY=<int>. When the size of an array argument is larger than <int>, a message about the copying is sent to stderr.

Other options#

-m <modulename>

Name of an extension module. Default is untitled.


Don’t use this option if a signature file (*.pyf) is used.

Changed in version 1.26.3: Will ignore -m if a pyf file is provided.


Do [not] lower the cases in <fortran files>. By default, --lower is assumed with -h switch, and --no-lower without the -h switch.


Writes additional headers in the C wrapper, can be passed multiple times, generates #include <header> each time. Note that this is meant to be passed in single quotes and without spaces, for example '-include<stdbool.h>'

--build-dir <dirname>

All F2PY generated files are created in <dirname>. Default is tempfile.mkdtemp().

--f2cmap <filename>

Load Fortran-to-C KIND specifications from the given file.


Run quietly.


Run with extra verbosity.


Do not generate wrapper files unless required by the inputs. This is a backwards compatibility flag to restore pre 1.22.4 behavior.


Print the F2PY version and exit.

Execute f2py without any options to get an up-to-date list of available options.

Python module numpy.f2py#


Changed in version 2.0.0: There used to be a f2py.compile function, which was removed, users may wrap python -m numpy.f2py via manually, and set environment variables to interact with meson as required.

When using numpy.f2py as a module, the following functions can be invoked.

Fortran to Python Interface Generator.

Copyright 1999 – 2011 Pearu Peterson all rights reserved. Copyright 2011 – present NumPy Developers. Permission to use, modify, and distribute this software is given under the terms of the NumPy License.



Return the directory that contains the fortranobject.c and .h files.


This function is not needed when building an extension with numpy.distutils directly from .f and/or .pyf files in one go.

Python extension modules built with f2py-generated code need to use fortranobject.c as a source file, and include the fortranobject.h header. This function can be used to obtain the directory containing both of these files.


Absolute path to the directory containing fortranobject.c and fortranobject.h.

See also


function that returns the numpy include directory


New in version 1.21.1.

Unless the build system you are using has specific support for f2py, building a Python extension using a .pyf signature file is a two-step process. For a module mymod:

  • Step 1: run python -m numpy.f2py mymod.pyf --quiet. This generates mymodmodule.c and (if needed) mymod-f2pywrappers.f files next to mymod.pyf.

  • Step 2: build your Python extension module. This requires the following source files:

    • mymodmodule.c

    • mymod-f2pywrappers.f (if it was generated in Step 1)

    • fortranobject.c


Equivalent to running:

f2py <args>

where <args>=string.join(<list>,' '), but in Python. Unless -h is used, this function returns a dictionary containing information on generated modules and their dependencies on source files.

You cannot build extension modules with this function, that is, using -c is not allowed. Use the compile command instead.


The command f2py -m scalar scalar.f can be executed from Python as follows.

>>> import numpy.f2py
>>> r = numpy.f2py.run_main(['-m','scalar','doc/source/f2py/scalar.f'])
Reading fortran codes...
        Reading file 'doc/source/f2py/scalar.f' (format:fix,strict)
        Block: scalar
                        Block: FOO
Building modules...
        Building module "scalar"...
        Wrote C/API module "scalar" to file "./scalarmodule.c"
>>> print(r)
{'scalar': {'h': ['/home/users/pearu/src_cvs/f2py/src/fortranobject.h'],
	 'csrc': ['./scalarmodule.c', 

Automatic extension module generation#

If you want to distribute your f2py extension module, then you only need to include the .pyf file and the Fortran code. The distutils extensions in NumPy allow you to define an extension module entirely in terms of this interface file. A valid file allowing distribution of the add.f module (as part of the package f2py_examples so that it would be loaded as f2py_examples.add) is:

def configuration(parent_package='', top_path=None)
    from numpy.distutils.misc_util import Configuration
    config = Configuration('f2py_examples',parent_package, top_path)
    config.add_extension('add', sources=['add.pyf','add.f'])
    return config

if __name__ == '__main__':
    from numpy.distutils.core import setup

Installation of the new package is easy using:

pip install .

assuming you have the proper permissions to write to the main site- packages directory for the version of Python you are using. For the resulting package to work, you need to create a file named (in the same directory as add.pyf). Notice the extension module is defined entirely in terms of the add.pyf and add.f files. The conversion of the .pyf file to a .c file is handled by numpy.distutils.