f2py-jit
Just-in-time compilation of Fortran code in Python via f2py.
Check out the documentation for full details.
Quick start
Start from a piece of Fortran, say code.f90
subroutine hello()
print*, "Hello world!"
end subroutine
Compile the code, import it and execute it
from f2py_jit import jit
f90 = jit('code.f90')
f90.hello()
Do the same but from a python string containing the source block
source = """
subroutine hello()
print*, "Hello world!"
end subroutine
"""
f90 = jit(source)
f90.hello()
If the Fortran source contains multiple subroutines calling each other, f2py will not perform interprocedural optimizations (at least not by default). f2py_jit can inline the source code before compiling it, and you will get a performace boost [This feature is experimental]
f90 = jit('code.f90', inline=True)
Features
- Compilation of Fortran source blocks as Python strings
- Caching of module builds across executions
- Support for Fortran derived types via f90wrap
- Inlining to improve performance (experimental)
Dependencies
- Fortran compiler (ex.
gfortran) numpymeson(for Python >= 3.11)
The package currently supports Python versions from 3.7 to 3.14.
Important: on Debian-based OS, packages pkg-config and python3-dev are required with Python>=3.11. They must be installed at the OS level ex. via apt.
Note: Python versions >= 3.11 will use the meson backend to build Fortran extensions, which has slower build times than distutils (used by default in versions < 3.11).
Installation
From pip
pip install f2py-jit
To install the package with support for derived types (courtesy of f90wrap
pip install f2py-jit[types]
Note that this requires Python >= 3.8.
From source
git clone https://framagit.org/coslo/f2py-jit.git
cd f2py_jit
pip install .
Credits
Part of this code is adapted from numpy.f2py module by Pearu Peterson, in accordance with the NumPy license.
Authors
Daniele Coslovich: https://www.units.it/daniele.coslovich/
1 maintainer
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