- Cookiecutter
- About the repository
- Previous lectures (if needed)
- Library directory structure
- Miscellaneous
You can create a new project from this repository's cookiecutter
template. You
can find it on the cookies
branch. If you are not familiar with cookiecutter simply
must do:
pip install cookiecutter
Then, in the folder you are going to start, your project
cookiecutter https://github.com/SalvadorBrandolin/fortran_meson_py --checkout cookies
Example of building Python API of Fortran project with Meson.
The objective is to demonstrate how to integrate a Fortran library that runs with the Fortran Package Manager (fpm) and a Python API within the same repository, enabling package building and distribution.
The idea is having an example of a Fortran library that runs with fpm and a Python API inside the same repository that builds and distributes the package.
First, the Fortran project is compiled with fpm. Then, the Meson build system
is used to compile the C
wrapper for the Fortran library using numpy.f2py,
linking with the fpm-compiled library. Finally, the repository builds different
Python API wheels for various Python versions and operating systems.
Apologies in advance for experienced users, the repository is intended for beginners in the field of Fortran, Python, and Meson. And useful to simple architectures of Fortran code. It is assumed that an experienced user will be capable to adapt the repository to more complex cases.
We made a post of this topic in fortan-lang discussion
. Maybe you can
understand more the motivations of this repository. Also, you may find
commentaries from other users that can help you.
Little knowledge of Fortran is needed. It's necessary to know how to install a
Fortran compiler (gfortran
is used in this example) and the Fortran Package
Manager (fpm). The following links can be useful:
- Learn Fortran: https://fortran-lang.org/learn/
- fpm: https://fpm.fortran-lang.org/
- Compiler and IDE: https://fortran-lang.org/learn/os_setup/
Little knowledge of Python is needed. It's necessary to know how to install Python on your system, and preferably, how to use virtual environments.
- Learn and install Python: https://wiki.python.org/moin/BeginnersGuide
- Virtual environments: https://virtualenv.pypa.io/en/latest/
- Numpy f2py meson: https://numpy.org/doc/stable/f2py/buildtools/meson.html
- Interesting to know: https://virtualenvwrapper.readthedocs.io/en/latest/
Meson build system lectures and specific sections of the documentation are provided:
- Meson tutorial: https://mesonbuild.com/Tutorial.html
- Meson py.extesion: https://mesonbuild.com/Python-module.html#extension_module
- meson-python: https://mesonbuild.com/meson-python/
If you are familiar with fpm
and you have a Fortran project that you want to
have a Python API, your project should look something like this:
├── app
│ └── main.f90
├── src
│ ├── circle
│ │ └── circle_props.f90
│ ├── constants.f90
│ └── fexample.f90
├── test
│ └── check.f90
├── LICENSE
├── fpm.toml
└── README.md
This is normally the structure of any new fpm
project.
fpm new <project name>
For this tutorial the app and test directories are not of our
interest. First, we focus on the fpm.toml file. There are all the
configurations of the Fortran project. Here it's important to set the library
setting to true
:
[install]
library = true
Is necessary like that to generate the necessary files to build the Python API
by linking the fpm
compilation. Also, you can observe that our library's name
is fexample
.
Next, in the src directory, we have the Fortran source code of the
library. The constants.f90 file contains the definition of
the constant pi
and the parameter pr
(the precision of the float numbers in
our project).
Then, the fexample.f90 file contains the definition of the main module of the library, called the same as the library. There we only import all the modules of the library.
Finally, the circle_props.f90 file contains the
definition of the calculate_area
and calculate_perimeter
subroutines. These
subroutines are used to calculate the area and circumference of a circle, with
a given radius. Those are the subroutines that we want to use in our Python
API.
Of course, the example is very simple, but it's enough to demonstrate the idea. Just imagine that those subroutines have a very complex and expensive calculation...
Note 1: Check the definition of the subroutines, you must explicitly define the
intent
of the variables.
Note 2: I told you that the app directory is not of our interest, but you can perform the
fpm run
command to test the two subroutines if you want.
Is kind to have the c_wrapper separated from everything else, but of course you
can do whatever you want. The c_wrapper directory contains the
necessary files to build the C
wrapper of the Fortran library. The C
wrapper uses the iso_c_binding
module to define subroutines compatible with
C
types.
Well, so I have to rewrite all my subroutines compatible with C?
Well, yes... I'm sorry. This is a pain for sure but necessary. Of course, we
don't have to implement again the subroutines, only the subroutines signatures.
Inside we call our fpm
library.
You can check the fexample_c.f90 file. There are
defined the same functions as in fexample
with addition of *_c
in their
names to differentiate them. Also, we differentiate:
fexample
:fpm
project (Fortran
library)fexample_c
: C-API offexample
The nightmare begins here (lots of commits till compiles).
In the case of fexample
there is no big problems, but for a more complex
library with OOP architecture and lots of linking dependencies in compilations
will take some time to make it work.
Fortran
users that are too used to fpm
capabilities as I (Salvador) and
don't have much experience dealing with compilations flags, this is your first
challenge.
Note 3 (Salvador): Really this is the true motivation of made this little example. To learn and mess around with a build system and compilations flags. In my
Fortran
language learning path I always usedfpm
and its was fun, its solves all the compilations for me. And for sure I don't want to solve the compilation order of any modernFortran
project,fpm
already does. So, It's possible to compilefexample
withfpm
, and the link it with f2py and be happy? We found that meson allows us to do that, and all works pretty fine.
We are using meson-python
as the build system for the Python library. For that you can check the configurations of:
As in any Python
we provide a requirements-dev.txt file with dependencies for developing. But here, we also provided a build-requirements.txt file with the dependencies for building the Python API. You can check that in the pyproject.toml and build-requirements.txt files the dependencies are the same.
Why we do that? Because, when developing the package the developer
need to install the Python
package in --editable
mode. With
meson-python
it's necessary to manually install the build dependencies and then install the package in --editable
mode.
The correct way of doing that is bay the commands:
cd python
pip install -r python/build-requirements.txt
pip install -e . --no-build-isolation
Then we have the python/fexample directory that contains the source code of the python library.
There we have the python/fexample/compiled
directory that contains the C
wrapper of the fexample
library. The C
wrapper is compiled with f2py
and linked with the fexample
library, and
finally, stored in that directory. You can check the meson.build configuration
file, on the py.extension
, how that is done.
This is not really neccesary, buy maybe you want to distribute your python package with PyPI
. Well, is the moment to obtain a compiled wheel matrix:
WheelMatrix = OS you want to support times Python versions you want to support
On the .github/workflows/wheels.yml there is an
action that uses cibuildwheel
to compile the wheels for the Python API. The
wheels are not uploaded to PyPI
, but you can do that with the twine
package.
.vscode settings are recommended to be used:
[email protected]:ipqa-research/vscode-fortran.git
There you can find the settings for the Fortran language compatible with fpm