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f90wrap-0.2.9
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مشاهده بیشترتوضیحات
Fortran to Python interface generator with derived type support
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | f90wrap-0.2.9 |
| نام | f90wrap |
| نسخه کتابخانه | 0.2.9 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | - |
| ایمیل نویسنده | James Kermode <james.kermode@gmail.com> |
| آدرس صفحه اصلی | - |
| آدرس اینترنتی | https://pypi.org/project/f90wrap/ |
| مجوز | - |
f90wrap: Fortran to Python interface generator with derived type support
========================================================================
f90wrap is a tool to automatically generate Python extension modules
which interface to Fortran code that makes use of derived types. It
builds on the capabilities of the popular
[f2py](https://sysbio.ioc.ee/projects/f2py2e/) utility by generating a
simpler Fortran 90 interface to the original Fortran code which is then
suitable for wrapping with f2py, together with a higher-level Pythonic
wrapper that makes the existance of an additional layer transparent to
the final user.
Copyright (C) James Kermode 2011-2021. Released under the GNU Lesser General
Public License, version 3. Parts originally based on f90doc - automatic
documentation generator for Fortran 90. Copyright (C) 2004 Ian Rutt.
If you would like to license the source code under different terms,
please contact James Kermode <james.kermode@gmail.com>
Dependencies
------------
1. [Python](http://www.python.org) 3.7+ (Python 2.7 no longer supported)
2. Recent version of [numpy](http://www.numpy.org) which includes `f2py`
3. Fortran compiler - tested with `gfortran` 4.6+ and recent `ifort` 12+
Installation
------------
For the latest stable release, install with `pip`:
```
pip install f90wrap
```
There is also a [conda package](https://anaconda.org/conda-forge/f90wrap) on conda-forge:
```
conda install -c conda-forge f90wrap
```
For the development version, installation is as follows:
```
pip install git+https://github.com/jameskermode/f90wrap
```
Note that if your Fortran 90 compiler has a non-standard name
(e.g. gfortran-9) then you need to set the `F90` environment variable
prior to installing f90wrap to ensure it uses the correct one, e.g.
```
F90=gfortran-9 pip install f90wrap
```
Examples and Testing
--------------------
To test the installation, run `make test` from the `examples/`
directory. You may find the code in the various examples useful.
Citing f90wrap
--------------
If you find `f90wrap` useful in academic work, please cite the following
(open access) publication:
> J. R. Kermode, f90wrap: an automated tool for constructing
> deep Python interfaces to modern Fortran codes.
> J. Phys. Condens. Matter (2020)
>[doi:10.1088/1361-648X/ab82d2](https://dx.doi.org/10.1088/1361-648X/ab82d2)
BibTeX entry:
```bibtex
@ARTICLE{Kermode2020-f90wrap,
title = "f90wrap: an automated tool for constructing deep Python
interfaces to modern Fortran codes",
author = "Kermode, James R",
journal = "J. Phys. Condens. Matter",
month = mar,
year = 2020,
keywords = "Fortran; Interfacing; Interoperability; Python; Wrapping codes;
f2py",
language = "en",
issn = "0953-8984, 1361-648X",
pmid = "32209737",
doi = "10.1088/1361-648X/ab82d2"
}
```
Case studies
------------
f90wrap has been used to wrap the following large-scale scientific
applications:
- [QUIP](http://libatoms.github.io/QUIP/) - molecular dynamics code
- [CASTEP](http://www.castep.org) - CasPyTep wrappers for electronic structure code
- [QEpy](http://qepy.rutgers.edu/index.html) - Python wrapper for Quantum Espresso electronic structure code
See this [Jupyter notebook](https://github.com/jameskermode/f90wrap/blob/master/docs/tutorials/f90wrap-demo.ipynb)
from a recent seminar for more details.
Usage
-----
To use `f90wrap` to wrap a set of Fortran 90 source files and produce
wrappers suitable for input to f2py use:
f90wrap -m MODULE F90_FILES
where `MODULE` is the name of the Python module you want to produce (e.g.
the name of the Fortran code you are wrapping) and `F90_FILES` is a list
of Fortran 90 source files containing the modules, types and subroutines
you would like to expose via Python.
This will produce two types of output: Fortran 90 wrapper files suitable
for input to `f2py` to produce a low-level Python extension module, and a
high-level Python module desinged to be used together with the
f2py-generated module to give a more Pythonic interface.
One Fortran 90 wrapper file is written for each source file, named
`f90wrap_F90_FILE.f90`, plus possibly an extra file named
`f90wrap_toplevel.f90` if there are any subroutines or functions defined
outside of modules in `F90_FILES`.
To use f2py to compile these wrappers into an extension module, use:
f2py -c -m _MODULE OBJ_FILES f90wrap_*.f90 *.o
where `_MODULE` is the name of the low-level extension module.
Optionally, you can replace `f2py` with `f2py-f90wrap`, which is a
slightly modified version of `f2py` included in this distribution
that introduces the following features:
1. Allow the Fortran `present()` intrinsic function to work correctly with
optional arguments. If an argument to an f2py wrapped function is
optional and is not given, replace it with `NULL`.
2. Allow Fortran routines to raise a RuntimeError exception with a
message by calling an external function `f90wrap_abort`().
This is implemented using a `setjmp()/longjmp()` trap.
3. Allow Fortran routines to be interrupted with `Ctrl+C` by installing
a custom interrupt handler before the call into Fortran is made.
After the Fortran routine returns, the previous interrupt handler
is restored.
Notes
-----
- Unlike standard `f2py`, `f90wrap` converts all `intent(out)` arrays to
`intent(in, out)`. This was a deliberate design decision to allow allocatable and automatic arrays of unknown output size to be used. It is hard in general to work out what size array needs to be allocated, so relying on the the user to pre-allocate from Python is the safest solution.
- Scalar arguments without `intent` are treated as `intent(in)` by `f2py`. To have `inout` scalars, you need to call `f90wrap` with the `--default-to-inout` flag and declare the python variables as 1-length numpy arrays (`numpy.zeros(1)` for example).
- Pointer arguments are not supported.
- Arrays of derived types are currently not fully supported: a workaround is provided for 1D-fixed-length arrays, i.e. `type(a), dimension(b) :: c`. In this case, the super-type `Type_a_Xb_Array` will be created, and the array of types can be accessed through `c.items`. Note that dimension b can not be `:`, but can be a parameter.
- Doxygen documentation in Fortran sources are parsed and given as docstring in corresponding python interfaces. Doxygen support is partial and keyword support is limited to `brief`, `details`, `file`, `author` and `copyright`.
How f90wrap works
-----------------
There are five steps in the process of wrapping a Fortran 90 routine to
allow it to be called from Python.
1. The Fortran source files are scanned, building up an
abstract symbol tree (AST) which describes all the modules, types,
subroutines and functions found.
2. The AST is transformed to remove nodes which
should not be wrapped (e.g. private symbols in modules, routines
with arguments of a derived type not defined in the project, etc.)
3. The `f90wrap.f90wrapgen.F90WrapperGenerator` class is used to write
a simplified Fortran 90 prototype for each routine, with derived
type arguments replaced by integer arrays containing a
representation of a pointer to the derived type, in the manner
described in
[Pletzer2008](https://doi.org/10.1109/MCSE.2008.94).
This allows opaque references to the
true Fortran derived type data structures to be passed back and
forth between Python and Fortran.
4. f2py is used to combine the F90 wrappers and the original compiled
functions into a Python extension module (optionally, f2py can be
replaced by f2py-f90wrap, a slightly modified version which adds
support for exception handling and interruption during exceution of
Fortran code).
5. The `f90wrap.pywrapgen.PythonWrapperGenerator` class is used to
write a thin object-oriented layer on top of the f2py generated
wrapper functions which handles conversion between Python object
instances and Fortran derived-type variables, converting arguments
back and forth automatically.
Advanced Features
-----------------
Additional command line arguments can be passed to f90wrap to customize
how the wrappers are generated. See the `examples/` directory to see how
some of the options are used:
-h, --help show this help message and exit
-v, --verbose set verbosity level [default: None]
-V, --version show program's version number and exit
-p PREFIX, --prefix PREFIX
Prefix to prepend to arguments and subroutines.
-c [CALLBACK [CALLBACK ...]], --callback [CALLBACK [CALLBACK ...]]
Names of permitted callback routines.
-C [CONSTRUCTORS [CONSTRUCTORS ...]], --constructors [CONSTRUCTORS [CONSTRUCTORS ...]]
Names of constructor routines.
-D [DESTRUCTORS [DESTRUCTORS ...]], --destructors [DESTRUCTORS [DESTRUCTORS ...]]
Names of destructor routines.
-k KIND_MAP, --kind-map KIND_MAP
File containting Python dictionary in f2py_f2cmap
format
-s STRING_LENGTHS, --string-lengths STRING_LENGTHS
"File containing Python dictionary mapping string
length names to values
-S DEFAULT_STRING_LENGTH, --default-string-length DEFAULT_STRING_LENGTH
Default length of character strings
-i INIT_LINES, --init-lines INIT_LINES
File containing Python dictionary mapping type names
to necessary initialisation code
-I INIT_FILE, --init-file INIT_FILE
Python source file containing code to be added to
autogenerated __init__.py
-A ARGUMENT_NAME_MAP, --argument-name-map ARGUMENT_NAME_MAP
File containing Python dictionary to rename Fortran
arguments
--short-names SHORT_NAMES
File containing Python dictionary mapping full type
names to abbreviations
--py-mod-names PY_MOD_NAMES
File containing Python dictionary mapping Fortran
module names to Python ones
--class-names CLASS_NAMES
File containing Python dictionary mapping Fortran type
names to Python classes
--joint-modules JOINT_MODULES
File containing Python dictionary mapping modules
defining times to list of additional modules defining
methods
-m MOD_NAME, --mod-name MOD_NAME
Name of output extension module (without .so
extension).
-M, --move-methods Convert routines with derived type instance as first
agument into class methods
--shorten-routine-names
Remove type name prefix from routine names, e.g.
cell_symmetrise() -> symmetrise()
-P, --package Generate a Python package instead of a single module
-a ABORT_FUNC, --abort-func ABORT_FUNC
Name of Fortran subroutine to invoke if a fatal error
occurs
--only [ONLY [ONLY ...]]
Subroutines to include in wrapper
--skip [SKIP [SKIP ...]]
Subroutines to exclude modules and subroutines from
wrapper
--skip-types [SKIP_TYPES [SKIP_TYPES ...]]
Subroutines to exclude types from wrapper
--force-public [FORCE_PUBLIC [FORCE_PUBLIC ...]]
Names which are forced to be make public
--default-to-inout Sets all arguments without intent to intent(inout)
--conf-file CONF_FILE
Use Python configuration script to set options
--documentation-plugin DOCUMENTATION_PLUGIN
Use Python script for expanding the documentation of
functions and subroutines. All lines of the given tree
object are passed to it with a reference to its
documentation
--py-max-line-length PY_MAX_LINE_LENGTH
Maximum length of lines in python files written.
Default: 80
--f90-max-line-length F90_MAX_LINE_LENGTH
Maximum length of lines in fortan files written.
Default: 120
--type-check Check for type/shape matching of Python argument with the wrapped Fortran subroutine
Author
------
James Kermode [jameskermode](https://github.com/jameskermode)
Contributors
------------
- Tamas Stenczel [stenczelt](https://github.com/stenczelt)
- Steven Murray [steven-murray](https://github.com/steven-murray)
- Greg Corbett [gregcorbett](https://github.com/gregcorbett)
- Bob Fischer [citibob](https://github.com/citibob)
- David Verelst [davidovitch](https://github.com/davidovitch)
- James Orr [jamesorr](https://github.com/jamesorr)
- [yvesch](https://github.com/yvesch)
- [Matthias Cuntz](https://github.com/mcuntz)
- Balthasar Reuter [reuterbal](https://github.com/reuterbal)
- Daniel Vanzo [danbeibei](https://github.com/danbeibei)
Developer Notes
---------------
### Triggering the wheel build
Wheels are built on push and pull requests to `master` using cibuildwheel
with [this workflow](.github/workflows/build-wheels.yml).
To make a release candidate create a tag with a suffix such as `-rc1` for the first attempt,
push to trigger the build:
```bash
git commit -m 'release v0.x.z.rc1'
git tag v0.x.y.rc1
git push --tags
```
If all goes well, the `.whl` files will show up as assets within a new GitHub
release. The installation process can now be tested locally.
### Release wheels to PyPI
Once everything works correctly, make a full release (i.e. create a tag named
just `v0.x.y` without the `-rc1` suffix). This will trigger the upload of wheels
and source distribution to PyPI.
نیازمندی
| مقدار | نام |
|---|---|
| - | numpy>=1.13 |
نحوه نصب
نصب پکیج whl f90wrap-0.2.9:
pip install f90wrap-0.2.9.whl
نصب پکیج tar.gz f90wrap-0.2.9:
pip install f90wrap-0.2.9.tar.gz