Merge branch 'master' of https://gricad-gitlab.univ-grenoble-alpes.fr/python-uga/training-hpc

ipynb/30_wrapping.ipynb

@@ -2,10 +2,18 @@
 
 # Wrapping codes in static languages
 
 %% Cell type:markdown id: tags:
 
+We consider here wrapping two static languages: C and fortran.
+
+We classically wrapp already existing code to access them via python. 
+
+
+
+%% Cell type:markdown id: tags:
+
 ## Fortran with [f2py](https://docs.scipy.org/doc/numpy/f2py/)
 
 `f2py` is a tool that allows to call Fortran code into Python. It is a part of `numpy` meaning that to use it, we only need to install and import numpy (which should already be done if you do scientific Python !) :
 
 ```bash
@@ -261,5 +269,104 @@
 The documentation of f2py (https://docs.scipy.org/doc/numpy/f2py/) can also help, covering notably:
 * `Cf2py` directives to overcome F77 limitations (e.g. intents)
 * How to integrate Fortran sources to your Python packages and compile them on install
 * How to use `f2py` inside Python scripts
 * ...
+
+%% Cell type:markdown id: tags:
+
+Wrapping C code
+--------------------------
+
+%% Cell type:markdown id: tags:
+
+They are different ways of wrapping C code. We present CFFI. 
+
+The workflow is the following:
+  1. Get your C code working (with a .c and a .h)
+  2. Set up your packaging to compile your code as a module
+  3. Compile your code
+  4. In the python code, declare the function you will be using
+  5. In the python code, open/load the compiled module
+  6. Use your functions
+
+
+%% Cell type:markdown id: tags:
+
+**1. Get your C code working (with a .c and a .h)**
+
+Ok, supposed to be done
+
+%% Cell type:markdown id: tags:
+
+**2. Set up your packaging to compile your code as a module**
+
+We give the compilation instructions in the file setup.py:
+
+
+%% Cell type:raw id: tags:
+
+from setuptools import setup, Extension
+
+version = "0.1"
+
+module_distance = Extension(
+    name="cdtw",
+    sources=["cdtw.c"],
+)
+
+setup(
+    name="dtw_cort_dist_mat",
+    version=version,
+    description="data scientist tool for time series",
+    long_description="data scientist tool for time series",
+    classifiers=[], 
+    author="Robert Bidochon",
+    author_email="robert@bidochon.fr",
+    license="GPL",
+    include_package_data=True,
+    install_requires=["cffi", "numpy", "setuptools"],
+    entry_points="",
+    ext_modules=[module_distance],
+)
+
+
+%% Cell type:markdown id: tags:
+
+**3. Compile your code**
+
+%% Cell type:markdown id: tags:
+
+in a terminal, type:
+
+python3 setup.py build_ext
+
+%% Cell type:markdown id: tags:
+
+**4. In the python code, declare the function you will be using**
+
+%% Cell type:code id: tags:
+
+``` python
+from cffi import FFI
+
+ffi = FFI()
+ffi.cdef("double square(double x, double y);")
+```
+
+%% Cell type:markdown id: tags:
+
+**5. In the python code, open/load the compiled module**
+
+%% Cell type:raw id: tags:
+
+dllib = ffi.dlopen(
+    str(my_dir / ("cdtw" + sysconfig.get_config_var("EXT_SUFFIX")))
+)
+
+%% Cell type:markdown id: tags:
+
+**6. Use your functions**
+
+%% Cell type:markdown id: tags:
+
+sq = dllib.square(2.0, 3.0)