:orphan: |rss_image| **C++ - 1/1** :ref:`Blog ` :ref:`C++ (3) ` .. |rss_image| image:: feed-icon-16x16.png :target: ../_downloads/rss.xml :alt: RSS ---- .. index:: C++ .. _ap-cat-C++-0: C++ - 1/1 +++++++++ .. blogpostagg:: :title: cppyy: a new module for to C++ in python :date: 2019-09-25 :keywords: C++,cppyy,clang,cling :categories: C++ :rawfile: 2019/2019-09-25_cppyy.rst I did not try but the approach seems interesting and less verbose than any others. `cppyy `_ uses `cling `_ to extend Python code with C++ code during the execution. The `tutorial `_ contains the following example: ... .. blogpostagg:: :title: Cython, Pythran, nuitka, numba :date: 2018-08-05 :keywords: Cython,Pythran,nuitka,numba :categories: C++ :rawfile: 2018/2018-08-05_pythran.rst I discovered than :epkg:`Pythran` was now a possible backend for :epkg:`Cython`: `Pythran as a Numpy backend `_. On one benchmark, it increases the speed by 2. I recommend the reading of the following article: `Optimizing your code with NumPy, Cython, pythran and numba `_ which instigates the performance brought by the four following tool and gives some hints on how to write efficient code with these tools: ... .. blogpostagg:: :title: Exploration with pybind11 and ExtensionArray :date: 2018-08-03 :keywords: pybind11,C++,pandas :categories: C++ :rawfile: 2018/2018-08-03_pybind11.rst I tried the version of :epkg:`pybind11` to expose a dummy C++ object :class:`WeightedDouble `, to implement a couple of operators and to see how it behaves into a dataframe. ... ---- |rss_image| **C++ - 1/1** :ref:`2018-08 (2) ` :ref:`2019-02 (1) ` :ref:`2019-03 (1) ` :ref:`2019-09 (1) ` :ref:`2021-01 (1) `