cython | 易学教程

Cythonize but not compile .pyx files using setup.py

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问题 I have a Cython project containing several .pyx files. To distribute my project I would like to provide my generated .c files as recommended in the Cython documentation, to minimize problems with different Cython versions. My current work flow is to build the project using: me@machine$ python setup.py build_ext --inplace This cythonizes (i.e. translate .pyx files to .c / .cpp files using Cython) all .pyx files and then compiles them. For a release I do not need the compiled ( .so ) files, so

Cythonize but not compile .pyx files using setup.py

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Pyside: addToJavaScriptWindowObject not working properly when application is compiled with cython

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问题 I have built an application that runs a couple thousand of lines of code. I am trying to hide the codes by compiling the python codes to c codes and then to an object file. This application works well in pyside. I converted this python file . py to a .c file and compiled the c to and object file .o . The name of this file is test2.py and my steps to convert it to an .o file: cython --embed -o test2.c test2.py from the above I now compile the test2.c to test2.o as follows gcc -I /usr/include

How to install IMUsim

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问题 This a guide rather than a question, because I spent a LOT of time fighting with compilation errors when installing IMUsim, and I know that many other researchers have struggled. The IMUsim code is currently unmaintained and the installation documentation is lacking. If you simply clone the current IMUsim repo and follow the instructions to build from source, it will fail citing missing files. See my answer below for the solution. 回答1: Installation instructions First, download the repo: git

ValueError: ndarray is not C-contiguous in cython

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问题 I have written the following function in cython to estimate the log-likelihood @cython.boundscheck(False) @cython.wraparound(False) def likelihood(double m, double c, np.ndarray[np.double_t, ndim=1, mode='c'] r_mpc not None, np.ndarray[np.double_t, ndim=1, mode='c'] gtan not None, np.ndarray[np.double_t, ndim=1, mode='c'] gcrs not None, np.ndarray[np.double_t, ndim=1, mode='c'] shear_err not None, np.ndarray[np.double_t, ndim=1, mode='c'] beta not None, double rho_c, np.ndarray[np.double_t,

python lib

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某厂面试归来，发现自己落伍了！>>> 7 essential PyPI libraries and how to use them Solve common Python problems by learning how to use these seven Python Package Index (PyPI) libraries. 7_essential_pypl_libraries-cover.jpg Download guide to 7 essential PyPI libraries Python is one of the most popular programming languages in use today—and for good reasons: it's open source, it has a wide range of uses (such as web programming, business applications, games, scientific programming, and much more), and it has a vibrant and dedicated community supporting it. In this guide, we'll look at seven Python Package Index

cython map with int k, with value a struct

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问题 I discovered cython yesterday and a couple of cdef for my numpy structures improved execution time by 50% making my 24 hr run just 12 hours. Incredible! I have a python dictionary with an integer key, containing a dictionary with 2 fixed keys each containing a float. This structure is accessed a crazy number of times. Hopping that cython can speed this up as well. cython documentation talks about c++ map and makes reference to map.pxd. I have zero experience in c++, but it appears cython will

Python的Cython在Windows环境下的部署安装

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大学课程主教java，搞过java web 后，突发感想对于OO语言的了解，以及设计模式与OO语言的优美的配合，但同时也发现java开发的周期性十分长，于是就四处需找不错的语言，终于发现了Python。不过，Python是解释性语言，机制效率相对于C/C++ 这种编译性语言效率会较低，也相对Java也会很低，不过，Python又名胶水语言，这也是吸引我的地方，他强大的类库，其他语言的扩充，如：Cython，Jython，IronPython等等，你说能不诱人么昨天一时兴起，玩起了Cython，但是发现，windows下的环境是多么的令人蛋疼，所以经过google，以及Python交流群的帮忙，最后终于完成了Cython编译的所需环境，下面，我来给大家说下，安装Cython所遇到的问题。 1、安装官方Cython提供的压缩包：地址： http://www.cython.org/#download 解压后，在解压目录运行cmd命令：(在此之前，你要确保你的系统环境Path，有Python的安装目录) python setup.py install 突然发现，运行出现‘error:Unable to find vcvarsall.bat’的错误别急，这时我们在Python的安装目录：Python27\Lib\distutils 下新建一个文件，文件名为：distutils.cfg

python使用Cython编译打包wheel

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https://stackoverflow.com/questions/39499453/package-only-binary-compiled-so-files-of-a-python-library-compiled-with-cython https://www.cnblogs.com/xueweihan/p/12030457.html https://zhuanlan.zhihu.com/p/57967281 https://zhuanlan.zhihu.com/p/25308951 https://blog.csdn.net/daniel_ustc/article/details/77622895 解释下相关参数： ‘cython_evaluate’ 是我们要生成的动态链接库的名字 sources 里面可以包含 .pyx 文件，以及后面如果我们要调用 C/C++ 程序的话，还可以往里面加 .c / .cpp 文件 language 其实默认就是 c，如果要用 C++，改成 c++ include_dirs 这个就是传给 gcc 的 -I 参数（numpy.get_include()其实这个只是示例，本程序不需要） library_dirs 这个就是传给 gcc 的 -L 参数 libraries 这个就是传给 gcc 的 -l 参数 extra_compile_args

Python生成词云

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1 概述利用Python生成简单的词云,需要的工具是cython,wordcloud与anaconda. 2 准备工作包括安装cython,wordcloud与anaconda. 2.1 安装anaconda 下载官网选择对应的版本下载即可. 2.2 安装cython cython是为了安装wordcloud准备的. pip -m pip install --upgrade cython 2.3 安装wordcloud 安装wordcloud前需要先安装Microsoft Visuall C++ 14.0. 这里下载安装好了以后重启,输入 python -m easy_install wordcloud 3 使用 3.1 打开Jupyter 打开Jupyter Notebook. 然后会在浏览器打开这个页面,新建一个notebook. 先把需要的库导入: from wordcloud import WordCloud import matplotlib.pyplot as plt 3.2 创建文字库简单的文字库可以直接选择一个txt文件,复杂的话可以选择创建一个excel,导出为csv文件,然后利用pandas库的read_csv()读入文件.这里创建一个txt,空格分隔单词即可. 然后上传到Jupyter中: 3.3 生成词云首先读入文件: text = open(