I’ve got the the Cython code working nicely. If you want to do data analysis in python, you always need to use python packages like Numpy, Pandas, Scipy and Matplotlib etc. pip attempts to run `python setup.py egg_info` to detemine the install requirements. Allow this command and other non-build related commands to be run without importing numpy or cython. # install a C compiler first pip install cython pip install amortization -v # Add -v to see what is happening behind the scenes To wrap up. Inside this file, you can start by writing regular Python code (note that there are some limitations in the Python code accepted by Cython, as clarified in the Cython docs). Cython increases the speed of a Python module by compiling a Python code to C. Although this is a common use-case for developers to use Cython, we can use it for code obfuscation. 接下来打开pycharm,去import pandas时,还是提示没有pandas模块,进入pycharm导包的地方,没有看到pandas加载进来,接着从pycharm file–>setting–>project interpreter–>‘+’,去导入pands时还是报错: command中提示Cannot cythonize without Cython installed.错误, Instructions for installing from source, PyPI, ActivePython, various Linux distributions, or a development version are also provided. 2 Hope it helps. In fact, Numpy, Pandas, and Scikit-learn all make use of Cython! Then the user doesn’t need Cython installed in order to install the package. To make your Python into Cython, first you need to create a file with the .pyx extension rather than the .py extension. closes #170 Hi, I remember facing this issue when installing scipy, do try installing cython using pip or easy_install using easy_install cython or pip install cython. cython, compiles to C/C++ files. Before going forward, make sure Cython is installed. For most people who just want to install the package, I’d like to include the .c file that Cython creates, and arrange for setup.py to compile that to produce the module. #Installation. There are two ways of compiling by using command lines: cython and cythonize. Cython (writing C extensions for pandas)¶ For many use cases writing pandas in pure Python and NumPy is sufficient. This is the recommended installation method for most users. For Ubuntu the packages cython and cython3 are available. Allow fastparquet to be installed when NumPy and Cython are not already installed. $ pip install cython $ easy_install cython anaconda using conda: $ conda install cython Enthought canopy using the enpkg package manager: $ enpkg cython Also the source code can be downloaded from github and installed manually using: $ python setup.py install Ubuntu, Debian. However, now I want to know how best to package it. I'm trying to install Python Pandas on my Raspi and I'm finding strange errors. In some computationally heavy applications however, it can be possible to achieve sizable speed-ups by offloading work to cython.. Now that we don't cythonize before creating the sdist, using the sdist fails to properly install the package if the freshly created environment doesn't include scipy. Hope it helps. The easiest way to install pandas is to install it as part of the Anaconda distribution, a cross platform distribution for data analysis and scientific computing. Chances are, the Python+C-optimized code in these popular libraries and/or using Cython is going to be far faster than the C code you might write yourself, and that's if you manage to write it without any bugs. Compiling by using command lines: Cython and cythonize make use of Cython for Pandas ) for! Your Python into Cython, first you need to create a file with.pyx... To create a file with the.pyx extension rather than the.py extension strange... 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