- Python Data Analysis
- Ivan Idris
- 236字
- 2021-08-05 17:31:48
Building NumPy, SciPy, matplotlib, and IPython from source
As a last resort or if we want to have the latest code, we can build from source. In practice, it shouldn't be that hard, although depending on your operating system, you might run into problems. As operating systems and related software are rapidly evolving, in such cases, the best you can do is search online or ask for help. In this chapter, we give pointers on good places to look for help.
The source code can be retrieved with git
or as an archive from GitHub. The steps to install NumPy from source are straightforward and given here. We can retrieve the source code for NumPy with git
as follows:
$ git clone git://github.com/numpy/numpy.git numpy
Note
There are similar commands for SciPy, matplotlib, and IPython (refer to the table that follows after this piece of information). The IPython source code can be downloaded from https://github.com/ipython/ipython/releases as a source archive or ZIP file. You can then unpack it with your favorite tool or with the following command:
$ tar -xzf ipython.tar.gz
Please refer to the following table for the git
commands and source archive/zip links:

Install on /usr/local
with the following command from the source code directory:
$ python setup.py build $ sudo python setup.py install --prefix=/usr/local
To build, we need a C compiler such as GCC and the Python header files in the python-dev
or python-devel
package.
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