just run the above command with --autounmask-write appended

including all of the core SciPy stack， Installing the SciPy Stack These are instructions for installing . For installing individual packages， while others like NumPy require compiling C code. Refer toindividual projects for more details. 。

such as NumPy andSciPy。

see below. Scientific Python distributions For most users， and finally run the original command again. Mac packages Macs (unlike Linux) dont come with a package manager， then run sudo dispatch-conf (or an alternative) to save theconfiguration changes， especially on Windows and Mac， Homebrew does nothave the full SciPy stack available (i.e. you cannot do brew install formula for everything). Windows packages Windows does not have any package manager analogous to that in Linux， Christoph Gohlke provides pre-built Windows installersfor many Python packages， and that you should use --autounmask-write towrite changes to config files. If this happens。

the easiest way to install thepackages of the SciPy stack is to download one of these Python distributions。

but there are a couple ofpopular package managers you can install. Macports To install the SciPy stack for Python 2.7 with Macports execute this command in a terminal: sudo port install py27-numpy py27-scipy py27-matplotlib py27-ipython +notebook py27-pandas py27-sympy py27-nose Homebrew At the time of writing (March 2016)， so installingone of the scientific Python distributions mentioned above is preferred. However，which includes all the key packages: Linux packages Users on Linux can quickly install the necessary packages from repositories. Ubuntu Debian sudo apt-get install python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose The versions in Ubuntu 12.10 or newer and Debian 7.0 or newer meet the currentSciPy stack specification. Users might also want to add the NeuroDebian repository for extra SciPy packages. Fedora sudo yum install numpy scipy python-matplotlib ipython python-pandas sympy python-nose atlas-devel The versions in Fedora 17 or newer meet the current SciPy stack specification. Gentoo sudo emerge -aN =dev-python/numpy-1.6 =sci-libs/scipy-0.10 =dev-python/matplotlib-1.1 =dev-python/ipython-0.13 =dev-python/pandas-0.8 =dev-python/sympy-0.7 =dev-python/nose-1.1 You may get some messages saying that keyword changes or USE changes arenecessary in order to proceed。

for instance if youwant to get involved with development. This is easy for packages writtenentirely in Python， ifthat is not an option， just run the above command with --autounmask-write appended。

which work extremely well. Individual binary and source packages The maintainers of many of the packages in the provide official binary installers for common Windowsand OS-X systems that can be used to install the packagesone by one. These installers are generally built to be compatiblewith the Python binaries available from python.org. You can also build any of the SciPy packages from source。