We can install Python SciPy with the help of following methods −
Scientific Python Distributions − There are various scientific Python distributions that provide the language itself along with the most used packages. The advantage of using these distributions is that they require little configuration and work on almost all the setups. Here we will be discussing three most useful distributions −
Anaconda − Anaconda, a free Python distribution, works well on MS Windows, Mac OS, and Linux. It provides us over 1500 Python and R packages along with a large collection of libraries. This Python distribution is best suited for beginners.
WinPython − It is another free Python distribution that includes scientific packages as well as Spyder IDE. As the name entails, it only works with MS Windows OS.
Pyzo − Pyzo is also a free Python distribution. It is based on Anaconda and the IEP interactive development environment. It supports all the major operating systems such as MS Windows, Mac OS, and Linux.
Via pip − Pip is an inbuilt package management system that comes with Python. You can use pip to install, update, or delete any official package. Below is the command to install SciPy along with other useful packages via pip −
python -m pip install --user numpy scipy matplotlib ipython jupyter pandas sympy nose
System Package Manager − You can use the system package managers to install the most common Python packages as follows −
Ubuntu and Debian− For Ubuntu and Debian OS, use apt-get as given in the below command -
sudo apt-get install python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose
Fedora 22 and later− For Fedora 22 and later OS, use dnf as given in the below command
sudo dnf install numpy scipy python-matplotlib ipython pythonpandas sympy python-nose atlas-devel
Mac OS− If you are using Macports package manager, you can execute the following command−
sudo port install py35-numpy py35-scipy py35-matplotlib py35- ipython +notebook py35-pandas py35-sympy py35-nose
Whereas if you are using Homebrew (having incomplete coverage of SciPy ecosystem), use the below command −
Sudobrew install numpy scipy ipython jupyter
Source packages − This method is best suited for those who are involved in development because with source packages they can get development versions or can alter the source code too. You can get the source packages for SciPy here.
Binaries − You can directly install the packages using its binary files. Binary files can either come from GitHub or PyPi or third-party repositories. For example, Ubuntu OS has package repositories from where you can download individual binaries.