Advanced installation instructions¶

Dependencies¶

Scikit-learn requires:

• Python (>= 3.5),

• NumPy (>= 1.11),

• SciPy (>= 0.17),

• Joblib (>= 0.11).

Building Scikit-learn also requires

• Cython >=0.28.5

• OpenMP

Running tests requires

• pytest >=3.3.0

Some tests also require pandas.

Retrieving the latest code¶

We use Git for version control and GitHub for hosting our main repository.

You can check out the latest sources with the command:

git clone git://github.com/scikit-learn/scikit-learn.git

If you want to build a stable version, you can git checkout <VERSION> to get the code for that particular version, or download an zip archive of the version from github.

Once you have all the build requirements installed (see below for details), you can build and install the package in the following way.

If you run the development version, it is cumbersome to reinstall the package each time you update the sources. Therefore it’s recommended that you install in editable mode, which allows you to edit the code in-place. This builds the extension in place and creates a link to the development directory (see the pip docs):

pip install --editable .

pip install --editable .

On Unix-like systems, you can equivalently type make in from the top-level folder. Have a look at the Makefile for additional utilities.

Mac OSX¶

The default C compiler, Apple-clang, on Mac OSX does not directly support OpenMP. The first solution to build scikit-learn is to install another C compiler such as gcc or llvm-clang. Another solution is to enable OpenMP support on the default Apple-clang. In the following we present how to configure this second option.

You first need to install the OpenMP library:

brew install libomp

Then you need to set the following environment variables:

export CC=/usr/bin/clang
export CXX=/usr/bin/clang++
export CPPFLAGS="$CPPFLAGS -Xpreprocessor -fopenmp"
export CFLAGS="$CFLAGS -I/usr/local/opt/libomp/include"
export CXXFLAGS="$CXXFLAGS -I/usr/local/opt/libomp/include"
export LDFLAGS="$LDFLAGS -L/usr/local/opt/libomp/lib -lomp"
export DYLD_LIBRARY_PATH=/usr/local/opt/libomp/lib

Finally you can build the package using the standard command.

FreeBSD¶

The clang compiler included in FreeBSD 12.0 and 11.2 base systems does not include OpenMP support. You need to install the openmp library from packages (or ports):

sudo pkg install openmp

This will install header files in /usr/local/include and libs in /usr/local/lib. Since these directories are not searched by default, you can set the environment variables to these locations:

export CFLAGS="$CFLAGS -I/usr/local/include"
export CXXFLAGS="$CXXFLAGS -I/usr/local/include"
export LDFLAGS="$LDFLAGS -L/usr/local/lib -lomp"
export DYLD_LIBRARY_PATH=/usr/local/lib

Finally you can build the package using the standard command.

For the upcomming FreeBSD 12.1 and 11.3 versions, OpenMP will be included in the base system and these steps will not be necessary.

Linux¶

Installing from source without conda requires you to have installed the scikit-learn runtime dependencies, Python development headers and a working C/C++ compiler. Under Debian-based operating systems, which include Ubuntu:

sudo apt-get install build-essential python3-dev python3-setuptools \
                 python3-pip

and then:

pip3 install numpy scipy cython

pip3 install matplotlib

When precompiled wheels are not avalaible for your architecture, you can install the system versions:

sudo apt-get install cython3 python3-numpy python3-scipy python3-matplotlib

On Red Hat and clones (e.g. CentOS), install the dependencies using:

sudo yum -y install gcc gcc-c++ python-devel numpy scipy

Windows¶

To build scikit-learn on Windows you need a working C/C++ compiler in addition to numpy, scipy and setuptools.

The building command depends on the architecture of the Python interpreter, 32-bit or 64-bit. You can check the architecture by running the following in cmd or powershell console:

python -c "import struct; print(struct.calcsize('P') * 8)"

The above commands assume that you have the Python installation folder in your PATH environment variable.

You will need Build Tools for Visual Studio 2017.

For 64-bit Python, configure the build environment with:

SET DISTUTILS_USE_SDK=1
"C:\Program Files (x86)\Microsoft Visual Studio\2019\BuildTools\VC\Auxiliary\Build\vcvarsall.bat" x64

Please be aware that the path above might be different from user to user. The aim is to point to the “vcvarsall.bat” file.

And build scikit-learn from this environment:

python setup.py install

Replace x64 by x86 to build for 32-bit Python.

Building binary packages and installers¶

The .whl package and .exe installers can be built with:

pip install wheel
python setup.py bdist_wheel bdist_wininst -b doc/logos/scikit-learn-logo.bmp

The resulting packages are generated in the dist/ folder.

Using an alternative compiler¶

It is possible to use MinGW (a port of GCC to Windows OS) as an alternative to MSVC for 32-bit Python. Not that extensions built with mingw32 can be redistributed as reusable packages as they depend on GCC runtime libraries typically not installed on end-users environment.

To force the use of a particular compiler, pass the --compiler flag to the build step:

python setup.py build --compiler=my_compiler install

where my_compiler should be one of mingw32 or msvc.