Installing silx in a virtualenv

This step-by-step guide explains how to install silx in a virtualenv.

Prerequisites

This guide assumes that your system meets the following requirements:

• a version of python compatible with silx is installed (python 2.7 or python >= 3.4)
• the pip installer for python packages is installed
• the Qt libraries is installed (optional, required for using silx.gui)

Installation procedure

Install vitrualenv

pip install virtualenv --user

Create a virtualenv

The files required by a virtual environment are created in a new folder with the same name as the virtualenv. So make sure you are in a directory in which you have write permissions.

In this tutorial we use a folder venvs in our home directory, and we create a virtual environment named silx_venv

cd
mkdir -p venvs
cd venvs
virtualenv silx_venv

A virtualenv contains a copy of your default python interpreter with a few tools to install packages (pip, setuptools).

To use a different python interpreter, you can specify it on the command line. For example, to use python 3.4:

virtualenv -p /usr/bin/python3.4 silx_venv

Activate a virtualenv

A script is provided in your virtualenv to activate it.

source silx_venv/bin/activate

After activating your new virtualenv, this python interpreter and the package tools are used, instead of the ones from the system.

Any libraries you will install or upgrade will be inside the virtual environment, and will not affect the rest of system.

Upgrade pip

After activating silx_venv, you should upgrade pip:

python -m pip install --upgrade pip

Upgrade setuptools and wheel

Upgrading the python packaging related libraries can make installing the rest of the libraries much easier.

pip install setuptools --upgrade
pip install wheel --upgrade

Install build dependencies

The following command installs libraries that are required to build and install silx:

pip install numpy cython

Install optional dependencies

The following command installs libraries that are needed by various modules of silx:

pip install matplotlib fabio h5py

The next command installs libraries that are used by the python modules handling parallel computing:

pip install pyopencl mako

Install pyqt

If your python version is 3.5, installing PyQt5 and all required packages is as simple as typing:

pip install PyQt5

For previous versions of python, there are no wheels available, so the installation is much more complicated.

If the Qt libraries are installed, you can install pyqt in your virtualenv. This is optional, but none of the silx widgets will work if you don’t have a python binding for Qt.

You must start by installing SIP:

hg clone http://www.riverbankcomputing.com/hg/sip
cd sip

python build.py prepare  # FIXME:  sh: 1: flex: not found
python configure.py -d ~/venvs/silx_venv/lib/python2.7/site-packages
make
make install
make clean

Download PyQt5 or PyQt4, depending on your Qt version.

For Qt 4, download the latest PyQt4 tarball.

wget http://sourceforge.net/projects/pyqt/files/PyQt4/PyQt-4.11.4/PyQt-x11-gpl-4.11.4.tar.gz

Alternatively, download the file using your web browser and save it in your virtualenv folder.

tar -xvf PyQt-x11-gpl-4.11.4.tar.gz
cd PyQt-x11-gpl-4.11.4/

Now, configure the PyQt4 installer to install the library inside your virtualenv:

python configure.py --destdir ~/venvs/silx_venv/lib/python2.7/site-packages
make
make install
make clean

Install silx

pip install silx

To test silx, open an interactive python console. If you managed to install PyQt or PySide in your virtualenv, type:

python

If you don’t have Qt, use:

WITH_QT_TEST=False python

Run the test suite using:

>>> import silx.test
>>> silx.test.run_tests()