Getting started

Quick installation

If you have all dependencies installed on your system, building and installing / updating PyTango can be as simple as:

easy_install -U PyTango

If you managed to run this line, the quick tour can guide you through the first steps on using PyTango.

Dependencies on other libraries

Don’t be scared by the graph. Probably most of the packages are already installed. The current PyTango version has four major dependencies:

• python (>= 2.4) (http://www.python.org/)

• omniORB (http://omniorb.sourceforge.net/)

• Tango (>= 7.2.0) (http://www.tango-controls.org/)

• boost python (http://www.boost.org):

  if python >= 2.6.3 then: boost-python >= 1.41 else: boost-python >= 1.33 We strongly recommend always using >= 1.41

plus two optional dependencies (activated by default) on:

• IPyhon (>=0.10) (http://ipython.scipy.org/) (necessary for ITango)
• numpy (>= 1.1.0) (http://numpy.scipy.org/)

Note

For the provided windows binary, numpy is MANDATORY!

Installing precompiled binaries

Linux

The PyTango team does not provide a precompiled binary for Linux since this would mean having to provide 12 different binaries: one for each major python version (2.4, 2.5, 2.6, 2.7, 3.0 and 3.1) times 2 for both 32bits and 64bits.

Tango contributers have written packages for at least ubuntu and debian linux distributions. Check the Ubuntu GNU/Linux binary distribution chapter under Tango downloads for more details.

Windows

PyTango team provides a limited set of binary PyTango distributables for Windows XP/Vista/7. The complete list of binaries can be downloaded from PyTango PyPI website.

version	Dependencies	Compilation env.
PyTango-7.2.2.win32-py2.6.msi PyTango-7.2.2.win32-py2.6.exe	Tango C++ >= 7.2.6 and < 8.0 Python 2.6.x (where x >= 0) numpy 1.x (where x >= 1. Recommended x >= 5)	Tango 7.2.6 windows distribution Python 2.6.6 Numpy 1.5 boost-python 1.41 mutithreaded dll Visual Studio 8.0 (2005) Windows XP Pro 2002 SP3 PC: Intel Xeon E5440 @ 2.83GHz 1GB RAM
PyTango-7.2.2.win32-py2.7.msi PyTango-7.2.2.win32-py2.7.exe	Tango C++ >= 7.2.6 and < 8.0 Python 2.7.x (where x >= 0) numpy 1.x (where x >= 1. Recommended x >= 5)	Tango 7.2.6 windows distribution Python 2.7.2 Numpy 1.5 boost-python 1.47 mutithreaded dll Visual Studio 8.0 (2005) Windows XP Pro 2002 SP3 PC: Intel Xeon E5440 @ 2.83GHz 1GB RAM

Until version 7.2.2 (due to internal incompatibilities between tango C++ API and PyTango), PyTango had to be shipped with an internal copy of tango and omniORB DLLs. Since version 7.2.2 ( and tango C++ version 7.2.6) this is no longer necessary. In other words, until 7.2.2 you could install and use PyTango without having tango c++ installed. Starting from 7.2.2 you must have tango C++ installed and the environment variable PATH must include the directory where the tango C++ DLLs are installed (usually C:\Program Files (x86)\tango\win32_vc8\win32_dll).

Regarding boost-python, since VS hard links with the boost-python DLL file of the machine where PyTango binary was originally compiled, PyTango ships with it’s own internal copy of the boost-python DLL. Maybe in the future PyTango will link with the static version of boost-python but for now we get to many errors at compile time so we are skipping this for now. Anyway, it’s just an internal developers detail. For you just means 250kb more of memory usage in windows.

The binary was compiled with numpy dependency therefore you need to have numpy installed in order to use PyTango.

If PyTango reports DLL load failed probably you are missing Visual Studio 2005 redistributable package. You can download and install it from Microsoft Visual C++ 2005 Redistributable Package (x86)

version	Includes the following DLLs
7.2.2	boost python 1.41 (VC++8, multi-threaded)
7.1.0	tango 7.1.1 (VC++ 8) omniORB 4.1.4 boost python 1.41 (VC++8, multi-threaded)
7.1.0 rc1	tango 7.1.1 (VC++ 8) omniORB 4.1.4 boost python 1.41 beta 1 (VC++8, multi-threaded) this version was used because it is the first version that fixes a bug that prevents PyTango from being used with python >= 2.6.3

Compiling & installing

Linux

Since PyTango 7 the build system used to compile PyTango is the standard python distutils.

Besides the binaries for the four dependencies mentioned above, you also need the development files for the respective libraries.

boost python dependency

PyTango has a dependency on the boost python library (>= 1.33). This means that the shared library file libboost-python.so must be accessible to the compilation command.

Note

If you use python >= 2.6.3 you MUST install boost python >= 1.41

Most linux distributions today provide a boost python package.

Furthermore, in order to be able to build PyTango, you also need the include headers of boost python. They are normaly provided by a package called boost_python-dev.

If, for some reason, you need to compile and install boost python, here is a quick recipie:

1. Download latest boost tar.gz file and extract it

2. Download latest bjam (most linux distributions have a bjam package. If not, sourceforge provides a binary for many platforms)

3. build and/or install:

   1. Simple build: in the root directory where you extracted boost type:

      bjam --with-python toolset=gcc variant=release threading=multi link=shared

      this will produce in bin.v2/libs/python/build/gcc-<gcc_ver>/release/threading-multi a file called libboost_python-gcc<gcc_ver>-mt-<boost_ver>.so.<boost_python_ver>

   2. Install (you may need administrator permissions to do so):

      bjam --with-python toolset=gcc variant=release threading=multi link=shared install

   3. Install in a different directory (<install_dir>):

      bjam --with-python toolset=gcc variant=release threading=multi link=shared install --prefix=<install_dir>

boost, omniORB and TangoC++ configuration

The second step is to make sure the three/four libraries (omniORB, tango, boost python and/or numpy) are accessible to the compilation command. So, for example, if you installed:

boost python under /home/homer/local

omniORB under /home/homer/local1

tango under /home/homer/local2

numpy under /usr/lib/python2.6/site-packages/numpy

you must export the three environment variables:

export BOOST_ROOT=/home/homer/local
export OMNI_ROOT=/home/homer/local1
export TANGO_ROOT=/home/homer/local2

# in openSUSE 11.1 this is the default base location for the include files
export NUMPY_ROOT=/usr/lib/python2.6/site-packages/numpy/core

(for numpy this is the default base location for the include files. This is distribution dependent. For example, ubuntu places a numpy directory under /usr/include, so exporting NUMPY_ROOT is not necessary for this distribution)

For the libraries that were installed in the default system directory (/usr or /usr/local) the above lines are not necessary.

build & install

Finally:

python setup.py build
sudo python setup.py install

This will install PyTango in the system python installation directory and, since version 7.1.2, it will also install ITango as an IPython extension.

Or if you whish to install in a different directory:

python setup.py build
python setup.py install --prefix=/home/homer/local --ipython-local

(This will try to install ITango as an IPython profile to the local user, since probably there is no permission to write into the IPython extension directory)

Or if you wish to use your own private python distribution:

/home/homer/bin/python setup.py build
/home/homer/bin/python setup.py install

For the last case above don’t forget that boost python should have also been previously compiled with this private python distribution.

test

If you have IPython installed, the best way to test your PyTango installation is by starting the new PyTango CLI called ITango by typing on the command line:

1. IPython <= 0.10:

   $ ipython -p tango

#.IPython > 0.10:

$ ipython --profile=tango

then, in ITango type:

ITango <homer:10000> [1]: PyTango.Release.version
              Result [1]: '7.2.3'

(if you are wondering, ITango automaticaly does import PyTango for you!)

If you don’t have IPython installed, to test the installation start a python console and type:

>>> import PyTango
>>> print PyTango.Release.version
7.2.3