Difference between revisions of "Python"
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== Basics == | |||
The available installations of Python can be listed using the command | |||
module av python | |||
Currently only one Python module is available and it can be loaded using | |||
module load python/2.7.9 | |||
With this command the corresponding Intel compilers and Intel MPI will be automatically loaded. | |||
== Additional installed packages == | == Additional installed packages == | ||
The actual release contains following additional packages: | The actual release contains (among others) the following additional packages: | ||
* numpy | * numpy | ||
| Line 18: | Line 21: | ||
* PyClimate | * PyClimate | ||
== Usage of Python | A complete list of packages can be obtained with the command | ||
pip list | |||
(only after the module was loaded). Additional packages can be installed upon request, but it is also possible to install packages in your own <tt>$HOME</tt>-directory (see below). | |||
== Usage of Python and MPI == | |||
For parallel scripts the Python installtion contains the package mpi4py. To launch an parallel Python script inside an [[SGE Job Management (Queueing) System| SGE]] script please use command line | For parallel scripts the Python installtion contains the package mpi4py. To launch an parallel Python script inside an [[SGE Job Management (Queueing) System| SGE]] script please use command line | ||
mpirun | mpirun -np $NSLOTS python ''SCRIPTNAME'' ''SCRIPT_CMDLINE_OPTIONS'' | ||
to enable SGE to control all processes of your script. | to enable SGE to control all processes of your script. | ||
The corresponding parallel environment in the SGE submission script is specified by | |||
#$ -pe impi NUMBER_OF_CORES | |||
#$ -R y | |||
== Installing Packages in your HOME-Directory == | |||
Most Python packages can be installed easily using the <tt>pip</tt>-command. In that case, the <tt>--user</tt>-option allows a local user based installation. E.g., to install the package <tt>PYPACKAGE</tt> use the command (after loading the module): | |||
pip install --user PYPACKAGE | |||
If the installation is successful, the corresponding files are installed in | |||
$HOME/.local/lib/pythonx.y/site-packages | |||
where <tt>x.y</tt> corresponds to the Python version currently loaded. Also, <tt>pip list</tt> should show the new package in the list. | |||
== Profiling Python programs == | |||
Details on how to profile entire programs, particular functions and other parts of your code can be found [[Profiling_using_gprof#Profiling_Python_programs| here]]. | |||
== External links == | == External links == | ||
Latest revision as of 18:52, 22 January 2015
Basics
The available installations of Python can be listed using the command
module av python
Currently only one Python module is available and it can be loaded using
module load python/2.7.9
With this command the corresponding Intel compilers and Intel MPI will be automatically loaded.
Additional installed packages
The actual release contains (among others) the following additional packages:
- numpy
- scipy
- nose_cov
- distribute
- ScientificPython
- PyClimate
A complete list of packages can be obtained with the command
pip list
(only after the module was loaded). Additional packages can be installed upon request, but it is also possible to install packages in your own $HOME-directory (see below).
Usage of Python and MPI
For parallel scripts the Python installtion contains the package mpi4py. To launch an parallel Python script inside an SGE script please use command line
mpirun -np $NSLOTS python SCRIPTNAME SCRIPT_CMDLINE_OPTIONS
to enable SGE to control all processes of your script.
The corresponding parallel environment in the SGE submission script is specified by
#$ -pe impi NUMBER_OF_CORES #$ -R y
Installing Packages in your HOME-Directory
Most Python packages can be installed easily using the pip-command. In that case, the --user-option allows a local user based installation. E.g., to install the package PYPACKAGE use the command (after loading the module):
pip install --user PYPACKAGE
If the installation is successful, the corresponding files are installed in
$HOME/.local/lib/pythonx.y/site-packages
where x.y corresponds to the Python version currently loaded. Also, pip list should show the new package in the list.
Profiling Python programs
Details on how to profile entire programs, particular functions and other parts of your code can be found here.
