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SIVO Python Distribution (SIVO-PyD)

VERSION 23  Click to view document history
Created on: Jun 7, 2011 3:31 PM by Jules Kouatchou - Last Modified:  Mar 30, 2015 1:04 PM by Jules Kouatchou
SIVO-PyD is a self-contained Python distribution that includes a set of Python related packages for scientific computing. It attempts to provide a simple and but robust alternative to the Enthought Python Distribution.



All the packages in SIVO-PyD are automatically (using a script) installed without many any modification to the source codes. New packages or new versions of existing ones can be added to the distribution by only editing the installation script.



a set of Python related packages for
scientific computing. It attempts to provide a simple and but robust
alternative to the Enthought Python Distribution
SIVO-PyD contains the following packages:


nose Alternate test discovery and running process for unittest.1.3.4
mockLibrary for testing in Python.1.0.1
bitarrayProvides an object type which efficiently represents an array of booleans.0.3.5

Provides a library of classes that client code uses to construct the grammar

directly in Python code.

Cython C extensions for the Python language.0.22

The fundamental package needed for scientific computing with Python.

Provides convenient and fast N-dimensional array manipulation.

ipython Provides a rich toolkit to help you make the most out of using Python interactively.3.0.0
scipyPython package for mathematics, science and engineering.0.15.1
ffnet Feed-forward neural network training solution for Python.0.6.2

Command-line program for     plotting profile, layer and earth view data sets from

CloudSat, CALIPSO     and Aqua MODIS products.

dbfpyModule for reading and writing DBF-files.2.2.5

Module that allows you to use ODBC to connect to almost any database from

Windows, Linux, OS/X, and more

pygrads Python interface to GrADS.1.1.7
pyhdfInterface           to the NCSA HDF4 library.0.8.3
h5pyInterface to the HDF5 binary data format.2.4.0
netCDF4Interface to the netCDF 4 data format.0.9.9

Python package for the creation, manipulation, and study of the structure, dynamics,

and functions of complex networks.

wxPythonGUI Toolkit for Python.
PyYAMLYAML parser and emitter for Python3.09
PILPython Imaging Library to add image processing capabilities to you Python interpreter.1.1.7
matplotlibPython 2D plotting library.1.4.3
basemapLibrary for plotting 2D data on maps in Python1.0.6
psycopg2 PostgreSQL adapter for Python.2.4
PyNIOPython package providing read and/or write access to a variety of data formats.1.4.1

Python language module used to visualize scientific data, with an emphasis

on high quality 2D visualizations.

mpy4py 1.3

Provides bindings of the Message Passing Interface (MPI) standard for the

Python programming language, allowing any Python program to exploit multiple processors.


Python module integrating classic machine learning algorithms in the

tightly-knit scientific Python world.

pycurl Python interface to libcurl.7.19.0
Jinja2Full featured template engine for Python.2.7.3

Open source version of the scalable, non-blocking web server and tools

that powerFriendFeed.

pyzmq Python bindings for zeromq.14.5.0
SimPyAn object-oriented, process-based discrete-event simulation language for Python.0.7.2
wsgirefA standard interface between web server software and web applications written in Python.0.1.2
eofsA Python package for EOF analysis of spatial-temporal data.0.4.0
PlotlyPlotting library for collaborative, interactive, web-based, pubication-quality graphs.0.5.4
pep8Tool to check your Python code against some of the style conventions in PEP
pykeIntroduces a form of Logic Programming (inspired by Prolog) to the Python community by providing a knowledge-based inference engine (expert system). 1.1.1
sixPprovides utility functions for smoothing over the differences between the Python versions 2 and 3).1.9.0
pyshpPure Python read/write support for ESRI Shapefile format.1.2.1
CartopyMake drawing maps for data analysis and visualisation as easy as possible.0.11.x
IrisTool for analysing and visualising meteorological and oceanographic data sets.1.7.3
seawaterPython re-write of the CSIRO seawater toolbox (SEAWATER-3.3) for calculating the properties of sea water. 3.3.2
pygribPython GRIB reader.1.9.8
virtualenvTool to create isolated Python environments.1.11.5


The first versions of SIVO-PyD were installed on discover using the modules:
  • other/comp/gcc-4.5
  • lib/mkl-


We have started using other versions of the gcc compiler and the MKL library.



In case you are looking for a specific version of the distribution, type the command


module avail


to identify the version you are interested in.


After you load a particular version of SIVO-PyD, you can issue the command:




to have the names (together with the versions) of all the Python related packages installed in the distribution.


Note that SIVO-PyD was designed and developed for a specific set of users (who made the request). Changes in the distribution may occur at anytime to meet the requirements of those users.


As of March 30, 2015, the following "main" versions of the distribution are available on SLES11:

  • 1.1.2 (has problems reading netCDF-3 files)
  • 1.1.2_un (can read netCDF-3 files. We had to install Python netCDF4 0.8.1 instead of 0.9.3 as in 1.1.2)
  • 1.4.0: same as 1.1.2 but added NCL, PyNIO and PyNGL. NCL was installed manually and we are not sure if we will continue to support it (together with PyNGL).
  • 1.6.0: same as 1.1.2 but changed the version of SciPy (now 0.11.0rc2) and added MPICH2 1.4.1p1 and mpi4pi 1.3.
  • 1.7.0: same as 1.6.0 (without MPICH2 and mpi4pi) but wxPython is now version and added scikit-learn 0.12.1.
  • 1.9.0: same as 1.7.0 but with a new version of iPython (0.13.1) and added zeromq 3.2.2, pyzmq, pycurl 7.19.0, tornado 2.4.1 and Jinja2 2.6. The key feature of this version is the ability to use iPython Notebook.
  • 1.10.0: same as 1.9.0 but with EOS2 and MKL
  • 1.23.0: Added Cartopy, Iris, pygrib, seawater, etc


We installed the distribution with ATLAS instead of Intel MKL. By using ATLAS we were able to properly build some internal packages of  SciPy. The module that you use with the ATLAS features is (no need to load any MKL module):







Reported users of SIVO-PyD are from Code 606, Code 610.1, Code 610.3, Code 663.0, and Code 587.0.
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