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Installation of cobrapy
=======================
For installation help, please use the `Google
Group <http://groups.google.com/group/cobra-pie>`_. For usage
instructions, please see the
`documentation <https://cobrapy.readthedocs.org/en/latest/>`_.
All releases require Python 2.7+ or 3.4+ to be installed before
proceeding. Mac OS X (10.7+) and Ubuntu ship with Python. Windows users
without python can download and install python from the `python
website <https://www.python.org/ftp/python/2.7.9/python-2.7.9.amd64.msi>`_.
Please note that though Anaconda and other python distributions may work
with cobrapy, they are not explicitly supported (yet!).
Stable version installation
~~~~~~~~~~~~~~~~~~~~~~~~~~~
cobrapy can be installed with any recent installation of pip.
Instructions for several operating systems are below:
Mac OS X or Linux
-----------------
0. `install
pip <http://pip.readthedocs.org/en/latest/installing.html>`_.
1. In a terminal, run ``sudo pip install cobra``
We highly recommend updating ``pip`` beforehand (``pip install pip --upgrade``).
Microsoft Windows
-----------------
The preferred installation method on Windows is also to use pip. The
latest Windows installers for Python 2.7 and 3.4 include pip, so if you
use those you will already have pip.
1. In a terminal, run ``C:\Python27\Scripts\pip.exe install cobra`` (you
may need to adjust the path accordingly).
To install without pip, you will need to download and use the
appropriate installer for your version of python from the `python
package index <https://pypi.python.org/pypi/cobra/>`_.
Installation for development
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Get the `detailed contribution instructions <CONTRIBUTING.rst>`_ for contributing to cobrapy.
Installation of optional dependencies
=====================================
Optional Dependencies
~~~~~~~~~~~~~~~~~~~~~
On windows, these can downloaded from [this site]
(http://www.lfd.uci.edu/~gohlke/pythonlibs/). On Mac/Linux, they can be
installed using pip, or from the OS package manager (e.g brew, apt,
yum).
1. `libsbml <http://sbml.org>`_ >= 5.10 to read/write SBML level 2
files
- `Windows libsbml installer <http://www.lfd.uci.edu/~gohlke/pythonlibs/#libsbml>`_
- Use ``sudo pip install python-libsbml`` on Mac/Linux
2. `lxml <http://lxml.de/>`_ to speed up read/write of SBML level 3 files.
3. `numpy <http://numpy.org>`_ >= 1.6.1 for double deletions
- `Windows numpy installer <http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy>`_
4. `scipy <http://scipy.org>`_ >= 0.11 for ArrayBasedModel and saving to \*.mat files.
- `Windows scipy installer <http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy>`_
Other solvers
~~~~~~~~~~~~~
cobrapy comes with bindings to the GNU Linear Programming Kit ([glpk]
(http://www.gnu.org/software/glpk/)) using its own bindings called
"cglpk" in cobrapy. In addition, cobrapy currently supports these linear
programming solvers:
- ILOG/CPLEX (available with
`Academic <https://www.ibm.com/developerworks/university/academicinitiative/>`_
and
`Commercial <http://www.ibm.com/software/integration/optimization/cplex-optimizer/>`_
licenses).
- `gurobi <http://gurobi.com>`_
- `QSopt\_ex
esolver <http://www.dii.uchile.cl/~daespino/ESolver_doc/main.html>`_
- `MOSEK <http://www.mosek.com/>`_
- `coin-or clp and cbc <http://coin-or.org/>`_ through
`cylp <https://github.com/coin-or/CyLP>`_.
ILOG/CPLEX, MOSEK, and Gurobi are commercial software packages that
currently provide free licenses for academics and support both linear
and quadratic programming. GLPK and clp are open source linear
programming solvers; however, they may not be as robust as the
commercial solvers for mixed-integer and quadratic programming.
QSopt\_ex esolver is also open source, and can solve linear programs
using rational operations, giving exact solutions.
Testing your installation
=========================
1. Start python
2. Type the following into the Python shell
.. code:: python
from cobra.test import test_all
test_all()
You should see some skipped tests and expected failures, and the
function should return ``False``.
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