Merge pull request #91 from aebrahim/v0.3_dev

0.3.0b1

.gitignore

@@ -4,8 +4,12 @@ gurobi.log
 documentation
 cobra.egg-info
 build/
+dist/
 .DS_Store
 setuptools-*egg
 setuptools-*.tar.gz
 cobra/solvers/cglpk.c
-cobra/solvers/cglpk.so
+cobra/solvers/cglpk*so
+glpk.h
+libglpk.a
+.idea/

.travis.yml

@@ -1,16 +1,15 @@
 language: python
-#python:
-# - "2.6"
-# - "2.7"
+python:
+ - "2.7"
+ - "3.3"
+ - "3.4"
 # command to install dependencies
-virtualenv:
-  system_site_packages: true
 before_install:
-  - sudo apt-get install libglpk-dev python-scipy libgmp-dev
+  - sudo apt-get install libglpk-dev libgmp-dev
+  - export PIP_OPTS="-f https://pypi.drosophi.la --no-index"
+  - if [[ $TRAVIS_PYTHON_VERSION == 2* ]]; then pip install glpk $PIP_OPTS; fi
+  - pip install python-libsbml-experimental cython numpy scipy $PIP_OPTS
 install:
-  - ln -s /usr/lib/python2.7/dist-packages/scipy ~/virtualenv/python2.7/lib/python2.7/site-packages/
-  - pip install http://clostridium.ucsd.edu/python_libsbml_experimental-5.9.2-cp27-none-linux_x86_64.whl
-  - pip install glpk cython
   - python setup.py develop
 # # command to run tests
 script: python setup.py test

INSTALL.md

@@ -1,168 +1,83 @@
-Installation instructions for Python and Jython are detailed below. The 
-Python instructions will be approrpriate for most users. For installation 
-help, please use the [Google Group](http://groups.google.com/group/cobra-pie).
+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/)
 
 --------------------------------------------------------------------------------
 
-# Python
-All releases require Python 2.7 to be installed before proceeding. 
+All releases require Python 2.7 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](http://www.python.org/download/releases/2.7.6/).
 
-Generally, installation should follow these steps:
+Python 3 support is still considered experimental.
 
-1. Install cobrapy (either the stable, development, or hacking version).
-2. Install an appropriate solver
-3. Install optional dependencies
-4. Test your installation
+#Installation of cobrapy
 
+## Stable version installation
+On Mac OS X or GNU/Linux, first [install pip]
+(http://pip.readthedocs.org/en/latest/installing.html).
+Afterwards, run this command in a terminal:
 
-## Stable version installation in Python
-On Mac OS X or GNU/Linux, use easy_install (or pip if you have it) by running
-the following command in a terminal.
-
-    sudo easy_install cobra
+    sudo pip install cobra
 
 For Windows, download and install the appropriate 32 bit or 64 bit installer,
 both of which can be downloaded from the [python package
 index](https://pypi.python.org/pypi/cobra/).
 
-## Development version installation in Python
-Use easy_install (or pip if you have it)
 
-    sudo easy_install https://github.com/opencobra/cobrapy/archive/master.zip
+## Hacking version installation
+Use pip to install [Cython](http://cython.org/). Install libglpk using your
+package manger. This would be ```brew install glpk``` on a Mac and
+```sudo apt-get install libglpk-dev``` on debian-based systems (including
+Ubuntu and Mint). This can also be installed by compiling GLPK from source.
 
-## Hacking version installation in Python
-First, clone the git repository using your preferred mothod. Cloning from your
+Clone the git repository using your preferred mothod. Cloning from your
 own [github fork](https://help.github.com/articles/fork-a-repo) is recommended!
-Afterwards, open a terminal, enter the cobrapy repository and run the following command:
+Afterwards, open a terminal, enter the cobrapy repository and run the following
+command:
 
     python setup.py develop --user
 
-If the command fails with an error about the --user option not being recognized,
-it means setuptools is not installed. Either install setuptools before
-trying again, or instead run ```sudo python setup.py develop```
+# 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, from binary installers, or from package managers.
+
+1. [libsbml](http://sbml.org) >= 5.10 to read/write SBML files
+  * [Windows installer](http://www.lfd.uci.edu/~gohlke/pythonlibs/#libsbml)
+  * Use ```sudo pip install python-libsbml-experimental``` on Mac/Linux
+2. [numpy](http://numpy.org) >= 1.6.1 for double_deletion_analysis
+  * [Windows installer](http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy)
+3. [scipy](http://scipy.org) >= 0.11 for ArrayBasedModel and saving to *.mat files.
+  * [Windows 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 cobrapy supports these linear
+programming solvers:
+
+ * ILOG/CPLEX
+  [Academic](https://www.ibm.com/developerworks/university/academicinitiative/)
+  [Commercial](http://www.ibm.com/software/integration/optimization/cplex-optimizer/)
+ * [gurobi](http://gurobi.com)
+ * GLPK through [pyGLPK](http://tfinley.net/software/pyglpk/)
 
-## Installation of a Solver in Python
-Currently cobrapy supports three linear programming solvers: ILOG/CPLEX, 
-Gurobi, and GLPK (through [pyGLPK](http://tfinley.net/software/pyglpk/)). 
 ILOG/CPLEX and Gurobi are commercial software packages that, currently, 
 provide free licenses for academics and support both linear and quadratic 
 programming. GLPK is an opensource linear programming solver; however, it 
 does not support quadratic programming and is not as robust as the 
 commercial solvers when it comes to mixed-integer linear programming.
 
-### Installation of a commercial solver in Python
-See the linked instructions for each solver
-* [ILOG/CPLEX Academic](https://www.ibm.com/developerworks/university/academicinitiative/)
-* [ILOG/CPLEX Commercial](http://www.ibm.com/software/integration/optimization/cplex-optimizer/)
-* [Gurobi Academic & Commercial](http://gurobi.com)
-
-### Installation of pyGLPK in Python
-Please note that pyGLPK is not the same as python-glpk.
-
-#### GNU/Linux Installation of pyGLPK in Python
-1. Install the glpk and gmp library packages. You will need the development 
-versions if they are available. You will also need development headers for 
-Python itself. For example, Ubuntu and Debian Wheezy (7.0) users would type the following into the 
-command line:
-```
-    sudo apt-get install libglpk-dev libgmp-dev python-dev python-setuptools
-```
-Debian Squeeze (6.0) users will need to build libgmp from source.
-
-2. install pyglpk with easy_install using the following command in the terminal:
-```
-    sudo easy_install glpk 
-```
-
-#### MAC OS X Installation of pyGLPK in Python
-1. Install homebrew if you don't have it. This may require downloading Xcode 
-from the AppStore and Command Line Tools for XCode from 
-https://developer.apple.com/devcenter/mac/index.action. If you're already 
-using macports then just use that to install glpk.
-```
-    brew install glpk
-```
-
-2. install pyglpk with easy_install using the following command in the terminal:
-```
-    sudo easy_install glpk
-```
-
-#### Windows Installation of pyGLPK in Python
-Download and install the executable from [here](https://sourceforge.net/projects/opencobra/files/python/cobra/extras/pyGLPK/).
-
-## Installation of Optional Dependencies
-Installation instructions are not provided for these libraries. However, 
-many of them can be easily built on GNU/Linux with easy_install. On windows, 
-many can downloaded from [this site](http://www.lfd.uci.edu/~gohlke/pythonlibs/).
-
-1. [libsbml](http://sbml.org) >= 4.0 to read/write SBML files
-  * [Windows installer](http://www.lfd.uci.edu/~gohlke/pythonlibs/#libsbml)
-2. [numpy](http://numpy.org) >= 1.6.1 and [scipy](http://scipy.org) >= 0.11 for 
-ArrayBasedModel, double_deletion analysis, and saving to MAT formats.
-  * Windows installers for 
-  [numpy](http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy) and 
-  [scipy](http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy)
-3. [Parallel Python](http://parallelpython.org) for parallel processing.
-4. [MATLAB](http://mathworks.com) and 
-[mlabwrap](http://mlabwrap.sourceforge.net) for connecting to the COBRA 
-Toolbox for MATLAB.
-  * Installation is tricky on most platforms.
 
-
-
-## Testing your installation
+# Testing your installation
 1. Start python
 2. Type the following into the Python shell
 
 ```python
 from cobra.test import test_all
 test_all()
 ```
-
---------------------------------------------------------------------------------
-
-
-#INSTALLATION - Jython
-All releases require Jython (2.5+).  JSBML (http://sbml.org) is required for reading / writing SBML files.
-NOTE: ArrayBasedModel, double_deletion analysis, saving to MAT formats, parallel processing,  and connecting to the
-COBRA Toolbox for MATLAB are currently unavailable when using Jython.
-
-I. Releases - Hosted on http://opencobra.sourceforge.net
-   A. Download the most recent bzipped archive.
-   B. Unzip the archive and make sure that the toplevel directory is in your Java CLASSPATH.
-   C. Install a linear programming solver (Section III).
-
-II. Development Code - Hosted on github
-  NOTE: Not intended for general users.  Some functions require advanced capabilities / settings.  Unless you're
-  willing to deal with headaches and heartaches it's better to install one of the releases.
-  1. git pull https://github.com/opencobra/cobrapy.git
-  2. Add the cobrapy directory to your Java CLASSPATH.
-  3. Install a linear programming solver (Section III).
-
-III. Installation of linear programming solvers
-    On Jython, cobrapy currently supports two linear programming solvers: ILOG/CPLEX and Gurobi.
-
-    A. ILOG/CPLEX and Gurobi are commercial software packages that, currently, provide free licenses for academics and
-    support both linear and quadratic programming.
-        1. Please download the software from their respective sites, install according to their instructions, and make
-        sure that their Java jars are in your Java CLASSPATH.
-        2. Current links are listed below. If they don't work then search using google.
-          * [ILOG/CPLEX Academic](https://www.ibm.com/developerworks/university/academicinitiative/)
-          * [ILOG/CPLEX Commercial](http://www.ibm.com/software/integration/optimization/cplex-optimizer/)
-          * [Gurobi Academic & Commercial](http://gurobi.com)
-
-    B. GLPK:  We are exploring the possibility of using GLPK through [GLPK for Java](http://glpk-java.sourceforge.net);
-    however, we've encountered irregular memory errors that we'll need to trace before listing it as a supported solver.
-    Advanced users may try http://glpk-java.sourceforge.net at their own risk.
-
-IV. Test your installation.
-  A. Start Jython
-  B. Enter: from cobra.test import test_all
-  C. Enter: test_all()

cobra/VERSION

@@ -1 +1 @@
-0.3.0.dev
+0.3.0b1

cobra/__init__.py

@@ -1,22 +1,17 @@
-import sys
-from version import get_version
+# set the warning format to be on a single line
+import warnings as _warnings
+def _warn_format(message, category, filename, lineno, file=None, line=None):
+    return "%s:%s %s: %s\n" % (filename, lineno, category.__name__, message)
+_warnings.formatwarning = _warn_format
+
+from .version import get_version
 __version__ = get_version()
-from os import name as __name
-from core import Object, Formula, Metabolite, Gene, Reaction, Model, DictList, Species
-if __name == 'java':
-    #raise Exception("Experimental modules of numpy/scipy for java that are" +\
-    #"not yet ready for prime time.")
-    #import oven.danielhyduke.jython.numpy as numpy
-    #import oven.danielhyduke.jython.scipy as scipy
-    from warnings import warn
-    warn("COBRA for Python is not optimized for JAVA.  If it's slow or crashes consider increasing JVM memory")
-else:
-    try:
-        from core import ArrayBasedModel
-    except Exception, e:
-        from warnings import warn
-        warn("cobra.ArrayBasedModel class is unavailable: %s"%repr(e))
+from .core import Object, Formula, Metabolite, Gene, Reaction, Model, DictList, Species
+from . import io, flux_analysis
+
+try:
+    from .core import ArrayBasedModel
+except ImportError:
+    None
 
-del __name, get_version
-__doc__ = """
-"""
+del get_version