PyMathProg 1.0 has just been released.
An easy and flexible mathematical programming environment for Python.
PyMathProg is a Python reincarnation of AMPL and GNU MathProg
modeling language, implemented in pure Python, connecting to GLPK via
swiglpk. Create, optimize, report, change and re-optimize your model
with Python, easily integrate database, plotting, etc.
PyMathProg provides an easy and flexible modelling syntax
using Python to create and optimize mathematical programming models.
Optimization is done by open source optimization packages such as
the GNU Linear Programming Kit (GLPK) that is made available
to PyMathProg by swiglpk.
The great features offered by PyMathProg include:
- Ergonomic syntax for modelling
- Friendly interactive session
- Sensitivity report
- Advanced solver options
- Automatic model update on parameter changes
- Parameters sharable between models
- Deleting variables/constraints
- Supporting both Python 2 and 3
- Supporting all major platforms
pip install pymprog
That’s it. Since it is a pure Python project that only depends on swiglpk,
it can be installed this way wherever swiglpk can be installed.
Currently, swiglpk comes with binary wheels for Windows, Mac, and Linux.
If you’d like to have PyMathProg installed on other platforms,
the only hurdle to overcome is to get swiglpk installed there first.
from pymprog import *
x, y = var('x, y') # variables
maximize(15 * x + 10 * y, 'profit')
x <= 3 # mountain bike limit
y <= 4 # racer production limit
x + y <= 5 # metal finishing limit
Help in the following ways are more than welcome:
- tutorials and samples.
- bug reports
- feature requests
- code contribution
I hope you will find it useful. Thank you!