https://github.com/freewheel/flipy

A Python linear programming interface library
https://github.com/freewheel/flipy

cbc gurobi linear-programming pulp python solver

Last synced: 9 months ago
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A Python linear programming interface library

• Host: GitHub
• URL: https://github.com/freewheel/flipy
• Owner: freewheel
• License: apache-2.0
• Created: 2020-01-29T22:21:24.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2022-03-18T04:30:07.000Z (almost 4 years ago)
• Last Synced: 2025-01-10T03:19:27.577Z (about 1 year ago)
• Topics: cbc, gurobi, linear-programming, pulp, python, solver
• Language: Python
• Homepage: https://freewheel.github.io/flipy
• Size: 12.5 MB
• Stars: 25
• Watchers: 7
• Forks: 3
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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README

          
# Flipy

![flipy_logo_60pt](https://user-images.githubusercontent.com/1311594/73421313-6cea4500-42f3-11ea-9ea7-25a0af70ac4f.png)

[![supported](https://img.shields.io/pypi/pyversions/flipy.svg)](https://pypi.python.org/pypi/flipy/)

[![Build Status](http://img.shields.io/travis/freewheel/flipy.svg?style=flat-square)](https://travis-ci.com/freewheel/flipy) 

[![Coverage](https://coveralls.io/repos/github/freewheel/flipy/badge.svg?branch=master)](https://coveralls.io/github/freewheel/flipy)

Flipy is a Python linear programming interface library, originally developed by [FreeWheel](https://freewheel.com). It currently supports Gurobi and CBC as the backend solver.

To use Gurobi, make sure you have a Gurobi license file, and gurobipy is installed in your Python environment. You can find details from [Gurobi’s documentation](https://www.gurobi.com/documentation/8.1/quickstart_mac/the_gurobi_python_interfac.html).

Flipy requires Python 3.6 or newer.

## Installation

The latest offical version of Flipy can be installed with `pip`:

```

pip install flipy

```

The latest development version can be get with Git:

```

git clone https://github.com/freewheel/flipy.git

cd flipy

python setup.py install

```

## Quickstart

Here is a simple example for Flipy:

```python

import flipy

# 1 <= x <= 3.5

x = flipy.LpVariable('x', low_bound=1, up_bound=3.5)

# 2 <= y <= 4

y = flipy.LpVariable('y', low_bound=2, up_bound=4)

# 5x + y <= 12

lhs = flipy.LpExpression('lhs', {x: 2.5, y: 1})

rhs = flipy.LpExpression('rhs', constant=12) 

constraint = flipy.LpConstraint(lhs, 'leq', rhs)

# maximize: 3x + 2y

objective = flipy.LpObjective('test_obj', {x: 3, y: 2}, sense=flipy.Maximize)

problem = flipy.LpProblem('test', objective, [constraint])

solver = flipy.CBCSolver()

status = solver.solve(problem)

```

## Get the solution 

After solving, a status is returned to indicate whether the solver has found a optimal solution for the problem:

```python

print(status)

# 

```

The objective value can be retrieved with `objective.evaluate()`:

```python

print(objective.evaluate())

# 17.6

```

The value of variables can be retrieved with `.evaluate()` as well:

```python

print(x.evaluate())

# 3.2

print(y.evaluate())

# 4.0

```