https://github.com/kdheepak/fono

Find number of optimal order from websites considering shipping costs
https://github.com/kdheepak/fono

Last synced: about 1 month ago
JSON representation

Find number of optimal order from websites considering shipping costs

• Host: GitHub
• URL: https://github.com/kdheepak/fono
• Owner: kdheepak
• License: bsd-3-clause
• Created: 2016-03-09T23:59:13.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2016-04-19T21:23:02.000Z (over 8 years ago)
• Last Synced: 2024-11-17T04:27:58.147Z (about 2 months ago)
• Language: Python
• Homepage:
• Size: 486 KB
• Stars: 2
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# fono - Find Optimal Number of Orders

Pyomo python program to find number of optimal order from websites including shipping costs (MILP)

![](https://raw.githubusercontent.com/kdheepak89/fono/master/screenshots/screenshot1.png)

## Install

    pip install fono

    pip install fono --upgrade

### Dependencies

* Install [`glpk`](https://www.gnu.org/software/glpk/)

        brew install glpk # osx

## Run

* Run the following to find the optimal order using input from individual files

        fono --quantity fono/data/quantity.csv --price fono/data/price.csv --shipping fono/data/shipping.csv

OR

* Run the following to find the optimal order using input in a folder

        fono --folder fono/data

![](https://raw.githubusercontent.com/kdheepak89/fono/master/screenshots/screenshot2.png)

Use help

    fono --help

Three files are required to find the optimal order

* prices.csv

* quantity.csv

* shipping.csv

Prices contains the price of an item when purchased from a website.

Quantity contains the number of items required.

Shipping contains the shipping cost from the individual websites.

## Troubleshooting

* Names of items in quantity.csv has to match prices.csv

* Names of websites in shipping.csv has to match prices.csv

* Remove all empty lines

## Contribution

Feel free to submit a pull request.

Thanks to Matt for the inspiration.