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https://github.com/connor-makowski/gloop

https://github.com/connor-makowski/gloop

Science Score: 26.0%

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    Low similarity (14.5%) to scientific vocabulary
Last synced: 11 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: connor-makowski
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 585 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 1
  • Releases: 2
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

Gloop

License: MIT PyPI version Github Documentation

Generalized Linear Object Oriented Programming (GLOOP) as a simple pythonic interface for OOP access to PULP. It features simple objects, helpful methods, and additional error checking that simplifies code and streamlines development.

Gloop also happens to be synonymous with the word "pulp" in the English language.

Why use Gloop?

  • Simple: Gloop is simple and easy to use.
  • Object Oriented: Gloop is object oriented by design.
  • Error Checking: Gloop has additional error checking to help you catch mistakes early.
    • This includes checking for duplicate names, invalid constraints, passed types, and more.
  • Intuitive: Gloop is intuitive
  • Unique: Gloops is unique in nature and can help you think differently about how you code for linear programming.

Setup

pip install gloop

Getting Started

gloop is a package designed for object oriented linear programming access to pulp. Technical docs can be found here.

Bare Bones Example

```py import gloop

Create a variable

myvariable = gloop.Variable(name='myvariable_name', lowBound=0)

Create a model

mymodel = gloop.Model(name="mymodel_name", sense="maximize")

Add an objective for the model

mymodel.addobjective(fn=my_variable)

Add a constraint to the model

mymodel.addconstraint(name="myconstraintname", fn=my_variable <= 5)

Solve the model

my_model.solve()

Get the results

mymodel.showoutputs()

=> {'status': 'Optimal', 'objective': 5.0, 'variables': {'myvariablename': 5.0}}

```

Example

Transportation Problem

A product is manufactured in two assembly plants and sold in three regions. Monthly demand per region is shared in Table 1. Currently, assembly plants have no capacity restrictions and can source as many items as needed. Transportation costs (USD)0.12 per unit per mile.

Table 1: Demand in units

Demand Region 1 Region 2 Region 3
Units per month 2500 4350 3296

Table 2: Distance in Miles

Miles Region 1 Region 2 Region 3
Assembly Plant 1 105 256 108
Assembly Plant 2 240 136 198

Formulate a model using the available information. Your goal is to minimize the total transportation cost.

```py

Transportation Problem

import gloop

############# DATA

Transportation data

transport = [ {"originname": "A1", "destinationname": "R1", "distance": 105}, {"originname": "A1", "destinationname": "R2", "distance": 256}, {"originname": "A1", "destinationname": "R3", "distance": 108}, {"originname": "A2", "destinationname": "R1", "distance": 240}, {"originname": "A2", "destinationname": "R2", "distance": 136}, {"originname": "A2", "destinationname": "R3", "distance": 198}, ]

Loop through the transport data to create variables and calculate cost

for t in transport: # Create decision variables for each item in transport t["amt"] = gloop.Variable( name=f"{t['originname']}{t['destinationname']}__amt", lowBound=0 ) # Calculate the variable cost of shipping for each item in tranport t["cost"] = t["distance"] * 0.12

Demand data

demand = [ {"name": "R1", "demand": 2500}, {"name": "R2", "demand": 4350}, {"name": "R3", "demand": 3296}, ]

############# Model

Initialize the model

mymodel = gloop.Model(name="transportationexample", sense="minimize")

Add the Objective Fn

mymodel.addobjective(fn=gloop.Sum([t["amt"] * t["cost"] for t in transport]))

Add Constraints

Demand Constraint

for d in demand: mymodel.addconstraint( name=f"{d['name']}_demand", fn=gloop.Sum( [t["amt"] for t in transport if t["destinationname"] == d["name"]] ) >= d["demand"], )

Solve the model

my_model.solve()

############# OUTPUT

Show the outputs

mymodel.showoutputs() #=>

{'objective': 145208.16,

'status': 'Optimal',

'variables': {'A1R1amt': 2500.0,

'A1R2amt': 0.0,

'A1R3amt': 3296.0,

'A2R1amt': 0.0,

'A2R2amt': 4350.0,

'A2R3amt': 0.0}}

```

Owner

  • Name: Connor Makowski
  • Login: connor-makowski
  • Kind: user
  • Location: Cambridge, MA

Cave Lab Project Manager and Digital Learning Lead at MIT

GitHub Events

Total
  • Create event: 6
  • Release event: 2
  • Issues event: 1
  • Delete event: 2
  • Push event: 11
  • Pull request event: 3
Last Year
  • Create event: 6
  • Release event: 2
  • Issues event: 1
  • Delete event: 2
  • Push event: 11
  • Pull request event: 3

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 14
  • Total Committers: 1
  • Avg Commits per committer: 14.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 14
  • Committers: 1
  • Avg Commits per committer: 14.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Connor Makowski c****8@g****m 14

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 1
  • Total pull requests: 4
  • Average time to close issues: N/A
  • Average time to close pull requests: less than a minute
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 4
  • Average time to close issues: N/A
  • Average time to close pull requests: less than a minute
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
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  • connor-makowski (1)
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  • connor-makowski (4)
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Packages

  • Total packages: 1
  • Total downloads:
    • pypi 17 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 5
  • Total maintainers: 1
pypi.org: gloop

Generalized Linear Object Oriented Programming (GLOOP)

  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 17 Last month
Rankings
Dependent packages count: 9.6%
Average: 31.9%
Dependent repos count: 54.3%
Maintainers (1)
connor
Last synced: 11 months ago