amplpy

Python API for AMPL

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Project description

AMPL API is an interface that allows developers to access the features of the AMPL interpreter from within a programming language. All model generation and solver interaction is handled directly by AMPL, which leads to great stability and speed; the library just acts as an intermediary, and the added overhead (in terms of memory and CPU usage) depends mostly on how much data is read back from AMPL, the size of the model as such is irrelevant. Functions for directly assigning data to AMPL parameters and sets are provided, which can be used instead of the normal AMPL data reading procedures. AMPL API has been written with usability in mind, and it is easy to access its functionalities from C++, Java, C#, MATLAB, R and Python.

The AMPL API can function as an add-on to any existing AMPL installation. If you do not yet have an AMPL installation on the computer where you will be working with the API, see our demo page or trial page to download a working version that can be installed quickly.

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Repositories:

GitHub Repository: https://github.com/ampl/amplpy
PyPI Repository: https://pypi.python.org/pypi/amplpy

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0.14.1b0 pre-release

May 21, 2024

0.14.0

May 21, 2024

0.14.0b0 pre-release

May 21, 2024

0.13.4b0 pre-release

May 20, 2024

0.13.3

Feb 20, 2024

0.13.3b0 pre-release

Feb 20, 2024

0.13.2

Jan 5, 2024

0.13.2b1 pre-release

Feb 20, 2024

0.13.2b0 pre-release

Jan 5, 2024

0.13.1

Dec 29, 2023

0.13.1b0 pre-release

Dec 29, 2023

0.13.0

Dec 26, 2023

0.13.0b0 pre-release

Dec 26, 2023

0.12.2

Dec 11, 2023

0.12.1

Sep 21, 2023

0.12.0

Aug 29, 2023

0.11.2

Jul 11, 2023

0.11.1

Jul 4, 2023

0.11.0

Jun 21, 2023

0.10.0

May 22, 2023

0.9.3

Apr 21, 2023

0.9.2

Apr 5, 2023

0.9.1

Mar 22, 2023

0.9.0

Mar 14, 2023

0.8.6

Jan 23, 2023

0.8.5

Aug 24, 2022

0.8.4

Aug 2, 2022

0.8.3

Jun 23, 2022

0.8.2

May 27, 2022

0.8.1

Jan 21, 2022

0.8.0

Dec 24, 2021

0.7.2

Dec 1, 2021

0.7.1

Jul 26, 2021

This version

0.7.0

Jan 25, 2021

0.6.11

Feb 28, 2020

0.6.10

Nov 17, 2019

0.6.7

Jun 22, 2019

0.6.6

May 11, 2019

0.6.5

Apr 14, 2019

0.6.4

Feb 13, 2019

0.6.3

Dec 4, 2018

0.6.2

Nov 20, 2018

0.6.1

Nov 13, 2018

0.6.0

Nov 4, 2018

0.5.0

May 6, 2018

0.4.1

Apr 12, 2018

0.4.0

Apr 9, 2018

0.3.4

Feb 24, 2018

0.3.3

Feb 12, 2018

0.3.2

Dec 14, 2017

0.3.1

Nov 17, 2017

0.3.0

Oct 13, 2017

0.2.0

Aug 4, 2017

0.1.2

Aug 4, 2017

0.1.1

Jul 30, 2017

0.1.0

Jul 22, 2017

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BLAKE2b-256	`4685f52554132b75640b39f6c8687db6cb0f7dd6e364244a72d69595b9b7a592`

Algorithm	Hash digest
SHA256	`7beb70336d202961fa28703018275f9f04ed2e41f65703f18929c9cd61ea8210`
MD5	`1590e30d5fb6519900fcf0b8bce21f68`
BLAKE2b-256	`3158c06d0fed448b2e25bf5a872d025a54610e07930a939bb10abf7fec9a9a55`

Algorithm	Hash digest
SHA256	`cf3265e78a3921eef85a2adb0781b6707c597db85fbc63a840448e8c8e276a62`
MD5	`418beedfe8415746d6843df134736a0a`
BLAKE2b-256	`307486d637e65d2187e80535c9d5cb08dbfde12db19e3285cad517f63c36fe8a`

Algorithm	Hash digest
SHA256	`088f08b43f16a13b5d8bff8d30268e855c74bfd326fe98f55ad8f4ebede254b5`
MD5	`595f9c5032ae184f4fc9e52900b4fca6`
BLAKE2b-256	`292dc2dce5aa326c3c047fc5bcf368bfa6b2b20aeb8da61b6d16bfc258c24079`

Algorithm	Hash digest
SHA256	`014f0073bd561dd7e78faa1679b941f351cbe2eaaa6439bce9e7950017fe2960`
MD5	`7200414d248748eca237009251f00232`
BLAKE2b-256	`715f4f422cb4769931cbb09c5c4dbab8b1085f14409b74f7a78412876c755925`

Algorithm	Hash digest
SHA256	`807ff3bfd92a794fb334b20ea0223edf14062a13c3de5b50b3669dbbf264b7a2`
MD5	`c7a6c9b06f0e1cd2088e306bb86af05c`
BLAKE2b-256	`b9d1ce410bce997585357ba2c429c37116a77f9068fdbb7279dfffbad19d35c2`