sdk.py
Python optimization SDK (by opvious)
python-mip
Python-MIP: collection of Python tools for the modeling and solution of Mixed-Integer Linear programs (by coin-or)
sdk.py | python-mip | |
---|---|---|
3 | 1 | |
8 | 507 | |
- | 2.0% | |
8.3 | 7.1 | |
6 months ago | 2 months ago | |
Python | Python | |
Apache License 2.0 | Eclipse Public License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
sdk.py
Posts with mentions or reviews of sdk.py.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-11-01.
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Opvious - deploy optimization models with just a few lines of code
I’m excited to introduce opvious, a Python SDK which enables you to build, validate, and deploy optimization models!
- Show HN: Opvious, a batteries-included optimization platform
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opvious.io - an API-first platform for deploying optimization models
If you are interested in trying it out, the best place to get started is the welcome guide which walks through an interactive end-to-end example (no account required). You can also browse all available interactive examples here or check out the Python SDK here.
python-mip
Posts with mentions or reviews of python-mip.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-20.
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Ask HN: Do you use an optimization solver? Which one? Why? Do you like it?
I've been using CBC via python-mip (https://github.com/coin-or/python-mip). It's great because it's got a super clean interface (milp variables/expressions/constraints), the code is quite accessible, and it's low overhead which makes it good for solving many very small problems.
Community sentiment seems to be beginning to shift toward favouring the HiGHS solver (https://github.com/ERGO-Code/HiGHS) over CBC. Something I'm keeping a close eye on.
nextmv seems to pitch itself as a generic solving ("decision automation") platform or something (unclear). But it seems that the only fleshed out product offering is for vehicle routing, based on the docs. Are there plans to offer, for instance, a solver binary that can be used to solve generic problems?
Also all the github repos under https://github.com/nextmv-io are private, so links from docs are 404.
What are some alternatives?
When comparing sdk.py and python-mip you can also consider the following projects:
notebooks - Optimization notebooks
or-tools - Google's Operations Research tools: