{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/18"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/9"}],"enrichment":{"capability":"amplpy is a Python interface to AMPL, an algebraic modeling language for optimization problems, allowing you to define, solve, and extract results from large-scale linear, nonlinear, and mixed-integer optimization models.","skillfed_tags":["optimization","mathematical-modeling","solver-interface"],"use_cases":["Portfolio optimization: define variance minimization with weight constraints, pass covariance matrices from pandas, solve with Gurobi.","Supply chain planning: model production, inventory, and distribution constraints in AMPL, feed demand forecasts from Python, retrieve optimal schedules.","Engineering design: set up nonlinear constraint systems, optimize over continuous or discrete variables, integrate results into a larger Python application.","Research and prototyping: quickly iterate on optimization formulations without rewriting solver interfaces for each model variant.","Production deployment: use the same AMPL model across Python, C++, or other languages by switching only the API layer."],"what_it_does":"amplpy is a Python binding for AMPL, a domain-specific language for mathematical optimization. It lets you express optimization problems\u2014linear, nonlinear, mixed-integer\u2014using natural mathematical syntax within Python, then solve them with industry-standard solvers like Gurobi, HiGHS, or CBC. The library handles model generation and solver communication directly in AMPL's optimized C code, so you get performance without sacrificing readability.\n\nYou define models using AMPL's syntax (passed as strings), populate them with data from Python lists, pandas DataFrames, or numpy arrays, call solve(), and extract results back into Python objects. This workflow is especially useful for large-scale optimization where you want the stability and speed of compiled solvers but the flexibility of Python for data preprocessing and post-processing.","worth_installing":"Yes, if you need to solve optimization problems and want a mature, language-agnostic modeling layer. The active maintenance, broad Python version support, and permissive license make it a solid choice. Caveat: you must install a solver separately and obtain an AMPL license (free Community Edition available); this adds setup friction beyond a typical pip install."},"id":"amplpy","links":{"html":"https://skillfed.io/packages/amplpy","md":"https://skillfed.io/packages/amplpy.md","pypi":"https://pypi.org/project/amplpy/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-21","license_spdx":null,"license_treatment":"permissive","name":"amplpy","python_support":"unspecified","summary":"Python API for AMPL"},"popularity":{"monthly_downloads":75216,"position":14738,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.18.0"}