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unified-planning

Unified Planning Framework

unified-planning v1.3.0 124.9K downloads/30d#11,848 on PyPI
Permissive license APACHE AGING released

What it is and what it does

Unified Planning is a framework for expressing automated planning problems in Python using standard representations like STRIPS and RDDL. It abstracts away the complexity of problem formulation, allowing developers and researchers to define planning domains, actions, fluents, and goals in a high-level Python API, then invoke automated planners to solve them.

The library depends on pyparsing for parsing, networkx for graph operations, and ConfigSpace for configuration handling. It targets researchers and developers working on AI planning, constraint satisfaction, and automated reasoning. The package is in Alpha development status and supports Python 3.8, 3.9, 3.10, and 3.11.

Use it for:

  • Formulate and test STRIPS-based planning problems without writing domain-specific planner syntax
  • Prototype automated planning solutions for robotics, scheduling, or resource allocation tasks
  • Integrate RDDL probabilistic planning domains into Python applications
  • Conduct research on planning algorithms by providing a unified problem representation interface

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Unified Planning provides a Python library for formulating automated planning problems and invoking planners to solve them, supporting STRIPS and RDDL problem representations.

Yes, if you need to formulate and solve automated planning problems in Python. The low install friction, permissive Apache license, and support for standard planning representations make it suitable for research and prototyping. The aging maintenance status is a minor concern—verify that external planner backends you need are still supported before committing to production use.

Install

unified-planning on PyPI

pip

pip install unified-planning

uv

uv add unified-planning

poetry

poetry add unified-planning

Installing unified-planning

Before you install

Low install friction with a pure-Python wheel distribution. Maintenance status is aging at 240 days since last release, though the package remains active.

License in practice

Licensed under Apache (permissive), allowing commercial use, modification, and distribution with minimal restrictions—suitable for most production and research contexts.

Quickstart

pip install unified-planning

from unified_planning.shortcuts import Problem, Fluent, InstantaneousAction

problem = Problem("my_planning_problem")
# Define fluents, actions, and goals to formulate a planning problem

Requires Python 3.8 or later; external automated planners may need separate installation depending on intended use.

Verify before relying

  • Whether the package actively maintains compatibility with planner backends or if external planner installation is required
  • Current state of documentation and community support given aging maintenance signal
  • Specific capabilities and limitations of STRIPS and RDDL support in this version

Package facts

License APACHE (permissive)
Python support supports the current Python release (>=3.8)
Install friction low — pure-Python wheel
Runtime dependencies 3 — pyparsing, networkx, ConfigSpace
Maintenance aging — 240 days since the last release
First released
Downloads 124,885/month — #11,848 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: unified_planning-1.3.0-py3-none-any.whl

Keywords: planning, logic, STRIPS, RDDL

Development Status :: 3 - AlphaIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/Engineering :: Artificial Intelligence

Tags

automated planning librarySTRIPS planningRDDL planningplanning problem formulationplanner invocation frameworkAI planninglogic-based planning
planningconstraint-solvingai-research

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Further reading