Metadata-Version: 2.4
Name: semantic_world
Version: 0.0.3
Summary: A world model that unifies kinematic information and semantic meaning for robotic world representations.
Author-email: Tom Schierenbeck <tom_sch@uni-bremen.de>
License: LGPL-3.0-only
Project-URL: Source, https://github.com/tomsch420/semantic_world
Project-URL: Bug Tracker, https://github.com/tomsch420/semantic_world/issues
Keywords: robotics
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: rustworkx
Requires-Dist: numpy
Requires-Dist: trimesh
Requires-Dist: typing_extensions
Requires-Dist: urdf-parser-py
Requires-Dist: matplotlib
Requires-Dist: casadi~=3.7.0
Requires-Dist: hypothesis
Requires-Dist: pytest
Requires-Dist: scipy
Requires-Dist: ormatic>=1.1.10
Requires-Dist: sqlacodegen
Requires-Dist: ripple_down_rules>=0.6.51
Requires-Dist: pytest-order
Requires-Dist: sqlalchemy
Requires-Dist: embreex
Requires-Dist: rtree
Requires-Dist: random_events
Requires-Dist: plotly
Requires-Dist: rtree
Requires-Dist: daqp
Requires-Dist: pathlib
Requires-Dist: probabilistic_model
Provides-Extra: gui
Requires-Dist: ripple_down_rules[gui]; extra == "gui"
Dynamic: license-file

# Welcome to the Semantic World Package

The semantic world is a Python package for querying and manipulating robot simulation data.  
It originates from PyCRAM's abstract world and unifies the functionality needed by multiple packages.

# User Installation


You can install the package directly from PyPI:

```bash
pip install -U semantic_world
```

# Contributing

If you are interested in contributing, you can check out the source code from GitHub:

```bash
git clone https://github.com/cram2/semantic_world.git
```

# Tests
The tests can be run using `pytest` after installing the package.

```bash
pytest test/
```

# Documentation

You can read the official documentation [here](https://cram2.github.io/semantic_world/intro.html)!
