Metadata-Version: 2.4
Name: pytwinnet
Version: 0.1.3
Summary: PyTwinNet: Wireless Digital Twin & Network Optimization Library
Author-email: Oluwaseyi Giwa <giwaoluwaseyi130@gmail.com>
License: MIT
Keywords: wireless,digital twin,network optimization,simulation,RIS,5G,Wi-Fi
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: System :: Networking
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: numpy>=1.23
Requires-Dist: matplotlib>=3.6
Provides-Extra: accel
Requires-Dist: numba>=0.58; extra == "accel"
Provides-Extra: cli
Requires-Dist: PyYAML>=6.0.1; extra == "cli"
Provides-Extra: docs
Requires-Dist: sphinx>=7; extra == "docs"
Requires-Dist: sphinx-rtd-theme>=2.0.0; extra == "docs"
Requires-Dist: myst-parser>=2.0.0; extra == "docs"
Provides-Extra: dev
Requires-Dist: pytest>=7; extra == "dev"
Requires-Dist: pytest-cov>=4; extra == "dev"
Requires-Dist: black>=24.4; extra == "dev"
Requires-Dist: isort>=5.13; extra == "dev"
Requires-Dist: flake8>=7.0; extra == "dev"
Requires-Dist: pre-commit>=3.6; extra == "dev"
Provides-Extra: dashboard
Requires-Dist: streamlit>=1.38; extra == "dashboard"
Requires-Dist: plotly>=5.24; extra == "dashboard"
Provides-Extra: rl
Requires-Dist: gymnasium>=0.29; extra == "rl"
Requires-Dist: tqdm>=4.66; extra == "rl"
Provides-Extra: all
Requires-Dist: pytwinnet[accel,cli,dashboard,dev,docs,rl]; extra == "all"

# PyTwinNet

Wireless **Digital Twin** & **Network Optimization** library for research and prototyping.

## Install

```bash
pip install pytwinnet                 # core
pip install pytwinnet[accel,cli]      # with Numba + CLI
pip install pytwinnet[all]            # everything (dev/docs too)
```

## Quickstart
```python
import pytwinnet as ptn
from pytwinnet.physics import Environment, FreeSpacePathLoss

twin = ptn.DigitalTwin()
twin.set_environment(Environment(dimensions_m=(300,300,30)))
twin.set_propagation_model(FreeSpacePathLoss())
```


### `LICENSE`
Use MIT (or your preferred). MIT example is fine.

## Creating your first Wireless Digital Twin
```python
from .core.digital_twin import DigitalTwin
from .core.network import Network
from .core.node import WirelessNode, TransceiverProperties
```

