pytwinnet

Name	pytwinnet JSON
Version	0.1.2 JSON
	download
home_page	None
Summary	PyTwinNet: Wireless Digital Twin & Network Optimization Library
upload_time	2025-09-02 20:40:33
maintainer	None
docs_url	None
author	None
requires_python	>=3.9
license	MIT
keywords	wireless digital twin network optimization simulation ris 5g wi-fi
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # 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

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.

## Step 3: Ensure `__version__` is exposed

In `pytwinnet/__init__.py`:

```python
__version__ = "0.1.0"

from .core.digital_twin import DigitalTwin
from .core.network import Network
from .core.node import WirelessNode, TransceiverProperties


            

Raw data

            {
    "_id": null,
    "home_page": null,
    "name": "pytwinnet",
    "maintainer": null,
    "docs_url": null,
    "requires_python": ">=3.9",
    "maintainer_email": null,
    "keywords": "wireless, digital twin, network optimization, simulation, RIS, 5G, Wi-Fi",
    "author": null,
    "author_email": "Oluwaseyi Giwa <giwaoluwaseyi130@gmail.com>",
    "download_url": "https://files.pythonhosted.org/packages/51/49/028968053bdfed29e5d03c7e4fa2de2d1ab91c8f5d5a8f3aeb7ef83488a9/pytwinnet-0.1.2.tar.gz",
    "platform": null,
    "description": "# PyTwinNet\r\n\r\nWireless **Digital Twin** & **Network Optimization** library for research and prototyping.\r\n\r\n## Install\r\n\r\n```bash\r\npip install pytwinnet                 # core\r\npip install pytwinnet[accel,cli]      # with Numba + CLI\r\npip install pytwinnet[all]            # everything (dev/docs too)\r\n\r\n\r\n## Quickstart\r\n\r\nimport pytwinnet as ptn\r\nfrom pytwinnet.physics import Environment, FreeSpacePathLoss\r\n\r\ntwin = ptn.DigitalTwin()\r\ntwin.set_environment(Environment(dimensions_m=(300,300,30)))\r\ntwin.set_propagation_model(FreeSpacePathLoss())\r\n\r\n\r\n\r\n### `LICENSE`\r\nUse MIT (or your preferred). MIT example is fine.\r\n\r\n## Step 3: Ensure `__version__` is exposed\r\n\r\nIn `pytwinnet/__init__.py`:\r\n\r\n```python\r\n__version__ = \"0.1.0\"\r\n\r\nfrom .core.digital_twin import DigitalTwin\r\nfrom .core.network import Network\r\nfrom .core.node import WirelessNode, TransceiverProperties\r\n\r\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "PyTwinNet: Wireless Digital Twin & Network Optimization Library",
    "version": "0.1.2",
    "project_urls": null,
    "split_keywords": [
        "wireless",
        " digital twin",
        " network optimization",
        " simulation",
        " ris",
        " 5g",
        " wi-fi"
    ],
    "urls": [
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "608b13e09ae3ad6b5454ce56a6ee852ffda3311fb45b7b7870609e2085583c1a",
                "md5": "4896a9b19ed656c64cbba5a9cd1d916f",
                "sha256": "d8e822f78ea765f81b644c92acfa864ffdfc35ea988d800aee13026c59e41e34"
            },
            "downloads": -1,
            "filename": "pytwinnet-0.1.2-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "4896a9b19ed656c64cbba5a9cd1d916f",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.9",
            "size": 44370,
            "upload_time": "2025-09-02T20:40:30",
            "upload_time_iso_8601": "2025-09-02T20:40:30.166351Z",
            "url": "https://files.pythonhosted.org/packages/60/8b/13e09ae3ad6b5454ce56a6ee852ffda3311fb45b7b7870609e2085583c1a/pytwinnet-0.1.2-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "5149028968053bdfed29e5d03c7e4fa2de2d1ab91c8f5d5a8f3aeb7ef83488a9",
                "md5": "88c9d8e8416f38c930c9ad4f5942bfac",
                "sha256": "9727b680b688a10a643b0c59b0a3c13303f8270988e2daa552e8670a75f0f632"
            },
            "downloads": -1,
            "filename": "pytwinnet-0.1.2.tar.gz",
            "has_sig": false,
            "md5_digest": "88c9d8e8416f38c930c9ad4f5942bfac",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.9",
            "size": 35916,
            "upload_time": "2025-09-02T20:40:33",
            "upload_time_iso_8601": "2025-09-02T20:40:33.329118Z",
            "url": "https://files.pythonhosted.org/packages/51/49/028968053bdfed29e5d03c7e4fa2de2d1ab91c8f5d5a8f3aeb7ef83488a9/pytwinnet-0.1.2.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-09-02 20:40:33",
    "github": false,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "lcname": "pytwinnet"
}