| Name | phare JSON |
| Version |
0.0.3
JSON |
| download |
| home_page | |
| Summary | Asynchronous and ergonomic Project Lighthouse client library |
| upload_time | 2023-12-23 18:20:42 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.9 |
| license | MIT License Copyright (c) 2023 fwcd Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
project-lighthouse
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Phare
[](https://pypi.org/project/phare)
[](https://github.com/fwcd/phare/actions/workflows/build.yml)
An asynchronous and ergonomic client library for the Project Lighthouse API.
## Example
```python
import asyncio
import numpy as np
import os
from phare.auth import Auth
from phare.lighthouse import Lighthouse
from phare.constants import LIGHTHOUSE_FRAME_SHAPE, LIGHTHOUSE_URL
async def main():
user = os.environ['LIGHTHOUSE_USER']
token = os.environ['LIGHTHOUSE_TOKEN']
url = os.environ.get('LIGHTHOUSE_URL', LIGHTHOUSE_URL)
async with await Lighthouse.connect(Auth(user, token), url) as lh:
frame = np.random.randint(0, 255, size=LIGHTHOUSE_FRAME_SHAPE, dtype=np.uint8)
await lh.put_model(frame)
asyncio.run(main())
```
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