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        "author": "Bruno Alano Medina",
        "author_email": "bruno@neurologic.com.br",
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        "description": "<h1 align=\"center\">aiotf</h1>\n\n<div align=\"center\">\n  <strong>Asyncio-based <code>Tensorflow Serving</code> Prediction</strong>\n</div>\n\n<br />\n\n<div align=\"center\">\n  <!-- Build Status -->\n  <a href=\"https://travis-ci.org/brunoalano/aiotf\">\n    <img src=\"https://img.shields.io/travis/brunoalano/aiotf/master.svg?style=flat-square\"\n      alt=\"Build Status\" />\n  </a>\n\n  <!-- Test Coverage -->\n  <a href=\"https://codecov.io/github/brunoalano/aiotf\">\n    <img src=\"https://img.shields.io/codecov/c/github/brunoalano/aiotf/master.svg?style=flat-square\"\n      alt=\"Test Coverage\" />\n  </a>\n\n  <!-- Downloads !-->\n  <a href=\"http://pepy.tech/badge/aiotf\">\n    <img src=\"http://pepy.tech/badge/aiotf\"\n      alt=\"Downloads\" />\n  </a>\n</div>\n\n## Features\n- __asyncio:__ better use of your cpu idle time\n- __pep8 compliant:__ following best code standards\n- __high-performance prediction:__ we use `aio-grpc`\n\n## Example\n```python\nimport aiotf\n\nasync def make_prediction(model_name: str, data):\n  async with aiotf.AsyncTensorflowServing('localhost:9000') as client:\n    predictions = await client.predict(model_name, data)\n```\nYou can find more examples in the `examples/` subdirectory.\n\n\n## Installation\n```sh\n$ pip install aiotf\n```\n\n## License\n[MIT](https://tldrlegal.com/license/mit-license)\n\n\n",
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