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        "author": "Luca Cappelletti",
        "author_email": "cappelletti.luca94@gmail.com",
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        "description": "keras_ding\n=========================================================================================\n|travis| |sonar_quality| |sonar_maintainability| |codacy| |code_climate_maintainability| |pip| |downloads|\n\nKeras callback for playing a sound when training is complete.\n\nHow do I install this package?\n----------------------------------------------\nAs usual, just download it using pip:\n\n.. code:: shell\n\n    pip install keras_ding\n\nThe callback is based upon the `python package playsound <https://github.com/TaylorSMarks/playsound>`_, which required\na little additional setup for getting it started. Do check out its documentation to get started.\n\nOn macOs it boils down to installing `pyobjc`, as follows:\n\n.. code:: shell\n\n    pip install pyobjc\n\nTests Coverage\n----------------------------------------------\nSince some software handling coverages sometime get slightly different results, here's three of them:\n\n|coveralls| |sonar_coverage| |code_climate_coverage|\n\nUsage examples\n-----------------------------------------------\nSo suppose you have your keras model `my_keras_model` and you want to hear a sound when it is done training.\nHere you go:\n\n.. code:: python\n\n    from keras_ding import Ding\n\n    my_keras_model.fit(\n        x, y,\n        callbacks=[\n            Ding()\n        ]\n    )\n\nWhat acount a custom sound? Just pass it as an argument.\n\n.. code:: python\n\n    from keras_ding import Ding\n\n    my_keras_model.fit(\n        x, y,\n        callbacks=[\n            Ding(path=\"my_custom_sound.mp3\")\n        ]\n    )\n\n\n.. |travis| image:: https://travis-ci.org/LucaCappelletti94/keras_ding.png\n   :target: https://travis-ci.org/LucaCappelletti94/keras_ding\n   :alt: Travis CI build\n\n.. |sonar_quality| image:: https://sonarcloud.io/api/project_badges/measure?project=LucaCappelletti94_keras_ding&metric=alert_status\n    :target: https://sonarcloud.io/dashboard/index/LucaCappelletti94_keras_ding\n    :alt: SonarCloud Quality\n\n.. |sonar_maintainability| image:: https://sonarcloud.io/api/project_badges/measure?project=LucaCappelletti94_keras_ding&metric=sqale_rating\n    :target: https://sonarcloud.io/dashboard/index/LucaCappelletti94_keras_ding\n    :alt: SonarCloud Maintainability\n\n.. |sonar_coverage| image:: https://sonarcloud.io/api/project_badges/measure?project=LucaCappelletti94_keras_ding&metric=coverage\n    :target: https://sonarcloud.io/dashboard/index/LucaCappelletti94_keras_ding\n    :alt: SonarCloud Coverage\n\n.. |coveralls| image:: https://coveralls.io/repos/github/LucaCappelletti94/keras_ding/badge.svg?branch=master\n    :target: https://coveralls.io/github/LucaCappelletti94/keras_ding?branch=master\n    :alt: Coveralls Coverage\n\n.. |pip| image:: https://badge.fury.io/py/keras-ding.svg\n    :target: https://badge.fury.io/py/keras-ding\n    :alt: Pypi project\n\n.. |downloads| image:: https://pepy.tech/badge/keras-ding\n    :target: https://pepy.tech/badge/keras-ding\n    :alt: Pypi total project downloads \n\n.. |codacy|  image:: https://api.codacy.com/project/badge/Grade/0a2a0da8f69a4d2cb0f5065cadad8c87\n    :target: https://www.codacy.com/manual/LucaCappelletti94/keras_ding?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=LucaCappelletti94/keras_ding&amp;utm_campaign=Badge_Grade\n    :alt: Codacy Maintainability\n\n.. |code_climate_maintainability| image:: https://api.codeclimate.com/v1/badges/34b3f4e943855bcc3a99/maintainability\n    :target: https://codeclimate.com/github/LucaCappelletti94/keras_ding/maintainability\n    :alt: Maintainability\n\n.. |code_climate_coverage| image:: https://api.codeclimate.com/v1/badges/34b3f4e943855bcc3a99/test_coverage\n    :target: https://codeclimate.com/github/LucaCappelletti94/keras_ding/test_coverage\n    :alt: Code Climate Coverate",
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