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        "author": "Jared Deckard",
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        "description": "# Marsha\n\n[![pipeline status](https://gitlab.com/deckar01/marsha/badges/master/pipeline.svg)](https://gitlab.com/deckar01/marsha/commits/master)\n[![coverage report](https://gitlab.com/deckar01/marsha/badges/master/coverage.svg)](https://gitlab.com/deckar01/marsha/commits/master)\n\nA serialization and validation library for python 3 based on the typing module.\n\n## Status\n\n### \ud83d\udd2c Experimental\n\nDon't put this code on servers. You can, but you probably shouldn't.\n\n## Documentation\n\n### \ud83d\udcd6 [https://deckar01.gitlab.io/marsha](https://deckar01.gitlab.io/marsha)\n\n## Features\n\n### \ud83d\udc82 Strictness\n\nWhen using python's builtin types for schema annotations, the data **must** be\ninstances of the specified types or the load operation will fail with an exception.\nUnexpected and missing data will error by default.\n\n### \ud83d\udd75 Clarity\n\nValidation errors mirror the structure of the data, provide insight into the values\nthat caused the error, and present meaningful information to help resolve the problem.\n\n### \ud83c\udfc3 Speed\n\nThe default functionality is fast and lean. The performance degrades gracefully as\ncomplex functionality is explicitly opted into by the developer.\n\n### \ud83e\udd38 Flexibility\n\nCustom data types are created by defining formatter classes, then transfored into\ntypes compatible with the builtin typing module.\n\n### \ud83d\udc83 Expressiveness\n\nPython's builtin typing generics can be leveraged to declare complex type unions that\nknow how to automatically handle multiple types using a syntax that is explicit and concise.\n\n## Installation\n\n```sh\npip install marsha\n```\n\n## Usage\n\n_Need to create database model instances from user input and expose them in serialized form?_\n\nCreating a schema that is separate from the model is a useful way to declare a \"view\" and\nallows defining multiple schemas to control how data is exposed in different contexts.\n\n```py\nfrom my_app.database_models import Artist, Album\n\nimport marsha\nfrom typing import List\n\n@marsha.schema(Artist)\nclass ArtistSchema:\n    name: str\n\n@marsha.schema(Album)\nclass AlbumSchema:\n    title: str\n    artists: List[Artist]\n\n# dict -> Album\nalbum = marsha.load(album_data, Album)\n# Do stuff\nalbum.save()\n# Album -> dict\nresponse_data = marsha.dump(album)\n```\n\n_Just need to validate some data and convert it to the correct type?_\n\nYou can automatically register the type annotations of any model as a schema by\nadding the `schema` decorator.\n\n```py\nimport marsha\nfrom typing import List\n\n@marsha.schema()\nclass Artist(dict):\n    name: str\n\n@marsha.schema()\nclass Album(dict):\n    title: str\n    artists: List[Artist]\n\n# dict -> dict\nalbum = marsha.load(album_data, Album)\n# Do stuff\nfirst_artist = album['artists'][0]\n```\n\n## Development\n\n### \ud83d\udcda Dependencies\n\n```sh\n# python >= 3.6\npip install -r dev-requirements.txt\n```\n\n### \ud83c\udfc5 Testing\n\n```sh\n# Quick testing.\nflake8\npytest\n# Ensure all statements and branches are covered with tests.\npytest --cov=marsha --cov-branch --cov-report html --cov-report term\n# Ensure documentations changes render correctly.\nmake html\n```",
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