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        "description": "# dictionaryutils\n\npython wrapper and metaschema for datadictionary.\nIt can be used to:\n- load a local dictionary to a python object.\n- dump schemas to a file that can be uploaded to s3 as an artifact.\n- load schema file from an url to a python object that can be used by services\n\n## Test for dictionary validity with Docker\nSay you have a dictionary you are building locally and you want to see if it will pass the tests.\n\nYou can add a simple alias to your `.bash_profile` to enable a quick test command:\n```\ntestdict() { docker run --rm -v $(pwd):/dictionary quay.io/cdis/dictionaryutils:master; }\n```\n\nThen from the directory containing the `gdcdictionary` directory run `testdict`.\n\n\n## Generate simulated data with Docker\nIf you wish to generate fake simulated data you can also do that with dictionaryutils and the data-simulator.\n\n```\nsimdata() { docker run --rm -v $(pwd):/dictionary -v $(pwd)/simdata:/simdata quay.io/cdis/dictionaryutils:master /bin/sh -c \"cd /dictionary && python setup.py install --force; python /src/datasimulator/bin/data-simulator simulate --path /simdata/ $*; export SUCCESS=$?; rm -rf build dictionaryutils dist gdcdictionary.egg-info; chmod -R a+rwX /simdata; exit $SUCCESS\"; }\nsimdataurl() { docker run --rm -v $(pwd):/dictionary -v $(pwd)/simdata:/simdata quay.io/cdis/dictionaryutils:master /bin/sh -c \"python /src/datasimulator/bin/data-simulator simulate --path /simdata/ $*; chmod -R a+rwX /simdata\"; }\n\n```\n\nThen from the directory containing the `gdcdictionary` directory run `simdata` and a folder will be created called `simdata` with the results of the simulator run. You can also pass in additional arguments to the data-simulator script such as `simdata --max_samples 10`.\n\nThe `--max_samples` argument will define a default number of nodes to simulate, but you can override it using the `--node_num_instances_file` argument. For example, if you create the following `instances.json`:\n\n```\n{\n        \"case\": 100,\n        \"demographic\": 100\n}\n\n```\nThen run the following:\n```\ndocker run --rm -v $(pwd):/dictionary -v $(pwd)/simdata:/simdata quay.io/cdis/dictionaryutils:master /bin/sh -c \"cd /dictionary && python setup.py install --force; python /src/datasimulator/bin/data-simulator simulate --path /simdata/ --program workshop --project project1 --max_samples 10 --node_num_instances_file instances.json; export SUCCESS=$?; rm -rf build dictionaryutils dist gdcdictionary.egg-info; chmod -R a+rwX /simdata; exit $SUCCESS\";\n```\nThen you'll get 100 each of `case` and `demographic` nodes and 10 each of everything else. Note that the above example also defines `program` and `project` names.\n\nYou can also run the simulator for an arbitrary json url by using `simdataurl --url https://datacommons.example.com/schema.json`.\n\n\n## Use dictionaryutils to load a dictionary\n```\nfrom dictionaryutils import DataDictionary\n\ndict_fetch_from_remote = DataDictionary(url=URL_FOR_THE_JSON)\n\ndict_loaded_locally = DataDictionary(root_dir=PATH_TO_SCHEMA_DIR)\n```\n\n## Use dictionaryutils to dump a dictionary\n```\nimport json\nfrom dictionaryutils import dump_schemas_from_dir\n\nwith open('dump.json', 'w') as f:\n    json.dump(dump_schemas_from_dir('../datadictionary/gdcdictionary/schemas/'), f)\n```\n",
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