{ "info": { "author": "qeds Data", "author_email": "admin@qedsdata.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Education", "Intended Audience :: Science/Research", "License :: OSI Approved :: BSD License", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3 :: Only", "Topic :: Database :: Front-Ends", "Topic :: Education" ], "description": "qeds\n====\n\nThis package provides a simplified interface to datasets that we use\nfrequently.\n\nLoading data\n------------\n\nTo see a list of available datasets run\n\n.. code:: python\n\n import qeds\n qeds.data.available()\n\nTo load one of the listed datasets run\n\n.. code:: python\n\n df = qeds.data.load(\"dataset_name\")\n\nwhere ``dataset_name`` is replaced by one of the names returned by\n``qeds.data.available()``.\n\nWhen you first load a dataset, qeds will fetch the data from\nsomewhere online. It will then save a local copy of the data to your\nhard drive. Subsequent requests to load a dataset (even in different\npython sessions) will first attempt to load the data from your hard\ndrive and only fetch from online if necessary.\n\nConfiguration\n-------------\n\nThe qeds library is configurable. Below is a listing of available\nconfiguration options.\n\nTo see a list of valid configuration options run\n\n.. code:: python\n\n import qeds\n qeds.data.config.describe_options()\n\nTo set a configuration use\n``valourm.data.options[section.option] = value``.\n\nFor example, to set the configuration option for the BLS api_key I would\ncall:\n\n.. code:: python\n\n import qeds\n qeds.data.options[\"bls.api_key\"] = \"MY_API_KEY\"\n\nDeveloper docs\n--------------\n\nContributing datasets\n~~~~~~~~~~~~~~~~~~~~~\n\nTo contribute a dataset you need to implement a function\n``_retrieve_{name}`` inside the file ``data/retrieve.py``. 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