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        "author": "Larry Hastings",
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            "License :: OSI Approved :: BSD License",
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        "description": "# perky\n\n## A friendly, easy, Pythonic text file format\n\n##### Copyright 2018-2019 by Larry Hastings\n\n\n### Overview\n\nPerky is a new, simple \"rcfile\" text file format for Python programs.\n\nThe following are Perky features:\n\n#### Perky syntax\n\nPerky configuration files look something like JSON without the\nquoting.\n\n    example name = value\n    example dict = {\n        name = 3\n        another name = 5.0\n        }\n    example list = [\n        a\n        b\n        c\n        ]\n    # lines starting with hash are ignored\n\n    # blank lines are ignored\n\n    \" quoted name \" = \" quoted value \"\n\n    triple quoted string = \"\"\"\n\n        indenting\n            is preserved\n\n        the string is automatically outdented\n        to the leftmost character of the ending\n        triple-quote\n\n        <-- aka here\n        \"\"\"\n\n#### Explicit transformation is better than implicit\n\nOne possibly-surprising design choice of Perky: the only\nnatively supported values for the Perky parser are dicts,\nlists, and strings.  Other commonly-used types (ints, floats,\netc) are handled using a different mechanism: _transformation._\n\nA Perky transformation takes a dict as input, and transforms\nthe contents of the dict based on a _schema_.  A Perky schema\nis a dict with the same general shape as the dict produced\nby the Perky parse, but it contains dicts, lists,\nand *transformation functions*.\nIf you want *myvalue* in `{'myvalue':'3'}` to be a real integer,\ntransform it with the schema `{'myvalue': int}`.\n\n### API\n\n`perky.loads(s) -> d`\n\nParses a string containing Perky-file-format settings.\nReturns a dict.\n\n`perky.load(filename, encoding=\"utf-8\") -> d`\n\nParses a file containing Perky-file-format settings.\nReturns a dict.\n\n`perky.dumps(d) -> s`\n\nConverts a dictionary to a Perky-file-format string.\nKeys in the dictionary must all be strings.  Values\nthat are not dicts, lists, or strings will be converted\nto strings using str.\nReturns a string.\n\n`perky.dump(filename, d, encoding=\"utf-8\")`\n\nConverts a dictionary to a Perky-file-format string\nusing `perky.dump`, then writes it to *filename*.\n\n`perky.map(d, fn) -> o`\n\nIterates over a dictionary.  Returns a new dictionary where,\nfor every *value*:\n  * if it is a dict, replace with a new dict.\n  * if it is a list, replace with a new list.\n  * if it is neither a dict nor a list, replace with\n    `fn(value)`.\n\nThe function passed in is called a *conversion function*.\n\n`perky.transform(d, schema, default=None) -> o`\n\nRecursively transforms a Perky dict into some other\nobject (usually a dict) using the provided schema.\nReturns a new dict.\n\nA *schema* is a data structure matching the general expected\nshape of *d*, where the values are dicts, lists, and\ncallables.  The transformation is similar to `perky.map()`\nexcept that individual values will have individual conversion\nfunctions.  Also, a schema conversion function can be specified\nfor any value in *d*, even dicts or lists.\n\n*default* is a default conversion function.  If there is a\nvalue *v* in *d* that doesn't have an equivalent entry in *schema*,\nand *v* is neither a list nor a dict, and if *default* is\na callable, *v* will be replaced with `default(v)` in the\noutput.\n\n`perky.Required`\n\nExperimental.\n\n`perky.nullable(fn) -> fn`\n\nExperimental.\n\n`perky.const(fn) -> o`\n\nExperimental.\n\n\n### TODO\n\n* Backslash quoting currently does \"whatever your version of Python does\".  Perhaps this should be explicit, and parsed by Perky itself?\n",
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