from __future__ import with_statement
import json
from rdflib import ConjunctiveGraph
from rdflib.compare import isomorphic
from rdflib_jsonld._compat import IS_PY3
from rdflib_jsonld.parser import to_rdf
from rdflib_jsonld.serializer import from_rdf
from rdflib_jsonld.keys import CONTEXT, GRAPH


# monkey-patch NTriplesParser to keep source bnode id:s ..
from rdflib.plugins.parsers.ntriples import NTriplesParser, r_nodeid, bNode
def _preserving_nodeid(self):
    if not self.peek('_'):
        return False
    return bNode(self.eat(r_nodeid).group(1))
NTriplesParser.nodeid = _preserving_nodeid
# .. and accept bnodes everywhere
_uriref = NTriplesParser.uriref
def _uriref_or_nodeid(self):
    return _uriref(self) or self.nodeid()
NTriplesParser.uriref = _uriref_or_nodeid


TC_BASE = "http://json-ld.org/test-suite/tests/"


def do_test_json(cat, num, inputpath, expectedpath, context, options):
    base = TC_BASE + inputpath
    input_obj = _load_json(inputpath)
    input_graph = ConjunctiveGraph()
    to_rdf(input_obj, input_graph, base=base, context_data=context,
            produce_generalized_rdf=True)
    expected_json = _load_json(expectedpath)
    use_native_types = True # CONTEXT in input_obj
    result_json = from_rdf(input_graph, context, base=TC_BASE + inputpath,
            use_native_types=options.get('useNativeTypes', use_native_types),
            use_rdf_type=options.get('useRdfType', False))

    def _prune_json(data):
        if CONTEXT in data:
            data.pop(CONTEXT)
        if GRAPH in data:
            data = data[GRAPH]
        #def _remove_empty_sets(obj):
        return data

    expected_json = _prune_json(expected_json)
    result_json = _prune_json(result_json)

    _compare_json(expected_json, result_json)


def do_test_parser(cat, num, inputpath, expectedpath, context, options):
    input_obj = _load_json(inputpath)
    expected_graph = _load_nquads(expectedpath)
    base = TC_BASE + inputpath
    result_graph = ConjunctiveGraph()
    to_rdf(input_obj, result_graph, base=base, context_data=context,
            produce_generalized_rdf = options.get('produceGeneralizedRdf', False))
    assert isomorphic(
            result_graph, expected_graph), "Expected:\n%s\nGot:\n%s" % (
            expected_graph.serialize(format='turtle'),
            result_graph.serialize(format='turtle'))


def do_test_serializer(cat, num, inputpath, expectedpath, context, options):
    input_graph = _load_nquads(inputpath)
    expected_json = _load_json(expectedpath)
    result_json = from_rdf(input_graph, context, base=TC_BASE + inputpath,
            use_native_types=options.get('useNativeTypes', False),
            use_rdf_type=options.get('useRdfType', False))
    _compare_json(expected_json, result_json)


def _load_nquads(source):
    graph = ConjunctiveGraph()
    with open(source) as f:
        data = f.read() if IS_PY3 else f.read().decode('utf-8')
    graph.parse(data=data, format='nquads')
    return graph


def _load_json(source):
    with open(source) as f:
        return json.load(f)


def _to_ordered(obj):
    if isinstance(obj, list):
        # NOTE: use type in key to handle mixed
        # lists of e.g. bool, int, float.
        return sorted((_to_ordered(lv) for lv in obj),
                key=lambda x: (_ord_key(x), type(x).__name__))
    if not isinstance(obj, dict):
        return obj
    return sorted((k, _to_ordered(v))
            for k, v in obj.items())


def _ord_key(x):
    if isinstance(x, dict) and '@id' in x:
        return x['@id']
    else:
        return x


def _dump_json(obj):
    return json.dumps(obj,
            indent=4, separators=(',', ': '),
            sort_keys=True, check_circular=True)


def _compare_json(expected, result):
    expected = json.loads(_dump_json(expected))
    result = json.loads(_dump_json(result))
    assert _to_ordered(expected) == _to_ordered(result), \
            "Expected JSON:\n%s\nGot:\n%s" % (
                    _dump_json(expected), _dump_json(result))