from .CQiClient import CQiClient
from .CQi import CONST_FIELD_MATCH, CONST_FIELD_MATCHEND
import time
from app import logger  # only works if imported into opaque web app


class CQiWrapper(CQiClient):
    """
    CQIiWrapper object

    High level wrapper that groups and renames some functions of CQiClient
    for ease of use. Also structures recieved data into python dictionaries.

    Keyword arguments:
    host -- host IP adress or hostname wher the cqp server is running
    port -- port of the cqp server
    username -- username used to connect to the cqp server
    password -- password of the user to connect to the cqp server
    """

    SUBCORPUS_NAMES = []

    def __init__(self, host='127.0.0.1', port=4877, username='opaque',
                 password='opaque'):
        super(CQiWrapper, self).__init__(host=host, port=port)
        self.username = username
        self.password = password

    def connect(self):
        """
        Connect with CQP server

        Connects via socket to the CQP server using the given username and
        password from class initiation.
        """
        self.ctrl_connect(self.username, self.password)

    def __create_attribute_strings(self):
        """
        Creates all needed attribute strings to query for word, lemma etc. in
        the given corpus.
        For example: CORPUS_NAME.word to query words
        """
        p_attrs = self.corpus_positional_attributes(self.corpus_name)
        struct_attrs = self.corpus_structural_attributes(self.corpus_name)
        self.attr_strings = {}
        self.attr_strings['positional_attrs'] = {}
        self.attr_strings['struct_attrs'] = {}
        for p_attr in p_attrs:
            self.attr_strings['positional_attrs'][p_attr] = (self.corpus_name
                                                             + '.'
                                                             + p_attr)
        for struct_attr in struct_attrs:
            self.attr_strings['struct_attrs'][struct_attr] = (self.corpus_name
                                                              + '.'
                                                              + struct_attr)
        # logger.warning(('All positional and '
                        # 'structural attributes: {}').format(self.attr_strings))

    def select_corpus(self, corpus_name):
        if corpus_name in self.corpus_list_coprora():
            self.corpus_name = corpus_name
            self.__create_attribute_strings()
            # logger.warning('{} does exist.'.format(corpus_name))
        else:
            # logger.warning('{} does not exist.'.format(corpus_name))
            pass

    def disconnect(self):
        """
        Disconnect from CQP server

        Disconnects from the CQP server. Closes used socket after disconnect.
        """
        self.ctrl_bye()
        self.connection.close()
        # logger.warning('Disconnected from cqp server.')

    def query_subcorpus(self, query, result_subcorpus_name='Query-results'):
        """
        Create subcorpus

        Input query will be used to create a subcorpus holding all cpos match
        positions for that query.

        Keyword arguments:
        result_subcorpus_name -- user set name of the subcorpus which holds all
        cpos match positions, produced by the query
        query -- query written in cqp query language
        """
        self.cqp_query(self.corpus_name, result_subcorpus_name, query)
        self.result_subcorpus = (self.corpus_name
                                 + ':'
                                 + result_subcorpus_name)
        self.SUBCORPUS_NAMES.append(self.result_subcorpus)
        self.nr_matches = self.cqp_subcorpus_size(self.result_subcorpus)
        print('Nr of all matches is:', self.nr_matches)
        # logger.warning('Nr of all matches is: {}'.format(self.nr_matches))

    def show_subcorpora(self):
        """
        Show all subcorpora currently saved by the cqp server.
        """
        return self.cqp_list_subcorpora(self.corpus_name)

    def show_query_results(self,
                           context_len=10,
                           result_len=1000,
                           result_offset=0):
        """
        Show query results

        Shows the actual matched strings produce by the query. Uses the cpos
        match indexes to grab those strings. saves them into an orderd
        dictionary. Also saves coresponding tags, lemmas and context. Gets those
        informations using the corresponding cpos.

        Keyword arguments:
        context_len -- defines how many words before and after a match will be
        shown (default 10)
        result_len -- defines how many results are actually grabbed
        """
        self.context_len = context_len
        self.corpus_max_len = self.cl_attribute_size(
                                   self.attr_strings['positional_attrs']['word']
                              )
        self.nr_matches = min(result_len, self.nr_matches)
        if self.nr_matches == 0:
            # logger.warning('Query resulted in 0 matches.')
            return None
        else:
            # Get match cpos boundries
            # match_boundries shows the start and end cpos of one match as a
            # pair of cpositions
            # [(1355, 1357), (1477, 1479)] Example for two boundry pairs
            offset_start = 0 + (result_offset + 1) if result_offset != 0 else result_offset
            offset_end = self.nr_matches + result_offset
            match_boundaries = zip(self.cqp_dump_subcorpus(self.result_subcorpus,
                                                           CONST_FIELD_MATCH,
                                                           offset_start,
                                                           offset_end),
                                   self.cqp_dump_subcorpus(self.result_subcorpus,
                                                           CONST_FIELD_MATCHEND,
                                                           offset_start,
                                                           offset_end))

        # Generate all cpos between match boundries including start and end boundries.
        # Also generate cpos for left and right context.
        # Save those cpos into dict as lists for the keys 'lc', 'hit' and 'rc'
        # Also collect all cpos together in one list for the final request of
        # all cpos informations
        all_matches = []
        all_cpos = []
        for start, end in match_boundaries:
            lc_cpos = list(range(max([0, start - self.context_len]), start))
            lc = {'lc': lc_cpos}
            match_cpos = list(range(start, end + 1))
            match = {'hit': match_cpos}
            rc_cpos = list(range(end, min([self.corpus_max_len, end + self.context_len])))
            rc = {'rc': rc_cpos}
            lc.update(match)
            lc.update(rc)
            all_cpos.extend(lc_cpos + match_cpos + rc_cpos)
            all_matches.append(lc)
        # print(all_matches)
        # print(all_cpos)

        # Get all cpos for all sneteces boundries
        # s_lookup = {}
        # for s_id in set(s_ids):
        #     s_start, s_end = self.cl_struc2cpos('UTOPIEN.s', s_id)
        #     # CHANGE to UTOPIEN.s will always be like this in nopaque
        #     s_cpos = range(s_start, s_end)
        #     s_lookup.update({s_id: list(s_cpos)})
        #     # print(list(s_cpos))
        #     all_cpos.extend(s_cpos)
        t0 = time.time()
        all_cpos = list(set(all_cpos)) # get rid of cpos duplicates
        t1 = time.time()
        t_total = t1 - t0
        print('TIME FOR ALL CPOS:', t_total)
        print('CPOS SUM:', len(all_cpos))

        # Get cpos informations like CORPUS_NAME.word or CORPUS_NAME.lemma for
        # all cpos entries in all_cpos_list
        # Also saves these informations into self.results dict
        t6 = time.time()
        all_cpos_infos, text_lookup = self.get_cpos_infos(all_cpos)
        t7 = time.time()
        t_final = t7 - t6
        print('GOT ALL RESULTS IN:', t_final)

        self.results = {'matches': all_matches, 'cpos_lookup': all_cpos_infos,
                        'text_lookup': text_lookup}
        return self.results

    def get_cpos_infos(self, all_cpos):
        '''
        Get cpos informations like CORPUS_NAME.word or CORPUS_NAME.lemma for
        all cpos entries specified in the parameter all_cpos.
        '''
        # Get all positional attribute informations
        cpos_infos = {}
        for p_attr_key in self.attr_strings['positional_attrs'].keys():
            match_strs = self.cl_cpos2str(self.attr_strings['positional_attrs'][p_attr_key], all_cpos)
            cpos_infos[p_attr_key] = match_strs

        # Get all strucutural attribute informations
        tmp_info = {}
        structs_to_check = []
        for struct_attr_key in self.attr_strings['struct_attrs'].keys():
            key = self.attr_strings['struct_attrs'][struct_attr_key]
            has_value = self.corpus_structural_attribute_has_values(key)
            struct_ids = self.cl_cpos2struc(key, all_cpos)
            if has_value is False:  # Get IDs of strucutural elements without values (this means get IDs of XML tags. Struct elements only have values if they are XML attributes)
                tmp_info[struct_attr_key] = []
                for id in struct_ids:
                    tmp_info[struct_attr_key].append(id)
            else:
                structs_to_check.append({key: struct_attr_key})
        struct_attr_values = list(tmp_info.values())
        struct_attr_keys = list(tmp_info.keys())

        # Build textlookup dictionary
        text_lookup_ids = list(set(struct_attr_values[0]))  # First is always one text
        text_lookup = {}
        for d in structs_to_check:
            s_key, s_value = zip(*d.items())
            s_value = s_value[0].split('_')[1]
            struct_values = self.cl_struc2str(s_key[0], text_lookup_ids)
            zipped = dict(zip(text_lookup_ids, struct_values))
            for zip_key, zip_value in zipped.items():
                check = text_lookup.get(zip_key)
                if check is None:
                    text_lookup[zip_key] = {s_value: zip_value}
                else:
                    text_lookup[zip_key].update({s_value: zip_value})

        # zip keys and values together
        attr_values_list = []
        attr_keys_list = []
        for key in cpos_infos.keys():
            attr_values_list.append(cpos_infos[key])
            attr_keys_list.append(key)
        attr_keys_list.extend(struct_attr_keys)
        attr_values_list.extend(struct_attr_values)
        joined_cpos_infos = zip(all_cpos, *attr_values_list)
        dict_cpos_infos = {}
        for info in joined_cpos_infos:
            dict_cpos_infos[info[0]] = dict(zip(attr_keys_list, info[1:]))
        return dict_cpos_infos, text_lookup