import argparse
import csv
import os

from lxml import etree, objectify, html


def write_general_statistics(path, out_list):
    if len(out_list) == 0:
        return
    with open(path, 'w') as csvfile:
        writer = csv.writer(csvfile, delimiter='\t',
                                quotechar='"')
        writer.writerow(['Semantic role', 'Valency pattern ratio', 'Valency sentence ratio'])
        for line in out_list:
            writer.writerow(line)


def write_statistics(path, out_list):
    if len(out_list) == 0:
        return
    with open(path, 'w') as csvfile:
        writer = csv.writer(csvfile, delimiter='\t',
                            quotechar='"')
        writer.writerow(['Valency pattern id', 'Frequency all GF', 'Semantic role', 'Pattern representation', 'Corpus example'])
        for line in out_list:
            writer.writerow(line)


def main(args):
    for file in sorted(os.listdir(args.input)):
        path = os.path.join(args.input, file)
        tree = etree.parse(path)
        gf_output = []
        ssj_output = []
        head = next(tree.iter('head'))
        headword = head.find('headword').find('lemma').text
        #for div in root.iterfind('.//div'):
        for elem in tree.iter('statisticsContainer'):
        # for element in tree.iterfind('statisticsContainer'):
        # for element in tree.find('statisticsContainer'):
            semRole = elem.find('semanticRole').text
            gf_pattern = None
            gf_sentence = None
            ssj_pattern = None
            ssj_sentence = None
            measure = elem.find('measureList')
            for el in measure:
                if el.attrib['type'] == 'valency_pattern_ratio' and el.attrib['source'] == 'Gigafida 2.0':
                    gf_pattern = el.text
                if el.attrib['type'] == 'valency_sentence_ratio' and el.attrib['source'] == 'Gigafida 2.0':
                    gf_sentence = el.text
                if el.attrib['type'] == 'valency_pattern_ratio' and el.attrib['source'] == 'ssj500k 2.2':
                    ssj_pattern = el.text
                if el.attrib['type'] == 'valency_sentence_ratio' and el.attrib['source'] == 'ssj500k 2.2':
                    ssj_sentence = el.text
            if gf_pattern is not None and gf_sentence is not None:
                gf_output.append([semRole, gf_pattern, gf_sentence])
            if ssj_pattern is not None and ssj_sentence is not None:
                ssj_output.append([semRole, ssj_pattern, ssj_sentence])

        print(file)

        analyze_output = []
        for elem in tree.iter('valencyPattern'):
            valency_pattern_id = elem.attrib['id']

            # get frequency
            measure = ''
            for measure_el in elem.find('measureList').findall('measure'):
                if measure_el.attrib['source'] == 'Gigafida 2.0':
                    measure = measure_el.text

            # get semantic roles
            semantic_roles_list = []
            for semantic_rol_con in elem.find('semanticRoleContainerList').findall('semanticRoleContainer'):
                semantic_roles_list.append(semantic_rol_con.find('semanticRole').text)
            semantic_roles = '_'.join(semantic_roles_list)

            # pattern representation
            pattern_representation = elem.find('patternRepresentation').text

            # corpus example
            if elem.find('exampleContainerList') is not None and elem.find('exampleContainerList').find('exampleContainer') is not None and elem.find('exampleContainerList').find('exampleContainer').find('corpusExample') is not None:
                corpus_example_text = html.tostring(elem.find('exampleContainerList').find('exampleContainer').find('corpusExample'), encoding='unicode')

            else:
                continue

            # ugly postprocessing to remove xmlns:xsi=... duh..
            root = etree.fromstring(corpus_example_text)

            # Remove namespace prefixes
            for elem in root.getiterator():
                elem.tag = etree.QName(elem).localname
            # Remove unused namespace declarations
            etree.cleanup_namespaces(root)

            corpus_example = etree.tostring(root, encoding='unicode')

            print(f"Valency pattern {valency_pattern_id}")


            analyze_output.append([valency_pattern_id, measure, semantic_roles, pattern_representation, corpus_example])

        write_general_statistics(os.path.join(args.output, headword + '_gf_stats.tsv'), gf_output)
        write_general_statistics(os.path.join(args.output, headword + '_ssj_stats.tsv'), ssj_output)
        write_statistics(os.path.join(args.output, headword + '_patterns.tsv'), analyze_output)

if __name__ == '__main__':
    arg_parser = argparse.ArgumentParser(description='Export and validate collocation data from DDD database.')
    arg_parser.add_argument('--input', type=str, help='Input directory')
    arg_parser.add_argument('--output', type=str, help='Output directory')

    args = arg_parser.parse_args()

    main(args)